EXAMINING THE PROPOSED ABAWD RULE 

AND ITS IMPACT ON HUNGER AND HARDSHIP 

HEARING 

BEFORE THE

SUBCOMMITTEE ON NUTRITION, OVERSIGHT, AND 

DEPARTMENT OPERATIONS 

OF THE

COMMITTEE ON AGRICULTURE 

HOUSE OF REPRESENTATIVES 

ONE HUNDRED SIXTEENTH CONGRESS 

FIRST SESSION 

APRIL 3, 2019 

Serial No. 116–2 

( 

Printed for the use of the Committee on Agriculture 

agriculture.house.gov 

EXAMINING THE PROPOSED ABAWD RULE AND ITS IMPACT ON HUNGER AND HARDSHIP 

U.S. GOVERNMENT PUBLISHING OFFICE

36–188 PDF WASHINGTON : 2019

EXAMINING THE PROPOSED ABAWD RULE 

AND ITS IMPACT ON HUNGER AND HARDSHIP 

HEARING 

BEFORE THE

SUBCOMMITTEE ON NUTRITION, OVERSIGHT, AND 

DEPARTMENT OPERATIONS 

OF THE

COMMITTEE ON AGRICULTURE 

HOUSE OF REPRESENTATIVES 

ONE HUNDRED SIXTEENTH CONGRESS 

FIRST SESSION 

APRIL 3, 2019 

Serial No. 116–2 

( 

Printed for the use of the Committee on Agriculture 

agriculture.house.gov 

COMMITTEE ON AGRICULTURE 

COLLIN C. PETERSON, Minnesota, Chairman 

DAVID SCOTT, Georgia 

JIM COSTA, California 

MARCIA L. FUDGE, Ohio 

JAMES P. MCGOVERN, Massachusetts 

FILEMON VELA, Texas 

STACEY E. PLASKETT, Virgin Islands 

ALMA S. ADAMS, North Carolina 

Vice Chair 

ABIGAIL DAVIS SPANBERGER, Virginia 

JAHANA HAYES, Connecticut 

ANTONIO DELGADO, New York 

TJ COX, California 

ANGIE CRAIG, Minnesota 

ANTHONY BRINDISI, New York 

JEFFERSON VAN DREW, New Jersey 

JOSH HARDER, California 

KIM SCHRIER, Washington 

CHELLIE PINGREE, Maine 

CHERI BUSTOS, Illinois 

SEAN PATRICK MALONEY, New York 

SALUD O. CARBAJAL, California 

AL LAWSON, JR., Florida 

TOM O’HALLERAN, Arizona 

JIMMY PANETTA, California 

ANN KIRKPATRICK, Arizona 

CYNTHIA AXNE, Iowa 

K. MICHAEL CONAWAY, Texas, Ranking 

Minority Member 

GLENN THOMPSON, Pennsylvania 

AUSTIN SCOTT, Georgia 

ERIC A. ‘‘RICK’’ CRAWFORD, Arkansas 

SCOTT DESJARLAIS, Tennessee 

VICKY HARTZLER, Missouri 

DOUG LAMALFA, California 

RODNEY DAVIS, Illinois 

TED S. YOHO, Florida 

RICK W. ALLEN, Georgia 

MIKE BOST, Illinois 

DAVID ROUZER, North Carolina 

RALPH LEE ABRAHAM, Louisiana 

TRENT KELLY, Mississippi 

JAMES COMER, Kentucky 

ROGER W. MARSHALL, Kansas 

DON BACON, Nebraska 

NEAL P. DUNN, Florida 

DUSTY JOHNSON, South Dakota 

JAMES R. BAIRD, Indiana 

JIM HAGEDORN, Minnesota 

ANNE SIMMONS, Staff Director 

MATTHEW S. SCHERTZ, Minority Staff Director 

SUBCOMMITTEE ON NUTRITION, OVERSIGHT, AND DEPARTMENT OPERATIONS

MARCIA L. FUDGE, Ohio, Chair 

JAMES P. MCGOVERN, Massachusetts 

ALMA S. ADAMS, North Carolina 

JAHANA HAYES, Connecticut 

KIM SCHRIER, Washington 

JEFFERSON VAN DREW, New Jersey 

AL LAWSON, JR., Florida 

JIMMY PANETTA, California 

DUSTY JOHNSON, South Dakota, Ranking 

Minority Member 

SCOTT DESJARLAIS, Tennessee 

RODNEY DAVIS, Illinois 

TED S. YOHO, Florida 

DON BACON, Nebraska 

JIM HAGEDORN, Minnesota 

JASMINE DICKERSON, Subcommittee Staff Director 

(II) 

(III) 

C O N T E N T S 

Page 

Johnson, Hon. Dusty, a Representative in Congress from South Dakota, opening statement ........................................................................................................ 5 

Fudge, Hon. Marcia L., a Representative in Congress from Ohio, opening 

statement .............................................................................................................. 1 

Prepared statement .......................................................................................... 3 

Submitted letters .............................................................................................. 131 

Submitted proposed rule .................................................................................. 132 

Hayes, Hon. Jahana, a Representative in Congress from Connecticut: 

Submitted comment letter; authored by Marc Egan, Director of Government Relations, National Education Association ....................................... 158 

Submitted comment letter; authored by Lisa Davis, Senior Vice President, No Kid Hungry Campaign, Share Our Strength .............................. 159 

Lawson, Jr., Hon. Al, a Representative in Congress from Florida, submitted 

comment letter; authored by Center for Law and Social Policy ....................... 356 

McGovern, Hon. James P., a Representative in Congress from Massachusetts: 

Submitted letter ................................................................................................ 154 

Submitted article .............................................................................................. 154 

Panetta, Hon. Jimmy, a Representative in Congress from California: 

Submitted comment letter; authored by Abby J. Leibman, President and 

Chief Executive Officer, MAZON: A Jewish Response to Hunger ............ 379 

Submitted comment letter; authored by Keith Carson, Vice President, 

Board of Supervisors, District 5; Chair, Personnel, Administration and 

Legislation (PAL) Committee ....................................................................... 387 

Peterson, Hon. Collin C., a Representative in Congress from Minnesota, submitted comment letter; authored by Tony Lourey, Commissioner, Minnesota 

Department of Human Services .......................................................................... 151 

Schrier, Hon. Kim, a Representative in Congress from Washington: 

Submitted comment letter; authored by Hon. Jay Inslee, Governor, State 

of Washington ............................................................................................... 162 

Submitted comment letter; authored by Stacy Dean, Vice President, Food 

Assistance Policy, Center on Budget and Policy Priorities ....................... 165 

Van Drew, Hon. Jefferson, a Representative in Congress from New Jersey; 

submitted comment letter; authored by Kate Leone, Chief Government 

Relations Officer, Feeding America .................................................................... 346 

Yoho, Hon. Ted S., a Representative in Congress from Florida, submitted 

comment letter ..................................................................................................... 392 

WITNESSES

Cunnyngham, Karen, Associate Director, Mathematica Policy Research, 

Washington, D.C. ................................................................................................. 7 

Prepared statement .......................................................................................... 8 

Submitted questions ......................................................................................... 398 

Adolphsen, Sam, Vice President of Executive Affairs, Foundation for Government Accountability, Naples, FL ........................................................................ 18 

Prepared statement .......................................................................................... 19 

Submitted questions ......................................................................................... 399 

Hamler-Fugitt, Lisa, Executive Director, Ohio Association of Foodbanks, Columbus, OH ........................................................................................................... 26 

Prepared statement .......................................................................................... 28 

Submitted questions ......................................................................................... 401 

Shambaugh, Ph.D., Jay C., Director, The Hamilton Project, and Senior Fellow, Economic Studies, Brookings Institution; Professor of Economics, 

George Washington University, Washington, D.C. ........................................... 55 

Prepared statement .......................................................................................... 57 

Page

IV 

Shambaugh, Ph.D., Jay C., Director, The Hamilton Project, and Senior Fellow, Economic Studies, Brookings Institution; Professor of Economics, 

George Washington University, Washington, D.C.—Continued 

Submitted questions ......................................................................................... 405 

(1) 

EXAMINING THE PROPOSED ABAWD RULE 

AND ITS IMPACT ON HUNGER AND HARDSHIP 

WEDNESDAY, APRIL 3, 2019 

HOUSE OF REPRESENTATIVES, 

SUBCOMMITTEE ON NUTRITION, OVERSIGHT, AND DEPARTMENT

OPERATIONS, 

COMMITTEE ON AGRICULTURE, 

Washington, D.C. 

The Subcommittee met, pursuant to call, at 9:00 a.m., in Room 

1300 of the Longworth House Office Building, Hon. Marcia L. 

Fudge [Chair of the Subcommittee] presiding. 

Members present: Representatives Fudge, McGovern, Adams, 

Hayes, Schrier, Van Drew, Lawson, Panetta, Johnson, DesJarlais, 

Davis, Yoho, Bacon, Hagedorn, and Conaway (ex officio). 

Staff present: Jasmine Dickerson, Kellie Adesina, Alison Titus, 

Caleb Crosswhite, Ashton Johnston, Callie McAdams, Jennifer Tiller, Dana Sandman, and Jennifer Yezak. 

OPENING STATEMENT OF HON. MARCIA L. FUDGE, A 

REPRESENTATIVE IN CONGRESS FROM OHIO 

The CHAIR. Good morning. This hearing of the Subcommittee on 

Nutrition, Oversight, and Department Operations entitled, Examining the Proposed ABAWD Rule and its Impact on Hunger and 

Hardship, will come to order. 

The purpose of today’s hearing is to examine proposed changes 

to a long-standing USDA Able Bodied Adults Without Dependents, 

or ABAWD, policy that will impact a significant number of SNAP 

recipients. Such a change demands careful and deliberate consideration. Today, we will have this long overdue conversation. 

On February 1, I sent a letter to Secretary of Agriculture, Sonny 

Perdue, outlining my serious concerns with the Department’s proposed rule on ABAWDs. The proposed rule included a 60 day comment period, which I now understand has been extended for a few 

days. However, given the seriousness of this topic, I requested an 

extension on the comment period so that there may be more time 

to explore its potential impacts. The Department rejected the request and, instead, Secretary Perdue responded to me by saying, 

and I quote, ‘‘The proposed rule . . . would encourage broader application of the statutory ABAWD work requirement, consistent 

with the Administration’s focus on fostering self-sufficiency and 

promoting the dignity of work. I believe these proposed changes 

support our mutual goal of improving the lives of those participating in SNAP.’’ 

2 

Well, Mr. Secretary, I disagree. The goal of improving lives is 

mutual. Your methods, though, are harsh, arbitrary, and mean. 

There is no dignity in taking food from the poorest and most vulnerable of our citizens. It is dishonest and immoral for anyone to 

assume or suggest that poor people do not want to work, especially 

if that work only pays an average of $125 per month. 

And before we go any further, I want to make it very clear. People want a hand up, not a hand out, and it is insulting to suggest 

otherwise. 

The proposal before us fails to consider that unemployment is not 

the sole problem for ABAWDs. Many ABAWDs experience other 

hardships, including lack of housing, undiagnosed mental illness, 

learning disabilities, and poor health. The proposal before us 

makes clear this Administration does not understand, nor care, 

about the lack of access or barriers and hardships that keep many 

from finding and securing long-term employment. The proposal 

also tells me the Administration foolishly assumes everybody has 

the same access to resources needed to escape the cycle of poverty. 

If they just work 20 hours per week, it would solve their problems 

and move them out of poverty, magically. Lifting yourself up by 

your boot straps only works if you have boots. 

What I want to know is what USDA actually knows about those 

who will be affected by this rule? Based on the reports from our 

witnesses, Mathematica in particular, we are most likely dealing 

with the poorest of the poor. In fact, I am still waiting on my request for information during last month’s hearing with the Secretary where I asked what percentage of ABAWD populations are 

veterans, homeless, have mental or physical limitations, or lack access to public transportation? 

Were any of these factors analyzed or data collected before the 

release of the proposed rule? Does the Department even internally 

track this kind of relevant information to better inform its rulemaking and policy decisions? If they were, please present it to us. 

It is time we call this what it is: a rush to accomplish a conservative political wish-list. If this was really about the dignity of work 

and efficiency of the program, we would wait to see the final results from the 2014 Farm Bill, which provided $200 million for ten 

employment and training pilot projects. It is ill-advised to issue a 

rule without the supporting data or best practices learned from the 

pilots, to better serve the ABAWD population. 

USDA estimates that 755,000 people will lose benefits and predicts a savings in Federal spending on SNAP benefits of $7.9 billion over 5 years. What will happen to the 755,000 people? If the 

Department is so eager to get people into jobs, will the Department 

hire them? The unemployment rate in my district is 9.8 percent. 

Where are the jobs? My Republican colleagues love to talk about 

the surplus of jobs or low unemployment numbers, but we should 

remember that there is a skills gap at play within this population 

and many ABAWDs live in smaller, rural communities where jobs 

are not as readily available. Was the skills gap taken into consideration during formulation of this proposed rule? Low unemployment 

rates do little to tell us whether jobless individuals in a specific 

geographical area lack the necessary skills to obtain gainful work 

in the community. However, the Department proposes to limit exVerDate Aug 31 2005 11:16 Jun 14, 2019 Jkt 041481 PO 00000 Frm 00008 Fmt 6633 Sfmt 6633 P:\DOCS\116-02\36188.TXT BRIAN
3 

isting state flexibility, to submit a variety of credible resources, and 

support materials to help tell the story a Bureau of Labor Statistics 

unemployment rate is unable to tell. A low unemployment rate 

does not erase the existence of significant barriers to unemployment in our nation’s poorest communities. 

Without the skills necessary to obtain gainful employment and 

meet SNAP work requirements, what other options are there for 

these individuals to put food on the table? 

I am very concerned about the added burden these proposed cuts 

to SNAP place on other low-income services and charities like food 

banks. Every time Republicans trot out calls for welfare reform, 

they argue the private-sector will pick up the slack. Let me ask 

this, what does $7.9 billion in savings from SNAP mean if it increases the demand for other low-income programs or local charities that are already stretched thin? This proposed rule is nothing 

more than another attempt by the GOP and the Trump Administration to reintroduce the thoughtless House Republican SNAP provisions that were rejected in the 2018 Farm Bill. We passed a bill. 

Please follow the law. 

The House and Senate passed a farm bill conference report by a 

historic 369 votes, and the President signed it without delay. Let’s 

just follow the law. Rehashing failed policies is an affront to the 

democratic process and an utter waste of time. We have seen this 

Administration and my colleagues reciting the same negative talking points about people who are on SNAP time and again, and I 

am really very weary of it. Instead of proposing cruel and unsound 

ideas without merit, let’s figure out how to help people in need. 

Our job is to do the most for those who have the least. Let’s just 

follow the law. 

[The prepared statement of Ms. Fudge follows:] 

PREPARED STATEMENT OF HON. MARCIA L. FUDGE, A REPRESENTATIVE IN CONGRESS

FROM OHIO

The purpose of today’s hearing is to examine proposed changes to a long-standing 

USDA Able Bodied Adults Without Dependents, or ABAWD, policy that will impact 

a significant number of SNAP recipients. Such a change demands careful and deliberate consideration. Today, we will have this long overdue conversation. 

On February 1st, I sent a letter to Secretary of Agriculture Sonny Perdue outlining my serious concerns with the Department’s proposed rule on ABAWDs. The 

proposed rule included a 60 day comment period. However, given the seriousness 

of this topic, I requested an extension on the comment period so that there may be 

more time to explore its potential impacts. 

The Department rejected that request and, instead, Secretary Perdue responded 

by saying, and I quote: 

‘‘The proposed rule . . . would encourage broader application of the 

statutory ABAWD work requirement, consistent with the Administration’s focus on fostering self-sufficiency and promoting the dignity of 

work. I believe these proposed changes support our mutual goal of improving the lives of those participating in SNAP.’’ 

Well Mr. Secretary, I disagree. The goal of improving lives is mutual—his methods are harsh, arbitrary and mean. 

There is no dignity in taking food away from the poorest and most vulnerable of 

our citizens. 

It is dishonest and immoral for anyone to assume or suggest that poor people do 

not want to work, especially if that work only pays an average of $125 a month. 

And before we go any further, I want to make it very clear: people want a hand 

up, not a hand out, and it is insulting to suggest otherwise. 

4 

The proposal before us fails to consider that unemployment is not the sole problem ABAWDs face. Many ABAWDs experience other hardships, including lack of 

housing, undiagnosed mental illnesses, learning disabilities, and poor health. 

The proposal before us makes clear this Administration does not understand nor 

care about the lack of access or barriers and hardships, that keep many from finding 

and securing long-term employment. 

The proposal also tells me the Administration foolishly assumes everybody has 

the same access to the resources needed to escape the cycle of poverty. ‘‘If they just 

work 20 hours per week, it would solve their problems and move them out of poverty.’’!? 

‘‘Lifting yourself up by your boot straps’’ only works if you have boots. 

What I want to know is what USDA actually knows about those who will be affected by their rule? 

Based on the report from our witness, Mathematica, we are most likely dealing 

with the poorest of the poor. 

In fact, I’m still waiting on my request for information during last month’s hearing with Secretary Perdue, where I asked, ‘‘what percentage of the ABAWD population are veterans, homeless, have mental or physical limitations, or lack access to 

public transportation?’’ 

Were any of these factors analyzed or data collected before the release of the proposed rule? Does the Department even internally track this kind of relevant information to better inform its rulemaking and policy decisions? 

If they were, please present it to us. 

It’s time we call this what it is: a rush to accomplish a conservative political wishlist. 

If this was really about the dignity of work and efficiency of the program, we 

would wait to see the final results from the 2014 Farm Bill, which provided $200 

million for ten Employment and Training pilot projects. 

It is ill-advised to issue a rule without the supporting data or best practices 

learned from the pilots, to better serve the ABAWD population. 

USDA estimates that 755,000 people will lose benefits and predicts a savings in 

Federal spending on SNAP benefits of $7.9 billion over 5 years. 

What will happen to the 755,000 people? If the Department is so eager to get people into jobs, will they hire them? 

The unemployment rate in my district is 9.8 percent. Where are the jobs? 

My Republican colleagues love to talk about the surplus of jobs or low unemployment numbers, but we should remember that there’s a skill gap at play within this 

population and many ABAWDs live in smaller, rural communities where jobs are 

not as readily available. 

Was the skills gap taken into consideration during formulation of this proposed 

rule? Low unemployment rates do little to tell us whether jobless individuals in a 

specific geographical area lack the necessary skills to obtain gainful work in their 

communities. 

However, the Department proposes to limit existing state flexibility to submit a 

variety of credible resources and support materials to help tell the story a Bureau 

of Labor Statistics unemployment rate is unable to tell. A low unemployment rate 

does not erase the existence of significant barriers to employment in our nation’s 

poorest communities. 

Without the skills necessary to obtain gainful employment and meet SNAP work 

requirements, what other options are there for these individuals to put food on the 

table? I am very concerned about the added burden these proposed cuts to SNAP 

place on other low-income services and charities like food banks. Every time Republicans trot out calls for welfare reform, they argue the private-sector will pick up 

the slack. 

Let me ask this, what does $7.9 billion in savings from SNAP mean if it increases 

the demand for other low-income programs or local charities that are already 

stretched thin? 

This proposed rule is nothing more than another attempt by the GOP and the 

Trump Administration to reintroduce the thoughtless House Republican SNAP provisions that were rejected in the 2018 Farm Bill. We passed a bill—follow the law! 

The House and Senate passed a farm bill conference report by a historic 369 

votes, and the President signed the bill without delay. Follow the law! 

Rehashing failed policies is an affront to the democratic process and an utter 

waste of time. 

We have seen this Administration and my Republican colleagues reciting the 

same negative talking points about people who are on SNAP time and again; I am 

tired of it. 

5 

Instead of proposing cruel and unsound ideas without merit—let’s figure out how 

to help people in need. 

Our job is to do the most for those who have the least. 

The CHAIR. I would now turn to my colleague, my friend, the 

Ranking Member, Mr. Johnson. 

OPENING STATEMENT OF HON. DUSTY JOHNSON, A 

REPRESENTATIVE IN CONGRESS FROM SOUTH DAKOTA 

Mr. JOHNSON. Thank you very much, Madam Chair, and I do appreciate Ms. Fudge convening this hearing, and I want to thank 

our witnesses for their participation. 

For me, an important foundation of all of this Subcommittee’s 

work on nutrition is, first, that we all want to improve the lives 

of Americans who are facing hard times. I think that is obvious. 

Second, that SNAP is an important poverty program. That is something worth maintaining, something worth holding up. Third, that 

work and education are a critically important, a necessary part of 

helping people realize opportunities to move out of poverty. 

And so, each of us today on this dais is fighting for the same 

goal. Madam Chair mentioned that. We all want to see the lives 

of Americans improve. And a number of us on the broader Agriculture Committee on both sides of the aisle have experienced welfare programs, poverty programs, on a personal basis. But whether 

we have or we haven’t, we all want to make sure that we maintain 

an effective and efficient social safety net. 

And so, we are going to disagree about the best way to do that, 

but the basic heart of the matter is intact. As a country, we spend 

$1 trillion a year on 80 social safety net programs, and we want 

to make sure they work. We are a nation of giving. We want to be 

a nation of opportunity. 

And so, able-bodied adults, the ABAWD population, we have 

been talking about this population for a long time. I know there 

have been a lot of hearings that have addressed this issue. I am 

excited to have our witnesses today hit on them even more. But 

from the welfare reform efforts of 1996, out of the farm bill discussions of 2018, for decades, this group and the broader Congress has 

been talking about ABAWDs, and we have made some progress. 

But nobody here would say that our work is done, and so, I am excited to work together to try to find a way to do even better, to find 

data-driven solutions for how we can improve the lives of these 

ABAWDs. 

You may have heard me say—because I say it a lot—that work 

has dignity. Work is opportunity. Work is an American value that 

we all need help to achieve. And I am excited to discuss today and 

in the future how we really can work with the Administration, 

work throughout Congress to try to make sure that able-bodied 

adults really do have a good pathway from welfare to work, and 

that is going to help us preserve these programs, this critically important SNAP Program, for our most in need friends and our most 

in need neighbors. 

As the Chair alluded to, my side of the aisle has talked a lot 

about a record economy, record job openings, and I do think that 

gives us a special opportunity to help people move out of poverty 

and into work. For that reason, I want to applaud Secretary 

6 

Perdue and USDA in taking this regulatory action to make work 

an even more central component of this important program. 

These proposed rules, they really are intended, honestly intended 

to help work capable individuals seek new employment opportunities and be in a better position to realize their dreams. Now, some 

states have taken too much flexibility. They have taken too much 

liberty with the flexibility that Congress has given them, and I 

know that has been a bipartisan sentiment in the past, that both 

Democratic and Republican Members of the Agriculture Committee 

have said that, and so, I am looking forward to working with my 

colleagues to right size the amount of flexibility, to hold states accountable, and move more people off poverty. 

The term able-bodied, as we have talked about, is so key to this 

discussion, and I want to make sure that we are working to empower and not stigmatize the ABAWD population. Of course, 

Madam Chair is exactly right, that these folks have a certain number of challenges. There are barriers to unemployment. That isn’t 

arguable. But despite those barriers, with help, they can still seek 

employment. They can stabilize their income. They can move to a 

place of even greater personal autonomy. That is the American 

dream. 

I think about during the farm bill discussions, there was a video 

that came out—and I was a private citizen at the time, but I was 

captivated by the video. It was about Latasha, and she was a 

former E&T participant here in Washington. She completed a certification program back in 2012, has been working successfully 

since. Her story is a story that should make us all proud. And with 

help, with additional accountability, with states doing a better job 

of managing their programs, there can be thousands more 

Latashas out there realizing a better life. And we all know that 

just ignoring the need for improvement, ignoring the need for a 

forum doesn’t really improve anybody’s life. That is not leadership. 

And so, let’s work with SNAP recipients. Let’s work with this Subcommittee. Let’s work with the Administration to move even more 

people from welfare to work. 

And with that, Madam Chair, I yield and I welcome our witnesses. 

The CHAIR. Thank you very much, Mr. Johnson. I would ask that 

all Members submit their opening statements for the record so that 

we can begin with our witnesses as quickly as possible. 

I would like to introduce and welcome our witnesses. We would 

begin today with Ms. Karen Cunnyngham, Associate Director, 

Mathematica Policy Research, Washington, D.C. Mr. Sam 

Adolphsen, Vice President of Executive Affairs, Foundation for 

Government Accountability, Naples, Florida. Ms. Lisa HamlerFugitt, Executive Director, Ohio Association of Food Banks, Columbus, Ohio; and Dr. Jay Shambaugh, Director of The Hamilton 

Project, Brookings Institution, Washington, D.C. 

Ms. Cunnyngham, you may begin. I would just bring your attention to the lighting system. The light will turn green when you 

begin. You will have 5 minutes to give your testimony. When you 

see the yellow light, it means you have 1 minute. When you see 

the red light, we would like you to conclude as quickly as possible. 

Thank you very much, and welcome. 

7 

STATEMENT OF KAREN CUNNYNGHAM, ASSOCIATE DIRECTOR, 

MATHEMATICA POLICY RESEARCH, WASHINGTON, D.C. 

Ms. CUNNYNGHAM. Chair Fudge, Ranking Member Johnson, and 

distinguished Members of the Subcommittee, thank you for inviting 

me to testify today. I am an associate director at Mathematica, and 

have been conducting research on SNAP for government agencies 

for 18 years. 

I currently direct a project commissioned by the Robert Wood 

Johnson Foundation to develop rigorous and objective estimates of 

the effects of proposed changes to SNAP. Much of what I will 

present today is based on findings from that project. 

SNAP participants who are ages 16 to 59 that do not have a disability, and are not working at least 30 hours per week must register for work unless they meet certain criteria, such as caring for 

an incapacitated person. Work registrants who are ages 18 to 49 

and don’t live with a child must work an average of at least 20 

hours per week, or face a time limit of 3 months of benefits in a 

3 year period. They are exempt from the time limit, however, if 

they participate in a qualifying employment and training program, 

or other meaningful work activity, have a percentage exemption 

from the state agency, or live in a waiver area, an area for which 

the state agency requested and received a Federal waiver from 

time limits because of high unemployment. 

USDA’s proposed regulatory change would eliminate or modify 

some current waiver area criteria. For example, states would no 

longer be able to request a waiver for counties with overall unemployment rates less than seven percent. Table 1 in my written testimony summarizes the proposed changes. 

According to USDA’s Regulatory Impact Analysis, among the 

SNAP participants who are ages 18 to 49 without a disability and 

childless SNAP households and in a waiver area in Fiscal Year 

2016, about 3⁄4 would be newly subject to the additional work requirement and time limit. USDA further estimates that under the 

proposed changes, between 755,000 and 851,000 of these people 

would not meet the work requirements in 2020, and would therefore lose eligibility after 3 months. 

Mathematica used Fiscal Year 2017 SNAP quality control data 

to examine the characteristics of SNAP participants who would be 

affected by the proposed changes. Specifically, we focused on the 

estimated 1.2 million SNAP participants who lived in a waiver 

area, could be newly subject to time limits, and were not working 

at least 20 hours per week. Among these SNAP participants, 97 

percent lived in poverty, and 88 percent lived in deep poverty, compared with 39 percent of other SNAP participants living in deep 

poverty. Eleven percent were working, although less than 20 hours 

per week, and another six percent lived with someone else who was 

working. However, only 1⁄3 were living in SNAP households with 

any reported income. Among those, the average household income 

was $557 a month, 43 percent of the poverty level. The average 

monthly SNAP benefit was $181 per person. Finally, these SNAP 

participants were much more likely to live alone than other SNAP 

participants, 78 percent compared with 23 percent. 

The potential impact on these individuals would vary by their 

circumstances and state. SNAP participants in the 17 states withVerDate Aug 31 2005 11:16 Jun 14, 2019 Jkt 041481 PO 00000 Frm 00013 Fmt 6633 Sfmt 6601 P:\DOCS\116-02\36188.TXT BRIAN
8 

out waiver areas would not be affected by the proposed changes. In 

other states, the state agency may offer slots in qualifying employment and training programs, or percentage exemptions to participants who would otherwise face a time limit. 

In many states, however, some SNAP participants would be 

newly required to work an average of at least 20 hours per week, 

or be subject to the time limit. Both SNAP participants’ job readiness and the local labor market will affect SNAP participants’ ability to find work. 

Although the Bureau of Labor Statistics estimates the national 

overall unemployment rate was 3.9 percent in 2018, some groups 

were less likely to find work. For example, the unemployment rate 

for young adults ages 20 to 24 was 6.9 percent, and the rate for 

African American men was seven percent. 

Policy decisions should be informed by the best data available, 

and this proposed rule is no exception. Policymakers could gain a 

more complete picture of the likely effects of the proposed regulatory change if detailed information on the areas that would no 

longer qualify for a waiver were incorporated into state estimates 

of the people potentially affected. In addition, examining unemployment rates for subgroups of a state population would provide valuable insights to the availability of jobs for SNAP participants, and 

the potential for some groups to experience a disproportionate impact from proposed changes. New data collection on the circumstances of people who lose eligibility for SNAP because of time 

limits also could help policymakers understand whether and how 

well policy objectives are being achieved. 

Thank you. I look forward to your questions. 

[The prepared statement of Ms. Cunnyngham follows:] 

PREPARED STATEMENT OF KAREN CUNNYNGHAM, ASSOCIATE DIRECTOR, 

MATHEMATICA POLICY RESEARCH, WASHINGTON, D.C. 

Addressing Proposed Changes to SNAP Waiver Area Criteria 

Good morning, Chairwoman Fudge, Ranking Member Johnson, and distinguished 

Members of the Subcommittee. Thank you for inviting me to testify at today’s hearing, ‘‘Examining the Proposed ABAWD Rule and its Impact on Hunger and Hardship.’’ I am an associate director in Mathematica’s Human Services Division and the 

director of a project, commissioned by the Robert Wood Johnson Foundation, to develop credible and objective estimates of the effect of proposed legislative and regulatory changes to the Supplemental Nutrition Assistance Program—or SNAP. My 

Mathematica colleagues and I are proud of this work, and appreciate the opportunity to apply our combined expertise in data, methods, policy, and practice to help 

enhance understanding of SNAP, refine strategies for its implementation, and ultimately improve the effectiveness of the program. 

SNAP, the largest of the domestic nutrition assistance programs administered by 

the Food and Nutrition Service of the U.S. Department of Agriculture (USDA), provides nutrition assistance to eligible, low-income people in need. The proposed regulatory change we are here to discuss today would affect a subset of the overall 

SNAP population—about three percent of the 41.5 million who participated in the 

program in Fiscal Year 2017. According to our analysis of Fiscal Year 2017 SNAP 

Quality Control (QC) data, the vast majority of SNAP participants who could be affected by the proposed rule are in deep poverty, and many live alone. 

In my testimony today, drawn from a research brief produced for the Robert Wood 

Johnson Foundation project, I will (1) outline the proposed regulatory changes, (2) 

discuss the estimated impacts, (3) summarize the characteristics of SNAP particiVerDate Aug 31 2005 11:16 Jun 14, 2019 Jkt 041481 PO 00000 Frm 00014 Fmt 6633 Sfmt 6621 P:\DOCS\116-02\36188.TXT BRIAN
9 

1 Cunnyngham, Karen. ‘‘Proposed Changes to the Supplemental Nutrition Assistance Program: 

Waivers to Work-Related Time Limits.’’ Issue brief submitted to the Robert Wood Johnson Foundation. Washington, D.C.: Mathematica Policy Research, March 2019. 

pants potentially impacted, and (4) suggest additional data collection and research 

to help inform this discussion.1

Understanding the Proposed Regulatory Changes 

Currently, SNAP participants ages 16 to 59 must register for work unless they 

are already working at least 30 hours per week; have a disability; or meet other 

criteria, such as caring for a young child or an incapacitated person. Work registrants who are ages 18 to 49 in childless SNAP households are subject to additional work requirements and a time limit: they must work an average of at least 

20 hours per week to continue receiving SNAP benefits for more than 3 months in 

a 3 year period. They are exempt from the time limits, however, if they (1) participate in a qualifying employment and training program or other meaningful work 

activity; (2) have a discretionary exemption from the state agency; or (3) live in a 

waiver area, an area for which the state agency requested and received a Federal 

waiver from time limits because of high unemployment. 

Table 1 shows how USDA’s proposed regulatory change would eliminate or modify 

some current waiver area policies and leave others unchanged. In recent years, 

states based most of their requests for geographic waivers on an area qualifying for 

the extended unemployment benefits authorized during the Great Recession or experiencing an unemployment rate at least 20 percent above the national average. After 

SNAP time limits were reinstated following the Great Recession, some states have 

requested and received waivers for all or parts of the state, while others have not 

requested any time limit waivers at all. Table 2 illustrates how the prevalence of 

state time limit waivers changed from 2009 through 2018. Currently, 17 states have 

no waiver areas, either because no area in the state qualified or the state agency 

chose not to request a waiver (Table 3). Although states with the highest unemployment rates in 2018—Alaska and New Mexico—had statewide waivers, others with 

overall unemployment rates above the national average of 3.9 percent chose not to 

apply for a waiver for any areas of the state. 

Table 1. Waiver Area Policies 

Current policy Proposed regulatory change 

Criteria to establish waiver area 

The U.S. Department of Labor designated the area as a Labor Surplus 

Area based on a recent 24 month average unemployment rate that is 

either (1) at least ten percent or (2) at least six percent and at least 20 

percent above the national average 

Eliminated 

The Department of Labor determined that the area meets the criteria 

for extended unemployment benefits, available to workers who 

have exhausted regular unemployment insurance benefits during periods of high unemployment 

No change 

Data from the U.S. Bureau of Labor Statistics (BLS) show the area had 

a recent 12 month average unemployment rate greater than ten 

percent 

No change 

Data from BLS show the area had a recent 24 month average unemployment rate at least 20 percent above the national average The unemployment rate also must be 

at least seven percent 

Alternate sources indicate a lack of sufficient jobs in an area, including 

an unemployment rate estimated with data from BLS and the Census 

Bureau’s American Community Survey; a low and declining employment-to-population ratio; a lack of jobs as a consequence of declining occupations or industries; or an academic study or other publication describing the area’s lack of a sufficient number of jobs 

The alternate criteria will be applicable only to areas for which data 

from BLS or a BLS-cooperating 

agency are limited or unavailable, 

such as a reservation area or U.S. 

territory 

Other waiver area policies 

Waivers may be statewide Only waivers based on extended unemployment benefits may be statewide 

State agencies may combine data from sub-state areas, such as counties, 

that are contiguous, share an economic region, or both 

State agencies may combine data 

only for areas collectively designated as Labor Market Areas by 

BLS 

Waivers may extend beyond the fiscal year Waivers based on a 24 month average unemployment rate may not 

extend beyond the fiscal year 

10 

2 ABAWDs, or ‘‘able-bodied adults without dependents’’ are SNAP participants who are subject 

to work registration, ages 18 to 49, without a disability, and living in childless SNAP households. 

Table 1. Waiver Area Policies—Continued 

Current policy Proposed regulatory change 

Approval by governor not explicitly required Governor must approve waiver request 

Table 2. Waiver Area Timeline 

April 2009 to September 2010 Congress temporarily suspended the time limits through the American 

Recovery and Reinvestment Act. 

October 2010 to December 2015 In Fiscal Year 2011, time limits continued to be waived based on extended unemployment benefits for 45 states, the District of Columbia, 

Guam, the Virgin Islands, and some areas of five additional states. 

By the end of Fiscal Year 2015, time limits were re-implemented in nine 

states and in some areas of 13 other states. 

January 2016 to Fiscal Year 2017 Few areas still qualified for extended unemployment benefits, but many 

areas received time limit waivers based on other indicators of high unemployment, such as an unemployment rate at least 20 percent above 

the national average. Seventeen states had no waiver areas for most of 

this time. 

December 2018 Seventeen states have no waiver areas; seven states, the District of Columbia, Guam, and the Virgin Islands have time limit waivers for 

their entire area; and the remaining states have waivers for some but 

not all areas of the state. 

Table 3. Current State Waiver Areas 

No waiver areas Some waiver areas Statewide waiver 

Alabama Missouri Arizona Massachusetts Pennsylvania Alaska 

Arkansas Nebraska California Michigan Rhode Island District of Columbia 

Delaware North Carolina Colorado Montana South Dakota Guam 

Florida Oklahoma Connecticut Nevada Tennessee Louisiana 

Indiana South Carolina Georgia New Hampshire Utah New Mexico 

Iowa Texas Hawaii New Jersey Vermont Virgin Islands 

Kansas Wisconsin Idaho New York Virginia 

Maine Wyoming Illinois North Dakota Washington 

Mississippi Kentucky Ohio West Virginia 

Maryland Oregon 

Source: The Food and Nutrition Service’s ‘‘ABAWD Waiver Status’’ reports available at https:// 

www.fns.usda.gov/snap/abawd-waivers. 

Discussion of Estimated Impacts 

According to USDA’s Regulatory Impact Analysis of the proposed rule, an estimated 3⁄4 of ABAWDs currently living in a waiver area would be newly subject to 

a 3 month limit on their benefits.2 Some of them would increase their existing work 

to an average of 20 hours per week, find work, or meet the work requirements by 

participating in an employment and training program or workfare (that is, unpaid 

work through a state-approved program). But USDA estimates that between 

755,000 and 851,000 people in 2020, depending on future unemployment rates, 

would not meet the additional work requirements and would therefore lose eligibility after 3 months. For those living with others unaffected by the policy change, 

the SNAP household could continue to receive benefits, but the amount would be 

reduced; those living alone would lose all SNAP benefits. Nationally, the proposed 

regulatory changes would result in a 2.5 percent reduction in spending on SNAP 

benefits, according to USDA estimates. 

The potential impact would vary by state and depends on a variety of factors, including state agency policies, the local labor market, and the characteristics and circumstances of the participants. We used Fiscal Year 2017 SNAP QC data to estimate state percentages of SNAP participants ages 18 to 49, without a disability, and 

living in childless SNAP households who could be newly subject to a time limit (Figure 1). SNAP participants in the 17 states without waiver areas would not be affected by the proposed changes because they already face time limits unless they 

are engaged in meaningful work activities or are exempt for other reasons. In other 

states, the state agency may offer a slot in a qualifying employment and training 

program to participants who would otherwise face a time limit or use Federal ‘‘percentage exemptions’’ to exempt some SNAP participants from the time limit. 

11 

Figure 1. Estimated impact by state 

Percentage of SNAP participants ages 18 to 49, without a disability, and 

living in childless SNAP households who were potentially subject to a time 

limit, lived in a waiver area, and did not work 20 hours per week. 

Source: Fiscal year 2017 SNAP QC data. 

Notes: States with a white background did not have waiver areas in Fiscal Year 2017. See appendix table for state percentages. 

In many states with waiver areas, at least some SNAP participants living in those 

areas would be newly required to work an average of at least 20 hours per week 

to continue receiving benefits for more than 3 months. Both the local labor market 

and SNAP participants’ job readiness will affect their ability to find work. Although 

the national overall unemployment rate was 3.9 percent in 2018, according to BLS 

estimates, that rate represents an average, and some groups are much less likely 

to find steady work. For example, the unemployment rate for young adults ages 20 

to 24 was 6.9 percent, and the rate for African American men was 7.0 percent. Access to a well-funded and robust SNAP employment and training program—which 

is not currently available in many areas—could help participants meet the work requirements. 

In addition, the characteristics and circumstances of SNAP participants will influence whether they lose eligibility for SNAP under the proposed change. For example, certain SNAP participants are not required to register for work because they 

care for an incapacitated person or meet other criteria; work requirements will not 

change for these participants. On the other hand, some participants who newly face 

a time limit might choose to forgo SNAP benefits and rely on other available resources, such as food banks or family members, rather than comply with work requirements. 

Characteristics of SNAP Participants Potentially Impacted 

Mathematica used Fiscal Year 2017 SNAP QC data to examine the characteristics 

of SNAP participants who could face time limits on receiving SNAP benefits under 

the proposed regulatory change. In Fiscal Year 2017, eight percent of all SNAP participants (3.2 million people) were ages 18 to 49, did not have a disability, and did 

not live with a child. Twenty-one percent of this group were working an average of 

at least 20 hours per week, with the percentage ranging from nine percent to 36 

percent across states. An estimated 1.2 million SNAP participants were not working 

an average of at least 20 hours per week and would have faced time limits but 

didn’t because they lived in a waiver area. Among these SNAP participants who 

could be affected by the proposed regulatory changes: 

• 97 percent lived in poverty, compared with 80 percent of other SNAP participants. 

• 88 percent had household income at or below 50 percent of the poverty level, 

compared with 39 percent of other SNAP participants. 

• Among the 1⁄3 living in SNAP households with reported income, the average 

monthly household income was $557, or 43 percent of the poverty level. 


11602001.eps
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• 11 percent were working, although less than an average of 20 hours per week, 

and another six percent lived with someone else who was working. 

• 5 percent lived with a person with a disability. 

• The average monthly SNAP benefit was $181 per person, compared with $120 

for other SNAP participants. 

• 78 percent lived alone (Figure 2), compared with 23 percent of other SNAP participants. 

Figure 2. Living situation of those potentially affected 

Source: Fiscal year 2017 SNAP QC data. 

Data-Driven Decision Making 

Objective, rigorously derived estimates of the potential impacts of proposed policy 

changes can provide additional insight for policymakers like you, who are faced with 

difficult decisions about how to allocate scarce resources in a way that helps the 

people who are most in need. To conduct the analysis I just described, we used the 

Fiscal Year 2017 SNAP QC data available at https://host76.mathematica-mpr.com/ 

fns/. Details about the small amount of data cleaning we did to ensure that state 

estimates aligned with state policy, and how we tabulated the data, are available 

upon request. 

Further analysis of existing data could provide additional insights into the likely 

effects of the proposed regulatory change. For example, state estimates of the number of people potentially affected could be refined using county-level data from state 

and Federal sources, incorporating more detailed information on which current 

waiver areas would not qualify under the proposed criteria. Examining unemployment rates for subgroups of a state population would also provide valuable insights 

into the availability of jobs for SNAP participants and the potential for some groups 

to experience a disproportionate impact from proposed changes. In addition, new 

data collection on the circumstances of people who lose eligibility for SNAP because 

of time limits could help policymakers understand whether and how well policy objectives are being achieved. Finally, Mathematica’s evaluation of SNAP employment 

and training pilots for USDA will provide important information on innovative 

strategies for increasing employment and earnings among SNAP participants. 

I’m grateful for the opportunity to share this evidence, as well as the companion 

issue brief attached to my written statement, with you today. Thank you. 

Table A.1. Estimated state percentage of SNAP participants that could 

potentially be affected by proposed changes to waiver area criteria 

Waiver areas 

SNAP participants † 

Number (in 

thousands) 

Number (in 

thousands) 

Alabama None 0 0 

Alaska Statewide Statewide 7 72

Arizona Arizona Some 15 20 

Arkansas None 0 0 

California Statewide Statewide 300 65

Colorado Colorado Some 3 12 

Connecticut Some 26 62

Delaware None 0 0 

District of Columbia Statewide Statewide 8 53

Florida None 0 0

Georgia Some 81 66

Guam Statewide Statewide 1 37 

Hawaii Some * 1 

Idaho Some * 1 

Illinois Statewide Statewide 178 77


11602002.eps
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Table A.1. Estimated state percentage of SNAP participants that could potentially be affected by proposed changes to waiver area criteria—Continued 

Waiver areas 

SNAP participants † 

Number (in 

thousands) 

Number (in 

thousands) 

Indiana None 0 0 

Iowa None 0 0 

Kansas None 0 0 

Kentucky Some 32 54

Louisiana Statewide Statewide 56 73

Maine None 0 0 

Maryland Maryland Some 18 31 

Massachusetts Massachusetts Some 18 28 

Michigan Michigan Some 78 51 

Minnesota Minnesota Some 2 6 

Mississippi None 0 0 

Missouri None 0 0 

Montana Montana Some 3 28 

Nebraska None 0 0 

Nevada Statewide Statewide 25 41 

New Hampshire New Hampshire Some * 2 

New Jersey New Jersey Some 1 2 

New Mexico Statewide Statewide 27 53

New York New York Some 84 39 

North Carolina None 0 0 

North Dakota North Dakota Some * 4 

Ohio Some 4 4 

Oklahoma None 0 0 

Oregon Some 46 50 

Pennsylvania Pennsylvania Some 51 43 

Rhode Island Statewide Statewide 14 75

South Carolina None 0 0 

South Dakota South Dakota Some 3 44 

Tennessee Some 69 67

Texas None 0 0 

Utah Some * 1 

Vermont Vermont Some * 5 

Virgin Islands Virgin Islands Statewide 1 Statewide 1 39 

Virginia Virginia Some 20 46 

Washington Some 60 53

West Virginia West Virginia Some 15 Some 15 47 

Wisconsin None 0 0 

Wyoming None 0 0 

† SNAP participants ages 18 to 49, without a disability, and living in childless SNAP households who were potentially subject to a time limit, lived in a waiver area, and did not work 20 hours per week. 

1–27 percent 1–27 percent

28–52 percent 28–52 percent 

53–77 percent

* Less than 500. 

Source: Fiscal year SNAP Quality Control data. 

ATTACHMENT

March 2019 

Nutrition 

Issue Brief 

KAREN CUNNYNGHAM


11602004.eps
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Proposed Changes to the Supplemental Nutrition Assistance Program: 

Waivers to Work-Related Time Limits 

A rule proposed (https://www.federalregister.gov/documents/2019/02/01/2018- 

28059/supplemental-nutrition-assistance-program-requirements-for-able-bodiedadults-without-dependents) by the U.S. Department of Agriculture (USDA) on February 2, 2019, would reduce the number of non-disabled childless people age 18 to 

49 who are receiving Supplemental Nutrition Assistance Program (SNAP) benefits. 

Currently, SNAP participants in this group must engage in meaningful work activity or face time limits on their benefits. However, if a geographic area has an unemployment rate that is at least 20 percent above the national rate or has other indicators of insufficient jobs, states can request that USDA waive the time limit for 

SNAP participants living in the area. The proposed rule would reduce the number 

of areas qualifying for a waiver by imposing stricter standards—for example, states 

would not be able to request a waiver for counties with unemployment rates less 

than seven percent. 

This issue brief, the third in a series of briefs analyzing the impact of proposed 

changes to SNAP, provides background on SNAP work requirements, time limits, 

and the proposed regulatory changes. The brief also sheds light on the characteristics of SNAP participants who could face time limits on receiving SNAP benefits 

under the proposed regulatory change. With support from the Robert Wood Johnson 

Foundation, Mathematica conducted this analysis using SNAP Quality Control (QC) 

data from Fiscal Year 2017, the most recent year for which data are available. 

SNAP Participants Potentially Affected By Proposed Changes 

In Fiscal Year 2017, an estimated 1.2 million SNAP participants were not working an average of at least 20 hours per week and would have faced time limits but 

did not because they lived in a waiver area. Among these SNAP participants who 

could be affected by the proposed regulatory changes: 

• 88 percent had household income at or below 50 percent of the poverty level. 

• About 1⁄3 lived in SNAP households with reported income; the average monthly 

household income of this group was $557, or 43 percent of the poverty level. 

• 11 percent were working, although less than an average of 20 hours per week, 

and another six percent lived with someone else who was working. 

A greater share of these SNAP participants lived in poverty (97 percent) compared to other SNAP participants (80 percent). 

• 5 percent lived with a person with a disability. 

• The average monthly SNAP benefit was $181 per person. 

Source: Fiscal year 2017 SNAP QC data. 

Under the proposed rule, an estimated 3⁄4 of these SNAP participants would be 

newly subject to a 3 month limit on their benefits, according to USDA. Some of 

them would increase existing work to an average of 20 hours per week, find work, 

or meet the work requirements by participating in an employment and training program or workfare (unpaid work through a state-approved program). However, USDA 

estimates that 2⁄3 (755,000 people in 2020) would not meet the additional work requirements and would therefore lose eligibility after 3 months. For those living with 

others unaffected by the policy change, the SNAP household could continue to receive benefits, but the amount would be reduced; those living alone would lose all 

SNAP benefits. 

SNAP Work Requirements and Current Waiver Policy 

Currently, SNAP participants age 16 to 59 must register for work unless they are 

already working at least 30 hours per week, have a disability, or meet other criteria, 

such as caring for a young child or an incapacitated person. Work registrants who 

are age 18 to 49 in childless SNAP households are subject to additional work reVerDate Aug 31 2005 11:16 Jun 14, 2019 Jkt 041481 PO 00000 Frm 00020 Fmt 6633 Sfmt 6621 P:\DOCS\116-02\36188.TXT BRIAN

11602003.eps
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quirements and a time limit: they must work an average of at least 20 hours per 

week to continue receiving SNAP benefits for more than 3 months in a 3 year period. However, they are exempt from the time limits if they (1) participate in a 

qualifying employment and training program or other meaningful work activity, (2) 

have a discretionary exemption from the state agency, or (3) live in a waiver area, 

an area for which the state agency requested and received a Federal waiver from 

the time limits due to high unemployment (see waiver area timeline). In recent 

years, states based most requests for geographic waivers on the area qualifying for 

the extended unemployment benefits authorized during the Great Recession or experiencing a high unemployment rate. Currently, 17 states have no waiver areas, either because no area in the state qualified or the state agency chose not to request 

a waiver (see map). 

Snapshot: Some SNAP Participants Age 18 To 21 Could Be Affected By the 

Proposed Changes 

In 2017, about 498,000 SNAP participants were age 18 to 21, did not 

have a disability, and were in a childless SNAP household. Some of 

these young adults would newly face time limits under the proposed 

rule changes. 

• One-third lived in a waiver area and did not work an average of at least 20 

hours per week; these are the young adults who might lose their SNAP 

benefit because of the proposed changes. 

• Slightly less than 1⁄2 lived with a parent and ten percent lived with another 

relative, a spouse, or a peer; the remainder—about 40 percent—did not 

share food resources with another person. 

• 23 percent worked an average of 20 hours per week or more (enough to 

avoid time limits on their benefits), six percent were working fewer hours, 

and 17 percent were not working but lived with someone who was. 

• The average monthly benefit was $142 per person. 

Source: Fiscal year 2017 SNAP QC data. 

USDA’s proposed regulatory change would eliminate or modify some current waiver area policies and leave others unchanged, as shown in the table below. 

Waiver area policies 

Current policy Proposed regulatory 

change 

Criteria to establish waiver area 

The Department of Labor (DOL) designated the area as a Labor Surplus Area based 

on a recent 24 month average unemployment rate that is either at least ten percent or at least six percent and at least 20 percent above the national average 

Eliminated 

DOL determined that the area meets the criteria for extended unemployment benefits, available to workers who have exhausted regular unemployment insurance 

benefits during periods of high unemployment 

No change 

Data from the Bureau of Labor Statistics (BLS) show the area had a recent 12 month 

average unemployment rate greater than ten percent 

No change 

Data from BLS show the area had a recent 24 month average unemployment rate at 

least 20 percent above the national average 

The unemployment rate 

also must be at least 

seven percent 

Other waiver area policies 

Waivers may be statewide Only waivers based on 

extended unemployment benefits may be 

statewide 

State agencies may combine data from sub-state areas, such as counties, that are 

contiguous, share an economic region, or both 

State agencies may combine data only for 

areas collectively designated as Labor Market Areas by BLS 

16 

Waiver area policies—Continued 

Current policy Proposed regulatory 

change 

Waivers may extend beyond the fiscal year Waivers based on a 24 

month average unemployment rate may 

not extend beyond the 

fiscal year 

Estimated Impact 

The proposed regulatory changes would result in a 2.5 percent reduction in spending on SNAP benefits nationally, according to USDA estimates. The potential impact varies by state and depends on a variety of factors, including state agency policies, the local labor market, and the characteristics and circumstances of the participants. For example, SNAP participants in the 17 states without waiver areas would 

not be affected by the proposed changes because they already face time limits unless 

they are engaged in meaningful work activities or are exempt for other reasons. In 

other states, the state agency may offer a slot in a qualifying employment and training program to participants who would otherwise face a time limit or use Federal 

‘‘percentage exemptions’’ to exempt some SNAP participants from the time limit. 

In many states with current waiver areas, at least some SNAP participants living 

in those areas will be newly required to work an average of at least 20 hours per 

week to continue receiving benefits for more than 3 months. Both the local labor 

market and SNAP participants’ job readiness will affect their ability to find work. 

To provide some perspective, 21 percent of non-disabled childless SNAP participants 

age 18 to 49 worked an average of at least 20 hours per week, according to the Fiscal Year 2017 SNAP QC data. The percentage ranged from nine percent to 36 percent across states. 

In addition to job readiness, other characteristics and circumstances of SNAP participants will influence whether they lose eligibility for SNAP under the proposed 

change. For example, certain SNAP participants are not required to register for 

work because they are caring for an incapacitated person or meet other criteria; 

work requirements will not change for these participants. On the other hand, some 

participants who newly face a time limit may choose to forgo SNAP benefits and 

rely on other available resources, such as food banks or family members, rather 

than comply with work requirements. 

Which states are more likely to be affected by the proposed changes? 

Percentage of non-disabled childless SNAP participants age 18 to 49 who 

were potentially subject to a time limit, lived in a waiver area, and did not 

work 20 hours per week. 

Source: Fiscal year 2017 SNAP QC data. 

Note: States with a white background did not have waiver areas in Fiscal 

Year 2017. 

Differences in State Use of Waiver Areas 

Since SNAP time limits were reinstated after the Great Recession, some states 

have requested and received waivers for all or parts of the state while others have 


11602005.eps
17 

not requested any time limit waivers. The waiver area timeline illustrates how the 

prevalence of state time limit waivers changed from 2009 through 2018; the callout box on the left shows state use of waiver areas in Fiscal Year 2017. While states 

with the highest unemployment rates in 2017—Alaska and New Mexico—had statewide waivers, others with overall unemployment rates above the national average 

of 4.4 percent chose not to apply for a waiver for any areas of the state. 

State Waiver Areas in Fiscal Year 2017 

No waiver areas 

Alabama Missouri 

Arkansas Nebraska 

Delaware North Carolina 

Florida Oklahoma 

Indiana South Carolina 

Iowa Texas 

Kansas Wisconsin 

Maine Wyoming 

Mississippi 

Some waiver areas 

Arizona New Jersey 

Colorado New York 

Connecticut North Dakota 

Georgia Ohio 

Hawaii Oregon 

Idaho Pennsylvania 

Kentucky South Dakota 

Maryland Tennessee 

Massachusetts Utah 

Michigan Vermont 

Minnesota Virginia 

Montana Washington 

New Hampshire West Virginia 

Statewide waiver 

Alaska Louisiana 

California Nevada 

District of Columbia New Mexico 

Guam Rhode Island 

Illinois Virgin Islands 

Waiver area timeline 

April 2009–September 2010 Congress temporarily suspended the time limits through the American 

Recovery and Reinvestment Act. 

October 2010–December 2015 In Fiscal Year 2011, time limits continued to be waived based on extended unemployment benefits for 45 states, the District of Columbia, 

Guam, and the Virgin Islands and in some areas of five additional 

states. By the end of Fiscal Year 2015, time limits were re-implemented in nine states and in some areas of 13 more states. 

January 2016–Fiscal Year 2017 Few areas still qualified for extended unemployment benefits, but many 

areas received time limit waivers based on other indicators of high unemployment, such as an unemployment rate at least 20 percent above 

the national average. Seventeen states had no waiver areas for most of 

this time. 

December 2018 Seventeen states have no waiver areas; seven states, the District of Columbia, Guam, and the Virgin Islands have time limit waivers for 

their entire area; and the remaining states have waivers for some but 

not all areas of the state. 

Sources 

Mathematica used Fiscal Year 2017 SNAP QC data to produce the estimates 

shown in the second half of page 1, the Snapshot on page 2, and the second paragraph and map on page 3. The underlying assumptions and key variables used are 

available upon request. USDA’s estimated impact of the proposed regulatory 

changes, mentioned at the top of page 2 and the first sentence of page 3, are drawn 

from the Regulatory Impact Analysis of the proposed rule. Finally, information on 

state waiver areas was compiled from FNS’s ‘‘ABAWD Waiver Status’’ reports. 

This brief series was created by Mathematica in collaboration with the Robert 

Wood Johnson Foundation to analyze the impact of proposed changes to SNAP. 

18 

Many individuals made important contributions, including Carmen Ferro, Sarah 

Lauffer, Joshua Leftin, Gwyneth Olson, and J.B. Wogan from Mathematica; Gina 

Hijjawi from RWJF; and Adam Zimmerman from Burness. Two other briefs in this 

series can be downloaded from Mathematica’s website: 

Proposed Changes to the Supplemental Nutrition Assistance Program: Heating and 

Cooling Standard Utility Allowances and Earned Income (https:// 

www.mathematica-mpr.com/our-publications-and-findings/publications/proposedchanges-to-the-supplemental-nutrition-assistance-program-heating-and-cooling-standard) 

Simulating Proposed Changes to the Supplemental Nutrition Assistance Program: 

Countable Resources and Categorical Eligibility (https://www.mathematicampr.com/our-publications-and-findings/publications/simulating-proposed-changesto-the-supplemental-nutrition-assistance-program-countable-resources) 

For more information about Mathematica’s work in this area, contact 

Senior Researcher Karen Cunnyngham at KCunnyngham@mathematicampr.com or (202) 264–3480. 

The CHAIR. Thank you very much. 

Mr. Adolphsen—obviously, you are not getting a yellow light for 

some reason, so when you see the red light, just please try to wrap 

up. 

STATEMENT OF SAM ADOLPHSEN, VICE PRESIDENT OF 

EXECUTIVE AFFAIRS, FOUNDATION FOR GOVERNMENT 

ACCOUNTABILITY, NAPLES, FL 

Mr. ADOLPHSEN. Chair Fudge, Ranking Member Johnson, Members of the Nutrition Subcommittee, thank you for the privilege of 

testifying. 

I was brought up in a household that believed in hard work. My 

dad was a landscaper. My mom cleaned houses. A job was a point 

of pride, and I can still remember getting that first paycheck from 

a tough day raking blueberries in rural Maine. 

For many of us, that is our story. Work is central to our lives. 

It provides dignity and purpose. The growth of our communities is 

built on people living this experience, living the American dream. 

And work is key to achieving the long-term goal of the food stamp 

program, lifting people out of poverty. That is why Congress and 

President Clinton passed bipartisan work requirements for ablebodied adults on food stamps in 1996. They recognized the power 

of work, and they were right. Where work requirements have been 

implemented, those leaving the program doubled their incomes in 

just 1 year. And they didn’t just go to work in retail or fast food. 

They went back to work in more than 1,000 different industries. 

Now, these figures aren’t extrapolations or anecdotes. Our experts studied the actual earnings of 600,000 able-bodied adults who 

left food stamps after work requirements were implemented in 

Florida, Kansas, and Arkansas. 

One young man in Arkansas—I will call him Nolan—reported no 

income while on welfare, $0. After work requirements were implemented, Nolan soon left the program. Then Nolan got a job. Within 

1 year, he was earning $63,000, and by the end of 2 years, he was 

making $93,000. Work requirements work. 

Unfortunately for millions of able-bodied adults on food stamps, 

this isn’t the experience at all. And government bears a big part 

of the blame. When I was Chief Operating Officer of the food stamp 

agency in Maine, before we reinstated work requirements, I had 

1,000 state employees helping fill out food stamp applications. But 

19 

no one helping fill out job applications. We were letting people like 

Nolan down. Government should be giving a hand up, not just a 

hand out. 

The loopholes created at the Federal agency level have gutted 

the 1996 law, allowing work to be waived across the country by 

gerrymandering areas and using old economic data. 

I want you to remember two numbers, 2.6 million and 7.6 million. 

First, 2.6 million. There are 2.6 million able-bodied adults on 

food stamps who will be waived from the work requirement this 

year, and three out of four don’t work at all. 

Second, 7.6 million. There are 7.6 million available jobs today, 

and the lowest unemployment rate in 50 years. Employers are desperate for workers. 

To be clear, Federal law allows waivers only when there are not 

enough jobs, or unemployment is at least ten percent. But just 23 

of the 1,100 counties and cities that waive work requirements have 

unemployment at or above ten percent. One California waiver 

county has 2.2 percent unemployment, and Ohio’s waiver has more 

than doubled since 2017, even as its unemployment rate declined 

to near record low levels. Waivers from work shouldn’t be so easy 

to get in the best economy in decades. 

Some have claimed that Congress rejected the type of changes 

proposed here by the Trump Administration, but the bipartisan 

2018 Farm Bill, like every other farm bill since 1996, reaffirmed 

the original work requirements, and it did not codify the current 

regulations that have allowed the waiver abuse. 

It is clear that the status quo does not reflect Congressional intent. Even Chairman Collin Peterson correctly pointed out that the 

loopholes have allowed states to ‘‘undermine Federal law.’’ 

The Trump Administration has the authority and the duty to fix 

the regulation and return waivers to their original purpose of exempting only those individuals in truly economically depressed 

areas. The track record of work requirements is clear. They work. 

And when this rule is implemented, we can all be confident that 

hundreds of thousands of Americans, people just like Nolan, will 

move from welfare to work and experience their own American 

dream. 

Thank you. I am happy to answer any questions. 

[The prepared statement of Mr. Adolphsen follows:] 

PREPARED STATEMENT OF SAM ADOLPHSEN, VICE PRESIDENT OF EXECUTIVE AFFAIRS, 

FOUNDATION FOR GOVERNMENT ACCOUNTABILITY, NAPLES, FL 

Examining the Proposed ABAWD Rule 

Chair Fudge, Ranking Member Johnson, and Members of the Committee, thank 

you for the privilege of testifying. I am Sam Adolphsen, the Vice President of Executive Affairs at the Foundation for Government Accountability (FGA). FGA is a nonpartisan research organization dedicated to helping millions of individuals achieve 

the American Dream. 

Prior to joining FGA, I served as the Chief Operating Officer of the Maine Department of Health and Human Services. In that role, I oversaw operations for Maine’s 

welfare programs, including the food stamp program. My duties included direct 

oversight of the food stamp eligibility and policy office. 

I was fortunate to be brought up in a household that believed in hard work. My 

dad was a landscaper and my mom cleaned houses. I knew from a young age that 

work is not a dirty word—it is a good thing. A job was a point of pride, and I can 

20 

1 7 U.S.C. § 2015(o) (2016), https://www.gpo.gov/fdsys/pkg/USCODE-2016-title7/pdf/ 

USCODE-2016-title7-chap51-sec2015.pdf. 2 Ibid. 

3 Ibid. 

4Kenneth Hanson and Karen S. Hamrick, ‘‘Moving public assistance recipients into the labor 

force, 1996–2000,’’ U.S. Department of Agriculture (2004), https://www.ers.usda.gov/webdocs/ 

publications/46832/49356_fanrr40.pdf. 5 Jonathan Ingram and Nicholas Horton, ‘‘The power of work: How Kansas’ welfare reform is 

lifting Americans out of poverty,’’ Foundation for Government Accountability (2016), https:// 

thefga.org/wp-content/uploads/2016/02/Kansas-study-paper.pdf. 6 Jonathan Ingram and Josh Archambault, ‘‘New report proves Maine’s welfare reforms are 

working,’’ Forbes (2016), https://www.forbes.com/sites/theapothecary/2016/05/19/new-reportproves-maines-welfare-reforms-are-working. 7 Nicholas Horton and Jonathan Ingram, ‘‘Work requirements are working in Arkansas: How 

commonsense welfare reform is improving Arkansans’ lives,’’ Foundation for Government Accountability (2019), https://thefga.org/wp-content/uploads/2019/01/Work-Requirement-areWorking-in-Arkansas-How-Commonsense-Welfare-Reform-is-Improving-Arkansans-Lives-1-9- 

19.pdf. 8 Nicholas Horton and Jonathan Ingram, ‘‘Commonsense welfare reform has transformed Floridians’ lives,’’ Foundation for Government Accountability (2019), https://thefga.org/wp-content/uploads/2019/03/FloridaTrackingStudyResearchPaper-3.1.19.pdf. 9Sam Adolphsen, et al., ‘‘Waivers gone wild: How states have exploited food stamp loopholes,’’ 

Foundation for Government Accountability (2018), https://thefga.org/wp-content/uploads/ 

2018/06/Waivers-Gone-Wild-6-5-18-update.pdf. 10 Jonathan Ingram, et al., ‘‘How the Trump administration can cut down on waivers gone 

wild,’’ Foundation for Government Accountability (2019), https://thefga.org/wp-content/ 

uploads/2019/02/LMA-Memo-FoodStampWaiversGoneWild-2.20.19.pdf. 11 House Committee on Agriculture, ‘‘Full House Agriculture Committee hearing with Secretary Perdue on the state of the rural economy,’’ U.S. House of Representatives (2019), https:// 

www.youtube.com/watch?v=m8t4etV1X8g. 

still remember that first paycheck from a tough day raking blueberries in coastal 

Maine. I’m sure you remember your first job, too, and what it taught you. 

For so many of us that’s our story-work is central to our lives. It provides us with 

dignity and purpose. The growth of our communities and our nation as a whole is 

dependent on people experiencing this—living their American Dream. 

And it is the key to achieving the long-term goals of the food stamp program: to 

help lift people out of poverty. Unfortunately, for millions of able-bodied adults on 

food stamps, this isn’t the experience at all. Work isn’t even in the picture and food 

stamp rules allow long-term dependency with no accountability. 

The law is clear: work requirements should be the standard for able-bodied adults 

with no children. And where the law is followed, work requirements have proven 

to move people from welfare to work and leave them better off. But despite an economy desperate for workers, loopholes in Federal food stamp rules continue to permit 

work requirements to be waived in states across the country, leaving millions of 

able-bodied adults with no kids on the sidelines. 

Work Is Key to Achieving the Food Stamp Program’s Goals 

In 1996, Congress passed—and President Clinton signed—commonsense, bipartisan welfare reform. As part of that reform, most able-bodied, childless adults were 

required to work, train, or volunteer part-time as a condition of food stamp eligibility.1 These requirements applied to non-pregnant adults who are mentally and 

physically fit for employment, who are between the ages of 18 and 50, and who have 

no dependent children or incapacitated family members.2 Able-bodied adults who refused to meet these requirements were limited to just 3 months of food stamp benefits every 3 years.3

When it was first implemented in the 1990s, this commonsense work requirement 

moved millions of able-bodied adults from welfare to work and spurred rapid economic growth.4 Analyses of state-level implementation have reached similar conclusions.5–8 But this progress has been undermined by Federal loopholes that have allowed states to weaken and waive the requirements for millions of adults, even during periods of sustained economic growth.9–10 States, which bear little of the cost for 

the program, continue to take advantage of these loopholes with regularity despite 

the booming economy. United States Department of Agriculture (USDA) Secretary 

Sonny Perdue recently noted in a hearing before Congress that the waivers, ‘‘were 

abused in Georgia,’’ and he believes, ‘‘are being abused in many places.’’ 11

As a result of these loopholes, most able-bodied adults receiving food stamps are 

not required to work. According to state data, nearly 63 percent of able-bodied 

adults without dependents on the program—some 2.6 million adults—will be waived 

21 

12 Jonathan Ingram, et al., ‘‘How the Trump administration can cut down on waivers gone 

wild,’’ Foundation for Government Accountability (2019), https://thefga.org/wp-content/ 

uploads/2019/02/LMA-Memo-FoodStampWaiversGoneWild-2.20.19.pdf. 13 Jonathan Ingram and Nicholas Horton, ‘‘How the Agriculture and Nutrition Act of 2018 

would rein in workrequirement waivers gone wild,’’ Foundation for Government Accountability 

(2018), https://thefga.org/wpcontent/uploads/2019/01/How-the-Agriculture-and-Nutrition-Actof-2018-would-rein-in-work-requirement-waivers-gone-wild.pdf. 14 Author’s calculations based upon data provided by the U.S. Department of Agriculture on 

enrollment and work status of able-bodied adults without dependents. See, e.g., Food and Nutrition Service, ‘‘Supplemental Nutrition Assistance Program quality control database,’’ U.S. Department of Agriculture (2016), https://host76.mathematica-mpr.com/fns/PUBLIC_USE/2015/ 

qcfy2015_st.zip. 15 Council of Economic Advisers, ‘‘Expanding work requirements in non-cash welfare programs,’’ Executive Office of the President (2018), https://www.whitehouse.gov/wp-content/ 

uploads/2018/07/ExpandingWork-Requirements-in-Non-Cash-Welfare-Programs.pdf. 16 7 U.S.C. § 2015(d), https://www.gpo.gov/fdsys/pkg/USCODE-2016-title7/pdf/USCODE2016-title7-chap51-sec2015.pdf. 17 Jonathan Ingram and Nicholas Horton, ‘‘The power of work: How Kansas’ welfare reform 

is lifting Americans out of poverty,’’ Foundation for Government Accountability (2016), https:// 

thefga.org/wp-content/uploads/2016/02/Kansas-study-paper.pdf. 18 Ibid. 19 Ibid. 20 Jonathan Ingram and Josh Archambault, ‘‘New report proves Maine’s welfare reforms are 

working,’’ Forbes (2016), https://www.forbes.com/sites/theapothecary/2016/05/19/new-reportproves-maines-welfare-reforms-are-working. 21 Ibid. 22 Nicholas Horton and Jonathan Ingram, ‘‘Work requirements are working in Arkansas: How 

commonsense welfare reform is improving Arkansans’ lives,’’ Foundation for Government Accountability (2019), https://thefga.org/wpcontent/uploads/2019/01/Work-Requirement-areWorking-in-Arkansas-How-Commonsense-Welfare-Reform-is-Improving-Arkansans-Lives-1-9- 

19.pdf. 23 Ibid. 24 Ibid. 

from the work requirement in Fiscal Year 2019.12–13 With no work requirement in 

place, few able-bodied adults on the program actually work. Just two percent of 

able-bodied adults without dependents on food stamps work full-time, while roughly 

3⁄4 do not work at all.14–15

These waiver loopholes have trapped millions of able-bodied adults in dependency. 

But these loopholes have also allowed state agencies to skip out on their duty to 

engage these adults and help put them back on the path to self-sufficiency. The 

work requirement was designed not just to require work or work activities by the 

recipient of the program, but also to require the administering agency to engage 

with able-bodied adults.16

In my role as chief operating officer at the Maine Department of Health and 

Human Services, I saw firsthand how—until we restored the work requirement 

statewide-agency bureaucrats would simply send out benefits on autopilot instead 

of engaging with adults to help reconnect them with their community. By waiving 

the work requirement for able-bodied adults, the food stamp agency’s responsibility 

to help people get back on their feet and move beyond welfare program dependency 

is also waived, making that important assistance more optional for the agency. 

When Enforced, Work Requirements Promote Independence 

These commonsense work requirements have a proven track record of success. 

After Kansas restored these work requirements in 2013, the number of able-bodied 

adults without dependents on the program dropped by more than 75 percent.17

Those able-bodied adults went back to work in hundreds of diverse industries and 

their incomes more than doubled within a year.18 Better still, those higher incomes 

more than offset lost welfare benefits, leaving them financially better off.19

Maine experienced similar successes after restoring the work requirement in 

2014.20 The number of able-bodied adults without dependents on the program 

dropped by more than 90 percent and average wages more than doubled within a 

year.21

When Arkansas followed suit in 2016, able-bodied adult enrollment dropped by 70 

percent.22 Those adults saw their incomes more than double in the year after leaving the program and then more than triple in the second year.23 Higher wages more 

than offset lost food stamp benefits, leaving individuals better off than when they 

were trapped in dependency.24

These adults moved into many diverse industries, touching virtually every corner 

of the American economy. After Florida restored the work requirement in 2016, 

able-bodied adults without dependents found work far beyond the fast food or big 

22 

25 Nicholas Horton and Jonathan Ingram, ‘‘Commonsense welfare reform has transformed Floridians’ lives,’’ Foundation for Government Accountability (2019), https://thefga.org/wp-content/uploads/2019/03/FloridaTrackingStudyResearchPaper-3.1.19.pdf. 26 Ibid. 27 Ibid. 28Sam Adolphsen and Jonathan Ingram, ‘‘Three myths about the welfare cliff,’’ Foundation 

for Government Accountability (2018), https://thefga.org/wp-content/uploads/2018/02/Threemyths-about-the-welfare-cliff-2-28-18.pdf. 29 Jonathan Ingram and Sam Adolphsen, ‘‘How moving able-bodied adults from welfare to 

work could help solve the opioid crisis,’’ Foundation for Government Accountability (2019), 

https://thefga.org/wp-content/uploads/2019/03/OpioidDeathsMemo-ResearchPaperDRAFT4.pdf. 30 Bureau of Labor Statistics, ‘‘Labor force statistics from the current population survey,’’ U.S. 

Department of Labor (2019), https://data.bls.gov/timeseries/LNS14000000. 31 Ibid. 32 Bureau of Labor Statistics, ‘‘Current unemployment rates for states and historical highs and 

lows, seasonally adjusted,’’ U.S. Department of Labor (2019), https://www.bls.gov/web/laus/ 

lauhsthl.htm. 33 Ibid. 34 Bureau of Labor Statistics, ‘‘Labor force statistics from the current population survey: Seasonally adjusted employment level,’’ U.S. Department of Labor (2019), https://data.bls.gov/ 

timeseries/LNS12000000. 35 Bureau of Labor Statistics, ‘‘Employment, hours, and earnings from the current employment 

statistics survey: Average hourly earnings of all employees,’’ U.S. Department of Labor (2019), 

https://data.bls.gov/timeseries/CES0500000003. 36 Council of Economic Advisers, ‘‘Economic report of the President together with the annual 

report of the Council of Economic Advisors,’’ Executive Office of the President (2019), https:// 

www.whitehouse.gov/wp-content/uploads/2019/03/ERP-2019.pdf. 37 Bureau of Labor Statistics, ‘‘Job openings and labor turnover survey: Total nonfarm job 

openings,’’ U.S. Department of Labor (2019), https://data.bls.gov/timeseries/JTS00000000JOL. 38Sam Adolphsen, ‘‘There has never been a better time for welfare reform,’’ Foundation for 

Government Accountability (2018), https://thefga.org/wp-content/uploads/2018/06/Its-TimeTo-Get-To-Work-FINAL.pdf. 39 Ibid. 40 Ibid. 

box retail industries.25 In fact, these adults found work in more than 1,000 different 

industries.26 Better still, they used those initial jobs as stepping stones to other jobs 

in higher-paid industries. Nearly 70 percent of those who initially found work in the 

fast food industry or at temp agencies left those industries within a year, moving 

from lower-wage industries to higher-wage industries over time.27

Work also provides powerful benefits far beyond the nominal value of earned 

wages. Work can help build new and positive social relationships, help individuals 

gain new skills, create new experiences that lead to future employment opportunities and higher incomes, and serves as the single best path out of poverty.28 It could 

even help solve major public health concerns like the opioid crisis.29 Work is a key 

predictor of success for someone recovering from substance abuse. 

Employers, and the Economy, Desperately Need Workers 

At 3.8 percent, the nation’s unemployment rate is hovering at its lowest point 

since 1969.30 The unemployment rate has stayed at or below four percent for 12 consecutive months, with some states seeing unemployment rates as low as 2.4 percent.31–32 Since June 2017, 19 states have hit new record-low unemployment levels, 

including some who waive work requirements across their state.33

More Americans are working today than at any point since the Bureau of Labor 

Statistics began tracking employment statistics.34 Average earnings have reached 

nearly $28 per hour—the highest level ever recorded.35 Nearly 3⁄4 of all individuals 

now finding work were pulled off the sidelines and back into the labor force—a 

record high.36

But even today’s booming economy is not enough: employers are searching desperately to fill a record-high 7.6 million open jobs.37 At least 1⁄3 of small businesses 

have unfilled job openings, the highest rate in 50 years.38 Employers are offering 

signing bonuses, student loan repayment, company cars, relocation fees, and more 

to find and retain talent—at all skill levels.39 For our economy to continue growing 

and thriving, we need the adults currently receiving food stamps and sitting on the 

sidelines to rejoin the workforce. 

Despite some concerns of a ‘‘skills gap,’’ the reality is that millions of jobs require 

little specialized education, training, or experience. In fact, according to the Bureau 

of Labor Statistics, nearly 3⁄4 of the job openings that will occur over the next decade 

require a high school education or less.40 Nearly four out of five job openings require 

23 

41 Ibid. 42 7 U.S.C. § 2015(o)(4)(A) (2016), https://www.gpo.gov/fdsys/pkg/USCODE-2016-title7/pdf/ 

USCODE-2016-title7-chap51-sec2015.pdf. 43Sam Adolphsen, et al., ‘‘Waivers gone wild: How states have exploited food stamp loopholes,’’ 

Foundation for Government Accountability (2018), https://thefga.org/wp-content/uploads/ 

2018/06/Waivers-Gone-Wild-6-5-18-update.pdf. 44 Jonathan Ingram, et al., ‘‘How the Trump administration can cut down on waivers gone 

wild,’’ Foundation for Government Accountability (2019), https://thefga.org/wp-content/ 

uploads/2019/02/LMA-Memo-FoodStampWaiversGoneWild-2.20.19.pdf. 45 Ibid. 46Sam Adolphsen, et al., ‘‘Waivers gone wild: How states have exploited food stamp loopholes,’’ 

Foundation for Government Accountability (2018), https://thefga.org/wp-content/uploads/ 

2018/06/Waivers-Gone-Wild-6-5-18-update.pdf. 47 Ibid. 48 Ibid. 49 Jonathan Ingram and Sam Adolphsen, ‘‘FNS–2018–0004–5999,’’ Opportunity Solutions 

Project (2019), https://solutionsproject.org/wp-content/uploads/2019/03/OSP-Comment-andsupplement.pdf. 50 Ibid. 51 Ibid. 52 Author’s calculations based upon data provided by Haver Analytics on February 2019 job 

postings gathered from more than 16,000 Internet job boards, corporate boards, and other job 

sites. 53 Author’s calculations based upon data provided by state labor market information agencies 

on average annual projected job openings over the next decade. 

no training or less than a month’s training on the job, while a whopping 87 percent 

require no prior experience.41

Loopholes Have Allowed States To Waive Work Requirements 

When Congress passed the food stamp work requirements into law in 1996, it 

gave the Secretary of the United States Department of Agriculture the authority to 

waive work requirements in areas that had unemployment rates above ten percent 

or otherwise lacked job opportunities for these able-bodied adults.42

Despite these narrow parameters set forth by Congress, Federal rulemaking led 

to a regulation that is far more expansive than intended, creating loopholes and 

gimmicks for states to continue waiving work requirements for millions of able-bodied adults, even during periods of record economic growth.43 As a result, these commonsense requirements are waived wholly or partially in 33 states and the District 

of Columbia.44 As a result, nearly 2.6 million able-bodied adults who would otherwise be required to work, train, or volunteer have those requirements waived altogether.45

Although the statute specifies that the waivers should only apply to areas with 

high unemployment that lack a sufficient number of jobs, regulatory loopholes allow 

states to waive work requirements in areas with record-low unemployment by combining and gerrymandering them with areas with somewhat higher unemployment 

rates.46 These loopholes also allow states to use data from years ago, even when 

that data has no connection to current economic conditions.47 If that weren’t bad 

enough, the regulation creates an alternative waiver option even in areas with unemployment rates below ten percent. Under this option, states can qualify for a 

waiver so long as their unemployment rates are 20 percent above the national average during a 2 year period, no matter how low that rate is and no matter how many 

open jobs are available.48

Of the more than 1,100 counties, towns, cities, and other jurisdictions where work 

requirements are currently waived, just 23 have unemployment rates above ten percent.49 More than 800 of these jurisdictions have unemployment rates at or below 

five percent and nearly 200 have unemployment rates at or below three percent.50

The waived jurisdictions have unemployment rates as low as zero percent—meaning 

work requirements are waived in areas with literally no unemployment.51 Despite 

claims that these areas are facing severe job shortages, the 33 states currently 

waiving the work requirement have more than a combined 3.7 million job openings 

posted online.52 These states are expected to experience nearly 13 million job openings per year over the next decade.53

Loopholes Have Expanded Work Requirement Exemptions 

Regulatory loopholes have also exempted hundreds of thousands of able-bodied 

adults from the work requirement in direct conflict with Congressional intent. 

Shortly before leaving office, the Clinton Administration created new exemptions for 

able-bodied adults who reside in households with children—regardless of whether 

24 

54 Jonathan Ingram, et al., ‘‘Why the Trump administration should move able-bodied adult siblings from welfare to work,’’ Foundation for Government Accountability (2019), https:// 

thefga.org/wp-content/uploads/2019/03/ABAWD-Siblings-to-Work-Research-PaperDRAFT6.pdf. 55 Jonathan Ingram, et al., ‘‘Closing the food stamp loophole that allows 50-year-olds to avoid 

work,’’ Foundation for Government Accountability (2019), https://thefga.org/wp-content/ 

uploads/2019/01/50-Year-Old-Food-Stamp-Loophole-Memo-1.24.19.pdf. 56 Jonathan Ingram, et al., ‘‘Why the Trump administration should move able-bodied adult siblings from welfare to work,’’ Foundation for Government Accountability (2019), https:// 

thefga.org/wp-content/uploads/2019/03/ABAWD-Siblings-to-Work-Research-PaperDRAFT6.pdf. 57 Jonathan Ingram, et al., ‘‘Closing the food stamp loophole that allows 50-year-olds to avoid 

work,’’ Foundation for Government Accountability (2019), https://thefga.org/wp-content/ 

uploads/2019/01/50-Year-Old-Food-Stamp-Loophole-Memo-1.24.19.pdf. 58 Jonathan Ingram, et al., ‘‘How the Trump administration can cut down on waivers gone 

wild,’’ Foundation for Government Accountability (2019), https://thefga.org/wp-content/ 

uploads/2019/02/LMA-Memo-FoodStampWaiversGoneWild-2.20.19.pdf. 59 Jonathan Ingram and Sam Adolphsen, ‘‘FNS–2018–0004–5999,’’ Opportunity Solutions 

Project (2019), https://solutionsproject.org/wp-content/uploads/2019/03/OSP-Comment-andsupplement.pdf. 60Sam Adolphsen, et al., ‘‘Waivers gone wild: How states have exploited food stamp loopholes,’’ 

Foundation for Government Accountability (2018), https://thefga.org/wp-content/uploads/ 

2018/06/Waivers-Gone-Wild-6-5-18-update.pdf. 61 Ibid. 62 Jonathan Ingram, et al., ‘‘How the Trump administration can cut down on waivers gone 

wild,’’ Foundation for Government Accountability (2019), https://thefga.org/wp-content/ 

uploads/2019/02/LMA-Memo-FoodStampWaiversGoneWild-2.20.19.pdf. 63 Ibid. 64 Ibid. 65 Ibid. 66 Ibid. 

they are parents or caretakers—as well as 50 year old able-bodied adults who would 

otherwise be required to work, train, or volunteer under the statute.54–55

These exemptions conflict with the plain meaning of the food stamp statute, Congressional intent, prior interpretation by state agencies, and even Food and Nutrition Service’s own interpretation of the same terms.56–57

The Proposed Rule Would Help Address Waiver Abuse 

The proposed rule represents a significant improvement over the status quo.58–59

By closing some of the most egregious loopholes that have led to widespread waiver 

abuse, the proposed rule brings waiver guidance more in line with statutory requirements that have been enshrined in law for more than 20 years. Under the proposal, 

states can continue to request waivers in areas that lack sufficient jobs but will not 

have as many avenues to abuse the process. 

The first major area of change in the proposed rule is an attempt to reduce gerrymandering abuse. Federal law allows the Secretary to grant waivers in areas that 

lack sufficient jobs, but does not define ‘‘areas’’ for waiver purposes.60 States have 

used this ambiguous language to gerrymander jurisdictions together to form ‘‘areas’’ 

solely to maximize the number of able-bodied adults waived from the work requirement.61 Illinois, for example, combines 101 of the state’s 102 counties into a single 

‘‘area,’’ while California combines all but three counties into a single ‘‘area’’ for waiver purposes.62 These waived jurisdictions do not form a single, local region with a 

shared economy. Instead, they just happen to the jurisdictions that, when combining 

data, just marginally meet the current regulatory thresholds for waivers. 

The proposed rule attempts to limit this abuse by only allowing states to combine 

jurisdictions together for waiver purposes if they form labor market areas.63 The 

purpose of this change is to ‘‘target waivers to jurisdictions with a demonstrable 

lack of sufficient jobs,’’ as required by the statute.64 But even this could be subject 

to abuse. States could still seek waivers in jurisdictions that have sufficient jobs and 

in areas where there are sufficient jobs within commuting distance.65

One solution the Trump Administration could take to solve this remaining problem—and better align the proposed rule with the food stamp statute—would be to 

prohibit states from combining jurisdictions for waiver purposes at all and to eliminate waivers for jurisdictions located in commuting zones with sufficient jobs.66

The second major change in the proposed rule sets a minimum unemployment 

floor for states seeking waivers. Although Federal law defines high unemployment 

as above ten percent, existing regulations allow waivers whenever an area’s unemVerDate Aug 31 2005 11:16 Jun 14, 2019 Jkt 041481 PO 00000 Frm 00030 Fmt 6633 Sfmt 6621 P:\DOCS\116-02\36188.TXT BRIAN
25 

67 7 U.S.C. § 2015(o)(4)(A) (2016), https://www.gpo.gov/fdsys/pkg/USCODE-2016-title7/pdf/ 

USCODE-2016-title7-chap51-sec2015.pdf. 68 7 CFR § 273.24(f)(3)(iii) (2018), https://www.gpo.gov/fdsys/pkg/CFR-2018-title7-vol4/pdf/ 

CFR-2018-title7-vol4-sec273-24.pdf. 69Food and Nutrition Service, ‘‘Supplemental Nutrition Assistance Program: Requirements for 

able-bodied adults without dependents,’’ U.S. Department of Agriculture (2018), https://fnsprod.azureedge.net/sites/default/files/snap/ABAWDtoOFR.pdf. 70 Jonathan Ingram and Sam Adolphsen, ‘‘FNS–2018–0004–5999,’’ Opportunity Solutions 

Project (2019), https://solutionsproject.org/wp-content/uploads/2019/03/OSP-Comment-andsupplement.pdf. 71 Ibid. 72 Chuck Abbot, ‘‘Food stamp revisions possible but not radical change, says key House Democrat,’’ Fern’s Ag Insider (2018), https://thefern.org/ag_insider/food-stamp-revisions-possible-notradical-change-says-key-house-democrat. 

ployment rate is 20 percent above the national average, with no minimum floor.67–68

This guarantees that at least some portion of the country will always be granted 

waivers, even during periods of unprecedented economic growth. 

The proposed rule attempts to address this abuse by setting a minimum floor of 

seven percent unemployment.69 But even this may not be enough to stop states from 

pursuing waivers in areas with sufficient jobs. 

A minimum unemployment rate of seven percent only truly matters during a period of near full employment, as the threshold would only activate when the national unemployment rate falls below 5.8 percent for a sustained 2 year window.70

This threshold is just slightly above the historical average ‘‘natural’’ unemployment 

rate—the level most economists agree is ‘‘full employment’’—and just below the average unemployment rate over the last 70 years.71

The Trump Administration could strengthen the rule even further—and more 

closely align with the food stamp statute—by raising that threshold to ten percent. 

This would better target waivers to areas that have objectively high unemployment 

and lack sufficient jobs. 

The Proposed Rule Better Reflects Congressional Intent 

Although some have claimed the proposed rule was ‘‘specifically rejected’’ by Congress in the 2018 Farm Bill, nothing could be further from the truth. The Housepassed version of the farm bill made significant changes to the work requirement, 

but those changes were materially different from the proposed rule. The Housepassed bill eliminated the time limit for able-bodied adults without dependents entirely, focusing instead on strengthening the work registration requirements for a 

broader group of able-bodied adults. It created new waivers and exemptions from 

the work registration requirements, but the qualifications for those waivers were 

materially different from those in the proposed rule. In short, the changes in the 

proposed rule were never even considered by Congress. 

Far from rejecting the changes proposed by the Trump Administration, the 2018 

Farm Bill left in place the original work requirements first enacted in 1996. Those 

statutory requirements serve as the basis for the proposed rule, which simply seeks 

to close unlawful loopholes created through regulatory guidance. It is undisputed 

that the current regulatory framework does not reflect Congressional intent. Even 

Chairman Collin Peterson noted last year that the loopholes have allowed states to 

‘‘undermine Federal law’’ by abusing these waivers.72

By leaving in place those statutory requirements exactly as first enacted in 1996, 

Congress signaled that it did not wish to codify the unlawful waiver expansions created through regulation. This left in place the authority—and the duty—of the 

Trump Administration to return these waivers to their original purpose. 

Work Will Improve Lives and Boost the Economy 

The proposed rule represents a significant step forward in moving able-bodied 

adults from welfare to work and realigning Federal regulations with statutory requirements. It would not simply require millions of able-bodied adults without children to work—the rule will also encourage state agencies to do a better job of actually engaging with individuals and putting them back on the pathway to self-sufficiency and better lives. The requirement will help connect able-bodied adults who 

are out of work with employers who desperately need workers to fill open jobs. For 

those who cannot work immediately, it will connect individuals to available job 

training or educational opportunities. Whether through work, training, or volunteering, these adults will be better connected to their communities. This will ultimately move millions more able-bodied adults from welfare to work and from government dependence to independence. 

26 

ATTACHMENT

More Than 2,567,550 Able-Bodied Adults Have No Food Stamp Work Requirements 

Source: U.S. Department of Agriculture. 

The CHAIR. Thank you. Ms. Hamler-Fugitt. 

STATEMENT OF LISA HAMLER-FUGITT, EXECUTIVE DIRECTOR, 

OHIO ASSOCIATION OF FOODBANKS, COLUMBUS, OH 

Ms. HAMLER-FUGITT. Thank you. Good morning, Chair Fudge, 

Ranking Member Johnson, and distinguished Members of the Subcommittee. Thank you for convening this hearing today and inviting me to testify on the Trump Administration’s proposed rules related to unemployed or underemployed adults without dependents 

participating in the SNAP Program. 

My name is Lisa Hamler-Fugitt, and I serve as the Executive Director of the Ohio Association of Food Banks, Ohio’s largest charitable response to hunger. We distributed over 200 million pounds 

of emergency food last year in an attempt to fill the gap for hungry 

Ohioans, but SNAP provides 12 times as much food while infusing 

resources into local communities. 

The Administration’s proposed rule would limit access to SNAP 

for adults with very limited resources without improving their 

overall employment outlook or health outcomes. Based on my Association’s firsthand experience operating the SNAP Work Experience 

Program, which provides services exclusively for clients required to 

find work under the current SNAP rule, I am here to provide you 

with my perspective on the impacts that this proposed rule would 

have in Ohio. 


11602115.eps
27 

Currently, 38 of Ohio’s 88 counties have waived SNAP time limits due to high unemployment. If the proposed rule were to take 

effect today with the seven percent threshold for waiver eligibility, 

only three Ohio counties would qualify for the waiver. These three 

counties account for less than one percent of Ohio’s current SNAP 

population, meaning that nearly all would be subject to the time 

limit if the proposed rule went into effect. 

Unfortunately, we know from our extensive experience that those 

subject to the time limit have profound barriers to employment. 

The Work Experience Program conducts in depth, comprehensive 

client assessments to determine the client employability and identify barriers to employment. Over the first 2 years of our program, 

we completed over 5,000 in depth interviews and gathered information on 5,500 self-reported employment and skills assessments. Our 

results represent the state’s most comprehensive and up-to-date 

data available on this population. 

Our single largest and biggest takeaway is the term ABAWD is 

a complete misnomer for who this population is. One in three clients reported a physical or mental limitation ranging from back injuries to heart conditions to depression to PTSD. Many participants 

appear to be marginally or functionally illiterate, and likely experiencing significant learning disabilities. Additionally, many clients 

appear to have social and/or cognitive impairments, difficulty communicating, and a tendency to engage in repetitive behaviors, all 

signs of autism spectrum disorder. We believe that there are high 

levels of undiagnosed autism and other developmental disabilities 

in this population. One in three clients have no high school diploma 

or GED. Nearly 1⁄2 reported that they do not have reliable transportation, whether through a personal vehicle, public transit, or 

ride sharing with family or friends. And 60 percent report that 

they do not have a current, valid driver’s license. About 1⁄3 of our 

clients had felony convictions, a stigma which can follow someone 

for a lifetime, even if their release is meant to suggest that they 

have been rehabilitated. 

Many of our clients are parents or caregivers with responsibilities that can serve as barriers to employment, and one in four of 

our clients had children that were not in their custody and many 

spent time parenting those children on a regular basis while the 

custodial parent works. Additionally, one in ten reported they are 

caregivers for family, friends, or relatives. In addition to these 

issues, many of our clients face other challenges which makes finding employment difficult. 

We serve hundreds of individuals who have aged out of the foster 

care system, only to find themselves living in homeless shelters, 

with friends, or on the street. Many other clients are experiencing 

challenges like homelessness and language barriers. These individuals face daunting challenges in finding employment, even when 

general unemployment rates are low, which is exactly why Congress gave states the option to waive the time limit in areas where 

there were insufficient jobs for those who were subject to the requirement. 

I would like to share just one story of a client, a Somalian refugee who relies on public transportation and requires an interpreter to fulfill his mandatory work requirements. Due to a paperVerDate Aug 31 2005 11:16 Jun 14, 2019 Jkt 041481 PO 00000 Frm 00033 Fmt 6633 Sfmt 6601 P:\DOCS\116-02\36188.TXT BRIAN
28 

work error, he was mistakenly cut off his SNAP benefits and was 

sent to our local food pantry network to get food, until his case 

could be sorted out. Sadly, this case is not unique. Tens of thousands of real people like him are slipping through the cracks. 

We know all too well that harsh and arbitrary time limits are 

misguided and only increase hunger and hardship. The proposed 

rule would shift the burden of providing food from the Federal Government on to cities, states, and local charities like mine. It would 

be harmful to the local economies, grocers, retailers, and the agriculture community by reducing the amount of SNAP benefits and 

dollars available and economic activity. 

The CHAIR. Please wrap up for me. 

Ms. HAMLER-FUGITT. Most importantly, the rule sidesteps the 

will of Congress, which rejected these changes when it enacted the 

2018 Farm Bill. 

We hope that we can work together to stop these harmful policies 

from taking effect, and I would be happy to answer any questions 

you may have. 

[The prepared statement of Ms. Hamler-Fugitt follows:] 

PREPARED STATEMENT OF LISA HAMLER-FUGITT, EXECUTIVE DIRECTOR, OHIO

ASSOCIATION OF FOODBANKS, COLUMBUS, OH 

The findings of our comprehensive assessment of able-bodied adults without dependents can be found at our website at: http://ohiofoodbanks.org/ 

wep/WEP-2013-2015-report.pdf. 

Good morning, Chair Marcia L. Fudge, Ranking Member Dusty Johnson, and distinguished Members of the U.S. House Agriculture Subcommittee on Nutrition, 

Oversight, and Department Operations. 

My name is Lisa Hamler-Fugitt and I serve as the executive director of the Ohio 

Association of Foodbanks, Ohio’s largest charitable response to hunger. My association represents Ohio’s 12 Feeding America food banks and their more than 3,500 

member hunger relief charities. Our mission is to provide food and resources to people in need and to pursue areas of common interest for the benefit of people in need. 

Last year, the association distributed 216 million pounds of food to more than two 

million low-income Ohioans—one in six of our hungry friends and neighbors. 

Thank you for convening this hearing today and inviting me to testify on the 

Trump Administration Proposed Rule: Supplemental Nutrition Assistance Program 

(SNAP): Requirements for Able-Bodied Adults without Dependents RIN 0584–AE57. 

This rule would limit the ability of states to waive the 3 month time limit that 

applies to unemployed and underemployed Able-Bodied Adults Without Dependents 

who receive benefits through the Supplemental Nutrition Assistance Program 

(SNAP). 

I’m here today to provide you with our association’s firsthand experiences operating the SNAP Work Experience Program that serves only work-mandated unemployed and underemployed Able-Bodied Adults without Dependents in Franklin 

County, Ohio. The program began in SFY 2014, when the Administration of thenGovernor John Kasich eliminated the statewide waiver and instead applied for a 

limited number of exemptions for only 16 predominantly rural, white counties. The 

Administration did not request exemptions for eligible cities where minority communities are concentrated and unemployment is high. Ohio had a statewide waiver 

that had been in place since mid-2000, when the Ohio General Assembly enacted 

legislation to compel the State of Ohio to apply for and implement the waiver. 

Current Ohio Landscape 

Ohio Counties Waived in FFY 2019 

29 

1Ohio Department of Job and Family Services FAL–171 Federal Fiscal Year 2019: Able-Bodied Adults without Dependents, http://jfs.ohio.gov/ofam/FAL-171-FFY-2019-ABAWD090718.stm. 2 Bureau of Labor Statistics. (2018). Local Area Unemployment Statistics, January 2017–December 2018. 3Supplemental Nutrition Assistance Program: Requirements for Able-Bodied Adults without 

Dependents [RIN 0584–AE57] The Center for Community Solutions, March 26, 2019. 

Adams, Ashtabula, Athens, Belmont, Brown, Carroll, Clinton, Columbiana, 

Coshocton, Crawford, Cuyahoga, Erie, Gallia, Guernsey, Harrison, Highland, 

Hocking, Huron, Jackson, Jefferson, Lawrence, Lorain, Lucas, Mahoning, 

Meigs, Monroe, Morgan, Muskingum, Noble, Ottawa, Perry, Pike, Richland, 

Ross, Scioto, Trumbull, Vinton, and Washington 

In FFY 2019, there are 38 counties in Ohio where the time limit has been waived 

due to high unemployment. Based on unemployment data obtained from the U.S. 

Bureau of Labor Statistics, the 24 month average unemployment rate in each of the 

counties was greater than 120 percent of the national unemployment rate during 

the same 24 month period.1

If the proposed rule were to take effect today with the seven percent threshold 

for waiver eligibility, only three Ohio counties would qualify for a time-limit waiver 

(according to BLS unemployment data over the most recent 24 month period available).2 These three counties—Adams, Meigs, and Monroe—account for less than one 

percent of Ohio’s SNAP population. If the geographic distribution of ABAWDs 

matches that of the broader SNAP population, over 99 percent of Ohio’s ABAWDs 

would now be subject to the SNAP time limit (up from 52 percent under current 

policy). In effect, the rule would add additional barriers blocking Ohioans in the 

poorest parts of the state from accessing basic nutrition.3

Current Policy If Proposed Rule Took Effect Today 

Federal Fiscal Year 2019 Based on Most Recent BLS 24 Month 

(10–1–2018 to 9–30–2019) Average Unemployment Data 

Map by The Center for Community Solutions. 

Sources: U.S. Census Bureau. (2018) American Community Survey 5 year 

estimates, poverty status in the past 12 months. Feeding America. (2018). 

Map the meal gap 2018: overall food insecurity in Ohio by county in 2016. 

Bureau of Labor Statistics. (2018). Local Area Unemployment Statistics, 

January 2017–December 2018. Author’s analysis, assuming waiver eligibility floor of seven percent county unemployment rates. 


11602006.eps
30 

4http://jfs.ohio.gov/ofam/FAL-171-FFY-2019-ABAWD-090718.stm. 

[5] President William Clinton, Statement on Signing the Personal Responsibility and Work Opportunity Reconciliation Act of 1996, August 22, 1996, http://www.presidency.ucsb.edu/ws/ 

?pid=53219. 

Americans want to work. The proposed SNAP able-bodied restrictions will 

hurt many who want to work but can’t for a whole host of reasons—often 

because there are no jobs for them. 

However, living in a county where the time-limit has been waived does not exempt ABAWDs from their obligation to participate in the labor force. Ohio administers a mandatory SNAP Employment and Training (SNAP E&T) program that is 

inclusive of ABAWDs. Under SNAP E&T, ABAWDs must participate in education/ 

job training, job search/job readiness activities, or work experience or else be subject 

to a sanction, regardless of whether the individual lives in a county where the timelimit has been waived.4

Background: How Did We Get Here? 

Under the 1996 welfare law, adults aged 18–49 who are not physically or 

mentally unfit for work or caring for a minor child are eligible to receive Food 

Stamp/Supplemental Nutrition Assistance Program (SNAP) benefits for only 3 

months in a 36 month period, unless the individual meets certain work requirements. These individuals are known as Able Bodied Adults Without Dependents (ABAWD) and are required to work at least 20 hours a week, participate 

in qualifying work or training program activities for at least 20 hours a week, 

or live in an area with high unemployment where the 3 month limit is temporarily waived. 

On the request of a state SNAP agency, the law also gives the USDA the authority to temporarily waive the time limit in areas that have an unemployment rate of over ten percent or a lack of sufficient jobs. The law also provides 

state agencies with a limited number of percentage exemptions that can be 

used by states to extend SNAP eligibility for ABAWDs subject to the time limit. 

The Department proposes to amend the regulatory standards by which the Department evaluates state SNAP agency requests to waive the time limit and to 

end the unlimited carryover of ABAWD percentage exemptions. 

When signing the welfare law in 1996, President Clinton singled out this as 

one of the bill’s most harmful provisions and called for it to be substantially 

changed. 

The Administration’s proposed rule RIN 0584–AE57 would encourage broader 

application of the statutory ABAWD work requirement and is intended to circumvent the will of Congress.[5] 

SNAP Is Essential for Ohio 

The households served by our statewide emergency food assistance network represent diverse circumstances and challenges. Clients face a wide array of obstacles 

to food security, such as health issues, education levels, housing instability, unemployment/underemployment, disabilities, and insufficient income and resources. 

Our association recognizes that hunger is merely a symptom of poverty and we 

engage in other efforts to eradicate poverty and hunger. For more than a decade, 

we have provided services to connect low-income Ohioans with nutrition benefits 

and other work support programs. Knowing first-hand that hunger and health are 

directly linked, the association partners with the Ohio Department of Job and Family Services and the USDA Food and Nutrition Service as the state’s SNAP outreach 

grantee. The association and our member food banks administer and conduct outreach and education on this critical food assistance program. We work on the front 

lines—reaching hungry Ohioans where they work, live, pray, play and learn. 

For more than 25 years, we have advocated for equitable public policy at the state 

and Federal levels to decrease hunger in Ohio. We work with local, regional, and 

national partners to inform policymakers, media, and other stakeholders about the 

issues facing Ohio’s families. 

We know that SNAP is the first line of defense against hunger in our state and 

nation—in fact, our charitable network could never respond to the lack of adequate 

access to nutritious food on our own. In December 2018, Ohio SNAP issuance was 

$165 million, which provided supplemental food assistance benefits to 1.3 million 

31 

6http://jfs.ohio.gov/pams/Case-Load-Summary-Report--December-(002).stm. 

Ohioans living in 660,000 Assistance Groups. These households received an average 

of $124.48 in SNAP benefits per person, per month. Nearly 1⁄2 (43 percent) were 

children.6

To get SNAP benefits, households must meet certain tests, including resource and 

income tests. Benefits are limited to a person with net income at or below 100% FPL 

(monthly net income of no more than $1,041 per month for a household of one and 

$1,409 for a household of two people). The program also has work and work registration requirements for everyone 16 to 60 years of age. 

In October 2013, 1.8 million Ohioans were receiving SNAP to help 

feed their families.i As of December 2018, enrollment had fallen to 1.3 

million, a decline of more than 26 percent.ii

i ‘‘Statement on the November 1st Cuts to the SNAP Program,’’ Food Research and Action Center. http://frac.org/statement-on-the-november-1stcuts-to-the-snap-program/. iiOhio Association of Foodbanks analysis of Ohio Department of Job and 

Family Services Public Assistance Monthly Statistics. http://jfs.ohio.gov/ 

pams/index.stm. 

The Beginning and Approach of Ohio’s Work Experience Program in 

Franklin County, Ohio 

The association was approached in late 2013 by the Franklin County Department 

of Job and Family Services (FC[D]JFS) to assist them in the development of a process to screen and evaluate an estimated 12,000 Franklin County SNAP recipients 

that would be affected by the state’s decision to reimpose the ABAWD work requirement and time limit. 

The goals of this partnership, which began as a pilot program, were multifaceted, 

including not only assisting recipients in meeting the Federal work requirement in 

order to maintain their food assistance, but also providing them with meaningful 

work experience and job training and enhancing their ability to secure sustainable 

employment in order to become economically self-sufficient. To do that we needed 

to understand the barriers and challenges these Ohioans already face. 

The association developed and utilized a Work Experience Assessment Portal to 

conduct in-depth, comprehensive interviews and assessments designed to determine 

employability and identify barriers to employment. The data collected included: age 

and gender demographics, access to reliable transportation, methods of communication and identification, housing and living situations, criminal history, education 

completion, physical and mental health disabilities and limitations, employment history, and dependent and family relationships. These findings provided us with a 

deeper understanding of the issues and challenges participants face and provided 

us a framework for identifying and recruiting the types of community organizations 

that we needed to partner with that could help and host participants in order for 

them to meet the work requirements. 

Our recruitment process for developing new sites involved calling, mailing, e-mailing, and visiting numerous nonprofit and faith-based organizations in Franklin 

County. Each organization is required to sign a Memorandum of Agreement, establishing a strong partnership that also holds these organizations accountable for reporting hours for clients. The Work Experience Program Host sites (WEP) provided 

each participant with a volunteer assignment intended to provide training, education, and on-the-job work experience that would be beneficial in their search for 

future employment. Some sites even report hiring WEP participants at their organizations when they had open positions available. 

Prior to the participants being placed at a WEP host site, they were required to 

attend a three-part clinic to conduct an FBI/BCI background check and meet with 

possible employers and other employment service providers who helped secure identification, develop resumes, and demonstrate job search opportunities. 

After clients complete the assessment and attend the clinic, participants are 

placed at a qualified WEP host site to complete their monthly work requirement 

which allows them to maintain their SNAP benefit eligibility for the duration of 

their participation. 

Our interest in the ABAWD participants did not end when they exit our program. 

We are concerned about the well-being and long-term outcomes of our clients. The 

association conducted a post-WEP client study to examine the course of clients after 

32 

they exited the program. The findings of this report provide information about postparticipation employment status and the most common causes of failure to comply 

with mandated ABAWD work requirements and WEP involvement. 

During the project’s pilot period, from December 10, 2013 through September 1, 

2015, WEP Assessment Specialists completed in-depth interviews with 4,827 

ABAWD participants and gathered information from 5,434 self-reported employability and skills assessments. Over the nearly 2 year pilot, the information obtained represents the most comprehensive and up-to-date information collected 

about this misunderstood population. These findings offer instructive, meaningful 

insight into who these individuals are and what is required in order to help address 

the barriers and challenges they face as they attempt to secure stable employment. 

These findings have provided the association with a framework that continues to 

guide our Work Experience Program partnership with the Franklin County Department of Job and Family Services that is now in its sixth year of operation. 

ABAWD—‘‘Able-Bodied’’—Is a Complete Misnomer for Who This Population 

Really Is 

‘‘Able-bodied’’ indicates that clients are not medically certified and/or documented 

as physically or mentally unfit for employment. As part of the association’s assessment, clients are asked to self-report disabilities or limitations, both physical and 

mental. Our findings identified elevated rates of participants with undiagnosed and 

untreated mental and physical limitations and disabilities. Clients who self-reported 

they were disabled with a physical or mental condition that rendered them unable 

to work required access to a doctor or medical professional who could provide the 

necessary documentation. Other clients were clearly disabled and required more intensive support services to complete an application for SSI or SSDI. 

Nearly one in ten clients requested special accommodations such as work assignments that require no heavy lifting, or no standing/walking for long periods of time. 

One in six clients reported that they had filed for Supplemental Security Income 

(SSI), or Social Security Disability Insurance (SSDI). 

Most Common Types of Physical and Mental Limitations Reported: 

• 18.3 percent—Back Injuries 

• 6.0 percent—Respiratory Difficulties 

• 5.9 percent—Knee Injuries 

• 3 percent—Diabetes 

• 2.8 percent—Shoulder Injuries 

• 2.5 percent—Arthritis 

• 2.3 percent—Heart Conditions 

• 10.1 percent—Depression 


11602007.eps
33 

• 9.3 percent—Bipolar Disorder 

• 8.1 percent—Anxiety 

• 3.1 percent—Post-Traumatic Stress Disorder (PTSD) 

• 1.5 percent—Schizophrenia 

According to the Ohio Department of Health, Adverse Childhood Experiences 

(ACEs) are a critical public health issue. ACEs are potentially traumatic experiences 

and events ranging from abuse and neglect to witnessing violent behavior and living 

with someone who has a problem with alcohol or drugs. Ohio is among five states 

where as many as one in seven children have experienced three or more ACEs— 

a significantly higher ratio than the national average. 

The association’s WEP Assessment Specialist reported when conducting assessments that many participants appeared to be marginally and functionally illiterate, 

and likely experiencing significant learning disabilities. This prompts a deeper examination of social promotion policies that may exist in schools. 

Additionally, while assessing and observing clients, WEP Specialists noted that 

many clients appeared to have social and/or cognitive impairments, difficulty communicating, and a tendency to engage in repetitive behaviors, all signs of autism 

spectrum disorder. Since autism is a more recently identified disorder and has become a well-recognized ailment effecting one out of every 68 kids, it is highly likely 

that the ABAWD population may have high levels of undiagnosed autism, and certainly warrants further exploration. 

Client Story: Mary is a 22 year old part-time college student who is studying 

to earn a Pharmacy Technician degree in hopes of one day becoming a Pharmacist. She is the first in her family to go to college and she has applied for and 

receives student loans that cover the cost of her tuition, books, and housing. She 

also receives SNAP and Medicaid benefits. Mary doesn’t own a car and relies on 

public transportation and catches rides with family and friends or she walks. 

Mary also helps her mother care for younger sisters. Mary works for a large 

drug store chain which is on a bus line near the school she attends. When she 

was hired for the job, the store manager promised Mary she would work between 

20 and 26 hours per week. Mary adjusted her class schedule to accommodate her 

work schedule, but unfortunately when the store sales began to lag behind projections, Mary’s hours were cut in half, causing her to lose her SNAP benefits 

and leaving her with no way to feed herself. She has been pleading with the 

store manager to schedule her for additional hours, as this is a 24 hour/7 day a 

week store. Mary was told that she would need to be on call, but there are no 

guarantees that she will be called into work. The loss of SNAP benefits now 

threaten Mary’s dreams and hopes and she is considering dropping out of school 

if she can’t secure additional hours and regain her SNAP benefits. 

Employment 

There is limited employer demand for the ‘‘hardest to employ’’ groups, such as 

those with criminal records, lengthy periods of unemployment, or other barriers to 

works. 

Working 20 or more hours of paid employment per week, every week, qualifies 

an ABAWD to receive SNAP. Unfortunately, many clients were unable to identify 

how many hours they work per week because they are employed through a temporary employment agency (including day labor and labor pool agencies), which 

means clients may not have consistent work on a weekly basis. 

11.3% Currently working 

8.3% Working in-kind for rent or housing 

24% Dismissed or fired from a job 

While some have described this population as ‘‘takers’’—our research found that 

nearly eight in ten ABAWD clients have never been eligible for unemployment 

compensation benefits. 

Education 

While the unemployment rate in Ohio is declining, clients in this population may 

not meet the educational standards for the jobs becoming available. Analyzing the 

34 

statistics collected on education, we find how limited the prospects are for clients 

to enter the workforce in a position that will pay a sustainable living wage. 

Thirty percent of clients have no high school diploma or GED. 

Although 69.2 percent of clients have graduated from high school or have earned 

a GED, only 38.1 percent have attended college. 

A very small portion of clients (11 percent) who have attended college went on 

to earn a degree. 

More than one million adults in Ohio do not have high school diplomas. 

Ohio’s Adult Basic Education Programs only have the capacity to serve approximately 7,000 Ohioans each year. 

1 https://obm.ohio.gov/Budget/operating/doc/fy-20-21/BlueBook_BookOne_ 

BudgetRecommendations_FY20-21.pdf. 

Transportation 

Clients are supposed to receive a monthly travel stipend from their FCDJFS caseworker. Many clients report that they have not received the stipend. This could be 

due to an inaccurate mailing address, the inability to contact their caseworker, or 

a delay in dispersing of funds. Some clients report that the travel stipend is not 

enough to cover travel to and from work sites. Some clients do not have bank accounts and have to pay a service fee to cash the check they receive from FCDJFS, 

leaving an insufficient amount to purchase a monthly bus pass which the stipend 

should cover. 

Suspended Driver’s Licenses 

In 2017, 1.1 million Ohioans had a suspended driver’s license—nearly 12 percent of those old enough to drive in the state. Some suspensions have nothing 

to do with driving. If you don’t pay your child support, you can lose your license. You can also lose it for dropping out of high school or getting caught 

smoking as a juvenile. It can be suspended if you miss a court date or fail to 

pay court fines on misdemeanor charges. 

https://www.daytondailynews.com/news/state--regional/ohio-fee-amnestyfor-suspended-drivers-has-started-but-only-lasts-six-months/5qQck20Vl2e3Mm 

EFRI1NTM/ 

Just 57 percent of clients report they have reliable access to transportation. This can be a personal vehicle, public transit, or utilizing friends and family 

members for transportation. 

Only 40 percent of clients have a valid driver’s license, which indicates that 

clients are either using public transportation or are driving without a license. Some 

clients may not be able to obtain a driver’s license if they owe child support and 

have had their driving privileges suspended, or if they have outstanding tickets or 

unpaid fines which they may be unable to resolve with their limited income. 

Fewer than one in five clients report having car insurance, inferring that 

some are driving without insurance which can be attributed to a variety of factors, 

including affordability. 

One in four clients do not live near a bus stop or bus line. 

About 15 percent of clients report they have been documented as Driving Under 

the Influence (DUI) or Operating a Vehicle Impaired (OVI). Having a DUI/OVI on 

an individual’s driving record can affect their ability to obtain employment or housing, result in higher car insurance which they may be unable to afford, and/or lead 

to loss of driving privileges. 

Criminal History 

As part of the assessment, clients are asked to complete an FBI/BCI background 

check. An overwhelming 96 percent of clients agreed to comply with this request. 

Clients who declined a background check do not qualify to participate in WEP with 

the Ohio Association of Foodbanks. 

Long-term impact of encounters with criminal justice system 

35 

People with criminal justice (CJ) system involvement are more likely than 

the general population to face poverty, homelessness, unemployment, and poor 

health conditions, even before arrest. For example, people returning to their 

communities after incarceration are three to six times more likely to be diagnosed with a mental illness and about 50 percent experience chronic health 

conditions such as asthma and hepatitis. 

http://www.georgetownpoverty.org/wp-content/uploads/2019/02/Unworkable-Unwise-20190201.pdf. 

Domestic violence can happen in any household regardless of socioeconomic status, race, age, or any other demographically defining factor. Studies show that domestic violence is three times as likely to occur when couples are experiencing financial strain. 11.2 percent of clients reported having domestic violence charges. 

A history of criminal activity or previous incarceration can have a tremendously 

negative impact on someone. They miss out on many opportunities, job related or 

otherwise. The stigma of a felony conviction can follow someone for a lifetime, even 

if their release is meant to suggest that they have been rehabilitated. 

Client Story: At 15 years old, David was sentenced to 15 years in prison. 

Now, at 30 he has been released and was eager to start his life over. He was 

nervous during the assessment, but the WEP Specialist was able to get him to 

relax as he told his story. Later, he called our office to thank the Specialist for 

being so kind and understanding during the assessment and for also believing 

in him. He was thrilled to tell her that he learned to drive and is now enrolled 

at Columbus State Community College. 

35.8 percent of the clients in our program have felony convictions; some clients 

have multiple felonies, or a combination of felonies and misdemeanors. 

12.8 percent of clients are on probation or parole which means they may not 

qualify for services offered through legal aid, such as record sealing. 

A recent report from the Kirwan Institute found that one in four people incarcerated in the State of Ohio were between the ages 18 to 24. The incarcerated population from the 18 to 24 age group in Ohio has grown nearly 70 percent in recent 

years. Prison intake data from Franklin County indicate that the median age of first 

arrest for those entering the state correctional system in 2012 was 19 years old. 

Other Issues Facing the ABAWD Population 

Youth Aging Out of the Foster Care system 

5 percent of the clients had aged out of the foster care system and reported 

they were living with friends, in homeless shelters, or on the street. 

Homelessness and Housing 

Clients experiencing homelessness, health problems, language barriers and a 

lack of stable employment to fit their skill set make up nearly 12.7 percent of 

clients who reported other barriers standing in the way of employment. 

Non-Custodial Parents and Caregivers 

According to the USDA definition of an ABAWD, it is assumed that all clients do not have dependents. We found that clients with children, although not 

in their custody, still spend time parenting their children on a regular basis 

while the custodial parent works. 

One in four clients (23.5 percent) indicated that they had children not in 

their custody. 

Nearly one in five clients (18 percent) indicated that they owe child support. 

An under-employed or unemployed noncustodial parent who loses SNAP may 

need to divert his or her income from child support payments in order to stay 

afloat financially. This would be devastating given that child support represents more than 1⁄2 of the income of the families in poverty who receive it. 

36 

Having the status of caregiver to a relative should potentially exempt an individual from the work requirement. Caregivers can often replace the services 

of a Medicaid or Medicare home-healthcare provider. Nearly 13 percent of clients indicated that they are caregivers for a parent, friend, or relative. 

Employment & Job Seeking Needs 

Client Story: Dahman speaks only Somali and requires an interpreter or 

translator to fulfill his mandatory work activities and assignment. He has no 

transportation and relies on public transportation. Dahman returned to the JFS 

office attempting to find out about his food assistance benefit. Dahman had a 

large open wound on his arm that is draining, making it impossible for him to 

participate in any form of activity. Unfortunately, his County caseworker had 

not changed his employability plan or there had been an administrative delay in 

updating his care record, causing him to be sanctioned and to lose his SNAP 

benefits. Dahman was sent to a local food pantry to get food until his case could 

be sorted out and a new WEP placement could be located for him. 

Ohio Means Jobs Registration 

In an effort to offer more job seeking resources to clients, they are referred to 

Ohio Means Jobs (www.ohiomeansjobs.com). When asked if clients were already registered with Ohio Means Jobs 74.1 percent reported they were not registered, and 

most clients reported they have never heard of the website. 

Additional Barriers 

To ensure a client is able to perform the duties assigned to them, we inquire 

about any supportive services they may need to successfully complete their work assignment. Over 15.7 percent of clients report needing supportive services. The most 

common services requested were language interpretation (especially for Somalian 

refugees) and help with transportation. 

Churn Rates Are High 

When a client is no longer a participant in WEP due to a sanction, they may need 

to apply for a state hearing to overturn their sanction. Nearly 66 percent of clients 

reported taking this step to overturn their sanction, or reapplied for food assistance 

in another way after exiting WEP. It is estimated that there is a 3 month churn 

window, which is the average amount of time it takes for WEP participants to reenter SNAP after exiting the program. 

The amount of churn generated by the most common causes of noncompliance creates increased work as an average two out of every three participants, including 

those who identified some form of employment, must restart the entire process by 

reapplying through their case worker for SNAP benefits. 


11602008.eps
37 

Food Sourcing Strategies of Clients Who No Longer Received SNAP Benefits 

If a client is not receiving food assistance due to a loss of SNAP benefits, they 

look for food elsewhere. When asked, ‘‘How are you providing food for yourself in 

the absence of food benefits,’’ clients gave multiple answers to the question, reflecting an increased demand on our emergency food network. 

Conclusion 

Based on our experience, we know that harsh and arbitrary time limits are misguided and only increase hunger and hardship. This proposed rule is harsh and unfair. It denies vulnerable people food benefits at a time when they most need it and 

it does not result in increased employment and earnings. By time-limiting food assistance to this group, Federal law clearly intends to shift the burden of providing 

food to these unemployed individuals off of SNAP and onto states, cities, and local 

charities like ours. We can’t meet the demand for emergency food assistance now— 

this rule will make a bad situation far worse. This rule will increase food insecurity 

among populations that are suffering from a lack of services, opportunities, and access to basic human needs. 

These individuals face daunting challenges in finding employment even when general unemployment rates are low. Our findings illustrate why Congress gave states 

the option to waive the time limit in areas where there are insufficient jobs for those 

subject to the rule. Without providing any evidence to the contrary, the rule proposes to limit the ways in which a state can demonstrate a lack of sufficient jobs 

for the individuals subject to the time limit. It does this by eliminating Labor Surplus Areas, low and declining employment-to-population ratios, and seasonal unemployment, and requiring recent unemployment rates to be at least seven percent. 

But the Department fails to explain how it determined that the proposed new standards relate to employment opportunities for those subject to the rule, particularly 

given the significant barriers to employment facing this population that I’ve just 

shared with you. 

Proposed rule undermines existing law 

The proposed rule would: 

• Take food away from 755,000 low-income Americans, cutting food benefits 

by $15 billion over 10 years (based on the Administration’s own estimates). 

• Not result in improvements in health or employment among the affected 

population (based on the Administration’s own estimates). 

• Fuel rates of hunger and poverty by denying vulnerable people nutrition 

assistance at a time when they most need it. 

• Harm the economy, grocery retailers, and agricultural producers by reducing the amount of SNAP dollars available to spur local economic activity. 

• Sidestep Congress, which rejected these changes when it enacted the 2018 

Farm Bill. 

The Department’s commissioned reports as well as other research, including the 

association’s WEP program results, paint a clear picture of individuals in this targeted group who have common characteristics that distinguish the group from other 

unemployed adults. These characteristics—including high poverty rates, health 

issues, and few supports—make finding and keeping employment a unique challenge. The Department simply asserts that the time limit will increase employment 

for this population but does not acknowledge its own research showing that this is 

not the case. While all aspects of the rule strike us as arbitrary, this disconnect between the agency’s basic knowledge of the affected population and the assertions 

about how the proposed policy would increase employment is particularly surprising. 

Additionally, adequate work training slots do not exist even for the ABAWDs already impacted by the work requirements as currently imposed. This rule would 

subject hundreds of thousands of additional people to a requirement to fulfill work 

training if unable to secure paid employment, without acknowledging that availability of work training slots is grossly inadequate. 

In closing, the Department’s proposed rule does not provide the analytical information needed to justify the policy change and to evaluate the proposed rule’s likely 

impacts. Because of the deficiencies in reasoning and analysis, the proposed rule 

fails to answer basic questions related to the impact of the change and the people 

whom the proposed rule would affect, and so does not contain the information and 

38 

7The Center for Community Solutions: Public Comment to the U.S. Department of Agriculture, 

Food & Nutrition Service. 

* Work Experience Program, Ohio Association of Foodbanks, 101 E. Town St. Ste, 540, Columbus, OH 43215, www.ohiofoodbanks.org, 614.221.4336. 

data necessary to fully evaluate the proposed rule or to comment on key aspects on 

the Department’s justification for the rule. 

The proposed rule would increase food insecurity and poverty in Ohio, as 

well as stifle economic activity. By scaling back one of the nation’s most effective 

poverty-reduction programs, the rule would exacerbate hardship and reduce economic activity in areas that are already economically disadvantaged compared to 

the rest of the country. 

The proposed rule undermines states’ ability to respond to economic hardship. By imposing artificial definitions of what it means for an area to ‘‘lack sufficient jobs,’’ the rule would undermine states’ discretion to provide hunger relief in 

economically disadvantaged areas. 

The intent of the proposed rule is not supported by evidence. Though the 

USDA predicts that subjecting more SNAP recipients to work requirements would 

result in higher workforce participation rates, there is a lack of evidence to support 

this theory. In fact, existing evidence suggests that SNAP enrollment improves employment outcomes. 

The proposed rule would have a disparate impact on people of color in 

Ohio. The rule would make it even more unlikely that Ohio counties where people 

of color are concentrated would receive a time limit waiver.7

The Ohio Association of Foodbanks requests that USDA consider each of 

these points and withdraw the proposed rule. 

ATTACHMENT

Franklin County—Work Experience Program * 

Comprehensive Report—Able-Bodied Adults Without Dependents 

Table of Contents 

Executive Summary 

Assessment of ABAWDS in Franklin County 

Age & Gender 

Veteran Status 

Communication 

Criminal History 

Forms of Identification 

Transportation 

Disabilities & Limitations 

Children & Families 

Education 

Employment 

Work Experience Program 

WEP Volunteer Host Sites 

Recommendations 

Host Site Partner Organizations 


11602009.eps
39 

Executive Summary 

For almost 2 years, the Ohio Association of Foodbanks has been assisting ablebodied adults without dependents (ABAWDs) receiving Supplemental Nutrition Assistance Program (SNAP) benefits in Franklin County with meeting the Federal 

work requirement to maintain their food assistance as part of an ongoing partnership with the Franklin County Department of Job and Family Services (FCDJFS). 

The association has been able to grow this Work Experience Program (WEP), offering more services and resources to ABAWDs in need. WEP provides work experience 

and job training for participants who are currently unemployed or underemployed, 

as a means to enhance their ability to secure sustainable employment. 

Prior to assigning a client in a job placement within our network of partner nonprofit and faith-based organizations, the association meets with each ABAWD to 

perform an in-depth assessment. To date, we have assessed close to 5,000 individuals. The data we have collected through these assessments continue to reinforce 

what we have been able to identify as key barriers for many of our clients as they 

seek gainful employment. Our findings indicate that many of our clients struggle 

with accessing reliable transportation, unstable living situations, criminal records, 

education, and both physical and mental health problems. Our deeper understanding of these issues has led us to partner with organizations that can help 

ABAWDs navigate through many of their challenges, giving our clients a better 

chance at improving their lives and supporting themselves. 

The data has prompted many recommendations to FCDJFS including but not limited to: providing additional funding for programs that support WEP participants 

and low-income households; expanding enrollment of nationally certified educational 

programs as well as programs for youth aging out of foster care; and creating an 

employment pipeline into strategic aspects of the job market. 

Assessment of ABAWDS in Franklin County 

When Franklin County Department of Job and Family Services (FCDJFS) caseworkers make the determination that a client receiving SNAP benefits meets the 

criteria to be considered an able-bodied adult without dependents (ABAWD) and is 

required to work under Federal regulations, the client is referred to their local opportunity center to meet with an Ohio Association of Foodbanks Work Experience 

Program (WEP) assessment specialist. Each specialist completes a comprehensive 

interview with each client using a series of questions on the Work Experience Assessment Portal. The assessment is designed to determine employability and identify barriers to employment. 

The assessment process is part of an ongoing contract targeting clients who are 

subject to a strict, 3 month time limit in every 36 month period for SNAP eligibility. 

As we approach the second anniversary of this program, we have closely examined 

the data collected from 4,827 ABAWDs and gathered from 5,434 self-reported employability and skills assessments that took place between December 10, 2013 and 

September 1, 2015. Over the past 2 years the information obtained for this ongoing 

project represents the most comprehensive and up-to-date information collected 

about this misunderstood population. These findings offer instructive, meaningful 

insight into who these individuals are and what will be needed to address the barriers and challenges faced by these individuals as they attempt to secure stable employment. 

40 

Monthly Assessments 

The chart depicts the number of ABAWD assessments performed by association 

staff for each month. Clients coming in for an initial assessment each month appear 

in blue, second time visits in any given month appear in orange, and clients who 

are completing the assessment for the third or more times appear in gray. 

Age & Gender 

Gender & Age Distribution 

From the total population of 4,827 ABAWDs surveyed, 1,880 clients (38.9%) were 

female, and 2,945 clients (61.0%) were male. Two clients preferred to be identified 

as transgender. 

The chart represents a distribution of the ABAWDs based on age and gender. This 

distribution does not include the 507 clients (176 female and 331 male) for which 


11602010.eps 11602011.eps
41 

there was no age listed, nor does it include the 83 clients (31 female and 52 male) 

who were over 50 at the time of the assessment and therefore exempted from the 

program. 

Veteran Status 

Percentage of Clients Reporting Military Service 

Only 156 clients (3.2%) reported that they were veterans. While veterans make 

up a relatively small percentage of all ABAWD clients, they represent a significant 

portion of the male population over the age of 35 as represented in the chart. As 

we encounter veterans, we are able to help them find resources designated to assist 

them with housing, employment, and shelter. 

Communication 

Communication is critical to clients participating in WEP, and maintaining a reliable form of communication with clients has continued to be a challenge as FCDJFS 

and the association communicate with clients primarily by mail. Since we started 

collecting mailing information in April 2014, 65 clients have indicated that they do 

not have a mailing address, while 31 clients provided a mailing address and identified themselves as homeless. Additionally, 152 clients have provided a mailing address that is known to be a homeless shelter, check-in center, or mental health facility. 

• Faith Mission (245 N Grant Ave ) 16 Clients 

• Friends of the Homeless (924 E. Main St.) 21 Clients 

• Open Shelter (61 E. Mound St.) 24 Clients 

• Holy Family Soup Kitchen and Shelter (57 S. Grubb St.) 17 Clients 

• Star House (1621 N. 4th) 4 Clients 

• YWCA (595 Van Buren) 17 Clients 

• YMCA (40 W. Long) 39 Clients 

• Southeast Community Mental Health Center (16 W. Long St.) 10 Clients 

• North Central Mental Health (1301 N. High St.) 4 Clients 

This indicates that at least 248 clients (5.1%) of our ABAWD clients are dealing 

with housing insecurity. These numbers do not capture the homeless clients who 

provide the mailing address of a relative or friend, and do not specifically identify 

that they are homeless. 


11602012.eps
42 

Types of Communication Reported 

Communication Avenues 

• 4,625 clients (95.8%) listed phone numbers 

• 1,800 clients (37.3%) listed e-mail addresses 

• 4,381 clients (90.8%) listed mailing addresses 

• 65 clients (1.3%) reported not having an address 

• 380 clients (7.9%) were assessed before address information was asked 

While 95.8% of clients reported having phone numbers, this does not mean that 

they have continuous access to a phone. Clients using subsidized government provided cell phones often run out of wireless minutes before the end of the month, 

or in many other cases their personal phones have been disconnected, or phone 

numbers are frequently changed due to using prepaid cellular devices. We can only 

assume that if we are unable to contact clients via phone, potential employers are 

also unable to reach them. 

The association always offers clients the opportunity to register for an e-mail address as a viable, dependable alternative to a phone. Because most major employers 

require clients to fill out job applications online, having an e-mail address is critical 

to the application process. We encourage clients to visit their local libraries to check 

their messages, but find that some clients may not have reliable or readily available 

community-based access to the Internet. In this process, we also find that many clients struggle with using technology and computers. 

Additional information gleaned from the 531 repeat ABAWD clients reinforces our findings, and provides insight into other forms of stable communication for this population. This 11% of ABAWD clients who have taken the assessment more than once shows: 

• 47% (253) have changed their phone number between assessments 

• 34% (181) have changed their addresses between assessments 

This transiency can have real consequences for ABAWD clients who are sanctioned (cut off from their benefits) because they did not receive an appointment 

or assignment notice from FCDJFS which required action to avoid a disruption 

in their benefits. 

Client Locations 

While the clients who have reported addresses represent 58 different [ZIP C]odes 

in Franklin County, over 55% of clients come from nine [ZIP C]odes: 


11602013.eps
43 

• 43223: 141 clients (7.0%) 

• 43224: 140 clients (6.9%) 

• 43211: 137 clients (6.8%) 

• 43232: 133 clients (6.6%) 

• 43204: 123 clients (6.1%) 

• 43206: 117 clients (5.8%) 

• 43207: 116 clients (5.7%) 

• 43205: 112 clients (5.5%) 

• 43219: 104 clients (5.1%) 

Criminal History 

As part of the ABAWD assessment, clients are asked if they are willing to complete an FBI/BCI background check. Over 96% of clients agree to comply with this 

request. 

A history of criminal activity or previous incarceration can have an incredibly 

damaging impact. The stigma of a felony conviction can follow someone for a lifetime, even if their release is meant to suggest that they have been rehabilitated. 

These restored citizens miss out on many opportunities, job related or otherwise. 

• Over 35.8% of the clients in our program reported having a felony conviction. 

Some clients have multiple felonies, or a combination of felonies and misdemeanors. 

• Close to 12.8% of clients are on probation or parole which means they may not 

qualify for services offered through legal aid, such as record sealing. 

• 541 clients (11.2%) have indicated that they have domestic violence charges. 

• 709 clients (14.7%) reported having DUI or OVI violation. These types of violations can severely limit a client’s ability to secure employment. 


11602014.eps
44 

Percentage of Clients Reporting Felonies 

Forms of ID 

To apply for jobs, housing, and government benefits, to vote, or to obtain a driver’s 

license, most agencies usually require two forms of Identification (ID). Because the 

association requires all participants to have an FBI and BCI background check to 

be placed at one of our host organizations we offer vouchers for clients to receive 

government issued state IDs when they indicate that they do not already have an 

ID. 

• 4,578 clients (94.8%) have some form of state Identification. 

» 1,963 (40.7%) of clients have indicated that they have a driver’s license. 

» 2,615 have indicated that their primary form of identification is a state ID. 

» 206 clients 4.3% indicated that they did not have any form of state identification. 

• 4,369 clients (90.5%) reported having access to their Social Security card. 

» 370 clients (7.7%) do not have access to their Social Security card. 

• 3,969 clients (82.2%) reported having access to their birth certificate. 

» An additional 752 (15.6%) do not have a birth certificate. 

Forms of ID 


11602015.eps 11602016.eps
45 

Transportation 

To assist with transportation, clients receive a monthly travel stipend from 

FCDJFS in the form of a $62 check. Many clients report that they have not received 

the travel stipend. This could be due to an inaccurate mailing address, the inability 

to contact their caseworker, or a delay in dispersing of funds. Some clients report 

that the travel stipend is not enough to cover travel to and from work sites. Some 

clients do not have bank accounts and have to pay a service fee to cash the check 

they receive from FCDJFS, leaving an insufficient amount to purchase a monthly 

bus pass which the stipend should cover. 

2,749 clients (57.0%) said they have access to reliable transportation, whether it 

is their own vehicle, the COTA bus system, or a ride from friends and family members. It is important to note that the use of a friend or family member’s vehicle may 

not always be reliable. Owning a vehicle may pose its own challenges for low-income 

populations, as the car could break down and the client may not have the means 

to fix it. 

• 40% of clients said they do not have reliable transportation. 

• 3,565 clients (73.9%) indicated that they live near a bus stop. 

• 610 clients (12.6%) indicated that they did not live near a bus stop. 

• Only 40% of clients indicated that they have a valid driver’s license, which indicates that clients are either using public transportation or are driving without 

a license. 

» Some clients may not be able to obtain a driver’s license if they owe child 

support and have had their driving privileges suspended, or if they have outstanding tickets or unpaid fines which they may be unable to resolve with 

their limited income. 

• 904 clients (18.7%) indicated that they did have car insurance. 

» An additional 3,232 clients (67.0%) indicated that they did not have car insurance, inferring that some are driving without insurance which can be attributed to a variety of factors, including affordability. As it is the law to 

maintain car insurance for any vehicles owned, some clients could be making 

the tough choice to pay for utilities, food, or medicine instead of car insurance. 

Disabilities & Limitations 

‘‘Able-bodied’’ indicates that clients should not be medically certified and documented as physically or mentally unfit for employment. As part of the assessment, 

clients are asked to self-report disabilities or limitations, both physical and mental. 

• 598 ABAWD clients (12.4%) have self-reported a disability. Of these clients, 261 

clients (44%) have indicated that they are not able to work and earn $1,010 a 

month, which could make them eligible for disability benefits. 

» 74 clients (12%) indicated that they are able to work and earn $1,010 per 

month. 

Percentage of Clients Reporting Disability 


11602017.eps
46 

• 1 in 3 ABAWD clients (32.5%) have self-reported some type of physical or mental limitation. Of these clients, 25% (392) have indicated that their condition 

limits their ability to perform daily activities. 

• 70.3% (1,102) indicated some type of physical limitation. 

• 30.1% (471) indicated some type of mental limitation. 

Most Common Types of Physical and Mental Limitations Reported: 

• Back Injuries 18.3% • Depression 10.1% 

• Respiratory Difficulties 6.0% • Bipolar Disorder 9.3% 

• Knee Injuries 5.9% • Anxiety 8.1% 

• Diabetes 3% 

• Arthritis 2.5% 

• Post-Traumatic Stress Disorder 

(PTSD) 3.1% 

• Shoulder Injuries 2.8% • Schizophrenia 1.5% 

• Heart Conditions 2.3% 

Additionally, a small percentage of clients reported physical difficulties due to 

crimes of violence. 

• 27 reported physical difficulties as the result of gunshot wounds. 

• 4 clients reported physical difficulties as the result of stab wounds. 

Physical or Mental Limitations 

Social Security and Health Care 

One in five ABAWD clients (18.6%) have reported filing for Supplemental Security Income (SSI) or Social Security Disability Insurance (SSDI). Of these clients, 

most have reported filing in the last 2 years: 

• 82 (9%) reported filing in 2015 

• 333 (37%) reported filing in 2014 

• 155 (17%) reported filing in 2013 

• 114 (13%) applied in 2012 

• 223 (25%) applied in 2011 or earlier 

One in four clients (25.0%) indicated said they were under a doctor’s care, and 

1,347 clients (27.9%) indicated that they were currently on medications. 

Nearly six in ten clients (58.2%) have reported already applying for Medicaid, 

although all clients may be eligible to receive this expanded necessary health coverage due to their low-income status. 1,950 clients (40.4%) said they had not applied 

for Medicaid. As part of our outreach process, we invite health care navigators to 

our monthly WEP events to help clients sign up for health coverage. 


11602018.eps
47 

Children & Families 

According to the USDA definition of an ABAWD, it is assumed that all clients do 

not have dependents. We found that clients with children, although not in their custody, still spend time parenting their children on a regular basis while the custodial 

parent works. 

• 1 in 4 clients (23.5%) indicated that they had children not in their custody. 

• 868 clients (18.0%) indicated that they owe child support. 

• 86 clients (1.8%) indicated that they need childcare. 

Having the status of caregiver to a relative should potentially exempt an individual from participating in WEP. Caregivers can often replace the services of a 

Medicaid or Medicare home-healthcare provider. 618 clients (12.8%) indicated that 

they are caregivers for a parent, friend, or relative. 

Education 

Percentage of Clients Reporting Not Completing HS or GED 

Many of the clients in this population have not earned a degree or certification 

to work in industries that pay more than entry level wages. 

• 3,342 clients (69.2%) report having earned a high school diploma or GED. 

• 1,424 (29.5%) of clients report never having graduated high school. 

Of those students that did not earn a GED or high school diploma: 

• 121 (2.5%) report having attended last in the 12th grade 

• 404 (8.4%) report having attended last in the 11th grade 

• 316 (6.5%) report having attended last in the 10th grade 

• 190 (3.9%) report having attended last in the 9th grade 

• 86 (1.8%) report having left school before high school 

• 5 clients (0.1%) report never having attended school before 

College Education 

Of the students who earned either a high school diploma or GED, an additional 

1,324 (28%) attended college, and an additional 520 (11%) earned some type of degree or certification. 


11602019.eps
48 

Highest Level of Education of ABAWD Clients 

Employment 

Working 20 or more hours of paid employment per week, every week can exempt 

an ABAWD from participating in WEP. 

• 547 clients (11.3%) indicated that they are currently working. 

» 16 clients (2.9%) indicate that they are working less than 10 hours per week 

» 62 clients (11.3%) indicate that they are working 10–20 hours per week 

» 75 clients (13.7%) indicate that they are working 20–30 hours per week 

» 34 clients (6.2%) indicate that they are working 30–40 hours per week 

» 23 clients (4.2%) indicate that they are working over 40 hours a week 

» 337 clients (61.1%) did not indicate how many hours they were working 

At least 91 clients (1.9%) reported that they generally work for temporary employment agencies (including day labor and labor pool agencies). These clients 

may be unable to identify how many hours they work per week due to inconsistent 

scheduling and availability of consistent job assignments. Because of this, clients 

may not be able to regularly fulfill the 20 hour work requirement to qualify for an 

exemption. 

Most Common Employment Industry 

• Warehouse Work (including pick/pack, forklift) 

• Customer Service 

• Food Service (including fast food, restaurants, cooking, and food preparation) 

• Janitorial and Cleaning 

• Construction (including carpentry, masonry, drywall, and electric) 


11602020.eps
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Employment History 

Having gaps in a re ́sume ́ can influence an employer’s decision in the hiring process, which can negatively impact a client’s chances of obtaining employment. Of the 

4,284 clients who reported the time since they were last employed, 1,579 (36.8%) 

reported working last sometime within the current year. An additional 1,216 clients 

(28.4%) reported working last in the previous year, 665 clients (15.5%) reported 

working last within the last 2–3 years, 429 (10.1%) reported working last within 4– 

6 years, 204 (4.8%) reported working last within the last 7–10 years, 109 clients 

(2.5%) reported working last between 11–15 years, 34 clients (0.7%) reported working last within the last 16–20 years, 12 clients (0.3%) reported working last over 

20 years ago, and 36 clients (0.8%) reported having never worked before. 

Year Client was Last Employed 

In-Kind Work 

Just as traditional employment can exempt a client from participating in WEP, 

in-kind work may qualify clients from an exemption as well. 402 clients (8.3%) reported working in-kind for food or housing. 

• 67 clients (16.7%) reported working less than 10 hours per week 

• 84 clients (20.9%) reported working 10 to 19 hours per week 

• 82 clients (20.4%) reporting working 20 to 29 hours per week 

• 21 clients (5.2%) reported working 30 to 39 hours per week 

• 28 clients (7.0%) reported working 40 or more hours per week 

• 120 clients (29.8%) did not report the number of hours they were working per 

week 

Employment Assistance 

The ABAWD assessment screens for additional assistance or equipment clients 

may need to perform tasks at their worksite. 

• 435 clients (9.0%) indicated that they needed special accommodations at 

their worksite in order to do a job. The most commonly requested accommodations were no heavy lifting and no standing or walking for long periods of 

time. 

• 757 clients (15.7%) indicated that they need supportive services to obtain employment. The most commonly requested services were language interpretation (especially for Somalian refugees) and help with transportation. 

Workforce Development 

In an effort to offer more job seeking resources to clients, they are referred to 

Ohio Means Jobs (www.ohiomeansjobs.com). 7 in 10 clients indicated that they were 

not registered to work through Ohio Means Jobs website. This shows that the outreach for the Ohio Means Jobs website has been ineffective in reaching this population. 

We assist clients with creating re ́sume ́s so they are able to take them to career 

fairs and apply for jobs that require re ́sume ́s. 

• 2,594 clients (53.8%) indicated that they did not have a current re ́sume ́. 

• 2,183 clients (45.2%) indicated that they would like help to write or update 

their re ́sume ́. 


11602021.eps
50 

• 2,410 clients (49.9%) indicated that they were not interested in help to write 

or update their re ́sume ́. 

Unemployment Compensation Benefits 

Many job applications ask if applicants have ever been fired or dismissed from 

a previous position. One in four clients (24.0%) reported having been previously 

fired or dismissed from a job. When this question appears on a job application 

it can be a deterrent for employers to hire an applicant. 

We inquire if clients have ever received unemployment compensation benefits, as 

this can qualify them for an exemption in participating in WEP if they are still receiving it. Nearly eight in ten clients (78.3%) reported that they have never received unemployment compensation benefits. 

• 886 clients (18.4%) reported that they are receiving or have received unemployment compensation, ranging in time from 1984 to February 2015. 

Work Experience Program 

Immediate program goals for WEP participants are to actively ensure viable work 

opportunities for ABAWDs in Franklin County to fulfill the work requirement to 

maintain their SNAP benefits and prepare ABAWDs for reentry into the workforce. 

The long-term goals and objectives for WEP participants are focused on decreasing 

unemployment among Franklin County ABAWDs to break systemic cycles of poverty 

and hunger and ensure clients can become economically self-sufficient. 

Consistent Outreach 

During the initial ABAWD assessment at the FCDJFS opportunity centers, clients 

are given information about job openings and job fairs in Franklin County. When 

we find that one of the many barriers the assessment is meant to capture is stifling 

a client in their attempt to secure employment, we refer them to clothing banks, 

resources for homelessness, mental health facilities, educational opportunities, and 

food pantries. 

All new clients are required to attend a WEP employment and resource fair their 

first month in the program. We bring together employers (with assistance from 

FCDJFS Workforce Development and Franklin County Economic Development), 

health care navigators and certified application counselors, Legal Aid Society of Columbus lawyers, workforce development agencies, GED and adult education or vocaVerDate Aug 31 2005 11:16 Jun 14, 2019 Jkt 041481 PO 00000 Frm 00056 Fmt 6633 Sfmt 6621 P:\DOCS\116-02\36188.TXT BRIAN

11602022.eps
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tional training organizations, and many more stakeholders to ensure we are able 

to offer clients a variety of valuable services. 

At this event, clients also receive a required background check for their job placements. They participate in hands-on activities and receive assistance with filling out 

job applications and creating or updating re ́sume ́s, assistance with using computers, 

and referrals to obtain suiting for job interviews. 

WEP Volunteer Host Sites 

Type of Host Sites 

The recruitment process for developing new sites involves calling, mailing, e-mailing, and visiting numerous nonprofit and faith-based organizations in Franklin 

County. Each organization is required to sign a Memorandum of Agreement, establishing a strong partnership that also holds these organizations accountable for reporting hours for clients. 

Each volunteer experience through WEP is intended to give participants training, 

education, or experience that would be beneficial in an ABAWD’s search for future 

employment. Some sites even report hiring WEP workers when they have open positions available. 

A list of possible volunteer roles could include but is not limited to: 

• Janitorial Work 

• Painting 

• Grounds Maintenance & Landscaping 

• Warehouse Positions 

• Office and Clerical Work 

• Manual Labor 

• Customer Service 

• Food Preparation and Service 

‘‘One of our WEP clients began working at the Broad Street Food Pantry 

in October 2014 as part of the Ohio Association of Foodbanks Work Experience Program. From the time she started, she demonstrated excellent work 

ethics—never missing a day, always working hard and making sure that 

customers were served efficiently, the shelves kept full, and the pantry kept 

clean and neat. Last winter when our assistant moved on to another job, our 


11602023.eps
52 

WEP client was one of the first candidates we identified. After a thorough 

search, we hired her for the permanent position.’’ 

KATHY KELLY-LONG, Broad Street Food Pantry Director. 

WEP participants paint a mural at Fusion Bakery and Cafe. 

Placements 

Our network of nonprofits, workforce development partners, and faith-based organizations make it possible for Franklin County ABAWDs to obtain their required 

work hours through volunteer service or job readiness activities, while also offering 

work experience. Placements are made at these organizations after clients have 

completed a background check at the WEP monthly employment and resource fair. 

The Ohio Association of Foodbanks requires clients to have a background check 

to ensure that we are not placing clients in situations that may compromise the integrity of our partners, and to protect their clients and staff in the event of a known 

conflict of interest. Clients are not eligible to be placed at a volunteer host site until 

their FBI/BCI background check is received. 

Through the assessment process we gather an inventory of job skills from each 

clients. We are able to determine what jobs would best suit that client, and strategically place them at sites where we believe they will thrive. We do make accommodations for any client that is already volunteering in the community, and make an attempt to bring their volunteer site on as a host organization so that the client can 

maintain their relationship with that organization. 

AB[A]WD Placement Compliance 

At times, it can be very difficult to place clients at a volunteer site. If the host 

location is not on the bus line or if it is not easily accessible by public transportation, clients can have a hard time getting to their placement. Some host sites even 

require a college education or degree, which many of our clients do not have. Some 

sites have a list of restricted felonies which would limit a large portion of our clients 

from volunteering with those sites. The same is true for workforce development programs. Many clients do not meet the minimum education requirements to enroll in 

such programs, or struggle with passing an entrance exam. 

The Ohio Association of Foodbanks placement specialist makes every effort to 

place all clients, no matter how limiting their personal situations may be. Even with 

the best effort to make sure that a client’s skills match the site’s needs, and that 

the location is less than an hour bus ride from their address, not all clients report 

to their assigned placements each month. In order for a client to remain compliant 

with WEP they must report to their worksite for 23 hours per month. When a client 

fails their work requirement hours they are sanctioned and at risk of losing their 

monthly SNAP benefits. 


11602024.eps
53 

ABAWD Placement Compliance 

Recommendations 

As we bring light to the situations this population faces, we are able to make the 

following insightful recommendations which are supported by the findings of the 

WEP assessment data. These recommendations have been presented to FCDJFS 

after the first analysis of this information. They are meant to encourage other government organizations to consider a further examination of the implication of programs like WEP. 

Program Next Steps 

The specific program needs of the Ohio Association of Foodbanks will enhance the 

overall client experience while strengthening relationships with our partners. 

• Coordinate with other Departments of Job and Family Services statewide in an 

effort to replicate the positive results we have seen in Franklin County, to expand this program to other metro and rural areas. 

• Increase the efficiency of our program in order to enhance client satisfaction 

and success while working with very limited resources. 

• Coordinate with Franklin County to offer more opportunities for clients to connect with available employment and training. 

• Improve quality assurance measures and outcomes as well as communication 

channels between the Ohio Association of Foodbanks, clients, host sites, and 

Franklin County Department of Job and Family Services. 

Increase Oversight To Improve Effectiveness 

• Analyze the expenditures of Workforce Development Programs funded by 

FCDJFS compared to outcomes. WEP at the Ohio Association of Foodbanks has 

proven a 24% success rate, compared to a 16% success rate of similar government funded workforce programs in Franklin County. 

Provide Additional Funding to Organizations Supporting WEP 

• When clients fail a WEP assignment and do not have access to their food stamp 

benefits, they may begin utilizing the services of their local emergency food programs. This warrants more emergency funding to be provided to Mid-Ohio 

Foodbank to support the purchase, acquisition, and distribution of additional 

food for Franklin County food pantries, soup kitchens, shelters, and churches 

who are feeding the individuals affected. 

• Ut[il]ize banked months of exemptions (estimated at 405,000) to re-enroll participants in the food assistance program while Departments of Job and Family 

Services work to establish additional work experience program infrastructure. 

• Provide additional funding to the Ohio Association of Foodbanks to support the 

cost of emergency vouchers for transportation, travel vouchers, and basic needs. 

• To increase interest in becoming a part of the host site network, there needs 

to be more incentive for organizations to serve ABAWDs through WEP. By ofVerDate Aug 31 2005 11:16 Jun 14, 2019 Jkt 041481 PO 00000 Frm 00059 Fmt 6633 Sfmt 6621 P:\DOCS\116-02\36188.TXT BRIAN

11602025.eps
54 

fering operating support to the nonprofit and faith-based organizations that are 

providing WEP services and slots, we can motivate more sites to partner with 

the Ohio Association of Foodbanks, while current sites may be able to effectively 

increase their capacity to serve more ABAWDs. 

• Provide supplemental support for the continuation, expansion, and analysis of 

workforce development programs operated by the Ohio Association of 

Foodbanks for young adults aging out of the foster care system. All youth who 

successfully complete these programs either enroll in school or start working, 

which in many cases exempts them from partic[i]pating in WEP as ABAWDs. 

• Improve the funding and training of a specialized unit dedicated to the implementation of this work requirement and the ABAWD population’s specific 

needs. 

Study the Social and Economic Impact of WEP 

• Monitor and report on the impacts to well-being, health, and safety of clients, 

WEP host site staff/volunteers, and the community at large. 

• Conduct an Economic Impact Analysis on the loss of food assistance/SNAP benefit issuance on the Franklin County economy. 

• Provide funding for comprehensive case-management, longitudinal tracking of 

employment, wages, public assistance participation, and well-being of the 

ABAWD population. 

Provide More Work Support Opportunities for ABAWDs 

• Expand enrollment, participation, and successful completion of nationally certified programs such as the FastPath program at Columbus State Community 

College, including ServSafe, customer service, advanced logistics, and STNA. 

• Create an employment enterprise or pipeline into strategic aspects of the job 

market. This will help harder-to-employ individuals find opportunities to gain 

sustainable employment. 

• Prioritize Workforce Investment Act funding to provide education, training, and 

supportive services to ensure a seamless delivery of services. 

• Establish a relationship with the Ohio Department of Rehabilitation and Correction in order to address the specific concerns of the employer community in 

regard to the future employment of felons. 

• Examine opportunities to secure additional USDA/SNAP Employment and 

Training funds to enhance service delivery. 

Examine and Evaluate the Needs of Special Populations 

• Provide support and funding for a study on the mental and physical health status and outcomes of the ABAWD population and their utilization of Medicaid. 

• Fund person-centered, community-based case management of ABAWDs applying for SSI/SSDI, and supportive services including Legal Aid assistance to noncustodial parents and individuals with criminal charges and felony convictions. 

• Convene a study group to examine the impact of temporary and day labor employment services and its effects on this population. 

• The Ohio Association of Foodbanks will continue to analyze assessments and 

data including current and previous encounters with the criminal justice system, community impact, and these associated costs. 

Host Site Partner Organizations 

Without the support of our wonderful network of nonprofit and faith-based organizations we could not offer so many meaningful volunteer opportunities to ABAWDs 

in Franklin County. We extend our sincere gratitude to each organization for their 

continued partnership and dedication to serving the community. 

Agora Ministries J. Ashburn, Jr. Youth Center 

Authority of the Believers King Arts Complex MLK 

Beatty Recreation Center Kingdom Alive Word Church 

Brice UMC Libraries for Liberia Foundation 

Bridge Community Center Long Lasting Community Development 

Broad Street Food Pantry Loving Hands Learning Center 

Broad Street UMC Lutheran Social Services Ohio Benefit Bank—South 

Calhoun Memorial Temple Lutheran Social Services Ohio Benefit Bank—West 

Cat Welfare Association Magic Johnson Bridgescape Academy—New Beginnings 

Catique Mock Rd University for Children 

Center for Family Safety National Parkinson Foundation Central & Southeast OH 

Chalmers P. Wylie VA Ambulatory Care Center New Salem Baptist Church and Community Development 

Charitable Pharmacy of Central Ohio, Inc. NNEMAP, Inc. 

Child Development Council of Franklin County Ohio Association of Foodbanks 

Christ Harvest Church Ohio Business Development Center 

55 

City of Whitehall Ohio Empowerment Coalition 

Clintonville Beechwold Pri-Value Foundation 

Colony Cats (& dogs) Project Redeem 

Columbus Arts Technology Academy R.F. Hairston Early Learning Center 

Columbus Chosen Generation Ministries Reeb-Hossack Community Baptist Church 

Columbus Growing Collective Seven Baskets Community Development Corp 

Columbus Humanities Arts & Technology Academy Shiloh Christian Center 

Columbus Urban League Short North Stage at The Garden Theater 

Community Kitchen, Inc. Society Of St. Vincent De Paul 

Core Resource Center, Inc. Soldiers of Life Food Pantry 

East Columbus Development Company Somali Bantu Youth Community of Ohio 

EL Hardy Center Southeast Friends of the Homeless 

Family Missionary Baptist Church Southeast, Inc. 

Franklinton Gardens St. Dominic Roman Catholic Church 

Genesis of Good Samaritans Ministries St. Marks United Methodist Church 

Glory Praise & Help Center St. Philip Episcopal Church Food Pantry 

Greater Ebenezer Cathedral of Praise and Kingdom Kids Daycare St. Stephens Community House 

Habitat for Humanity’s ReStore Stoddart Avenue Community Garden 

Hands On Central Ohio Temple Israel 

Heart Food Pantry Trinity Assembly 

Heart of Christ Community Church United House of Prayer 

Helping Hands Health And Wellness Center, Inc. Unity of Columbus 

Holy Family Soup Kitchen Welcome Home Ohio 

House of Refuge for All People Wesley Church of Hope UMC 

HUB Community Development Corporation 

The CHAIR. Thank you very much. Dr. Shambaugh. 

STATEMENT OF JAY C. SHAMBAUGH, PH.D., DIRECTOR, THE 

HAMILTON PROJECT, AND SENIOR FELLOW, ECONOMIC 

STUDIES, BROOKINGS INSTITUTION; PROFESSOR OF 

ECONOMICS, GEORGE WASHINGTON UNIVERSITY, 

WASHINGTON, D.C. 

Dr. SHAMBAUGH. Chair Fudge, Ranking Member Johnson, and 

Members of the Subcommittee, thank you for inviting me to join in 

this important discussion. My name is Jay Shambaugh. I serve as 

the director of The Hamilton Project, the Senior Fellow of Economic 

Studies at the Brookings Institution, and as a professor of economics at George Washington University. I am here to provide evidence 

regarding SNAP, a program that lifts millions of Americans out of 

poverty, reduces food insecurity, improves economic security, and 

acts as a crucial fiscal automatic stabilizer. 

Research shows that SNAP is a highly effective program. It also 

shows that work requirements keep people out of the SNAP Program, but have little or no impact on work. The proposed rule 

takes a number of steps to reduce the flexibility of states in using 

waivers or exemptions from work requirements. The proposed rule 

and its impact analysis are correct, that the changes will reduce 

SNAP participation, but provide literally zero evidence that the 

changes would increase employment. 

Agencies may change regulations when there is compelling public 

need and when benefits outweigh costs. In my remaining time, I 

would like to highlight three areas where the proposed rule fails 

to meet this standard. 

First, in theory, work requirements are in place to motivate 

those who do not want to work to do so. But very few ABAWDs 

on SNAP, 1.4 percent, are ‘‘not interested’’ in working. The vast 

majority are, in fact, in the labor force. However, their labor market experience, as is true for many low paid workers, is highly unstable as participants tend to cycle in and out of full-time employment. 

In the research I have conducted with my Brookings colleague, 

Lauren Bauer, which has been provided to the Committee, we find 

that 75 percent of ABAWDs over 2 years are labor force participants. Over 1⁄3 of those in the labor force would satisfy the work 

56 

requirements at some points in time, but not at other points in 

time over that 2 year window, almost as many would consistently 

satisfy the work requirement. 

Of those who generally work but sometimes do not, the majority 

are not working due to ‘‘work related reasons.’’ That is, they lost 

a job or couldn’t get enough hours in a given month to satisfy the 

work requirement. We also find that the title ‘‘able-bodied’’ is a 

misnomer for some of this group, as 80 percent of ABAWDs who 

were not in the labor force at all over the 2 year window list health 

and disability as the reason they are not working. These are people 

who should be eligible for exemptions but could fail to receive 

them. 

Based on the characteristics of the targeted population, the Federal Government should not be impeding states’ ability to apply for 

waivers from work requirements in areas where there is evidence 

of a lack of sufficient jobs or limiting states’ ability to use exemptions to address individual cases. 

Second, the proposed rule fails to consider the effect of the proposed changes in the face of a deteriorating economy. Consider that 

when the economy was shedding 300,000 jobs a month in 2008, 

states successfully applied for waivers to work requirements statewide or for distressed regions using geographies and indicators that 

USDA would deem invalid under the proposed rule. Our analysis 

provided to the Committee demonstrates that the rule would have 

reduced waiver eligibility early in the Great Recession. 

In 2008, the State of Ohio was granted a work requirement waiver for the entire state for 2 years. By the proposed rule, Ohio could 

not apply for the statewide waiver, the 20 percent rule they used 

would be compromised by an excessively high unemployment rate 

floor, and the extended time period granted would be denied. Our 

submitted analysis shows the proposed rule takes a waiver system 

that is already too slow to respond to an economic downturn and 

makes it worse. 

Last, the goal of the proposed rule is to incentivize work, but the 

consequences of the rule is to, in fact, incentivize ABAWDs to reside in distressed economies if they want to avoid time limits. Work 

requirements are applied to places of residence. Individuals wanting to move to places with a stronger economy would risk their food 

resources because they would suddenly face work requirements. 

Reducing the statewide or geographic grouping waivers could lower 

labor mobility. 

In conclusion, the evidence recommends against expanding work 

requirements, whether through restricting states’ ability to apply 

for waivers or extending exposure to sanction to parents or older 

Americans. There are better ways to encourage work within the 

SNAP Program, such as adjusting the earnings disregard, expanding wrap-around services, and improving training and placement. 

There are also better ways to improve waiver eligibility, such as 

automatically granting waivers in the event Congress authorizes 

emergency unemployment compensation. These reforms would 

strengthen and support SNAP as well as the economy. 

I am also happy to take any questions. 

[The prepared statement of Dr. Shambaugh follows:] 

57 

PREPARED STATEMENT OF JAY C. SHAMBAUGH, PH.D., DIRECTOR, THE HAMILTON

PROJECT, AND SENIOR FELLOW, ECONOMIC STUDIES, BROOKINGS INSTITUTION; 

PROFESSOR OF ECONOMICS, GEORGE WASHINGTON UNIVERSITY, WASHINGTON, D.C. 

Chair Fudge, Ranking Member Johnson, and Members of the Committee: 

Thank you for inviting me to join this important discussion regarding the U.S. Department of Agriculture’s Proposed Rule: SNAP Requirements for Able-Bodied 

Adults Without Dependents. 

My name is Jay Shambaugh, and I serve as the Director of The Hamilton Project 

and as a Senior Fellow in Economic Studies at the Brookings Institution and a Professor of Economics at George Washington University. I am here to provide evidence 

regarding SNAP, a program that lifts millions of Americans out of poverty, reduces 

food insecurity, improves economic security, and acts as a crucial fiscal automatic 

stabilizer. 

Research shows that SNAP is a highly effective program. It also shows that work 

requirements keep people out of the SNAP program but have little or no impact on 

work. The proposed rule takes a number of steps to reduce the flexibility of states 

in using waivers or exemptions from work requirements. The USDA’s Notice of Proposed Rulemaking and its Regulatory Impact Analysis are correct that the changes 

will reduce SNAP participation, but provide no evidence that the changes would increase employment. 

Agencies, such as USDA, may issue regulations when there is a compelling public 

need and when the benefits outweigh the costs. In my remaining time, I would like 

to highlight three areas where the proposed rule fails to meet this standard. 

(1) The proposed rule ignores the reality of the population that receives SNAP 

and the volatility they face within the labor market. 

In theory, work requirements are in place to motivate those who do not want to 

work to do so. But very few ABAWDs on SNAP, 1.4 percent, are ‘‘not interested in 

working.’’ The vast majority are in the labor force. However, the labor market experience of SNAP participants—as it is for many low-paid workers—is highly unstable, 

and participants tend to cycle in and out of full-time employment. 

In research that I have conducted with my Brookings colleague Lauren Bauer, 

which has been provided to the Committee, we find that 75 percent of ABAWDs are 

labor force participants. Over 1⁄3 of those in the labor force would satisfy the work 

requirements at some points but not at others over a 2 year window, almost as 

many as would consistently satisfy them. Of those who generally work but sometimes do not, the majority don’t work due to ‘‘work related reasons.’’ That is, they 

lost a job or couldn’t get enough hours. We also find that the title ‘‘Able-bodied’’ is 

a misnomer given that 80 percent of ABAWDs who were not in the labor force said 

it was due to health and disability; these are people who should be eligible for exemptions but could fail to receive them. 

Based on the characteristics of the targeted population, the Federal Government 

should not be impeding states’ ability to apply for waivers from work requirements 

in areas where there is evidence of a lack of sufficient jobs or limiting states’ ability 

to use exemptions to address individual cases. 

(2) The proposed rule fails to consider the effect of proposed changes in the face 

of a deteriorating economy. 

USDA’s proposed rule and Regulatory Impact Analysis also fail to weigh the detrimental effect of their proposal during economic downturns. Consider that when the 

economy was shedding 300,000 jobs a month in 2008, states successfully applied for 

waivers to work requirements state-wide or for distressed regions using geographies 

and indicators that the USDA would deem invalid under the proposed rule. Our 

analysis shows the rule would have reduced waiver eligibility early in the Great Recession. 

For example, in 2008, the State of Ohio was granted a work requirement waiver 

for the entire state for 2 years. By the proposed rule, Ohio could not apply for a 

statewide waiver, the 20 percent rule they used would be compromised by an excessively high unemployment rate floor, and the extended time period granted based 

on evidence of dire economic conditions would be denied. 

Our submitted analysis shows the proposal takes a waiver system that is already 

too slow to respond to an economic downturn and makes it even worse. 

(3) This proposed rule could reduce labor mobility and trap people in areas with 

less economic opportunity. 

The goal of the proposed rule is to incentivize work, but the consequence of the 

rule is to incentivize ABAWDs to reside in distressed economies if they want to 

58 

avoid time limits. Work requirements are applied to the place of residence. Individuals wanting to move to places with a stronger economy would risk their food resources because they would suddenly face work requirements. Reducing statewide 

or geographic grouping waivers could lower labor mobility. 

In conclusion, the evidence recommends against expanding work requirements, 

whether through restricting states’ ability to apply for waivers or extending exposure to sanction to parents or older Americans. There are better ways to encourage 

work within the SNAP program, such as adjusting the earnings disregard, expanding wrap-around services, and improving training and placement. There are also 

better ways to improve waiver eligibility, such as automatically granting waivers in 

the event that Congress authorizes Emergency Unemployment Compensation. These 

reforms would support and strengthen SNAP as well as the economy. 

ATTACHMENT

Good Afternoon: 

Thank you for inviting me to testify before the Nutrition Subcommittee on the 

topic ‘‘Examining the ABAWD Rule and its Impact on Hunger and Hardship.’’ My 

written testimony is attached. 

For your reference, you will also find recent Hamilton Project research regarding 

this issue that we submit for the record, including: 

Comment on USDA’s Proposed Work Requirement Rules: In response to the 

U.S. Department of Agriculture’s Notice of Proposed Rulemaking, Lauren Bauer, 

Jana Parsons, and Jay Shambaugh analyze the effect of changing eligibility for 

work requirement waivers on coverage over time and describe the characteristics 

and employment statuses of Able-Bodied Adults without Dependents. In this comment, we provide evidence and analysis that the USDA has proposed a rule that 

is arbitrary, that the rule runs counter to the compelling public need for waivers 

to work requirements during economic downturns, and that the rule fails to consider 

much less prove that the benefits to participants and the economy outweigh the 

costs. 

Work Requirements and Safety Net Programs: In this paper, Lauren Bauer, 

Diane Whitmore Schanzenbach, and Jay Shambaugh describe who would be impacted by an expansion of work requirements in SNAP and an introduction of work 

requirements into Medicaid. We find that most SNAP and Medicaid participants 

who would be exposed to work requirements are attached to the labor force, but that 

a substantial share would fail to consistently meet a 20 hours per week threshold. 

Among persistent labor force non-participants, health issues are the predominant 

reason given for not working. There may be some subset of SNAP and Medicaid participants who could work, are not working, and might work if they were threatened 

with the loss of benefits. This paper adds evidence to a growing body of research 

that shows that this group is very small relative to those who would be sanctioned 

under the proposed policies who are already working or are legitimately unable to 

work. 

For more than a decade The Hamilton Project has produced evidence-based policy 

proposals on how to create a growing economy that benefits more Americans. We 

believe this can be accomplished by promoting strong, sustainable, long-term economic growth; recognizing the mutually reinforcing roles of economic security and 

economic growth; and, embracing a role for effective government in making needed 

public investments. 

We welcome the opportunity to share more of our research and policy proposals 

with you. Your staff can contact me at [Redacted] or [Redacted] as well as The 

Hamilton Project’s Managing Director Kriston McIntosh at [Redacted] or [Redacted]. 

Warm regards, 

JAY SHAMBAUGH, 

Director, The Hamilton Project; 

Senior Fellow, the Brookings Institution. 

ATTACHMENT 1

March 28, 2019 

Food and Nutrition Service, U.S. Department of Agriculture 


11602114.eps
59 

7 CFR Part 273 

Docket Number: FNS–2018–0004 

Docket RIN 0584–AE57 

Certification Policy Branch, Program Development Division, 

Food and Nutrition Service, U.S. Department of Agriculture, 

3101 Park Center Drive, 

Alexandria, Virginia 22302 

To whom it may concern: 

We are writing in response to the Department of Agriculture’s notice of proposed 

rulemaking (NPRM) regarding Supplemental Nutrition Assistance Program: Requirements for Able-Bodied Adults with Dependents (Docket ID FNS–2018–0004). 

Given that SNAP is a highly effective automatic stabilizer, proposals that change 

the conditions by which economically distressed places become eligible for work requirement waivers should be held to the highest evidentiary standards. 

This comment summarizes and provides evidence relevant to the rulemaking. The 

USDA’s Proposed Rule does not meet an evidentiary standard and would weaken 

SNAP’s responsiveness to an economic downturn without increasing labor force participation rates. 

Based on the research produced and attached herein, we find no evidence of a 

compelling public need for regulation nor that the benefits outweigh the costs. We 

ask that the USDA review and address each evidentiary point herein, as well from 

the research attached, as part of the notice and comment process. The existing rules 

should be sustained. 

Sincerely, 

LAUREN BAUER, Fellow, Economic Studies, The Brookings Institution; 

JANA PARSONS, Senior Research Assistant, The Hamilton Project; 

JAY SHAMBAUGH, Director, The Hamilton Project; Senior Fellow, Economic Studies, The Brookings 

Institution; Professor, The George Washington University. 

Table of Contents 

I. Introduction 

II. Supplemental Nutrition Assistance Program 

A. SNAP and Incentives to Work 

B. SNAP Effectiveness 

C. Macroeconomic Stabilization 

III. Modeling Waiver Eligibility 

A. Regulatory Impact Analysis 

1. Waiver Take-up 

2. Statewide Waivers and Geographic Areas 

3. 20 Percent Rule 

4. Labor Surplus Areas 

5. Effect on Society and Uncertainties 

B. Analysis Based on Eligibility 

1. Work Requirement Waiver Eligibility during the Great Recession 

2. Modeled Eligibility Versus the Proposed Rule 

3. Eligibility Versus The Proposed Rule 

IV. Employment Status Changes 

V. Conclusion 

VI. References 

VII. Appendix 

I. Introduction 

The goals of safety net programs are to provide insurance protection to those who 

are experiencing poor economic outcomes and to support those who are trying to improve their situation. The Supplemental Nutrition Assistance Program (SNAP, formerly the Food Stamp Program) ensures that eligible participants and families have 

access to food when they have no or low income. SNAP does so by providing participants with resources to raise their food purchasing power and, as a result, improve 

their health and nutrition. SNAP lifts millions out of poverty and supports work 

while reducing food insecurity. Evidence shows that SNAP increases health and economic security among families in the short term as well as economic self-sufficiency 

in the long-term. 

60 

SNAP is designed to expand as unemployment rates rise and household income 

falls, and in fact, caseloads increase as the unemployment does (Ganong and 

Liebman 2018). SNAP, Medicaid, and Unemployment Insurance provide the majority of automatic spending fiscal stabilization during economic downturns (Russek 

and Kowalewski 2015) and SNAP’s responsiveness to downturns has increased over 

time (Bitler and Hoynes 2010). Studies show that when SNAP payments increase 

to a local area in response to an economic downturn, they serve as an effective fiscal 

stimulus to the local area (Blinder and Zandi 2015; Keith-Jennings and Rosenbaum 

2015). 

In accordance with the law, including the recently reauthorized farm bill, Congress authorizes states to manage the work requirement for so-called able-bodied 

adults without dependents (ABAWDs) in accordance with the needs of their state. 

After 1996, certain non-disabled SNAP participants ages 18–49 without dependent 

children are limited to 3 months of benefits out of 36 months if they do not work 

or participate in a training program at least 20 hours per week or participate in 

workfare. States have had the option to impose work requirements on certain beneficiaries since the 1980s. See Rosenbaum (2013) and Bolen, et al. (2018) for a detailed description of SNAP work requirements. States are not required to assign 

these participants or provide slots in training programs, so for many participants, 

this provision functions as a time limit rather than a work requirement. 

Exempt from ABAWD work requirements are those outside the age range, those 

who are medically certified as unfit for employment, those with dependents or who 

reside in a household with a minor, those who are pregnant, and those who are otherwise exempt. States must exempt certain individuals, such as those who are 

‘‘unfit’’ for work, and are permitted to exempt a share of individuals for other reasons. States are permitted to apply to the U.S. Department of Agriculture (USDA) for 

waivers to the time limit provisions for the entire state as well as sub-state geographic areas if their economic conditions meet certain standards. The state must 

be able to provide evidence that the state or a state-determined sub-state area has 

(1) a recent 12 month average unemployment rate over ten percent, (2) a recent 3 

month average unemployment rate over ten percent, (3) a historical seasonal unemployment rate over ten percent, (4) is designated as a Labor Surplus Area (LSA), 

(5) qualifies for Extended Benefits to Unemployment Insurance (EB), (6) has a low 

and declining employment-to-population ratio, (7) has a lack of jobs in declining occupations or industries, (8) is described in an academic study or other publications 

as an area where there is a lack of jobs, (9) has a 24 month average unemployment 

rate 20 percent above the national average for the same period, starting no earlier 

than the start of the LSA designation period for the current fiscal year. 

The intent of the work requirement waivers is to ensure that participants are not 

penalized for not working when it is difficult to find a job. As there is no one way 

to measure job finding difficulty, there are a variety of ways to measure labor market weakness in the current rules. The current waivers can be at the county, regional, or state level. They are both absolute (above certain levels of unemployment) 

and relative (compared to national average) as both may be an important signal to 

a state that economic conditions warrant waiving work requirements. 

The USDA proposes to disallow states from applying for statewide waivers except 

on the basis of the state qualifying for EB (option 5) and from making regional determinations. USDA proposes to maintain options 1 and 5 and eliminate waiver eligibility options 3, 4, 6, 7, and 8 of the preceding paragraph with regard to counties 

or Labor Market Areas (LMAs). It proposed to modify option 2 (an unemployment 

rate of ten percent in a recent 3 month period) to only be used in support of ‘‘an 

exceptional circumstance (p. 983),’’ ‘‘the rapid disintegration of an economically and 

regionally important industry or the prolonged impact of a natural disaster (p. 

985).’’ The USDA proposed to modify option 9 (the so-called ‘‘twenty-percent rule’’) 

such that ‘‘an area must have an average unemployment rate at least 20 percent 

above the national average and at least seven percent for a recent 24 month period 

(p. 984).’’ USDA also requests feedback on using six and ten percent unemployment 

as rate floors. 

The proposed rule also reduces states’ ability to use exemptions for individuals by 

limiting states ability to accumulate those exemptions. The exemptions allow states 

to shield individuals from work requirements if state administrators feel the work 

requirements are inappropriate for that individual, for example due to temporary 

problems with hours, health, caregiving, or other issues that restrict their ability 

to work. 

The USDA proposes new rules that are arbitrary. The USDA and its Regulatory 

Impact Analysis (RIA) fail to fully consider the costs and benefits of the proposed 

rule, including the costs and benefits under alternative economic conditions. 

61 

The proposed rule limits a state’s ability to apply for work requirement waivers 

when its economy is weak or relatively weak compared to the overall national economy. The USDA and the RIA do not consider the benefits to program participation 

for individuals nor SNAP’s role as an automatic stabilizer when weighing proposed 

changes. The rule is likely to push a considerable number of current beneficiaries 

who are either in the labor market or unable to work off the SNAP rolls while failing to expand for newly eligible participants at the onset of a recession. It does so 

absent evidence that labor force attachment among ABAWDs would increase as a 

result of this proposal even in a strong economy and without consideration to the 

costs both for individuals and the economy in any circumstance. 

The analyses reported in this comment show that the proposed rule would weaken 

one of the strongest automatic stabilizers in the fiscal policy toolkit. The analysis 

presented below that fewer counties would be eligible for waivers at the start of a 

recession relative to current rules. Instead of SNAP participation expanding promptly, rapidly, and expansively as the unemployment rate rises, the proposed rule 

would slow eligibility for geographic waivers, and in fact, could cause the program 

to contract. The proposed rule undermines the role that SNAP plays at the onset 

of a recession, during poor economic times, and in mitigating the effects of recessions. While the stated goal is to limit waiver eligibility in a strong economy, the 

proposed rule fails to ensure waivers are available to states in a weak economy. The 

USDA and its RIA have failed to consider this critical issue, much less weigh the 

costs and benefits to these changes. 

The proposed work requirements would make regional waivers more difficult to 

obtain and state-wide waivers difficult to obtain in the absence of EB. By making 

it more difficult for states to apply for a statewide waiver and by limiting state’s 

ability to determine economically-linked areas, USDA reduces the geographic mobility of program participants and ties their benefit receipt to maintained residency in 

an area that, by its own definition, is economically lagging. This seems likely to reduce employment and labor force participation of SNAP program participants as it 

effectively traps them in lagging economic areas. No analysis in the RIA is presented to consider these costs. 

While proposing to eliminate evidentiary standards that are not based on federally-produced data, the USDA proposes eliminating two that are (LSAs and seasonal 

unemployment) and introduce uncertainty into what is currently a standard with 

clear and universal applications (3 month unemployment rate over ten percent.) No 

analysis in the RIA is presented to consider these costs. 

The analyses reported in this comment suggest that the proposed changes to work 

requirement regulations will put at risk access to food assistance for millions who 

are working, trying to work, or face barriers to working. We find the USDA provides 

no evidence that limiting waivers from work requirements makes this population 

more likely to work or more self-sufficient. Our analysis shows that the overwhelming majority of SNAP participants subject to work requirements, ABAWDs, 

are in fact in the labor force; but, most have volatile employment experiences that 

would leave them failing the work requirements from time to time. Our analysis 

also shows that labor force participants experiencing a gap in employment do so for 

work-related reasons outside their control. Furthermore, the vast majority of 

ABAWDs not in the labor force are not in fact able-bodied, but suffer from serious 

health problems or have a disability. By further proscribing the individual waiver 

eligibility pool and the use of exemptions, the proposed rule limits state’s discretion 

to provide food assistance. No analysis in the RIA is presented to consider the work 

experiences and health conditions of ABAWDs, the benefits to them for SNAP program participation, and the costs to them and to society of time limits. 

This comment summarizes and provides evidence relevant to the rulemaking. 

Based on the research produced and attached herein, we find no evidence of a compelling public need for regulation nor that the benefits outweigh the costs. We ask 

that the USDA review and address each evidentiary point herein, as well from the 

research attached, as part of the notice and comment process. The existing rules 

should be sustained. 

II. Supplemental Nutrition Assistance Program 

In this section we review published evidence on SNAP and work requirements. 

A. SNAP and Incentives to Work 

SNAP is the most near universal of means-tested transfer programs in the United 

States. Certain households’ SNAP eligibility is determined by meeting a gross income test whereby all sources of income fall below 130% of the Federal poverty level 

(FPL) for its household size. The net income test requires that a household’s net inVerDate Aug 31 2005 11:16 Jun 14, 2019 Jkt 041481 PO 00000 Frm 00067 Fmt 6633 Sfmt 6621 P:\DOCS\116-02\36188.TXT BRIAN
62 

come, i.e., gross income minus the earnings disregard and other deductions, is below 

100% FPL. 

Subject to meeting the income and asset limits, benefits are allocated to households through the following formula: 

Household SNAP benefit = maximum benefit¥0.3 * net income. 

Households without any net income receive the maximum benefit for their household composition. Those with positive net income see their benefit levels reduced by 

30¢ on the dollar of net income. 

While one might worry that providing income support decreases the incentive to 

work, SNAP currently addresses work disincentives in a variety of ways. SNAP has 

an earnings disregard of 20 percent as part of the net income calculation, meaning 

that the value of the earnings disregard increases as income does and that those 

with earned income receive larger SNAP benefits than those with no earned income 

(Wolkomir and Cai 2018). This means that when a person moves from being a labor 

force non-participant to working while on SNAP, total household resources will increase; as a beneficiary earns more up to the eligibility threshold, total household 

resources continue to increase. The combination of the earnings disregard and a 

gradual phase-out schedule—that states have the option to further extend and 

smooth—ameliorate but do not eliminate work disincentives. 

Work requirements in SNAP are meant to force work-ready individuals to increase their work effort and maintain that work effort every month by threatening 

to withhold and subsequently withholding food assistance if a person is not working 

a set number of hours. In practice, the application of work requirements sanctions 

many groups: those who are unable to work, those who are able to work but who 

do not find work, those who are working but not consistently above an hourly 

threshold, and those who are meeting work or exemption requirements but fail to 

provide proper documentation. 

During the Food Stamp Program’s introduction in the 1960s and 1970s, reductions in employment and hours worked were observed, particularly among femaleheaded households (Hoynes and Schanzenbach 2012). But in general, there is little 

evidence that SNAP receipt itself depresses work effort substantially (Fraker and 

Moffitt 1988; Hoynes and Schanzenbach 2012). Whether work requirements could 

offset the small work disincentive would depend on their targeting and whether 

those who are not working could readily increase their labor supply. In fact, the evidence suggests that work requirements decrease SNAP participation, including at 

times when roll expansion is aligned with automatic stabilization (Ganong and 

Liebman 2018; Harris 2019; Ziliak, Gundersen, and Figlio 2003). Recent analysis 

published as a working paper suggests that SNAP participation by ABAWDs is substantially reduced by work requirements but that increase in work is minimal (Harris, 2019). Even the specifications that find the largest increases in work suggest 

five participants would lose SNAP benefits for every one that becomes employed due 

to work requirements. 

The USDA and RIA provided no evidence that there would be any increase in 

labor supply resulting from a change in what areas would qualify to apply for a 

waiver. Projections for increased labor supply are tied to the 2019 President’s Budget projections for an ever-decreasing national unemployment rate. In fact, because 

there is no evidence that ABAWDs will increase their labor supply in response to 

work requirements, USDA also ‘‘estimated the impacts under an alternate scenario 

that assumes instead that rate of employment remains at 26 percent (p. 26).’’ Failure to prove that labor supply would increase as a result of the proposal in good 

economic times, much less bad, suggests that there is no compelling public need for 

new regulation. 

B. SNAP Effectiveness 

Several studies have found that SNAP reduces the likelihood that a household 

will experience food insecurity or very-low food security (Collins, et al., 2014; 

Kreider, et al., 2012; Mabli, et al., 2013; Nord and Prell 2011; Ratcliffe, McKernan, 

and Zhang 2011; Shaefer and Gutierrez 2013; Schmidt, Shore-Sheppard, Watson 

2016). Moreover, evidence from safety net expansions—such as the temporary benefit increase under the American Recovery and Reinvestment Act of 2009 (ARRA) 

and a pilot program that provided additional benefits to families of children during 

the summer months when school meals were not available—shows reductions in 

rates of food insecurity and very-low food security (Collins, et al., 2013; 

Schanzenbach, Bauer, and Nantz 2016; Smith and Valizadeh 2018). Recent studies 

have shown that SNAP improves health outcomes and households’ financial wellbeing, and even improves the later-life outcomes of individuals who had access to 

63 

the program as children (Almond, Hoynes, and Schanzenbach 2011; Hinrichs 2010; 

Hoynes, Schanzenbach, and Almond 2016; Shaefer and Gutierrez 2013). 

For example, a recent study by Hoynes, Schanzenbach, and Almond (2016) finds 

long-term positive effects from consistently providing access to the Food Stamp Program (now called SNAP) during early life. Taking advantage of the relatively long 

rollout period when the program was originally introduced, the study compares children who lived in different counties within a state and who were born at different 

times to measure the long-term impacts of access to the program. Access to the Food 

Stamp Program at early ages—starting before birth in cases where the mother received food stamps during pregnancy, and continuing through age five—leads to a 

number of positive long-run health and economic outcomes. 

As shown in figure 1, access to the Food Stamp Program over this age range has 

substantial positive impacts on later health, lowering women’s and men’s incidence 

of metabolic syndrome—a health measure that includes diabetes, high blood pressure, obesity, heart disease, and heart attack—by 0.3 and 0.5 standard deviations, 

respectively. Women are also 34 percentage points more likely to report excellent 

or very good health if they had access to food stamps from before birth through age 

5. 

These gains also extend to economic outcomes. Women with access to the Food 

Stamp Program over the full early life period have much higher economic self-sufficiency—a measure that includes completed education, employment status, earnings, 

and financial success—than those who did not. Furthermore, access to food stamps 

increased high school graduation rates by more than 18 percentage points. 

Figure 1. Impact of Access to Food Stamps During Early Life on Adult 

Health and Economic Outcomes 

Source: Hoynes, Schanzenbach, and Almond 2016. 

Note: Hollowed bars are not statistically significant. 

In addition to reducing food insecurity, SNAP participation may also reduce 

households’ risk of suffering financial hardships (Figure 2). Shaefer and Gutierrez 

(2013) use variation in state-level policies that affect SNAP access to study the impact of SNAP participation on a variety of outcomes. They find that receiving SNAP 

reduces the likelihood of food insecurity by 13 percentage points. 

SNAP also has spillover impacts on other aspects of families’ financial well-being. 

Households have more resources available for other essential expenses, such as 

housing, utilities, and medical bills. Shaefer and Gutierrez estimate that SNAP participation reduces the risk of falling behind on rent or mortgage payments by seven 

percentage points and on utility bills (gas, oil, and electricity) by 15 percentage 

points. Participants are also less likely to experience medical hardship: SNAP participation decreases the likelihood of forgoing a necessary visit to a doctor or hospital by nine percentage points. 


11602026.eps
64 

Figure 2. Impact of SNAP Participation on Food Insecurity and Other Financial Hardships 

Source: Shaefer and Gutierrez 2013. 

Note: Sample includes low-income households with children. Medical 

hardship is measured as whether the interviewee reported that in the past 

12 months someone in the household chose not to see a doctor or go to the 

hospital when needed because of cost. 

The USDA and RIA fail to consider the costs and benefits to restricting access 

to SNAP on food security, economic security, and health. While labor force attachment is a path to economic self-sufficiency as the rule states, the evidence shows 

that SNAP benefit receipt also leads to economic self-sufficiency, household budget 

stabilization, and improved health. The rule states that imposing additional work 

requirements ‘‘would also save taxpayers’ money (p. 982)’’ but does not provide an 

analysis that considers the countervailing costs to limiting access to SNAP. The 

USDA and RIA fail to consider the costs to nonparticipation on both individual 

households and, as we will show throughout, the economy as a whole. 

C. Macroeconomic Stabilization 

While the safety net should expand to provide resources to households experiencing firsthand economic losses, governments may use fiscal policy—additional government spending or tax cuts—to stimulate the economy during a recession. A fiscal 

multiplier is an estimate of the increased output caused by a given increase in government spending or reduction in taxes. Any multiplier greater than zero implies 

that additional government spending (or reduced taxes) adds to total output. Fiscal 

multipliers greater than one indicate an increase in private-sector output along with 

an increase in output from government spending. This can occur because the additional spending can turn into increased employment or wages which subsequently 

increase output. 

Although there is disagreement among economists over the exact size of various 

fiscal multipliers (see Auerbach, Gale, and Harris [2010] for a discussion), multipliers are generally believed to be higher during recessions than they are under normal economic conditions when the economy is near its full potential, and they are 

in particular thought to be higher when the central bank is not raising rates in response to economic fluctuations (Auerbach and Gorodnichenko 2012; Fazzari, Morley, and Panovska 2014; see Ramey and Zubairy 2014 for a dissenting view). This 

is likely because downturns are characterized by slack in both labor and capital 

markets (i.e., available resources are not fully employed), thereby allowing fiscal 

stimulus to increase total output. Multipliers are also higher when the spending 

program or tax cut targets lower-income people, who are more likely to spend the 

stimulus (Parker, et al., 2013; Whalen and Reichling 2015). 

Not all spending or tax cuts are created equal, as indicated by the variation in 

fiscal multipliers shown below in Figure 3. But during the depths of the recession, 

each spending multiplier analyzed by Blinder and Zandi (2015) was greater than 

one, indicating that spending on these programs raised output by more than their 

costs. Note that the multipliers reported here are broadly similar to those estimated 

by CBO (Whalen and Reichling 2015). 

As shown in the below figure, the most stimulative type of spending during the 

recession was a temporary increase in the SNAP maximum benefit: for every $1 increase in government spending, total output increased by $1.74. Work-share programs and UI benefit extensions were also relatively stimulative. Consistent with 


11602027.eps
65 

economic theory, the programs with the largest multipliers were those directed at 

low-income or newly unemployed people. More recently, as the economy has improved, the multipliers have diminished. However, the multipliers for SNAP benefits, workshare programs, and UI benefits remain above one, indicating that these 

programs remain highly effective as forms of stimulus, generating additional private-sector economic activity. SNAP multipliers were also estimated to be greater 

than 1 in 2015Q1, well after the recession had ended. 

Figure 3. Fiscal Stimulus Multipliers (Spending Programs), 2009 and 2015 

Source: Blinder and Zandi 2015. 

Poverty and economic hardship typically increase in recessions and decrease in 

economic expansions. In particular, households with few resources are especially affected by the business cycle. Among poor households, the effect of the Great Recession was particularly severe relative to previous recessions. The unemployment rate 

rose notably more for lower education workers. This is a typical feature of recessions: less-educated workers face larger employment losses when the economy turns 

down (see Aaronson, et al., 2019 for a review). The safety net plays an important 

role in mitigating these effects, partly by automatically expanding during economic 

downturns as eligibility for safety net programs increases. 

Over the course of the Great Recession, SNAP rightly expanded to provide more 

benefits to eligible and newly eligible participants, including ABAWDs. Part of this 

expansion was the result of Bush Administration, Congressional, and Obama Administration action at several points over the course of the recession to expand 

waiver eligibility because existing policy was not sufficient to meet economic goals. 

These actions were necessary for macroeconomic stabilization and because the existing rules for ‘‘lack of sufficient jobs evidence’’ in applying for ABAWD work requirement waivers insufficiently responded to economic circumstances. 

The USDA and its RIA fail to model and consider the costs and benefits to the 

proposed rule during any alternate economic conditions. USDA proposes making 

changes to existing policy that would weaken responsiveness to indicators of an economic downturn (statewide waiver; 20 percent rule; 3 month lookback), its persistence (statewide waiver; 3 month lookback), and sluggish recoveries in particular 

places (statewide waiver; 20 percent rule). Our analysis provides evidence that existing policy (20 percent rule without a floor, ten percent rule with two lookback periods) provided coverage more in keeping with the economic conditions at various 

points in time than the proposed changes. Furthermore, the USDA fails to offer proposals, such as linking waiver eligibility to Emergency Unemployment Compensation (EUC) in the event that EUC is authorized, that would make waiver eligibility 

more responsive during the onset of a recession. 

III. Modeling Waiver Eligibility 

A. Regulatory Impact Analysis 

The USDA’s proposed rule makes several changes for which the Regulatory Impact Analysis must account. The USDA proposes to disallow states from applying 


11602028.eps
66 

1 2017 is the last year for which there is publicly available data on waiver take-up by county. 

for statewide waivers except in the case of EB eligibility and to define regions at 

their discretion. The USDA proposed maintaining eligibility for geographic areas 

qualifying for EB and with 12 month unemployment rates above ten percent. USDA 

proposes to modify eligibility for those places with an unemployment rate of ten percent in a recent 3 month period to only be used in support of ‘‘an exceptional circumstance p. 985.’’ USDA proposes to put an unemployment rate floor of seven percent to the 20 percent rule. We provide evidence that the RIA does not properly analyze the effects of these proposed changes, thus substantially underestimating the 

impacts. 

1. Waiver Take-up 

The Regulatory Impact Analysis (RIA) is based on areas that have taken up a 

waiver in a single contemporaneous period. The RIA failed to consider eligibility for 

waivers in its analysis for the single time period it did analyze. The RIA did not 

consider the effect of their proposal under alternative macroeconomic conditions, either in actual take-up or in eligibility. In doing so, it materially underestimates the 

number of program participants who would be subject to time limits during recessions. 

The RIA writes that they chose to model actual waiver take-up rather than eligibility because ‘‘States do not always seek waivers for eligible areas. Some States 

seek no time limit waivers; others only seek waivers for a portion of qualifying areas 

within the State. Therefore, the Department assumed that if a county was not currently waived, the State would not seek a waiver for that area under the revised 

criteria (p. 20).’’ 

This logic is faulty and false by recent evidence. States that have declined to takeup waivers for which they are eligible are assumed to have made a choice that they 

would never make differently—even if economic conditions in their state deteriorated. Similarly, states that have applied for waivers for which they are eligible are 

assumed to be the only places where the impacts of more stringent eligibility would 

be felt in perpetuity. 

By this logic, we could look at waiver status in any preceding year as the expression of a state’s policy preference—preferences that change based on economic conditions. As USDA noted in the RIA, in July 2013, 44 states and D.C. applied for statewide waivers and six states had waivers for part of their state. Had the RIA used 

recently expressed actual preferences for rather than the single time period that 

they considered or modeled the effect based on eligible areas, they would have found 

larger impacts in Federal spending and the number of individuals denied access to 

resources to purchase food. 

In 2017,1 each of the 17 states that did not avail themselves of time limit waivers 

had at least one county that was eligible. This does not mean they would always 

choose to decline to use waivers. In fact, of the 17 states currently eligible for waivers that are not using them, 14 were using waivers to cover counties not individually eligible in 2008 (shown later in figure 8) and every state received waivers for 

at least a part of the state in 2009. The existing waiver process allows states to determine when it makes sense to apply for them based on their understanding of 

their local economy. It is incumbent on the NPRM to explain why limiting that discretion furthers program goals. 

2. Statewide Waivers and Geographic Areas 

The RIA does not consider the effect of eliminating statewide waivers except as 

downstream to other policy changes. It does not model whether a state would ever 

qualify for a waiver based on each underlying geographic unit’s qualification. It does 

not model state eligibility for EB, or in relation to EUC. In doing so, the NPRM 

and RIA fail to justify proposed restrictions on statewide waivers. 

Statewide waivers are particularly critical during serious economic downturns. 

Any heterogeneity in the use of waivers impedes the geographic mobility of program 

participants. Unlike in UI, where individuals retain benefits if they move to a better 

labor market, SNAP ties benefit receipt to their place of residence. In order to maintain benefits, participants are incentivized not to move to find work, but to maintain 

residency in an area that is economically lagging but waiver eligible. This reduces 

employment and labor force participation of SNAP program participants and does 

not increase economic self-sufficiency. USDA does not provide analysis to consider 

these costs. 

The RIA does not consider Labor Market Areas (LMAs) in its analysis, though a 

county can become eligible for a waiver due to being a part of an LMA. It writes, 

‘‘Because a small number of areas estimated to lose eligibility may actually qualify 

67 

as part of a larger LMA, the Department rounded the impact from 77.4% down to 

76 percent (p. 22).’’ There is no justification for this rounding nor for excluding counties eligible as part of an LMA from their analysis. The result is misattribution of 

some counties otherwise eligible to the state-selected geographic group or statewide 

standard and an unspecified effect on policy impacts. Our analyses show that more 

than five percent of counties qualify only through being a part of an LMA. 

The RIA does not include most of New England—Connecticut, Maine, Massachusetts, New Hampshire, and Vermont—in its analysis. Failure to do so both affects 

the validity of the estimates and calls into question whether counties and LMAs are 

an appropriate level of geography as is argued. 

3. 20 Percent Rule 

The Regulatory Impact Analysis failed to correctly model the 20 percent rule. 

They write: ‘‘The Department obtained monthly unemployment and labor force data 

from BLS . . . for the 24 month period from January 2016 to December 2017 for 

3,077 counties and county-equivalents (p. 21).’’ The Department therefore determined that any waived county that was waived but not by the 20 percent rule was 

part of a contiguous state-determined geographic group or through a statewide waiver. 

This is incorrect because the RIA fails to accurately model the 20 percent rule or 

consider other paths to eligibility. The 20 percent rule states that the first month 

of the 24 month period used to identify whether an area’s unemployment rate is 20 

percent above cannot be earlier than the first month BLS uses to determine LSAs. 

The RIA does not say what period it is calculating 20 percent eligibility, but it does 

so using only one 24 month period. Within a window for applications, there are in 

fact ten distinct 24 month periods against which a state can submit a waiver application. 

The RIA states that in linking the 20 percent rule to LSA designations states will 

be prevented ‘‘from using older data (p. 16).’’ This is false. The proposed rule does 

not make any changes with regard to the time period over which data can be taken, 

only that the waiver expiration date would be proscribed. 

The NPRM defends a six percent unemployment rate floor by noting that if there 

is agreement the ‘‘natural rate’’ of unemployment hovers near five percent, then 20 

percent above that would be six percent. But, the Department does not choose a six 

percent floor, instead preferring a seven percent floor (in part because of a concern 

that ‘‘too few individuals would be subject to ABAWD work requirements’’ without 

explaining why the number would be too few.) In addition, the Administration’s 

forecast suggests the unemployment rate will stabilize at 4.2 percent and never rise 

above it this decade. Twenty percent above that rate would be a floor of five percent. 

No attempt to justify a higher floor like seven percent is made beyond noting it will 

subject more people to work requirements. 

4. Labor Surplus Areas 

By failing to provide sufficient evidence for the seven percent floor to the 20 percent rule, the USDA consequently fails to justify removing Department of Labor 

(DOL) designation as a Labor Surplus Area (LSA) as a waiver qualification. Essentially, LSAs are also determined by the 20 percent rule and the ten percent rule, 

but have a floor of six percent unemployment. A city with a population of at least 

25,000, a town or township of at least 25,000, counties, balances of counties, and 

county-equivalents can all qualify as LSAs. Under exceptional circumstances, civil 

jurisdictions, Metropolitan Statistical Areas and Combined Statistical Areas are geographies that could qualify as LSAs. The justifications for removing LSAs run 

counter to stated goals: high-quality and federally-produced data and clear standards for areas with insufficient jobs should determine waiver eligibility. The USDA 

and RIA fail to provide sufficient evidence for removing waiver eligibility based on 

LSA designation. 

5. Effect on Society and Uncertainties 

The RIA acknowledges that it fails to consider actual impacts under any alternative economic conditions, ‘‘(including cyclical (p. 29).’’ They also acknowledge that 

meeting work requirements is a function of both the availability of jobs and the ‘‘extent that States offer qualifying E&T or workfare opportunities (p. 29).’’ 

The RIA acknowledges that ‘‘there may be increases in poverty and food insecurity (p. 28)’’ for those who fail to meet work requirements, ‘‘those ABAWDs who become employed will likely see increased self-sufficiency and an overall improvement 

in their economic well-being (p. 28),’’ and that ‘‘a number of those affected by 

strengthened work requirements are able to secure employment in a wide range of 

different industries (p. 28).’’ 

68 

2To understand maximum eligibility, we look at county eligibility based on the county-level 

data as well as the LMA-level data. Because the LMAs in New England States are made up 

of minor civil divisions and not counties, eligibility in counties in ME, MA, NH, VT, and CT 

is only modeled on county data. 3The Regulatory Impact Analysis conducted by USDA also does not model sub-state groups 

for eligibility optimization. 4We follow the USDA guidance and rounded national and local unemployment rates to the 

nearest tenth. 5The window for a waiver application based on the 20 percent rule is based on Section V of 

the USDA guidance. We assume that states will apply for waivers on the last possible application date, i.e., the end of a fiscal year period as defined in the guidance. The guidance states 

that ‘‘For example, the 24 month period for the Fiscal Year 2017 LSA list runs from January 

1, 2014 through December 31, 2015. Thus, a waiver that would start in Fiscal Year 2017 could 

be supported with a 24 month period beginning any time after (but not before) January 1, 2014.’’ 

Therefore, if a geographic unit has a 24 month average that starts on January 1, 2014 and ends 

on January 1, 2016, the latest they could apply for the waiver would be September 30, 2017. 

The waiver period extends 12 months from the application date. We therefore assume that the 

geographic unit in question is eligible for a waiver from January 1, 2016 through September 

30, 2018. 6We follow USDA guidance with regard to EB-based eligibility. A state is eligible for a work 

requirement waiver based on EB if a state has (1) a 13 Week Insured Unemployment Rate 

(IUR) of five percent and 120 percent of each of the last 2 years; (2) an IUR of six percent; (3) 

a 3 Month Total Unemployment Rate (TUR) of 6.5 percent and 110 percent of either of the last 

2 years. 

The effect of the proposed regulatory changes were inadequately analyzed, failing 

to take into account the costs and benefits of restricting access to the program. The 

RIA does not provide estimates for increases in rates of poverty or food insecurity 

and its attendant costs. In particular, it does not engage with the evidence of the 

long-run benefits of SNAP, the effect of SNAP on reductions in food insecurity and 

poverty, nor with the concerns regarding reducing resources to the children of noncustodial parents. It does not provide evidence for increased labor supply among 

ABAWDs, and in fact the RIA acknowledges elsewhere that employment rates may 

not increase at all as a result of the policy change. ‘‘A number of those affected (p. 

28)’’ is not a specific analysis on which to base a regulatory change. 

Without evidence that any affected program participant would become employed 

as a result of the policy, it remains unclear whether there are any benefits to the 

proposed rules. 

B. Analysis Based on Eligibility 

In this section, we provide evidence for the share of counties that would have been 

eligible for a waiver based on each trigger from 2007 to the present (1) in existing 

regulation, (2) through policy changes throughout the Great Recession, and (3) in 

the proposed rules including for each unemployment rate floor to the twenty-percent 

rule. Modeling eligibility and take-up over time is appropriate for identifying program effects. 

The geographic unit considered in each of the following models are the share of 

counties eligible for a waiver. These counties can gain eligibility individually, as a 

county in a labor market area (LMA) that is eligible, or because the county is in 

a state that has a statewide waiver.2

We are unable to show the share eligible based on state-selected geographic areas 

under current rules.3 We do not model triggers based on the following rules: a historical seasonal unemployment rate above ten percent; Labor Surplus Area designation by the Department of Labor’s Employment and Training Administration; a low 

and declining employment-to-population ration; a lack of jobs in declining occupations or industries; or, is described in an academic study or other publication as an 

area where there is a lack of jobs. 

In our model, a geographic unit can be eligible for a waiver based on three unemployment rate thresholds (in addition to other policy mechanisms discussed below). 

First, a geographic unit is eligible if it has a 24 month average unemployment rate 

that is 20 percent above the national average for the same 24 month period.4 Second, a geographic unit is eligible for a waiver if it has a 12 month average unemployment rate above ten percent. Third, a geographic unit is eligible for a waiver 

if it has a 3 month unemployment rate above ten percent. A state can generally request a 12 month waiver and specify the implementation date on the waiver request.5

If a state qualifies under any of these triggers or if a state’s unemployment insurance extended benefits program triggers on, then the state is eligible for a statewide 

SNAP waiver. In this analysis, we model EB eligibility based on the first date that 

a state is shown to be eligible on a Department of Labor EB trigger notice.6 We also 

model eligibility based on EUC and ARRA. 

69 

7 EUC trigger notices are issued on a weekly basis. Our analysis is on a monthly basis. If a 

state was eligible for EUC in at least 2 weeks in a month, we consider it to be eligible for EUC 

in that month. 

In the following sections, we model waiver eligibility and waiver take-up as a 

share of counties from 2007 to present. 

1. Work Requirement Waiver Eligibility during the Great Recession 

Work requirement waivers in a recession are important for two reasons. First, job 

finding rates fall in recessions and difficulty finding work may mean many individuals who are trying to be labor force participants will be sanctioned for failure to 

work the required number of hours. This is counter to program goals. It is wellknown that recessions strike marginalized populations in the labor force more 

harshly than higher income, higher education individuals. Because during a recession more people become eligible for and would benefit from program participation 

due to recent job or income loss as well as the inability to find sufficient work, it 

is particularly important to waiver time limits for the SNAP-eligible population. 

Second, removing individuals from SNAP during a recession shrinks SNAP’s role as 

an automatic stabilizer by providing spending in depressed areas during a downturn. 

In order to expand access to geographic waivers in response to the recession, executive and Congressional action was necessary. None of the automatic triggers were 

sufficient to turn on the waivers for much of the country promptly. The Bush and 

Obama Administrations, Congress, and states took action throughout the Great Recession to increase geographic eligibility for waivers, directly and through clarifying 

ties to Unemployment Insurance (UI). 

During the Great Recession, Congress enacted Emergency Unemployment Compensation (EUC), a temporary program that extended the amount of time during 

which an eligible UI participant could retain benefits. Congress authorized EUC on 

June 30, 2008, extending the expiration date to January 1, 2014 (American Taxpayer Relief Act of 2012). 

Additionally, the Bush Administration clarified on January 8, 2009 that eligibility 

for Emergency Unemployment Compensation (EUC) also qualified states for SNAP 

waivers.7 EUC established several tiers of additional weeks of UI benefits, with 

each tier contingent on a state having a total unemployment rate that exceeded a 

given threshold. EUC tier qualifications interacted in different ways with SNAP 

Waiver eligibility over the EUC period. Importantly, states were eligible for SNAP 

waivers if they were eligible for particular tiers of EUC, and not just if they took 

EUC (see table 1 for eligibility thresholds and the interaction of SNAP waivers and 

EUC tiers). 

ARRA was enacted on February 17, 2009. It stated that for the remainder of 

FY2009 and through FY2010 ABAWDs were waived from work requirements to 

maintain access to the program. While a few localities declined this authorization, 

every county in the U.S. was eligible for waiver from February 17, 2009 to September 30, 2010. 

Figure 4 models each component of work requirement waiver eligibility that was 

operational from 2006 to present. The unit is the share of counties eligible for a 

waiver, whether individually, as part of an LMA, or as part of an eligible state. The 

set of triggers and eligibility standards are based on standing regulation as well as 

policy changes made over the course of the Great Recession to increase waiver eligibility. The criteria that did not change over the course of the Great Recession were 

eligibility based on EB, the twenty-percent rule, and the ten percent unemployment 

rate by two look-back period rules. 

70 

Figure 4. Counties Eligible for A Work Requirement Waiver by Trigger, 

2007–present 

Source: Local Area Unemployment Statistics, BLS (2000–2018); EB and 

EUC Trigger notices (DOL); Bureau of Labor Statistics (2000–2018). 

The 20 percent rule (light blue) slowly increases the availability of waivers at the 

start of the recession in the absence of Congressional action as some parts of the 

country had its unemployment rate rising before the rest. This analysis shows that 

the vast majority of areas waived from the rules in the third quarter of 2008—a 

period when the economy was losing over 300,000 jobs a month—was due to the 20 

percent rule. Since 2016, the vast majority of counties eligible for an ABAWD waiver is due to qualifying under the 20 percent rule. Still, it is not a perfect trigger. 

If the entire country is facing rising unemployment rates, the waivers would not be 

available anywhere until local 3 month (or 12 month) unemployment rates exceed 

ten percent or EB-based triggers come on under standing rules. This analysis shows 

that the 20 percent rule plays a critical part in SNAP’s role as an automatic stabilizer and should not be weakened. 

Standing policy with regard to statewide waivers would have provided wider coverage in the event that eligibility based on EUC and ARRA did not occur. The Extended Benefit (EB) trigger for UI in-law has failed to trigger on during recessions 

without Congressional and state action since its enactment (Wandner 2018), though 

work requirement waivers are based on eligibility by USDA-determined thresholds 

that ameliorate this issue. For a short period of time in late 2008 and the first week 

of 2009, EB eligibility provided the widest amount of coverage, but its acceleration 

in 2008 was not sufficiently early or fast enough to reduce the value of the 20 percent rule. USDA proposes to maintain EB-based eligibility, and the evidence presented here shows this is a necessary but not sufficient waiver eligibility condition. 

During the Great Recession, Emergency Unemployment Compensation was authorized in June 2008 but it was not until January 2009 that the Bush Administration clarified that states eligible for a particular tier of EUC were also eligible for 

SNAP work requirement waivers. About 90 percent of counties became eligible 

based on this measure, and through ongoing memorandums linking work requirement waiver eligibility to different EUC tiers, a high level of waiver eligibility was 

maintained through 2016. Given that roughly 35 percent of counties were already 

eligible based on the 20 percent rule in 2008, the expansion of waiver eligibility 

based on EUC dramatically expanded waiver eligibility. Had waiver eligibility been 

tied to EUC upon enactment, work requirement waivers would have been an even 

more effective counter-cyclical tool. An improvement to the rules would be to clarify 


11602029.eps
71 

that in the event EUC is authorized, states become immediately eligible for work 

requirement waivers. 

Combining these indicators into three bins—eligibility based on standing policy as 

of 2006, additional eligibility based on EUC, and additional eligibility based on 

ARRA—we can model the effect of existing waiver policy and of the policy preferences of Administrations of both parties and Congress with regard to waiver eligibility (figure 5). 

Figure 5. Counties Eligible for ABAWD Work Requirement Waiver, 2007– 

present 

Source: Local Area Unemployment Statistics, BLS (2000–2018); EB and 

EUC Trigger notices (DOL), Bureau of Labor Statistics (2000–2018). 

Current policy with regard to waiver eligibility provided all the coverage until the 

Bush Administration linked waiver eligibility to EUC. Existing and recession-responsive policy functioned to provide close to 100 percent waiver eligibility from 

2009 to 2014. The scope of coverage was driven by policy actions taken at the Federal and state levels to increase eligibility for EUC and EB, which had downstream 

effects on SNAP work requirement waivers. In the absence of such actions, the 20 

percent rule is the most effective of standing rules at providing waiver eligibility at 

the start of the recession and EB is the most effective during recovery. No standing 

rules provide coverage of the scale and speed instigated by policy actions taken during the Great Recession. 

2. Modeled Eligibility Versus the Proposed Rule 

We compare existing standing policy (purple) for waiver eligibility with the proposed rules including three options proposed by the USDA for the 20 percent rule 

as they would have performed not just ‘‘now,’’ as the RIA showed, but over the 

course of the Great Recession (figure 6). The model for the proposed rule also maintains eligibility for areas having an unemployment rate above ten percent over a 

recent 12 month period and for areas in which EB would have triggered eligibility. 

Because eligibility based on EB is consistent across standing and proposed rules, 

we focus on how the different floors to the 20 percent rule (no floor, six, seven, and 

ten percent unemployment floors) affect access to SNAP at the onset and during the 

Great Recession before discussing considerations of when, whether, and how to have 

waivers trigger off. 

USDA’s preferred modification is to implement a seven percent floor for the 20 

percent rule and eliminate the 3 month lookback and statewide waivers (light 


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8The new regulations state that for the 20 percent rule, the period of eligibility for a state 

will only last through the end of the fiscal year in which a state applied, as opposed to 1 year 

from the date of the application. We have assumed that the waiver application limits are the 

same as the current regulations, and have extended the period of waiver through the end of 

the fiscal year. Additionally, we have applied the same rounding standards to the respective 

floors as to the 20 percent cutoff above. 

green).8 Had this rule been in place in the first quarter of the Great Recession, 

when the economy was losing 300,000 jobs a month and when SNAP rolls should 

be expanding, waivers would have been limited to less than 20 percent of counties. 

The ten percent floor (teal) would have performed worse, with less than ten percent 

of counties eligible. The six percent standard (dark green) covered less than 30 percent of counties. 

Figure 6. Counties Eligible for ABAWD Work Requirement Waiver, Existing 

and Proposed Regulations 

Source: Local Area Unemployment Statistics, BLS (2000–2018); EB and 

EUC Trigger notices (DOL), Bureau of Labor Statistics (2000–2018). 

Note: Because eligibility for waivers due to EB status is included in each 

line, the lines converge once widespread EB status occurs in early 2009. 

By standing and proposed rules, waiver eligibility dissipate measurably in 2013. 

But, the revealed preference of the policymakers at the time was that the current 

rules were too restrictive and needed to be relaxed. A number of decisions were 

made to expand and extend waiver eligibility, both early in the recession and afterwards. Figure 7 highlights the difference between the revealed preferences of policymakers working to stabilize the economy during the recession and how waiver eligibility would have worked based on the proposed rules. 

The purple line shows eligibility for work requirement waivers based on standing 

regulations, EUC, and ARRA. This line contrasts with eligibility for the proposed 

rules: EB eligibility, ten percent unemployment with a 12 month lookback, and the 

20 percent rule with varying floors. The revealed preferences on policymakers during the Great Recession was to use policy tools relevant to identifying areas with 

insufficient jobs to expand SNAP work requirement waiver eligibility, in part because existing rules were insufficient to the task. Both at the start of the recession 

and in the event of a sluggish recovery, the proposed rules diminish SNAP’s role 

as an economic stabilizer and safety net. 


11602031.eps
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9The data on work requirement waiver eligibility can be found at https://www.cbpp.org/research/food-assistance/States-have-requested-waivers-from-snaps-time-limit-in-high-unemployment. The data on county eligibility was copied by hand and duplicated by a second researcher 

using mapchart.net to produce a JSON, which converted the visualization into data used to 

produce the analyses. We did not have access to any waiver application information or to USDAproduced information regarding waiver eligibility. If any area of a county received a waiver, we 

counted the entire county as receiving a waiver due to an inability to be more precise. These 

maps are predicated on waiver take-up; we continue to be unable to identify waiver eligibility 

based on regional eligibility or LSAs for states that chose not to apply. 

Figure 7. Counties Eligible for ABAWD Work Requirement Waiver, Proposed Regulations versus Actual Eligibility during the Great Recession 

Source: Local Area Unemployment Statistics, BLS (2000–2018); EB and 

EUC Trigger notices (DOL); Bureau of Labor Statistics (2000–2018). 

As this analysis emphasizes, if there is a problem with the current rules, it is in 

the beginning of a recession because existing rules do not allow states to respond 

promptly to a recession. The proposed rule does not address or fix waiver 

responsivity to the onset of an economic downturn. Thus, the fact that the proposed 

rule would make the waiver process less responsive to an economic downturn and 

less able to accomplish the goals of the program is absent from considerations of 

costs and benefits. It is incumbent on the proposed rule to ensure that it does not 

make responsiveness to an economic downturn worse. 

3. Eligibility Versus The Proposed Rule 

In the preceding sections, we have modeled waiver eligibility to the extent possible and clearly articulated the ways in which we would not be able to model legitimate features of the existing rules. Most notably, we were unable to model regional 

eligibility and were unable to model eligibility based on Labor Surplus Areas. By 

adding to these models data from publicly available maps produced by the Center 

on Budget and Policy Priorities, we are able to identify counties that are eligible 

for work requirement waivers by triggers that we were unable to model through our 

method for those states that implemented these standards.9

For focal years 2008 and 2017, we produce maps of the continental United States 

to identify differences in waiver eligibility by the proposed rule, the existing rules 

as modeled, and the existing rules as waived. Figures 8 and 9 are maps showing 

which counties would be eligible for work requirement waivers under both current 

rules (which do not model eligibility based on grouping of contiguous areas) and the 

proposed rules (EB, ten percent rule with a 12 month lookback, 20 percent rule with 

the seven percent unemployment rate floor [purple]), which counties would lose eligibility due to changes in standing rules (blue), and which counties would lose eligiVerDate Aug 31 2005 11:16 Jun 14, 2019 Jkt 041481 PO 00000 Frm 00079 Fmt 6633 Sfmt 6621 P:\DOCS\116-02\36188.TXT BRIAN

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bility because they are regionally eligible or eligible by one of the criteria (like 

LSAs) that we are unable to model (orange). 

In 2008, during the Great Recession, most states used the flexibility afforded to 

them by standing rules to quickly respond to changing economic conditions and 

cover areas that would not be individually eligible—either by applying for statewide 

waivers or through regional eligibility. For example, Ohio applied for and was granted a 2 year statewide waiver in June of 2008 to cover July 1, 2008 to June 30, 2010 

based on the state qualifying under the 20 percent rule (Ohio Job and Family Services 2008) and parts but not all of Pennsylvania qualified regionally (Pennsylvania 

Department of Human Services 2008). As economic conditions deteriorated, existing 

flexibility with regard to both geographic unit and economic indicators allowed 

states to respond more quickly to the recession than Congress or the Executive 

Branch. 

Figure 8. Waiver Eligibility by Standing and Proposed Rules, 2008 

2008 

The NPRM states ‘‘a significant number of states continue to qualify for and use 

ABAWD waivers under the current waiver standards (p. 981).’’ Based on the USDA 

waiver status notifications, over the course of 2017, eight states and D.C. were approved to receive a statewide waiver, 26 states had a partial waiver, and 16 states 

were implementing time limits statewide. Figure 10 shows that six states would 

have no eligible areas for work requirements under the proposed rules, of which 

three (Vermont, New Hampshire, Connecticut) have currently eligible areas that 

would lose coverage. The states who submitted waiver applications, in doing so expressing their preference for waiver flexibility, and who would have seen coverage 

reduced based on the proposed rules had they been implemented in 2017 are Alabama, Arizona, California, Colorado, Connecticut, Georgia, Idaho, Kentucky, Maryland, Massachusetts, Michigan, Minnesota, Montana, Nevada, New Hampshire, 

New Jersey, North Dakota, Ohio, Oregon, Pennsylvania, Rhode Island, South Dakota, Tennessee, Utah, Vermont, and Washington. According to USDA and affirmed 

in our analysis, 17 states declined to submit a waiver for eligible areas: Alabama, 

Arkansas, Delaware, Florida, Indiana, Iowa, Kansas, Maine, Mississippi, Missouri, 

Nebraska, North Carolina, Oklahoma, South Carolina, Texas, Wisconsin, and Wyoming (USDA 2017a). 


11602033.eps
75 

Figure 9. Waiver Eligibility and Take-up, 2017 

2017 

Table 1 shows where in the U.S. and through which eligibility trigger would counties have lost eligibility in 2017. We show RIA Table 3 for comparison and assume 

that Table 3 refers to 2018. By our calculations, in 2017, 1,322 counties were eligible 

and 1,012 counties took up a waiver. 

Table 1. Impact of Rule Provisions 

RIA Table 3. Impact of Rule Provisions on Currently-Waived Areas 

Currently waived areas = 975 

Areas still 

qualifying 

for waivers 

Reduction 

in waived 

areas 

Percent 

reduction 

Eliminate other eligibility criteria 621 ¥354 ¥36% 

Eliminate statewide waivers 582 ¥39 ¥4% 

Implement 7% UR threshold 220 ¥362 ¥37% 

Total 220 ¥755 ¥76% 

Impact of Rule Provisions on Take-up Areas, 2017 

Current areas taking up waivers = 1,012 Areas still 

taking up 

waivers 

Reduction in 

waiver 

areas, takeup 

Percent 

reduction 

Eliminate 10% UR, 3 month lookback 1,011 ¥1 0% 

Implement 7% UR threshold 853 ¥158 ¥16% 

Eliminate EUC 853 0 0% 

Eliminate ARRA-related triggers 853 0 0% 

Eliminate statewide waivers 820 ¥33 ¥4% 

Eliminate other eligibility criteria 574 ¥246 ¥30% 

Total 574 ¥438 ¥43% 

Looking first at counties that would qualify individually or as part of an LMA, 

one county would lose eligibility due to the elimination of the 3 month lookback on 

ten percent unemployment and 158 counties would lose eligibility based on the implementation of a seven percent floor to the 20 percent rule. This is substantially 

smaller than the 362 counties that the RIA states would lose eligibility due to the 

implementation of a seven percent unemployment rate floor to the 20 percent rule. 


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76 

10 20 percent of ABAWDs in the SIPP reported having a child under the age of 21 who lived 

in a different household or who reporting being a parent but who did not have a child living 

at home. 

This is evidence that the RIA incorrectly modeled the 20 percent rule and that failing to account for LMA-based eligibility has substantially affected their estimates. 

Next, we look at the effect of eliminating statewide waivers on eligibility. In 2017, 

the following states had statewide work requirement waivers: Alaska, California, 

District of Columbia, Illinois, Louisiana, Nevada, and New Mexico. Alaska would 

maintain statewide eligibility based on EB, but 33 counties would lose eligibility because of the loss of these statewide waivers. 

Like the RIA, we do not directly model the remaining eligibility criteria. Unlike 

the RIA, we assign the remainder of take-up counties to this category, rather than 

starting with it. We find that 246 counties taking up waivers would lose eligibility 

by eliminating the remaining eligibility criteria, compared with 354 for the RIA. We 

find that 574 counties among those actually waived in 2017 would retain eligibility, 

while the RIA finds that 220 counties would. 

The NPRM has misspecified the justification for the NPRM and has failed to 

properly analyze the regulatory impact. This analysis finds a deleterious effect of 

the new rules at the onset of a recession and less reduction in coverage ‘‘today.’’ For 

these reasons, the current rules should be maintained. 

IV. Employment Status Changes 

When an area is not subject to a waiver, work requirements subject Able-bodied 

Adults without Dependents (ABAWDs) to a time limit for receiving SNAP benefits 

under the law. The exemptions to this rule are at the participant level, for example, 

those receiving disability income or who are ‘‘unfit’’ for employment based on a 

physical or mental disability, those who have dependent minor children, and those 

outside the targeted age range are not subject to the work requirements. 

This section provides evidence that suggests waivers from work requirements at 

both the individual and geographic area should be more readily available. We show 

that economic conditions beyond the control of program participants are driving 

whether they can meet the 20 hour a week standard consistently, as work-related 

reasons explain a substantial share of gaps in working for pay. ABAWDs also appear to be in substantially poorer health than non-SNAP recipients. Furthermore, 

about 20 percent of ABAWDs are non-custodial parents, potentially exposing children to benefit loss from which the law protects them.10

The proposed rule would make it more difficult for geographic areas to qualify to 

apply for waivers. This will mean that some areas where states have weak enough 

economies to warrant the waivers would not be able to use them. We show that during 2013 and 2014, when only seven states and the District of Columbia had annual 

unemployment rates above seven percent: 

• A plurality of ABAWDs experience labor force status transitions over an extended period of time that would expose workers to benefit loss even though 

they are in the labor force; 

• More than 1⁄3 of workers who experienced a period of not working said that it 

was due to a work-related reason, such as failure to find work or being laid off 

while less than 1⁄2 of one percent of ABAWDs were not working due to lack of 

interest; and, 

• Four out of five ABAWDs who are out of the labor force are not in fact ablebodied: while they do not receive disability income, they report health or disability as the reason for not working. 

The decline in labor force participation—especially among prime-age males—has 

drawn extensive attention in academic and policy circles (e.g., Abraham and 

Kearney 2018; Juhn 1992; White House 2016). Some recent academic work has emphasized the fact that participation may be declining in part because an increasing 

number of labor force participants cycle in and out of the labor force: a pattern with 

direct relevance to proposed work requirements. The most comprehensive look at 

the behavior of people cycling through the labor force is Coglianese (2018). He documents that, among men, this group he refers to as ‘‘in-and-outs’’ take short breaks 

between jobs, return to the labor force fairly quickly (within 6 months), and, crucially, are no more likely than a typical worker to take another break out of the 

labor force. See also Joint Economic Committee (2018) for a discussion of the in-andout behavior of nonworking prime-age men and reasons for their non-employment. 

SNAP participants who are employed but who work in jobs with volatile employment and hours would be at risk of failing work requirements. This group includes 

77 

11The states which had an unemployment rate above seven percent in both 2013 and 2014 

were: Georgia, Illinois, Michigan, California, Mississippi, Rhode Island, Washington D.C., and 

Nevada. 

those who lose their job, sanctioning those who were recently employed and are 

searching for a new job. Similarly, those who work in jobs with volatile hours would 

be sanctioned in the months that their average hours fell below 20 hours per week, 

whether due to illness, lack of hours offered by the employer, or too few hours 

worked by the participant if they fail to receive a good-cause waiver. By making it 

more difficult for states to provide waivers when they feel conditions warrant, the 

proposed rule will cause more people to lose SNAP benefits. 

Low-wage workers in seasonal industries such as tourism would potentially be eligible for SNAP in the months when they are working, but not in the months without employment opportunities. In other words, while benefits are most needed when 

an individual cannot find adequate work, under proposed work requirements these 

are the times that benefits would be unavailable. Disenrollment could make it more 

difficult for an individual to return to work—for example, if a person with chronic 

health conditions is unable to access needed care while they are between jobs. Any 

work requirement that banned individuals from participation for a considerable 

amount of time after failing the requirements would be even more problematic for 

those facing churn in the labor market. 

In a set of analyses, Bauer (2018), Bauer and Schanzenbach (2018a, 2018b) and 

Bauer, Schanzenbach, and Shambaugh (2018) found that although many SNAP 

beneficiaries work on average more than 20 hours a week every month, they frequently switch between working more than 20 hours and a different employment 

status over a longer time horizon. 

For this comment, we examine labor force status transitions and the reasons 

given for not working among ABAWDs over 24 consecutive months, January 2013– 

December 2014. The data used are from the first two waves of the Survey of Income 

and Program Participation (SIPP). By using a data set that allows us to track workers over time, we identify the share of program participants who are consistently 

out of the labor force, the share who would consistently meet a work requirement, 

and the share who would be at risk of losing benefits based on failing to meet a 

work requirement threshold. 

We assume that to comply with a program’s work requirement, beneficiaries 

would have to prove each month that they are working for at least 20 hours per 

week, or at least 80 hours per month, which is the typical minimum weekly requirement among the SNAP work requirement proposal. We calculate the share of program participants who would be exposed to benefit loss because they are not working sufficient hours over the course of 24 consecutive months. Among those who 

would be exposed to benefit loss and who experienced a gap in employment, we describe the reasons given for not working to help quantify potential waiver eligibility. 

We remove from the analysis all those who have a categorical exemption, excluding those outside the targeted age range, those with dependent children, full- or 

part-time students, and those reporting disability income. Program participants are 

those who reported receiving SNAP at any point between January 1, 2013, and December 31, 2014. The vast majority of states over time period covered by the analysis had unemployment rates below seven percent in either 2013, 2014, or both.11

The preponderance of evidence presented shown here is thus occurring in labor markets that the proposed rule says has sufficient jobs available to ABAWD SNAP participants. 

We categorize each individual in each month into one of four categories: (1) employed and worked more than 20 hours a week, (2) employed and worked less than 

20 hours a week, (3) unemployed and seeking employment, or (4) not in the labor 

force. If a worker was employed at variable weekly hours but maintained hours 

above the monthly threshold (80 hours for a 4 week month and 120 hours for a 5 

week month) then we categorize them as (1) employed and worked more than 20 

hours a week for that month. Individuals are considered to have a stable employment status if they do not change categories over 2 years, and are considered to 

have made an employment status transition if they switched between any of these 

categories at least once. There is no employment status transition when a worker 

changes jobs but works more than 20 hours a week at each job. 

Among working-age adults, SNAP serves a mix of the unemployed, low-income 

workers, and those who are not in the labor force (USDA 2017b (https:// 

www.fns.usda.gov/snap/facts-about-snap)). Figure 10 describes employment status 

of ABAWDs. Those receiving SNAP benefits who are in the demographic group currently exposed to work requirements—adults aged 18–49 with no dependents—generally participate in the labor market, with just 25 percent consistently not in the 

78 

labor force (discussed below). While 58 percent worked at least 20 hours per week 

in at least 1 month over 2 years, 25 percent were over the threshold at some point 

but fell below the 20 hour threshold during at least 1 month over 2 years. Very few 

are always working less than 20 hours a week or always unemployed (less than two 

percent in either case), and 14 percent move across these categories. 

These findings give a markedly different impression than a snapshot in time— 

1 month. When we compare the 1 month (December 2013) against 24 months (January 2013–December 2014), we find that using 1 month of data, more program participants appear to be labor force non-participants and more appear to meet the 

work requirement threshold. That is, looking only at 1 month of data, an observer 

would both think there is a bigger problem of labor force non-participation in SNAP 

than there really is, and would think that fewer labor force participants would lose 

benefits in a state or county with work requirements. 

There is a meaningful portion of SNAP participants in the labor force and working, but not all are working above the monthly work requirement threshold consistently. Coglianese’s (2018) finding that workers who are in and out of the labor force 

are not more likely to take another break later on suggests it is unclear how much 

more consistently work requirements would attach these people to the labor force. 

In our work, too, we find that frequent movement between labor status categories 

over time increases the number of people exposed to losing benefits for failing to 

consistently meet a work requirement and decreases the number of people who are 

entirely out of the labor market. 

Figure 10. Employment Status in One Month versus Two Years, SNAP Participants 18–49 with No Dependents 

Source: Survey of Income and Program Participation; authors’ calculations. 

It is helpful to consider specifically what types of individuals would be affected 

by proposed work requirements and why they are not currently working if they are 

not in the labor force to better understand the possible impacts of expanded work 

requirements. It is clear that some people face barriers to working outside the home 

and as such, many work requirements exempt people receiving disability income, 

people with young dependents, or students; but, accurately exempting all those who 

are eligible can be challenging and is likely to result in terminating coverage for 

many people with health conditions or caregiving responsibilities that fall outside 

of states’ narrow definitions. 

We next examine the reasons ABAWDs gave for not working over the 2 year period (figure 11). Those in solid green were in the labor force but experienced at least 

one spell of unemployment or labor force nonparticipation. Among the labor force 

participants who were asked why they were not working for pay during at least 1 

week, we report the reason for not working in months they were not working. For 

perspective, the share of the population that worked consistently over the 2 years 

and therefore was never asked why they were not working, are shown in the green 

crosshatch. Those in the blue were out of the labor force for the entire 2 year period. 

Each person is assigned one reason—their most frequent reason—for not working. 


11602035.eps
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Figure 11. Most-Frequent Reason for Not Working for Pay, SNAP Participants 18–49 with No Dependents 

Source: Survey of Income and Program Participation; authors’ calculations. 

Focusing first on the 25 percent of the SNAP ABAWD population that was not 

in the labor force over the full sample, we find almost 85 percent reported that the 

reason that they were not working was poor health or disability (this is about 20 

percent of all ABAWDs). Another quarter of the sample is in stable work. The remaining 50 percent, though, were in the labor force at some point, but at other 

times not working. Among that group, more than 1⁄2 (28 percent of all ABAWDS) 

reported that a work-related reason, such as not being able to find work or being 

laid off, was their reason for not working for pay. 

As shown in figure 12 below, a substantially larger share of adult SNAP participants were not working due to work-related reasons than the overall population, 

even during this time period (2013–14) when the economy was on an upswing. More 

than a quarter of ABAWDs experienced a period of not working for pay or nonparticipation due to labor market conditions outside their control. This share is 80 

percent larger than the share of work-related reasons among the overall population. 

That is, even when the economy is improving, SNAP participants may be in particularly vulnerable occupations and find themselves frequently unable to work due to 

their local job markets. This is the group that a waiver for economic reasons is most 

directly intended to help, and this evidence shows that even when the economy is 

over 4 years after a recession, this group may still be at risk of losing benefits not 

because they do not want to work, but because they are unable to either find a job 

or get the requisite number of hours. 


11602036.eps
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12Those who were not working due to health or disability reported that they were not working 

for pay because they were unable to work because of chronic health condition or disability, temporarily unable to work due to injury, or temporarily unable to work due to illness. Those in 

the stable work category did not experience a period of unemployment or nonparticipation over 

the 2 year period. Those in the period of unemployment or nonparticipation group were at least 

once not working for pay during the 2 year period. Labor force non-participants did not work 

for pay at all during the 2 year period. Those in the labor force non-participant due to health 

group did not work for pay at all during the 2 year period and the most frequent reason given 

for their nonparticipation was health. 

Figure 12. Share Not Working for Pay for Work-Related Reasons Overall 

versus SNAP, by Demographic Characteristics 

Source: Survey of Income and Program Participation; authors’ calculations. 

This evidence presented thus far shows that those who are most at risk to losing 

benefits under the proposed rules are workers experiencing normal labor market 

fluctuations and those who should be eligible for exemptions but often fail to receive 

them. Among persistent labor force non-participants, we find that health issues are 

the predominant reason given for not working even though the analysis excludes 

program participants who reported disability income because they would be eligible 

for a categorical exemption from a work requirement. This group would also lose 

SNAP benefits if work requirement waivers were removed. 

Some have questioned whether survey respondents are likely to provide accurate 

information about their health. This criticism stems from social desirability bias; 

survey respondents might feel pressure to report a more publicly acceptable reason 

for not working than what might actually be true. In this case, a respondent who 

simply does not want to work would say that they are not working because of a 

health condition; a health problem is a socially acceptable reason for not working, 

but the real reason is not. 

In this analysis, we show that those reporting health as a reason for not working 

do appear to be in poor health. We investigate the prevalence of reported health conditions among ABAWD SNAP participants.12

Using the information from the prior analyses, we divide the SNAP participants 

into five groups: 

• Stable work—those who worked consistently for 2 years; 

• Transitioned in and out of work due to health—those who were in the labor 

force but experienced a period of unemployment or nonparticipation due to a 

health condition or disability; 

• Transitioned in and out of work, other—those who were in the labor force but 

experienced a period of unemployment or nonparticipation for a reason other 

than health or disability; 

• Labor force non-participant due to health—those who did not work at all for 2 

years due to a health condition or disability; and, 


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81 

13Those in self-reported poor health responded ‘‘poor’’ to the question ‘‘what is your health 

status?’’ Those in the daily prescription medication group responded affirmatively to the question ‘‘Did you take prescription medication on a daily basis?’’ Those in the any disability responded affirmatively to at least one of the following questions: Do you have serious difficulty 

walking or climbing stairs; do you have difficulty dressing or bathing; do you have serious difficulty concentrating, remembering, or making decisions; do you have a serious physical or mental condition or a developmental delay that limits ordinary activity; do you have difficulty doing 

errands alone; do you have difficulty finding a job or remaining employed; are you prevented 

from working; are you deaf or do you have serious difficulty hearing; are you blind or do you 

have serious difficulty seeing? Those who spent more than 30 days in bed responded to the question ‘‘How many days did illness or injury keep you in bed more than half of the day’’ for at 

least 30 days over the 2 year period. 

• Labor force nonparticipation, other—those who did not work at all for 2 years 

for a reason other than health or disability. 

Figure 13. Health Characteristics of ABAWDs, by Employment Status 

Source: Survey of Income and Program Participation; authors’ calculations. 

We look at whether SNAP participants who would be exposed to work requirements are in self-reported fair or poor health, take a prescription medication daily, 

respond affirmatively to at least one in a battery of questions about disability, or 

spent more than 30 days over a 2 year period in bed due to ill health.13 These questions about health are self-reported, but are considerably less subject to the social 

desirability bias that may affect how a respondent answers the question as to why 

they are not working. In fact, these questions are asked in the survey long before 

the respondent is asked about their labor force status, reducing the likelihood they 

are manipulating their response to justify not working. 

Ninety-nine percent of ABAWD labor force non-participants who reported the reason for their nonparticipation was due to health in fact reported health problems; 

91 percent reported a disability, 86 percent reported taking medication daily, 82 percent reported being in self-reported fair or poor health, and 39 percent reported 

spending more than 30 days in bed. For those labor force non-participants reporting 

a different reason for their nonparticipation, three in five reported a health problem. 

More than 1⁄3 reported a disability, almost 1⁄2 took daily medication, and 15 percent 

spent more than 30 days in bed. Among those who were labor force participants but 

experienced a period of unemployment or nonparticipation due to health, nine out 

of ten reported a health condition. About seven in ten reported a disability and taking a daily prescription, about 60 percent were in self-reported fair or poor health, 

and a quarter spent more than 20 days in bed. 

The prevalence of health conditions among ABAWD labor force non-participants 

as well as labor force participants working unstably due to health contrasts with 

those working stably. But to be clear, even among this group, a quarter report a 

disability, 44 percent are taking a daily prescription medication, 1⁄5 are in self-reported fair or poor health, and six percent spent substantial time in bed. 

Those who are SNAP participants with health issues who are unable to work and 

who would be exposed to work requirements would be required to obtain documents 

verifying their health problems frequently in order to retain an exemption. These 


11602038.eps
82 

people could lose access to the program due to paperwork requirements unless administrative capacity were expanded greatly to monitor and adjudicate these health 

concerns. Even then, administrative failures could lead to loss of access to food benefits. 

There may be some SNAP participants who might join the labor force if they were 

threatened with the loss of benefits. Recent evidence shows that this group is very 

small relative to those who would be improperly sanctioned by work requirements 

who are already working or are legitimately unable to work. This evidence is directly relevant to claims in the NPRM and RIA that exposing more areas to work 

requirements would increase self-sufficiency. The USDA has failed to provide evidence that this would be the case, and the evidence produced in this section make 

it clear that work requirement would harm labor force participants who experience 

market volatility and labor force non-participants, the vast majority of whom have 

a health condition. 

V. Conclusion 

Executive Order 12866 states that agencies, such as USDA, may issue regulations 

when there is a compelling public need and when the benefits outweigh the costs 

in such a way as to maximize net benefits. We find that both the NPRM and its 

RIA insufficiently analyze the proposed rule and fail to consider the costs and benefits under alternate economic conditions or to the participants in any circumstance. 

In this comment, we have provided evidence and analysis that the USDA has proposed a rule that is arbitrary, that the rule runs counter to the compelling public 

need for waivers to work requirements during economic downturns, and fails to consider much less prove that the benefits outweigh the costs. The existing rule should 

be sustained. 

VI. References 

Aaronson, Stephanie R., Mary C. Daly, William Wascher, and David W. Wilcox. 2019. ‘‘Okun Revisited: Who Benefits Most From 

a Strong Economy?’’ Brookings Papers on Economic Activity, Conference Draft. 

Abraham, Katharine G., and Melissa S. Kearney. 2018. ‘‘Explaining the Decline in the U.S. Employment-to-Population Ratio: A 

Review of the Evidence.’’ Working Paper 24333, National Bureau of Economic Research, Cambridge, MA. 

Almond, Douglas, Hilary W. Hoynes, and Diane Whitmore Schanzenbach. 2011. ‘‘Inside the War on Poverty: The Impact of Food 

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83 

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VII. Appendix 

Appendix Table 1. Interactions between Emergency Unemployment Compensation and 

SNAP Waiver Eligibility 

Date range 

EUC threshold 

for SNAP 

Waiver eligibility 

Tier eligibility Source 

January 8, 2009– 

November 5, 

2009 

Tier II 3 month seasonally adjusted total 

unemployment rate (TUR) of at 

least six percent; or 13 week insured unemployment rate (IUR) 

of at least 4.0 percent (CRS 

2014 1) 

The Bush Administration clarified 2 that EUC counted for 

SNAP waivers on January 8, 

2009. Any state that was eligible for Tier II EUC was eligible 

for SNAP waivers based on 

EUC eligibility. From January 

9, 2009 to November 6, 2009, 

eligibility for Tier II was conditional on having a TUR of at 

least six percent or an IUR of at 

least four percent. Tier II was 

not universal among states before November 6, 2009 (Table 1 

in Rothstein 2011 3). 

84 

14 Because we round to the nearest month, we end the EUC eligibility period in December 

2013. Waivers based on EUC were granted through 2016. 

Appendix Table 1. Interactions between Emergency Unemployment Compensation and 

SNAP Waiver Eligibility—Continued 

Date range 

EUC threshold 

for SNAP 

Waiver eligibility 

Tier eligibility Source 

November 6, 

2009–May 31, 

2012 

Tier III 3 month seasonally adjusted TUR 

of at least six percent; or 13 

week IUR of at least 4.0 percent 

(CRS 2014 1) 

When all states were eligible for 

Tier II benefits, states had to 

additionally qualify for Tier III 

benefits in order to be eligible 

for a SNAP waiver application 

(CBPP4 2018). State eligibility 

for EUC tier II became unconditional on November 6, 2009 

(Rothstein 2011 3). 

June 1, 2012– 

Dec. 31 2013 

Tier II 3 month seasonally adjusted TUR 

of at least six percent (CRS 

2014 1) 

On June 1, 2012 5 Tier II qualifications go back to a 3 month 

seasonally adjusted TUR of at 

least six percent and therefore 

Tier II is no longer a universal 

tier. According to DOL, as of 

January 12, 2014 EB is not currently available in any state 

(DOL6).14

1https://fas.org/sgp/crs/misc/R42444.pdf. 2https://fns-prod.azureedge.net/sites/default/files/snap/ABAWD%20Statewide%20 

Waivers.pdf. 3https://www.brookings.edu/wp-content/uploads/2011/09/2011b_bpea_rothstein.pdf. 4https://www.cbpp.org/sites/default/files/atoms/files/3-24-17fa.pdf. 5https://en.wikipedia.org/wiki/Unemployment_extension. 6https://oui.doleta.gov/unemploy/docs/supp_act_eb-euc-expired.pdf. 

ATTACHMENT 2

ECONOMIC ANALYSIS ≥ October 2018 


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85 

* LAUREN BAUER, The Hamilton Project and the Brookings Institution; DIANE WHITMORE

SCHANZENBACH, The Hamilton Project, the Brookings Institution, and Northwestern University; 

and JAY SHAMBAUGH, The Hamilton Project, the Brookings Institution, and The George Washington University. 

Work Requirements and Safety Net Programs * 

Acknowledgments 

We thank reviewers John Coglianese, Jason Furman, Heather Hahn, 

Kriston McIntosh, Ryan Nunn, and the Center on Budget and Policy Priorities. We also thank the following who provided research assistance: Patrick 

Liu, Jimmy O’Donnell, Jana Parsons, Becca Portman, and Areeb Siddiqui. 

Mission Statement 

The Hamilton Project seeks to advance America’s promise of opportunity, 

prosperity, and growth. 

We believe that today’s increasingly competitive global economy demands 

public policy ideas commensurate with the challenges of the 21st Century. 

The Project’s economic strategy reflects a judgment that long-term prosperity is best achieved by fostering economic growth and broad participation in that growth, by enhancing individual economic security, and by embracing a role for effective government in making needed public investments. 

Our strategy calls for combining public investment, a secure social safety 

net, and fiscal discipline. In that framework, the Project puts forward innovative proposals from leading economic thinkers—based on credible evidence and experience, not ideology or doctrine—to introduce new and effective policy options into the national debate. 

The Project is named after Alexander Hamilton, the nation’s first Treasury Secretary, who laid the foundation for the modern American economy. 

Hamilton stood for sound fiscal policy, believed that broad-based opportunity for advancement would drive American economic growth, and recognized that ‘‘prudent aids and encouragements on the part of government’’ 

are necessary to enhance and guide market forces. The guiding principles 

of the Project remain consistent with these views. 

Abstract 

Basic assistance programs such as the Supplemental Nutrition Assistance Program (SNAP, formerly the Food Stamp Program) and Medicaid ensure families have 

access to food and medical care when they are low-income. Some policymakers at 

the Federal and state levels intend to add new work requirements to SNAP and 

Medicaid. In this paper, we analyze those who would be impacted by an expansion 

of work requirements in SNAP and an introduction of work requirements into Medicaid. We characterize the types of individuals who would face work requirements, 

describe their labor force experience over 24 consecutive months, and identify the 

reasons why they are not working if they experience a period of unemployment or 

labor force nonparticipation. We find that the majority of SNAP and Medicaid parVerDate Aug 31 2005 11:16 Jun 14, 2019 Jkt 041481 PO 00000 Frm 00091 Fmt 6633 Sfmt 6621 P:\DOCS\116-02\36188.TXT BRIAN

11602040.eps
86 

labor force nonparticipation. We find that the majority of SNAP and Medicaid participants who would be exposed to work requirements are attached to the labor 

force, but that a substantial share would fail to consistently meet a 20 hours per 

week-threshold. Among persistent labor force non-participants, health issues are the 

predominant reason given for not working. There may be some subset of SNAP and 

Medicaid participants who could work, are not working, and might work if they 

were threatened with the loss of benefits. This paper adds evidence to a growing 

body of research that shows that this group is very small relative to those who 

would be sanctioned under the proposed policies who are already working or are legitimately unable to work. 

Introduction 

Basic assistance programs such as the Supplemental Nutrition Assistance Program (SNAP, formerly the Food Stamp Program) and Medicaid ensure families have 

access to food and medical care when they are low-income. These programs lift millions out of poverty while reducing food insecurity and increasing access to medical 

care. They also support work, and increase health and economic security among 

families in the short term as well as economic self-sufficiency in the long-term. 

Today, some policymakers at the Federal and state levels intend to add new work 

requirements in order for beneficiaries to receive SNAP benefits and participate in 

the Medicaid health insurance program. In general, those exposed to a work requirement would be required to prove that they are working or participating in a 

training program for at least 20 hours per week each month. Failure to prove that 

they have met the work requirement or are eligible for an exemption would mean 

that a program participant would lose food assistance benefits or health insurance 

for a time, or until they met the standard. 

Work requirements are meant to force work-ready individuals to increase their 

work effort and maintain that work effort every month by threatening to withhold 

and subsequently withholding food assistance or health coverage if a person is not 

working a set number of hours. The strategy presumes that the reasons that many 

low-income individuals are not working or meeting an hourly threshold every month 

is either due to their own lack of effort or to work disincentives theoretically inherent to means-tested programs. It is clear that some people face barriers to working 

outside the home and as such, many work requirements exempt people that receive 

disability income, people with young dependents, or students; but, accurately exempting all those who are eligible can be challenging and is likely to result in terminating coverage for many people with health conditions or caregiving responsibilities 

that fall outside of states’ narrow definitions. Proponents of work requirements 

would ideally only like to sanction individuals who are able to work, but choose not 

to. But in practice strict enforcement of proposed work requirements will sanction 

many groups, including: those who are unable to work, those who are able to work 

but who do not find work, those who are working but not consistently above an 

hourly threshold, and those who are meeting work or exemption requirements but 

fail to provide proper documentation. Evidence suggests that the vast majority of 

those exposed to proposed work requirements for SNAP and Medicaid fall into these 

groups. 

In this paper, we analyze those who would be impacted by an expansion of work 

requirements in SNAP and an introduction of work requirements into Medicaid. Our 

principal contribution is to characterize the types of individuals who would face 

work requirements, describe what their work experiences are over a 2 year period, 

and identify the reasons why they are not working if they experience a period of 

unemployment or labor force nonparticipation. We find that most of those who fail 

the new work requirements are either those who are in the labor force already but 

who experience unstable employment, or those who might be eligible for hardship 

exemptions, such as those with health problems who are not already receiving disability income. The compositional and labor market analyses reported below suggest 

that the proposed work requirements will put at risk access to food assistance and 

health care for millions who are working, trying to work, or face barriers to working. 

Adding explicit work requirements to assistance programs must be analyzed in 

the context of program goals and from many angles. Who would be impacted by an 

expansion of work requirements? What are the administrative costs and challenges 

of managing the work requirements? How do the requirements interact with the realities of the low-wage work experience? And how would the requirements impact 

the health and economic benefits to program participation? For example, removing 

Medicaid coverage may have little positive work-incentive effect for the currently 

healthy but may undermine public health goals and reduce the labor supply of those 

who do encounter health problems and have lost their coverage. Removing SNAP 

benefits from working-age adults may impact resources available not just to them, 

87 

but also to any seniors and dependents in the household. Finally, tight work requirements can undermine the automatic stabilizer aspect of these programs. Instead of SNAP expanding as the unemployment rate rises, the work requirements 

would cause the program to contract, resulting in more people losing benefits when 

work becomes difficult for them to find. 

There may be some subset of individuals who could work, are not working, and 

might work if they were threatened with the loss of benefits. This paper adds evidence to a growing body of research that shows that this group is very small relative 

to those who would be sanctioned under the proposed policies who are already working or are legitimately unable to work (Bauer and Schanzenbach 2018a, 2018b; Garfield, et al., 2018; Goldman, et al., 2018). 

The goals of safety net programs are to provide insurance protection to those who 

are experiencing poor economic outcomes and to support those who are trying to improve their situation. Our analysis suggests that work requirements will harm more 

individuals and families than they would help the small share who might increase 

their labor supply. 

SNAP, Medicaid, and Incentives to Work 

The social safety net is intended to provide insurance against bad outcomes. But, 

for means-tested benefit programs, economic theory suggests it may reduce the incentive to work because (1) individuals are only eligible for a program when their 

income remains below a given threshold and (2) participants stand to lose benefits 

as income increases or reaches the eligibility threshold. In addition, any time someone receives unearned income of sufficient size, it may theoretically reduce the 

amount of work that an individual wants to supply to the market. In some cases, 

worries about work disincentives have led to the implementation of time limits or 

work requirements for a set of individuals as a condition for program eligibility. 

Such work requirements can undermine the insurance value of the programs, 

though, if people who are not working either cannot work due to individual limitations or are unable to find steady work due to economic fluctuations. Evaluating 

whether work requirements are an appropriate policy lever—as opposed to addressing work disincentives through other means—thus depends on the goals of the program overall, the characteristics of the target population, the design of the work requirements, the cost of administering the program, the likelihood of erroneously limiting access, and the strength of the incentive effects. 

Work requirement policies often have difficulty distinguishing between those who 

are able to work and those who are unable to work, because both groups can be 

hard to observe and verify. As a result, strict enforcement of work requirements will 

sanction those who are unable to work, as well as those who could work but do not 

obtain employment in response to the requirements. They may also sanction some 

who are able to work but who are not able to find work, as well as those who are 

working but fail to provide proper documentation. 

In order to evaluate whether a work requirement is in keeping with the purpose 

of a means-tested program, there are a number of dimensions by which a proposal 

should be evaluated. One would want to exempt those whom society does not feel 

should be forced to work, accommodate changes in the business cycle that make 

work more difficult to find, and have a system of verification and exemption that 

does not raise barriers to entry or remove program participants who should maintain access. But, one would have to ensure that work requirements do not punish 

those who cannot obtain a job due to economic conditions in their area, penalize 

those who are actually working but have temporarily lost hours, limit access to programs for an extended period of time after failing a work requirement, or, compromise the insurance goals of the program in question. These parameters can be 

quite difficult to meet and they set the criterion by which policymakers can determine whether work requirements are inappropriate for the program in question. 

There is an extensive literature on whether work requirements can in fact push 

people into the labor force, principally studying the impacts of the 1996 Temporary 

Assistance for Needy Families (TANF) reform (see Blank 2002 and Ziliak 2016 for 

reviews). The labor supply of the TANF population did in fact rise, but this took 

place amidst a strong economy and support from the Earned Income Tax Cred[i]t 

(EITC) expansion as well (Schanzenbach 2018). For example, Fang and Keane 

(2004) find that while work requirements were the most important factor driving 

the decline in participation in welfare programs, the EITC expansion and macroeconomic factors were more important in driving the increase in work participation 

(they find work requirements had a positive impact as well, but the contribution 

was smaller). Work requirements often come with a variety of supports and involve 

different enforcement mechanisms and levels of stringency. See Hamilton, et al., 

(2001) for a detailed review as part of the National Evaluation of Welfare-to-Work 

88 

Strategies. Many of the work requirement programs that have generated positive 

results also had substantial education and skills training components (Pavetti and 

Schott 2016). Other studies, such as Meyer and Rosenbaum (2001) and Grogger 

(2004) suggest a smaller or negligible role for the TANF reforms compared with 

other factors, especially the EITC expansion. 

In this analysis, we focus more on the people who would be impacted by new work 

requirements and the reasons why they are not working, as opposed to the question 

of the labor supply response. Given the extent to which the labor market conditions—in particular for potentially impacted populations—are different than those 

in the 1990s (Black, Schanzenbach, Breitwieser 2017; Butcher and Schanzenbach 

2018), it is helpful to consider specifically what types of individuals would be affected by proposed work requirements and why they are not currently working to 

better understand the possible impacts of expanded work requirements. In this section we describe the SNAP and Medicaid programs, the structure of their work incentives, and evidence of the programs’ incentive effects on labor supply. 

SNAP 

Since the 1960s SNAP has provided resources to purchase food for millions of lowincome households. The goal of the program is to provide beneficiaries with resources to raise their food purchasing power and, as a result, improve their health 

and nutrition. Households are eligible for SNAP if they meet an asset and income 

threshold, or if they receive assistance from programs like Supplemental Security 

Income. SNAP benefit levels are targeted based on a given household’s income and 

expenses. 

SNAP currently addresses work disincentives in a variety of ways. Similar to the 

EITC, SNAP addresses work disincentives through an earnings disregard of 20 percent and a gradual benefit reduction schedule. This means that the size of the earnings disregard increases as income increases and that those with earned income receive larger SNAP benefits than those with no earned income (Wolkomir and Cai 

2018). When a person moves from being a labor force non-participant to working 

while on SNAP, total household resources will increase; as a beneficiary’s earnings 

approach the eligibility threshold, total household resources continue to increase. 

The combination of the earnings disregard and a gradual phase-out schedule—that 

states have the option to further extend and smooth—ameliorate but do not eliminate work disincentives. 

States have had the option to impose work requirements on certain beneficiaries 

since the 1980s. Most SNAP participants between the ages of 18 and 59 without 

dependents under 6 are required to register for work, accept a job if one is offered 

to them, and not reduce their work effort. States are required to operate an employment and training program, and may require some SNAP recipients to participate 

or suffer sanctions. See Rosenbaum (2013) and Bolen, et al., (2018) for a detailed 

description of SNAP work requirements. After 1996, SNAP work requirements and 

benefit time limits were imposed on individuals aged 18–49 without dependents 

under the age of 18, requiring them to register for work and accept a job if one is 

offered to them. If they work or participate in a training program for at least 20 

hours per week, they can maintain access to the program. This population is allowed to receive 3 months of benefits out of 36 months if they do not work or participate in a training program. States are permitted to exempt a share of individuals 

and apply to the U.S. Department of Agriculture (USDA) for a waiver to the time 

limit provisions, an essential capacity for SNAP’s function as an automatic stabilizer. Studies show that when SNAP payments increase to a local area in response 

to an economic downturn, they serve as an effective fiscal stimulus to the local area 

(Blinder and Zandi 2015; Keith-Jennings and Rosenbaum 2015). Among other 

changes, the proposed work requirements would make these regional waivers more 

difficult to obtain. 

SNAP improves health and economic outcomes in both the near and long terms 

(see Hoynes and Schanzenbach 2016 for a review), but had a negative effect on employment in the past. During the Food Stamp Program’s introduction in the 1960s 

and 1970s, reductions in employment and hours worked were observed, particularly 

among female-headed households (Hoynes and Schanzenbach 2012). Whether work 

requirements could offset this disincentive would depend on their targeting and 

whether those who are not working could readily increase their labor supply. 

Medicaid 

Since 1965, the Medicaid program has been administered in partnership between 

Federal and state governments to provide medical assistance to eligible individuals. 

The core goal of the program is to provide health services and to cover health-care 

costs in order to improve health. Under the Patient Protection and Affordable Care 

89 

Act (ACA), the eligible population expanded to include low-income adults under the 

age of 65 who previously did not qualify. 

Although some SNAP beneficiaries have been subject to work requirements since 

the 1980s, Medicaid work requirements are being rolled out for the first time in certain states. The ACA does not allow work requirements to be imposed as a condition 

for program participation in Medicaid, but states may apply for a waiver under Section 1115 of the Social Security Act to introduce work requirements if the Department of Health and Human Services determines doing so advances program objectives. Though the Obama Administration and the U.S. District Court for the District 

of Columbia (which rejected Kentucky’s proposal for work requirements in Medicaid) 

did not view work requirements as supporting core program goals, the Trump Administration has expressed its conviction that work requirements are allowable 

(Centers for Medicare & Medicaid Services 2018; Garfield, Rudowitz, and Damico 

2018; Stewart v. Azar). 

In the case of Medicaid, there are societal costs to taking health insurance away 

from an otherwise eligible person due to work requirements. For example, since 

there are rules requiring hospitals to provide medical care to those experiencing lifethreatening emergencies regardless of the individual’s ability to pay, those without 

insurance will in many cases seek and receive treatment in ways that are more expensive for society (Institute of Medicine 2003). Second, care delivered via insurance 

may include preventive care, check-ups, and other care that is more efficient than 

delaying care until a medical problem becomes severe enough to be treated in an 

emergency room. Thus, denying insurance may not reduce costs for society. Finally, 

evidence suggests that health insurance is valued by participants at less than its 

cost, making proposed work requirements less effective at raising employment 

(Finkelstein, Hendren, and Luttmer 2015). 

Box 1. 

Trends in Prime-Age Labor Force Participation 

For a number of decades labor force participation in the United States rose. 

This was especially true for prime-age (25–54) workers, whose participation 

rose from 65 percent in the middle of the 20th century to a peak of 84 percent 

in 1999. This persistent trend obscured an offsetting force: Prime-age men were 

steadily working less while prime-age women were working more. In 1949 97 

percent of prime-age men were in the labor force, but only 36 percent of women 

were. By 1999 those figures were 92 percent for men and 77 percent for women. 

Although women’s labor force participation rose in the 1980s and early 1990s, 

policymakers were concerned about the low labor force participation for single 

women with children, which remained relatively flat over that period. But for 

the past 20 years single women who head households with children have participated in the labor market at nearly the same rate as single women without 

children or married women without children. In fact, for the first time, in 2017 

the labor force participation rate of single women with children was higher 

(79.09 percent) than single women without dependents (79.06 percent.) Married 

women with children are still more likely to be out of the labor force (box figure 

1). More recently, overall labor force participation has declined, in part due to 

the aging population. Older working-age Americans (55–64) are less likely to 

work, with a labor force participation rate in 2017 around 72 percent for those 

aged 55–59 and 57 percent for those aged 60–64, compared to the current 82 

percent for those aged 25–54. 

These trends provide context for who is not currently working that society 

might prefer to work. Most prime-age men work, though nearly ten percent do 

not. Most unmarried prime-age women with children also work. A much smaller share of older Americans work. 

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Box Figure 1. 

Prime-Age Women’s Labor Force Participation, by Marital Status and Presence of Children under Age 18 

Source: Current Population Survey Annual Social and Economic Supplement (ASEC) (Bureau of Labor Statistics [BLS] 1977–2017); authors’ calculations. 

Evidence of the effect of Medicaid participation on employment for childless adults 

is decidedly mixed, with population differences and prevailing economic conditions 

as potential explanations for why studies have shown positive, negative, and no effects on employment (Buchmueller, Ham, and Shore-Sheppard 2016). Nevertheless, 

in the years since Medicaid expansion through the ACA, the preponderance of evidence suggests that Medicaid receipt has had little or positive effects on labor supply (Baicker, et al., 2014; Duggan, Goda, and Jackson 2017; Garthwaite, Gross, and 

Notowidigdo 2014; Gooptu, et al., 2016; Kaestner, et al., 2017), with notable exceptions (e.g., Dague, DeLeire, and Leininger 2017). 

While there is no research evidence regarding the effect of work requirements in 

Medicaid, last month, as the first state to implement a plan, Arkansas disenrolled 

program participants for failing to comply with work requirements. Arkansas terminated coverage for 4,353 citizens for failing to qualify for an exemption or to meet 

work requirements, while an additional 1,218 reported 20 hours per week of work 

activities and 2,247 reported an exemption in the month of August (Rudowitz and 

Musumeci 2018). 

For these programs to accomplish their goals, eligible people should not be dissuaded from applying for or improperly prevented from receiving those benefits. Evidence suggests that, under a variety of scenarios, the vast majority of those losing 

access to Medicaid would not lose access because they failed to meet a work requirement, but because they failed to successfully report their work/training activity or 

exemption (Garfield, Rudowitz, and Musumeci 2018; Goldman, et al., 2018). For example, in Arkansas, the only state currently implementing a work requirement in 

Medicaid, beneficiaries are required to report through an online portal, Access Arkansas (Arkansas Department of Human Services n.d.), despite a large number of 

program-eligible Arkansans who lack Internet access (Gangopadhyaya, et al., 2018). 

Characteristics of Those Who Would Face New Work Requirements 

Potential loss of access to SNAP and Medicaid on the basis of a work requirement 

is a function of whether the person is qualified for and verified as exempt from 

working and, if not, whether the person works sufficient hours each month to meet 

the requirement. Those who have a categorical exemption from work requirements— 

students, for example—are not required to work unless their status changes. Exemptions from work requirements can be applied individually for a variety of reasons, including temporary health problems, or, more broadly, when the unemployment rate for a location is high. Certain educational or training activities can also 

qualify for meeting hourly thresholds. 


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Box 2. 

Proposed Expansion of Work Requirements 

In April 2018 President Trump issued an Executive Order requiring that all 

means-tested programs be reviewed for the presence of current work requirements, the current state of enforcement and exemption, and, for those programs 

without current work requirements, whether such requirements could be added 

(White House 2018). 

This Executive Order builds on executive action to implement work requirements in Medicaid for the first time. In letters to governors (Price and Verma 

2017) and state Medicaid directors (Neale 2018), the U.S. Department of Health 

and Human Services (HHS) has offered guidance for states considering submitting a waiver request to apply work requirements for those receiving Medicaid. 

Since the Centers for Medicare & Medicaid Services offered guidance to the 

states with regard to Medicaid in 2017, 14 states have submitted work requirement proposals to HHS. HHS has approved four states’ plans, though Kentucky’s plan was vacated. The state of Arkansas has begun to enforce work requirements (Urban Institute 2018). State proposals vary in terms of the age 

range and household composition of exposure, who is exempt, and the hours required for work or approved activities. 

Additionally, in reauthorizing the farm bill, in June 2018 the House voted to 

expand the scope of who is required to work in order to receive SNAP benefits 

to include adults 18–59 with dependent children aged 6–18 as well as those 

aged 50–59 without dependents under the age of 6. As of publication, the conference committee is considering this proposal. 

To highlight one difficulty in designing a work requirement policy, consider the 

group of SNAP and Medicaid participants who usually are not working. Many individuals in this group are not expected to work, including the elderly, disabled, children, students, caregivers, and the infirm. In fact, nearly 2⁄3 of individuals who participate in SNAP are elderly, disabled, or children (USDA 2017a). 

Some of these characteristics are straightforward to observe and verify, such as 

age, school enrollment, and receipt of disability benefits. Other characteristics are 

difficult to observe and costly to verify, such as those with temporary medical conditions that make it impossible for them to work, those who have a chronic health 

condition but do not meet the high standard set for disability benefits (or have not 

applied for disability benefits), and those who do not have the skills, childcare, or 

transportation to obtain a job in their local economy at present. Another share of 

this group might be capable of employment but not willing to work; in that case 

the work requirements might or might not provide enough incentive for them to get 

jobs. 

Using data from the Current Population Survey Annual Social and Economic Supplement (ASEC), we quantify exposure to work requirements in 2017 based on broad 

demographic characteristics. To do so, we separate those who would likely qualify 

for a categorical exemption from those who would be required to work or who would 

qualify for a waiver to maintain eligibility. To be clear, while we model who is eligible for a categorical exemption, evidence suggests that not everyone in these groups 

will successfully navigate the system and obtain the exemption; in fact, estimates 

suggest that most people who lose coverage under this policy will be eligible for an 

exemption or already be working. For SNAP we followed the Federal guidelines for 

categorical exemption; for Medicaid we created a composite from among the different plans put forth by the states based on how frequently such groups are exempt. 

For SNAP, minors, those who are older than 59 years, students, those receiving 

disability benefits, and those with a child under the age of 6 are exempt from both 

current and new, proposed work requirements. The samples are further limited to 

U.S. citizens and non-active military. For simplification, we describe those aged 18– 

49 without dependents as being currently exposed to work requirements and those 

aged 18–59 with a dependent between the ages of 6 and 17 (inclusive) as well as 

those between the ages of 50 and 59 with no dependents under the age of 6 as newly 

required to meet work requirements or to participate in a training program in order 

to receive SNAP benefits. For the current group, some may live in places exempt 

from work requirements or have an unobserved good-cause exemption. 

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Figure 1. 

Exposure to Work Requirements among Adult SNAP Participants, 2017 

Source: ASEC (BLS 2018); authors’ calculations. 

How many adult SNAP participants are—or would be—exposed to work requirements? Figure 1 shows the entire adult population (18 or older) who reported SNAP 

participation in 2017. Each rectangle represents a share of the total population and 

whether the individuals in that share were eligible for a categorical exemption to 

work requirements (teal), were in a population currently exposed to a work requirement (green), or would be newly exposed to work requirements under the House 

proposal (purple). The shaded rectangles sum to 100 percent, the total adult SNAP 

participant population. 

Under the House bill parameters (described in box 2), combined with current work 

requirements, 1⁄3 of all adults who reported receiving SNAP benefits during 2017 

would be exposed to work requirements, though a portion of those impacted could 

apply for exemptions based on verified health- or work-related concerns. Some already face work requirements, but 22 percent of all participants would be newly exposed to work requirements under the House bill (purple). 

Figure 1 also shows the reasons some participants would be exempt from new requirements. The majority (67 percent) of adults currently receiving SNAP benefits 

would still be exempt from work requirements based on age, having a dependent 

under the age of 6, or having student or disability status. Some would be exempt 

for multiple reasons; we group them first by age, then by the presence of dependents, and then by student or disability status. For example, while figure 1 shows 

just 14 percent exempt due to disability, 24 percent of all adult SNAP recipients 

report receipt of disability benefits. 

In 2017, 2.2 million people who reported SNAP benefit receipt were exposed to 

work requirements during the year based on their demographic characteristics. 

Under the House proposal and based on 2017 numbers, this would more than double 

with 2.5 million adults aged 18–49 with dependent children aged 6–17 and 1.6 million adults aged 50–59 who would be exposed to work requirements nationally for 

the first time. 

In any household, there may be others who rely on the benefits, and not just the 

individual facing work requirements. The solution to concerns for other individuals 

in the household has typically been to waive work requirements for those who likely 

cannot work or who reside with those for whom shielding from benefit loss is a priority. Any reduction in SNAP benefits to adults would reduce the total amount of 

resources available to them to purchase food, including food for children. There are 

3.5 million children and 710,000 seniors in these households that would be exposed 

to possible benefit loss due to work requirements. 


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Figure 2. 

Exposure to Work Requirements among Adult Medicaid Participants, 2017 

Source: ASEC (BLS 2018); authors’ calculations. 

We perform the same exercise to show the share of Medicaid beneficiaries who 

are targeted by the policy based on potential new rules (figure 2). Minors, seniors 

(those over the age of 64), students, those receiving disability benefits or Medicare, 

and those with a child under the age of 6 are those who are generally eligible to 

be exempt from work requirements based on the plans that states submitted, 

though there is variation across states. We apply these categories to the entire adult 

Medicaid population, acknowledging that not every state has submitted a work requirement proposal and that the affected population varies by state plans. A nationwide expansion of these rules would target 22.4 million Americans for a possible loss 

of Medicaid coverage. 

Almost 1⁄2 of all adult Medicaid beneficiaries would be targeted by work requirements if the composite rules were applied nationwide. The largest share of those exempt from work requirements are parents with young children (22 percent) followed 

by those reporting disability income (13 percent) and Medicare/Medicaid dual enrollees (12 percent). About six percent of Medicaid participants are students. 

Volatility in the Low-Wage Labor Market 

The decline in labor force participation—especially among prime-age males—has 

drawn extensive attention in academic and policy circles (e.g., Abraham and 

Kearney 2018; Council of Economic Advisers [CEA] 2016; Juhn 1992). Some recent 

academic work has emphasized the fact that participation may be declining in part 

because an increasing number of labor force participants cycle in and out of the 

labor force: a pattern with direct relevance to proposed work requirements. The 

most comprehensive look at the behavior of people cycling through the labor force 

is Coglianese (2018). He documents that, among men, this group—which he refers 

to as ‘‘in-and-outs’’—takes short breaks between jobs, returns to the labor force fairly quickly (within 6 months), and, crucially, is no more likely than a typical worker 

to take another break out of the labor force. See also Joint Economic Committee 

(2018) for a discussion of the in-and-out behavior of nonworking prime-age men and 

reasons for their non-employment. 

SNAP or Medicaid participants who are employed but who work in jobs with volatile employment and hours would be at risk of failing work requirements. This 

group includes those who lose their job; for example, the House bill sanctions participants for months they are not working or in training for at least 20 hours per 

week, even if they were recently employed and are searching for a new job. Similarly, those who work in jobs with volatile hours would be sanctioned in the months 

that their average hours fell below 20 hours per week, whether due to illness, lack 


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of hours offered by the employer, or too few hours worked by the participant if they 

fail to receive a good cause waiver. 

Low-wage workers in seasonal industries such as tourism would potentially be eligible for SNAP in the months when they are working, but not in the months without employment opportunities. In other words, while benefits are most needed when 

an individual cannot find adequate work, under proposed work requirements these 

are the times that benefits would be unavailable. Disenrollment could make it more 

difficult for an individual to return to work—for example, if a person with chronic 

health conditions is unable to access needed care while they are between jobs. Any 

work requirement that banned individuals from participation for a considerable 

amount of time after failing the requirements would be even more problematic for 

those facing churn in the labor market. 

In a set of analyses, Bauer and Schanzenbach (2018a, 2018b) found that although 

many SNAP beneficiaries work on average more than 20 hours a week every month, 

they frequently switch between working more than 20 hours and a different employment status over a longer time horizon. Using the ASEC, those authors found that, 

over the course of 16 months between 2016 and 2018, about 20 percent of individuals aged 18–59 without a dependent child under age 6 switched between working 

more than 20 hours a week and working fewer than 20 hours per week, seeking employment, or being out of the labor force. 

In this economic analysis we examine labor force status transitions and the reasons given for not working among those targeted for work requirements over 24 consecutive months, January 2013–December 2014, using the first two waves of the 

Survey of Income and Program Participation (SIPP).1 By using a dataset that allows 

us to track workers over time, we identify the share of program participants who 

are consistently out of the labor force, the share who would consistently meet a 

work requirement, and the share who would be at risk of losing benefits based on 

failing to meet a work requirement threshold. 

We assume that to comply with a program’s work requirement, beneficiaries 

would have to prove each month that they are working for at least 20 hours per 

week averaged over the month, which is the typical minimum weekly requirement 

among the SNAP and Medicaid work requirement proposals. Looking first at SNAP 

and then at Medicaid, we calculate the share of program participants who would 

be exposed to benefit loss because they are not working sufficient hours would be 

exposed to benefit loss and who experienced a gap in employment, we describe the 

reasons given for not working to help quantify potential waiver eligibility. 

We remove from the analysis all those who have a categorical exemption. For 

SNAP and Medicaid, we exclude those outside the targeted age range, those with 

children under 6, full- or part-time students, and those reporting disability income. 

Those receiving Medicare are additionally excluded from the Medicaid analysis. As 

an instructive example, the labeled group ‘‘18–49, no dependents’’ is additionally exclusive of students and those reporting disability income. Program participants are 

those who reported receiving SNAP or Medicaid at any point between January 1, 

2013, and December 31, 2014. 

We categorize each individual in each month into one of four categories: (1) employed and worked more than 20 hours a week on average, (2) employed and worked 

less than 20 hours a week on average, (3) unemployed and seeking employment, or 

(4) not in the labor force. If a worker was employed at variable weekly hours but 

maintained hours above the monthly threshold (80 hours for a 4 week month and 

120 hours for a 5 week month), then we categorize them as ‘‘employed and worked 

more than 20 hours a week for that month.’’ Individuals are considered to have a 

stable employment status if they do not change categories over 2 years, and are considered to have made an employment status transition if they switched between any 

of these categories at least once. There is no employment status transition when a 

worker changes jobs but works more than 20 hours a week at each job. 

Exposure To Proposed Work Requirements in SNAP 

Among working-age adults, SNAP and Medicaid serve a mix of the unemployed, 

low-income workers, and those who are not in the labor force (USDA 2017b). Figure 

3 describes employment status by those groups who are currently exposed to work 

requirements and who would be newly subject to work requirements under the 

House proposal. 

During the Great Recession, waivers to work requirements were implemented nationwide. During the time period covered by the SIPP (2013–14), eight states 

stopped implementing these waivers fully, and ten states partially (Silberman 

2013).2 For analytic purposes, we look at employment status transitions among 18 

to 49 year olds without dependents as the demographic group currently exposed to 

work requirements, regardless of whether they lived in state in which waivers were 

95 

implemented during 2013 and 2014. Those receiving SNAP benefits who are in the 

demographic group currently exposed to work requirements—adults aged 18–49 

with no dependents—generally participate in the labor market, with just 25 percent 

consistently not in the labor force (discussed below). While 58 percent worked at 

least 20 hours per week in at least 1 month over 2 years, 25 percent were over the 

threshold at some point but fell below the 20 hour threshold during at least 1 month 

over 2 years. Very few are always working less than 20 hours a week or always unemployed (less than two percent in either case), and 14 percent move across these 

categories. 

Figure 3. 

Employment Status over Two Years, SNAP Participants 

Source: Survey of Income and Program Participation (SIPP) (U.S. Census 

Bureau 2013–14); authors’ calculations. 

Those aged 18–49 who are not subject to the 3 month time limit because they 

have a dependent aged 6–17 but who would face it under the House proposal demonstrate a similar distribution of employment status as those without a dependent, 

but they are more likely to work. There are fewer individuals who are always out 

of the labor force (14 percent) and more that consistently work 20 hours a week or 

more (46 percent).3 There is also substantial month-to-month churn (16 percent) between working above 20 hours per week and less than 20 hours per week and churn 

(12 percent) between working above 20 hours per week and being either unemployed 

or not in the labor force. This highlights the number who are actively in the workforce and meeting the 20 hour threshold in at least 1 month, but who might fail 

new work requirements from time to time. 

Older SNAP participants (aged 50–59 without dependents under age 6) who 

would also be newly exposed to work requirements and time limits have a distinct 

employment status pattern from those aged 18–49. Almost 1⁄2 were permanently out 

of the labor force in large part due to their health. While 23 percent worked consistently above the threshold of 20 hours a week, nearly as many (18 percent) worked 

above the threshold at some point but also below the threshold at some point, meaning they would fail the work requirement despite having sometimes met the threshold. 

There is a meaningful portion of SNAP participants in the labor force and working, but not all are working above the monthly work requirement threshold consistently. Coglianese’s (2018) finding that workers who are in and out of the labor force 

are not more likely to take another break later on suggests it is unclear how much 

more consistently work requirements would attach these people to the labor force. 

We next examine the reasons given for not working over the 2 year period, first 

for those aged 18–49 with a dependent between the ages of 6 and 17, and second 

for those 50 to 59 without a dependent under age 6 (figures 4a and 4b). The green 

crosshatch shows the share of the population that did not experience a gap in employment over the 2 year period, and thus were never asked why they were not 

working. Among those who were asked why they were not working for pay during 

at least 1 week, we report the reason for not working in months they were not working. Those in solid shades of green were in the labor force but experienced at least 

one spell of unemployment or labor force nonparticipation. Those in the blue were 


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out of the labor force for the entire 2 year period. Each person is assigned one reason—their most frequent reason—for not working. 

Figure 4a. 

Most-Frequent Reason for Not Working for Pay, SNAP Participants Aged 

18–49 with Dependents Age 6–17 

Source: SIPP (U.S. Census Bureau 2013–14); authors’ calculations. 

Figure 4b. 

Most-Frequent Reason for Not Working for Pay, SNAP Participants Aged 

50–59 with No Dependent under Age 6 


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Source: SIPP (U.S. Census Bureau 2013–14); authors’ calculations. 

Among those aged 18–49 with dependents aged 6–17 who are newly exposed to 

work requirements (figure 4a), 86 percent were in the labor force at some point over 

2 years but not all worked stably. Among those who did not work for pay for at least 

1 week but were in the labor force, the overwhelming majority gave work-related 

reasons (68 percent), such as temporary loss of job, temporary loss of hours (e.g., 

weather-related, not getting enough shifts, etc.), or a company shutting down a plant 

or location. Other large groups include those who are caregivers and those with 

health concerns. In a program with extensive good-cause waivers, it appears the 

bulk of these workers would not lose benefits if waivers were implemented with fidelity; but the administrative burden required to sort those with work-related problems from those who choose to not work could be quite high. 

Among those out of the labor force for the entire 2 year period, more than 1⁄2 cite 

health reasons for being out of the labor force. In total, 0.3 percent of those aged 

18–49 who would be newly exposed to work requirements and who were labor force 

non-participants said that they were not interested in working. 

Among individuals aged 50–59 (figure 4b), far more are out of the labor force consistently and far fewer have stable work. Overall, health (87 percent) and work-related (eight percent) issues dominate. The prevalence of health problems is striking 

considering we have already limited the sample to those not receiving disability payments. Fewer than one percent were retired or not interested in working. 

The share of older SNAP participants listing caregiving as a reason for being not 

in the labor force is notably smaller than the share of the younger SNAP participant 

population. 

Roughly 11 percent of SNAP participants aged 18–49 with a dependent 6–17 that 

were out of the labor force for the entire 24 month period list caregiving as a reason 

for not being in the labor force. However, even 11 percent is smaller than many 

might expect. Many caregivers who are not in the labor force are in two-adult 

households where the other adult is working. In addition, many are in households 

with dependents aged 0–5, and those households are exempt from work requirements. 

In summary, based on 2013–14 data, 5.5 million adult SNAP participants would 

be newly exposed to work requirements with 3.8 million who would have failed them 

at some point in this 2 year window. Notable among those who were asked about 

a spell of not working, 2.1 million report health or disability issues and 1.5 million 

report work-related issues. Only about 90,000 list a lack of interest or early retirement as their reason for not working. 

Exposure to Proposed Work Requirements in Medicaid 

We study the work participation of Medicaid beneficiaries in a similar manner. 

Unlike SNAP, there is no current population of participants who face work requirements across the country to use as a comparison group. As noted above, previous 

Administrations and the courts have not viewed Medicaid work requirements as 

supporting core program goals; there are substantive doubts about whether work requirements for health insurance are appropriate. Nevertheless, we consider the employment status of Medicaid beneficiaries to illuminate how such requirements 

would function. 

Since Medicaid beneficiaries do not currently face work requirements, we do not 

separately examine the population aged 18–49 without dependents. It is instructive 

to differentiate the work status transitions of younger (aged 18–49) and older (aged 

50–64) Medicaid beneficiaries, restricted to those who either have a dependent 6– 

17 or no dependents, i.e., no dependents under the age of 6. We identify employment 

status transitions and the reasons given for not working among those targeted for 

work requirements over 24 consecutive months (January 2013–December 2014). 

Figure 5 shows that over 2 years (2013 and 2014), 80 percent of Medicaid beneficiaries aged 18–49 without a dependent child under age 6 were in the labor force 

at some point. While about 40 percent consistently worked over the 20 hour threshold, 25 percent worked more than 20 hours at some point but would potentially lose 

benefits for falling below the 20 hour threshold for a month at another point. 

The picture is quite different for older Medicaid beneficiaries (50 to 64) who would 

be exposed to work requirements. Of that population, 44 percent were out of the 

labor force for all 24 months. About 29 percent worked consistently more than 20 

hours a week and about 17 percent worked more than 20 hours at least once but 

failed to do so every month. The reasons given among working-age adult Medicaid 

beneficiaries not working for pay suggest that labor market reasons dominate 

among labor force participants and health reasons dominate among labor force nonparticipants (figures 6a and 6b). Once again, only a small number of labor force nonparticipants are not interested in work or are retired. 

98 

Figure 5. 

Employment Status over Two Years, Medicaid Participants 

SIPP (U.S. Census Bureau 2013–14); authors’ calculations. 

Figure 6a. 

Most-Frequent Reason for Not Working for Pay, Medicaid Participants 

Aged 18–49 with No Dependents under Age 6 


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Figure 6b. 

Most-Frequent Reason for Not Working for Pay, Medicaid Participants 

Aged 50–64 with No Dependents under Age 6 

Source: SIPP (U.S. Census Bureau 2013–14); authors’ calculations. 

Among older participants of Medicaid (aged 50–64 without a dependent under age 

6, the population making up 37 percent of the sample population), 35 percent of 

those with Medicaid coverage are out of the labor force for health reasons; this 

group represents 79 percent of those who were not in the labor force for the full 

2 years. It is worth noting that work requirements for this group would necessitate 

either lax requirements with a very large portion of the population getting waivers, 

or an administratively burdensome process to determine which individual’s health 

concerns truly limit them from work. 

Work Status in a Snapshot vs. Two Years 

In its report on work requirements, the Council of Economic Advisers (CEA 2018) 

looked at employment among adult program participants for the month of December 

2013 using the SIPP and found that about three in five participants worked fewer 

than 20 hours per month. The CEA concludes that this level of work—or lack thereof—‘‘suggest[s] that legislative changes requiring them to work and supporting their 

transition into the labor market, similar to the approach in TANF, would affect a 

large share of adult beneficiaries and their children in these non-cash programs’’.1–2

A critical empirical takeaway from the analysis presented herein is that frequent 

movement between labor status categories over time increases the number of people 

exposed to losing benefits for failing to consistently meet a work requirement, and 

decreases the number of people who are entirely out of the labor market. We now 

examine how the analysis of work experiences differs when we compare a snapshot 

in time—one month—with analysis that includes transitions across status over 2 

years. When we compare the 1 month of SIPP data cited in the CEA report (December 2013) against 24 months, we find that fewer program participants are labor 

force non-participants and fewer meet the work requirement threshold. 

Figure 7 demonstrates how observed employment status is different in 1 month 

versus 2 years. The first two bars show employment status categories for the full 

population aged 18–59 without dependents aged 0–5, disability payments, or status 

as students. The second two bars show employment status categories in 1 month 

and 2 years for SNAP participants aged 18–59 with no dependents aged 0–5, disability payments, or status as students. An ‘‘other’’ transition during a 1 month period are those who report being unemployed and a labor force non-participant during different weeks within December 2013. 


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Figure 7. 

Employment Status in One Month vs. Two Years, SNAP 

SIPP (U.S. Census Bureau 2013–14); authors’ calculations. 

The first feature that jumps out of the data is that far fewer people are out of 

the labor force than is generally assumed. While a 1 month snapshot shows that 

20 percent of the overall population is not working (either out of the labor force or 

unemployed), over the course of 2 years more than 90 percent of the overall population is employed at some point. Many people are not truly on the sidelines as 

much as they are cycling in and out of the game. Furthermore, fewer people are 

solidly in the 20+ hours workforce. The share of the overall population that stably 

works more than 20 hours per week falls from 76 percent in the 1 month snapshot 

to 69 percent over 2 years. 

Looking only at those who participated in SNAP at any point during the 2 year 

period, the 1 month snapshot is also different from the 2 year, both in terms of the 

number of participants out of the labor force and the number who would retain benefits under the work requirement proposal. Instead of 42 percent being out of the 

labor force and roughly 11 percent unemployed in the 1 month snapshot—leading 

to more than 1⁄2 of the group being labeled ‘‘not working’’ in the 1 month snapshot— 

roughly 29 percent are out of the labor force and just one percent are persistently 

unemployed over 2 years, meaning fewer than 1⁄3 are not working consistently. Recall that the higher ‘‘not working’’ rate among SNAP beneficiaries is largely driven 

by those aged 50–59. SNAP recipients aged 18–49 without dependents have a ‘‘not 

working’’ rate of 25 percent over 2 years, and those with dependents aged 6–17 have 

a ‘‘not working’’ rate of just 14 percent. Almost a quarter of SNAP participants 

would fail the work requirements some months and pass them in others, with the 

majority giving work-related reasons for their change in status. 

A similar pattern holds for Medicaid beneficiaries: the monthly snapshot overstates the number of labor force non-participants and understates those who would 

meet a work requirement. There is a ten percentage point-reduction in the share 

of those not working over 1 month (39 percent) versus 2 years (29 percent). Fortytwo percent would meet the work requirement in 1 month, but only 36 percent do 

over 2 years. In addition, in the 2 year sample 22 percent of participants work over 

20 hours in at least 1 month in the sample but fail to in other months (figure 8). 


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Figure 8. 

Employment Status in One Month vs. Two Years, Medicaid 

SIPP (U.S. Census Bureau 2013–14); authors’ calculations. 

Conclusion 

The combination of a strong labor market, work requirements to receive cash benefits through TANF, and work incentives generated by the EITC raised labor force 

participation rates among single mothers in the mid-1990s (Ziliak 2016), leading 

some to believe that further participation gains could be obtained by extending only 

the work requirement component to other programs (Haskins 2018; CEA 2018). 

Work requirements are intended to counter any work disincentives that come 

from a social safety net and to ensure that society is not unnecessarily supporting 

people who could otherwise support themselves. At the same time, such work requirements add administrative complexity to social programs and risk keeping benefits from parts of the population that should be receiving them. This economic analysis establishes a set of facts that are relevant when considering the expansion of 

work requirements. 

What types of populations will face these new work requirements? How many 

would fail to meet the requirements? Do program participants appear to already be 

in the labor force facing work-related constraints on hours or do they choose not to 

work? And how many would in theory be eligible for waivers relative to those individuals that society would like to push toward work? 

A large number of SNAP and Medicaid participants who would face new work requirements cycle in and out of the labor force and would thus lose benefits at certain times. Among those who are in the labor force, spells of unemployment are either due to job-related concerns or health issues. Very few reported that they were 

not working due to lack of interest. 

Among those out of the labor force for the entire 2 year period, health concerns 

are the overriding reason for not working, even after removing those who receive 

disability benefits from the sample. The older portion of the population newly exposed to work requirements is more likely to be out of the labor force for extended 

periods of time. Among this group, again, health reasons are the overriding factor 

in not working. Work requirements for this group might push more onto disability 

rolls, make the disability adjudication even more consequential, and require a separate health investigation to settle all the necessary waivers. Failure to receive a 

waiver would result in disenrollment; losing access to these programs would reduce 

resources available to purchase food and health insurance among otherwise eligible 

households. 

For those who qualify for exemptions, satisfy waiver requirements, or work 

enough to meet the requirements, there are still significant informational and administrative barriers to compliance. Program participants must understand how the 

work requirement policy relates to them, obtain and submit documentation, and do 

so at the frequency prescribed by the state (Wagner and Solomon 2018). Frequent 

exposure to verification processes, such as the monthly reporting periods prescribed 

in the Agricultural Act of 2014 (the farm bill) and many states’ Medicaid proposals, 

increases the administrative burden on participants and enforcers, the likelihood of 

error, and cost (Bauer and Schanzenbach 2018b). These continuing roadblocks to 

participation, with attendant informational and transactional costs, are likely to result in lower take-up among the eligible population and disenrollment (Finkelstein 

and Notowidigdo 2018). 


11602051.eps
102 

Looking at snapshots of work experience, such as a single month, inflates both 

the number of SNAP and Medicaid participants who are out of the labor force and 

the number of people who work sufficient hours to satisfy work requirements. Over 

24 consecutive months the number of SNAP and Medicaid program beneficiaries not 

working or seeking work as well as those working consistently above 20 hours fall 

substantially. 

There are safety net levers that can be used to pull those out of the labor force 

into work. Steps such as increasing the EITC might be a very effective way to increase work participation in this group without the same administrative burdens 

and negative spillovers to vulnerable populations. (See Hoynes, Rothstein, and 

Ruffini 2017 for a specific proposal along these lines.) That proposal is estimated 

to increase participation by 600,000 people. Raising the returns to work via the 

EITC or other measures, creating training or educational opportunities that can increase individuals’ human capital, and providing child care or improved treatment 

and medical care to reduce health barriers to work could make full attachment to 

the labor force more viable for many individuals. 

Endnotes 

1. See technical appendix tables 1 and 2 for additional work status transition statistics. 

2. The states not implementing able-bodied adult without dependents waivers at 

some point during 2013–14 are: Delaware, Guam, Iowa, Kansas, Nebraska, Oklahoma, Utah, Virginia, and Wyoming. States implementing a partial waiver (partial 

referring to different parts of the state or only part of the year): Colorado, Minnesota, New Hampshire, New York, North Dakota, Ohio, South Dakota, Texas, 

Vermont, Wisconsin. 

3. Those who meet the 20 hour threshold monthly hours variable include both 

those who meet the threshold every week and those whose hours varied each week 

but averaged to 20 hours per week each month. The volatility of their hours may 

suggest they are more likely to fail the work requirement threshold but they did 

not do so over the 2 year window. 

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Appendix 

Appendix Table 1. 

Employment Status, SNAP Participants 

Stable 

(not in 

labor 

force) 

Stable 

(unemployed) 

Stable 

(employed 

20+ hours) 

Stable 

(employed 

<20 hours) 

Transitioned 

between 20+ 

hours and 

<20 hours 

Transitioned 

between 20+ 

hours and 

unemployment or not 

in labor force 

Other 

transition 

Age 18–49, no dependents 

2013 34.3% 5.5% 33.3% 4.1% 7.9% 4.9% 10.0% 

2014 32.6% 5.5% 37.4% 3.5% 9.1% 7.2% 4.7% 

2013–14 24.6% 1.7% 32.6% 1.7% 16.0% 9.3% 14.1% 

Age 18–49, dependent 6–17 

2013 20.4% 4.9% 49.9% 2.4% 8.9% 6.0% 7.5% 

104 

Appendix Table 1.—Continued 

Employment Status, SNAP Participants 

Stable 

(not in 

labor 

force) 

Stable 

(unemployed) 

Stable 

(employed 

20+ hours) 

Stable 

(employed 

<20 hours) 

Transitioned 

between 20+ 

hours and 

<20 hours 

Transitioned 

between 20+ 

hours and 

unemployment or not 

in labor force 

Other 

transition 

2014 21.0% 4.2% 50.2% 2.4% 8.6% 9.9% 3.8% 

2013–14 14.0% 0.7% 45.6% 0.4% 15.9% 12.3% 11.3% 

Age 50–59, no dependent under 6 

2013 50.4% 4.6% 25.8% 2.6% 5.7% 3.9% 7.0% 

2014 53.3% 3.5% 26.1% 2.5% 5.9% 5.1% 3.6% 

2013–14 45.7% 1.3% 23.0% 1.4% 10.1% 7.9% 10.7% 

Source: SIPP (U.S. Census Bureau 2013–14); authors’ calculations. 

Note: The sample is limited to U.S. citizens, non-active military, who reported receiving SNAP benefits at any 

point between January 2013 and December 2014. Only respondents with 24 months of data were included. Those 

with children under age 6, full- or part-time students, and those who reported receiving disability benefits were 

excluded from the sample based on categorical work requirement exclusions. Those who were assigned to ‘‘stable’’ 

categories were observed as not in the labor force, unemployed, above the 20 hour threshold, or below the 20 hour 

threshold per week. Those who were stable and employed more than 20 hours a week were assigned either by 

meeting the threshold every week or because the monthly hours total averaged to above 20 hours per week. Regardless of the number of transitions made, each person who was observed as switching between work statuses 

was assigned to one group in the following order: first, transitioned between more than and less than 80 hours per 

month; second, transitioned between more than 80 hours per month and unemployment or labor force nonparticipation; third, other. ‘‘Other’’ includes those who transitioned between less than 80 hours per month and unemployment or labor force nonparticipation as well as those who transitioned between unemployment and labor force 

nonparticipation. 

Appendix Table 2. 

Employment Status, Medicaid Participants 

Stable 

(not in 

labor 

force) 

Stable 

(unemployed) 

Stable 

(employed 

20+ hours) 

Stable 

(employed 

<20 hours) 

Transitioned 

between 20+ 

hours and 

<20 hours 

Transitioned 

between 20+ 

hours and 

unemployment or not 

in labor force 

Other 

transition 

Age 18–49, no dependent under 6 

2013 27.7% 3.8% 42.6% 3.6% 8.1% 4.1% 10.0% 

2014 26.4% 4.2% 46.1% 3.3% 7.3% 7.6% 5.1% 

2013–14 19.6% 1.1% 39.6% 1.1% 14.8% 10.9% 12.8% 

Age 50–64, no dependent under 6 

2013 48.4% 3.2% 32.9% 3.8% 5.5% 2.2% 4.0% 

2014 51.2% 2.7% 29.9% 3.5% 5.0% 4.6% 3.1% 

2013–14 44.1% 0.8% 28.5% 1.8% 11.7% 5.0% 8.2% 

Source: SIPP (U.S. Census Bureau 2013–14); authors’ calculations. 

Note: The sample is limited to U.S. citizens, non-active military, who reported receiving Medicaid benefits at 

any point between January 2013 and December 2014. Only respondents with 24 months of data were included. 

Those with children under age 6, full- or part-time students, those who reported receiving Medicare, and those 

who reported receiving disability benefits were excluded from the sample based on categorical work requirement 

exclusions. Those who were stable labor force non-participants are contrasted with those who were in the labor 

force (working or seeking work) at least once during the 2 year period. Those who were assigned to ‘‘stable’’ categories were observed as not in the labor force, unemployed, working above the 20 hour threshold, or working 

below the 20 hour threshold per week. Those who were stable and employed more than 80 hours per week were assigned either by meeting the 20 hours per week threshold every week or because the monthly hours total averaged 

above 20 hours per week. Regardless of the number of transitions made, each person who was observed as switching between work statuses was assigned to one group in the following order: first, transitioned between more than 

and less than 80 hours per month; second, transitioned between more than 80 hours per month and unemployment or labor force nonparticipation; third, other. ‘‘Other’’ includes those who transitioned between less than 80 

hours per month and unemployment or labor force nonparticipation as well as those who transitioned between unemployment and labor force nonparticipation. 

Technical Appendix 

Box Figure 1. Prime-Age Women’s Labor Force Participation, by Marital 

Status and Presence of Children under Age 18 

Source: Current Population Survey Annual Social and Economic Supplement (ASEC) (Bureau of Labor Statistics [BLS] 1977–2017); authors’ calculations. 

Note: ‘‘Prime-age’’ indicates ages 25 to 54, inclusive. ‘‘Married’’ is defined 

by women who have a spouse in the household or not in the household. 

‘‘Single’’ is defined as all other women, including divorced and widowed 

women. ‘‘With children’’ is defined as having at least one child in the household under the age of 18. ‘‘No children’’ is defined as having no children in 

105 

the household under the age of 18. Population counts calculated using the 

Annual Social and Economic Supplement weight. 

Figure 1. Exposure to Work Requirements among Adult SNAP Participants, 2017 

Source: ASEC (BLS 2018); authors’ calculations. 

Notes: Those who would be exempt from work requirements if the House 

bill work requirements were passed include those over the age of 59, those 

with a dependent under the age of 6, full- or part-time students, and those 

who receive disability benefits. While in some states work requirements are 

waived for those aged 18–49 with no dependents, state-level differences are 

not accounted for in identifying those who are currently exposed to work 

requirements. Population counts calculated using the Annual Social and 

Economic Supplement weight among U.S. citizens over the age of 18 who 

reported receiving SNAP benefits at some point during 2017. 

Figure 2. Exposure to Work Requirements among Adult Medicaid Participants, 2017 

Source: ASEC (BLS 2018); authors’ calculations. 

Note: States applying for waivers to add work requirements to Medicaid 

have identified different categorical exemptions and conditions for waivers. 

For this exercise, we identified the most frequent categorical exemptions 

and applied those rules nationally. Those who are over the age of 64 or who 

are dual Medicare enrollees are exempt, those receiving disability income 

are exempt, those with a dependent under the age of 6 are exempt, and 

full- or part-time students are exempt. Population counts are calculated 

using the Annual Social and Economic Supplement weight among U.S. citizens over the age of 18 who reported receiving Medicaid benefits at some 

point during 2017. 

Figure 3. Employment Status over Two Years, SNAP Participants 

Source: Survey of Income and Program Participation (SIPP) (U.S. Census Bureau 2013–14); authors’ calculations. 

Note: The sample is limited to U.S. citizens, non-active military, aged 

18–59 who reported receiving SNAP benefits at any point between January 

2013 and December 2014. Only respondents with 24 months of data were 

included. Those with children under age 6, full- or part-time students, and 

those who reported receiving disability benefits were excluded from the 

sample based on categorical work requirement exclusions. Those who were 

assigned to ‘‘stable’’ categories were observed as not in the labor force, unemployed, working above the 20 hour threshold, or working below the 20 

hour threshold per week. Those who were stable and employed more than 

20 hours a week were assigned either by meeting the threshold every week 

or because the monthly hours total averaged to above 20 hours per week. 

Regardless of the number of transitions made, each person who was observed as switching between work statuses was assigned to one group in 

the following order: first, transitioned between more than and less than 80 

hours per month; second, transitioned between more than 80 hours per 

month and unemployment or labor force nonparticipation; third, other. 

‘‘Other’’ includes those who transitioned between less than 80 hours per 

month and unemployment or labor force nonparticipation as well as those 

who transitioned between unemployment and labor force nonparticipation. 

Figures 4a and 4b. Most Frequent Reason for Not Working for Pay, SNAP 

Participants 

Source: SIPP (U.S. Census Bureau 2013–14); authors’ calculations. 

Notes: The sample is limited to U.S. citizens, non-active military, aged 

18–59 who reported receiving SNAP benefits at any point between January 

2013 and December 2014. Only respondents with 24 months of data were 

included. Those with children under age 6, full- or part-time students, and 

those who reported receiving disability benefits were excluded from the 

sample based on categorical work requirement exclusions. Figure 4a is further restricted to those between the ages of 18 and 49 with a dependent 

between the ages of 6 and 17 while figure 4b is limited to those between 

the ages of 50 and 59 with no dependents under the age of 6. Each person’s 

most frequent response for why they were not working was used to calculate the distribution; ties were assigned in descending order by work-related, health or disability, caregiving, student, early retirement, not interVerDate Aug 31 2005 11:16 Jun 14, 2019 Jkt 041481 PO 00000 Frm 00111 Fmt 6633 Sfmt 6621 P:\DOCS\116-02\36188.TXT BRIAN
106 

ested in working, and other. The ‘‘stable work, not asked’’ group indicates 

that the respondent was never asked this survey question because they 

were working for pay every week. ‘‘Work-related’’ includes not being able 

to find work, being laid off, or working for more than 15 hours for no pay 

at a family business or farm. ‘‘Health or disability’’ includes being unable 

to work because of an injury, illness, or chronic health condition or disability. ‘‘Caregiving’’ includes those not working due to pregnancy or recent 

childbirth, or taking care of children or other persons. Students included in 

the sample are those who did not report that they were enrolled full- or 

part-time but reported not working because they were going to school. 

Figure 5. Employment Status over Two Years, Medicaid Participants 

Source: SIPP (U.S. Census Bureau 2013–14); authors’ calculations. 

Note: The sample is limited to U.S. citizens, non-active military, aged 

18–64 who reported receiving Medicaid benefits at any point between January 2013 and December 2014. Only respondents with 24 months of data 

were included. Those with children under age 6, full- or part-time students, 

those who reported receiving Medicare, and those who reported receiving 

disability benefits were excluded from the sample based on categorical work 

requirement exclusions. See technical appendix entry for figure 3 with regard to employment status assignment. 

Figures 6a and 6b. Most Frequent Reason for Not Working for Pay, Medicaid Participants 

Source: SIPP (U.S. Census Bureau 2013–14); authors’ calculations. 

Note: The sample is limited to U.S. citizens, non-active military, aged 

18–64 who reported receiving Medicaid benefits at any point between January 2013 and December 2014. Only respondents with 24 months of data 

were included. Those with children under age 6, full- or part-time students, 

those who reported receiving Medicare, and those who reported receiving 

disability benefits were excluded from the sample based on categorical work 

requirement exclusions. Those who were stable labor force non-participants 

are contrasted with those who were in the labor force (working or seeking 

work) at least once during the 2 year period. Figure 6a is further restricted 

to those between the ages of 18 and 49 with a dependent between the ages 

of 6 and 17, whereas figure 6b is limited to those between the ages of 50 

and 64 with no dependents under the age of 6. See technical appendix entry 

for figures 4a and 4b with regard to reason assignment. 

Figure 7. Employment Status in One Month vs. Two Years, SNAP 

Source: SIPP (U.S. Census Bureau 2013–14); authors’ calculations. 

Note: The sample is limited to U.S. citizens, non-active military, aged 

18–59. Only respondents with 24 months of data were included. Those currently exposed to work requirements, those with children under age 6, fullor part-time students, and those who reported receiving disability benefits 

were excluded from the sample. The 1 month and 2 year samples differ by 

reported SNAP benefit receipt. In the 1 month sample, ‘‘other’’ refers to 

those who switched between labor force nonparticipation and unemployment during the month of December 2013, the month chosen in the SIPP 

by CEA for its report on work requirements. 

Figure 8. Employment Status in One Month vs. Two Years, Medicaid 

Source: SIPP (U.S. Census Bureau 2013–14); authors’ calculations. 

Note: The sample is limited to U.S. citizens, non-active military, aged 

18–64. Only respondents with 24 months of data were included. Those with 

children under age 6, full- or part-time students, those who reported receiving Medicare, and those who reported receiving disability benefits were excluded from the sample based on categorical work requirement exclusions. 

The 1 month and 2 year samples differ by reported Medicaid benefit receipt. In the 1 month sample, ‘‘other’’ refers to those who switched between 

labor force nonparticipation and unemployment during the month of December 2013. 

Advisory Council 

GEORGE A. AKERLOF, University Professor, Georgetown University 

ROGER C. ALTMAN, Founder & Senior Chairman, Evercore 

KAREN L. ANDERSON, Senior Director of Policy & Communications, Becker Friedman Institute for Research in Economics, The University of Chicago 

107 

ALAN S. BLINDER, Gordon S. Rentschler Memorial Professor of Economics & Public Affairs, Princeton University; Nonresident Senior 

Fellow, The Brookings Institution 

ROBERT CUMBY, Professor of Economics, Georgetown University 

STEVEN A. DENNING, Chairman, General Atlantic 

JOHN M. DEUTCH, Institute Professor, Massachusetts Institute of Technology 

CHRISTOPHER EDLEY, JR., Co-President & Co-Founder, The Opportunity Institute 

BLAIR W. EFFRON, Partner, Centerview Partners LLC 

DOUGLAS W. ELMENDORF, Dean & Don K. Price Professor of Public Policy, Harvard Kennedy School 

JUDY FEDER, Professor & Former Dean, McCourt School of Public Policy, Georgetown University 

ROLAND FRYER, Henry Lee Professor of Economics, Harvard University 

JASON FURMAN, Professor of the Practice of Economic Policy, Harvard Kennedy School;Senior Counselor, The Hamilton Project 

MARK T. GALLOGLY, Cofounder & Managing Principal, Centerbridge Partners 

TED GAYER, Executive Vice President Joseph A. Pechman Senior Fellow, Economic Studies, The Brookings Institution 

TIMOTHY F. GEITHNER, President, Warburg Pincus 

RICHARD GEPHARDT, President & Chief Executive Officer, Gephardt Group Government Affairs 

JOHN GRAY, President & Chief Operating Officer, Blackstone 

ROBERT GREENSTEIN, Founder & President, Center on Budget and Policy Priorities 

MICHAEL GREENSTONE, Milton Friedman Professor in Economics & the College Director of the Becker Friedman Institute for Research 

in Economics; Director of the Energy Policy Institute, University of Chicago 

GLENN H. HUTCHINS, Co-founder, North Island 

JAMES A. JOHNSON, Chairman, Johnson Capital Partners 

LAWRENCE F. KATZ, Elisabeth Allison Professor of Economics, Harvard University 

MELISSA S. KEARNEY, Professor of Economics, University of Maryland; Nonresident Senior Fellow, The Brookings Institution 

LILI LYNTON, Founding Partner, Boulud Restaurant Group 

HOWARD S. MARKS, Co-Chairman, Oaktree Capital Management, L.P. 

MARK MCKINNON, Former Advisor to George W. Bush; Co-Founder, No Labels 

ERIC MINDICH, Chief Executive Officer & Founder, Eton Park Capital Management 

ALEX NAVAB, Former Head of Americas Private Equity, KKR; Founder, Navab Holdings 

SUZANNE NORA JOHNSON, Former Vice Chairman, Goldman Sachs Group, Inc. 

PETER ORSZAG, Vice Chairman & Global Co-Head of Healthcare, Lazard; Nonresident Senior Fellow, The Brookings Institution 

RICHARD PERRY, Managing Partner & Chief Executive Officer, Perry Capital 

PENNY PRITZKER, Chairman, PSP Partners 

MEEGHAN PRUNTY, Managing Director, Blue Meridian Partners Edna McConnell Clark Foundation 

ROBERT D. REISCHAUER, Distinguished Institute Fellow & President Emeritus, Urban Institute 

ALICE M. RIVLIN, Senior Fellow, Economic Studies, Center for Health Policy, The Brookings Institution 

DAVID M. RUBENSTEIN, Co-Founder & Co-Executive Chairman, The Carlyle Group 

ROBERT E. RUBIN, Former U.S. Treasury Secretary, Co-Chair Emeritus, Council on Foreign Relations 

LESLIE B. SAMUELS, Senior Counsel, Cleary Gottlieb Steen & Hamilton LLP 

SHERYL SANDBERG, Chief Operating Officer, Facebook 

DIANE WHITMORE SCHANZENBACH, Margaret Walker Alexander Professor, Director, The Institute for Policy Research, Northwestern 

University; Nonresident Senior Fellow, The Brookings Institution 

STEPHEN SCHERR, Chief Executive Officer, Goldman Sachs Bank USA 

RALPH L. SCHLOSSTEIN, President & Chief Executive Officer, Evercore 

ERIC SCHMIDT, Technical Advisor, Alphabet Inc. 

ERIC SCHWARTZ, Chairman & CEO, 76 West Holdings 

THOMAS F. STEYER, Business Leader & Philanthropist 

LAWRENCE H. SUMMERS, Charles W. Eliot University Professor, Harvard University 

LAURA D’ANDREA TYSON, Professor of Business Administration & Economics Director, Institute for Business & Social Impact, Berkeley-Haas School of Business 

JAY SHAMBAUGH, Director 

Abstract 

Basic assistance programs such as the Supplemental Nutrition Assistance Program (SNAP, formerly the Food Stamps Program) and Medicaid ensure families 

have access to food and medical care when they are low-income. Some policymakers 

at the Federal and state levels intend to add new work requirements to SNAP and 

Medicaid. In this paper, we analyze those who would be impacted by an expansion 

of work requirements in SNAP and an introduction of work requirements into Medicaid. We characterize the types of individuals who would face work requirements, 

describe their labor force experience over 24 consecutive months, and identify the 

reasons why they are not working if they experience a period of unemployment or 

labor force nonparticipation. We find that the majority of SNAP and Medicaid participants who would be exposed to work requirements are attached to the labor 

force, but that a substantial share would fail to consistently meet a 20 hours per 

week-threshold. Among persistent labor force non-participants, health issues are the 

predominant reason given for not working. There may be some subset of SNAP and 

Medicaid participants who could work, are not working, and might work if they 

were threatened with the loss of benefits. This paper adds evidence to a growing 

body of research that shows that this group is very small relative to those who 

would be sanctioned under the proposed policies who are already working or are legitimately unable to work. 

108 

Figure 3. 

Employment Status over Two Years, SNAP Participants 

Source: Survey of Income and Program Participation (SIPP) (U.S. Census 

Bureau 2013–14); authors’ calculations. 

The CHAIR. Thank you all for your testimony. 

We will now begin questioning. Members will be recognized for 

questioning in the order of seniority for Members who were here 

at the beginning of the hearing. After that, Members will be recognized in order of their arrival. 

I will now yield 5 minutes to Mr. McGovern. 

Mr. MCGOVERN. Thank you very much, and thank you for your 

testimony. 

Last Congress, Republicans held 23 hearings on SNAP, and I disagree with Mr. Johnson. We didn’t talk about this issue at all. In 

fact, they intentionally avoided a hearing on this. I requested a 

hearing and it never happened, and I now know why, because the 

bottom line is the ABAWD population is a complicated population. 

It doesn’t fit into a nice, neat category that you can stigmatize, that 

you can demonize. This is a population that includes returning veterans, people with limited educational experiences, some who are 

aging out of foster care, people who have undiagnosed mental illnesses, people who live in rural areas who don’t have access to 

transportation. I mean, there are lots and lots of issues involved in 

this population. 

And I should also point out for the record that the majority of 

able-bodied adults on SNAP right now actually work. They earn so 

little they still qualify for SNAP. And the notion that somehow this 

population is just lazy and just wants to benefit from this benefit, 

I will remind people that the average SNAP benefit is about $1.40 

per person per meal, and so, it doesn’t provide very much of anything. 

I asked Secretary Perdue when he was here in February to provide me the demographic data that the USDA used to justify this 

new rule. I have received nothing to date. Maybe it is lost in the 

mail, but hopefully we will get that at some point. But my frustration is we passed a farm bill and it was a bipartisan farm bill. It 

rejected all the cruel provisions that were contained in the House 

bill, but it passed overwhelmingly when it came back to the House, 


11602044.eps
109 

and yet, we have the Administration ignoring what Congress decided, which is frustrating. 

I want to also point out that in terms of the consequences of 

what the Administration is trying to do. I mean, Maine tightened 

up on the work requirements. There was an article in The Washington Post in May of 2017. Let me read the beginning of it. It said, 

‘‘For a period last year after he lost his food stamps, Tim Keefe, 

an out-of-work and homeless Navy veteran, used his military training to catch, skin and eat squirrels, roasting the animals over an 

open fire outside the tent he pitched in frigid Augusta, Maine. The 

new additions to Keefe’s diet resulted from a decision by state authorities to tighten work requirements for recipients of the social 

safety net—forcing the 49 year old who lost his job at a farm equipment factory because of an injury, off the food stamp rolls.’’ I mean, 

this is the kind of stuff that can happen if we are not thoughtful 

about how we approach this issue. Yes, we want to help people get 

into the workforce. We ought to be investing in worker training, 

education, and transportation. There are a whole bunch of things 

we should be doing. Not cutting of their benefit because they find 

themselves in a difficult circumstance. 

I don’t know how cutting off somebody’s SNAP benefit is going 

to make it easier for them to get to a job where there is no transportation or somebody who, again, has an undiagnosed mental illness, how that is going to help them get into the workforce. This 

is a simple-minded approach to a complicated problem, I believe it 

is red meat to the right-wing base, who it seems, never tires of demonizing this population. 

Let me ask Ms. Hamler-Fugitt, Ms. Cunnyngham, and Dr. 

Shambaugh, I understand that a lot of your work has explored the 

complexities that arise from ABAWDs and low-income workers. 

Just for the record, again, do you believe that low-income persons 

who work less than 20 hours a week do so by choice, is this something they desperately want to do, or is it because of disadvantages? 

Ms. HAMLER-FUGITT. To the Chair, to the Congressman, today in 

America, a job doesn’t mean a living. There are people that work 

and they work hard; but, unfortunately in the current economy, 

jobs don’t provide full time benefits. The folks who are part of our 

program, they work, they want a job. 

I would also point out that we have done longitudinal studies of 

the levers in our program. What we found is that when they do 

work, they generally work less than 30 hours a week for about $10 

an hour with no benefits, and the average length of employment is 

79 days, which is very interesting. Seventy-nine days would not 

trigger their eligibility for unemployment compensation. SNAP is a 

hunger lifeline for these individuals. A hungry worker is not a 

healthy worker, is not a productive worker. 

Dr. SHAMBAUGH. I would just say, Congressman, not only do they 

want to work, but the evidence shows that most of them do work. 

And so, most of them are cycling in and out of jobs and the small 

portion who are not cycling in and out of jobs typically face significant barriers, health and otherwise, to work. 

Ms. CUNNYNGHAM. I examine evidence and it is true that we 

know that, as you mentioned, that SNAP participants cycle in and 

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out of work, that time limits can—well, to directly answer your 

question, yes, I believe people want to work and the evidence shows 

that most of them do work. 

Mr. MCGOVERN. Thank you. 

The CHAIR. Thank you. The gentleman’s time has expired. 

Ranking Member Johnson, you are now recognized. 

Mr. JOHNSON. Thank you, Madam Chair. 

Mr. Adolphsen, remind me. You had analyzed 600,000 ABAWDs 

in maybe three states. What were those three states? 

Mr. ADOLPHSEN. Florida, Kansas, and Arkansas. 

Mr. JOHNSON. In Florida, Kansas, and Arkansas, did your research indicate that there were SNAP recipients who had learning 

disabilities? 

Mr. ADOLPHSEN. Well by definition, an ABAWD is not disabled, 

but then the Department when they intake that person, particularly when the requirements are in place, will screen them for 

those types of barriers to make sure that they are directed to a 

place where they can get assistance for those. 

Mr. JOHNSON. In Florida, Kansas, and Arkansas, were there 

SNAP recipients who were not fully literate? 

Mr. ADOLPHSEN. I think that is probably likely. With 600,000 

sample size, there were people that had issues that the Department would work with them on to help them get back to work. 

Mr. JOHNSON. In Florida, Kansas, and Arkansas, do you believe 

that there were SNAP recipients within your studied population 

who were caregivers for family members at home? 

Mr. ADOLPHSEN. If they are actually responsible for the care of 

a child, they wouldn’t be considered an ABAWD, so they wouldn’t 

have been in that population. 

Mr. JOHNSON. In Florida, Kansas, and Arkansas, do you believe 

that there were returning veterans within the studied population? 

Mr. ADOLPHSEN. Certainly. 

Mr. JOHNSON. Do you believe within Florida, Kansas, and Arkansas that within the studied population there would be people who 

lacked access to reliable transportation? 

Mr. ADOLPHSEN. Yes, there certainly would be. For the folks that 

left the program, they would have had to earn more income and 

then come off the program. Because if they lacked transportation 

and therefore could not get to a job or training, they wouldn’t have 

been in the group that we studied that left the program, because 

they would be exempt from the work requirement. 

Mr. JOHNSON. I guess I’m a little confused, sir. If the populations 

within those states—they sound an awful lot like the populations 

in my state and an awful lot like the populations in the states that 

the other witnesses described. I thought you said that there were 

successes for those populations that moved off the program? Did I 

misunderstand you? 

Mr. ADOLPHSEN. No, absolutely, and I think that is what is concerning about the way the waivers operate right now is you have 

states doing very well with implementing the work requirement 

fully, in Florida, for example. And then you go to California and 

you have nearly one million people who have no work requirement. 

They are similar populations. They are similar income levels. They 

111 

are the same age, same type of household situation. The waiver 

makes for a very uneven application of the program rules. 

Mr. JOHNSON. This has worked in some states, is that what your 

research indicates? 

Mr. ADOLPHSEN. Absolutely. It has been very effective. 

Mr. JOHNSON. Give me a sense of the types of support that exist, 

things that states can do to help ABAWDs find meaningful employment? 

Mr. ADOLPHSEN. Sure. There is a whole number of things. The 

Federal Government funds employment and training portions of it 

at 100 percent. States can get a 50/50 match for things like job 

search, education, job training. They can get funding for transportation, even buy equipment, things like boots if they need those for 

their job. States really can be very hands-on in helping people. 

The challenge is when you don’t have the requirement in place, 

it also waives the requirement for the government to help them. 

They are simply sending them the benefit month after month, 

maybe checking in once a year for recertification. But they never 

really engage with them to find out where they can help. 

Mr. JOHNSON. Well, this is a population that clearly does have 

challenges, and no one should dispute that. I think you did a nice 

job, sir, of explaining that in the states you studied, there were 

people who had challenges. And I know my friends—Patty who 

works as a retail clerk in Mitchell who has some serious barriers. 

Mike and Paul, my friends who work in Mitchell, they have some 

challenges that I don’t have. They have found meaningful employment. It is a meaningful part of their life. It is important that we 

remember that nobody is denigrating these folks. Nobody is suggesting that their path forward is easy. We are called to do an even 

better job than we are doing in helping them and work is a critically important part of that process. 

I want to thank you for your research, sir. I yield back, ma’am. 

The CHAIR. Thank you. Ms. Adams is recognized for 5 minutes. 

Ms. ADAMS. Thank you, Madam Chair, and thank you to the 

Ranking Member as well, and to the individuals who are here testifying. Thank you. 

Before I begin, I just want to reiterate that USDA is unilaterally 

changing rules around requirements for ABAWDs, despite Congress’ negotiating a farm bill at the end of 2018 which explicitly 

avoids changing these requirements. 

While North Carolina does not currently have a waiver, lawmakers in my state are assessing the need to authorize waivers for 

some counties that meet current requirements. But you know, because states can do doesn’t mean they will do or that they are able 

to. 

But I am deeply concerned that the proposed changes will take 

away needed flexibility for my state to help communities and individuals who are struggling with unemployment, opioid addiction, 

and other barriers to work. 

Ms. Hamler-Fugitt, Mecklenburg County is a part of my district. 

It is an area with a strong economic and population growth, and 

even in our county, we have more than 7,500 ABAWD individuals 

who are unable to find work, full-time work, and they are receiving 

SNAP benefits. If you can imagine the countless regions, especially 

112 

in rural areas, that are seeing years of stagnant growth and continue to have high unemployment. The lack of access to work and 

the chronic barriers to work that many of these individuals face are 

some of the reasons that USDA estimates that 755,000 people will 

lose food assistance. And so, the rule would really force people who 

haven’t been able to find work to enroll in E&T, or somehow find 

work when it has been impossible before. 

With your experience in this space, do you think that it makes 

sense to ask E&T Programs to do more than double their enrollment in programming with no funding, and what do you think the 

impacts will be to the quality of training? 

Ms. HAMLER-FUGITT. To Congresswoman Adams, I can assure 

you that based on our firsthand experience in Ohio, slots just don’t 

materialize. You have to have an infrastructure that is set up by 

the county or the state that does require funding as well to provide 

these services, and then the support services to get individuals into 

those work and training slots and ensuring that if they are available, that they are being trained for jobs that are currently available. It is a very expensive endeavor, and I have just done some 

numbers based on Ohio. If Ohio were to lose its current waivers in 

35 counties, an estimated about 75,000 individuals would have to 

have a slot made available to them. The cost associated with that 

would be about $600 million. On average, the cost of a good Employment and Training Program varies from $4,500 on the low end 

to about $12,000 on the high end. 

Ms. ADAMS. Thank you very much. Let me just move onto ask 

Ms. Cunnyngham and Dr. Shambaugh, according to the National 

Education Association, more than 2.5 million children are being 

raised by their grandparents or other relatives because families are 

dealing with parental alcohol, substance abuse issues, and others. 

As a result, they face obstacles in securing an exemption from 

ABAWD time limits. How do you see this rule impacting those 

struggling with opioid and other forms of addiction, and do you expect that there will be unexpected consequences for the children? 

This is to Dr. Shambaugh and Ms. Cunnyngham. 

Dr. SHAMBAUGH. Well, as has already been mentioned today, we 

know that there are people who are in the ABAWD population who 

sometimes are taking care of children, and so they are not considered a caregiver because they are not the primary caregiver in 

some cases, but they have some responsibility for children. Having 

them lose SNAP benefits would take resources away from a family 

with kids. I think that is something that is certainly is a concern. 

Ms. ADAMS. Okay. Ms. Cunnyngham? 

Ms. CUNNYNGHAM. Sure. Well, another population that would be 

affected are non-custodial parents, so not only grandparents, but if 

you are looking for non-custodial parents to contribute to their children’s well-being, it is important that they have a job. It is important that they are supported while looking for a job. 

Ms. ADAMS. Unexpected consequences. I have about 23 seconds. 

Ms. CUNNYNGHAM. Unexpected consequences, non-custodial parents are critical to the well-being of their children, and so we want 

to support them. 

Ms. ADAMS. Thank you. Madam Chair, I yield back. 

113 

The CHAIR. Thank you very much. Mr. DesJarlais, you are recognized for 5 minutes. 

Mr. DESJARLAIS. Thank you, Madam Chair. 

We live in a country that takes care of people who can’t take care 

of themselves, and that is the right thing to do. The SNAP Program is there to help people who are hungry, make sure that they 

have food in their mouths and that hunger is reduced, and it is our 

responsibility in Congress to make sure that we have the funding 

to take care of those in need. 

Thankfully, our economy is doing much better. Unemployment, 

as mentioned in your oral statement, Mr. Adolphsen, is at 50 year 

lows. In fact, in my home State of Tennessee, about the only thing 

holding back economic growth is an adequate workforce. It is fortuitous that we are having this hearing today that Mr. McGovern 

had asked for. 

It seems like we probably agree on a lot of things that we are 

just not even seeing here. The fact that able-bodied people who can 

work, should work, is a pretty common concept. I asked Secretary 

Perdue when he was here last month if he had any idea why there 

is so much pushback to this idea, and he responded, ‘‘I have no 

clue.’’ I can understand that when you look statistically that across 

all political spectrums, about 80 percent of people believe that ablebodied people who can work, should work. We just have to figure 

out how to get that done. 

And I guess I would like to ask our witnesses, in concept, do you 

agree that able-bodied people who can work, should work? We will 

start at this end. 

Ms. CUNNYNGHAM. Yes, I agree it is best for everyone, for the individuals. 

Mr. DESJARLAIS. Okay. Mr. Adolphsen? 

Mr. ADOLPHSEN. Yes, I do. 

Ms. HAMLER-FUGITT. Yes, sir. 

Dr. SHAMBAUGH. Yes, I do. 

Mr. DESJARLAIS. That is a great place to work from. We all agree 

that that should happen, and the problem is, how do we do that? 

And we have heard of all kinds of barriers that stand before us, 

it is our job to solve that. 

Mr. Adolphsen, within the framework of the existing funding for 

employment and training, what changes have been made to increase the effectiveness of those funds, or how are we making it 

easier for people to find work and transition into the workforce? 

Mr. ADOLPHSEN. Sure. Well, the funds in programs that you 

mentioned, Congressman, are really critical, and we can’t leave 

that piece out. We put a lot of money into employment and training, not just in the SNAP Program, but also across the board. As 

was mentioned, we have adult ed, community colleges, Department 

of Labor career one-stops. There are a lot of resources designed to 

help these precise individuals, and for them to really be effective, 

the key is that people actually utilize them. We have seen problems 

where when these programs are purely voluntary, there is a type 

of requirement in place, there has been very little participation. 

And what we really want to see is these folks utilizing all those 

great resources that are being provided. 

114 

That is one of the key values of the work requirement being in 

effect is it connects them to those resources, where otherwise, we 

are just loading the EBT card every month and we are not really 

working with them on getting back to work. 

Some of the places where it has been really effective recently, 

there has been a real urgency on connecting folks to a job and taking that first step. We saw in Florida, in particular, a lot of people 

took an initial first step and maybe landed at a temp agency or in 

fast food or retail, but that was just the first step. They quickly 

moved on to higher paying industries with more wages. The best 

way to make these programs effective is to get them in the door. 

Mr. DESJARLAIS. All right. It seems that at these hearings we always hear the best case scenarios from one side and the worst case 

scenarios from the other side, and I have heard that here today. 

You can be the group that wants to talk about successes. You can 

be the group that wants to talk about failures. I want to be the 

group that talks about successes, and we want more successes. 

Some of the other witnesses have talked extensively about all the 

barriers for able-bodied adults joining the workforce. Do you agree 

that these barriers are as bad as they say, or are you more optimistic? 

Mr. ADOLPHSEN. Congressman, my experience at the agency, that 

was one of the things that was most disappointing is the whole system was revolved around this point of view of what people can’t do. 

And it is really important that we flip that, and when someone 

walks through our door asking for help with the food benefit, right 

away we say, ‘‘All right, here is your benefit. What can we do to 

get you moving forward? What are you able to do?’’ Where can we 

help you maybe remediate some skills, things we talked about. But 

we really need to come at it from the point of view that these individuals are very capable. They can work. They can improve their 

skills, their education, and meet them at that point instead of 

starting right off the bat by having a long list of everything they 

can’t do, moving forward. 

Mr. DESJARLAIS. I would agree. I think that we need to try to 

succeed, not just accept failing. Thank you for your testimony, all 

of you for being here. 

I yield back. 

The CHAIR. Thank you. Ms. Schrier, you are recognized for 5 

minutes. 

Ms. SCHRIER. Thank you to all of our witnesses. Thank you, 

Madam Chair. 

I wanted to first just repeat some of the really interesting things 

that I heard, because they really deserve emphasis. 

I believe it was you, Dr. Shambaugh, who said work requirements keep people out of SNAP, but have little to no effect on employment. And I thought that was a really profound statement. Another that I believe you said, but others said as well, was that the 

able-bodied workers without dependents is really a misnomer, that 

it misses a lot of people with undiagnosed mental illness, learning 

disabilities, and people on the autism spectrum who really are not 

truly able-bodied. I thought another really important point was 

that the average benefit is a $1.40 per meal, and I think about how 

115 

we are nickel and diming over this benefit that is providing nutrition to people in need. 

I heard that only 11⁄2 percent truly don’t want to work, which is 

a small number, and in my opinion, not enough to throw the baby 

out with the bath water, and that the unemployment rates just 

don’t paint a true picture, because the skill sets needed may not 

match where the job openings are. 

I wanted to talk a little bit about the State of Washington. The 

State of Washington is firmly committed to improving the lives of 

those on SNAP through work, by helping beneficiaries become selfsufficient through good paying jobs. In fact, in 2018 alone, the state 

spent $22 million of its own money on top of Federal funds on 

SNAP Employment and Training Programs, otherwise known as 

SNAP E&T. And making this investment among the top five states 

in the country, and in addition, we were granted one of ten SNAP 

E&T pilots that were funded in the 2014 Farm Bill. In 2016, our 

Assistant Secretary for Economic Services, David Stillman, testified 

before this Committee about our state’s successful Education and 

Training Program, and under his leadership, the best practices 

learned are now being shared with others throughout the country. 

We have also engaged employers like Amazon, Microsoft, Providence Health, and others to be active partners in this training program, and the bottom line is that that part is working, and we 

know what we are doing. 

Now, the proposed rule will completely undermine all of that 

work. Our governor agrees, and in fact, I would like to enter into 

the record Governor Jay Inslee’s letter of comment on the proposed 

rule, because it talks about the devastating impact that this will 

have on our state’s 91,000 ABAWDs. 

[The letter referred to is located on p. 162.] 

Ms. SCHRIER. I had a question for Ms. Hamler-Fugitt, which is 

this: In Washington, we estimate that more than 43 percent of our 

state’s ABAWD population currently experience homelessness, disproportionately higher than the broader SNAP population in the 

country at 11 percent. Nearly 60 percent of our ABAWD population 

is suffering from behavioral or physical health conditions, including 

substance use disorder. For these individuals, the USDA proposal 

would do nothing to help them find work, while adding yet another 

obstacle in their way, which is food insecurity and hunger. And the 

proposed rule would not achieve the goal of promoting self-sufficiency and jobs. It would make it more difficult to find employment. 

How does this description fit your experience in Ohio? 

Ms. HAMLER-FUGITT. To the Congresswoman, very similar, except Washington State is to be commended for its commitment of 

$22 million of state general revenue funds to expand your program. 

Again, Washington residents are very fortunate to have that kind 

of leadership. Unfortunately, it is the luck of the draw. Other 

states or counties, in our situation, a county devolved system, that 

is up to local county commissioners. I would say it is very similar. 

One final remark. What is really missing from this is a standardized set of data. We need to be measuring the same thing. The assessments should be standardized across all states on the information, upon intake. These are not social workers that are doing this 

116 

intake. These are clerks. They are not qualified to make determinations about one’s mental or physical disabilities. 

Ms. SCHRIER. I appreciate that comment, especially as a medical 

professional myself, that these can be difficult diagnoses to make, 

and that we need to consider that the rate of undiagnosed everything, including learning disabilities in certain populations. 

Dr. Shambaugh, I had a question for you, and I would love to 

hear your thoughts on this excerpt from Governor Inslee’s letter. 

‘‘While the unemployment rate does provide essential data, it does 

not take into account a community’s individualized workforce needs 

or that its residents may not be well-suited to find and keep locally 

available jobs due to a lack of housing, hard skills, certifications, 

and employers in Washington.’’ 

Dr. SHAMBAUGH. I think that is exactly right, and one thing that 

is important to recognize is even when the aggregate unemployment rate is low, it doesn’t mean it is low for all groups or in all 

areas. As mentioned, in some places it is as high as ten percent. 

When it first crossed under seven percent nationally, it was still 

10.7 for people with less than a high school degree. There are some 

people are going to be struggling a great deal, even when the overall rate is low. 

Ms. SCHRIER. Thank you. I appreciate that. Thank you to all of 

you. 

The CHAIR. Thank you very much. I now recognize Mr. 

Hagedorn, for 5 minutes. 

Mr. HAGEDORN. Thank you, Madam Chair, Ranking Member. I 

appreciate the opportunity. Thanks for this hearing, and thanks to 

the witnesses. 

This is an issue that has been important to me for over 30 years. 

I used to work for Congressman Arlan Stangeland, who was a 

Member of this Committee, and he and Congressman Stenholm of 

Texas at that time introduced bipartisan Work for Welfare legislation in the 1980s. We had broad support. Couldn’t get a vote from 

the Majority party at that time, but a few years later, Newt Gingrich and some others picked up the provisions of that bill and 

passed it three times. It finally made it to the President’s desk 

where he signed it, and the Clinton/Gingrich—however you want to 

put it—welfare reform bill was highly successful. We drove down 

the cost of government. We empowered people and got them back 

into private-sector work. Most people would recognize, including 

even President Clinton, that that was quite a success. 

But over time, those work requirements went away, and we have 

had some issues with waivers and things of that nature and some 

loopholes that need to be closed. 

In my district we went around and we talked to all sorts of 

thought leaders, including mayors and social workers and others, 

and time after time, I was told there are people on the sidelines 

who could work, but for a number of reasons, are not working. I 

have never used the word lazy. That comes from the other side. 

Sometimes there are impediments. They lose benefits and so forth 

as they get in the workforce, and we need to look at that. 

But the Chairman himself, Chairman Peterson, who interestingly enough succeeded my old boss, Congressman Stangeland, in 

1990. He has made comments to say that these waivers aren’t 

117 

working, particularly in the State of Minnesota. And he has talked 

not just here in Committee, but in press as well. And I would ask 

any of you, does anybody disagree with the Chairman’s comments 

as it refers to the State of Minnesota and these waivers? Anyone? 

I guess not. Okay, we have some uniformity on that. 

What I would say is this: Work for Welfare is a concept that is 

empowering for people. It is a fairness issue for the taxpayers, because if people are able-bodied to work, they should do so, just like 

the taxpayers do to make it possible. It eliminates fraud. It drives 

down the cost of benefits. 

Now, if we want to talk in a serious way about helping folks, let’s 

talk about the concept of transition wages. When people are moving from welfare into the workforce and they reach that cliff where 

they are going to lose medical benefits and other things, how do we 

transition them to keep them in private-sector work so they can 

continue to be upwardly mobile? That, to me, is important. I hope 

the Chair and others will work with me on those issues. 

Technical training: there are lots of jobs out there just begging, 

and we have to look at people’s potential. That is the highest calling. What is the potential of each individual? Not just able-bodied 

folks, disabled people, people that want to be in the workforce and 

contribute. What is their potential? We have to have confidence in 

them and do whatever we can in order to promote that. 

And last, the Secretary was here a few weeks ago. He talked 

about this regulation, and I told him in my opinion—it was on the 

record—that it is God’s work because it is moving people in the 

right direction. It is showing confidence in folks and it is not allowing states to cut them short and to do that. 

And I just say to my friends on the other side, if you don’t like 

this regulation, you think the Executive Branch has gone too far, 

then join us in enacting the REINS Act. Let’s make sure that every 

regulation coming out of the Executive Branch has to receive the 

vote of the House and the Senate and be affirmed before it goes 

live. That is only fair for all industries. 

With that, I would yield back. 

The CHAIR. Thank you very much. Mrs. Hayes, you are recognized for 5 minutes. 

Mrs. HAYES. Thank you, Madam Chair. 

In my home State of Connecticut, we have 107 towns, including 

13 towns in my own district, that would lose the 2018 waivers proposed under this rule. This would translate to about 26,000 people 

in Connecticut automatically becoming vulnerable to losing the 

Federal help they need to simply put food on their tables. 

I will say to my friends on the other side that I was a SNAP beneficiary. I worked two jobs, was grossly underemployed, and was a 

full-time college student. It was temporary. It took much longer 

than 3 months, but it was temporary. While this 3 month time 

limit for SNAP benefits for ABAWDs in theory should only impact 

adults who do not have children, in practice, it will inevitably and 

disproportionately impact children and young people. 

As a teacher, this damaging impact is personal for me. SNAP is 

the first line of defense amongst childhood hunger. It is also the 

first line of defense against economic instability and hunger for 

118 

young people, especially for the 20,000 kids aging out of the foster 

care system every year. 

Madam Chair, I ask to submit two letters into the record, one 

from the NEA that talks about the effects on young children in the 

classroom, and the other one from Share Our Strength and No Kid 

Hungry. 

The CHAIR. Without objection. 

[The letters referred to are located on p. 158 and p. 159.] 

Mrs. HAYES. I have seen what a hungry 16 year old looks like, 

and it is not much different than a hungry 19 year old. Hunger is 

merely a symptom of poverty. The reality is that very few ABAWD 

recipients of SNAP are not interested in working. Rather, they are 

desperately underemployed, undereducated, or in low wage work 

that is highly unstable. 

The unemployment rate for young adults is nearly seven percent. 

According to a national survey of youth who aged out of the foster 

care system, only 12 percent were employed full time at age 19. 

Forty-four percent had not obtained a high school diploma or GED 

equivalent at age 19, leaving them at a significant disadvantage in 

seeking stable employment and livable wages. 

Instead of punishing people for being poor or for being in foster 

care, we need to further invest in job training and education as a 

way out of poverty so that people can, in fact, help themselves. 

By ripping away a lifeline of an already vulnerable population, 

this Administration is making yet another unconscionable attack 

on young people and poor people. This Administration is telling 

this population, one that has already struggled enough, that they 

don’t deserve help the day they turn 18 and age out of the foster 

care system, that they don’t deserve compassion from the Federal 

Government, and that they don’t even deserve a hot meal. 

My question is for you, Dr. Shambaugh. What are the long-term 

social and economic cost effects of ripping away this safety net for 

food security for young people aging out of the foster care system? 

Dr. SHAMBAUGH. Thank you for the question. We have very good 

evidence, certainly for children in particular, that spending time in 

a household with SNAP relative to people in the same economic situation without SNAP benefits has substantial positive impacts on 

health, income, and earnings later in life. I think that would probably translate that type of result to that next population just a few 

years older, as you mentioned. 

We know that in many ways, you are making investments that 

make people more employable, better workers, healthier later in 

life, and in that sense, you wind up saving money in the long run. 

Mrs. HAYES. Well, I appreciate that because I have seen that. Because, in my experience, these young people do cycle back into the 

system, and it is not always with SNAP benefits. It is the criminal 

justice system. It is the unemployment system. It is all of these 

other programs that could have been prevented if the investment 

was made on the front end to help them to support themselves. 

Ms. Hamler-Fugitt, can you think of ways that we can increase 

outreach so that foster youth or young people who were formerly 

in foster care know about the benefits that are available to them 

and are better positioned to help themselves? 

119 

Ms. HAMLER-FUGITT. Congresswoman, we need to understand 

that as they are in the foster care system, that they are getting the 

kind of life skills and support necessary. They are being exposed 

to opportunities of higher education and training. We need to make 

sure that there are also transitional benefits. 

I know our state is continuing to do some more support around 

a bridges program that will provide that transition, but again, a lot 

of these children as they age out of the foster care system, they are 

dumped on their 18th birthday onto the street. That is wrong. I 

know for a fact that we have spent, in some cases, hundreds of 

thousands of dollars getting these young people to adulthood, only 

to turn our back on them. We can do better. I know we can. 

Mrs. HAYES. We can do better. 

Thank you, Madam Chair. I yield back. 

The CHAIR. Thank you. Mr. Bacon, you are recognized for 5 minutes. 

Mr. BACON. Thank you, Madam Chair, and I appreciate our four 

folks here today. I appreciate you sharing your perspective. It is a 

very important topic. 

I just want to take a moment to thank Chairman Peterson who 

has weighed in on this, in recent years, talking about some of the 

abuses of the state waiver process. I appreciate his candor, especially his candor coming from the other side of the aisle. 

The ABAWDs are just that. We are talking about able-bodied 

adults without young children, and in a time of record low unemployment, 2.7 percent in Nebraska, where we have more job openings than people seeking jobs right now, there is an expectation by 

most for folks to seek that work and there is an expectation of having some time limits within the SNAP Program, which there are. 

There is that expectation there that we should try to enforce that 

to the best of our ability. 

And so, my question for Mr. Adolphsen, if I may. In your studies, 

have you seen a contrast of those states who are enforcing these 

time limits versus those who are not or they are doing the waivers, 

and helping the ABAWDs get out of poverty? Is there some direct 

correlation between these individuals who are struggling, but once 

they get back in the workforce, how does that affect their prosperity or their getting out of poverty? Thank you. 

Mr. ADOLPHSEN. Sure. Thank you, Congressman, for the question. 

What we looked at with those more than 1⁄2 million adults that 

we tracked individually with their incomes, their incomes within a 

year doubled. In Arkansas, we had another year of data and their 

incomes tripled within the 2 year period. What you have is they are 

actually moving not just up in income, but out of poverty. The 

amount they were earning actually replaced the benefitted amount 

as well. In total, they were earning more than they were before, 

even when you count the benefit. We are seeing real upward economic mobility from that population. 

You contrast that with states where the waiver is in place, and 

there is no work requirement for this population. They are still on 

the program. By definition, they are still in poverty, right, they are 

in that income bracket that would keep them eligible. We know 

120 

that three out of four of them aren’t working. We are not seeing 

that same movement in those states. 

Mr. BACON. Well, thank you. Really, full time work is the best 

way out of poverty, and often a year or 2 later, there are raises and 

promotions. It is the first step for getting people out of that poverty 

area. 

I just want to point out in Nebraska, we have such a shortage 

in some of our more technical career fields, whether it is welding, 

electrical work. There is a shortage of folks and they are being offered $40,000 a year jobs in training, while they are in training, 

with health insurance, just to get them started. We are having a 

hard time filling those positions. 

Thank you very much. I yield back, Madam Chair. 

The CHAIR. Thank you very much. Mr. Lawson, you are recognized for 5 minutes. 

Mr. LAWSON. Thank you, Madam Chair, and welcome, witnesses, 

to the Committee. 

A perception of people who are receiving SNAP benefits that extend across America and dealing with the issue when I was in the 

state legislature to come into Congress was that people were lazy, 

they did not want to work, they just wanted government assistance. 

But when you go a little bit deeper into the situation, you find 

out that this is not true. In listening to your testimony this morning, one would think that because of all of the knowledge that you 

all have in dealing with people who are receiving SNAP benefits, 

that we could possibly learn a great deal as lawmakers about how 

the programs really should be established instead of some people 

saying what programs should be without any knowledge of it. 

I represent an area that has two major urban areas, and the rest 

of it is rural, and the rural community extends maybe for a distance of about 150 miles between from Gaston County—I would 

like to say from the Chattahoochee River to the St. John’s River 

in Jacksonville. And in those areas, there is high unemployment 

and transportation issues where people have difficulty in trying to 

get into the city. And Florida in itself doesn’t utilize the waivers. 

Now my question would be simply that food insecurity within college student population, which you know, I have a lot of student 

populations at universities and in the community colleges, is growing. And not only in the areas in Florida, but throughout the 

United States, especially at community colleges where many of 

these students are part-time and they are working and trying to 

make ends meet to really better themselves. 

Can you discuss any experience that you have had, Ms. HamlerFugitt, and am I saying that right, Fugitt? Okay. At Ohio Association of Foodbanks where part-time students have benefitted from 

their food stamps status while working hard to complete their degree? 

Ms. HAMLER-FUGITT. Yes. To the Congressman, yes, that is one 

of the struggles. In fact, in my written testimony I talk about 

Mary, a young woman who is balancing both a pharmacy tech career track at a local community college, trying to work for a drugstore chain, trying to maintain that 20 hours of employment while 

also assisting her mother to care for her younger sisters. And unVerDate Aug 31 2005 11:16 Jun 14, 2019 Jkt 041481 PO 00000 Frm 00126 Fmt 6633 Sfmt 6601 P:\DOCS\116-02\36188.TXT BRIAN
121 

fortunately, she fell into a situation where because the sales 

weren’t there in the store, she wasn’t able to get her 20 hours that 

then put her SNAP benefits in peril, which then her lifelong dream 

of becoming a pharmacy tech, the first generation to graduate from 

high school or from college was left in the peril, where she was 

looking at having to drop out of college. 

I also want to say, as Ohio’s largest charitable response to hunger, I am sure that your food banks are in a similar situation. The 

greatest demand we are currently having is for colleges and universities, both technical schools and 4 year institutions, as well as our 

K–12, to come on site and set up food pantries, not only to feed 

their students, but also to be able to feed the families of those students as well. 

Hunger is a problem in America. In my great state, it affects one 

in six. Hunger looks a whole lot like you and me, and it lives just 

six doors down. 

Mr. LAWSON. That is incredible, and I noticed that many of the 

universities now are setting up food banks and working with some 

of the local grocery chains. One would think that once you are in 

college and you have this ambition to go to college, that there 

would be resources there with the financial aid so forth you get 

would help you through this. But most of those students who are 

also receiving financial aid and assistance—I know my time is running out—also have to rely heavily on food banks in the community 

as well as other people who are working in those communities. 

With that, Madam Chair, I yield back. 

The CHAIR. Thank you. Thank you very much. 

We will now recognize Mr. Davis. 

Mr. DAVIS. Thank you. 

The CHAIR. You are recognized for 5 minutes. 

Mr. DAVIS. Thank you, Madam Chair, and thanks to the panel. 

I am starting my fourth term here as a Member of the House Agriculture Committee, and we can probably all agree as Republicans 

and Democrats that the issue isn’t about getting people off of SNAP 

benefits. The issue is about making sure that people who are on 

SNAP benefits have access to the jobs that we know are available 

in this country right now. And we can all agree, it may not be our 

Committee’s jurisdiction, but there are some loopholes that still 

exist within our workforce training programs that perpetuate families staying on SNAP benefits, which is why we have right now 

nine million more people on SNAP benefits in this country today, 

when there are 6.1 million jobs available, less than four percent 

unemployment, than when we had 9.5 percent unemployment. 

Today is a day that I certainly hope we can take your testimony 

and come together and try to find solutions. In the 2018 Farm Bill, 

obviously a lot of us here in the House wanted to try and close 

what we saw as a loophole in our workforce investment programs 

by allowing for investment within SNAP education and training to 

allow families to go get training for jobs that we know are available 

in our communities. If we don’t do it now when unemployment is 

at 3.9 percent, we are never going to do it when unemployment is 

at 9.5 percent. Help us come up with some solutions. Help us come 

up with some solutions to allow families to get money to go back 

and get training so they don’t have to worry about what they can 

122 

or cannot buy at the grocery store anymore, when they are doing 

everything they can to get a job in our communities that we know 

that are available. 

It is very frustrating to me that this debate becomes more about 

politics than clearly it does about policy. That is a very frustrating 

point for me as a legislator, and I certainly hope now that we have 

the other side in charge that we can come up with some solutions, 

because that loophole in our workforce investment system still exists. And if we do nothing, we are not helping those families who 

want to get off of SNAP benefits. That is my point. 

Being from Illinois, I also have an issue with the waiver process. 

Following the passage of the 2018 Farm Bill, I sent a letter to our 

then-Governor of Illinois, Bruce Rauner, asking what justification 

that the State of Illinois had to waive the ABAWD time limit in 

101 of 102 counties. While individuals should not be penalized if 

jobs are unavailable, I inquired regarding what steps the state had 

taken to encourage the SNAP recipients to get training for employment. And the Governor’s Administration at the time claimed a 

need for a waiver was due largely to administrative burdens, not 

out of any particular necessity in all of the 101 of 102 counties. Administrative governmental burdens. 

Again, it is cruel to do nothing to help a system recover. It is 

cruel not to help families get training for jobs that we know are 

available, even in the rural communities that I serve. That is what 

is cruel. 

Now, Mr. Adolphsen, I have a quick question for you. Why in the 

world a State like Illinois, where we have low unemployment, why 

in the world did our governor ask for a waiver for 101 of 102 counties? 

Mr. ADOLPHSEN. Thank you, Congressman. You hit on it already. 

One reason is it is driven by the workload on their end, or perceived workload on their end. The other reason is simply to maximize the number of people that are waived. We have heard that 

explicitly from states. That is what they are doing. They are not 

looking strategically at where are people actually unable to get 

work or get into training. They are just looking at how do we maximize this waiver to cover as many people as possible so they don’t 

have to be engaged, which is a problem. That is exactly what the 

rule tries to do, it is not getting rid of the waiver. The waiver exists. It is in Federal law. It is just making sure that it can only 

be used where it is actually targeted. 

On the administrative side, I heard the same thing in Maine. I 

have heard it in many other states. Well, that is a lot of work. Well 

first of all, that is the job of the government agency so yes, it is 

going to take some work. That is the job. On the other hand, it 

really hasn’t proven to be an administrative burden in any way. 

The systems are all set up to do it because of the 1996 law, and 

it is work that they are already able to do. 

And I would just say, Congressman, quickly. I have heard a couple times the mention of college students. There are other ways to 

meet this requirement, other than working part-time. Individuals 

who are enrolled at least half time in any recognized school, training program, or institution of higher education are exempt from the 

123 

requirement. That really doesn’t come into play with this particular 

population or waiver. 

Mr. DAVIS. Great point. Thank you, and I yield back. 

The CHAIR. Thank you. Mr. Van Drew? 

Mr. VAN DREW. I want to thank you, Madam Chair, and thank 

you all for being here today. 

This is obviously an issue of great concern all across the country 

in so many of our communities, and I find an interesting and intriguing part of the conversation is it seems as if we have almost 

gotten to a point we are saying we either are going to have programs to train individuals or we are going to give them SNAP benefits. And I don’t really believe that is the issue. I believe the issue 

is that at certain points in people’s lives, they need benefits in 

order to move on to the next point of their life, and that is really 

the hope and the desire of what we should be doing here. 

This proposed rule is going to have a major effect in many communities across the country. I come from an interesting district. I 

come from the State of New Jersey, and everybody always assumes 

because New Jersey is generally a wealthy state with a high per 

capita income that a lot of these issues don’t exist. They exist in 

our urban areas up north, and they exist in my district, which is 

40 percent of the state. I have 40 percent of the state. I have eight 

counties and 92 towns, much of it rural, much of it seasonal, so we 

have a lot of shore communities. And what does that all mean? 

That means that a lot of folks don’t have an easy opportunity to 

find access to full time good employment year-round. We certainly 

don’t have the type of transportation that makes it easy, and we 

don’t have some of the other amenities. 

I would point out in one of my deep south counties down in south 

Jersey, it was only a number of years ago that we got our first 

county college. It is different. It depends upon where you live. It 

depends on what the issues are. Unemployment is not unemployment everywhere. It is not the same. The numbers don’t mean the 

same thing, and employment numbers don’t mean the same thing 

everywhere. 

In northern New Jersey, if you are in the financial industry, that 

is a whole different thing if you are picking cranberries down in 

south Jersey. And everybody has to realize that and understand 

that. 

It isn’t either/or. You can do both. We do have to train people. 

We do need more transportation. We do need more opportunity. 

Every single person up here wants everybody to work all the time. 

That is the goal. But in the process, people fall through the cracks 

and that is what we are talking about. 

Jobs just aren’t always as easy to come by as some of the statistics show. One of the interesting parts of this is the Administration 

expects about 3⁄4 of a million people to lose food assistance under 

this proposed rule, and probably would save, if my understanding 

is correct, about $15 billion in Federal savings from the cuts presented as a primary benefit of change. But what are the costs or 

what is the involvement going to be to those food pantries? 

We have food pantries and I deal with them and I visit them, 

and there are lots of good people who work real hard. They really 

are. They are hardworking people. They are just not making as 

124 

much money, and they go to the food pantry and that helps them 

get through while they are trying to educate their kids more and 

they are trying to work harder, and they are working their two 

jobs, and God help them, sometimes three jobs. They are going to 

be getting hit more. They are going to have greater requirements 

upon them, and who is going to fill that? How are we going to take 

care of that? What is going to happen there? Or do you believe anything is going to happen at these food pantries and these types of 

facilities that exist out there? And I guess that is a question for 

Ms. Hamler-Fugitt. 

Ms. HAMLER-FUGITT. To the Chair, to the Congressman, food 

pantries can’t do it. Our food banks and 3,540 member charities 

are already overwhelmed. Eighty percent of our member charities 

are faith-based organizations operating on budgets of less than 

$25,000 a year. They are overwhelmed with the demand, not only 

from working people who work every day and play by the rules but 

aren’t earning enough to meet their basic needs, more senior citizens than we have ever seen, we are an aging state. They are the 

canary in the coal mine. More grandparents raising grandchildren, 

and now we place this additional burden on top of folks who have 

lost their SNAP benefits through no fault of their own because they 

can’t find paid employment or work experience opportunity or 

SNAP Employment and Training Program. We can’t do it. SNAP 

is the first line of defense against hunger in this country, not food 

banks. 

Mr. VAN DREW. It is your considered opinion, then, that we are 

going to fall short? That they literally are not going to be able to 

keep up, and their shelves, at times, are going to be empty? 

Ms. HAMLER-FUGITT. Yes, Congressman. It happens every day in 

your community and my community and across the U.S. 

Mr. VAN DREW. And the last point—I know I am running out of 

time here, I am out of time. I might as well just admit it, right? 

Thank you, Chair. Oh, and Chair, also real quick, may I have 

unanimous consent to enter into the record Feeding America’s comments on the proposed rule regarding able-bodied adults without 

dependents, and its impact on hunger and hardship? 

The CHAIR. Without objection. 

[The letter referred to is located on p. 346.] 

Mr. VAN DREW. Thank you. 

The CHAIR. Thank you. Mr. Yoho? 

Mr. YOHO. Thank you, Madam Chair, and Dusty, I appreciate it. 

Thank you guys for being here. I know it has been a long day, and 

before I get started, Madam Chair, I would like to insert a February 19 letter signed by myself and 64 other Members in support 

of the Administration’s proposed rule. 

The CHAIR. Without objection. 

[The letter referred to is located on p. 392.] 

Mr. YOHO. Thank you, ma’am. 

It shameful that politics gets involved in this, because it 

shouldn’t. We are looking to reform programs that make America 

stronger. Our ultimate goal is we want a strong economy. We want 

strong job markets. We want people thriving and living the American dream, and I am not going to bore you with my story going 

125 

from being broke as a church mouse to being on food stamps to 

where I am today. 

The programs are there for the people that truly need it, and we 

want to make sure the integrity of those programs are there. And 

Florida is one of the many states focused on work-oriented reforms, 

and a new report shows the incredible impact they are having on 

our state, as you brought out, Mr. Adolphsen. Since the state implemented a food work requirement in 2016, nearly 94 percent of 

able-bodied childless adults have left Florida’s food stamp program. 

Alabama saw 85 percent reduction. Maine saw more than 80 percent. And when we talk about able-bodied adults with no dependents, we are talking about a small group of people. We are looking 

for no physical disabilities, no mental disabilities, just a small section. And if we focus on that, what can we do? With these kinds 

of results, what can we do to implement these somewhere else in 

other states? 

And I guess the question for the panel is, was there any detriment that you know of people moving off in these states? I will 

take Florida, since that is where I am from. Can anybody say, 

‘‘Well, since 94 percent got off of that, there was this massive malnutrition or starvation’’? Anybody? I will take that as a no. You 

were going to say something? 

Dr. SHAMBAUGH. I would just say, we know what SNAP does to 

provide food security, and so, we know if not everyone is finding 

jobs, then there are people who are losing resources and are then 

left with food insecurity. 

Mr. YOHO. Is there any evidence that people that moved off of 

these programs fell into a bigger food insecurity? I mean, is there 

documented peer review articles? 

Dr. SHAMBAUGH. There is also, just for the record, absolutely no 

documented evidence that the people moving to work were moving 

to work because of the work requirements. The only documented 

studies that have actually tried to study it carefully by looking at 

populations that face work requirements compared to those that 

didn’t find literally no impact on the propensity to work, based on 

exposure to work requirements. 

Mr. YOHO. But if we have a reduction of 94 percent, 85 percent 

in Alabama, 80 in Maine, we know that is a measurable—— 

Dr. SHAMBAUGH. We also know, though, that in the places that 

don’t have work requirements, people cycle off SNAP all the time. 

Mr. YOHO. At what percent? 

Dr. SHAMBAUGH. In 2008 to 2012, when the economy was terrible 

and work requirements were waived almost everywhere, the Department of Agriculture reports that 80 percent were off SNAP 

within 2 years. And that is with almost no—— 

Mr. YOHO. Okay. I am glad you brought that up, because in the 

late 1990s, the share of Americans living in the country or city 

waived from SNAP work requirements was under 20 percent. It 

climbed a bit under the George Bush Administration to 1⁄3. In 2009 

a waiver program designed to accommodate exceptional circumstances became a national panacea. As part of the American 

Recovery and Reinvestment Act signed in by President Obama that 

February, Congress temporarily suspended the conditions on 

ABAWDs, SNAP, nationwide. The suspension was supposed to exVerDate Aug 31 2005 11:16 Jun 14, 2019 Jkt 041481 PO 00000 Frm 00131 Fmt 6633 Sfmt 6601 P:\DOCS\116-02\36188.TXT BRIAN
126 

tend only though 2010, but no government initiative is temporary, 

and 8 years later, ABAWD time limit waivers are still in effect in 

at least part of 36 counties. 

The point that I want to get across is we are at full employment, 

pretty much, in this country. And we know prior to the recession, 

there was about 17, 18 million people on the SNAP Program. With 

the waivers, it went up to 41 to 42 million. It has come down to 

around 38 to 39 million. We should see, I would think, a ratio of 

decrease with the full employment. And we should take the politics 

out of this. Let’s get people into higher paying jobs. As we have 

seen, there are 6.3 million unfulfilled jobs. In my district, we have 

people starting minimum wage, $15 an hour, through competition 

because the economy is so good. Let’s maximize that and let’s help 

people transition off and move from aid on a program, get them 

educated, and off a program. I am out of time, so I have to go. 

Thank you. 

The CHAIR. Thank you. Mr. Panetta, you are recognized for 5 

minutes. 

Mr. PANETTA. Thank you, Madam Chair. It is good to be here. 

Ranking Member Johnson, good to see you, too. 

Thanks to all the witnesses for being here, as well as your preparation to be here. I know it takes a lot of work, so thank you very 

much. 

First of all, just some housekeeping. I would like to enter into the 

record this letter from MAZON, a national advocacy organization 

working to end hunger. It is a pretty extensive letter, almost a 20- 

page letter that talks about how this proposed rule would cause 

certain groups, like rural Americans, working poor, and veterans, 

to lose out on many of their benefits and the difficulties that they 

may undergo if this rule is in place. If I could enter that into the 

record? 

The CHAIR. Without objection. 

[The letter referred to is located on p. 379.] 

Mr. PANETTA. Thank you, Madam Chair. 

I understand what Mr. Yoho and Mr. Davis are saying, and I 

agree with them partly. Not just because they are my friends, but 

because I agree that we have to start looking at policy when it 

comes to this issue. We know it can be very political on both sides, 

and I saw it last term as a freshman Member sitting right down 

there in the Agriculture Committee and dealing with the farm bill 

and the presentation of significant changes to the SNAP Program 

without any significant evidence supporting such changes. And 

when I sat there and I asked the Chairman about the evidence that 

he had in support of these changes that would actually work, the 

Chairman’s response to me was well, we have 2 years to figure that 

out. And I believe that on this type of issue that is very sensitive, 

that is very important to my 74,000 recipients of SNAP in my district on the central coast of California, we don’t have 2 years just 

to figure it out. We need to basically lay a foundation of evidence 

to do so. 

Now, part of that is my background. I am a prosecutor and I 

learned that I just couldn’t go into court early on as a young misdemeanor deputy prosecutor and stand up and say he is guilty and 

127 

sit back down. I had to prove my case with evidence, and then I 

could make my argument based on that evidence. 

That is something that obviously we need to do, not just on this 

Committee and the Agriculture Committee—not just on this Subcommittee. Obviously, it should be something done in Congress, to 

be frank. I think that is a common sense statement. But, this is 

the type of issue where you see the effects, where you see the politics at play, and I just hope, moving forward, we can continue to 

look at the evidence to support these types of programs, because we 

want to help people. That is wholehearted, that is important, and 

that is why we are here. 

We understand that the evidence is missing, and what we are 

seeing is that we can’t just base one metric, a 20 hour work week— 

we can’t just use that to tell us everything that we need to know 

about a recipient of SNAP benefits. We have to look at everything, 

and unfortunately, I do believe that this proposed rule does just 

that. It reduces benefits by singling out a group that USDA assumes is less deserving, those who are deemed able-bodied but are 

unable to work. 

We are learning today that there is more to this story about 

these recipients’ stories than meets the eye, and that this proposed 

rule will harm those with vulnerabilities that we may not be able 

to see at first glance. And some of those deemed able-bodied may 

actually not be and others may face difficulties we would not otherwise anticipate. 

That is what this hearing is demonstrating, and why the USDA 

should rethink this proposal, gather more data, gather more evidence, and learn more about the challenges these targeted SNAP 

beneficiaries really face. 

Now obviously, one of those groups is veterans. In my district on 

the central coast, we have about 30,000 veterans for a number of 

reasons, but I just would like to throw out there to Ms. HamlerFugitt, basically with this proposed rule, what would be some of 

the obstacles that veterans would face in trying to find employment? 

Ms. HAMLER-FUGITT. To Congressman Panetta, what we see in 

Franklin County in our vets population, we have a vets outreach 

worker that works specifically with this population. We are seeing 

servicemen and -women who have been on multiple tours of deployment returning to the community with a lot of issues, mental 

health issues, jobs that were promised that are not there for them 

to transition back into, and a desperate need for mental health 

treatment, as well as the transitional supports and housing supports. Again, just prioritizing that. 

If I could just reiterate what you said about the policy needs to 

be driven by empirical evidence. We have been having this conversation for more than 20 years, since this provision went into the 

1996 Welfare Reform Act. And that is one thing that I urge all of 

you to do is to set the standard for data collection so we can measure this information, measure the participants, measure their outcomes across all states by using the same data sets. 

Mr. PANETTA. Outstanding. Thank you. Madam Chair, I yield 

back. 

128 

The CHAIR. Thank you very, very much. I thank all of you for 

being here today and your testimony. 

The Chair recognizes herself for 5 minutes. 

If I didn’t know better, I would think that this was a hearing 

about waivers. It is not. If I didn’t know better, I would think that 

there were no job requirements or training requirements for 

ABAWDs. There are. It is the law now. 

I listened to one of the witnesses talk about what happened in 

2006. This is 2019. In 2006, we were a manufacturing society in 

most major cities in this country. Today, we are more service and 

we don’t make anything in this country anymore. There was a time 

you could come out of high school and go into a factory and get a 

job. That doesn’t exist today, because the same corporations we 

give big tax breaks to take all of their business and make everything offshore. Yes, there were jobs in 2006. There aren’t today for 

low-skilled and unskilled workers. 

Let’s just talk about who really are ABAWDs. They are the people who clean these buildings that we work in every day and that 

some people sleep in every night. They are the people who serve 

us in the cafeteria, who fix our food. Those are ABAWDs. They 

work every single day, and even this government doesn’t pay them 

enough to make a living. There are people who work in this building who qualify for SNAP every month, that $1.40 a meal. Let’s 

talk about what it really is, and let’s also talk about jobs. 

We know that over the next 20 years, 80 percent of all jobs will 

require some form of STEM education. Most of the people we are 

talking about, the poorest of the poor, don’t have those skills, don’t 

have that education. There may be jobs, but they don’t qualify for 

them. 

If I had grown up maybe around a blueberry patch, I might have 

done that, too. There is not one in my neighborhood. My neighborhood is one where people just try to survive every day. I think that 

we have to be realistic about who we are talking about. 

I got into an elevator in this building. A person who cleans the 

building gets on with me, which is not really allowed for them to 

put their carts on with us. She wanted to tell me in tears how 

much it meant for her to get the SNAP benefits she gets every 

month. 

But no, we want to make this some big deal about being partisan, and it is not partisan. Hungry people are hungry people. People who work are people who work. If we are really honest with 

ourselves, and we started to talk to the people who are in these situations instead of believing that they are invisible and they are unworthy and undeserving, we might have a different outcome. 

Maybe we would sit down, as my colleague said here, and find a 

way to get them to the jobs that are available. Maybe we provide 

some transportation. Maybe we provide some training. Not just filling out an application, actually training them to do a job that exists. 

If I just didn’t know better, I wouldn’t even think I was in this 

country, if I didn’t know better. 

And so, I just want to say to all of my colleagues, I know we all 

care about the people we represent, but maybe sometimes we need 

to come out of these buildings and talk to them. Maybe we need 

129 

to go into a food bank and see who comes. That might be helpful, 

and not just assume who they are and what they are. And until 

the USDA can tell me who they are, then I am never going to support something like this, because not only does it not rely on any 

data when they could just wait a little while and get the data from 

the trials we have already done, but more importantly, because 

they don’t know who they are talking about. They have no idea. 

And so, you just make up something for people. 

It is time that this Congress, the people’s House, the Representatives of the people of this country, find out what our people want. 

And with that, I would close and ask my colleague if he has a 

closing statement. Oh, before that, Chairman Peterson asked that 

I enter into the record a letter of comment from Commissioner 

Tony Lourey with the Minnesota Department of Human Services. 

Without objection. 

[The letter referred to is located on p. 151.] 

Mr. JOHNSON. Yes, it is indeed true that the people who clean 

this building at night are worthy and deserving, and they are 

ABAWDs. And of course, it is absolutely true that the people who 

make the food in the cafeteria, they are worthy and they are deserving and they are ABAWDs. 

It is just as important to acknowledge that they are working and 

that their work is important, and that it is worthy of our respect. 

They are working and they are doing what they can to try to eke 

out a living and put themselves in a position where tomorrow can 

be better than yesterday. Work does that, and if a couple of things 

came out loud and clear that there is basis for agreement, it is first 

off that people who can work, should work. I want to thank the 

panelists for bringing that to the fore. 

Another thing that came out, particularly with Mr. Van Drew’s 

comments and others, is the importance of data, the importance of 

evidence. Evidence is powerful and data can light our way forward, 

and that is why I am concerned that there was resistance on the 

part of some Members of this Committee to a robust data capture 

component championed by Chairman Conaway and others during 

the last farm bill discussion. I am hopeful that since we all acknowledge the importance of data, we can work together to have 

better data capture opportunities in days to come. 

I would close by saying this, Madam Chair. I have heard that 

you run a tight ship and a fair one. You do. Thank you for a good 

hearing. 

The CHAIR. Thank you very much, Mr. Johnson. I appreciate it 

and I appreciate your ability to work with me and willingness to 

do so. 

Thank you all very much for being here. I appreciate your testimony. 

Under the Rules of the Committee, the record of today’s hearing 

will remain open for 10 calendar days to receive additional material and supplementary written responses from the witnesses to 

any questions posed by a Member. 

This hearing of the Subcommittee on Nutrition, Oversight, and 

Department Operations is adjourned. 

[Whereupon, at 10:50 a.m., the Subcommittee was adjourned.] 

[Material submitted for inclusion in the record follows:] 

131 

SUBMITTED LETTERS BY HON. MARCIA L. FUDGE, A REPRESENTATIVE IN CONGRESS

FROM OHIO

February 1, 2019 

Hon. SONNY PERDUE, 

Secretary, 

U.S. Department of Agriculture, 

Washington, D.C. 

Dear Secretary Perdue: 

As Chair of the Nutrition, Oversight, and Department Operations Subcommittee 

of the House Agriculture Committee, I write to request an extension of the 60 day 

comment period for the proposed rule regarding the treatment of Able-Bodied Adults 

Without Dependents (ABAWDs) in the Supplemental Nutrition Assistance Program 

(SNAP) entered into the Federal Register today. Given the complexity of and the significant interest in this topic, I request an immediate extension of the comment period from 60 to 120 days to allow for meaningful and robust comments. 

The proposed rule includes assumptions about ABAWDs and state administrative 

agencies that have been recently and thoroughly considered by Congress, and overwhelmingly rejected. In fact, legislative language similar to the proposed rule was 

included in the initial version of H.R. 2. This language was vetted in detail for 5 

months by Members of the 2018 Farm Bill Conference Committee before being 

struck from the final bill. As you know, the House and Senate ultimately passed 

a farm bill conference report by historic margins, and the President signed the bill 

without delay. 

During the farm bill signing ceremony, you said that USDA would do its ‘‘best 

to implement that bill’’ as Congress intended. This proposed rule does just the opposite. Therefore, I ask for an immediate extension of the comment period from 60 to 

120 days to allow Members of Congress, and the countless other advocates in favor 

of protecting SNAP from unwarranted attacks, the opportunity to better inform 

USDA of the hardships that will result if the Department moves forward with this 

harmful and intolerable proposed rule. 

Respectfully, 

Hon. MARCIA L. FUDGE, 

Chair, 

Subcommittee on Nutrition, Oversight, and Department Operations. 

February 26, 2019 

Hon. MARCIA L. FUDGE, 

Chair, 

Subcommittee on Nutrition, Oversight, and Department Operations, 

U.S. House of Representatives, 

Washington, D.C. 

Dear Chair Fudge: 

Thank you for your letter dated February 1, 2019, requesting an extension of the 

public comment period for the recently proposed rule affecting Supplemental Nutrition Program (SNAP) work requirements and the participation time limit for ablebodied adults without dependents (ABAWDs). 

The proposed rule includes administrative actions within the authority delegated 

to the Secretary within the Food and Nutrition Act of 2008. It would encourage 

broader application of the statutory ABAWD work requirement, consistent with the 

Administration’s focus on fostering self-sufficiency and promoting the dignity of 

work. I believe these proposed changes support our mutual goal of improving the 

lives of those participating in SNAP. 

I appreciate your interest in ensuring that the U.S. Department of Agriculture is 

able to receive meaningful and robust comments to this rule. Before the rule was 

published in the Federal Register on February 1, 2019, and before the 60 day comment period began, the proposed rule was available on our website beginning December 20, 2018, thereby providing interested stakeholders additional time to review the proposal and begin formulating their comments. Given the additional 

amount of time that the rule has been on public display, I believe that a 60 day 

comment period is a sufficient amount of time to receive meaningful and robust 

comments. 


11602111.eps
132 

Thank you for your support. If you need further assistance, please have your staff 

contact Erin Wilson with the Office of Congressional Relations at (202) 720–7095 

or erin.wilson@usda.gov. 

Sincerely, 

Hon. SONNY PERDUE, Secretary. 

SUBMITTED PROPOSED RULE BY HON. MARCIA L. FUDGE, A REPRESENTATIVE IN

CONGRESS FROM OHIO

Federal Register 

Vol. 84, No. 22 

Friday, February 1, 2019 

Proposed Rules 

DEPARTMENT OF AGRICULTURE 

FOOD AND NUTRITION SERVICE

7 CFR PART 273

[FNS–2018–0004] 

RIN 0584–AE57

SUPPLEMENTAL NUTRITION ASSISTANCE PROGRAM: REQUIREMENTS FOR ABLE-BODIED ADULTS

WITHOUT DEPENDENTS

AGENCY: Food and Nutrition Service (FNS), USDA. 

ACTION: Proposed rule. 

SUMMARY: Federal law generally limits the amount of time an able-bodied adult 

without dependents (ABAWD) can receive Supplemental Nutrition Assistance Program (SNAP) benefits to 3 months in a 36 month period, unless the individual 

meets certain work requirements. On the request of a state SNAP agency, the law 

also gives the Department of Agriculture (the Department) the authority to temporarily waive the time limit in areas that have an unemployment rate of over ten 

percent or a lack of sufficient jobs. The law also provides state agencies with a limited number of percentage exemptions that can be used by states to extend SNAP 

eligibility for ABAWDs subject to the time limit. The Department proposes to amend 

the regulatory standards by which the Department evaluates state SNAP agency requests to waive the time limit and to end the unlimited carryover of ABAWD percentage exemptions. The proposed rule would encourage broader application of the 

statutory ABAWD work requirement, consistent with the Administration’s focus on 

fostering self-sufficiency. The Department seeks comments from the public on the 

proposed regulations. 

DATES: Written comments must be received on or before April 2, 2019 to be assured of consideration. 

ADDRESSES: The Food and Nutrition Service, USDA, invites interested persons to 

submit written comments on this proposed rule. Comments may be submitted in 

writing by one of the following methods: 

• Preferred Method: Federal eRulemaking Portal: Go to http:// 

www.regulations.gov. Follow the online instructions for submitting comments. 

• Mail: Send comments to Certification Policy Branch, Program Development Division, FNS, 3101 Park Center Drive, Alexandria, Virginia 22302. 

• All written comments submitted in response to this proposed rule will be included in the record and will be made available to the public. Please be advised 

that the substance of the comments and the identity of the individuals or entities submitting the comments will be subject to public disclosure. FNS will 

make the written comments publicly available on the Internet via http:// 

www.regulations.gov. 

FOR FURTHER INFORMATION CONTACT: Certification Policy Branch, Program Development Division, FNS, 3101 Park Center Drive, Alexandria, Virginia 22302. 

SNAPCPBRules@fns.usda.gov. 


11602116.eps
133 

SUPPLEMENTARY INFORMATION: 

Background 

Acronyms or Abbreviations 

[Phrase, Acronym or Abbreviation] 

Able-Bodied Adult without Dependent(s), ABAWD(s) 

Advanced Notice of Public Rulemaking, ANPRM 

Bureau of Labor Statistics, BLS 

Census Bureau’s American Community Survey, ACS 

Code of Federal Regulations, CFR 

Department of Labor, DOL 

Employment and Training Administration, ETA 

Employment and Training, E&T 

Food and Nutrition Act of 2008, Act 

Food and Nutrition Service, FNS 

Labor Market Area(s), LMA(s) 

Labor Surplus Area(s), LSA(s) 

Supplemental Nutrition Assistance Program, SNAP 

The Personal Responsibility and Work Opportunity Reconciliation Act of 1996, 

PRWORA 

U.S. Department of Agriculture, the Department or USDA 

References 

The following references may be useful to help inform those wishing to provide 

comments. 

(1) Section 6(d) and section 6(o) of the Food and Nutrition Act of 2008, as 

amended 

(2) Title 7 of the Code of Federal Regulations, parts 273.7 and 273.24 

(3) Food Stamp Program: Personal Responsibility Provisions of the Personal Responsibility and Work Opportunity Reconciliation Act of 1996, Proposed Rule, 

64 FR 70920 (December 17, 1999). Available at: https:// 

www.federalregister.gov/?documents/?1999/?12/?17/?99-32527/?food-stampprogram-personalresponsibility-provisions-of-the-personalresponsibility-andwork 

(4) Food Stamp Program: Personal Responsibility Provisions of the Personal Responsibility and Work Opportunity Reconciliation Act of 1996, Final Rule, 66 

FR 4437 (January 17, 2001). Available at: https://www.federalregister.gov/ 

?documents/?2001/?01/?17/?01-1025/?foodstamp-program-personal-responsi 

bilityprovisions-of-the-personal-responsibilityand-work 

(5) Guide to Serving ABAWDs Subject to Time-limited Participation, 2015. 

Available at: https://fns-prod.azureedge.net/sites/default/files/Guide_to_ 

Serving_ABAWDs_Subject_to_Time_Limit.pdf 

(6) Guide to Supporting Requests to Waive the Time Limit for Able-Bodied Adults 

without Dependents, 2016. Available at: https://fns-prod.azureedge.net/sites/ 

default/files/snap/SNAP-Guide-to-Supporting-Requests-to-Waive-the-TimeLimit-for-ABAWDs.pdf 

(7) Expiration of Statewide ABAWD Time Limit Waivers, 2015. Available at: 

https://fns-prod.azureedge.net/sites/default/files/snap/SNAP-Expiration-ofStatewide-ABAWD-Time-Limit-Waivers.pdf 

(8) ABAWD Time Limit Policy and Program Access, 2015. Available at: https:// 

fns-prod.azureedge.net/sites/default/files/snap/ABAWD-Time-Limit-Policyand-Program-Access-Memo-Nov2015.pdf 

(9) ABAWD Questions and Answers, 2015. Available at: https://fnsprod.azureedge.net/sites/default/files/snap/ABAWD-Questions-and-AnswersJune%202015.pdf 

(10) ABAWD Questions and Answers, 2013. Available at: https://fnsprod.azureedge.net/sites/default/files/snap/ABAWD-Questions-and-AnswersDecember-2013.pdf 

(11) BLS Local Area Unemployment Statistics. Available at: https:// 

www.bls.gov/lau/ 

(12) BLS Labor Surplus Area. Available at: https://www.doleta.gov/programs/ 

lsa.cfm 

134 

The Rationale for Modifying Waiver Standards 

The President’s Executive Order on Reducing Poverty in America by Promoting 

Opportunity and Economic Mobility (April 10, 2018) provided guiding principles for 

public assistance programs, one of which was to improve employment outcomes and 

economic independence by strengthening existing work requirements for work-capable individuals. The Executive Order directed Federal agencies to review regulations 

and guidance documents to determine whether such documents are consistent with 

the principles of increasing self-sufficiency, well-being, and economic mobility. Consistent with the Executive Order and the Administration’s focus on fostering selfsufficiency, as well as the Department’s extensive operational experience with 

ABAWD waivers, the Department has determined that the standards for waivers 

must be strengthened so that the ABAWD work requirement is applied to ABAWDs 

more broadly. The Department is confident that these changes would encourage 

more ABAWDs to engage in work or work activities if they wish to continue to receive SNAP benefits. 

The Department believes that the proposed changes reinforce the Act’s intent to 

require these individuals to work or participate in work activities in order to receive 

SNAP benefits for more than 3 months in a 36 month period. Section 6(o) of the 

Act, entitled, ‘‘Work Requirements,’’ allows these individuals to meet the ABAWD 

work requirement by working and/or participating in a qualifying work program at 

least 20 hours per week (averaged monthly to 80 hours per month) or by participating in and complying with workfare. For the purposes of meeting the ABAWD 

work requirement, working includes unpaid or volunteer work that is verified by the 

state agency. The Act specifically exempts individuals from the ABAWD time limit 

and corresponding work requirement for several reasons, including, but not limited 

to, age, unfitness for work, having a dependent child, or being pregnant. 

The Act authorizes waivers of the ABAWD time limit and work requirement in 

areas in which the unemployment rate is above ten percent, or where there is a lack 

of sufficient jobs. The Department believes waivers of the ABAWD time limit are 

meant to be used in a limited manner in situations in which jobs are truly unavailable to ensure enforcement of the ABAWD work requirements as much as possible 

to promote greater engagement in work or work activities. 

Immediately following the Great Recession, the vast majority of the states, including the District of Columbia, Guam, and the Virgin Islands, qualified for and implemented statewide ABAWD time limit waivers in response to a depressed labor market. In the years since the Great Recession, the national unemployment rate has 

dramatically declined. Despite the national unemployment rate’s decline from 9.9 

percent in April 2010 to 3.9 percent in April 2018, a significant number of states 

continue to qualify for and use ABAWD waivers under the current waiver standards. Right now, nearly 1⁄2 of ABAWDs live in areas that are covered by waivers 

despite a strong economy. The Department believes waiver criteria need to be 

strengthened to better align with economic reality. These changes would ensure that 

such a large percentage of the country can no longer be waived when the economy 

is booming and unemployment is low. 

The Department is committed to enforcing the work requirements established by 

Congress and is concerned about the current level of waiver use in light of the current economy. The regulations afforded states broad flexibility to develop approvable 

waiver requests. The Department’s operational experience has shown that some 

states have used this flexibility to waive areas in such a way that was likely not 

foreseen by the Department. 

Some of the key concerns have stemmed from the combining of data from multiple 

individual areas to waive a larger geographic area (e.g., a group of contiguous counties) and the application of waivers in individual areas with low unemployment 

rates that do not demonstrate a lack of sufficient jobs. For example, some states 

have maximized the number of areas or people covered by waivers by combining 

data from areas with high unemployment with areas with low unemployment. This 

grouping has resulted in the combined area qualifying for a waiver when not all individual sub-areas would have qualified on their own. States have combined counties with unemployment rates under five percent with counties with significantly 

higher unemployment rates in order to waive larger areas. For example, current 

regulations required the Department to approve a state request to combine unemployment data for a populous county with a high unemployment rate of over ten 

percent with the unemployment data of several other less populous counties with 

very low unemployment rates that ranged between three and four percent. Other 

states have combined data from multiple areas that may only tenuously be considered an economic region. In some cases, states have grouped areas that are contiguous but left out certain low-unemployment areas that would otherwise logically be 

considered part of the region. In this manner, states have created questionable selfVerDate Aug 31 2005 11:16 Jun 14, 2019 Jkt 041481 PO 00000 Frm 00140 Fmt 6621 Sfmt 6621 P:\DOCS\116-02\36188.TXT BRIAN
135 

defined economic areas with gaping holes to leverage the flexibility of the regulations. 

The Department has also noted that, despite the improving economy, the lack of 

a minimum unemployment rate has allowed local areas to qualify for waivers based 

solely on having relatively high unemployment rates as compared to national average, regardless of how low local areas unemployment rates fall. Since the current 

waiver criteria have no floor, a certain percentage of states will continue to qualify 

for waivers even if unemployment continues to drop. 

It is the Department’s understanding that the intent of Congress in passing the 

Personal Responsibility and Work Opportunity Reconciliation Act of 1996 was to 

provide SNAP to unemployed ABAWDs on a temporary basis (3 months in any 3 

year period) with the expectation that they work and/or engage in a work program 

at least 20 hours per week, or participate in workfare, to receive SNAP on an ongoing basis. The Department is committed to implementing SNAP as Congress intended and believes that those who can work should work. The widespread use of 

waivers has allowed some ABAWDs to continue to receive SNAP benefits while not 

meeting the ABAWD work requirement for longer than 3 months. The proposed rule 

addresses these areas of concern and places safeguards to avoid approving waivers 

that were not foreseen by Congress and the Department, and to restrict states from 

receiving waivers in areas that do not clearly demonstrate a lack of sufficient jobs. 

As stated above, given the widespread use of ABAWD waivers during a period of 

historically low unemployment, the Department believes that the current regulatory 

standards should be reevaluated. Based on the Department’s approximately 2 decades’ experience with reviewing ABAWD waivers, the Department is proposing that 

the standards for approving these waivers be updated to ensure the waivers are applied on a more limited basis. The application of waivers on a more limited basis 

would encourage more ABAWDs to take steps towards self-sufficiency. 

The Department proposes stricter criteria for ABAWD waiver approvals that 

would establish stronger, updated standards for determining when and where a lack 

of sufficient jobs justifies temporarily waiving the ABAWD time limit. The proposed 

rule would also ensure the Department only issues waivers based on representative, 

accurate, and consistent economic data, where it is available. Limiting waivers 

would make more ABAWDs subject to the time limit and thereby encourage more 

ABAWDs to engage in meaningful work activities if they wish to continue to receive 

SNAP benefits. The Department recognizes that long-term, stable employment provides the best path to self-sufficiency for those who are able to work. The Department believes it is appropriate and necessary to encourage greater ABAWD engagement with respect to job training and employment opportunities that would not only 

benefit ABAWDs, but would also save taxpayers’ money. The Department and the 

states share a responsibility to help SNAP participants—especially ABAWDs—find 

a path to self-sufficiency. Through the stricter criteria for waiver approvals, the Department would encourage greater engagement in meaningful work activities and 

movement toward self-sufficiency among ABAWDs, thus reducing the need for nutrition assistance. 

Waiver Standards Framework 

Current regulations at 7 CFR 273.24(f) set standards and requirements for the 

data and evidence that states must provide to FNS to support a waiver request. 

States enjoy considerable flexibility to make these waiver requests pursuant to the 

current regulations. For example, these regulatory standards give states broad flexibility to define the waiver’s geographic scope. The discretion for states to define 

areas allows waivers based on data for combined areas that are not necessarily economically tied. An economically tied area is an area within which individuals can 

reside and find employment within a reasonable distance or can readily change employment without changing their place of residence. In addition, while the current 

regulations establish criteria for unemployment data that rely on standard Bureau 

of Labor Statistics (BLS) data or methods, the regulations also allow states to rely 

on alternative, less robust economic indicators, which include data other than unemployment data from BLS, to demonstrate a lack of sufficient jobs. Moreover, the 

waiver standards allow areas within states to qualify for waivers as a result of unemployment rates relative to the national average, without consideration for whether the national or local area unemployment rate is high or low. Put differently, 

under the current regulations, which do not include a local unemployment rate floor, 

even if the national unemployment rate falls, a particular area’s unemployment rate 

may support a waiver if that area’s unemployment rate is low but sufficiently higher 

than the national average. As a result of these and other shortcomings, the current 

regulations give states an opportunity to qualify for waivers and avoid the ABAWD 

time limit when economic conditions do not justify such relief. For these reasons, 

136 

1The term ‘‘state’’ refers to any of the 50 states, the District of Columbia, and the U.S. 

territories[.] 

the Department believes that the waiver standards under this proposed rule will 

better identify areas that do not have a sufficient number of jobs to provide employment for ABAWDs. 

As of September 2018, the national unemployment rate is the lowest unemployment rate since 1969; however, states continue to request and qualify for ABAWD 

waivers based on the current waiver criteria, which define the lack of sufficient jobs 

in an area too broadly. In April 2010, the national unemployment rate stood at 9.9 

percent. From 2010 through 2013, the vast majority of states qualified for and continued to implement statewide ABAWD time limit waivers. SNAP participation 

peaked at an average of 47.6 million recipients per month in FY 2013 and has 

gradually declined since then. In July 2013, the national unemployment rate was 

7.3 percent; 45 ABAWD time limit waivers covered the entire state,1 and six waivers covered specific areas within the state. In April 2018, SNAP participation totaled 39.6 million participants, and the national unemployment rate stood at 3.9 

percent. In April 2018, eight waivers applied to an entire state, and 28 covered specific areas within a state. Although the national unemployment rate has dropped 

from 9.9 percent in April 2010 to 3.9 percent in April 2018, many states continue 

to qualify for and use ABAWD time limit waivers under the current waiver standards, and nearly 1⁄2 of all ABAWDs live in areas that are covered by waivers. 

The Department is concerned that ABAWD time limit waivers continue to cover 

significant portions of the country and are out of step with a national unemployment rate hovering at less than four percent. Since the current waiver criteria have 

no floor, a certain percentage of states will continue to qualify for waivers even if 

unemployment continues to drop. In other words, regardless of how strong the economy is, the criteria are written in such a way that areas will continue to qualify 

even with objectively low unemployment rates. Many currently-waived areas qualified based on 24 month local unemployment rates below six percent. 

The current criteria for waiver approval permit states to qualify for waivers without a sufficiently robust standard for a lack of sufficient jobs. The waiver criteria 

should be updated to ensure states submit data that is more representative of the 

economic conditions in the requested areas. Such reforms would make sure the Department issues waivers based on representative, accurate, and consistent economic 

data. 

This proposed rule would set clear, robust, and quantitative standards for waivers 

of the ABAWD time limit. The proposal would also: Eliminate waivers for areas that 

are not economically tied together; eliminate the ability of an area to qualify for a 

waiver based on its designation as a Labor Surplus Area (LSA) by the Department 

of Labor; limit the use of alternative economic indicators to areas for which standard data is limited or unavailable, such as Indian Reservations and U.S. Territories; 

and provide additional clarity for states regarding the waiver request process. The 

proposed changes would ensure the Department issues waivers only to provide targeted relief to areas that demonstrate a lack of sufficient jobs or have an unemployment rate above ten percent and that the ABAWD time limit encourages SNAP participants to find and keep work if they live in areas that do not lack sufficient jobs. 

Background 

Previous Action 

On February 23, 2018, the Department published an Advanced Notice of Public 

Rulemaking (ANPRM) entitled ‘‘Supplemental Nutrition Assistance Program: Requirements and Services for Able-Bodied Adults Without Dependents’’ (83 FR 8013) 

to seek public input to inform potential policy, program, and regulatory changes 

that could consistently encourage ABAWDs to obtain and maintain employment and 

thereby decrease food insecurity. The Department specifically asked whether 

changes should be made to: (1) The existing process by which state agencies request 

waivers of the ABAWD time limit; (2) the information and data states must provide 

to support the waiver request; (3) the Department’s implementation of the waiver 

approval; and (4) the waiver’s duration. The ANPRM generated nearly 39,000 comments from a range of stakeholders including private citizens, government agencies 

and officials, food banks, advocacy organizations, and professional associations. 

The comments addressed the broad scope of topics covered by the ANPRM. Comments about the ABAWD waiver included diverse perspectives, ranging from those 

who supported stricter waiver approval requirements to those who favored maintaining or expanding the criteria for waiver approval. Many commenters favored no 

change or expressed support for greater flexibility. Other commenters identified a 

137 

number of areas of concern with current practices, including the use of waivers by 

states to waive the ABAWD work requirement and avoid promoting work, waiving 

areas with relatively low unemployment rates, and allowing the use of certain 

metrics for waiver approvals. 

The Department received more than 3,500 comments regarding potential reforms 

to the ABAWD time limit and waivers of the time limit through the Department’s 

request for information (RFI) entitled, ‘‘Identifying Regulatory Reform Initiatives’’ 

published July 17, 2017 (82 FR 32649). This RFI requested ideas on how the Department can provide better customer service and remove unintended barriers to 

participation in the Department’s programs in ways that least interfere with the Department’s customers and allow the Department to accomplish its mission. The Department specifically requested ideas on regulations, guidance documents, or any 

other policy documents that require reform. While commenters disagreed with certain SNAP provisions outlined previously, specific changes to regulations and policies were not provided. The Department received a range of comments to the RFI 

in addition to the comments listed above that are not relevant to this proposed rule. 

Summary of Proposed Changes 

The Department believes current regulations at 7 CFR 273.24(c) and 7 CFR 

273.24(f) should be updated and strengthened. The proposed rule focuses on updating the standards for ABAWD waivers. Current regulations at 7 CFR 273.24(f) set 

standards and requirements for the data and evidence that states must provide to 

FNS to support an ABAWD waiver request. States enjoy considerable flexibility to 

make these waiver requests pursuant to the current regulations. This flexibility has 

resulted in the widespread use of waivers during a period of low unemployment, 

which reduces the application of the work requirement. 

The Department proposes several changes. First, the proposed rule would limit 

the ability of areas to qualify for waivers as local economies and the overall national 

economy improve. Second, the proposed rule would no longer allow state agencies 

to combine unemployment data from areas with high unemployment with areas 

with lower unemployment and more plentiful employment opportunities in order to 

maximize the area waived. Instead, the proposed rule would ensure the Department 

issues waivers only to economically tied areas that meet the new criteria defining 

what is meant by a lack of sufficient jobs. The proposed rule would also limit the 

duration of waivers to 1 year, and curtail the use of less robust data to approve 

waivers. The subsequent sections provide details about the changes proposed in this 

rule. 

Discussion of Proposed Changes 

General 

The Department proposes that the rule, once finalized, would go into effect on October 1, 2019, which is the beginning of Federal Fiscal Year 2020. All waivers in 

effect on October 1, 2019, or thereafter, would need to be approvable according to 

the new rule at that time. Any approved waiver that does not meet the criteria established in the new rule would be terminated on October 1, 2019. States would be 

able to request new waivers if the state’s waiver is expected to be terminated. The 

Department requests feedback from states regarding the implementation date. In 

addition, the Department proposes clarifying that any state agency’s waiver request 

must have the Governor’s endorsement to ensure that such a critical request is supported at the highest levels of state government. 

Establishing Core Standards for Approval 

The Department proposes updating criteria for ABAWD time limit waivers to improve consistency across states and only allow approvals in areas where waivers are 

truly necessary. These revisions would include the establishment of core standards 

that would allow a state to reasonably anticipate whether it would receive approval 

from the Department. These core standards would serve as the basis for approval 

for the vast majority of waiver requests, save for areas with exceptional circumstances or areas with limited data or evidence, such as Indian Reservations and 

U.S. Territories. The proposed rule would continue to allow approvals for waivers 

based on data from BLS or a BLS-cooperating agency that show an area has a recent, 12 month average unemployment rate over ten percent. 

The proposed rule emphasizes that the basis for approval of waivers would be 

sound data and evidence that primarily relies on data from BLS or BLS-cooperating 

agencies. Any supporting unemployment data provided by the state would need to 

rely on standard BLS data or methods. BLS unemployment data is generally considered to be reliable and robust evidence for evaluating labor market conditions. BLS 

is an independent Federal statistical agency that is required to provide accurate and 

138 

objective statistical information and is the principal fact-finding agency for the Federal Government in the broad field of labor economics and statistics. It collects, 

processes, analyzes, and disseminates essential statistical data for the public and 

Federal agencies. 

The proposed core standards for waiver approval would be codified in 7 CFR 

273.24(f)(2). 

Core Standards: Retaining Waivers Based On An Unemployment Rate Over Ten 

Percent 

The Department does not propose changes to the regulations for waivers when an 

area has an unemployment rate over ten percent. The proposed rule would continue 

to allow approvals for waivers based on data from BLS or a BLS-cooperating agency 

that show an area has a recent, 12 month average unemployment rate over ten percent. 

Core Standards: Establishing a Floor for Waivers Based On the 20 Percent Standard 

Current regulations at 7 CFR 273.24(f)(2) and (3) provide for waiver approvals for 

requested areas with an average unemployment rate at least 20 percent above the 

national average for a recent 24 month period, beginning no earlier than the same 

24 month period that DOL uses to determine LSAs for the current fiscal year (otherwise known as the ‘‘20 percent standard’’). Under the current regulations, the Department adopted the 20 percent standard, in addition to LSA designation, to provide states with the flexibility to support waivers for areas in the country that are 

not considered by DOL for LSA designation and to allow states to use a more flexible 24 month reference period. 

There are key differences between the two standards. DOL’s criteria for LSAs require an average unemployment rate that is at least 20 percent above the national 

average and at least six percent for the preceding 2 calendar years (a 24 month period). DOL’s local unemployment rate floor of six percent prevents areas with unemployment rates below that threshold from qualifying as LSAs. The 20 percent standard is the same, except that it allows for a flexible 24 month data reference period 

(no earlier than that which is used for LSAs) and it does not include any unemployment rate floor. 

Based upon operational experience, the Department has observed that, without an 

unemployment rate floor, local areas will continue to qualify for waivers under the 

Department’s 20 percent standard based on high unemployment relative to the national average even as local unemployment rates fall to levels as low as five to six 

percent (depending upon the national rate). The Department believes that amending 

the waiver regulations to include an unemployment floor is a critical step in achieving more targeted criteria. While the 20 percent standard is similar to the calculation of an LSA, the Department believes it is appropriate to request public comment 

to explore a floor that is designed specifically for ABAWD waivers. 

The Department believes a floor should be set for the 20 percent standard so that 

areas do not qualify for waivers when their unemployment rates are generally considered to be normal or low. The ‘‘natural rate of unemployment’’ is the rate of unemployment expected given normal churn in the labor market, with unemployment 

rates lower than the natural rate tending to result in inflationary pressure on 

prices. Thus, unemployment rates near or below the ‘‘natural rate of unemployment’’ 

are more indicative of the normal delay in unemployed workers filling the best existing job opening for them than a ‘‘lack of sufficient jobs’’ in an area. Generally, the 

‘‘natural rate of unemployment’’ hovers around five percent. The Department believes that only areas with unemployment rates above the ‘‘natural rate of unemployment’’ should be considered for waivers. The Department seeks to establish a 

floor that is in line with the Administration’s effort to encourage greater engagement in work and work activities. The Department believes that the seven percent 

floor for the 20 percent standard would strengthen the standards for waivers so that 

the ABAWD work requirement would be applied more broadly and fully consider the 

‘‘lack of sufficient jobs’’ criteria in the statute. Furthermore, this aligns with the proposal in the Agriculture and Nutrition Act of 2018, H.R. 2, 115th Cong. § 4015 (as 

passed by House, June 21, 2018). As stated previously, the Department seeks to 

make the work requirements the norm rather than the exception to the rule because 

of excessive use of ABAWD time limit waivers to date. Using the proposed rule’s 

seven percent floor for this criterion and eliminating waiver approvals based on an 

LSA designation (as well as utilizing the proposed limit on combining areas discussed below), an estimated 11 percent of ABAWDs would live in areas subject to 

a waiver. Currently, approximately 44 percent of ABAWDs live in a waived area. 

The Department views the proposal as more suitable for achieving a more comVerDate Aug 31 2005 11:16 Jun 14, 2019 Jkt 041481 PO 00000 Frm 00144 Fmt 6621 Sfmt 6621 P:\DOCS\116-02\36188.TXT BRIAN
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prehensive application of work requirements so that ABAWDs in areas that have 

sufficient number of jobs have a greater level of engagement in work and work activities, including job training. In sum, the proposed rule modifies the current waiver criterion so that an area must have an average unemployment rate at least 20 

percent above the national average and at least seven percent for a recent 24 month 

period, beginning no earlier than the same 24 month period that DOL uses to determine LSAs for the current fiscal year, to qualify for a waiver. The seven percent 

floor prevents a requested area with an unemployment rate 20 percent above the 

national average, but below seven percent, from qualifying for a waiver. 

Although the Department believes the local unemployment floor should be set at 

seven percent to best meet its goals of promoting self-sufficiency and ensuring areas 

with unemployment rates generally considered normal are not waived, it is requesting evidence-based and data-driven feedback on the appropriate threshold for the 

floor. Specifically, the Department requests feedback on which unemployment rate 

floor—six percent, seven percent, or ten percent—would be most effective at limiting 

waivers consistent with the Act’s requirement that waivers be determined based on 

a lack of sufficient jobs. 

The Department is interested in public comments on establishing an unemployment floor of six percent, which would be consistent with DOL standards for LSAs. 

A six percent floor would require that an area demonstrate an unemployment rate 

of at least 20 percent above the national average for a recent 24 month period and 

at least a six percent unemployment rate for that same time period in order to receive waiver approval. The six percent floor also bears a relationship to the ‘‘natural 

rate of unemployment.’’ in that it is approximately 20 percent higher. As previously 

noted, the ‘‘natural rate of unemployment’’ generally hovers around five percent, 

meaning that 20 percent above that rate is 6.0 percent. In combination with other 

changes in the proposed rule, the Department estimates that a six percent floor 

would reduce waivers to the extent that approximately 24 percent of ABAWDs 

would live in waived areas. The Department is concerned that too many areas would 

qualify for a waiver of the ABAWD time limit with a six percent floor and that too 

few individuals would be subject to the ABAWD work requirements, which can be 

met through working or participating in a work program or workfare program, 

thereby moving fewer individuals towards self-sufficiency. 

The Department would also like to receive comments on establishing a floor of ten 

percent for the 20 percent standard. A ten percent floor would allow for even fewer 

waivers than the other options and would result in the work requirements being applied in almost all areas of the country. In combination with other changes in the 

proposed rule, the Department estimates that a ten percent floor would reduce waivers to the extent that approximately two percent of ABAWDs would live in waived 

areas. 

It is important to note that a ten percent floor would be distinct from the criteria 

for approval of an area with an unemployment rate of over ten percent. The ten percent unemployment floor would be attached to the 20 percent standard, which would 

mean an area would require an average unemployment rate 20 percent above the 

national average for a recent 24 month period and at least ten percent for the same 

period; the other similar, but separate standard requires an area to have an average 

unemployment rate of over ten percent for a 12 month period. 

Based on the Department’s analysis, nearly 90 percent of ABAWDs would live in 

areas without waivers and would be encouraged to take steps towards self-sufficiency if a floor of seven percent was established. In comparison, a six percent floor 

would mean that 76 percent of ABAWDs would live in areas without waivers and 

a ten percent floor would mean that 98 percent of ABAWDs would live in areas 

without waivers. A higher floor allows for the broader application of the time limit 

to encourage self-sufficiency. 

The Department is thus requesting comments on the various proposed options for 

setting a floor for the 20 percent standard. This will ensure that the Department 

fully considers the range of evidence available to establish a floor that meets the 

need of evaluating waivers. 

Core Standards: Retaining the Extended Unemployment Benefits Qualification 

Standard 

Under the proposed rule, the Department would continue to approve a state’s 

waiver request that is based upon the requesting state’s qualification for extended 

unemployment benefits, as determined by DOL’s Unemployment Insurance Service. 

Extended unemployment benefits are available to workers who have exhausted regular unemployment insurance benefits during periods when certain economic conditions exist within the state. The extended benefit program is triggered when the 

state’s unemployment rate reaches certain levels. Qualifying for extended benefits 

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is an indicator, based on DOL data, that a state lacks sufficient jobs. Current regulations include this criterion as evidence of lack of sufficient jobs. The Department 

has consistently approved waivers based on qualification for extended unemployment benefits because it has been a clear indicator of lack of sufficient jobs and an 

especially responsive indicator of sudden economic downturns, such as the Great Recession. Therefore, the Department proposes to continue to include this criterion, reframed as a core standard for approval in this proposed regulation. 

The three provisions described above (the unemployment rate over ten percent 

standard, the 20 percent standard, and the qualification for extended unemployment 

benefits standard), would be considered the core standards for approval and, thus, 

the basis for most conventional waiver requests and approvals. The core standards 

would be codified in 7 CFR 273.24(f)(2). 

Criteria Excluded From Core Standards 

The proposed core standards would not include some of the current ABAWD time 

limit waiver criteria that are rarely used, sometimes subjective, and not appropriate 

when other more specific and robust data is available, such as unemployment rates 

from BLS. These excluded criteria include a low and declining employment-to-population ratio, a lack of jobs in declining occupations or industries, or an academic 

study or other publication(s) that describes an area’s lack of jobs. These standards 

would no longer suffice for a waiver’s approval if BLS data is available. These proposed changes would ensure that ABAWD time limit waiver requests are only approved in areas where waivers are truly necessary. 

The proposed rule would emphasize sound data and evidence that primarily relies 

on BLS and other DOL data for waiver approvals. Any supporting unemployment 

data that a state provides must, under the core standards, rely on standard data 

from BLS or a BLS-cooperating agency. 

Other Data and Evidence in Exceptional Circumstances 

The proposed core standards would form the primary basis for determining waiver 

approval. However, the rule also proposes that the Department can approve waiver 

requests in exceptional circumstances based on other data and evidence. The Department proposes that other data and evidence still primarily rely on BLS unemployment data. Such alternative data would only be considered in exceptional circumstances or if BLS data is limited, unavailable, or if BLS develops a new method 

or data that may be applicable to the waiver review process. Given that economic 

conditions can change quickly, the Department believes it is appropriate to maintain 

a level of flexibility to approve waivers as needed in extreme, dynamic circumstances. Such waiver requests must demonstrate that an area faces an exceptional circumstance and provide data or evidence that the exceptional circumstance 

gives rise to an area not having a sufficient number of jobs to provide employment 

for the individuals in the area. For example, an exceptional circumstance may arise 

from the rapid disintegration of an economically and regionally important industry 

or the prolonged impact of a natural disaster. A short-term aberration, such as a 

temporary closure of a plant, would not fall within the scope of exceptional circumstances. For waiver requests in exceptional circumstances, the state agency may 

use additional data or evidence other than those listed in the core standards to support its need for a waiver under exceptional circumstances. In these instances, the 

state may provide data from the BLS or a BLS-cooperating agency showing an area 

has a most recent 3 month average unemployment rate over ten percent. This provision to strengthen the standards for waivers would be codified in 7 CFR 273.24(f)(3). 

Restricting Statewide Waivers 

Current regulations at 7 CFR 273.24(f)(6) and the Department’s policy guidance 

provide states with the discretion to define the areas to be covered by waivers. A 

state may request that a waiver apply to the entire state (statewide) or only to certain areas within the state (e.g., individual counties, cities, or towns), as long as the 

state provides data that corresponds to each requested area showing that the area 

meets one of the qualifying standards for approval. 

The proposed rule would eliminate statewide waiver approvals when sub-state 

data is available through BLS, except for those waivers based upon a state’s qualification for extended unemployment benefits as determined by DOL’s Unemployment Insurance Service. The Department proposes this change so that waivers of 

the ABAWD time limit are more appropriately targeted to those particular areas in 

which unemployment rates are high. Since statewide unemployment figures may include areas in which unemployment rates are relatively low, the Department believes that a more targeted approach would ensure that waivers exist only in areas 

that do not have a sufficient number of jobs to provide employment for the individuals living in that specific area. This proposed change further supports the DepartVerDate Aug 31 2005 11:16 Jun 14, 2019 Jkt 041481 PO 00000 Frm 00146 Fmt 6621 Sfmt 6621 P:\DOCS\116-02\36188.TXT BRIAN
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2 An LMA is an economically integrated geographic area within which individuals can reside 

and find employment within a reasonable distance or can readily change employment without 

changing their place of residence. LMAs include Federally-designated statistical areas such as 

metropolitan statistical areas, micropolitan statistical areas, and other combined statistical 

areas. A nationwide list of every LMA is maintained by BLS. 

ment’s goal that more individuals are subject to the ABAWD time limit and work 

requirement, which can be met through working or participating in a work program 

or workfare program, consistent with the intent of the Act. 

The Department requests public comment specific to the proposed restriction on 

statewide waivers, especially with consideration to how the change may affect different states in different ways based upon geographic size, population, and other 

factors. 

These changes would be codified in 7 CFR 273.24(f)(4). 

Restricting the Combining of Data to Group Sub-State Areas 

Current regulations at 7 CFR 273.24(f)(6) and the Department’s policy guidance 

provide states considerable flexibility to define areas covered by ABAWD waivers. 

This flexibility allows states to combine data to group two or more sub-state areas, 

such as counties, together (otherwise referred to as ‘‘grouped’’ areas or ‘‘grouping’’). 

In order to meet the requirement for qualifying data or evidence that corresponds 

to the requested area, states use the unemployment and labor force data from the 

individual areas in the group to calculate an unemployment rate representative of 

the whole group. States can only group areas and support approval based on qualifying unemployment data. Under current regulations, states must demonstrate that 

the areas within any such group are contiguous and/or share the same Federal- or 

state-recognized economic region. For example, two or more contiguous counties 

could be grouped together, and the group’s average unemployment rate could be calculated, by combining the unemployment and labor force data from each individual 

county. 

The Department’s existing general conditions for the grouping of areas—that the 

areas must be either contiguous and/or share the same economic region—were intended to ensure that the areas grouped together are economically tied. However, 

in practice, the Department has learned that its standards for combining areas provide too much flexibility for state agencies and are often ineffective at ensuring that 

states are only grouping areas that are economically tied. For example, some states 

have grouped nearly all contiguous counties in the state together while omitting a 

few counties with relatively low unemployment in order to maximize the waived 

areas in the state. In other cases, states have grouped certain towns together that 

share the same economic region while omitting others with relatively low unemployment from the group, thereby maximizing the waived areas in the state. 

The proposed rule would prohibit states from grouping areas, except for areas that 

are designated a Labor Market Area (LMA) by the Federal Government.2 This 

change would ensure that only areas that are economically tied are grouped together. Moreover, the proposed rule would require states to include the unemployment data representative of all areas in the LMA in the state. As a result, states 

would be unable to omit certain areas within the LMA in the state for the purposes 

of achieving a qualifying unemployment rate for part of an LMA. These changes 

would be codified in 7 CFR 273.24(f)(5). 

The Department requests public comments on whether it should include Labor 

Market Areas (LMAs) defined by the Federal Government as the basis for grouping 

areas or whether it should prohibit grouping entirely. If grouping were prohibited 

entirely, waived areas would be limited to individually qualifying jurisdictions with 

corresponding data (for example, counties and their equivalents, cities, and towns). 

The Department requests comments on the potential impacts of either policy. The 

Department believes that only allowing the use of Federally designated LMAs will 

limit the combination of areas that are not contiguous and economically integrated. 

The Department is interested in feedback on whether the LMA definition will target 

waivers to jurisdictions with a demonstrable lack of sufficient jobs without including 

jurisdictions that do not lack sufficient jobs. 

Duration of Waiver Approvals and Timeliness of Data 

The proposed approach would limit the duration of waiver approvals. Under the 

current regulations, the Department typically approves waivers for 1 year. However, 

the current regulations allow the Department to approve shorter or longer waivers 

in certain circumstances. The Department proposes limiting a waiver’s duration to 

1 year, but continuing to allow a waiver for a shorter period at a state’s request. 

The Department believes that a 1 year waiver term allows sufficient predictability 

142 

for states to plan and implement the waiver; at the same time, a 1 year waiver term 

ensures that the waiver request reflects current economic conditions. 

The proposed rule would also prioritize recent data by preventing states from requesting to implement waivers late in the Federal fiscal year, which broadens the 

available data reference period. Through operational experience, the Department 

has observed that several states that have historically requested 12 month waivers 

on a fiscal year basis (i.e., October 1 of 1 year through September 30 of the following 

year), have shifted their waiver request and implementation dates to later in the 

fiscal year (e.g., September 1 through August 31). The states that have made this 

shift have supported their waivers based on the 20 percent standard. In the current 

regulations, the 24 month data reference period for this waiver is tied to the fiscal 

year and only updates each year on October 1. The Department has noticed that 

as the unemployment rates have improved, states that shift the waiver operational 

period to later in the fiscal year have been able to capitalize on older data and qualify for waivers of the ABAWD time limit for additional time. States are able to take 

advantage of this loophole if their unemployment rates for the requested areas have 

been improving relative to the national average. As a result, these states are able 

to obtain a waiver and maximize the areas waived into the next fiscal year, using 

data that is no longer appropriate as of the October 1 update. 

To curtail this practice, the Department proposes that waivers based on the 20 

percent standard would not be approved beyond the fiscal year in which the waiver 

is implemented. In addition, these waivers must utilize data from a 24 month period 

no less recent than that DOL used in its current fiscal year LSA designation. Such 

an approach ensures waivers rely on sufficiently recent data for the current fiscal 

year and prevents states from using older data, which may not accurately reflect 

current economic conditions. 

This provision would streamline the implementation of the program and would be 

codified in 7 CFR 273.24(f)(6). 

Areas With Limited Data or Evidence 

Current practices provide flexibility to state agencies to rely on alternative data 

sources regardless of whether the area has corresponding BLS unemployment data 

available. Currently, the Department may approve requests supported by an estimated unemployment rate of an area based on available data from BLS and Census 

Bureau’s American Community Survey (ACS), a low and declining employment-topopulation ratio, a lack of jobs as a consequence of declining occupations or industries, or an academic study or other publication describing the area’s lack of a sufficient number of jobs. At times, state agencies will use these alternative data sources 

to justify a waiver request even when the corresponding BLS data shows that the 

unemployment rate in the area is relatively low. As stated previously, the Department believes that waivers of the ABAWD time limit should be limited to only circumstances in which the area clearly does not have a sufficient number of jobs to 

provide employment for the individuals. By not restricting the use of these alternative to areas with limited data or evidence, the Department has permitted states 

to take advantage of these alternative data sources, when BLS employment data is 

readily available. 

Under the proposed rule, all of these criteria would only be applicable to areas 

for which BLS or a BLS-cooperating agency data is limited or unavailable, such as 

a reservation area or U.S. Territory. In these areas, the Department could approve 

requests supported by an estimated unemployment rate of an area based on available data from BLS and ACS, a low and declining employment-to-population ratio, 

a lack of jobs as a consequence of declining occupations or industries, or an academic study or other publication describing the area’s lack of a sufficient number 

of jobs. Waiver requests for an area for which standard data from BLS or a BLScooperating agency is limited or unavailable would not be required to conform to the 

criteria for approval proposed under paragraphs (f)(2), (f)(3), (f)(4), (f)(5), and (f)(6). 

Additionally, the Department would consider other data in line with BLS methods 

or considered reliable. This allows for flexibility if new methods or data are developed for Indian Reservation or U.S. Territory regions currently with limited or no 

data. 

Using an estimated unemployment rate based on available data from BLS and 

ACS is part of current practice. The Department proposes codifying this criteria in 

the regulations only for areas with limited data or evidence, such as a reservation 

area or U.S. Territory. Currently, states often estimate unemployment rates for reservation areas by applying data from ACS to available BLS data. In addition, some 

Tribal governments generate their own labor force and/or unemployment data, 

which would remain acceptable to support a waiver. 

These changes would be codified in 7 CFR 273.24(f)(7). 

143 

3 Under current regulations, the state must certify that data from the BLS or the BLS-cooperating agency show a most recent 12 month average unemployment rate over ten percent or that 

ETA designated the area as an LSA for the current fiscal year. 

Other Changes to Waivers 

The proposed rule would eliminate three provisions in current regulations: The 

designation as an LSA as a criterion for approval; the implementation of waivers 

before approval; and the historical seasonal unemployment as a criterion for approval. These provisions are eliminated to ensure that the ABAWD work requirement is applied in accordance with the Department’s goal to strengthen work requirements. 

The proposed rule would no longer allow an area to qualify for a waiver based 

on DOL’s Employment and Training Administration (ETA) designation of the area 

as an LSA for the current fiscal year. This change is central to the Department’s 

efforts to raise the standards by which it determines whether an area is lacking a 

sufficient number of jobs to provide employment for ABAWDs in order to require 

more ABAWDs to engage in work, work training, or workfare if they wish to receive 

SNAP. As explained in a previous section, DOL’s criteria for LSAs require an average unemployment rate that is at least 20 percent above the national average and 

at least six percent for the preceding 2 calendar years (a 24 month period). The Department is eliminating LSA designation as a basis for waiver approval because 

LSAs are determined using a minimum unemployment rate floor of six percent, 

whereas the Department proposes using a minimum unemployment rate of seven 

percent for its similar, but more flexible, 20 percent standard. Continuing to allow 

LSA designation as a basis for waiver approval would be inconsistent. Moreover, 

LSAs are not designated for all different types of areas across the country, and having an LSA criteria separate from the 20 percent criteria could be seen as unnecessary moving forward. 

The proposed rule would bar states from implementing a waiver prior to its approval. Though rarely used, current regulations allow a state to implement an 

ABAWD waiver as soon as the state submits the waiver request based on certain 

criteria.3 By removing the current pertinent text in 273.24(f)(4), the proposed rule 

would require states to request and receive approval before implementing a waiver. 

This would allow the Department to have a more accurate understanding of the status of existing waivers and would provide better oversight in the waiver process. It 

would also prevent waivers from being implemented until the Department explicitly 

reviewed and approved the waiver. 

The proposed rule would also remove the criterion of a historical seasonal unemployment rate over ten percent as a basis for approval. Historical seasonal unemployment does not demonstrate a prolonged lack of sufficient number of jobs to provide employment for the individuals. Historical seasonal unemployment rates, by 

definition, are limited to a relatively short period of time each year. Nor does a historical seasonal unemployment rate indicate early signs of a declining labor market. 

Historical seasonal unemployment rates are cyclical rather than indicative of declining conditions. Based on operational experience, the Department has not typically 

seen the use of this criterion by states. The Department has not approved a waiver 

under this criterion in more than 2 decades. For these reasons, the Department proposes removing a historical seasonal average unemployment rate as a way to qualify 

for a waiver. 

In addition, as stated previously, the proposed rule would no longer provide for 

statewide waivers except for those waivers approved based upon a state’s qualification for extended unemployment benefits. 

Ending the ‘‘Carryover’’ of ABAWD Exemptions 

The proposed rule would end the unlimited carryover and accumulation of 

ABAWD percentage exemptions, previously referred to as 15 percent exemptions before the enactment of the Agriculture Improvement Act of 2018. Upon enactment, 

Section 6(o)(6) of the Act provides that each state agency be allotted exemptions 

equal to an estimated 12 percent of ‘‘covered individuals,’’ which are the ABAWDs 

who are subject to the ABAWD time limit in the state in Fiscal Year 2020 and each 

subsequent fiscal year. States can use these exemptions available to them to extend 

SNAP eligibility for a limited number of ABAWDs subject to the time limit. When 

one of these exemptions is provided to an ABAWD, that one ABAWD is able to receive 1 additional month of SNAP benefits. The Act and current regulations give 

states discretion whether to use these exemptions, and, as a result, some states use 

the exemptions that are available to them and others do not. 

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able to each state. Based on the Act’s instructions, the regulations provide the specific formulas that the Department must use to estimate the number of exemptions, 

which are referred to as ‘‘earned’’ exemptions, and to adjust the exemptions available to the state each year. The proposed rule would not change any part of the 

calculation that the Department follows to estimate earned exemptions, or any other 

part of 273.24(g). The proposed rule would only change the calculation that the Department uses to adjust the number of exemptions available for each fiscal year at 

7 CFR 273.24(h). 

The regulation’s current interpretation of Section 6(o)(6)(G) of the Act, which requires the adjustment of exemptions, causes unused exemptions to carry over and 

accumulate from 1 year to the next, unless the state uses all of its available exemptions in a given year. For FY 2018, states earned approximately 1.2 million exemptions, but had about an additional 7.4 million exemptions available for use due to 

the carryover of unused exemptions from previous fiscal years. The Department 

views the carryover of significant amounts of unused exemptions to be an unintended outcome of the current regulations. The Department is concerned that such 

an outcome is inconsistent with Congressional intent to limit the number of exemptions available to states each year. Concerns about the carryover of exemptions were 

also expressed by the September 2016, USDA Office of the Inspector General (OIG) 

audit report ‘‘FNS Controls Over SNAP Benefits for Able-Bodied Adults Without Dependents.’’ Therefore, the Department proposes revising 7 CFR 273.24(h) to end the 

unlimited carryover of unused percentage exemptions. The Department proposes 

this change to implement the Act more effectively and to advance further the Department’s goal to promote self-sufficiency. 

In order to address the carryover issue, the proposed rule would change the adjustment calculation that the Department uses to increase or decrease the number 

of exemptions available to each state for the fiscal year based on usage during the 

preceding fiscal year. The proposed rule would no longer allow for unlimited carryover from all preceding years. Instead, each state agency’s adjustment would be 

based on the number of exemptions earned in the preceding fiscal year minus the 

number of exemptions used in the preceding fiscal year. The resulting difference 

would be used to adjust (by increasing or decreasing) the earned exemption amount. 

In addition, the adjustment will apply only to the fiscal year in which the adjustment is made. 

The three examples below show how the proposed rule’s adjustment calculation 

would work in practice based on no exemption use, varied exemption use, and exemption overuse. These examples assume that a state earns five new exemptions 

every year over a 4 year period. 

Example 1, No Exemption Use 

Example 1 shows how the proposed adjustment calculation would work for a state 

that uses zero exemptions, and how it would end the carryover and accumulation 

of unused exemptions. The state earned five exemptions for the current fiscal year 

(FY) of 2021 in this example (row A). The state’s adjustment for FY 2021 is based 

on the number of exemptions earned in the previous year (FY 2020) minus the number of exemptions used for the previous year (FY 2020). In this example, we assume 

the state earned five exemptions in FY 2020 and used no exemptions in FY 2020, 

so the adjustment for FY 2021 is five (row B). The adjustment of five (row B) is 

then added to the five earned for FY 2021 (row A) to obtain the state’s total of ten 

exemptions after adjustment for FY 2021 (row C). In FY 2021, the state uses zero 

exemptions (row D), so it does not have any overuse liability for that year because 

row E results in a positive number. In FY 2022, FY 2023, and FY 2024, the calculation is the same and results are the same each year. The number of exemptions 

available to the state is increased based on the number earned for and used in the 

preceding fiscal year, but the state does not carryover accumulated exemptions indefinitely. Whereas the state would have 25 total exemptions after adjustment for 

FY 2024 under the current regulations, the state would have ten total exemptions 

after adjustment for FY 2024 under the proposed regulation. 

EXAMPLE 1

Fiscal year (FY) 2021 2022 2023 2024 

A ......... Earned for current FY ............................................................. 5 5 5 5 

B ......... (+) Adjustment for current FY (earned minus used for previous FY).5 5 5 5 

C ......... (=) Total after adjustment for current FY ............................. 10 10 10 10 

D ......... (¥) Used in current FY ........................................................... 0 0 0 0 

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EXAMPLE 1—CONTINUED

Fiscal year (FY) 2021 2022 2023 2024 

E ......... (=) Liability for overuse? (Yes or No) ..................................... 10 (No) 10 (No) 10 (No) 10 (No) 

Example 2, Varied Exemption Use 

Example 2 shows how the proposed adjustment calculation would work for a state 

that uses different amounts of exemptions each fiscal year and therefore receives 

an increase or decrease in the exemptions available to it each subsequent fiscal 

year. In other words, the number of exemptions available to the state is adjusted 

for an increased total exemptions 1 year, then a decreased total exemptions the 

next. The state earned five exemptions for the current FY of 2021 (row A). The 

state’s adjustment for FY 2021 is based on the number of exemptions earned in the 

previous year (FY 2020) minus the number of exemptions used for the previous year 

(FY 2020). We assume the state earned five exemptions in FY 2020 but used zero 

exemptions in FY 2020, so the state’s total after adjustment for FY 2021 is ten (row 

C). In FY 2021, the state uses eight exemptions (row D), so it does not have any 

over-usage liability for that year (row E). That is, though the state only earned five 

exemptions for FY 2021, the adjustment allowed the state to avoid any over usage 

liability for FY 2021. However, for the purposes of adjustment in FY 2022, the eight 

used exemptions are subtracted from the five earned exemptions for FY 2021, not 

from the ten adjusted exemption amount available in FY 2021. Therefore, the adjustment amount for FY 2022 is negative three. In FY 2022, the state again earns 

five exemptions but the adjustment is negative three (the result of subtracting row 

D, FY 2021 from row A, FY 2022). The state then has a total of two exemptions 

for FY 2022. The state chooses to use two exemptions for FY 2022, therefore it has 

no overuse in FY 2022. This example shows how the proposed regulation increases 

or decreases the number of exemptions available to states while also limiting the 

average number of exemptions in effect to 12 percent over time. As shown in row 

D, the state can use no more than ten exemptions over the course of any 2 year 

period, which is equal to the ten exemptions earned over every 2 year period. 

EXAMPLE 2

Fiscal year (FY) 2021 2022 2023 2024 

A ......... Earned for current FY ............................................................. 5 5 5 5 

B ......... (+) Adjustment for current FY (earned minus used for previous FY).5 ¥3 3 ¥3 

C ......... (=) Total after adjustment for current FY ............................. 10 2 8 2 

D ......... (¥) Used in current FY ........................................................... 8 2 8 2 

E ......... (=) Liability for overuse? (Yes or No) ..................................... 2 (No) 0 (No) 0 (No) 0 (No) 

Example 3, Exemption Overuse 

Example 3 shows how the proposed adjustment calculation would work for a state 

that overuses exemptions. In this example, we again assume the state earned five 

exemptions in FY 2020 but used zero exemptions in FY 2020, so the state’s total 

after adjustment for FY 2021 is ten (row C). In FY 2021, the state uses six exemptions (row D); once again, it does not have any over-usage liability for that year (row 

E), but the adjustment for FY 2022 will be negative one (the result of subtracting 

row D, FY 2021 from row A, FY 2022). Put differently, the five exemptions earned 

for FY 2022 offset the adjustment of negative one. The state then has a total of four 

exemptions for FY 2022 (row C). However, the state uses six exemptions in FY 2022. 

Because the state used more exemptions in FY 2022 than its total after adjustment 

for FY 2022, it has an overuse liability of two for FY 2022. The Department would 

consider the exemption overuse an over-issuance and would hold the state liable for 

the total dollar value of the exemptions, as estimated by the Department. 

EXAMPLE 3

Fiscal year (FY) 2021 2022 2023 2024 

A ......... Earned for current FY ........................................................... 5 5 5 5 

B ......... (+) Adjustment for current FY (earned minus used for 

previous FY).

5 ¥1 ¥1 1 

C ......... (=) Total after adjustment for current FY ........................... 10 4 4 6 

D ......... (¥) Used for current FY ........................................................ 6 6 4 4 

E ......... (=) Liability for overuse? (Yes or No) ................................... 4 (No) ¥2 (Yes) 0 (No) 2 (No) 

146 

* Editor’s note: the document referred to was not published in the Federal Register; and 

therefore, is not published in this hearing. 

Under the proposed rule, the Department would continue to provide states with 

its estimated number of exemptions earned for each upcoming fiscal year as data 

becomes available, typically in September. The Department would also continue to 

provide states with the exemption adjustments as soon as updated caseload data is 

available and states have provided final data on the number of exemptions used in 

the preceding fiscal year, typically in January. 

The Department also seeks comments from states on how to treat state agencies’ 

existing total number of percentage exemptions, which in some cases have carried 

over and accumulated over many years, and on when the proposed change should 

be implemented. Under the proposed rule, these accumulated percentage exemptions would not be available to states once the change is implemented. Additionally, 

because the adjusted number of exemptions is based on the preceding fiscal year, 

the change in regulatory text will impact state’s ability to use exemptions in the 

fiscal year preceding the fiscal year that the provision goes into effect. Therefore, 

the Department seeks comment on how to best handle these issues. 

The proposed rule would not change or affect the ‘‘caseload adjustments’’ at 

273.24(h)(1), which apply to any state that has a change of over ten percent in its 

caseload amount. However, the Department is taking this opportunity to correct the 

cross-reference that this paragraph makes to 273.24(g)(2) for accuracy. The proposed 

regulation cross-references 273.24(g)(3), instead of (g)(2). The Department is making 

this change because it is more accurate and precise to cross-reference to 

273.24(g)(3), given that the caseload adjustments apply to the number of exemptions 

estimated as earned for each state for each fiscal year. 

Procedural Matters 

Executive Order 12866 and 13563 

Executive Orders 12866 and 13563 direct agencies to assess all costs and benefits 

of available regulatory alternatives and, if regulation is necessary, to select regulatory approaches that maximize net benefits (including potential economic, environmental, public health and safety effects, distributive impacts, and equity). Executive 

Order 13563 emphasizes the importance of quantifying both costs and benefits, of 

reducing costs, of harmonizing rules, and of promoting flexibility. This proposed rule 

has been determined to be economically significant and was reviewed by the Office 

of Management and Budget (OMB) in conformance with Executive Order 12866. 

Regulatory Impact Analysis 

As required for rules that have been designated as economically significant by the 

Office of Management and Budget, a Regulatory Impact Analysis (RIA) was developed for this proposed rule. It follows this rule as an Appendix.* The following summarizes the conclusions of the regulatory impact analysis: 

The Department has estimated the net reduction in Federal spending associated with the proposed transfer rule to be approximately $1.1 billion in fiscal year (FY) 

2020 and $7.9 billion over the 5 years 2020–2024. This is a reduction in Federal 

transfers (SNAP benefit payments); the reduction in transfers represents a 2.5 percent decrease in projected SNAP benefit spending over this time period. 

Under current authority, the Department estimates that about 60 percent of 

ABAWDs live in areas that are not subject to a waiver and thus face the ABAWD 

time limit. Under the revised waiver criteria the Department estimates that nearly 

90 percent of ABAWDs would live in such an area. Of those newly subject to the 

time limit, the Department estimates that approximately 2⁄3 (755,000 individuals in 

FY 2020) would not meet the requirements for failure to engage meaningfully in 

work or work training. 

Regulatory Flexibility Act 

The Regulatory Flexibility Act (5 U.S.C. 601–612) requires Agencies to analyze 

the impact of rulemaking on small entities and consider alternatives that would 

minimize any significant impacts on a substantial number of small entities. Pursuant to that review, it has been certified that this rule would not have a significant 

impact on a substantial number of small entities. 

This proposed rule would not have an impact on small entities because the proposed rule primarily impacts state agencies. As part of the requirements, state 

agencies would have to update their procedures to incorporate the new criteria for 

approval associated with requesting waivers of ABAWD time limit. Small entities, 

such as smaller retailers, would not be subject to any new requirements. However, 

all retailers would likely see a drop in the amount of SNAP benefits redeemed at 

147 

stores if these provisions were finalized, but impacts on small retailers are not expected to be disproportionate to impact on large entities. As of FY 2017, approximately 76 percent of authorized SNAP retailers (nearly 200,000 retailers) were 

small groceries, convenience stores, combination grocery stores, and specialty stores, 

store types that are likely to fall under the Small Business Administration gross 

sales threshold to qualify as a small business for Federal Government programs. 

While these stores make up the majority of authorized retailers, collectively they redeem less than 15 percent of all SNAP benefits. The proposed rule is expected to 

reduce SNAP benefit payments by about $1.7 billion per year. This would equate 

to about a $100 loss of revenue per small store on average per month ($1.7 billion 

× 15%/200,000 stores/12 months). In 2017, the average small store redeemed more 

than $3,800 in SNAP each month; the potential loss of benefits represents less than 

three percent of their SNAP redemptions and only a small portion of their gross 

sales. Based on 2017 redemption data, a 2.7 percent reduction in SNAP redemptions 

represented between 0.01 and 0.5 percent of these stores gross sales. 

Executive Order 13771 

Executive Order 13771 directs agencies to reduce regulation and control regulatory costs and provides that the cost of planned regulations be prudently managed 

and controlled through a budgeting process. 

This proposed rule is expected to be an Executive Order 13771 deregulatory action. The rule does not include any new costs. FNS is proposing a reduction in burden hours since state agencies are no longer able to group areas together for waiver 

approval. The reduction would result in an estimated collective savings of $12,092 

for state agencies. 

Unfunded Mandates Reform Act 

Title II of the Unfunded Mandates Reform Act of 1995 (UMRA), Public Law 104– 

4, establishes requirements for Federal agencies to assess the effects of their regulatory actions on state, local and Tribal governments and the private sector. Under 

section 202 of the UMRA, the Department generally must prepare a written statement, including a cost benefit analysis, for proposed and final rules with ‘‘Federal 

mandates’’ that may result in expenditures by state, local or Tribal governments, 

in the aggregate, or the private sector, of $100 million or more in any 1 year. When 

such a statement is needed for a rule, Section 205 of the UMRA generally requires 

the Department to identify and consider a reasonable number of regulatory alternatives and adopt the most cost effective or least burdensome alternative that 

achieves the objectives of the rule. 

This proposed rule does not contain Federal mandates (under the regulatory provisions of Title II of the UMRA) for state, local and Tribal governments or the private sector of $100 million or more in any 1 year. Thus, the rule is not subject to 

the requirements of sections 202 and 205 of the UMRA. 

Executive Order 12372 

SNAP is listed in the Catalog of Federal Domestic Assistance under No. 10.551. 

For the reasons set forth in the Final Rule codified in 7 CFR part 3015, subpart 

V and related Notice (48 FR 29115), this Program is excluded from the scope of Executive Order 12372, which requires intergovernmental consultation with state and 

local officials. 

Federalism Summary Impact Statement 

Executive Order 13132 requires Federal agencies to consider the impact of their 

regulatory actions on state and local governments. Where such actions have Federalism implications, agencies are directed to provide a statement for inclusion in 

the preamble to the regulations describing the agency’s considerations in terms of 

the three categories called for under Section 6(b)(2)(B) of Executive Order 13132. 

The Department has determined that this rule does not have Federalism implications. Therefore, under Section 6(b) of the Executive Order, a Federalism summary 

impact statement is not required. 

Executive Order 12988, Civil Justice Reform 

This proposed rule has been reviewed under Executive Order 12988, Civil Justice 

Reform. This rule is not intended to have preemptive effect with respect to any state 

or local laws, regulations or policies which conflict with its provisions or which 

would otherwise impede its full and timely implementation. This rule is not intended to have retroactive effect unless so specified in the Effective Dates section 

of the final rule. Prior to any judicial challenge to the provisions of the final rule, 

all applicable administrative procedures must be exhausted. 

148 

Civil Rights Impact Analysis 

FNS has reviewed the proposed rule, in accordance with the Department Regulation 4300–4, ‘‘Civil Rights Impact Analysis’’ to identify and address any major civil 

rights impacts the proposed rule might have on minorities, women, and persons 

with disabilities. While we believe that a reduction in the number of ABAWD waivers granted to state agencies will adversely affect potential program participants in 

all groups who are unable to meet the employment requirements, and have the potential for disparately impacting certain protected groups due to factors affecting 

rates of employment of members of these groups, we find that the implementation 

of mitigation strategies and monitoring by the Civil Rights Division of FNS will lessen these impacts. 

Executive Order 13175 

This rule has been reviewed in accordance with the requirements of Executive 

Order 13175, ‘‘Consultation and Coordination with Indian Tribal Governments.’’ Executive Order 13175 requires Federal agencies to consult and coordinate with Tribes 

on a government-to-government basis on policies that have Tribal implications, including regulations, legislative comments or proposed legislation, and other policy 

statements or actions that have substantial direct effects on one or more Indian 

Tribes, on the relationship between the Federal Government and Indian Tribes or 

on the distribution of power and responsibilities between the Federal Government 

and Indian Tribes. 

The USDA’s Office of Tribal Relations (OTR) has assessed the impact of this rule 

on Indian Tribes and determined that this rule has Tribal implications that require 

Tribal consultation under E.O. 13175. FNS invited Tribal leaders to a consultation 

held on March 14, 2018. Tribal leaders did not provide any statement or feedback 

to the Department on the rule. FNS and OTR will determine if a future consultation 

is needed. If a Tribe requests consultation, FNS will work with the Office of Tribal 

Relations to ensure meaningful consultation is provided where changes, additions, 

and modifications identified herein are not expressly mandated by Congress 

Paperwork Reduction Act 

The Paperwork Reduction Act of 1995 (44 U.S.C. Chap. 35; 5 CFR 1320) requires 

the Office of Management and Budget (OMB) approve all collections of information 

by a Federal agency before they can be implemented. Respondents are not required 

to respond to any collection of information unless it displays a current valid OMB 

control number. In accordance with the Paperwork Reduction Act of 1995, this proposed rule will contain information collections that are subject to review and approval by the Office of Management and Budget; therefore, FNS is submitting for 

public comment the changes in the information collection burden that would result 

from adoption of the proposals in the rule. 

Comments on this proposed rule must be received by April 2, 2019. Comments 

are invited on: (a) Whether the proposed collection of information is necessary for 

the proper performance of the functions of the agency, including whether the information shall have practical utility; (b) the accuracy of the agency’s estimate of the 

burden of the proposed collection of information, including the validity of the methodology and assumptions used; (c) ways to enhance the quality, utility, and clarity 

of the information to be collected; and (d) ways to minimize the burden of the collection of information on those who are to respond, including use of appropriate automated, electronic, mechanical, or other technological collection techniques or other 

forms of information technology. 

All responses to this notice will be summarized and included in the request for 

OMB approval. All comments will also become a matter of public record. 

Title: Supplemental Nutrition Assistance Program Waivers of Section 6(o) of the 

Food and Nutrition Act. 

OMB Number: 0584–0479. 

Expiration Date: [July 31, 2021]. 

Type of Request: Revision of a currently approved collection. 

Abstract: Section 6(o) of the Food and Nutrition Act of 2008, (the Act, as amended 

through Pub. L. 113–xxx), limits the amount of time an able-bodied adult without 

dependents (ABAWD) can receive Supplemental Nutrition Assistance Program 

(SNAP) benefits to 3 months in a 36 month period, unless the individual is working 

and/or participating in a work program half-time or more, or participating in 

workfare. The Act exempts individuals from the time limit for several reasons, including age, unfitness for work, or having a dependent child. The ABAWD time 

limit and work requirement currently apply to people ages 18 through 49, unless 

they are already exempt from the general work requirements, medically certified as 

physically or mentally unfit for employment, responsible for a child under 18, or 

149 

pregnant. ABAWDs are also work registrants and must meet the general work requirements. In addition, ABAWDs subject to the time limit must work and/or participate in a work program 80 hours per month or more, or participate in and comply with workfare to receive SNAP for more than 3 months in a 36 month period. 

Participation in SNAP E&T, which is a type of work program, is one way a person 

can meet the 80 hour per month ABAWD work requirement, but other work programs are acceptable as well. 

The Act also provides state agencies with flexibility to request a waiver of this 

time limit if unemployment is high or the area does not have a sufficient number 

of jobs to provide employment. State agencies can request to waive the ABAWD 

time limit if an area has an unemployment rate of over ten percent or the state can 

meet one of the regulatory options to show it does not have a sufficient number of 

jobs to provide employment. If the time limit is waived, individuals are not required 

to meet the ABAWD work requirement to receive SNAP for more than 3 months 

in a 36 month period. This collection of information is necessary for FNS to perform 

its statutory obligation to review waivers of the SNAP ABAWD time limit. 

This is a revision of a currently approved information collection request associated 

with this rulemaking. In the previous submission, the Food and Nutrition Service 

(FNS) estimated 35 hours for each waiver request for a total of 1,198 hours. Based 

on the experience of FNS during calendar year 2018, FNS projects that 36 out of 

53 state agencies would submit requests for a waiver of the time limit for ABAWD 

recipients based on a high unemployment rate or lack of sufficient number of jobs. 

FNS estimates a response time of 28 hours for each waiver request based on labor 

market data, which require detailed analysis of labor markets within the state. FNS 

projects a total of 1,008 hours, which would be a reduction of 190 hours compared 

to the 1,198 hours estimated provided in the pending approval. 

FNS is proposing a reduction in burden hours since state agencies are no longer 

able to group areas together for waiver approval. The reduction will burden hours 

would result in an estimated collective savings of $12,092 for state agencies. This 

rule does not require any recordkeeping burden. Reporting detail burden details are 

provided below. 

Respondents: State agencies. 

Estimated Number of Respondents: 36. 

Estimated Number of Responses per Respondent: 1. 

Estimated Total Annual Burden on Respondents: 1,008. 

OMB No. 

0584–0479 Requirement (7 CFR 273.24(f) 

Estimated 

number of 

respondents 

Response 

annually 

per 

respondent 

Total 

annual 

responses 

Hours per 

response 

Annual 

burden 

hours 

Previous 

submission 

total hours 

Differences 

due to 

program 

changes 

Differences 

due to 

adjustment 

Affected Public: State Agencies 

Reporting 

burden.

Submissions of waiver request based 

on labor market data..

36 1 36 28 1,008 1,190 ¥182 0 

7 CFR 273.24(f)—Submission of 

waiver request based on Labor 

Surplus Area designation..

0 0 0 0 0 8 ¥8 0 

Reporting totals ...................................................... 36 1,008 ¥190 

Total Reporting Burden due to Rulemaking .. 1,008 

E-Government Act Compliance 

The Department is committed to complying with the E-Government Act of 2002, 

to promote the use of the Internet and other information technologies to provide increased opportunities for citizen access to government information and services, and 

for other purposes. 

List of Subjects in 7 CFR Part 273 

Able-bodied adults without dependents, Administrative practice and procedures, 

Employment, Indian reservations, Time limit, U.S. territories, Waivers, Work requirements. 

Accordingly, FNS proposes to amend 7 CFR part 273 to read as follows: 

PART 273—CERTIFICATION OF ELIGIBLE HOUSEHOLDS

0 1. The authority citation for part 273 continues to read as follows: 

Authority: 7 U.S.C. 2011–2036. 

0 2. In § 273.24, revise paragraph (f) to read as follows: 

§ 273.24 Time Limit for able-bodied adults. 

* * * * * 

(f) Waivers—.(1) General. The state agency may request FNS approval to temporarily waive the time limit for a group of individuals in the state in the area in 

150 

which the individuals reside. To be considered for approval, the request must be endorsed by the state’s governor and supported with corresponding data or evidence 

demonstrating that the requested area: 

(i) Has an unemployment rate of over ten percent; or 

(ii) Does not have a sufficient number of jobs to provide employment for the 

individuals. 

(2) Core standards. FNS will approve waiver requests under (1)(i) and (ii) that are 

supported by any one of the following: 

(i) Data from the Bureau of Labor Statistics (BLS) or a BLS-cooperating agency that shows an area has a recent 12 month average unemployment rate over 

ten percent; 

(ii) Data from the BLS or a BLS-cooperating agency that shows an area has 

a 24 month average unemployment rate 20 percent or more above the national 

rate for a recent 24 month period, but in no case may the 24 month average 

unemployment rate of the requested area be less than seven percent. The 24 

month period must be no earlier than the same 24 month period used by the 

Department of Labor’s Employment and Training Administration to designate 

Labor Surplus Areas for the current fiscal year; or 

(iii) Evidence that an area qualifies for extended unemployment benefits as 

determined by the Department of Labor (DOL). 

(3) Other data and evidence. FNS may approve waiver requests that are supported 

by data or evidence other than that listed under paragraph (f)(2) of this section if 

the request demonstrates an exceptional circumstance in an area. In addition, the 

request must demonstrate that the exceptional circumstance has caused a lack of 

sufficient number of jobs, such as data from the BLS or a BLS-cooperating agency 

that shows an area has a most recent 3 month average unemployment rate over ten 

percent. Supporting unemployment data provided by the state must rely on standard BLS data or methods. 

(4) Restriction on statewide waivers. FNS will not approve statewide waiver requests if data for the requesting state at the sub-state level is available from BLS, 

except for waivers under paragraph (f)(2)(iii) of this section. 

(5) Restricting the combining of data to group sub-state areas. The state agency 

may only combine data from individual areas that are collectively considered to be 

a Labor Market Area by DOL. 

(6) Duration of waiver approvals. In general, FNS will approve waivers for 1 year. 

FNS may approve waivers for a shorter period at the state agency’s request and 

waivers under paragraph (f)(2)(ii) of this section will not be approved for a period 

beyond the fiscal year in which the waiver is implemented. 

(7) Areas with limited data or evidence. Waiver requests for an area for which 

standard BLS data or a BLS-cooperating agency data is limited or unavailable, such 

as a reservation area or U.S. Territory, are not required to conform to the criteria 

for approval under paragraphs (f)(2), (f)(3), (f)(4), (f)(5) and (f)(6) of this section. The 

supporting data or evidence provided by the state must correspond to the requested 

area. 

(i) FNS may approve waivers for these areas if the requests are supported by 

sufficient data or evidence, such as: 

(A) Estimated unemployment rate based on available data from BLS and 

Census Bureau’s American Community Survey; 

(B) A low and declining employment-to-population ratio; 

(C) A lack of jobs in declining occupations or industries; or 

(D) An academic study or other publication describing the area as lacking 

a sufficient number of jobs to provide employment for its residents. 

(ii) In areas with limited data or evidence, such as reservation areas or U.S. 

Territories, FNS may allow the state agency to combine data from individual 

areas to waive a group of areas if the state agency demonstrates that the areas 

are economically integrated. 

* * * * * 

0 3. In § 273.24, revise paragraph (h) to read as follows: 

* * * * * 

(h) Adjustments. FNS will make adjustments as follows: 

(1) Caseload adjustments. FNS will adjust the number of exemptions estimated for a state agency under paragraph (g)(3) of this section during a fiscal 

151 

1The following counties are currently eligible for a waiver from the 3 month time limit: Aitkin, Becker, Beltrami, Carlton, Cass, Clearwater, Cook, Cottonwood, Crow Wing, Hubbard, 

Isanti, Itasca, Kanabec, Kittson, Koochiching, Lake, Lake of the Woods, Mahnomen, Marshall, 

Continued 

year if the number of SNAP recipients in the state varies from the state’s caseload by more than ten percent, as estimated by FNS. 

(2) Exemption adjustments. During each fiscal year, FNS will increase or decrease the number of exemptions allocated to a state agency based on the difference between the number of exemptions used by the state for the preceding 

fiscal year and the number of exemptions estimated for the state for the preceding fiscal year under paragraphs (g)(3) and (h)(1) of this section. The increase or decrease will only apply for the fiscal year in which the adjustment 

is made. For example: 

(i) If the state agency uses fewer exemptions in the preceding fiscal year 

than were estimated for the state agency by FNS for the preceding fiscal 

year under paragraphs (g)(3) and (h)(1) of this section, FNS will increase 

the number of exemptions allocated to the state agency for the current fiscal year by the difference to determine the adjusted exemption amount. 

(ii) If the state agency uses more exemptions in the preceding fiscal year 

than were estimated for the state agency by FNS for the preceding fiscal 

year under paragraphs (g)(3) and (h)(1) of this section, FNS will decrease 

the number of exemptions allocated to the state agency for the current fiscal year by the difference to determine the adjusted exemption amount. 

* * * * * 

Dated: December 20, 2018. 

Brandon Lipps, 

Acting Deputy Under Secretary, Food, Nutrition, and Consumer Services. 

[FR Doc. 2018–28059 Filed 1–31–19; 8:45 a.m.] 

BILLING CODE 3410–30–P

SUBMITTED COMMENT LETTER BY HON. COLLIN C. PETERSON, A REPRESENTATIVE IN

CONGRESS FROM MINNESOTA; AUTHORED BY TONY LOUREY, COMMISSIONER, 

MINNESOTA DEPARTMENT OF HUMAN SERVICES

March 29, 2019 

BRANDON LIPPS, 

Administrator, Food and Nutrition Service 

U.S. Department of Agriculture; 

Certification Policy Branch, 

Program Development Division, 

United States Department of Agriculture—Food and Nutrition Service, 

Alexandria, Virginia 22302 

Re: Docket No. FNS–2018–0004, RIN 0584–AE57, Comments in Response to 

Proposed Rulemaking: Supplemental Nutrition Assistance Program: 

Requirements and Services for Able-Bodied Adults without Dependents 

Dear Mr. Lipps: 

The Minnesota Department of Human Services (MN DHS) oversees the state’s 

Supplemental Nutrition Assistance Program (SNAP) to provide critical food assistance to low-income families. As Commissioner of the department, I have serious concerns about the proposed rule regarding SNAP waivers that the Food and Nutrition 

Service (FNS) published in the Federal Register on February 1, 2019. This rule will 

likely increase hunger and deprivation among thousands of people in Greater Minnesota by causing them to lose their benefits. 

Under current law, working-age adults who do not have dependent children must 

either have a job or be enrolled in officially-recognized employment training for 20 

hours per week in order to receive more than 3 months of SNAP benefits in a 3 

year time period. States can waive the time limit for this population in geographic 

areas that have an unemployment rate that is 20 percent above the national average. In Minnesota, 30 counties and 11 American Indian reservations and Tribal 

areas, all of which are in rural areas, currently receive these SNAP waivers.1 The 

152 

Mille Lacs, Morrison, Murray, Norman, Pennington, Pine, Red Lake, Roseau, St. Louis, Todd, 

Wadena. 2 U.S. Government Accountability Office (2003). Food Stamp Employment and Training Program Better Data Needed to Understand Who Is Served and What the Program Achieves: 

https://www.gao.gov/assets/240/237571.pdf. 3The counties that would still qualify under an unemployment rate floor of seven percent are: 

Clearwater, Itasca, Koochiching, and Marshall. 

proposed rule would limit the existing criteria for granting SNAP waivers in a way 

that would cause much of the population in these areas to lose SNAP benefits. 

Understanding the low-wage labor market is critical to understanding the role 

that SNAP plays in helping workers mitigate the instability of low-wage work. 

SNAP is a critical support for workers who earn wages that are so low that they 

live in poverty despite working. It also helps these workers when they experience 

a spell of unemployment. The vast majority of working-age SNAP recipients in Minnesota work in low-wage jobs that offer little employment security, erratic and unpredictable schedules, and few benefits. These industries include hotels and restaurants, retail, temporary placement agencies, and health care’s low-wage occupations. The jobs in these industries are much more likely than other sectors to be 

part-time and have high worker turnover. Many of the adults subject to SNAP time 

limits lack basic skills in reading, math, and writing and face other barriers to employment which can limit their job prospects. This group of SNAP recipients is also 

more likely than the larger SNAP population and the overall statewide population 

to be homeless, lack transportation, have an addiction, or experience domestic violence.2 SNAP helps mitigate the effects of low pay and job unpredictability to help 

workers weather the inevitable unemployment spells that come with low-wage jobs. 

The concerns outlined below highlight changes proposed in the rule that would 

further undermine the well-being of low-wage workers receiving SNAP in Minnesota: 

(1) The rule proposes to eliminate statewide waivers, which would leave 

Minnesota vulnerable during severe economic crises. In addition to providing a nutrition safety net during periods of economic volatility, the use of 

SNAP benefits also boosts local economies by providing economic stimulus to 

grocers, farmers, and others in the food pipeline. The Great Recession which 

began in 2008 eliminated 160,000 jobs in Minnesota. When people lose their 

jobs, the wider economy is vulnerable because those individuals can no longer 

make purchases or pay bills. SNAP not only ensures that people who are unemployed can purchase groceries, but also that local food retailers still have 

customers and can keep their staff employed during difficult economic times. 

A USDA Economic Research Service analysis estimated that each $1 in Federal SNAP benefits generates $1.79 in economic activity. Those dollars 

help food retailers (many of which are operating on thin margins) improve 

food access for all residents. Historically, Minnesota has had a relatively 

strong economy and only had a statewide waiver during the 2008 recession. 

That is exactly the sort of scenario in which programs like SNAP must respond quickly and effectively to diminish the impact of the crisis on individuals and slow a widening economic crisis. 

(2) The proposed rule changes the criteria used to qualify a region for 

a SNAP waiver based on high unemployment. The current standard for 

‘‘insufficient jobs’’ that can qualify an area for a waiver is an unemployment 

rate of at least 20% above the national average. This rule would create an 

additional standard by requiring waivered areas to also have a minimum unemployment rate of either 6%, 7%, or 10% (the proposed rule asks for public 

comment on the impact of each of these unemployment rates). 

The unemployment rate is not a complete measure of economic stress and 

establishing a minimum unemployment rate in this arbitrary manner lacks 

the evidence-based rigor needed when making a major policy change. Minnesota has very distinct regions, some of which rely primarily on agriculture, 

mining, food processing, health care, or mixed sectors which each follow distinct economic cycles. Some regions can be flourishing in our state while others are struggling economically. If FNS were to apply a minimum unemployment rate of 7%, only four of the 30 counties 3 that are included in the waiver 

would continue to qualify. All American Indian reservations and Tribal areas 

would continue to qualify. Under such a change, 2,650 Minnesotans would be 

subject to the 3 month time limit. 

(3) The proposed rule would limit local control and state flexibility in 

defining areas of high unemployment by forcing states to make the 

153 

determinations using only small Labor Market Areas recognized by 

the Bureau of Labor Statistics (BLS). This approach fails to recognize 

the economic reality in rural areas of Minnesota. The Bureau of Labor 

Statistics designated a small Labor Market Area by measuring whether at 

least 25% of a county’s residents or employees are associated with a neighboring county. Applying that narrow methodology to SNAP waivers misses 

that fact that in some counties, workers may have to travel in all directions 

and often beyond a contiguous county for their job. States have the best understanding of the regional patterns in their labor markets and can best account for that when applying for waivers. Using the BLS small Labor Market 

Area for such determinations is misguided. 

(4) While the 2018 Farm Bill modified the number of exemptions from 

SNAP time limits that states can receive each year from 15% to 12%, 

it did not change their ability to carry over unused exemptions. The 

proposed rule would no longer allow states to carry over all unused exemptions from 1 year to another. This change restricts states’ ability to use the 

program’s policies to respond to shifts in the labor market and the economy. 

Minnesota would naturally use fewer exemptions when the labor markets 

across the state are relatively strong and would increase the use of exemptions when the labor markets weaken. That ability to respond should not be 

restricted. 

The proposal would also allow FNS to apply this aspect of the rule change 

retroactively, which would also be harmful to Minnesota. States that have 

earned exemptions and were allowed to carry them over across Federal fiscal 

years should be able to continue to do so. Our current accumulations from 

previous years should not be dismissed. States know their residents and their 

geographic regions best, and should be allowed to determine how these exemptions could be used to address continued challenges for some of their lowwage workers. 

(5) Implementing the proposed rule changes by October 1, 2019 would 

undoubtedly lead to errors and confusion. Major changes in complex systems need to be well-planned so they can be well-implemented. If any of the 

provisions of the proposed rule are enacted, they should not be implemented 

any sooner than October 1, 2020. 

If the changes outlined in this proposed rule go into effect, they would force many 

workers in areas with unemployment rates at least 20% more than the national rate 

to lose their SNAP benefits. They would be forced to find jobs that are not available 

or to enroll in employment services that do not exist. There is not enough funding 

in the SNAP Employment and Training program to serve the people currently subject to time limits, much less thousands of new workers subject to the time limit. 

If Minnesota were to apply the small increase in funding for the SNAP Employment 

and Training program from the 2018 Farm Bill to all the individuals affected by 

this rule change, we estimate that we would only have $35 per person to spend on 

employment and training services for people that face multiple barriers to work. 

Congress had the opportunity to include these policy changes in the recently 

passed farm bill but chose to not do so. To make these changes through executive 

action, without providing the resources to help low-wage workers improve their odds 

of getting jobs, only increases hardship for people who are already struggling to afford the basics. The rules governing eligibility for waivers and individual exemptions have been in place for nearly 20 years. In that time, they have proven to be 

reasonable, transparent, and manageable for states to operationalize. 

Although this rule may be meant to increase the number of people engaged in 

work, these changes would actually undermine low-wage workers’ ability to reach 

stability. Minnesota’s economic well-being depends on all workers being able to meet 

their basic needs and provide local businesses with customers, even when the economy weakens. I urge you, for the benefit of working people in Greater Minnesota, 

to reject the changes proposed in this rule. 

Sincerely, 

TONY LOUREY, 


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Commissioner. 

SUBMITTED LETTER BY HON. JAMES P. MCGOVERN, A REPRESENTATIVE IN CONGRESS

FROM MASSACHUSETTS

February 27, 2018 

HON. GLEN THOMPSON, 

Chairman, 

Subcommittee on Nutrition, 

House Committee on Agriculture, 

Washington, D.C. 

Dear Chairman Thompson: 

It has been a pleasure serving with you on the Nutrition Subcommittee, and I 

have appreciated the Majority’s diligence in conducting a thorough review of the 

Supplemental Nutrition Assistance Program (SNAP) over the past several years. 

During the 23 hearings our Committee has held on SNAP, we’ve heard from experts—conservative and liberal—that SNAP works. We’ve learned that benefits 

should not be cut, and that current benefits are inadequate. We also learned that 

SNAP does not discourage work, and that eliminating work waivers will hamper 

state flexibility and increase hunger. 

Despite all of these hearings and findings, I’m concerned by reports that the Committee is drafting a bill, behind closed doors, that will seek to dramatically undermine access to SNAP benefits for the population of very vulnerable able-bodied 

adults without dependents, known as ABAWDs. My concern has only grown in the 

past several weeks as the Administration has proposed drastic changes to this population through its budget proposal and solicited feedback on advancing its goal of 

moving ABAWDs out of the SNAP program. 

I am now respectfully requesting that the Nutrition Subcommittee hold a hearing 

on the ABAWD population before making any changes to current SNAP law impacting this group of vulnerable adults. 

Members of this Committee deserve the opportunity to learn more about the 

ABAWD population from expert witnesses before voting on any legislation that 

could limit their access to modest food benefits. 

Thank you for your consideration of this request, and I look forward to hearing 

from you soon. 

Sincerely, 

HON. JAMES P. MCGOVERN, 

Ranking Minority Member, 

Subcommittee on Nutrition. 

SUBMITTED ARTICLE BY HON. JAMES P. MCGOVERN, A REPRESENTATIVE IN CONGRESS

FROM MASSACHUSETTS

Trump to poor Americans: Get to work or lose your benefits 

The Washington Post 

Wonkblog/Analysis 

By Caitlin Dewey and Tracy Jan 

May 22, 2017 


11602053.eps
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A group of homeless men and women receive meals from volunteers on 

May 18 in Morgantown, West Virginia. West Virginia is one of the nation’s 

poorest states where nearly one in five struggled to afford basic necessities 

in 2015. (Spencer Platt/Getty Images) 

For a period last year after he lost his food stamps, Tim Keefe, an out-of-work 

and homeless Navy veteran, used his military training to catch, skin and eat squirrels, roasting the animals over an open fire outside the tent he pitched in frigid Augusta, Maine. 

The new additions to Keefe’s diet resulted from a decision by state authorities to 

tighten work requirements for recipients of the social safety net—forcing the 49 year 

old, who lost his job at a farm equipment factory because of an injury, off the food 

stamp rolls. 

‘‘I was eating what I could find, and borrowed from friends and strangers,’’ Keefe 

said in testimony to the Maine legislature. ‘‘There were many times . . . when I 

would go 2 or even 3 days without food. If one was inclined to lose a lot of weight, 

I could recommend this diet wholeheartedly.’’ 

Now the Trump Administration in its first major budget proposal has proposed 

more stringent work requirements—similar to those in effect in Maine and other 

states—to limit eligibility for food stamps and a host of other benefits as part of 

sweeping cuts to anti-poverty programs. 

The White House budget proposal, due to be unveiled on Tuesday, would reduce 

spending on anti-poverty programs from food stamps to tax credits and welfare payments by $274 billion over a decade, largely by tightening eligibility for these programs, according to Administration officials. With additional reforms on Medicaid 

and disability insurance, total safety net cuts would top $1 trillion over 10 years. 

Making low-income Americans work to qualify for so-called welfare programs is 

a key theme of the budget. ‘‘If you are on food stamps and you are able-bodied, we 

need you to go to work,’’ said budget director Mick Mulvaney during a White House 

briefing on Monday. 

He said the strengthened requirements in the budget focuses on putting the 6.8 

million unemployed or underemployed Americans back to work. ‘‘There is a dignity 

to work,’’ he said, ‘‘and there’s a necessity to work to help the country succeed.’’ 

The White House did not offer details Monday on how the work requirements 

would be implemented, other than saying it would be ‘‘phased in’’ for able-bodied 

adults without dependent children. 

The White House estimated the combined reforms to the Supplemental Nutrition 

Assistance Program, better known as food stamps, would generate nearly $193 billion in savings over a decade. 

In addition to SNAP reforms, Trump will propose taking the earned income and 

child tax credits away from undocumented immigrants working in the United 


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156 

States, many of whom pay taxes or have American born-children. That reform alone 

would save $40 billion over a decade, according to the White House. 

Anti-poverty advocates say the White House could implement its desired reforms 

to SNAP in two ways: require recipients to work more than the current minimum 

of 20 hours a week, or cut the unemployment waivers in areas with high joblessness 

rates. 

The influential Heritage Foundation, as well as a number of House conservatives 

have championed a crackdown on waivers, leading many anti-poverty advocates to 

conclude that is the most likely way the White House would implement its proposed 

reforms. 

Robert Rector, a senior research fellow at the Heritage Foundation who has asked 

the White House to prioritize work requirements, said the Trump Administration 

needs to ‘‘go after’’ the four million able-bodied adults without dependents in the 

food stamp program. 

‘‘You say to them, ‘We will give you assistance, but come to the office 1 day a 

week to do job search or community service,’ ’’ Rector said. ‘‘When Maine did that, 

they found almost immediately that their caseload dropped 85 percent.’’ 

Critics say such a change could endanger people like Keefe, a veteran who has 

been unable to find a job after injuring his wrist on the job at a plow factory in 

Rockland, Maine. As a result, Keefe now is medically unable to lift more than 25 

pounds—which disqualifies him from other work in manufacturing. 

The Navy veteran was one of several thousand former food stamp recipients who 

lost benefits when Maine, in 2015, declined to renew its waiver and reinstated statewide work requirements. He has spent much of the last year living in a tent. 

‘‘I don’t wanna worry no one,’’ said Keefe, who recently testified to Maine’s Committee on Health and Human Services about the impact the work requirement had 

on him. But, he added: ‘‘I hope they understand that people fall through the cracks.’’ 

The Trump Administration is considering other changes to SNAP. While details 

remain sparse, Mulvaney said the Federal Government would be asking states to 

share in the costs for the food stamps program, through a phased-in ‘‘state match’’ 

so they have a ‘‘little more skin in the game.’’ 

‘‘We believe in the social safety net. We absolutely do,’’ Mulvaney said. ‘‘What 

we’ve done is not to try and remove the safety net for folks who need it, but to try 

and figure out if there’s folks who don’t need it that need to be back in the workforce.’’ 

Suspending employment waivers would hit hard in areas with high unemployment such as southern and central California, where the unemployment rate can 

spike as high as 19 percent, as well as cities such as Detroit and Scranton, Pa., 

where joblessness remains rampant. The change would also hit hard in large portions of New Mexico, Oregon, Washington, Georgia, Kentucky, Tennessee, West Virginia, Idaho and Michigan. 

‘‘It’s unconscionable, cruel and ineffective,’’ said Josh Protas, the Vice President 

of Public Policy at MAZON, a national anti-hunger organization. ‘‘I’m honestly not 

sure what their goal is.’’ 

Critics say the changes in unemployment waivers would be devastating for Native 

American families living on reservations in North and South Dakota, Arizona and 

Montana where there is chronic poverty and high unemployment. 

‘‘The President’s budget proposal will force kids in rural America to go hungry 

while wasting billions of taxpayer dollars on misplaced priorities like a wall that 

won’t keep us safe,’’ said Senator Jon Tester (D–MT), in a statement to the Post. 

‘‘Parents in Montana and across Indian Country should not have to choose between 

food for their tables, gas for their cars, and shoes for their kids.’’ 

The number of Americans on SNAP remains high, however. In 2016, 44 million 

Americans receive the benefits, compared to just 28 million people in 2008. 

‘‘They have not come down like we would expect them to do,’’ Mulvaney said. 

‘‘That raises a very valid question: Are there folks on SNAP who shouldn’t be?’’ 

Anti-hunger advocates argue that, generally speaking, there are not. Because 

SNAP benefits decrease gradually with increased income, there is no incentive for 

people to avoid work to get benefits—a phenomenon economists call the ‘‘welfare 

cliff.’’ And benefits are too small for people to subsist on them without working: The 

average food stamp benefit was $465 a month for a family of four in 2015. Most 

people are on the program for between 7 and 9 months on average. 

‘‘The notion that people would prefer not to work to get that benefit, give me a 

break,’’ said U.S. Representative Jim McGovern, (D-Mass.) a longtime anti-hunger 

advocate. ‘‘This is a lousy and rotten thing to do to poor people. They look at SNAP 

as an ATM to pay for their other priorities.’’ 

Additionally, 3⁄4 of households using SNAP contain children, seniors, or people 

with disabilities, said Elaine Waxman, a senior fellow in the Income and Benefits 

157 

Policy Center at the Urban Institute. Without SNAP, the country would have had 

three to 4.5 million more people in poverty during the recession, she said. 

More than 1⁄4 of able-bodied adults without dependents on SNAP do not have a 

high school diploma, Waxman said; another 57 percent don’t have college degrees— 

putting them at a disadvantage when it comes to finding work. 

A number are also veterans, young adults aging out of the foster care system, and 

felons recently released from jail. SNAP recipients who cannot find work, for these 

or other reasons, are supposed to attend job training programs—but they’re not 

widely available because of lack of funding. 

‘‘This is the trick. On the one hand, you want people to do something, when in 

fact a lot of folks may not realistically be able to find a job,’’ Waxman said. ‘‘Most 

states don’t want to put the money in. This is a dilemma that we’re in.’’ 

The evidence that stricter work requirements actually cause people to get jobs is 

mixed, at best. In Kansas, which reinstated the requirements in October 2014, 40 

percent of unemployed adults were still unemployed a year after being kicked off 

SNAP. Among former SNAP participants who lost benefits, the average annual income was only $5,562, according to the Foundation for Government Accountability, 

a right-wing think tank based in Florida. 

Progress has also been hotly debated in Maine, a state that conservatives regularly hold up as evidence that stricter work-requirements are effective. When the 

state dropped its waiver in 2015, the number of unemployed adults in the program 

immediately fell by nearly 80 percent. 

But a May 2016 report by the state found that nearly 60 percent of those affected 

individuals did not report any income in the year after they left the program—suggesting they were still unemployed or underemployed a year later. 

On the national level, Michael Tanner, a senior fellow who focuses on social welfare issues at the Cato Institute, a libertarian think tank, said he doesn’t think 

similar mandates will have a huge impact on moving large numbers of recipients 

into employment or result in significant budget savings. Most SNAP recipients who 

can work are already working, and many of those who are not meet one of the various exemptions such as being disabled. 

‘‘It’s making a statement that Republicans think people who are on public assistance should be doing all they can to get off,’’ Tanner said, ‘‘and that means working 

whenever possible.’’ 

McGovern, who sits on the House Agriculture Committee, said he was surprised 

to learn about the White House proposal given Agriculture Secretary Sonny 

Perdue’s testimony before the Committee last week saying he did not favor any 

major changes to the food stamps program. 

‘‘It’s been a very important, effective program,’’ Perdue said, according to a recording of the hearing. ‘‘As far as I’m concerned we have no proposed changes. You don’t 

try to fix things that aren’t broken.’’ 

The Trump Administration is advocating other ‘‘fixes’’ to the safety net, as well. 

The budget will also propose requiring people to have a Social Security [N]umber 

to collect tax credits. Mulvaney said it is unfair that taxpayers support immigrants 

working illegally in this country. 

‘‘How do I go to somebody who pays their taxes and say, ‘Look, I want you to give 

this earned income tax credit to somebody who is working here illegally? That’s not 

defensible,’’ Mulvaney said. 

Rector, of the Heritage Foundation, said he also hopes Trump will prioritize work 

requirements for those receiving housing subsidies. Mulvaney did not address that 

on Monday. 

Diane Yentel, President of the National Low Income Housing Coalition, said the 

majority of Americans receiving housing subsidies are elderly, disabled or already 

include someone who works. Of the remaining households, nearly 1⁄2 include a preschool child or an older child or adult with a disability who needs the supervision 

of a caregiver. 

Establishing work requirements for the remaining six percent of households who 

are ‘work able’ but not employed would require state and local housing agencies already facing funding shortfalls to establish cumbersome monitoring and enforcement systems for a very narrow segment of rental assistance recipients, she said. 

‘‘This is neither cost effective nor a solution to the very real issue of poverty impacting millions of families living in subsidized housing or in need,’’ Yentel said in 

a statement to the Post. 

Correction: This story incorrectly stated the average annual income for SNAP 

participants in Kansas who had lost and then found jobs was $5,562. That figure applied to all SNAP participants who had lost the benefit. 

158 

Caitlin Dewey is the food policy writer for Wonkblog. Subscribe to her 

daily newsletter: tinyletter.com/cdewey, @caitlindewey. 

Tracy Jan covers the intersection of race and the economy for The Post. 

She previously was a national political reporter at The Boston Globe, 

@TracyJan. 

SUBMITTED COMMENT LETTER BY HON. JAHANA HAYES, A REPRESENTATIVE IN

CONGRESS FROM CONNECTICUT; AUTHORED BY MARC EGAN, DIRECTOR OF

GOVERNMENT RELATIONS, NATIONAL EDUCATION ASSOCIATION

March 19, 2019 

Certification Policy Branch, 

SNAP Program Development Division, 

Food and Nutrition Service, USDA, 

Alexandria, Virginia 

RE: Proposed Rule: Supplemental Nutrition Assistance Program (SNAP): Requirements for Able-Bodied Adults without Dependents RIN 0584–AE57 

Dear Certification Policy Branch: 

Thank you for the opportunity to comment in opposition to USDA’s Proposed Rule 

on Requirements for Able-Bodied Adults without Dependents (ABAWDs). 

In theory, the 3 month time limit for Supplemental Nutrition Assistance Program 

(SNAP) benefits for ABAWDs impacts only adults who do not have children. In practice, it also harms children living in low-income, food-insecure households. Making 

it more difficult for states to waive the 3 month time limit for low-income individuals facing barriers to employment, as the proposed rule would do, makes it more 

likely that vulnerable children will go hungry or be poorly nourished. 

First line of defense against childhood hunger 

SNAP, our nation’s largest Federal food assistance program, is the first line of defense against childhood hunger. The program provides low-income households with 

monthly funds specifically designated for food purchases. Research links participation in SNAP for 6 months with an 8.5 percentage point decrease in food insecurity 

in households with children, according to USDA itself (Measuring the Effect of Supplemental Nutrition Assistance Program (SNAP) Participation on Food Security, 

(https://fns-prod.azureedge.net/sites/default/files/Measuring2013.pdf) Aug. 2013). 

Food insecurity is a major threat to the health and well-being of the 12.5 million 

children in America—one in six—living in food-insecure households. The consequences are devastating. Every day, educators like the three million members of 

the National Education Association (NEA) see firsthand how hungry children struggle to learn. Access to enough healthy food is essential to academic success. 

In 2015, 19.2 million children relied on SNAP for consistent access to food—44 

percent of the program’s participants. In addition to fighting food insecurity, SNAP 

significantly reduces child poverty and helps struggling families make ends meet: 

the program lifted 1.5 million children out of poverty in 2017 alone. 

Overly tight requirements are cruel and counterproductive 

Federal law limits SNAP eligibility for childless, unemployed or underemployed 

adults age 18–50 (except those who are exempt) to just 3 months out of every 3 

years unless they obtain and maintain an average of 20 hours a week of employment—and can prove it. These requirements are often already untenable for individuals who face structural barriers to employment and/or sufficient regular work 

hours. Data from 2013 and 2014 show that the overwhelming majority of SNAP participants struggling to work 20 hours a work are not uninterested in working—they 

are experiencing the consequences of volatile low-wage labor markets, caregiving duties, or personal health issues. 

The proposed rule would limit states’ flexibility and tighten requirements for 

waiving this 3 month time limit for ABAWDs, causing an estimated 750,000 individuals to lose access to SNAP—an approach that is counterproductive as well as cruel. 

Denying people critical food assistance harms their health and productivity, hindering their ability to find and keep employment and achieve economic self-sufficiency. 

Proposed changes do not reflect today’s realities 

Technically, children under age 18 and the adults who live with them are exempt 

from the 3 month time limit for SNAP. This approach does not fully reflect the comVerDate Aug 31 2005 11:16 Jun 14, 2019 Jkt 041481 PO 00000 Frm 00164 Fmt 6621 Sfmt 6621 P:\DOCS\116-02\36188.TXT BRIAN
159 

plex arrangements necessary for low-income families to put food on the table. Specifically: 

• Children with non-custodial parents (NCPs). Some 4.5 million poor and 

low-income custodial parents rely on child support payments from NCPs and 

use SNAP to put food on the table for their children. NCPs are often low-income 

themselves: 2.1 million were below the poverty line in 2015 and 1.5 million 

accessed SNAP to supplement their resources. Since NCPs are not exempt from 

the 3 month time limit for ABAWDs, the proposed rule threatens them as well 

as their children. An NCP who loses SNAP benefits may no longer be able to 

make child support payments. 

• Children whose extended family members provide financial support. 

Some low-income children receive food, financial assistance, or care from extended family members, family friends, or a parent’s significant other who is 

receiving SNAP benefits—people who are often struggling financially themselves. The most economically precarious households are the most likely to rely 

on such networks. So-called ABAWDs who lose their SNAP benefits may have 

to stop providing support for children they previously helped. 

• Children impacted by the opioid crisis: Today, more than 2.5 million children are being raised by their grandparents or other relatives, in part because 

families are dealing with parental alcohol and substance abuse issues, which 

are growing rapidly due to the opioid epidemic. The adults who provide informal 

kinship care for children impacted by substance abuse issues may not do so on 

a consistent schedule, however. As a result, they may face obstacles in securing 

an exemption from ABAWD time-limits. If they lose access to SNAP in the face 

of tightened waiver requirements, the children they care for could experience 

increased poverty and food insecurity as a result. 

• Youth aging out of foster care and unaccompanied homeless youth: 

SNAP plays a significant role in the health and well-being of youth in foster 

care and unaccompanied homeless youth who often lack support systems. They 

disproportionately experience significant barriers to obtaining a high school diploma, entering college, obtaining a driver’s license, accessing health insurance, 

maintaining housing stability, obtaining steady employment, and accessing sufficient food. SNAP can help address their food insecurity, but because former 

foster youth and unaccompanied homeless youth often meet the definition of an 

Able-Bodied Adult Without Dependents, they face obstacles accessing this critical assistance and would likely disproportionately suffer under tightened state 

waiver requirements. This is of particular concern after recent changes made 

by the Agriculture Improvement Act of 2018 (P.L. 115–334) that reduced states’ 

automatic exemption threshold from 15 percent to 12 percent. 

Conclusion 

SNAP time limits for ABAWDs adversely affect children and vulnerable youth, 

even though they are not the policy’s intended targets. The proposed rule would exacerbate this problem. Furthermore, it flies in the face of Congressional intent. Congress just concluded a review and reauthorization of SNAP in the Agriculture Improvement Act of 2018, and explicitly rejected the proposed changes. This proposed 

rule is executive overreach that clearly disregards Congressional intent. The National Education Association represents educators who will see in their classrooms 

every day how vulnerable children, as a result of this rule, will experience a reduction in important resources that help meet their basic needs. NEA strongly opposes 

the proposed rule because it would limit SNAP benefits for more low-income adults, 

as well as children who may rely on them to help meet basic needs. 

Sincerely, 

MARC EGAN, 

Director of Government Relations. 

SUBMITTED COMMENT LETTER BY HON. JAHANA HAYES, A REPRESENTATIVE IN

CONGRESS FROM CONNECTICUT; AUTHORED BY LISA DAVIS, SENIOR VICE

PRESIDENT, NO KID HUNGRY CAMPAIGN, SHARE OUR STRENGTH

March 29, 2019 

Certification Policy Branch, 

SNAP Program Development Division, 


11602054.eps
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1 Bolen, Ed, et al., 2016. More than 500,000 Adults Will Lose SNAP Benefits in 2016 as Waiver 

Expire (https://www.cbpp.org/research/food-assistance/more-than-500000-adults-will-lose-snapbenefits-in-2016-as-waivers-expire). Center on Budget and Policy Priorities. 2Waxman, Elaine and Nathan Joo. 2019. Reinstating SNAP Work-Related Time Limits: A 

Case Study of Able-Bodied Adults Without Dependents in Kentucky (https://www.urban.org/ 

sites/default/files/publication/100027/reinstating_snap_time_limits_1.pdf). Urban Institute. 3 United States Department of Agriculture. 2018. Proposed Rulemaking: Supplemental Nutrition Assistance Program: Requirements for Able-Bodied Adults Without Dependents (https:// 

s3.amazonaws.com/public-inspection.federalregister.gov/2018-28059.pdf). FNS–2018–0004, RIN 

0584–AE57. PP40. 

Food and Nutrition Service, USDA, 

Alexandria, Virginia 

Re: Proposed Rulemaking: Supplemental Nutrition Assistance Program (SNAP): 

Requirements for Able-Bodied Adults Without Dependents; RIN 0584–AE57, 

Docket ID: FNS–2018–0004 

Dear Certification Policy Branch: 

Thank you for the opportunity to comment on USDA’s Proposed Rulemaking on 

Supplemental Nutrition Assistance Program (SNAP) Requirements for Able-Bodied 

Adults Without Dependents (ABAWDs). 

Share Our Strength is a national anti-hunger and anti-poverty organization. 

Through our No Kid Hungry campaign, we work to end childhood hunger in the 

United States by ensuring children have access to healthy food, every day all year 

round. 

While we support the stated goal of fostering self sufficiency, we are deeply concerned that the proposed changes to further restrict ABAWD’s ability to receive 

SNAP benefits would cause significant hardship to very low-income individuals, restrict state flexibility and do nothing to help those struggling to find employment 

and secure jobs. To the contrary, the loss of food assistance will likely create additional financial and emotional stress making it harder to achieve this goal. The proposed rule also circumvents the will of Congress by attempting to implement, 

through executive action, policy changes Congress rejected in the bipartisan Agriculture Improvement Act of 2018 (the farm bill) which was recently enacted by an 

overwhelming majority. 

Current law limits individuals between the ages of 18 through 49, who have not 

received a disability certification or are raising minor children, to just 3 months of 

SNAP benefits out of every 3 years unless they can document they are working or 

participating in a job training program at least 20 hours per week. However, states 

aren’t required to offer work or training options to those impacted and most states 

do not. When several states began re-instating time limits that had been waived 

during the recession, at least 500,000 ABAWDs lost SNAP.1 And, mostly recently, 

reinstatement of the time-limit for ABAWDs in Kentucky led to an estimated 13,000 

individuals to lose their SNAP benefits, not because they found employment, but because they reached their benefit time-limit.2 This represented a 20 to 22 percent decline in ABAWDs caseload in the state between January 2017 and September 2018. 

Recognizing that communities across the United States often face specific local 

challenges around employment and that state leaders are better equipped than their 

Federal counterparts to evaluate local economic conditions, states have long had the 

ability to seek waivers from the strict 3 month limit in areas where jobs are lacking 

and to waive the requirements for portions of their caseload who face particular 

challenges meeting the work requirement. This flexibility allows states to be responsive to local labor market variables and to protect individuals who live in areas of 

high unemployment, areas where economic conditions are lagging, and/or areas impacted by catastrophic events such as a natural disaster. The proposed rule would 

undermine states’ flexibility, implementing a one-size-fits-all approach that eliminates some waiver grounds and restricts others. 

We agree that the best pathway from poverty to self-sufficiency is through adequate and stable employment. However, even though national unemployment has 

dropped to about four percent, millions of people in communities across the country 

continue to struggle to make ends meet due to difficulty finding a job, low wages 

and inadequate hours, limited skills, poor health or inadequate transportation. This 

rule would do nothing to help those impacted obtain employment. To the contrary, 

it would increase hunger and economic hardship by eliminating SNAP benefits for 

more than 750,000 3 unemployed and underemployed Americans according to 

161 

4 Cunnyangham, Karen. 2019. Proposed Changes to the Supplemental Nutrition Assistance 

Program: Waivers to Work-Related Time Limits (https://www.mathematica-mpr.com/our-publications-and-findings/publications/proposed-changes-to-the-supplemental-nutrition-assistanceprogram-waivers-to-work-related-time). Mathematica Policy Research; Federal Poverty Level for a single individual is $12,490 for 2019. 5 Bolen, Ed. 2015. Approximately 1 Million People Would Lose Food Assistance Benefits in 

2016 As State Waivers Expire: Affected Individuals Are Very Poor: Few Qualify for Other Help. Center On Budget and Policy Priorities. 6Shared Justice. 2017. Aging Out of Foster Care: 18 and On Your Own (http:// 

www.sharedjustice.org/most-recent/2017/3/30/aging-out-of-foster-care-18-and-on-your-own). 7Supra note at 9. 8 Center on Poverty and Social Policy. 2018. Understanding Recent Trends In Food Stamp 

Usage and implications for Increased Work Requirements (https://static1.squarespace.com/static/5743308460b5e922a25a6dc7/t/5b69b61970a6adeee8860dc8/1533654555824/Poverty+and+So 

cial+Policy+Brief_2_5.pdf). Columbia University 9Wheaton, Laura and Victoria Tran. 2018. The Anti-Poverty Effects of the Supplemental Nutrition Assistance Program (https://www.urban.org/sites/default/files/publication/96521/ 

the_antipoverty_effects_of_the_supplemental_nutrition_assistance_program_3.pdf). Urban Institute. 10 Berkowitz, Seth, et al., 2017. Supplemental Nutrition Assistance Program (SNAP) Participation and Health Care Expenditure Among Low-Income Adults (https://jamanetwork.com/journals/jamainternalmedicine/article-abstract/2653910?redirect=true). JAMA INTERNAL MEDICINE. 11Ohio Association of Food Banks. 2015. Franklin County: Work Experience Program, AbleBoded Adults Without Dependents (http://admin.ohiofoodbanks.org/uploads/news/ 

ABAWD_Report_2014-2015-v3.pdf). 

USDA’s own calculations. Other studies estimate the impact to be higher—with 1.2 

million individuals loosing food access.4

Those hit hardest would be those facing the greatest challenges in the labor market, including people of color, young adults aging out of foster care, veterans, homeless individuals, and those with limited education or skills or under-diagnosed physical or mental health issues. Research shows that only 1⁄2 of ABAWDs nationally 

have a high school diploma or the equivalent,5 making it difficult to find and maintain stable employment in today’s knowledge-based economy. Children aging out of 

foster care are particularly vulnerable. By age 24, only 1⁄2 of these youths will obtain 

employment and only three to four percent will have earned a college degree by age 

26, making them especially vulnerable to hunger and poverty.6

Those impacted by SNAP time limits are often living in extreme poverty. According to latest research, 88 percent of ABAWDs that would be impacted by the proposed rule are making less than $6,245 per year per individual.7 They constitute 

a relatively small portion of all SNAP recipients—representing 12 percent or seven 

million individuals nationwide—and their numbers do not appear to be increasing 

despite claims to the contrary.8

Further restricting benefits for ABAWDs is poor public policy and counterproductive, particularly in light of the growing body of research demonstrating 

SNAP’s effectiveness and short and longer-term impact on health and economic security. In 2015 alone, SNAP lifted 8.4 million people out of poverty.9 SNAP does this 

by freeing up resources that participants can spend on other critical needs such as 

housing, childcare, health care costs and transportation. In addition, studies found 

that SNAP participation was tied to an annual reduction of $1,400 in health care 

costs among low-income adults.10

SNAP already functions as an effective work support program. Most SNAP participants who can work are working or have worked in the past year, often for limited hours or in seasonal employment. This is particularly true for those considered 

ABAWDs: 25 percent are working while receiving benefits and 75 percent worked 

the year before or after receiving benefits. The experience of Franklin County, Ohio, 

demonstrates the challenges ABAWDs face in meeting the 20 hours per week work 

requirement due to unpredictable work schedules and lack of stable jobs.11

There is no evidence to suggest that restricting state waiver authority and thus 

eliminating benefits for hundreds of thousands of current SNAP beneficiaries would 

serve to increase employment and earnings among ABAWDs. Instead, it would punish those who were unable to find stable employment of at least 20 hours per week 

by denying them food benefits at a time when they most need it. The effect would 

be increased hunger and hardship. In fact, SNAP is one of the only supports available to individuals who fall under the ABAWD definition, as childless adults are not 

eligible for most other safety-net programs. 

Rather than reducing state flexibility and further restricting SNAP benefits for 

ABAWDs, policy change should be focused on addressing the underlying barriers to 

employment among those impacted such as limited education and skills, physical 

and mental health issues, unstable housing and lack of access to transportation. Investments in effective employment and training programs that are based on an indiVerDate Aug 31 2005 11:16 Jun 14, 2019 Jkt 041481 PO 00000 Frm 00167 Fmt 6621 Sfmt 6621 P:\DOCS\116-02\36188.TXT BRIAN
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12Waxman, Elaine, et al., 2019. Poverty, Vulnerability, and the Safety Net (https:// 

www.urban.org/urban-wire/social-safety-net-2019-four-trends-watch-snap). Urban Institute. 

vidualized assessment of the beneficiary and tailored to their skills and challenges 

would be a much more effective way to help SNAP ABAWDs move from poverty to 

self-sufficiency. Research shows that SNAP Employment and Training (E&T) programs remain limited in their capacity to meet current needs, serving only a small 

percentage of those who are subject to work requirements,12 reinforcing the challenges facing ABAWDs who would be impacted by the proposed rule. 

While the SNAP Employment and Training pilots authorized and funded through 

the 2014 Farm Bill will offer important learnings and best practices, work requirements should not be expanded unless adequate and effective job training programs 

and supports are in place to ensure meaningful pathways to self-sufficiency. 

We encourage strong coordination between SNAP Employment and Training with 

other federally funded job training and placement programs, as well as adequate 

funding for programs and services that support work, such as child-care, transportation, mental health counseling and casework management. 

Work requirements or benefit time limits that are not accompanied by the resources to ensure those impacted can find and sustain employment run counter to 

the objective of achieving economic self-sufficiency and serve only to restrict benefits, thus increasing hunger and poverty rather than increasing employment and 

wages. 

We urge you to maintain states’ flexibility to both request time limit waivers 

when jobs and employment supports are not available and to waive the work requirements for portions of their caseload who face particular challenges in meeting 

the work requirement. The rules governing areas eligibility for waivers were enacted with bipartisan support, have been in place for nearly 20 years and every 

state except Delaware has availed themselves of waivers at some point since the 

time limit became law. The waiver rules are reasonable, transparent, and manageable for states to operationalize. Thus, any change that would restrict, impede, or 

add uncertainty to states’ current ability to waive areas with high unemployment 

should be avoided. 

Therefore, we respectfully request USDA to withdraw this harmful proposal. Congress has deliberated on these issues and rejected the restrictions included in the 

proposed rule in the 2018 Farm Bill, opting instead to including provisions to 

strength, encourage, and prioritize effective job training and employment-related activities. 

Sincerely, 

LISA DAVIS, 

Senior Vice President, No Kid Hungry Campaign, 

Share Our Strength. 

SUBMITTED COMMENT LETTER BY HON. KIM SCHRIER, A REPRESENTATIVE IN

CONGRESS FROM WASHINGTON; AUTHORED BY HON. JAY INSLEE, GOVERNOR, STATE

OF WASHINGTON

March 29, 2019 

The Honorable SONNY PERDUE, 

Secretary, 

U.S. Department of Agriculture 

Washington, D.C. 

Dear Secretary Perdue: 

On behalf of the State of Washington, I write to express my grave concerns with 

the Food and Nutrition Service’s (FNS) proposed rule, ‘‘Supplemental Nutrition Assistance Program (SNAP): Requirements for Able-Bodied Adults Without Dependents (ABAWDs).’’ This misguided and harmful policy would severely restrict access 

to food assistance for those who need it most, exacerbating hunger and making it 

even more difficult for people in poverty to find work. It removes state flexibility, 

rips away food assistance from 755,000 vulnerable Americans, worsens our homelessness crisis, and fails to achieve the Administration’s stated goal of improving 

self-sufficiency. I strongly urge that it be withdrawn. 

Evidence shows that SNAP is one of the most important lifelines for families and 

communities facing economic hardship, lifting millions of Americans out of poverty 


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1 Center for Budget and Policy Priorities (CBPP), March 2018. 

2Washington State Department of Agriculture (WSDA), January 2018. 

3 CBPP, April 2018. 

and food insecurity every year. More than 42 million people across the country rely 

on SNAP for food assistance, including more than 920,000 in Washington alone.1 It 

is a particularly significant safety net for our most vulnerable, as 75 percent of 

SNAP households include a child, an elderly person, or a person with disabilities.2

The program is also a key economic driver that supports food producers, farmers’ 

markets, and retailers. Every dollar spent on nutrition assistance expands the economy by approximately $1.70, boosting local economies and supporting 260,000 individual retailers nationwide.3

This Administration’s proposal would radically alter the SNAP program for certain populations and take away needed flexibility from states, imposing a top-down, 

one-size-fits-all approach that prevents Washington from addressing the unique and 

individualized needs of our local communities. It would directly harm our people 

and our economy, threatening to rip away food assistance from more than 91,000 

individuals who currently receive an average monthly benefit of $210.40, while reducing annual total revenue for Washington by over $32.6 million. Nationally, the 

proposed changes would result in a loss of $85 billion in economic activity for grocery stores, farmers, and other local food retail suppliers. It is a cruel and meanspirited policy that damages people and businesses alike. 

Congress rejected these exact changes on a bipartisan basis last year. In considering the 2018 Farm Bill (P.L. 115–[334]), which was approved by large majorities 

in both chambers and signed by the President on December 20, 2018, Congress debated and subsequently excluded these changes to the SNAP program that would 

strip state flexibility and impose harsh, inflexible requirements on beneficiaries. To 

any objective observer, it is clear that these changes were not intended to be made 

and that USDA’s proposal runs counter to Congressional intent. I encourage USDA 

to heed the advice of Congress in withdrawing this deeply harmful policy. 

I appreciate the opportunity to share our state’s concerns and hope you give them 

the attention and consideration they deserve. Below, please find additional feedback 

from our state on specific questions raised by USDA in the proposed rule. 

Labor Market Areas for Grouping 

In USDA’s proposal, the Department specifically requested comments on the use 

of Labor Market Areas (LMAs) for grouping areas. We believe LMAs defined by the 

Federal Government should be included as the basis for grouping areas, and that 

grouping should not be prohibited entirely. States are currently given discretion to 

define groups or areas to be combined, provided the areas are contiguous or considered part of the same economic region. Availability of jobs is examined when counties are in close proximity to counties where individuals often commute. Washington 

uses this discretion for LMA groupings because we understand our residents are 

disadvantaged when they are required to travel unreasonable distances for employment. People should be able to readily change jobs without being forced to change 

their place of residence, particularly as most ABAWDs have limited resources and 

cannot easily commute or change residences to obtain employment. 

If LMAs are not a basis for grouping, participants may not be able to reside and 

find employment within a reasonable distance or change jobs without also having 

to change their residence. Denying states the ability to group counties would negatively impact an estimated 91,203 individuals in Washington identified as ABAWDs. 

The loss of waivers for these counties would also cause a negative impact on our 

local economies. 

Setting a Floor for the 20 Percent Standard 

Washington does not support USDA’s proposal to establish a floor for the 20 percent standard, which would further limit state flexibility and restrict necessary 

waivers to appropriately serve SNAP beneficiaries. We do not believe that a floor 

of six percent, seven percent or ten percent is needed or advisable. (See Table 2 

for additional data on how these changes would adversely affect our state.) We believe the current floor setting that has been established at 20 percent above the average national unemployment rate is appropriate and necessary. 

The current standard is essential to allow flexibility in requesting necessary waivers. This flexibility is granted with the knowledge that state and local leaders are 

best equipped to develop solutions for their specific labor markets and industries. 

While the unemployment rate does provide essential data, it does not take into account a community’s individualized workforce needs or that its residents may not 

be well-suited to find and keep locally available jobs due to lack of housing, skills, 

164 

4Department of Social and Health Services (DSHS) Economic Services Administration (ESA), 

January 2019. 5DSHS ESA, January 2019. 

training, or other barriers. To illustrate this, Table 1 highlights the top ten occupations, hard skills, certifications, and employers in Washington according to our Employment Security Department (ESD): 

Table 1: Employmer Demand in Washington State 

Occupations Hard Skills Certifications Employers 

Software Developers Microsoft Office Driver’s License Amazon 

Registered Nurses Quality Assurance Commercial Driver’s License Providence Health & Services 

Retail Salespersons 

Computer Occupations 

Microsoft PowerPoint 

Freight+ 

Class A Commercial Driver’s 

License 

State of Washington 

Peace Health 

First-Line Supervisors of Retail 

Sales Workers 

Software Development 

Java 

Basic Life Support 

Certified Registered Nurse 

University of Washington 

Microsoft 

Marketing Managers 

Stock Clerks and Order Filers 

Structured Query Language 

Python 

Certification in Cardiopulmonary Resuscitation Catholic Health Initiatives 

MultiCare Health System 

Customer Service Representatives Bilingual 

Forklifts 

Security Clearance 

Continuing Education 

Schweitzer Engineering Laboratories 

Heavy and Tractor-Trailer 

Drivers 

First Aid Certification 

HAZMAT 

Kaiser Permanente 

First-Line Supervisors of Food 

Preparation and Serving 

Workers 

Job readiness in these fields can be an insurmountable goal for individuals who 

must navigate numerous and repetitive barriers on a daily basis. From homelessness and housing instability to domestic violence, mental health, and substance use 

disorder, there are myriad and significant barriers facing ABAWDs that prevent 

them from effectively seeking and obtaining employment. In many cases, these barriers must be addressed first for an individual to be ready for job training and the 

workforce. A person experiencing homelessness must primarily focus on where they 

are going to sleep and eat, for example, not where are they going to find work. 

In Washington, we estimate that more than 43 percent of our state’s ABAWD population is currently experiencing homelessness—disproportionately higher than the 

broader SNAP population, of which only 11 percent are experiencing homelessness. 

Nearly 60 percent of the ABAWD population is suffering from behavioral or physical 

health conditions, including substance use disorder.4 For these individuals, USDA’s 

proposal would do nothing to help them find work, while adding yet another obstacle in their way—food insecurity. It would not achieve USDA’s stated goal of promoting self-sufficiency and in fact would make it more difficult for ABAWDs to find 

employment. 

Large percentages of SNAP recipients also experience labor market fluctuations 

due to seasonal employment, part-time work, or underemployment, and would be directly harmed by USDA’s proposal despite their participation in the workforce. The 

vast majority of those who transition between working more than 20 hours a week 

and a different employment status—less than 20 hours a week, seeking employment, or not in the labor force—are working on a monthly basis but still may not 

meet USDA’s one-size-fits-all work requirement. Under the proposed rule, a large 

number of individuals would lose food assistance as a result of volatility in the labor 

market and through no fault of their own. 

We support current Federal regulations that allow states to waive the 3 month 

time limit in geographic areas with high unemployment or insufficient jobs. Creating an unemployment rate floor would negatively impact a large number of counties across our state, including wide swaths of rural and economically disadvantaged 

communities. The loss of waivers would affect SNAP eligibility for tens of thousands 

of Washington citizens who may otherwise not qualify for food assistance. 

Table 2 below illustrates how the proposed changes would impact SNAP recipients 

in Washington under USDA’s proposed changes. A review of data shows that there 

is no difference in the number of counties and SNAP recipients adversely affected 

at seven or ten percent. 

Table 2: Impact of Proposed Changes to Washington State 5

Proposed Change Loss of Grouping 6% Floor 7% or 10% Floor 

SNAP Recipients Adversely Affected 15,321 75,407 91,203 

165 

6 Centers for Disease Control and Prevention (CDC), July 2017. 

Table 2: Impact of Proposed Changes to Washington State 5—Continued

Proposed Change Loss of Grouping 6% Floor 7% or 10% Floor 

Counties Adversely Affected Asotin, King, San Juan, Snohomish, Walla Walla, Whitman 

(6 counties) 

Adams, Asotin, Benton, Chelan, Clark, Columbia, Cowlitz, Douglas, Franklin, Island, Jefferson, King, 

Kitsap, Kittitas, Klickitat, 

Lincoln, Pierce, San Juan, 

Skagit, Skamania, Snohomish, Spokane, Thurston, 

Walla Walla, Whatcom, and 

Whitman (26 counties) 

All counties except Ferry (38 

counties) 

Eliminating the Carryover Exemption Provision 

Washington strongly disagrees with USDA’s interpretation of the ABAWD exemption provision of the 2018 Farm Bill, which decreases ABAWD exemptions granted 

to states from 15 percent to 12 percent It is our interpretation that the law did not 

intend for USDA to limit the carryover of exemptions for ‘‘covered individuals,’’ and 

only lowered the percentage of exemptions granted to each state. We believe this 

proposal is contrary to Congressional intent and should be withdrawn. 

The 2018 Farm Bill and current regulations give states flexibility over whether 

and when to use and carryover these exemptions. Washington depends on this flexibility to effectively operate our program. In 2015, Washington was one of ten states 

awarded a SNAP Employment and Training (E&T) pilot, which tests innovative approaches to employment for work registrants. Participants were randomly assigned 

to a control and treatment group. Washington was able to use our 15 percent exemptions to ensure participants assigned to the control group remained engaged and 

eligible for food assistance to ensure accuracy of our pilot. The elimination of carryover exemptions would significantly impact our state’s ability to carry out the E&T 

pilot and effectively operate our SNAP program. 

Conclusion 

Washington strongly opposes USDA’s proposal threatening food assistance for 

more than 91,000 individuals in our state and 755,000 Americans nationwide. We 

understand that obtaining employment can be difficult for many ABAWDs working 

to reach their full potential, many of whom face significant barriers—including 

homelessness and substance use disorder—with little or no resources. We also understand that state flexibility is necessary to meet the unique needs of the ABAWD 

population and our local economies. The current rules, which have been in place for 

20 years, are reasonable, transparent, manageable, and effective. We see no rational 

justification for this Administration’s sweeping changes that would undermine our 

state’s success in reducing hunger and moving people to employment. I urge that 

it be withdrawn.6

We appreciate your consideration of our state’s perspective. If you have any questions, please contact the Director of my Washington, D.C. Office, Casey Katims, at 

Casey.Katims@gov.wa.gov. Thank you. 

Very truly yours, 

Hon. JAY INSLEE, Governor. 

CC: 

Washington Congressional Delegation; 

CHERYL STRANGE, Secretary, Department of Social and Health Services (DSHS); 

DAVID STILLMAN, Assistant Secretary, DSHS Economic Services Administration; 

BABETTE ROBERTS, Director, DSHS Community Services Division. 

SUBMITTED COMMENT LETTER BY HON. KIM SCHRIER, A REPRESENTATIVE IN

CONGRESS FROM WASHINGTON; AUTHORED BY STACY DEAN, VICE PRESIDENT, FOOD

ASSISTANCE POLICY, CENTER ON BUDGET AND POLICY PRIORITIES

April 1, 2019 

Ms. SASHA GERSTEN-PAAL, 


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Chief, 

Certification Policy Branch, 

Program Development Division, 

Food and Nutrition Service, 

Alexandria, VA 

Re: Proposed Rule: Supplemental Nutrition Assistance Program: Requirements 

and Services for Able-Bodied Adults Without Dependents RIN 0584–AE57 

Dear Ms. Gersten-Paal: 

We are writing to provide comments on USDA’s Notice of Proposed Rule Making 

(NPRM) regarding the Supplemental Nutrition Assistance Program’s (SNAP) Requirements and Services for Able-Bodied Adults Without Dependents. The proposed 

rule would restrict longstanding state flexibility to waive areas from SNAP’s 3 

month time limit as well as limit states’ ability to exempt certain individuals from 

the time limit. As a result, USDA estimates that when fully implemented in a typical month some 755,000 individuals would lose food assistance benefits because 

they could not document an average of 80 hours per month of employment or that 

they qualify for an exemption. USDA does not provide any evidence to support its 

assertion that the policy would result in greater employment or earnings. This is 

likely because such evidence does not exist. Instead, there is an extensive body of 

research that suggests the very likely outcome of the proposed policy is that more 

individuals will experience hardship and poverty, including a risk of hunger. Moreover, given available research on work requirements and the labor market, the proposed policy is very likely to have even worse outcomes for African Americans, Native Americans, Latinos, and individuals with disabilities. 

The Center on Budget and Policy Priorities is a nonpartisan research and policy 

institute. We pursue Federal and state policies designed both to reduce poverty and 

inequality and to restore fiscal responsibility in equitable and effective ways. We 

apply our deep expertise in programs and policies that help low-income people in 

order to help inform debates and achieve better policy outcomes. We work to protect 

and strengthen programs that reduce poverty and inequality and increase opportunity for people trying to gain a foothold on the economic ladder. Our work on Federal nutrition programs, including SNAP, is a core component of our organization’s 

work. Our food assistance analyst team includes nine people, including eight analysts and researchers who work on SNAP policy and operations. We have deep expertise on SNAP time limit policy including waivers and individual exemptions. 

Three members of our team, as well as our organization’s President, have worked 

on SNAP for more than 2 decades, including during the time period when the law 

governing the time limit was enacted and the current regulations were proposed and 

codified. 

We have deep concerns with the proposed policy and offer extensive comments to 

support our strong recommendation that USDA withdraw the NPRM and maintain 

current policy. In addition to causing harm to vulnerable individuals who are in between jobs or underemployed, the proposed policy runs counter to Congressional intent. When legislating the time limit policy, Congress established a waiver authority 

that allows for states to waive the rule for areas with insufficient jobs for individuals subject to the rule. Given that individuals who fall into the group subject to 

the time limit face extreme difficulty in the labor market, a fact validated by extensive research, the proposed rule would undercut Congressional intent by setting arbitrary limits unrelated to the purpose of the waiver. 

The proposed rule is also poorly argued, internally inconsistent, and wildly out 

of sync with extensive research findings. It offers little, and in some cases, no reasoning or evidence to support such a dramatic change in a longstanding Federal policy that would have significant consequences on participants, states and other key 

stakeholders such as retailers and small business. The Department also provided 

flawed and contradictory analysis in the NPRM and did not include information 

available to the agency that would have informed the rulemaking process. USDA’s 

rationale for such a sweeping and harmful change was cursory at best making it 

almost impossible to comment in a way that is responsive to its thinking. Because 

USDA did not make its reasoning transparent or provide evidence to support its position, we feel obligated to review and provide years of well-known research and 

data (some of which USDA funded) that provides evidence counter to USDA’s proposed policy. We strongly encourage USDA to review these materials as we are concerned the Department is unaware of the overwhelming evidence that undermines 

their assertions and poorly formed conclusions in the proposed rule. This has resulted in lengthy comments in which we conclude that the best course of action for 

167 

the proposed policy and under the rulemaking process would be for USDA to withdraw the NPRM. We strongly urge that course of action. 

In this proposed rule, USDA proposed many damaging and ill-advised changes to 

waivers and individual exemptions from the 3 month time limit. The major changes 

include: 

• Mandating that areas must have a minimum of a seven percent average unemployment rate over a 2 year period in order to qualify for a waiver from the 

time limit; 

• Restricting states’ flexibility to define the area they wish to waive; 

• Eliminating several waiver criteria that have been part of program rules for 

over 20 years, including a low and declining employment-to-population ratio; 

• No longer allowing states to implement waivers that meet USDA’s criteria 

while not requiring that USDA approve waivers in a timely manner; 

• Requiring states to seek their governor’s written consent; and 

• Restricting states’ ability to accumulate unused individual exemptions. 

Our comments on the proposed regulation fall into several major categories: 

Proposed Changes to Waiver Criteria 

• Chapter 1: Overview of Waivers from the Three-Month Time Limit—Their Purpose and History 

• Chapter 2: FNS Waiver Policy Has Been Consistent for the Last 22 Years 

• Chapter 3: Setting a Floor for Waivers for Areas With 20% Above National Unemployment Is Inconsistent with Congressional Intent and Would Be Harmful 

to Vulnerable Individuals 

• Chapter 4: Dropping Several Key Criteria from the Insufficient Jobs Criteria Is 

Inconsistent with the Statute 

• Chapter 5: Restricting State Flexibility on Grouping Areas Is Counter to Evidence 

• Chapter 6: Taking Away Food Benefits from Individuals Who Cannot Document 

20 Hours a Week of Work Will Not Increase Labor Force Participation for This 

Population 

• Chapter 7: Proposed Rule’s Requirement That State Waiver Requests Have the 

Governor’s ‘‘Endorsement’’ Violates Congressional Intent 

• Chapter 8: Proposed Rule Would Make Implementing Time Limit Harder by Removing Provisions That Give States Certainty Around Approval 

Proposed Changes to Individual Exemptions 

• Chapter 9: Eliminating the Carryover of Unused Individual Exemptions Would 

Cause Hardship and Exceeds Agency Authority 

Problems with the Proposed Rule Process 

• Chapter 10: The Proposed Rule Fails to Provide Sufficient Rationale or Supporting Evidence for the Proposed Policy 

• Chapter 11: The Proposed Rule’s ‘‘Regulatory Impact Analysis’’ Highlights FNS’ 

Faulty Justification and Includes Numerous Unclear or Flawed Assumptions 

• Chapter 12: The Proposed Rule Would Disproportionately Impact Individuals 

Protected by Civil Rights Laws, Violating the Food and Nutrition Act’s Civil 

Rights Protections 

• Chapter 13: The Proposed Rule Fails to Adequately Estimate the Impact on 

Small Entities 

Appendix that includes all cited studies and references 

• Appendix A: CBPP Bios 

• Appendix B: Materials Cited in Comments 

We strongly urge USDA to withdraw the rule and maintain current policy. If you 

have any questions regarding our comments, please do not hesitate to contact us. 

Sincerely, 

STACY DEAN, 

Vice President, Food Assistance Policy. 


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1Steven Carlson, et al., ‘‘Who Are the Low-Income Childless Adults Facing the Loss of SNAP 

in 2016?’’ Center on Budget and Policy Priorities, February 8, 2016, http://www.cbpp.org/research/food-assistance/who-are-the-low-income-childless-adults-facing-the-loss-of-snap-in-2016. 

CENTER ON BUDGET AND POLICY PRIORITIES COMMENTS ON RIN 0584–AE57: SUPPLE- MENTAL NUTRITION ASSISTANCE PROGRAM: REQUIREMENTS AND SERVICES FOR ABLE- BODIED ADULTS WITHOUT DEPENDENTS

Table of Contents 

Proposed Changes to Waiver Criteria 

• Chapter 1: Overview of Waivers from the Three-Month Time Limit—Their Purpose and History 

• Chapter 2: FNS Waiver Policy Has Been Consistent for the Last 22 Years 

• Chapter 3: Setting a Floor for Waivers for Areas With Percent Above National 

Unemployment Is Inconsistent with Congressional Intent and Would Be Harmful to Vulnerable Individuals 

• Chapter 4: Dropping Several Key Criteria From Waiver Criteria Is Inconsistent 

With the Statute 

• Chapter 5: Restricting State Flexibility on Grouping Areas Is Counter to Evidence 

• Chapter 6: Taking Away Food Benefits from Individuals Who Cannot Document 

20 Hours a Week of Work Will Not Increase Labor Force Participation for This 

Population 

• Chapter 7: Proposed Rule’s Requirement That State Waiver Requests Have the 

Governor’s ‘‘Endorsement’’ Violates Congressional Intent 

• Chapter 8: Proposed Rule Would Make Implementing The Time Limit Harder 

by Removing Provisions That Give States Certainty Around Approval 

Proposed Changes to Individual Exemptions 

• Chapter 9: Eliminating the Carryover of Unused Individual Exemptions Would 

Cause Hardship and Exceeds Agency Authority 

Problems with the Proposed Rule Process 

• Chapter 10: The Proposed Rule Fails to Provide Sufficient Rationale or Supporting Evidence for the Proposed Policy Change 

• Chapter 11: The Proposed Rule’s ‘‘Regulatory Impact Analysis’’ Highlights FNS’ 

Faulty Justification and Includes Numerous Unclear or Flawed Assumptions 

• Chapter 12: The Proposed Rule Would Disproportionately Impact Individuals 

Protected by Civil Rights Laws, Violating the Food and Nutrition Act’s Civil 

Rights Protections 

• Chapter 13: The Proposed Rule Fails to Adequately Estimate the Impact on 

Small Entities 

Appendix that includes all cited studies and references 

• Appendix A: CBPP Bios 

• Appendix B: Materials Cited in Comments 

Note, throughout these comments, we use the terms: Food and Nutrition Service 

(FNS), U.S. Department of Agriculture (USDA), and ‘‘the Department’’ somewhat 

interchangeably. We are not aware of a particular convention and it is not our intent to suggest difference when we use one term vs. the other. In addition, when 

we refer to ‘‘state’’ or ‘‘states’’ we intend to include counties in their role administering the program in county-administered states. 

Chapter 1: Overview of Waivers from the Three-Month Time Limit—Their 

Purpose and History 

The time limit is one of the harshest rules in the Supplemental Nutrition Assistance Program (SNAP, formerly known as the Food Stamp Program). Childless 

adults on SNAP are extremely poor. Like adults with children, childless adults often 

turn to SNAP for assistance when they are no longer able to make ends meet, especially as they lose jobs, their hours are cut, or their wages hover at the Federal minimum. While participating in SNAP, their income averages 29 percent of the poverty 

line, the equivalent of about $3,400 per year for a single person in 2016.1 The U.S. 

Department of Agriculture (USDA), which administers SNAP, has established 

standards that have remained consistent over the last 20 years under which states 

can request a waiver of the time limit for areas with consistently high unemployVerDate Aug 31 2005 11:16 Jun 14, 2019 Jkt 041481 PO 00000 Frm 00174 Fmt 6621 Sfmt 6621 P:\DOCS\116-02\36188.TXT BRIAN
169 

2For a more comprehensive discussion of the time limit rule, see: Ed Bolen, et al., ‘‘More Than 

500,000 Adults Will Lose SNAP Benefits in 2016 as Waivers Expire,’’ Center on Budget and Policy Priorities, updated March 18, 2016, http://www.cbpp.org/research/food-assistance/morethan-500000-adults-will-lose-snap-benefits-in-2016-as-waivers-expire. 3 ‘‘FNS Controls Over SNAP Benefits for Able-Bodied Adults Without Dependents,’’ USDA Office of Inspector General, Audit Report 27601–0002–31, September 2016, https:// 

www.usda.gov/oig/webdocs/27601-0002-31.pdf. 

ment. States request waivers for multiple reasons, including to ease administrative 

burden, implement more effective work programs, and exempt vulnerable individuals who likely will struggle to find work. The proposed rule would severely weaken 

this flexibility, increasing administrative burden for states and hardship for SNAP 

participants who struggle to find work. This chapter describes the history of these 

waivers, Congressional intent and early implementation of waiver rules, and the 

reasons why states choose to waive areas in their state. 

One of SNAP’s harshest rules limits unemployed individuals aged 18 to 50 not 

living with children to 3 months of SNAP benefits in any 36 month period when 

they aren’t employed or in a work or training program for at least 20 hours a week.2

Under the rule, implemented as part of the 1996 welfare law, states are not obligated to offer affected individuals a work or training program slot, and most do not. 

SNAP recipients’ benefits are generally cut off after 3 months irrespective of whether they are searching diligently for a job or willing to participate in a qualifying 

work or job training program. As a result, this rule is, in reality, a time limit on 

benefits and not a work requirement, as it is sometimes described. 

In addition to being harsh policy that punishes individuals who are willing to 

work but can’t find a job, the rule is one of the most administratively complex and 

error-prone aspects of SNAP law. Many states also believe that the rule undermines 

their efforts to design meaningful work requirements, as the time limit imposes unrealistic dictates on the types of job training that can qualify. For these reasons, 

many states and organizations that represent SNAP participants have long sought 

the rule’s repeal. 

The time limit law does provide states with the ability to seek waivers from 

USDA to temporarily suspend the 3 month limit for individuals in areas with insufficient jobs. These waivers are the primary subject of the proposed rulemaking along 

with states’ authority to use flexible individual exemptions to exempt individuals of 

their choosing from the time limit. Since passage of the welfare law, many states 

have sought waivers for counties, cities, or reservations with relatively high and 

sustained unemployment. Every state except Delaware has sought a waiver at some 

point since the time limit’s enactment.3

States can choose (or choose not) to request a waiver. In some cases, states with 

areas that have a persistently struggling labor market, such as the Central Valley 

in California or rural West Virginia, have sought waivers to avoid penalizing those 

who cannot find a 20 hour per week job within 3 months. In other cases, governors 

have sought waivers because extraordinary events have hurt their local labor markets, such as the 2010 Gulf of Mexico oil spill, Hurricane Katrina, or layoffs from 

a major local employer. 

Many states also seek waivers from the time limit because they would prefer to 

devote the resources needed to implement the administratively complex time limit 

to implementing a more rational and appropriate work requirement tailored to their 

local economy and to available job training programs. 

170 

4During the recession and its aftermath, Congress made a large portion of the country temporarily eligible for a waiver in recognition of widespread elevated unemployment. Some have misinterpreted this temporary expansion of waivers as a permanent expansion of the policy or an 

Obama Administration-led effort to eliminate the time limit. 5Supplemental Nutrition Assistance Program: Requirements and Services for Able-Bodied 

Adults without Dependents, 84 FED. REG. § 980 (proposed rule February 1, 2019) found at 

https://www.federalregister.gov/documents/2019/02/01/2018-28059/supplemental-nutritionassistance-program-requirements-for-able-bodied-adults-without-dependents#p-45, hereafter we 

will refer to this as the ‘‘NPRM.’’ 6FNS White Paper, ‘‘Time Limit Waivers for Able-Bodied Food Stamp Recipients,’’ April 23, 

1997. Faxed from FNS to OMB analyst Lester Cash on April 25, 1997. 

Figure 1 

Estimated Impact of USDA Proposed Rule 

Share of U.S. Waived from SNAP’s 3 Month Time Limit 

Note: Represents share of U.S. population living in a waived area, i.e., 

county or city. 

* Estimated [share] of U.S. population living in a waived area under 

USDA proposed rule, if rule were in effect in 2018. 

Source: CBPP analysis of state waivers; U.S. Census Bureau population 

estimates. 

USDA’s guidelines regarding waiver criteria, articulated in guidance and regulations, have set clear, consistent standards for waivers since soon after the statute 

adopted the time limit and waiver provisions in 1996. A review of waivers over the 

last 20 years shows that just over 1⁄3 of the country (as measured by the share of 

the total population living in waived counties) is waived in a typical year.4 (See Figure 1.) 

In the NPRM, USDA states that the current rate of waivers was unforeseen, 

which is inconsistent with the historical record that demonstrates that USDA’s 

original estimate of the extent of waiver coverage under its rules was in line with 

current actual coverage. In the NPRM preamble, the Department states: ‘‘The proposed rule addresses these areas of concern and places safeguards to avoid approving waivers that were not foreseen by Congress and the Department, and to restrict 

states from receiving waivers in areas that do not clearly demonstrate a lack of sufficient jobs.’’ 5 This statement stands in contrast to USDA’s own documents. USDA 

was fully cognizant that its original proposed waiver policy, which it later codified 

into final regulations, could result in more than 1⁄3 of the country being waived. In 

an internal summary of waivers from April 23, 1997 entitled, ‘‘Time Limit Waivers 

for Able-bodied Food Stamp Participants,’’ FNS staff wrote to Office of Management 

and Budget staff that ‘‘Thirty percent to 45 percent of the able-bodied caseload may 

be waived. However, USDA’s best estimate is that the areas that have been waived 

represent approximately 35 percent of the able-bodied caseload in the nation as a 

whole.’’ 6 This was written at a time of relatively low unemployment and early in 

the implementation of waivers when take up of waivers was relatively low. This 

would suggest that current policy, which has resulted in 36 percent of the general 


11602063.eps
171 

7 Based on CBPP internal analysis of unemployment data from the U.S. Bureau of Labor Statistics and the U.S. Census Bureau. The list of areas is included in Appendix B as ‘‘CBPP Summary of Areas That Would Have Lost Their Waivers form the SNAP Three-Month Time Limit 

in 2018 if the Proposed Rule Were Implemented in 2018.’’ 8 142 Cong. Rec. H7905 (daily ed. July 18, 1996). In fact, only about ten states had food stamp 

workfare programs at that time, and most such programs were very small. Many of them operated in only a few counties in these states, an some were only open to families with children. 

Even today, SNAP workfare is unavailable to a great many people subject to the time limits. 9 142 Cong. Rec. H7905 (daily ed. July 18, 1996). 10 142 Cong. Rec. H7905 (daily ed. July 18, 1996). 

population living in waived areas except during the Great Recession and its aftermath, is consistent with what USDA originally intended rather than something that 

has exceeded its vision. Moreover, the memo does not suggest any concern with the 

share of the country waived. And, these criteria were nearly exact to those codified 

in final rules. 

Under USDA’s proposed rule, however, areas eligible for waivers would be dramatically reduced. Our organization applied the proposed rule to the areas waived 

in 2018 and determined that: 

• Of the 985 counties (or county equivalents) waived in 2018, 639 counties (65 

percent of all waived counties) in 28 states would have lost their waivers. 

• Of the 309 towns located outside of waived counties in 2018, 285 towns (92 percent of all waived towns) would have lost their waivers, including 259 New England towns. 

• 170 out of the 273 reservations (62 percent of all waived reservations) waived 

in 2018 would have lost their waivers.7

Under the proposed policy, we estimate that the share of the U.S. population living in waived areas would have declined by over 80 percent in 2018, from 36 percent 

to 6.1 percent of the U.S. population. The proposed rule would therefore result in 

a dramatic reduction in states’ ability to waive areas from the time limit. Unfortunately, that appears to be USDA’s goal rather than designing and implementing a 

policy consistent with the statute, i.e., setting waiver criteria and policy that would 

allow states to waive areas with insufficient job for individuals subject to the time 

limit. 

A. Current Rules Governing Waivers for Areas With Insufficient Jobs for Individuals 

Subject to the Time Limit 

The SNAP time limit provision is based in substantial part on an amendment successfully offered on the House floor on July 18, 1996, by Reps. Robert Ney and John 

Kasich. When considering the appropriateness of some of the proposals in the proposed rule, it is illuminating to example the floor debate to see what Congress did— 

and did not—think it was requiring. 

The floor debate indicates that the amendment’s cosponsors believed that then 

food stamp workfare (participation in which would have exempted an individual 

from benefit termination) to be widespread and assumed that large numbers of 

those who cannot find a private-sector job would be offered a workfare slot. For example, Rep. Kasich stated on the floor: ‘‘ . . . let me be clear what the amendment 

does so that there is no confusion. If you are [able]-bodied, single, between the ages 

of 18 and 5-, and you get food stamps, we are saying you have to work . . . If you 

cannot get a job, you go to a workfare program; 45 out of 50 states have a workfare 

program.’’ 8

The sponsors heatedly disputed the statements by opponents of the amendment 

that the amendment would cause substantial hardship by denying assistance to people who want to work but cannot find a job or a workfare slot. And, they emphasized that the amendment contains waivers and other means to avert such situations. For example: 

• Rep. Ney stated: ‘‘ . . . if we read the text, there are hardship exemptions. It 

can be waived. There are safeguards in this.’’ 9 Mr. Ney also noted: ‘‘ . . . it is 

an amendment that provides some safety, it provides a course of a safety net 

[sic], it has the ability to have waivers from the state department of human 

services.’’ 10

• Rep. Kasich also addressed this issue. ‘‘It is only if you are able-bodied, if you 

are childless, and you live in an area where you are getting food stamps and 

there are jobs available, then it applies. So, if you are able-bodied, you go and 

you have to work 20 hours to get your food stamps. The of course if you cannot 

find a job then you do workfare. That is what it is. But there are a number 

172 

11 142 Cong. Rec. H7905 (daily ed. July 18, 1996) (emphasis added). 12 U.S. Department of Agriculture, Food and Nutrition Service (FNS) ‘‘Guidance for States 

Seeking Waivers for Food Stamp Limits,’’ FNS guidance to states, December 3, 1996. 13 U.S. Department of Agriculture, Food and Nutrition Service (FNS) ‘‘Guidance for States 

Seeking Waivers for Food Stamp Limits,’’ FNS guidance to states, December 3, 1996. Copy included in the appendix. 14 Ibid. 15 64 Fed. Reg. No. 242, page 70920, RIN: 0584–AC39 (proposed rule December 17, 1999.) 16 CBPP Comments on 64 Fed. Reg. No. 242, page 70920, RIN: 0584–AC39, February 17, 2000. 17 Comments submitted by the Greater Upstate Law Project, Center for Civil Justice and the 

American Public Human Services Administration on 64 Fed. Reg. No. 242, page 70920, RIN: 

0584–AC39, February 17, 2000. 

of exemptions in here for people who find themselves in particularly difficult 

circumstances . . .’’ 11

As their statements indicate, the amendment’s sponsors visualized the amendment largely as one under which people were prodded to look for work, were generally provided a workfare slot if a private sector jobs was not available and would 

be protected by a waiver if there were insufficient jobs and workfare slots for them. 

The sponsors did not see their amendment as one under which large numbers of 

individuals who want to work but cannot fund a job end up with neither work nor 

food stamps. It should be noted that the sponsors were not cognizant of the extremely limited number of food stamp workfare slots throughout the country. 

In the final legislation Congress established that states could waive areas lacking 

jobs. USDA has established criteria to implement that authority that have been consistent for 2 decades. The rule was designed to permit states to seek waivers in 

areas where jobs aren’t available. To qualify for a waiver, states must provide detailed evidence of high unemployment in local areas, in accordance with rigorous requirements set by USDA. USDA has consistently used the same criteria to define 

high unemployment since the late 1990s. 

The Federal law gives states the option to request a waiver of the time limit if 

they can document that a given geographic area has an insufficient number of jobs 

(or has an unemployment rate over ten percent). The standards that define how a 

state may document ‘‘insufficient jobs’’ were first outlined in FNS Guidance issued 

in December 1996.12 In the guidance, USDA offered several reflections on its understanding of Congressional intent at the time. First, USDA shared its belief that 

Congress understood that this group of individuals could find it especially challenging to find permanent employment and that waivers are intended recognize this 

problem. ‘‘USDA believes that the law provided authority to waive these provisions 

in recognition of the challenges that low-skilled workers may face in finding and 

keeping permanent employment. In some areas, including parts of rural America, 

the number of employed persons and the number of job seekers may be far larger 

than the number of vacant jobs. This may be especially so for person with limited 

skills and minimal work history.’’ 

In addition, the guidance provided key background on some of the policy that 

USDA seeks to restrict in the NPRM. With respect to how states can set or define 

the area within the state that it seeks to waive, USDA said, ‘‘USDA will give states 

broad discretion in defining areas that best reflect the labor market prospects of 

program participants and administrative needs.’’ 13 The guidance also recognized 

that the statute seeks to identify whether or not there are sufficient jobs for individuals subject to the time limit. ‘‘The guidance that follows offers some examples of 

the types and sources of data available to states as the consider waiver requests for 

areas with insufficient jobs. Because there are not standard data or methods to 

make the determination of the sufficiency of jobs, the list that follows is not exhaustive. States may use these data sources as appropriate, or other data as available, 

to provide evidence that the necessary conditions exist in the area for which they 

intend the waiver to apply. The absence of a particular data source or approach (for 

example, data or statistics compiled by a university is not meant to imply that it 

would not be considered by USDA if requested by a state.’’ 14

In its original NPRM that covered how USDA would regulate the waiver authority, FNS included the conceptual framework of the criteria detailed guidance but did 

not include all of the specifics in the actual regulation language.15 Commenters, including the Center on Budget and Policy Priorities comments that USDA should include and codify the details of the guidance into rule in order to prevent changes 

in how waiver policy was interpreted and applied, allowing for consistency.16 Other 

commenters expressed appreciation for the substance of the waiver criteria as articulated in the guidance and provided for in the NPRM.17 USDA adopted the suggestion and included the guidance almost verbatim in the final rule. These criteria 

173 

18 U.S. Department of Labor, ‘‘Labor Surplus Area: Frequently Asked Questions,’’ updated August 21, 2015, https://www.doleta.gov/programs/lsa_faq.cfm. 19The EB program has criteria in law under which unemployed workers in a state are eligible 

to receive extended unemployment benefits, and states can opt to offer EB benefits under certain additional criteria. (For more information, see ‘‘Conformity Requirements for State UI 

Laws,’’ Department of Labor, https://workforcesecurity.doleta.gov/unemploy/pdf/uilaws_ 

extended.pdf.) Because these unemployment criteria (known as ‘‘triggers’’) establish high unemployment, a state is eligible for a waiver if it meets the criteria under the triggers, even if the 

state does not elect to provide EB benefits under that trigger. 20The employment-to-population ratio is the share of the non-institutional, civilian adult population (over age 16) that is employed. The employment-to-population ratio provides useful information in assessing labor market conditions over the business cycle because it takes into account changes in labor market ‘‘slack’’ (insufficient jobs) due to changes in both unemployment 

and labor-force participation. For more information, see Sarah Donovan, ‘‘An Overview of the 

Employment-Population Ratio,’’ Congressional Research Service, May 27, 2015, https://fas.org/ 

sgp/crs/misc/R44055.pdf. 21 U.S. Department of Agriculture, Food and Nutrition Service (FNS), ‘‘Supplemental Nutrition Assistance Program—Guide to Supporting Requests to Waive the Time Limit for Able-Bodied Adults without Dependents (ABAWD),’’ December 2, 2016, https://www.fns.usda.gov/sites/ 

default/files/snap/SNAP-Guide-to-Supporting-Requests-to-Waive-the-Time-Limit-forABAWDs.pdf. 22For example, see: ‘‘SNAP—Guide to Supporting Requests to Waive the Time Limit for AbleBodied Adults without Dependents (ABAWD)’’: https://fns-prod.azureedge.net/sites/default/ 

files/snap/SNAP-Guide-to-Supporting-Requests-to-Waive-the-Time-Limit-for-ABAWDs.pdf. 

were modified only slightly in USDA’s final regulation waivers based on the experience learned during the waiver application and approval process (for example, 

states were allowed to apply to more recent time periods the criteria the Labor Department uses to identify Labor Surplus Areas in order to determine if an area 

qualifies for a waiver). The regulations were proposed by the Clinton Administration 

and fully codified in regulations under the Bush Administration in 2001. In setting 

the waiver criteria, USDA adhered to longtime Labor Department standards to 

identify areas with labor-market weakness. To qualify for the insufficient jobs 

standard, a state must demonstrate that a geographic area (as defined by the state) 

meets specified criteria. 

Federal regulations deem waiver requests that are based on certain criteria as 

‘‘readily approvable’’—meaning USDA approves them once it confirms that the data 

are correct—because the data clearly establish high unemployment in the area. (In 

other words, USDA cannot arbitrarily deny a state that provides adequate documentation showing that the area’s unemployment rate would qualify it for a waiver.) These criteria are: 

• Designation as a Labor Surplus Area—a criterion that several Federal agencies 

use to prioritize government contracts or assistance.18

• An average unemployment rate at least 20 percent above the national average 

over a recent 24 month time period. This standard tracks the Labor Department’s definition of a Labor Surplus Area but can use more recent data. 

• An average 12 month unemployment rate over ten percent. 

In addition, waivers based on unemployment rates that meet the criteria to qualify for additional weeks of Extended Benefits (EB) under the Unemployment Insurance (UI) system may also be approved by USDA.19 States may also make the case 

for a waiver for a given area based on certain other criteria; approval of these waivers is left to the discretion of the Secretary of Agriculture. One example is a low 

and declining employment-to-population ratio,20 a measure that labor economists 

use to capture weak labor markets in areas where there is a notable lack of jobs 

relative to the size of the working-age population. States have used this criterion 

sparingly, and USDA requires states to demonstrate additional evidence of weak 

labor markets for approval, such as a spike in unemployment or a significant company layoff that affects local labor markets.21 Typically, only a handful of rural 

counties and Indian reservations receive waivers under this criterion. 

USDA has not issued major policy changes since the criteria were initially published via guidance in 1996, and state waiver requests have consistently been evaluated according to these criteria. The agency has provided guidance to states on the 

specifics of how to do the required calculations and what information to attach.22

B. Congressional Action to Expand Waivers During the Great Recession 

Waiver criteria have been consistent since 1996, with the exception of temporary 

expansions in response to the Great Recession. In response to the 2007 recession, 

Congress took action that had the effect of temporarily expanding the circumstances 

under which an area could qualify for a waiver. Some have mistakenly portrayed 

174 

23 Chad Stone, ‘‘Congress Should Renew Emergency Unemployment Compensation Before the 

End of the Year,’’ Center on Budget and Policy Priorities, November 21, 2013, http:// 

www.cbpp.org/research/congress-should-renew-emergency-unemployment-compensation-beforethe-end-of-the-year. 24 USDA Memo, ‘‘SNAP—ABAWD Statewide Waivers—New Criteria for Unemployment Insurance Extended Benefits Trigger,’’ January 8, 2009, https://fns-prod.azureedge.net/sites/default/ 

files/snap/ABAWD%20Statewide%20Waivers.pdf. When all states were eligible for both the first 

and second tiers of EUC, USDA required states to be eligible for at least the third tier to qualify 

for a waiver. 25 U.S. Department of Labor, ‘‘Emergency Unemployment Compensation Expired on January 

1, 2014,’’ updated July 1, 2015, http://ows.doleta.gov/unemploy/supp_act.asp. 26 ‘‘SNAP Time Limits: Waivers from the Time Limit Are Back to Historic Norms,’’ Center on 

Budget and Policy Priorities, March 24, 2017, http://www.cbpp.org/sites/default/files/atoms/ 

files/3-24-17fa1.pdf. 27 ‘‘FNS Controls Over SNAP Benefits for Able-Bodied Adults Without Dependents.’’ 

these temporary expansions as a permanent expansion of waiver authority. These 

temporary policies were the only two expansions in waiver criteria since the time 

limit took effect in 1996—and both have ended. 

• In recognition of the Great Recession’s impact on job loss and increased hardship for unemployed workers, Congress enacted the Federal Emergency Unemployment Benefits (EUC) program in 2008. EUC, like the Federal emergency 

unemployment insurance programs enacted in every major recession since 1958, 

was a temporary program that provided additional weeks of UI to qualifying 

jobless workers during periods when jobs were hard to find.23 EUC established 

several ‘‘tiers,’’ with each tier making a specified number of additional weeks 

of UI benefits available to jobless workers in the state, depending on the state’s 

unemployment rate. Workers in states with higher unemployment rates would 

be in higher tiers and hence could receive more weeks of UI benefits. Because 

qualifying for higher tiers of benefits under EUC signified higher unemployment and a lack of jobs, the Bush Administration allowed states to qualify for 

a waiver based on qualifying for at least the second tier of EUC.24

Congress extended and modified the EUC program several times, allowing it 

to operate through January 1, 2014.25 Many states qualified for at least the second tier of EUC through December 2013. As a result, they qualified for waivers 

from the time limit into 2015 (since USDA approved waivers for up to 1 year 

from the date a state qualified for EUC). 

• Meanwhile, the 2009 Recovery Act suspended the time limit nationwide for part 

of 2009 and all of Fiscal Year 2010. States had the option to retain the time 

limit if they offered work opportunities, such as job training and workfare, to 

all individuals subject to the rule. During this time, states didn’t have to request a waiver (though almost every state qualified for a statewide waiver due 

to the exceptionally high levels of unemployment across the country). The suspension of the time limit ended in September 2010. After that, most states continued to qualify for statewide waivers for a few years under EUC-related and 

other, longstanding USDA waiver criteria. 

The requirement that states demonstrate to USDA that an area exceeds a high 

threshold of persistent unemployment in order to qualify for a waiver has limited 

the waivers’ scope. A review of waivers over the last 20 years shows that just over 

1⁄3 of the country (as measured by share of the total population living in waived 

counties) has been waived in a typical year.26 Only during the recession and its 

aftermath was more than 1⁄2 the county temporarily waived from the time limit, and 

that was due to widespread elevated unemployment. Some have mistakenly interpreted the temporary suspension of the time limit in 2009–2010, or the temporary 

expansion of waivers during the aftermath of the recession when job growth remained sluggish for some time, as a permanent expansion of the policy or an Obama 

Administration-led effort to eliminate the time limit. 

C. Why Do States Seek Waivers? 

Individual state decisions to seek a time-limit waiver have varied over time depending on states’ leadership and the economic circumstances at the time of their 

request. Nevertheless, the reasons remain consistent with those put forward by 

USDA in their early guidance. USDA’s Office of Inspector General documented 

states’ motivation in a recent audit of this policy.27 Because states waive the time 

limit to exempt individuals in areas lacking jobs and to ease administrative burden, 

the proposed rule would significantly increase the burden on states and make the 

time limit less reflective of areas lacking jobs, as we explain in greater depth later. 

175 

28 Hours spent in job search can count toward an individual’s required 20 hours per week, 

so long as they constitute less than 1⁄2 of the total number of hours spent in E&T activities. 29 ‘‘The State of American Jobs,’’ Pew Research Center, October 6, 2016, http:// 

www.ledevoir.com/documents/pdf/etude_travail_pewresearch.pdf. 30 U.S. Department of Agriculture, ‘‘Rural America at a Glance: 2017 Edition,’’ November 

2017, https://www.ers.usda.gov/webdocs/publications/85740/eib-182.pdf?v=43054. 

• The time limit provision is very complicated and difficult to administer. 

State administrators have expressed strong concern with the complexity of the 

time-limit provision since its passage in 1996. The rule requires them to track 

individuals with a level of specificity that is inconsistent with how they otherwise operate SNAP and other low-income assistance programs. States find the 

rule to be error-prone and believe that it can increase their payment error rate. 

Some states seek waivers, in part, to ease the administrative burden associated 

with the rule. 

• Waiving the time limit allows states to set a genuine work requirement. 

Under the time limit, states are not required to offer a job or training program 

to every individual (or, for that matter, to any affected individuals), and they 

do not receive sufficient funds through the SNAP Employment and Training 

(E&T) program to do so. In addition, the law limits the types of slots a state 

can provide, making them expensive and out of sync with the needs of much 

of this population. As a result, very few states commit to offering work opportunities to all individuals subject to the time limit. 

Waivers, by contrast, can make meaningful work requirements a reality. A 

state requesting a waiver of the 3 month time limit can still require individuals 

to engage in work-related activities as a condition of receiving benefits through 

the SNAP E&T program. Every state operates a SNAP E&T program, through 

which the state can provide a wide range of employment-related activities to a 

broad range of individuals who are able to work. While there is little evidence 

that SNAP E&T requirements lead to long-term sustainable jobs, they do allow 

a state to require a SNAP participant to engage in work activities in order to 

remain eligible. 

Some states require SNAP participants to participate in a job search program, 

as a way of testing an individual’s willingness to work, to remain eligible. These 

job search programs are relatively inexpensive to operate. But stand-alone job 

search is explicitly prohibited from being a qualifying E&T activity for childless 

adults subject to the time limit. The only activities states are allowed to offer 

to individuals subject to the time limit are job training, education, and workfare 

programs, which typically are too expensive to offer to all such individuals.28

Moreover, this population often isn’t a state’s priority for such investments. 

In short, if a childless adult searches diligently for work but is unable to find 

a job or a slot in a work or training program, he or she loses benefits after 3 

months, despite showing effort and willingness to work. Waivers, by contrast, 

allow states to ensure that they are denying benefits based only on bad conduct, 

not bad luck. 

• States wish to protect individuals living in relatively high unemployment areas. Even in states with relatively low statewide unemployment rates, 

parts of the state may have significantly weaker labor markets, with few jobs 

available. The flexibility that allows states to apply for area waivers recognizes 

that parts of a state may have insufficient jobs for low-income workers. For example, some states may seek waivers for areas where a dominant industry is 

struggling. 

States frequently use waiver authority for rural areas, where about 3⁄4 of 

adults say good jobs are hard to come by where they live.29 Urban areas as a 

whole have fully recovered the jobs lost in the recession, while the number of 

jobs in rural areas continued to remain below pre-recession levels in 2017.30

D. Current Waiver Authority Is Insufficient to Address Needs of Unemployed Workers 

While a waiver offers a necessary, temporary reprieve from the time limit for individuals living in areas with high unemployment, both the waiver authority and the 

underlying time limit are not responsive to the immediate employment challenges 

that many people subject to the rule face, even in areas of more modest unemployment. That, in part, is why USDA’s proposed rule to restrict states’ ability to seek 

waivers is so surprising and ill-informed. Geographic waivers provide needed but inadequate protection for individuals subject to the time limit. While the underlying 

rule exempts some individuals from the time limit (such as people with physical or 

mental conditions and those caring for incapacitated individuals) and states can exVerDate Aug 31 2005 11:16 Jun 14, 2019 Jkt 041481 PO 00000 Frm 00181 Fmt 6621 Sfmt 6621 P:\DOCS\116-02\36188.TXT BRIAN
176 

31Federal regulations identify certain individuals as exempt (see 7 CFR § 273.24(c)) and states 

receive a limited number of individual exemptions they can use to exempt any individual subject 

to the rule, though these are underutilized in most states (see 7 CFR § 273.24(g)). 32Steven Carlson, Dorothy Rosenbaum, and Brynne Keith-Jennings, ‘‘Who Are the Low-Income Childless Adults Facing the Loss of SNAP in 2016?’’ Center on Budget and Policy Priorities, February 8, 2016, http://www.cbpp.org/research/food-assistance/who-are-the-low-incomechildless-adults-facing-the-loss-of-snap-in-2016. 33 ‘‘Food Stamp Employment and Training Program,’’ United States General Accounting Office 

(GAO–3–388), March 2003, p. 17. 34 Congressional Record, 104th Congress, Welfare and Medicaid Reform Act of 1996 (House 

of Representatives—July 18, 1996), page H7905, https://www.congress.gov/crec/1996/07/18/ 

CREC-1996-07-18.pdf. 35 U.S. Department of Agriculture, Food and Nutrition Service (FNS) ‘‘Guidance for States 

Seeking Waivers for Food Stamp Limits,’’ FNS guidance to states, December 3, 1996. 

empt a limited number of additional individuals in unique circumstances, the waiver flexibility allows states the option to fully exempt all individuals who face insufficient job opportunities for reasons other than area unemployment.31 As noted above, 

USDA indicated in their early guidance on waivers that the unemployment rate can 

mask the labor market realities for individuals subject to this rule. 

Many of the individuals subject to the time limit struggle to find employment 

even in normal economic times. States utilize waivers in recognition of this fact, 

which also demonstrates why the proposed rule is so harsh. Those subject to this 

rule are extremely poor, tend to have limited education, and sometimes face barriers 

to work such as a criminal justice history or racial discrimination. While participating in SNAP, childless adults have average incomes of 33 percent of the poverty 

line—the equivalent of about $4,000 per year for a single person in 2019. About a 

quarter have less than a high school education, and 1⁄2 have at most a high school 

diploma or GED.32 SNAP participants subject to the 3 month cutoff are more likely 

than other SNAP participants to lack basic job skills like reading, writing, and basic 

mathematics, according to the Government Accountability Office.33 As we will discuss in much greater depth, an extensive body of research shows why these adults 

likely face much higher unemployment rates than their area’s unemployment rate 

and why the proposed rule would severely curtail waivers in areas where these individuals do not have access to adequate job opportunities. 

A much preferable alternative to the USDA’s proposed rule would have been an 

effort to make it more possible for states to waive the time limit for more individuals who live in areas with insufficient jobs for those subject to its eligibility restriction. Restricting this flexibility would be counter to the intent of the law, inconsistent with more than 2 decades of practice, and would not produce the stated outcomes USDA claims its proposal would achieve. 

Chapter 2: FNS Waiver Policy Has Been Consistent for the Last 22 Years 

A. Current Rules Governing Waivers for Areas with Insufficient Jobs for Individuals 

Subject to the Time Limit 

Congress established that states could waive areas lacking jobs, and U.S. Department of Agriculture (USDA) has established criteria that have been consistent for 

2 decades. When the time limit was being debated in Congress as part of the 1996 

welfare law, its proponents claimed that the proposed rule was not intended to take 

effect in areas where jobs weren’t available. Then-Congressman and co-author of the 

provision John Kasich said, ‘‘It is only if you are able-bodied, if you are childless, 

and if you live in an area where you are getting food stamps and there are jobs 

available, then it applies.’’ 34 The rule was designed to permit states to seek waivers 

in areas where jobs aren’t available. To qualify for a waiver, states must provide 

detailed evidence of high unemployment in local areas, in accordance with rigorous 

requirements set by USDA. USDA has consistently used the same criteria to define 

high unemployment since the late 1990s. 

The Federal law gives states the option to request a waiver of the time limit if 

they can document that a given geographic area has an insufficient number of jobs 

(or has an unemployment rate over ten percent). The standards that define how a 

state may document ‘‘insufficient jobs’’ for individuals subject to the time limit were 

first outlined in FNS guidance issued in December 1996.35 In the guidance, USDA 

offered several reflections on its understanding of Congressional intent at the time. 

First, USDA shared its belief that Congress understood that this group of individuals could find it especially challenging to find permanent employment and that 

waivers are intended to recognize this problem: 

USDA believes that the law provided authority to waive these provisions in 

recognition of the challenges that low-skilled workers may face in finding and 

177 

36 Ibid. 37 Ibid. 38 U.S. Department of Labor, ‘‘Labor Surplus Area: Frequently Asked Questions,’’ updated August 21, 2015, https://www.doleta.gov/programs/lsa_faq.cfm. 39The EB program has criteria in law under which unemployed workers in a state are eligible 

to receive extended unemployment benefits, and states can opt to offer EB benefits under certain additional criteria. (For more information, see ‘‘Conformity Requirements for State UI 

Laws,’’ Department of Labor, https://workforcesecurity.doleta.gov/unemploy/pdf/uilaws_ extended.pdf.) Because these unemployment criteria (known as ‘‘triggers’’) establish high unemployment, a state is eligible for a waiver if it meets the criteria under the triggers, even if the 

state does not elect to provide EB benefits under that trigger. 40The employment-to-population ratio is the share of the non-institutional, civilian adult population (over age 16) that is employed. The employment-to-population ratio provides useful information in assessing labor market conditions over the business cycle because it takes into account changes in labor market ‘‘slack’’ (insufficient jobs) due to changes in both unemployment 

and labor-force participation. For more information, see Sarah Donovan, ‘‘An Overview of the 

Continued 

keeping permanent employment. In some areas, including parts of rural America, the number of employed persons and the number of job seekers may be far 

larger than the number of vacant jobs. This may be especially so for persons 

with limited skills and minimal work history. 

In addition, the guidance provided key background on some of the policy that 

USDA seeks to restrict in the NPRM. With respect to how states can set or define 

the area within the state that it seeks to waive, USDA said, ‘‘USDA will give states 

broad discretion in defining areas that best reflect the labor market prospects of 

program participants and administrative needs.’’ 36 The guidance also recognized 

that the statute seeks to identify whether or not there are sufficient jobs for individuals subject to the time limit: 

‘‘The guidance that follows offers some examples of the types and sources of 

data available to states as they consider waiver requests for areas with insufficient jobs. Because there are not standard data or methods to make the determination of the sufficiency of jobs, the list that follows is not exhaustive. States 

may use these data sources as appropriate, or other data as available, to provide evidence that the necessary conditions exist in the area for which they intend the waiver to apply. The absence of a particular data source or approach 

(for example, data or statistics compiled by a university) is not meant to imply 

that it would not be considered by USDA if requested by a state.’’ 37

These criteria were modified only slightly in USDA’s final regulation on waivers 

based on the experience learned during the waiver application and approval process 

(for example states were allowed to apply to more recent time periods the criteria 

the Labor Department uses to identify Labor Surplus Areas in order to determine 

if an area qualifies for a waiver.) The regulations were proposed by the Clinton Administration and fully codified in regulations under the Bush Administration in 

2001. In setting the waiver criteria, USDA adhered to long-time Labor Department 

standards to identify areas with labor-market weakness. To qualify for the insufficient jobs standard, a state must demonstrate that a geographic area (as defined 

by the state) meets specified criteria. 

Federal regulations deem waiver requests that are based on certain criteria as 

‘‘readily approvable’’—meaning USDA approves them once it confirms that the data 

are correct—because the data clearly establish high unemployment in the area. (In 

other words, USDA cannot arbitrarily deny a state that provides adequate documentation showing that the area’s unemployment rate would qualify it for a waiver.) These criteria are: 

• Designation as a Labor Surplus Area—a criterion that several Federal agencies 

use to prioritize government contracts or assistance.38

• An average unemployment rate at least 20 percent above the national average 

over a recent 24 month time period. This standard tracks the Labor Department’s definition of a Labor Surplus Area but can use more recent data. 

• An average 12 month unemployment rate over ten percent. 

In addition, waivers based on unemployment rates that meet the criteria to qualify for additional weeks of Extended Benefits (EB) under the Unemployment Insurance (UI) system may also be approved by USDA.39 States may also make the case 

for a waiver for a given area based on certain other criteria; approval of these waivers is left to the discretion of the Secretary of Agriculture. One example is a low 

and declining employment-to-population ratio,40 a measure that labor economists 

178 

Employment-Population Ratio,’’ Congressional Research Service, May 27, 2015, https://fas.org/ 

sgp/crs/misc/R44055.pdf. 41 U.S. Department of Agriculture, Food and Nutrition Service (FNS), ‘‘Supplemental Nutrition Assistance Program—Guide to Supporting Requests to Waive the Time Limit for Able-Bodied Adults without Dependents (ABAWD),’’ December 2, 2016, https://www.fns.usda.gov/sites/ 

default/files/snap/SNAP-Guide-to-Supporting-Requests-to-Waive-the-Time-Limit-forABAWDs.pdf. 42For example, see: U.S. Department of Agriculture, Food and Nutrition Service (FNS), ‘‘Supplemental Nutrition Assistance Program—Guide to Supporting Requests to Waive the Time 

Limit for Able-Bodied Adults without Dependents (ABAWD),’’ December 2, 2016, https:// 

www.fns.usda.gov/sites/default/files/snap/SNAP-Guide-to-Supporting-Requests-to-Waive-theTime-Limit-for-ABAWDs.pdf. 43 2019 NPRM, p. 8. 44 2019 NPRM, p. 16. 

use to capture weak labor markets in areas where there is a notable lack of jobs 

relative to the size of the working-age population. States have used this criterion 

sparingly, and USDA requires states to demonstrate additional evidence of weak 

labor markets for approval, such as a spike in unemployment or a significant company layoff that affects local labor markets.41 Typically, only a handful of rural 

counties and Indian reservations receive waivers under this criterion. 

USDA has not issued major policy changes since the criteria were initially published via guidance in 1996, and state waiver requests have consistently been evaluated according to these criteria. The agency has provided guidance to states on the 

specifics of how to do the required calculations and what information to attach.42

B. Department Claims to Return to Original Policy Intent and That Current Waiver 

Standards are Inconsistent 

In the 2019 NPRM, the Department declared its commitment to ‘‘implement 

SNAP as Congress intended,’’ 43 implying that waiver policy has diverged significantly from the original policy set in the 1996 welfare reform law. It also claims 

that the rule will ‘‘improve consistency across states,’’ 44 but fails to define what the 

current inconsistency is, why the current standards are causing such inconsistency, 

does not provide any evidence to support its claim of inconsistency, or explain why 

and how it is a problem. Two possible interpretations of the ‘‘inconsistency’’ claim 

are that current waiver standards do not apply consistently to all states, or that the 

current standards produce inconsistent waived areas across states. Neither of these 

claims holds up to scrutiny. 

FNS Waiver Criteria Have Not Changed Significantly Since 1996 

The Department’s suggestion that waiver policy has deviated from Congressional 

intent suggests that either the Department now knows something that it did not 

22 years ago when it put forward guidance to implement the law or that the final 

regulations deviated from the original guidance set in December 1996. 

On the first count, the Department provided no information or evidence from legislative history that would suggest that its knowledge or understanding of Congressional intent has improved since it issued its first guidance on waiver policy just 

a few short months after the welfare law passed. In fact, the NPRM does not provide any reference to legislative history to help reviewers understand why current 

policy is out of sync with the goal of the statute. It is impossible to respond to the 

Department’s reasoning other than to provide the available legislative history as we 

have in Chapter 1 (Overview of Waivers From the Three-Month Time Limit—Their 

Purpose and History) which explains how legislative history runs counter to the Department’s assertions. 

Similarly, we observe no significant policy shift in the waiver policy that the Department originally set forth in its December 1996 guidance from current policy. In 

fact, comparing waiver standards from 1996 to the current standards can provide 

insight into how much waiver policy has significantly changed over the past 2 decades. The best evidence for this comes from FNS’ 1996 guidance, which describes 

in detail the waiver criteria that were available to states at the time. Table 2.1 

below compares the key waiver criteria included in FNS’ December 1996 guidance 

to the current criteria described in FNS’ December 2016 guidance (which is the most 

recent articulation of the rules set forth in the 2001 Federal regulations). 

179 

45 U.S. Department of Agriculture, Food and Nutrition Service (FNS) ‘‘Guidance for States 

Seeking Waivers for Food Stamp Limits,’’ FNS guidance to states, December 3, 1996. 46 66 Fed. Reg., No. 11, 4438 (January 17, 2001). 47 ‘‘SNAP—Guide to Supporting Requests to Waive the Time Limit for Able-Bodied Adults 

without Dependents (ABAWD),’’ FNS guidance issued December 2, 2016, https://fnsprod.azureedge.net/sites/default/files/snap/SNAP-Guide-to-Supporting-Requests-to-Waive-theTime-Limit-for-ABAWDs.pdf. 48 66 Fed. Reg., No. 11, 4438 (January 17, 2001). 49 U.S. Department of Agriculture, Food and Nutrition Service (FNS) ‘‘Guidance for States 

Seeking Waivers for Food Stamp Limits,’’ FNS guidance to states, December 3, 1996. 50 ‘‘ABAWD Waivers—New Method for Calculating Average Unemployment Rates,’’ FNS 

Northeastern Region Food Stamp Regional Letter, April 28, 2004. 51 U.S. Department of Agriculture, Food and Nutrition Service (FNS), ‘‘Supplemental Nutrition Assistance Program—Guide to Supporting Requests to Waive the Time Limit for Able-BodContinued 

Table 2.1 

FNS Waiver Policy Has Been Consistent Since 1996 

December 

1996 FNS 

Guidance 45

January 

2001 Final 

Rule 46

December 

2016 FNS 

Guidance 47

Waiver Eligibility Criteria 

Labor Surplus Area Designation (LSA) Yes Yes Yes 

LSA-Like: 24 month average unemployment rate 20 percent 

above the national average using more current data than 

LSA 

No Yes Yes 

Qualification for Extended Unemployment Benefits Yes Yes Yes 

12 month average unemployment rate over ten percent Yes Yes Yes 

3 month average unemployment rate over ten percent Yes Yes Yes 

Historical seasonal unemployment rate over ten percent Yes Yes Yes 

Employment-to-Population Ratios Yes Yes Yes 

Demonstration of lack of jobs in declining occupations or industries Yes Yes Yes 

Demonstration of lack of jobs in an area Yes Yes Yes 

Other Waiver-Eligibility Policy 

Combining data for geographic and economic regions Yes Yes Yes 

Estimating unemployment rates for Tribal lands Yes Yes Yes 

Requesting 2 year waivers No No Yes 

Table 2.1 demonstrates that the waiver criteria set in the 1996 welfare reform law 

have remained remarkably consistent over the past 2 decades. For example, FNS’ 

1996 guidance indicated that high unemployment areas can be waived by being designated as Labor Surplus Areas (LSA), qualifying for extended unemployment benefits, or having average unemployment rates of over ten percent. These are the same 

criteria described in current FNS guidance. Moreover, criteria that are seldom used 

by states, such as demonstrating historical seasonal unemployment or a lack of jobs 

in declining occupations are described in the 1996 guidance and remain the same 

today. The meaningful change was to allow states to use more recent unemployment 

data when considering whether an area met the LSA criteria of having average unemployment rates at least 20 percent above the national average for a recent 24 

month period. This variation of the LSA criteria also permits areas to qualify with 

24 month average unemployment rates below six percent. This criterion is informally known as ‘‘LSA-like.’’ Using more recent unemployment data allows for a 

more current assessment of the unemployment situation of an area and is an enhancement of the LSA criteria, not a significant change. This was added in the early 

2000s and is codified in current Federal regulations.48

Similarly, the 1996 guidance included other waiver policies such as the ability to 

combine data and estimating unemployment rates for Tribal lands, urging states to 

‘‘consider areas within, or combinations of counties, cities and towns’’ and to ‘‘consider the particular needs of rural areas and Indian reservations.’’ 49 These policies 

remain in place in current guidance, with small changes made over the years. 

The small changes that have occurred are largely refinements of the original criteria, not major additions to waiver policy. For example, FNS guidance issued in December 2004 revised the method for calculating average unemployment rates over 

24 month periods.50 Current FNS guidance also provides specific instructions on 

how to round 24 month average unemployment rates, and a standard methodology 

for estimating unemployment rates for Native American reservations.51 FNS also ofVerDate Aug 31 2005 11:16 Jun 14, 2019 Jkt 041481 PO 00000 Frm 00185 Fmt 6621 Sfmt 6621 P:\DOCS\116-02\36188.TXT BRIAN
180 

ied Adults without Dependents (ABAWD),’’ December 2, 2016, https://www.fns.usda.gov/sites/ 

default/files/snap/SNAP-Guide-to-Supporting-Requests-to-Waive-the-Time-Limit-forABAWDs.pdf. 52 ‘‘FSP—2-Year Approval of Waivers of the Work Requirements for ABAWDs under 7 CFR 

273.24,’’ FNS memorandum issued February 3, 2006. 53 66 Fed. Reg., No. 11, 4438 (January 17, 2001). 54 Ibid. 55 NPRM, p. 7. 

fered states ‘‘the option of 2 year waiver approvals’’ in a February 2006 memorandum; while this was an addition to waive policy at the time, it was not a major 

revision of waiver standards—the criteria for 2 year waivers are more restrictive 

than those for shorter waivers.52 (See Chapter 8 for more.) 

The final rule published in January 2001 offers clear evidence that the Department at the time intended to codify the waiver policies from its 1996 guidance, so 

that they would become a consistent set of rules that states use to determine their 

waiver eligibility in the future. In the final rule, the Department discussed the comments issued in response to its NPRM on the waiver policy, and why this influenced 

its codification of waiver criteria. It acknowledged that it did not include the 1996 

guidance in its initial regulations, not because it deviated from the Department’s 

intent, but because ‘‘[the guidance] was extensive and detailed.’’ 53 The Department 

also explained that it ‘‘received several comments suggesting [the Department] include all or some of the guidance in the regulations. Commenters argued that unless 

the guidance is incorporated into the regulations, a subsequent Administration 

could abolish it without public comment. Based on these comments, [it] decided to 

incorporate some of the more pertinent aspects of the guidance into the regulation. 

More specifically, [it] modified the regulations at 7 CFR 273.24(f) to include a nonexhaustive list of the kinds of information a state agency may submit to support 

a claim of ten percent unemployment or ‘lack of sufficient jobs.’ ’’ 54 The final rule 

goes on to list the same waiver eligibility criteria described in Table 2.1 as part of 

the December 2016 guidance, and shows that Department recognized at the time 

that a consistent and predictable waiver policy would be an essential asset to states 

in the future. 

This evidence demonstrates that current waiver criteria are not wildly out of step 

with the original intent of waiver policy at its inception. The original guidance set 

the flexibility that states currently have in waiving areas, contrary to the Department’s claim in the proposed rule that they use their flexibility ‘‘in a way that was 

not likely foreseen.’’ 55

Furthermore, the consistency in waiver policy over the decades has been important for states, which have relied on it for 20 years. The Department’s claim that 

its proposed rule will allow ‘‘States to reasonably anticipate whether it would receive approval’’ ignores the reality that current waiver policy already accomplishes 

this goal. In reality, the rule would make it harder for states to obtain waivers and 

would disrupt their long-standing waiver implementation procedures. 

The Proposed Rule Does Not Provide Evidence of Inconsistency in Current Waiver 

Standards 

As noted earlier, the Department does not explain or justify in the rule its implication that current waiver standards are inconsistent, and reasonable interpretations of what it meant do not hold up to scrutiny. For example, the Department may 

have meant that there is not a consistent set of waiver standards that apply to all 

states. This is not the case, as waiver standards apply uniformly to all states. States 

might use different criteria to show their eligibility for waivers; for example, a state 

with unemployment well above ten percent might request a waiver based on the ten 

percent threshold, whereas another state with rapidly rising unemployment might 

request a waiver based on qualifying for extended unemployment benefits. The fact 

that states use different criteria reflects differences in their demographic composition and economies, among other factors. It does not mean, as the Department 

might be implying, that states do not have the option of using any of the criteria 

to show their waiver eligibility, particularly as their local economic conditions 

change over time. 

Over the past 2 decades, FNS has regularly updated its guidance to states to inform them of their options as the economy changed. One of the strengths of the current rules and USDA’s application of them is the extraordinary consistency with 

which USDA applied the rules across the years and states. Until 2017, states could 

predict with extreme accuracy whether the Department would approve a waiver 

based on the listed criteria and guidance. It was only after the current Administration took office that USDA began denying waivers that it had long approved—such 

as no longer approving 2 year waivers for areas that met the standards set in guidVerDate Aug 31 2005 11:16 Jun 14, 2019 Jkt 041481 PO 00000 Frm 00186 Fmt 6621 Sfmt 6621 P:\DOCS\116-02\36188.TXT BRIAN
181 

56 U.S. Department of Agriculture, Food and Nutrition Service (FNS), ‘‘Supplemental Nutrition Assistance Program—Guide to Supporting Requests to Waive the Time Limit for Able-Bodied Adults without Dependents (ABAWD),’’ December 2, 2016, https://www.fns.usda.gov/sites/ 

default/files/snap/SNAP-Guide-to-Supporting-Requests-to-Waive-the-Time-Limit-forABAWDs.pdf. 

ance or for areas eligible under the Employment-to-Population ratio.56 While there 

were not a lot of these types of requests historically, it was the new Administration 

that introduced uncertainty into the process. Similarly, waiver requests that would 

typically be approved in 1 to 3 months can now take upwards of 6 months to approve. This has resulted in USDA sometimes not approving waivers until after the 

requested start date. FNS regional and national office staff have not known what 

would and would not be approved or when. The political leadership at USDA has 

introduced uncertainty and inconsistency in the review and approval process. Moreover, they have been inconsiderate of states’ need for certainty and predictability in 

order to implement waivers after approval. 

If the Department meant instead that the current waiver standards do not 

produce consistent waived areas across states, then it is making an unreasonable 

argument. The only inconsistency across states is the Department’s own application 

of the flexibility afforded to it, not in USDA’s application of the rules (until recently). It is incumbent upon USDA to define and demonstrate the inconsistency it 

observes given that this argument is a core element of its reason to re-regulate 

these long-standing rules. 

The evidence shows how little of the Department’s proposed rule is based on a 

clear knowledge of the waiver policy’s history and an intimate understanding of the 

waiver standards’ application to states. This clearly demonstrates the brittle nature 

of the Department’s justifications of the changes to current waiver policy contained 

in the proposed rule. 

Chapter 3: Setting a Floor for Waivers For Areas With 20 Percent Above 

National Unemployment Is Inconsistent With Congressional Intent and 

Would Be Harmful to Vulnerable Individuals 

The most significant change of the proposed rule would drastically roll back waivers of the time limit by requiring states to show that areas meet an unemployment 

rate threshold of 20 percent above the national average (which the Department of 

Agriculture, or the Department, and we will refer to as the ‘‘20 percent standard’’) 

and, if the 20 percent standard is below a specific threshold, meet this specific 

threshold, referred to as the ‘‘unemployment rate floor’’ to qualify for a waiver. We 

believe this proposal is out of sync with the goal and purpose of the underlying legislation. Furthermore, the Department did not discuss whether it considered a substantial body of relevant research that contradicts the claims it made in support of 

this change and provided little to no evidence to back up its proposal, making it difficult for us to comment on the process the Food and Nutrition Service (FNS) used 

to develop this regulation. Below we discuss each of the following reasons in detail 

that explain the flaws in this process: 

• This proposal is contrary to Congressional intent, which clearly was to allow 

states flexibility to use a variety of metrics to demonstrate that the population 

subject to the time limit does not have access to enough jobs. Congress has rejected past proposals to impose an unemployment rate floor and otherwise restrict the current waiver criteria. 

• Considerable evidence shows that the adults without dependent children potentially subject to the rule face overlapping labor market disadvantages, and 

therefore experience significantly higher unemployment rates than the general 

unemployment rate for their area. Because an area’s overall unemployment rate 

overstates job availability for the individuals subject to the time limit, imposing 

an unemployment rate floor would disqualify many areas from eligibility for a 

waiver where childless SNAP participants have very few job opportunities. The 

statute clearly gives states that want to the ability to waive the time limit for 

some or all individuals in areas where there aren’t enough jobs to employ these 

individuals. 

• The Department misleadingly cites the unemployment rate floor used by the 

Department of Labor in establishing Labor Surplus Areas (LSAs) to support the 

proposal, without recognizing that LSAs are meant for different purposes, and 

that LSAs also include an unemployment rate ceiling. 

• The Department uses the concept of a ‘‘natural rate of unemployment’’ to support the proposed unemployment rate floor of seven percent, which is a misinterpretation of a macroeconomic concept that is not a fixed or precisely identiVerDate Aug 31 2005 11:16 Jun 14, 2019 Jkt 041481 PO 00000 Frm 00187 Fmt 6621 Sfmt 6621 P:\DOCS\116-02\36188.TXT BRIAN
182 

57 H.R. Report 104–651, Welfare and Medicaid Reform Act of 1996, https://www.congress.gov/ 

congressional-report/104th-congress/house-report/651. 58Food and Nutrition Act, 7 U.S.C. § 2015(o)(4). This language is identical to the language 

in P.L. 104–193, PRWORA. 

fiable unemployment rate. Furthermore, the Department then suggests a significantly higher unemployment rate floor than what it states the natural rate 

is without explaining how the natural rate relates to the proposed unemployment rate floor of seven percent. This lack of explanation for choosing the substantially higher rate of seven percent demonstrates how this specific unemployment rate floor was chosen arbitrarily. 

• While no specific rate of unemployment would properly reflect these individuals’ 

circumstances, evidence shows that seven percent unemployment specifically is 

too high, given that many of these individuals are often in groups that experience unemployment rates significantly above that level and they often face barriers to employment. 

• The proposal would fail to adequately provide states with waiver coverage during times of rising unemployment, as the combination of the high unemployment rate with the lengthy 24 month lookback would preclude many states with 

rising unemployment from eligibility. The Department lacked transparency in 

not referencing whether they examined the potential impact of this proposal at 

other times in the business cycle besides the current moment. 

• The Department attempts to support its proposed unemployment rate floor by 

explaining that such a floor would decrease the share of who it refers to as 

‘‘ABAWDs’’ living in a waived area. This justification ignores Congressional intent and lacks transparency in the underlying assumptions and methodology 

used to estimate this metric. 

• The Department also sought feedback on alternative unemployment rate floors 

of six and ten percent, which are both unworkable and an inappropriate reading 

of the statute. Its proposal of these alternate floors demonstrates the arbitrariness of the proposed seven percent floor, but also shows that it is impossible 

to designate a specific unemployment rate floor that would adequately interpret 

the law by accurately reflecting jobs available to childless adults. 

In proposing an unemployment rate floor for waivers based on the 20 percent 

standard, the Department ignores the intent of Congress and uses misleading justifications with no transparent evidence to support its claims. While the current 20 

percent standard may not perfectly represent areas that lack jobs for childless 

adults because the overall unemployment rate masks divergent labor market opportunities for sub-groups such as these individuals, the proposed rule would only exacerbate the shortcomings of current policy. 

A. Unemployment Rate Floor Proposal Inconsistent With Congressional Intent 

When Congress established the 3 month time limit in the Personal Responsibility 

and Work Opportunity Reconciliation Act of 1996 (PRWORA), Public Law 104–193, 

it established that a state may seek a waiver for a geographic area. Congress gave 

states this authority in recognition that individuals may not have success in finding 

a job if there are limited job opportunities. When the House Committee on Budget 

reported the original bill, the report stated: 

The Committee understands that there may be instances in which high unemployment rates in all or part of a state or other specified circumstances may 

limit the jobs available for able-bodied food stamp participants between 18 and 

50 years with no dependents. Therefore the Secretary, upon request from a 

state, is provided with the authority to waive job requirements in these circumstances or if unemployment rates are above ten percent.57

Congress created waiver authority to enable states to waive areas with ‘‘high unemployment rates’’ or ‘‘otherwise specific circumstances,’’ indicating that a range of 

circumstances may be indicative of depressed labor market conditions. The welfare 

reform law established that a state could seek a waiver for an area if it: ‘‘(i) has 

an unemployment rate of over ten percent; or (ii) does not have a sufficient number 

of jobs to provide employment for the individuals.’’ 58 (Herein, as with the current 

regulations, we will use ‘‘area’’ to refer to geographic areas, which generally refers 

to areas for which states generally seek waivers, such as counties, cities, towns, 

Tribal areas, or metropolitan areas.) 

Congress therefore created two distinct categories to establish the circumstances 

under which a state can request a waiver: 

183 

59 USDA, ‘‘Guidance for States Seeking Waivers for Food Stamp Limits,’’ December 3, 1996. 60 66 Fed. Reg., No. 11, 4438 (January 17, 2001), p. 4462. https://www.federalregister.gov/d/ 

01-1025/p-205. 

• The first criterion establishes that an area with an unemployment rate of ten 

percent may qualify for a waiver. The unemployment rate measures the share 

of the labor force that is actively looking for work. Historically, a ten percent 

unemployment rate is an indicator of severe labor market distress, such as during an economic downturn. Since the Bureau of Labor Statistics (BLS) began 

publishing monthly unemployment rates in 1948, the national unemployment 

rate has equaled or exceeded ten percent only during the 1981–1982 recession 

and during the Great Recession of 2007–2009. Congress recognized that a local 

area with such a high unemployment rate likely would not offer adequate job 

opportunities so that people who are subject to the time limit could find work. 

With such high unemployment, even the most readily employable jobseekers 

will likely struggle to find work, and those who are more disadvantaged will 

face even more challenges. States that prefer to waive only areas with extremely high unemployment rates can also request waivers based on this criterion. 

• The second criterion is focused on measuring employment opportunities for the 

specific individuals affected by the time limit. Congress recognized that while 

useful for measuring the health of a local labor market, the unemployment rate 

may not give a complete picture of job availability for all workers in that area, 

particularly for individuals facing labor market disadvantages. An area may not 

have a sufficient number of jobs because the share of jobseekers who are out 

of work is relatively high, as indicated by the employment rate. Even with a 

low unemployment rate, however, there can be instances where there aren’t 

enough jobs to provide employment for specific individuals or groups. Even if 

there are enough jobs in number to match the number of jobseekers, the individuals’ skills might not match the requirements of the available jobs, the jobs 

may be inaccessible due to geographic or transit limitations, or employers may 

discriminate against some jobseekers based on their race, work history, disability, or other characteristics, for example. 

In its original interpretation, the Department recognized that Congress intended 

for the ‘‘insufficient jobs’’ criterion to include a range of metrics that are targeted 

towards the individuals subject to the time limit. The Department published guidance on December 3, 1996, which stated: 

The statute recognizes that the unemployment rate alone is an imperfect 

measure of the employment prospects of individuals with little work history and 

diminished opportunities. It provides states with the option to seek waivers for 

areas in which there are not enough jobs for groups of individuals who may be 

affected by the new time limits in the Food Stamp Program. 

To some extent, the decision to approve waivers based on an insufficient number of jobs must be made on an area-by-area basis. Examples of such situations 

include areas where an important employer has either relocated or gone out of 

business. In other areas there may be a shortage of jobs that can be filled by 

persons with limited skills and work experience relative to the number of persons seeking such jobs.59

The Department therefore originally (in 1996) interpreted the intent of Congress 

in creating the second category for waiver authority as a recognition of the shortcomings of the unemployment rate for measuring job opportunities for the individuals subject to the time limit, and established that it could use flexibility in determining whether a state demonstrates a lack of jobs. In response to comments, when 

preparing the original final rule, the Department balanced the need to provide specific guidance that would be codified in regulation so that it would remain consistent 

across subsequent Administrations with the need to retain the flexibility that the 

Department recognized that Congress had created in its original lawmaking. The 

final rule stated: 

Based on these comments, we have decided to incorporate some of the more 

pertinent aspects of the guidance into the regulation. More specifically, we have 

modified the regulations at 7 CFR 273.24(f) to include a non-exhaustive list of 

the kinds of information a state agency may submit to support a claim of ten 

percent unemployment or ‘lack of sufficient jobs.’ 60

FNS’ original (2001) interpretation therefore was clear that in providing guidance 

about specific methods states can use to demonstrate a lack of jobs in an area, it 

184 

61 Audrey Breitwieser, Ryan Nunn, and Jay Shambaugh. ‘‘The recent rebound in prime-age 

labor force participation,’’ Brookings Institution, August 2, 2018. https://www.brookings.edu/ 

blog/up-front/2018/08/02/the-recent-rebound-in-prime-age-labor-force-participation/. 

was not precluding states from using other data or metrics to demonstrate insufficient jobs, given that it is a concept not easily shown by any one numeric quantity 

or metric. 

By proposing an unemployment rate floor, the Department is proposing to restate 

the waiver criteria in a manner that is inconsistent with the intent of the statute. 

Currently, states can waive areas with insufficient jobs to employ a specific, more 

disadvantaged, population. The current 20 percent standard already has limitations 

in its ability to reflect jobs available for individuals subject to the time limit, who 

likely experience much higher unemployment rates than the overall unemployment 

rate in their area. As we discuss in detail below, areas with unemployment rates 

that are 20 percent above the national average may still lack jobs for those with 

barriers to unemployment. As we will explain, there are several reasons why current aspects of the 20 percent standard in the context of the current regulations 

allow for a greater ability to demonstrate a lack of sufficient jobs than the proposed 

regulation would allow. The proposed regulations would therefore significantly worsen the problem with the current 20 percent standard as a measure of ‘‘insufficient 

jobs.’’ 

First, under the current regulation, an area with elevated unemployment compared to national unemployment can qualify for a waiver, without meeting a specific 

unemployment rate standard. Defining high unemployment at a relative level rather 

than a specific unemployment rate threshold allows for greater consideration of 

trends such as those in labor force participation, which may affect low unemployment rates, especially relevant for disadvantaged groups. If workers who are not 

employed stop looking for work and therefore exit the labor force, measures of labor 

force participation will decline. Because the unemployment rate measures the share 

of the labor force that is not employed but is actively seeking work, lower labor force 

participation may be a signal of weak labor markets that is not reflected in the unemployment rate (for example, if discouraged workers stop looking for work). 

Overall labor force participation has fallen over the last 2 decades, including particularly sharply during the Great Recession, and only began rebounding in about 

2015. Labor force participation fell sharply among prime-age workers (thus less affected by population aging and retirement) with lower educational attainment from 

2000 to 2015 and in 2018 were still below 2000 levels.61

Lower unemployment rates are thus less indicative of strong labor markets in recent years than in the past, and particularly so for a group that tends to fare worse 

in the labor market, such as those with lower levels of education. The 20 percent 

standard, which currently does not have a floor, relies on unemployment rates, 

which are an imperfect proxy of jobs available for this population. Because the current unemployment rate threshold needed to qualify for a waiver varies along with 

national trends, however, the current standard gives more flexibility to capture 

those trends. Not having a specific unemployment rate floor therefore allows for the 

20 percent standard to better capture insufficient jobs than it would with a specific 

floor. In addition, currently states have the ability to group together counties to better represent local labor market opportunities, which the proposed rule would also 

restrict. (We discuss these changes in more detail in Chapter 5.) This flexibility also 

helps mitigate some of the shortcomings in the current 20 percent standard. 

Second, the Department is also proposing to eliminate other criteria existing in 

current regulations that can serve as an alternative to measuring ‘‘insufficient jobs’’ 

in cases where the 20 percent standard does not adequately reflect job opportunities. 

In the context of these changes, the 20 percent standard takes on increasing importance as one of the sole methods to demonstrate a lack of sufficient jobs. The effect 

of these proposed changes largely results in a requirement that states demonstrate 

a specific unemployment rate threshold to qualify for a waiver under the ‘‘insufficient jobs’’ criterion, when Congress expressly intended for this criterion to encompass a broader range of metrics. 

The Department proposes to eliminate most of the remaining alternatives to 

metrics based on the unemployment rate that current regulations at 7 CFR 

§ 273.24(f)(2)(ii) allow, such as the elimination of the option to demonstrate a ‘‘low 

and declining employment-population ratio’’ or to demonstrate declining industries. 

The Department would also sharply reduce the ability of states to request waivers 

for groups of neighboring counties, which may be useful in cases where the unemployment rate is a particularly poor proxy for labor market opportunities for individuals subject to the time limit. (We discuss the changes to employment-population 

ratio and other means of showing a lack of sufficient jobs in Chapter 4, and changes 

185 

62 NPRM, p. 992. 63Personal Responsibility and Work Opportunity Reconciliation Act of 1996, P.L. 104–193, 

§ 403(b)(6), https://www.congress.gov/104/plaws/publ193/PLAW-104publ193.pdf. 

to grouping in Chapter 5.) With these changes, for the most part an area could only 

qualify for a waiver by demonstrating that it has a 12 month unemployment rate 

average of at least ten percent, a 2 year unemployment rate of at least seven percent, or that it qualifies for extended unemployment insurance benefits, the eligibility for which is based on a recent 3 month insured or total unemployment rate. 

The proposal does allow for states to demonstrate ‘‘exceptional circumstances,’’, 

but even then suggests that it must support this claim with evidence, such as of 

a ten percent unemployment rate: ‘‘the request must demonstrate that the exceptional circumstance has caused a lack of sufficient number of jobs, such as data from 

the BLS or a BLS-cooperating agency that shows an area has a most recent 3 month 

average unemployment rate over ten percent.’’ 62 Under the proposed rule, states 

will largely be limited to demonstrating that an area meets a specific unemployment 

rate threshold to qualify for a waiver under the ‘‘insufficient jobs’’ category of waivers, which does not align with the intent of Congress to provide for multiple metrics 

under this category. 

Congress regularly includes specific unemployment rate thresholds for policy purposes when that is its intent. Congress included ten percent unemployment as one 

of the criteria to qualify for a waiver of SNAP’s 3 month time limit, as stated above. 

Similarly, in the same legislation, Public Law 104–193, Congress created a specific 

definition of a ‘‘needy state’’ under the TANF program, which allows states additional weeks of job search and readiness. One of the qualifications for a ‘‘needy 

state’’ was a 3 month unemployment rate of at least 6.5 percent that exceeds 110 

percent of the unemployment rate for the same period in either of the last 2 years.63

Congress clearly understood that unemployment rates may be an appropriate 

threshold in some instances, but chose to include a criterion that was more loosely 

defined and allowed for alternative economic measures to demonstrate a lack of jobs. 

Congress also chose to allow waivers based on economic circumstances that reflect 

jobs available for a targeted population, the individuals subject to the time limit. 

Had Congress intended to allow states to qualify for waivers only based on unemployment rates, it would have only included waiver criteria with those unemployment rate parameters, rather than including the second criteria targeted towards 

childless adult SNAP participants. 

In the original final rule, published in 2001, the Department made clear that they 

interpreted the ‘‘lack of sufficient jobs’’ as encompassing a broad range of metrics 

and not exclusively tied to demonstrating a high unemployment rate. By proposing 

a specific unemployment rate threshold for the 20 percent standard, reducing the 

ability of states to group together areas, and eliminating most of the alternative criteria that would let states use alternative information, the Department has substantially changed its interpretation of how states can demonstrate that an area lacks 

jobs for the individuals subject to the time limit. In practice, except during times 

when states qualify for extended benefits, under the proposed regulation, states 

would largely be limited to showing that an area has a seven percent unemployment 

rate over 2 years to show it lacks enough jobs to employ people subject to the time 

limit. The Department did not attempt to demonstrate that a specific unemployment 

rate threshold shows an area lacks jobs for these individuals, instead discussing the 

unrelated fact that the proposal would have the effect of narrowing the number of 

waived areas, which we explain below. The Department therefore provides no evidence that the changes in the rulemaking are aligned with the intent of the statute 

to allow waivers in areas lacking sufficient jobs, a broader concept than areas meeting specific unemployment rate thresholds. 

Congress Recently Rejected Proposals to Limit Current Waiver-Approval Standards 

Congress also has rejected attempts to narrow waiver-approval criteria to impose 

an unemployment rate floor for the ‘‘20 percent standard.’’ H.R. 2, the House Agriculture Improvement Act of 2018, as passed by the House on June 21, 2018, included a restriction similar to the Administration’s proposal, requiring an area to 

have an unemployment rate of at least seven percent to qualify based on having a 

2 year unemployment average greater than the national average. The Senate did 

not include such a restriction on waivers. The Conference Committee adapted the 

Senate’s approach, which then passed and was signed into law. As Rep. Marcia 

Fudge, a conferee, noted in the Congressional Record: 

The Conference Committee also rejected House provisions that would shorten 

SNAP’s 3 month time limit to 1 month and expand the population subject to 

186 

64See the floor statement by Congresswoman Fudge, 164 Cong. Rec. H10149 (daily ed. December 12, 2018), https://www.congress.gov/congressional-record/2018/12/12/house-section/article/H10142-3. 65 H.R. Rept. 115–1072, Agriculture Improvement Act of 2018, Title IV (3), https:// 

www.congress.gov/congressional-report/115th-congress/house-report/1072. 66 NPRM, p. 984. 

the rule to a broader group of recipients. We also rejected the House’s proposal 

to limit states’ flexibility to waive high-unemployment areas from the 3 month 

limit.64

Similarly, the Conference Report noted that Congress chose not to change the underlying statute: 

The Managers also acknowledge that waivers from the ABAWD time limit are 

necessary in times of recession and in areas with labor surpluses or higher 

rates of unemployment. The Managers intend to maintain the practice that 

bestows authority on the state agency responsible for administering SNAP to 

determine when and how waiver requests for ABAWDs are submitted.65

Congress therefore chose not to change the criteria by which states could request 

area waivers. While the Administration cited the House-passed version of the H.R. 

2 to support the proposed seven percent unemployment floor, Congress ultimately 

rejected this proposal in favor of the Senate approach, demonstrating intent to keep 

the current interpretation of the ‘‘insufficient jobs’’ criterion intact. 

B. Unemployment Rates Overstate Jobs Available to Childless Adult SNAP Participants 

By proposing an unemployment rate floor for the ‘‘20 percent standard,’’ the Department argues that areas with unemployment rates below this threshold offer 

enough jobs so that those individuals can find work. For example, when describing 

its support for its proposed unemployment rate floor, the Department states, ‘‘The 

Department views the proposal as more suitable for achieving a more comprehensive application of work requirements so that ABAWDs in areas that have sufficient 

number of jobs have a greater level of engagement in work and work activities, including job training.’’ 66 The Department therefore states that areas with unemployment rates below its proposed floor of seven percent over 2 years offer a sufficient 

number of jobs to the individuals subject to the time limit. This interpretation that 

areas with lower unemployment have enough jobs to employ adults without dependent children ignores the reality that overall unemployment rates overstate jobs 

available to disadvantaged individuals. 

The Department states that the unemployment rate floor proposal would prevent 

areas with low unemployment from qualifying for a waiver but ignores evidence that 

the individuals subject to the time limit are in demographic groups that experience 

higher unemployment rates than their area’s average. In explaining why it chose 

to propose an unemployment rate floor, the Department noted: 

Based upon operational experience, the Department has observed that, without an unemployment rate floor, local areas will continue to qualify for waivers 

under the Department’s 20 percent standard based on high unemployment relative to the national average even as local unemployment rates fall to levels as 

low as five to six percent (depending upon the national rate). 

The Department is therefore stating that the floor is necessary to prevent areas 

with unemployment rates it considers ‘‘low’’ from qualifying for a waiver. Adult 

SNAP participants without dependent children, however, are likely to face barriers 

to employment that result in fewer jobs available for those individuals than for the 

general population. It is unrealistic to set a specific threshold that guarantees that 

the labor market creates a sufficient number of jobs to provide employment to this 

group, and any such threshold based on the overall unemployment rate in an area 

would guarantee that many areas where childless adult SNAP participants could 

not find work were ineligible. When it explained its position that it does not believe 

areas with low unemployment rates should qualify for waivers, the Department did 

not provide any research to support its position that areas with low unemployment 

rates provide enough jobs so that the individuals subject to the time limit can find 

work, nor did it address the extensive research that demonstrates that these individuals struggle to find work even when unemployment rates are low. Because the 

Department did not provide this information, it is difficult for commenters to understand how they are interpreting a specific unemployment rate as measuring job 

availability for this population and to respond to this reasoning. 

187 

67We looked at U.S. Agriculture Department’s Fiscal Year 2017 SNAP Households Characteristic data (QC), the 2017 American Community Survey (ACS) 1 year estimates, and the 

March 2018 Community Population Survey (CPS). Reporting of race/ethnicity is voluntary and 

is missing for 13 percent of ABAWDs in QC. About 12 percent of ABAWDs self-identified or 

were coded by an eligibility worker as ‘‘Latino or Hispanic’’, but the share increased to 17 percent in high-reporting states (missing for less than ten of SNAP participants). CPS and ACS 

capture more Hispanics than QC. Hispanics account for 22 percent of ABAWDs in CPS and 20 

percent in ACS. Compared to ACS, the disability income questions are much more detailed and 

comprehensive in CPS. 68 CBPP analysis of the March 2018 Current Population Survey. Some 12 percent are unknown. 69 CBPP analysis of FY 2017 USDA Household Characteristics data. 70 ‘‘Food Stamp Employment and Training Program,’’ United States General Accounting Office, revised March 2003, https://www.gao.gov/assets/240/237571.pdf. 

The unemployment rate is a broad labor market metric that masks differences in 

the labor market outcomes experienced by different groups. Some groups, such as 

African American workers, have historically and consistently higher unemployment 

rates. The recent Great Recession also demonstrated how less-advantaged groups 

fared more poorly in the recession, losing more jobs and recovering more slowly. 

Evidence shows that the adults targeted by the time limit often face barriers to 

work. While these low-income adults without dependents are a diverse group and 

there has been limited research on this specific population, the available evidence 

demonstrates that many face greater struggles to find work than the overall population. This group, while diverse, has many characteristics that, as we will explain 

below, are associated with worse labor market outcomes: 

• Over 3⁄4 of this group have a high school diploma or less, and studies show that 

many lack skills sought by employers. 

• This group is demographically diverse. Of adult SNAP participants aged 18 

through 49 who do not receive disability income or have children in the household, about 53 percent are male, and 47 percent are female. About 2⁄5 are aged 

18 through 29, 1⁄4 are aged 30 to 39, and 1⁄3 are aged 40 to 49. About 2⁄5 are 

white, over 1⁄4 are African American, and approximately 20 percent are 

Latino.67 They live in a range of areas: about 2⁄5 live in urban areas, 2⁄5 live 

in suburban areas, and about 15 percent live in rural areas.68

• Like most SNAP participants, this group largely works, but in low-wage jobs 

that provide little stability, and as a result, many move in and out of work and 

experience periods when they are out of work. 

• Research indicates that many of these individuals face barriers to employment, 

including low skills, inconsistent work history, health conditions that limit their 

ability to work, inadequate access to transportation, criminal justice history, or 

unstable access to housing. 

Because this population is distinct from the United States population, and faces 

greater disadvantages with regards to accessing employment, an overall unemployment rate or other overall labor force metric will largely overstate the jobs available 

to this group. The section below explains the research documenting the unique barriers to employment that childless adult SNAP participants face, and the higher unemployment rates associated with many of these characteristics. 

Childless and Non-Custodial Parent Adult SNAP Participants Are Likely to Have 

Lower Levels of Educational Attainment, Which Is Associated With Higher Unemployment Rates and More Sensitivity to Labor Market Shocks 

The majority of adult SNAP participants without dependents have a high school 

education or less. According to 2017 USDA Household Characteristics data, about 

1⁄4 (24 percent) of non-disabled individuals aged 18 through 49 in households without children report having less than a high school education, and about 54 percent 

report a high school diploma or a GED. (Some eight percent do not report educational attainment.) 69 They are more likely than other SNAP participants to lack 

basic job skills like reading, writing, and basic mathematics, according to a 2003 

Government Accountability Office (GAO) study.70 A more recent study of SNAP employment and training (E&T) participants, which includes many childless adults 

ages 18 through 49, but did not separately report results for that population, found 

that 3⁄4 of employment and training providers surveyed found that at least some of 

the E&T participants they serve lack basic skills when they enter the program, over 

1⁄2 said some participants have low literacy levels or were high school dropouts, and 

over 2⁄5 cited that participants’ skills were mismatched to industry needs or were 

out of date. Over 1⁄4 of E&T participants surveyed identified limited education as 

188 

71Gretchen Rowe, Elizabeth Brown, and Brian Estes, ‘‘SNAP Employment and Training 

(E&T) Characteristics Study: Final Report,’’ United States Department of Agriculture, Food and 

Nutrition Services, revised October 2017, https://fns-prod.azureedge.net/sites/default/files/ 

ops/SNAPEandTCharacteristics.pdf. 72 ‘‘A Comprehensive Assessment of Able-Bodied Adults Without Dependents and Their Participation in the Work Experience Program in Franklin County, Ohio,’’ Ohio Association of 

Foodbanks, revised 2014, http://admin.ohiofoodbanks.org/uploads/news/WEP-2013-2014-report.pdf. 73 ‘‘Employment Status of the Civilian Population 25 Years and Over by Educational Attainment,’’ Bureau of Labor Statistics, revised February 1, 2019, https://www.bls.gov/news.release/ 

empsit.t04.htm. 74 Hilary Hoynes, Douglas L. Miller, and Jessamyn Schaller, ‘‘Who Suffers During Recessions?’’ Journal of Economic Perspectives (Summer 2012), pp. 27–48. https://pubs.aeaweb.org/ 

doi/pdfplus/10.1257/jep.26.3.27. 75Lauren Bauer and Jay Shambaugh, ‘‘Workers with Low Levels of Education Still Haven’t 

Recovered From the Recession,’’ The Hamilton Project (September 2018), pp. 1–4, http:// 

www.hamiltonproject.org/blog/employment_rate_gap_workers_with_low_levels_of_education_ 

still_havent_recov. 

a barrier to employment.71 Caseworkers in a work experience program in Ohio 

found signs of functional illiteracy even among those with a high school degree.72

Research shows that adults with lower educational attainment have higher unemployment rates than those with more education. (Figure 3.1.) For example, in 2018, 

while the unemployment rate for workers with a bachelor’s degree or more was 2.1 

percent, the unemployment rate for high school graduates was 4.1 percent, and for 

those with less than a high school education, 5.6 percent. African Americans with 

less than a high school diploma had an unemployment rate of 10.4 percent.73

Figure 3.1 

Unemployment Higher Among Those With Less Education 

Monthly unemployment rate 

Source: U.S. Bureau of Labor Statistics. 

Workers with less education are more likely to lose jobs during an economic downturn and will recover more slowly in the aftermath of a recession. Researchers have 

found that an increase of one percentage point in the state unemployment rate leads 

to almost a two-percentage-point increase in unemployment for workers with less 

than a high school degree compared to less than 0.5-percentage-point increase for 

those with a college degree.74 Workers with a high school diploma had lower employment rates in 2007 than college graduates: 55 percent for those with only high 

school education, compared to 72.5 percent for those with a bachelor’s degree. Employment rates, or the share of the population with a job, fell more sharply for the 

group with lower levels of educational attainment, and in 2018 had yet to return 

to pre-recession levels.75 Counties with large shares of workers with less than a 


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76 Brian Thiede and Shannon Monnat, ‘‘The Great Recession and America’s Geography of Unemployment’’ Demographic Research (September 2016), pp. 891–928. https:// 

www.ncbi.nlm.nih.gov/pmc/articles/PMC5486972/. 77 Alicia Modestino, Daniel Shoag, and Joshua Balance, ‘‘Upskilling: Do Employers Demand 

Greater Skill When Skilled Workers are Plentiful?’’ Harvard Kennedy School Taubman Center 

for State and Local Government (May 2015), pp. 1–4. https://www.hks.harvard.edu/sites/default/files/centers/taubman/files/Upskilling.pdf. 78 Hannes Schwandt and Till von Wachter, ‘‘Unlucky Cohorts: Estimating the Long-Term Effects of Entering the Labor Market in a Recession in Large Cross-Sectional Data Sets,’’ Journal 

of Labor Economics, Vol. 37, No. 51 (January 2019), S161–S198, https:// 

www.journals.uchicago.edu/doi/10.1086/701046. 79 CBPP analysis of FY 2017 USDA Household Characteristics data, the March 2018 Current 

Population Survey, and 2017 American Community Survey (ACS) 1 year estimates. 80 ‘‘Table E–16. Unemployment Rates by age, sex, race, and Hispanic or Latino ethnicity,’’ Bureau of Labor Statistics, revised January 4, 2019, https://www.bls.gov/web/empsit/ 

cpsee_e16.htm. 81 Valerie Wilson, ‘‘Before the State of the Union, a fact check on black unemployment,’’ Economic Policy Institute, February 2019, pp. 1–4. https://www.epi.org/blog/before-the-state-of-theunion-a-fact-check-on-black-unemployment/. 82 ‘‘Labor Force Statistics from the Current Population Survey, Table 7. Employment status 

of the civilian noninstitutional population 25 years and over by educational attainment, sex, 

race, and Hispanic or Latino ethnicity,’’ Bureau of Labor Statistics, revised January 18, 2019, 

https://www.bls.gov/cps/cpsaat07.htm. 

high school degree also saw greater employment losses during the Great Recession.76

Workers with less education may be hit harder by recessions in part because 

when unemployment rises, employers may raise the skill requirements for positions: 

one study found that a one-percentage-point increase in the local unemployment 

rate raises the fraction of jobs requiring a bachelor’s degree by about 0.4 percentage 

points and the fraction of jobs requiring 2 or more years of experience by about 0.8 

percentage points.77 Evidence also suggests that for workers entering the labor market during a recession, the effects can be long-lasting: those workers had reduced 

earnings that persisted up to 10 years into workers’ careers, and the effect was most 

pronounced for those with less than a high school education, driven by greater 

losses in employment.78

The majority of adult SNAP participants without dependents have a high school 

diploma or lower educational attainment. Evidence shows that workers with a high 

school diploma or less have higher unemployment rates, lower employment rates, 

experience greater employment losses during economic downturns, and recover more 

slowly. The overall unemployment rate therefore will significantly overstate the employment opportunities available to less-educated workers, particularly during a recession and the aftermath. FNS does not appear to have considered any of this research in developing this proposal. We urge FNS to carefully review this literature, 

which demonstrates that because adults with less education, typically have higher 

unemployment rates than the overall average in their area, the proposed unemployment rate floor would be a much higher rate for adults with less education, the majority of childless adults. 

Over Two-Fifths of Childless Adult SNAP Participants Aged 18–49 Are African 

American or Latino, Groups That Experience Higher Unemployment Rates and 

More Employment Discrimination 

Over 1⁄4 of childless adult SNAP participants targeted by the time limit are African American and approximately 20 percent are Latino.79 These groups, particularly 

African Americans, also have higher unemployment rates than white Americans and 

are more affected by recessions. 

Black and Latino workers generally have higher unemployment rates than white 

Americans. According to data published by the BLS, in the fourth quarter of 2018, 

for example, the overall unemployment rate was 3.6 percent and 3.2 percent for 

white workers, but Latinos had an unemployment rate of 4.3 percent, and the unemployment rate for African Americans was 6.1 percent.80 In fact, for about the past 

4 decades, unemployment rates among black workers have been about double those 

of white workers.81 This relationship is true even when comparing unemployment 

rates for those with similar education levels. The unemployment rate among African 

American workers with less than a high school education in 2018 was 10.4 percent, 

more than double the unemployment rate of whites with the same education level, 

which was 5.1 percent. Black high school graduates had unemployment rates of 6.7 

percent in 2018, close to double the unemployment rate for white high school graduates in 2018, of 3.5 percent.82

These disparities are also found at the local level. Researchers have found significant racial disparities in labor force statistics within the same city, which may be 

190 

83Martha Ross and Natalie Holmes, ‘‘Employment by Race and Place: Snapshots of America,’’ 

Brookings Institution, February 2017, pp. 1–16. https://www.brookings.edu/blog/the-avenue/ 

2017/02/27/employment-by-race-and-place-snapshots-of-america/. 84Kenneth Couch and Robert Fairlie, ‘‘Last Hired First Fired? Black-White Unemployment 

and the Business Cycle,’’ Demography (February 2010), pp. 227–247. https:// 

www.ncbi.nlm.nih.gov/pmc/articles/PMC3000014/. 85Tomaz Cajner, et al., ‘‘Racial Gaps in Labor Market Outcomes in the Last Four Decades 

and over the Business Cycle,’’ Federal Reserve Board, June 2017, pp. 1–33, https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2996084. 86 Richard Rothstein, ‘‘The Racial Achievement Gap, Segregated Schools, and Segregated 

Neighborhoods—A Constitutional Insult,’’ Economic Policy Institute, November 12, 2014, 

https://www.epi.org/publication/the-racial-achievement-gap-segregated-schools-and-segregatedneighborhoods-a-constitutional-insult/. 87Lincoln Quillian, et al., ‘‘Meta-Analysis of Field Experiments Shows No Change in Racial 

Discrimination in Hiring Over Time,’’ Proceedings of the National Academy of Sciences of the 

United States of America (April 2017), pp. 1–6, https://www.pnas.org/content/early/2017/09/ 

11/1706255114. 

explained in part by complex and deeply rooted factors such as industry concentration, investments in housing and infrastructure, and demographic trends. Chicago, 

San Francisco, Washington, and the borough of Manhattan all had relatively low 

black employment rates in 2015 (56, 53, 64, and 62 percent, respectively), and white 

employment rates that were at least 20 percentage points higher (83, 84, 88, and 

85 percent, respectively).83 It is unclear if the Department considered the consistently high unemployment rates among African American and Latino workers when 

proposing a minimum unemployment rate floor of seven percent, which would essentially be an unemployment rate that is close to 14 percent for African Americans. 

Employment outcomes for African Americans are also more affected by the business cycle than white Americans. One study found that over the period of 1990 

through 2004, as the unemployment rate increased by one percentage point, men 

were 0.16 percentage points more likely to become unemployed, but this rate rose 

to 0.27 percentage points for African American men. Black men were also less likely 

to transition from unemployment to employment than white men, though the researchers found that this relationship didn’t change significantly during the business cycle, the same study found. These results control for differences in education 

and other characteristics.84 Another study found that black and Latino workers are 

more likely to work part-time for economic reasons than white workers, even after 

controlling for other demographic and economic differences between the groups. This 

analysis found that this involuntary part-time work rose for all groups during the 

Great Recession, but recovered much more quickly for white men than for black 

men, with black men much less likely to transition from part-time to full-time work 

in the years following the recession than white men.85

Multiple deep-rooted factors contribute to these employment disparities. For example, decades of discriminatory housing policies have contributed to unequal access to quality education for black children, which may affect employment opportunities later in life.86 In addition to these complex causes, a large body of research 

also demonstrates that employer discrimination contributes to higher unemployment 

rates among African Americans, especially compared to white Americans. 

Researchers have conducted dozens of field studies over the past 3 decades in 

which they have compared outcomes for otherwise identical job applications that differ only by racial or ethnic markers (such as identical re ́sume ́s with distinct names). 

One meta-analysis of such studies found that white applicants receive 36 percent 

more callbacks than African Americans with the same qualifications, and 24 percent 

more callbacks than Latinos. They found there was little change in the callback disparities between white and black Americans over the 25 years studied, from 1990 

to 2015, and a slight reduction in the disparities between Latino and white applicants, though barely statistically significant.87 We strongly urge FNS to review all 

of these studies, as they help explain why an unemployment rate is an especially 

poor predictor of job availability for African American workers, who may not be 

hired for available jobs due to discrimination. For example: 

• Two field studies, in Milwaukee and New York City, found consistently higher 

callbacks for white applicants compared to African American applicants. Both 

studies had young men (ages 21 to 24) play the role of job applicants. They were 

matched with applicants with similar appearance and verbal and social skills, 

and presented with similar re ́sume ́s demonstrating similar levels of education 

and job experience, and they received job interview training to be similarly preVerDate Aug 31 2005 11:16 Jun 14, 2019 Jkt 041481 PO 00000 Frm 00196 Fmt 6621 Sfmt 6621 P:\DOCS\116-02\36188.TXT BRIAN
191 

88Devah Pager and Bruce Western, ‘‘Identifying Discrimination at Work: The Use of Field Experiments,’’ Journal of Social Issues (2012) pp. 221–237, http://scholar.harvard.edu/files/ 

pager/files/identifying_discrimination_pager_western.pdf?m=1462807104. 89Devah Pager, Bruce Western, and Bart Bonikowski, ‘‘Discrimination in a Low-Wage Labor 

Market: A Field Experiment,’’ American Sociological Review (October 2009), pp. 777–799, 

http://scholar.harvard.edu/files/bonikowski/files/pager-western-bonikowski-discrimination-ina-low-wage-labor-market.pdf. 90Marianne Bertrand and Sendhil Mullainathan, ‘‘Are Emily and Greg More Employable than 

Lakisha and Jamal? A Field Experiment on Labor Market Discrimination,’’ National Bureau of 

Economic Research (July 2003), pp. 1–27 https://www.nber.org/papers/w9873. 91 Ed Bolen and Stacy Dean, ‘‘Waivers Add Key State Flexibility to SNAP’s Three-Month Time 

Limit,’’ Center on Budget and Policy Priorities, updated February 6, 2018, https:// 

www.cbpp.org/research/food-assistance/waivers-add-key-state-flexibility-to-snaps-three-monthtime-limit. 

pared. In both Milwaukee and New York, white applicants received callbacks 

or job offers at roughly double the rate of African American applicants.88

• Another field study found that black applicants were about 1⁄2 as likely to receive a callback as white applicants. This study also found that white applicants 

who were recently released from prison had similar levels of callbacks as black 

and Latino applicants: whites with criminal records obtained positive responses 

in 17.2 percent of job applications, compared to 15.4 percent for Latinos and 

13.0 percent for blacks.89

• One field experiment found that when comparing outcomes of identical re ́sume ́s 

with names that were typically associated with white or black identities, white 

applicants had a 50 percent higher chance of being called back.90

While they make up a small share of childless adults subject to the time limit, 

Native Americans are likely to be disproportionately affected by this proposed rule 

given the estimate that many Tribal reservations may lose waiver eligibility, as outlined in Chapter 1. Native Americans also traditionally have higher unemployment 

rates and worse labor force outcomes than white Americans, in part due to sparse 

job opportunities on or near Tribal and other rural areas and the legacy of historical 

factors contributing to lower educational attainment and other barriers to employment. (Figure 3.2.) 91

Figure 3.2 

Native Americans Face Higher Unemployment 

2006–2018 annual averages 

Note: ‘‘Native American’’ refers to individuals identifying as American Indian or Alaska Native alone or in combination with some other racial category. ‘‘White’’ refers to individuals identifying as white alone. Both Native 

American and white data includes Hispanics. 

Source: U.S. Bureau of Labor Statistics, Current Population Survey. 


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192 

92 ‘‘SNAP Helps 1 in 10 Workers in the United States Put Food on the Table,’’ Center on 

Budget and Policy Priorities, revised November 2018, https://www.cbpp.org/sites/default/files/ 

atoms/files/factsheets_11-27-18fa_us.pdf. 93Gretchen Rowe, Elizabeth Brown, and Brian Estes, ‘‘SNAP Employment and Training 

(E&T) Characteristics Study: Final Report,’’ United States Department of Agriculture, Food and 

Nutrition Services, revised October 2017, https://fns-prod.azureedge.net/sites/default/files/ 

ops/SNAPEandTCharacteristics.pdf. 94 ‘‘Labor Force Statistics from the Current Population Survey, Table 25, Annual Averages, 

Unemployed persons by occupation and sex,’’ Bureau of Labor Statistics, revised January 18, 

2019, https://www.bls.gov/cps/cpsaat25.htm. 95Kristin Butcher and Diane Whitmore Schanzenbach, ‘‘Most Workers in Low-Wage Labor 

Market Work Substantial Hours, in Volatile Jobs,’’ Center on Budget and Policy Priorities, revised July 24, 2018, https://www.cbpp.org/sites/default/files/atoms/files/7-24-18pov.pdf. 96Maria E. Canon, Marianna Kudlyak, Guannan Luo, and Marisa Reed, ‘‘Flows To and From 

Working Part Time for Economic Reasons and the Labor Market Aggregates During and After 

the 2007–09 Recession,’’ Economic Quarterly, Vol. 100, No. 2, Second Quarter 2014, Pp.87–111. 

https://www.richmondfed.org/-/media/richmondfedorg/publications/research/economic_ quarterly/2014/q2/kudlyak.pdf; Lonnie Golden, ‘‘Still falling short on hours and pay,’’ Economic 

Policy Institute, December 5, 2016, https://www.epi.org/publication/still-falling-short-on-hoursand-pay-part-time-work-becoming-new-normal/#epi-toc-8. 97 John Coglianese ‘‘The Rise of In-and-Outs: Declining Labor Force Participation of Prime Age 

Men,’’ Working Paper, February 28, 2018, https://scholar.harvard.edu/coglianese/publications/ 

rise-of-in-and-outs. 

This evidence shows that black and Latino workers as well as Native American 

workers, have historically and consistently higher unemployment rates than white 

workers, and that these outcomes cannot be explained solely by differences in education or other characteristics. Significant numbers of individuals subject to the 

time limit therefore are in groups that experience unemployment rates that are significantly higher than that of their state or local area. An unemployment rate floor 

would therefore disallow states from requesting waivers from areas where black and 

Latino workers have few job opportunities, even if the general unemployment rate 

for their area is relatively low. If implemented, this proposal would therefore disproportionately harm black, Latino and Native American adults subject to the time 

limit. This disparate impact of this policy is therefore in conflict with 7 U.S.C. 

§ 2020(c)(2), which establishes that program administration of SNAP must be consistent with existing civil rights law. 

Childless Adult SNAP Participants Are More Likely to Work in Jobs With High 

Rates of Un- And Underemployment and Instability 

The individuals who are targeted by the time limit do work, but in occupations 

where workers experience instability, including underemployment, gaps in employment, and higher unemployment rates. The general unemployment rate for the area 

therefore does not reflect the unemployment rates for workers such as those in service occupations, who are more likely to be unemployed at any given time than other 

workers. 

SNAP participants who work generally work in service or sales occupations, such 

as cashiers, cooks, home health aides, janitors, or drivers.92 A recent study of SNAP 

E&T participants, which includes many childless adult SNAP participants ages 18– 

49, found that sales and service occupations, such as cashiers and food preparation 

workers, were among the most common reported by participants.93

There are higher unemployment rates among workers in many of these occupations. People who report their occupation as a service occupation had unemployment 

rates about 23 percent higher than the general unemployment rate in 2018, with 

food preparation and serving workers reporting unemployment rates about 56 percent higher than the overall average.94 One analysis that looked at working-age 

workers who did not receive disability income and did not have young children in 

the household found that unemployment rates among those individuals were especially high for cashiers, housekeepers, and laborers in 2017.95

Low-skill and low-wage workers are also more likely to be working part time for 

economic reasons, and to cycle in and out of the labor force. For example, one study 

found that the share of workers in low-skill jobs (classified by the types of tasks 

required, which are manual and routine, as opposed to cognitive and non-routine) 

who were working part time involuntarily was about three times that of workers 

in the highest-skill occupations (11 percent versus 3 percent), and another found 

that involuntary part-time workers were concentrated in the retail trade and hospitality industries.96 Another study observed a broader trend of workers cycling in 

and out of the labor force.97

One of the reasons why these workers might have higher rates of un- and underemployment and non-labor force participation is higher turnover: because these occupations lack stability, workers are likelier to move in and out of jobs, and likelier 

193 

98For more information, see Brynne Keith-Jennings and Vincent Palacios, ‘‘SNAP Helps Millions of Workers,’’ Center on Budget and Policy Priorities, May 10, 2017, https://www.cbpp.org/ 

research/food-assistance/snap-helps-millions-of-low-wage-workers. 99 Bureau of Labor Statistics, Employee Benefits Survey, https://www.bls.gov/ncs/ebs/benefits/2017/ownership/civilian/table32a.htm. This survey constructs hourly wage percentiles by 

looking at average reported hourly wages for workers by occupation. (Because these averages 

are for occupations, workers may fall into a different percentile than their occupation as a whole 

if they earn more or less than the average for their occupation.) 100 Heather Hill, ‘‘Paid Sick Leave and Job Stability,’’ Work and Occupations, Vol. 40, Issue 

2, 2013, https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3825168/. 101Saravanan Kesavan and Camelia Kuhnen, ‘‘Demand fluctuations, precarious incomes, and 

employee turnover,’’ working paper, May 2017, http://public.kenan-flagler.unc.edu/faculty/ 

kuhnenc/research/kesavan_kuhnen.pdf. 102Matthew Desmond and Carl Gershenson, ‘‘Housing and Employment Insecurity Among the 

Working Poor,’’ Social Problems, Vol. 63, Issue 1, February 2016, https://academic.oup.com/ 

socpro/article-abstract/63/1/46/1844105. 103 Bureau of Labor Statistics, ‘‘America’s Young Adults at 29: Labor Market Activity, Education and Partner Status: Results from a Longitudinal Survey,’’ April 8, 2016, [https:// 

www.bls.gov/news.release/archives/nlsyth_04082016.pdf]; Bureau of Labor Statistics, ‘‘Number 

of Jobs Held, Labor Market Activity, and Earnings Growth Among the Youngest Baby Boomers: 

Results from a Longitudinal Survey Summary,’’ August 24, 2017, https://www.bls.gov/ 

news.release/nlsoy.nr0.htm. 104 Bureau of Labor Statistics, ‘‘Employee Tenure in 2016,’’ https://www.bls.gov/news.release/ 

pdf/tenure.pdf. 

to be unemployed or out of the labor force at a given time or take a part-time job 

when they would desire a full-time job. Low-paying jobs often have irregular schedules that change from week to week. Workers in low-wage jobs are sometimes given 

little notice of schedule changes or are expected to be on call, and are more likely 

to work part-time hours when they would prefer a full-time schedule.98 Low-wage 

jobs are also more likely to lack paid sick leave or other paid leave. For example, 

only 46 percent of workers in jobs with average hourly wages in the bottom 25 percent of the wage distribution had paid sick leave in 2016, compared to 91 percent 

of workers in the highest-paid jobs (and 72 percent overall).99

Workers in jobs with lower wages, more volatility, and fewer benefits are more 

likely to experience turnover, research shows. For example, a study found that 

workers with access to paid sick leave or paid vacation were more likely to stay in 

their current job. This study found these effects even when controlling for other 

characteristics of workers, such as education level or income, or characteristics of 

jobs (such as the size of the firm and other benefits provided) that are associated 

with more job separations.100 Another study that examined data from a large chain 

of retailers found that workers who earned lower wages and had more schedule volatility (which was driven by changes in consumer demand, not by employee choice) 

were more likely to leave their jobs; this study found that these effects were not 

due to worker ability.101

In addition to job conditions, the lack of key supports such as stable housing may 

also contribute to volatility or periods of joblessness among low-income workers. For 

example, recent research finds that low-income renters who experience a forced 

move (such as following an eviction) are more likely to be laid off from their jobs, 

compared to similar renters who did not experience a forced move.102

At least in part because of these conditions, workers in low-wage jobs are more 

likely to be employed at jobs for shorter periods and to experience periods of nonwork. Workers with lower levels of education (who are more likely to work in lowwage jobs) spend more weeks unemployed than those with more education and they 

experience less wage growth over the course of their lifetimes, according to studies 

by the Bureau of Labor Statistics that follow workers over time. These studies also 

find that younger workers with less education are more likely to have short-term 

jobs of 6 months or less, compared to workers of a similar age with more education.103 Workers in jobs that tend to have low wages, such as in the leisure and 

hospitality industry and service occupations, also tend to stay at jobs for shorter 

lengths than workers in other jobs.104 We strongly urge FNS to carefully review this 

research, which helps explain why unemployment rates may not capture the dynamic nature of work for low-wage workers, who comprise the vast majority of 

SNAP participants. 

Working SNAP participants often work in occupations and industries with low 

wages and more volatility. Compared to all workers, a greater share of workers who 

participate in SNAP are employed in service occupations and in industries such as 

retail and hospitality, where jobs are more likely to pay low wages and have other 

194 

105 Brynne Keith-Jennings and Vincent Palacios, ‘‘SNAP Helps Millions of Workers,’’ Center 

on Budget and Policy Priorities, May 10, 2017, https://www.cbpp.org/research/food-assistance/ 

snap-helps-millions-of-low-wage-workers. 106Lauren Bauer, ‘‘Workers Could Lose SNAP Benefits Under Trump’s Proposed Rule,’’ The 

Hamilton Project, December 2018, http://www.hamiltonproject.org/blog/workers_could_lose_ 

snap_benefits_under_trumps_proposed_rule. 107 7 CFR § 273.24(c)(2). 108 CBPP analysis of the March 2018 Current Population Survey. 109 John L. Czajka, et al., ‘‘Imposing a Time Limit on Food Stamp Receipt: Implementation 

of the Provisions and Effects on Food Stamp Program Participation, Volume I,’’ U.S. Department 

of Agriculture, Food and Nutrition Service, September 2001, https://fns-prod.azureedge.net/ 

sites/default/files/abawd.pdf. 110 ‘‘A Comprehensive Assessment of Able-Bodied Adults Without Dependents and Their Participation in the Work Experience Program in Franklin County, Ohio,’’ Ohio Association of 

Foodbanks, revised 2015, http://ohiofoodbanks.org/wep/WEP-2013-2015-report.pdf. 111Gretchen Rowe, Elizabeth Brown, and Brian Estes, ‘‘SNAP Employment and Training 

(E&T) Characteristics Study: Final Report,’’ United States Department of Agriculture, Food and 

Nutrition Services, revised October 2017, https://fns-prod.azureedge.net/sites/default/files/ 

ops/SNAPEandTCharacteristics.pdf. 112 ‘‘Economic News Release: Table 1, Employment status of the civilian noninstitutional population by disability status and selected characteristics, 2018 annual averages,’’ Bureau of Labor 

Statistics, revised June 21, 2018, https://www.bls.gov/news.release/disabl.t01.htm. 

features of low quality.105 Childless adults are also likely to experience gaps in employment, despite being employed regularly. For example, one study that compared 

a snapshot, December 2013, with the 24 month period surrounding that month (January 2013 through December 2014), found that while 3⁄4 of childless adult SNAP 

participants were in the labor force at some point during this period, only about 1⁄3

consistently worked at least 20 hours per week throughout the entire period.106 Because childless adult SNAP participants work in jobs that contribute to periods of 

non-employment, unemployment rates in their area likely do not capture their labor 

trends. The Department did not say whether it considered the unemployment rate 

floor in the context of the types of jobs that childless adults are likely to work in. 

Its lack of transparency makes it difficult to assess the claim that individuals subject to the time limit have access to a sufficient number of jobs in an area with 

seven percent unemployment over a 2 year period. 

Many Childless Adult SNAP Participants Have Health Conditions That Limit Their 

Ability to Work 

While adults are exempt from the time limit if they are ‘‘medically certified as 

physically or mentally unfit for employment,’’ 107 evidence suggests that many childless adult non-elderly SNAP participants have health conditions that serve as a barrier to employment. These adults may not fit the state’s definition of ‘‘unfit for 

work’’ or may struggle to understand the rules or document their condition in order 

to obtain an exemption. Research shows that adults with disabilities and other 

health issues tend to have higher unemployment rates and fewer employment opportunities than individuals without such conditions. 

Various sources illustrate the health conditions that many childless adult SNAP 

participants have. Survey data indicate that among individuals aged 18 through 49 

who do not receive disability benefits or identify as disabled, nor have children in 

their household, about 1⁄5 report a health problem or disability that prevents them 

from working or limits the type of work they can do, report leaving the job or the 

labor force due to disability, or report not having worked in the last year due to 

disability.108 Research funded by FNS reports that state caseworkers found multiple 

barriers to employment among individuals subject to the time limit as they worked 

to implement welfare reform’s time limits and work requirements. The most frequently cited barriers included medical or mental health issues, or substance use 

disorders.109 A detailed study of childless adults who were referred to a work experience program in Franklin County (Columbus), Ohio found that 1⁄3 have a mental 

or physical limitation, including depression, post-traumatic stress disorder, mental 

or learning disabilities, or physical injuries.110 A more recent study of characteristics of employment and training participants, which includes many childless adults 

ages 18–49, found that about 30 percent of E&T participants identified health issues 

as a barrier to employment.111

Research finds that people with disabilities tend to face greater barriers to employment and have worse labor force outcomes than individuals without disabilities. 

The Bureau of Labor Statistics, for example, finds that the unemployment rate 

among working-age individuals with a disability (ages 16 to 64), was ten percent 

in 2017, more than double the unemployment rate for working-age individuals without a disability, which was 4.2 percent.112 Earlier BLS research describes some of 

195 

113 ‘‘Persons With a Disability: Barriers to Employment, Types of Assistance, and Other LaborRelated Issues,’’ Bureau of Labor Statistics, revised April 24, 2013, https://www.bls.gov/ 

news.release/pdf/dissup.pdf. 114Pamela Loprest and Elaine Maag, ‘‘Barriers to and Supports for Work Among Adults with 

Disabilities: Results from the NHIS–D,’’ The Urban Institute, January 2001, pp. 1–22, https:// 

www.bls.gov/news.release/pdf/dissup.pdf. 115Katrina Vornholt, et al., ‘‘Disability and Employment—Overview and Highlights,’’ European Journal of Work and Organizational Psychology (2018), pp. 40–55, https:// 

www.tandfonline.com/doi/pdf/10.1080/1359432X.2017.1387536. 116 James Ziliak, ‘‘Restoring Economic Opportunity for ‘The People Left Behind’: Employment 

Strategies for Rural America,’’ Aspen Institute, revised 2019. https://www.aspeninstitute.org/ 

longform/expanding-economic-opportunity-for-more-americans/restoring-economic-opportunityfor-the-people-left-behind-employment-strategies-for-rural-america/. 117Tom Hertz, et al., ‘‘Rural Employment Trends in Recession and Recovery,’’ U.S. Department of Agriculture, Economic Research Service, revised August 2014, https:// 

www.ers.usda.gov/webdocs/publications/45258/48731_err172.pdf?v=0. 

the barriers to employment that individuals with disabilities identified. About 1⁄2 of 

the individuals who were out of the labor force or unemployed in May 2012 identified experiencing these challenges, with the most common being that their own disability limited their work ability, and with smaller shares identifying a lack of training, lack of transportation, or the need for accommodations.113 Other research has 

identified challenges jobseekers with disabilities face, such as difficulty finding appropriate jobs (which could include difficulty finding jobs that provide appropriate 

accommodations), lack of social networks to facilitate job connection, or lack of accessible transportation for job-seeking.114 Research has also documented that employers’ attitudes may also harm jobseekers with disabilities, as employers may inadvertently underestimate the capacity of individuals with disabilities.115

Many childless adults report physical or mental health conditions that limit their 

ability to find a job and to work, and research shows that adults with disabilities 

face higher unemployment rates. While some of these individuals may be exempt 

from the time limit based on disability, others face difficulty documenting their 

health conditions, or have conditions that fall short of the ‘‘unfit for work’’ standard. 

Imposing an unemployment rate floor for 20 percent standard waivers would therefore cause many areas to lose waivers where individuals with health conditions are 

unable to find jobs. The Department did not address the disparate impact of the proposed rule on people with disabilities and other health conditions. 

Childless Non-Elderly Adults Seeking Work May Face Geographic or Transportation 

Limitations With Respect to Available Jobs 

As stated above, about 2⁄5 each of childless adult SNAP participants without disabilities live in urban or suburban areas, and about 15 percent live in rural areas. 

Many rural areas have stalled economic development, which may result in relatively 

few job opportunities available. Even in urban or suburban areas where jobs may 

be more plentiful, many workers face transportation limitations to access those jobs. 

Some childless adults may face obstacles to finding work based on geographic factors. 

Individuals living in rural areas are less likely to be employed than other areas. 

Factors such as out-migration of younger workers and the aging of the remaining 

workforce, and declining infrastructure and investment have contributed to this 

trend. Beginning in the 1970s, the share of men with less than a high school education who are employed has declined more in rural areas than in urban areas. By 

2016, only about 50 percent of these men with lower educational attainment were 

employed, about 15 percentage points lower than men without a high school diploma 

in urban areas.116 While both rural and urban counties saw steep employment 

losses that began recovering in 2010, the recovery stalled for rural counties, contributing to a significant employment gap between rural and urban counties, according 

to a 2014 USDA study. Counties with large share of African Americans saw greater 

impacts from the recession, which can only partially be explained by factors such 

as industry mix or educational composition of those counties, this study found.117

In addition to individuals living in rural areas may facing significant challenges 

to finding work, many individuals in all types of areas do not have access to available jobs, either because their skills do not align with the job requirements, or because transportation options to those jobs are inadequate. In these areas, the area 

unemployment rate is an especially poor proxy for jobs available to those individuals, if such jobs are inaccessible. We strongly urge FNS to carefully review all of 

the below studies, which are key to understanding why an unemployment rate for 

an area does not accurately portray the number of jobs available to the individuals 

subject to the time limit. 

196 

118 Elizabeth Kneebone and Natalie Holmes, ‘‘The Growing Distance Between People and Jobs 

in Metropolitan America,’’ Metropolitan Policy Program at Brookings, March 2015, pp. 1–24, 

http://kedc.com/wp-content/uploads/2015/04/Brookings_JobCommuteDistance2015.pdf. 119The researchers identified [ZIP C]odes where job postings ‘‘far exceeded’’ jobseekers as [ZIP 

C]odes that are in the top quintile of job seekers minus job postings within 6.3 miles of the [ZIP 

C]ode’s population-weighted centroid, which is the average distance between job seekers and applicants in their dataset. 120 Christina Stacy, Brady Meixell, and Serena Lei. ‘‘Too Far from Jobs: Spatial Mismatch and 

Hourly Workers,’’ Urban Institute, February 21, 2019, https://www.urban.org/features/too-farjobs-spatial-mismatch-and-hourly-workers. 121 Rucker Johnson, ‘‘Landing a job in urban space: The extent and effects of spatial mismatch,’’ Regional Science and Urban Economics (February 2006), pp. 331–372, https:// 

www.ssc.wisc.edu/∼gwallace/Papers/Johnson%20(2006).pdf. 

• The number of jobs within a typical commuting distance in major metro areas 

fell by seven percent between 2000 and 2012, with steeper losses for Latino and 

African American residents, which fell by 17 and 14 percent respectively, and 

for residents with income below the poverty line, which fell by 17 percent, compared to six percent for non-poor residents. The majority of Census tracts with 

high poverty rates or a majority of residents of color experienced losses in accessible jobs.118

• In a number of metropolitan areas, low-income workers live far from available 

jobs, one recent study found by comparing the distance between the residence 

of low-wage jobseekers and job postings based on data from an online marketplace for hourly jobs. This study found, for example, that in 12 major metropolitan areas, within at least nine percent of [ZIP C]odes in each area, job postings 

far exceeded jobseekers in those [ZIP C]odes.119 In some of these cities such as 

San Francisco, jobs may be clustered in areas of the city where housing costs 

are high, and low-wage job-seekers live farther away and have limited transit 

options. For example, in Boston, low-wage job postings far exceed the number 

of applicants in 41 percent of [ZIP C]odes, and in New York, San Francisco, Chicago, Minneapolis, and Denver, available jobs far outnumber job seekers in 

about 1⁄4 or more of [ZIP C]odes. There are also many pockets of metropolitan 

areas with the opposite issue, where many job seekers are clustered, but available jobs are far from where they live. This is the case for over 1⁄2 of the [ZIP 

C]odes in Atlanta and Miami, where job applicants far outweigh open jobs 

(measured as [ZIP C]odes in the bottom quintile of job seekers minus job postings within 6.3 miles of the [ZIP C]ode’s center). In cities such as Columbus, 

Detroit, Austin, and Nashville, there are far more job applicants then there are 

available jobs in over 1⁄4 of [ZIP C]odes. In many cities in the study such as 

Columbus, Nashville, Dallas, and Washington, D.C., sizable shares of [ZIP 

C]odes have both problems, demonstrating the mismatch between the distribution of available jobs and workers.120

• Increasing job accessibility, a measure of proximity to employment opportunities 

relative to other nearby jobseekers, significantly increases the chance of finding 

a job for African Americans and Latinos, a 2006 study that looked at jobseekers 

in three major metropolitan areas found. This shows how disparities in access 

to jobs contribute to disparities in labor market outcomes. The authors identified several factors as contributing to this phenomenon, including that African 

Americans were more likely to live in central cities farther from suburban areas 

with more jobs and were less able to move to a new neighborhood due to housing segregation and residential discrimination; jobs were located in cheaper suburban areas due to land use policy; and that there was a lack of public transit 

options and lower car ownership rates among African Americans. 

This study found that increasing accessibility by one standard deviation above 

the mean value would increase the probability of completing a job search within 

6 months by 61 percent for black non-college graduates, while not increasing 

this effect for white workers with similar levels of education. Having access to 

a car, searching in a job-rich area, being able to accept a longer commute, having a higher-quality social network, and having more education were all associated with an increase in the probability of finding a job within 6 months, while 

being black or having child care concerns were associated with a decrease in 

this probability. The cumulative effects of spatial job search variables such as 

job accessibility or car ownership rates accounted for about 40 percent of the 

gap between the time it takes black and white jobseekers to find a job.121

• Increased job accessibility reduced the length of time it took recently laid-off 

workers in nine metropolitan areas to find a job. This study looked specifically 

at jobseekers who had been employed but laid off to ensure that these individVerDate Aug 31 2005 11:16 Jun 14, 2019 Jkt 041481 PO 00000 Frm 00202 Fmt 6621 Sfmt 6621 P:\DOCS\116-02\36188.TXT BRIAN
197 

122Fredrik Andersson, et al., ‘‘Job Displacement and the Duration of Joblessness: The Role 

of Spatial Mismatch,’’ National Bureau of Economic Research (April 2014), pp. 1–50. https:// 

www.nber.org/papers/w20066.pdf. 123 Jangik Jin and Kurt Paulsen, ‘‘Does Accessibility Matter? Understanding the Effect of Job 

Accessibility on Labour Market Outcomes,’’ Urban Studies (2018), pp. 92–115. https://journals.sagepub.com/doi/abs/10.1177/0042098016684099. 124 John L. Czajka, et al., ‘‘Imposing a Time Limit on Food Stamp Receipt: Implementation 

of the Provisions and Effects on Food Stamp Program Participation, Volume I,’’ U.S. Department 

of Agriculture, Food and Nutrition Service, September 2001. https://fns-prod.azureedge.net/ 

sites/default/files/abawd.pdf. 125 ‘‘Food Stamp Employment and Training Program,’’ United States General Accounting Office, revised March 2003, https://www.gao.gov/assets/240/237571.pdf. 126Gretchen Rowe, Elizabeth Brown, and Brian Estes, ‘‘SNAP Employment and Training 

(E&T) Characteristics Study: Final Report,’’ United States Department of Agriculture, Food and 

Continued 

uals were searching for reasons unrelated to characteristics associated with 

higher unemployment. It found that ‘‘an increase in one unit in job accessibility 

(from ¥0.5 to 0.5) is approximately equal to an increase from the 20th to the 

80th percentile of job accessibility. Such an increase is associated with a 5.0 

percent reduction in search duration for finding any job, and a 6.6 and 8.3 percent reduction for accessions to a new job with 75 and 90 percent of prior job 

earnings, respectively.’’ Black and Hispanic workers were more sensitive to job 

accessibility than were white workers.122

• An analysis of job accessibility in the Chicago metropolitan area found that increasing job accessibility is linked with lower unemployment. At the mean, an 

increase in job accessibility of one standard deviation was associated with a 

0.43-point reduction in the unemployment rate overall, a 0.57-point reduction 

in the African American unemployment rate, and a 0.47-reduction in the unemployment rate for low-income households.123

Research shows how geographic factors can influence labor market outcomes such 

as employment for individuals in ways that are not readily apparent based on unemployment rates. An individual living in an area with a relatively low unemployment rate may not have access to jobs for which they are qualified due to transportation limitations. Some rural areas may have relatively low unemployment rates 

due in part to low labor force participation, and individuals living there may have 

relatively few job opportunities. We are concerned that when considering an unemployment rate floor for the purposes of time limit waivers, the Department did not 

appear to consider whether job accessibility may limit the potential for childless 

SNAP participants to obtain a job, even if the area in which they live has a relatively low unemployment rate. 

Childless Adult SNAP Participants Report Other Barriers That Are Associated With 

Higher Unemployment Rates 

The unemployment rate for the area does not reflect the availability of jobs for 

adult SNAP participants because these individuals face many disadvantages compared to the overall labor force. In addition to some of the characteristics already 

discussed that are associated with higher unemployment rates and other worse 

labor force outcomes, many individuals face barriers to work that may make it more 

difficult to find available jobs, complete a job search, be selected by employers, or 

maintain a job once employed. Here again, FNS’ proposed rule seemed to either ignore or dismiss without explanation the considerable research that finds that unemployment rates do not reflect job availability for the individuals subject to the time 

limit. We encourage FNS to carefully review these research, which demonstrates 

how barriers to employment limit job availability for people subject to the time limit 

even if the unemployment rate is low. 

• Housing instability and homelessness. Several studies have reported that 

some childless adult SNAP participants lack access to stable housing and some 

experience homelessness. A USDA research report looking at individuals first 

subject to the time limit found that homelessness was among the barriers that 

case managers reported.124 A GAO study that looked at employment and training programs for childless adults also found that some case managers reported 

housing difficulties as a barrier to work; for example, Colorado officials estimated that about 40 percent of their employment and training participants experienced homelessness.125 Similarly, a more recent USDA study of employment 

and training providers found that over 2⁄5 of these providers identified a lack 

of stable housing as a barrier for at least a quarter of participants in these programs, which include many adults targeted by the time limit.126

198 

Nutrition Services, revised October 2017, https://fns-prod.azureedge.net/sites/default/files/ 

ops/SNAPEandTCharacteristics.pdf. 127David Long, John Rio, and Jeremy Rosen. ‘‘Employment and Income Supports for Homeless 

People,’’ 2007 National Symposium on Homelessness Research, https://aspe.hhs.gov/system/ 

files/pdf/180356/report.pdf. 128 ‘‘Taking Away Medicaid for Not Meeting Work Requirements Harms People Experiencing 

Homelessness,’’ Center on Budget and Policy Priorities, revised December 14, 2018, https:// 

www.cbpp.org/sites/default/files/atoms/files/4-18-18health.pdf. 129Matthew Desmond and Carl Gershenson, ‘‘Housing and Employment Insecurity among the 

Working Poor,’’ Social Problems (January 2016), pp. 1–22. https://scholar.harvard.edu/files/ 

mdesmond/files/desmondgershenson.sp2016.pdf?m=1452638824. 130 ‘‘A Comprehensive Assessment of Able-Bodied Adults Without Dependents and Their Participation in the Work Experience Program in Franklin County, Ohio,’’ Ohio Association of 

Foodbanks, 2014, http://admin.ohiofoodbanks.org/uploads/news/WEP-2013-2014-report.pdf. 131Gretchen Rowe, Elizabeth Brown, and Brian Estes, ‘‘SNAP Employment and Training 

(E&T) Characteristics Study: Final Report,’’ United States Department of Agriculture, Food and 

Nutrition Services, revised October 2017, https://fns-prod.azureedge.net/sites/default/files/ 

ops/SNAPEandTCharacteristics.pdf. 132 Claire Wilson and Brian Estes, ‘‘Examining the Growth of the Zero-Income SNAP Caseload: Characteristics, Circumstances, and Dynamics of Zero-Income SNAP Participants,’’ U.S. 

Department of Agriculture, revised October 2014. https://fns-prod.azureedge.net/sites/default/ 

files/ops/ZeroIncome-Vol2.pdf. 133 National Research Council, The Growth of Incarceration in the United States: Exploring 

Causes and Consequences, (Washington, D.C.: The National Academies Press, 2014), pp. 233– 

259. https://www.nap.edu/catalog/18613/the-growth-of-incarceration-in-the-united-states-exploring-causes. 134 Elizabeth Wolkomir, ‘‘How SNAP Can Better Serve the Formerly Incarcerated,’’ Center on 

Budget and Policy Priorities, revised March 16, 2018. https://www.cbpp.org/sites/default/files/ 

atoms/files/3-6-18fa.pdf. 135Kamala Mallik-Kane and Christy A. Visher, ‘‘Health and Prisoner Reentry: How Physical, 

Mental, and Substance Abuse Conditions Shape the Process of Reintegration,’’ Urban Institute 

Justice Policy Center, revised February 2008. https://www.urban.org/sites/default/files/publication/31491/411617-Health-and-Prisoner-Reentry.PDF. 136 Henry J. Steadman, et al., ‘‘Prevalence of Serious Mental Illness Among Jail Inmates,’’ Psychiatric Services (June 2009), pp. 1–5. https://ps.psychiatryonline.org/doi/pdf/10.1176/ 

ps.2009.60.6.761. 

Barriers to work among individuals experiencing homelessness are well-documented, including limited skills and inconsistent work histories, lack of transportation, or physical or mental health conditions.127 Those who are homeless 

may lack consistent access to resources needed to maintain personal hygiene 

and meet dress codes, and the sleep deprivation and stress of lacking housing 

may also affect these workers. People experiencing homelessness also lack access to a reliable mailing address and may not have consistent access to a 

phone or computer for job application and communication needs.128 Individuals 

who experience evictions are also more likely to be laid off, research finds.129

• Criminal records. Some childless adult SNAP participants may face additional barriers to work due to having a criminal record. For example, a study 

of childless adults referred to a work experience program in Franklin County, 

Ohio found that about 1⁄3 reported having a criminal record.130 Over 1⁄2 of SNAP 

E&T providers reported that a significant share of participants reported a criminal record as a barrier to work.131 An in-depth interview study of SNAP participants who experienced periods of time with no other income, approximately 1⁄2

of whom were ages 18 through 49 and who did not have dependent children, 

found that about 1⁄5 of study participants had a criminal record that served as 

a barrier to employment.132 While many of these studies have relatively small 

study populations and some are focused on populations who are more likely to 

have criminal justice records and are therefore not always representative samples, it is clear that there are individuals potentially subject to the time limit 

who have experience with the criminal justice system. 

Formerly incarcerated individuals face steep barriers to work, and as a result, 

on average face periods of unemployment following release. Longitudinal studies 

that have tracked prisoners upon their release, for example, find that up to 1⁄2

remain without a job 12 months after release.133 A recent CBPP paper summarizes some of this research: 134

» Studies document that the majority of individuals returning from incarceration face health conditions. For example, one study found that 1⁄2 of men and 2⁄3 of women had been diagnosed with chronic physical ailments such as asthma, diabetes, hepatitis, or HIV/AIDS.135 People leaving jail and prison are 

three to six times likelier than others to suffer from mental illness, another 

study found.136

199 

137 National Research Council, The Growth of Incarceration in the United States: Exploring 

Causes and Consequences, (Washington, D.C.: The National Academies Press, 2014), pp. 233– 

259. https://www.nap.edu/catalog/18613/the-growth-of-incarceration-in-the-united-states-exploring-causes. 138 Bruce Western, ‘‘Collateral Costs: Incarceration’s Effect on Economic Mobility,’’ The Pew 

Charitable Trusts, revised 2010. https://www.pewtrusts.org/∼/media/legacy/uploadedfiles/ 

pcs_assets/2010/collateralcosts1pdf.pdf. 139 Elizabeth Wolkomir, ‘‘How SNAP Can Better Serve the Formerly Incarcerated,’’ Center on 

Budget and Policy Priorities, revised March 16, 2018. https://www.cbpp.org/sites/default/files/ 

atoms/files/3-6-18fa.pdf. 140 NPRM, p. 984. 

» Formerly incarcerated individuals also tend to lack education and training 

sought by employers. They have an average of fewer than 12 years of education and in some cases limited cognitive capacity, a history of behavioral 

problems, or a low level of functional literacy.137 Furthermore, they miss out 

on opportunities to gain work experience while in prison, and often do not 

have access to training programs.138

» Evidence also suggests that employers are more averse to hiring those with 

criminal convictions than any other disadvantaged group, and formerly incarcerated individuals can also face occupational licensing and other restrictions.139

Unemployment Rates Significantly Overstates Jobs Available to Childless Adult 

SNAP Participants, Evidence Suggests 

The preamble to the proposed rule suggests that adding an unemployment rate 

floor to qualify for a waiver is necessary because ‘‘the Department believes a floor 

should be set for the 20 percent standard so that areas do not qualify for waivers 

when their unemployment rates are generally considered to be normal or low.’’ 140

The Department proposes this unemployment floor to interpret the statute which 

provides that states can waive areas that lack a ‘‘sufficient number of jobs to provide employment for the individuals,’’ therefore suggesting that areas with unemployment rates below the proposed threshold do have enough jobs to provide employment for the individuals who are subject to the time limit. 

A significant body of research, provided above, demonstrates why FNS’ reasoning 

is flawed and lacks transparency. The area unemployment rate is a poor proxy for 

employment opportunities available to adult SNAP participants without dependent 

children. These individuals on average are more likely than other workers to have 

limited education and skills, experience discrimination, lack geographic access to 

jobs, face housing instability, and experience other barriers to employment. Many 

of these individuals likely experience multiple barriers that affect their ability to 

find a job. For example, an African American worker with less than a high school 

education living far from available jobs with no reliable transportation options will 

likely have access to far fewer jobs than their area unemployment rate suggests. A 

rural area may have a low unemployment rate in part because of low labor force 

participation, where many have given up searching for work due to few job opportunities. Not only did FNS not provide any evidence on whether it considered research 

showing how the unemployment rate overstates jobs available based on different demographic characteristics, it also did not provide research that shows how these economic conditions may interact with each other and affect the opportunities to find 

work for the very disadvantaged population that is subject to the time limit. 

Because these adults are in many groups that have significantly higher unemployment rates than the overall unemployment rate for their area, the proposed unemployment rate floor would likely disqualify many areas where these individuals have 

few opportunities. The unemployment rate among the group of individuals subject 

to the time limit in a county with a seven percent unemployment rate is likely much 

higher than seven percent. Under the proposed regulation, states would be much 

less effective at identifying areas where there are not enough jobs for the individuals subject to the time limit, as many of these areas would have overall unemployment rates below the proposed threshold. The Department did not discuss how the 

unemployment rate relates to job availability for individuals subject to the time 

limit. It appears FNS ignored the considerable research that shows how the individuals subject to the time limit belong to demographic groups with much higher unemployment rates than the average or face barriers to accessing jobs. Without this 

research, it is difficult to understand how it came to the conclusion that a seven 

percent 2 year unemployment rate (or a 1 year unemployment rate of ten percent) 

accurately captures the number of jobs available to this population. 

200 

141 NPRM, p. 983. 142 Executive Order 12073, Federal procurement in labor surplus areas, 43 FR 36873, 3 CFR, 

1978 Comp., p. 216, https://www.archives.gov/federal-register/codification/executive-order/ 

12073.html. 143 U.S. Department of Labor, ‘‘Labor Surplus Areas: Frequently Asked Questions,’’ https:// 

www.doleta.gov/programs/lsa_faq.cfm. 144 Ibid. 145 USDA, ‘‘Guidance for States Seeking Waivers for Food Stamp Limits,’’ December 3, 1996 

and Federal Register, Vol. 66, No. 11, January 17, 2001. P. 4462. https:// 

www.federalregister.gov/d/01-1025/p-205. 146 Bureau of Labor Statistics, ‘‘Alternative Measures of Labor Underutilization for States, 

2018 Annual Averages.’’ https://www.bls.gov/lau/stalt.htm. 

C. Citation of Labor Surplus Area Unemployment Floor Inappropriate for this Population 

The Department cites the fact that the Department of Labor (DOL) has an unemployment floor in its classification of Labor Surplus Areas (LSAs) as support for its 

proposal to impose a similar floor for the purposes of waiver criteria, implying its 

approach is consistent with DOL’s. The Department, however, proposes a higher 

floor than DOL uses without providing evidence, when research suggests if anything 

the floor for this population would be substantially lower than DOL’s. The Department also fails to acknowledge that DOL uses a ten percent ceiling in its identification of LSAs, demonstrating that its citation of LSAs is either misleading or based 

on incomplete information. 

In the preamble for the rule, the Department explained how the DOL has an unemployment rate floor for Labor Surplus Areas, implying that implementing an unemployment rate floor for an area to qualify for a waiver based on having unemployment rates 20 percent above the national average would be appropriate to be consistent with DOL’s approach.141 Labor Surplus Areas are areas that DOL identifies 

as having a ‘‘surplus of labor’’ based on having an unemployment rate of 20 percent 

higher than the national average for a designated 24 month period. Federal, state, 

and local agencies use LSA designations for multiple purposes. Executive Order 

12073 required executive agencies to ‘‘emphasize procurement set asides in order to 

strengthen our nation’s economy.’’ 142 DOL lists several other agencies that use 

Labor Surplus Areas, such as ‘‘The Small Business Administration uses the LSA list 

for bid selections for small business awards in Historically Underutilized Business 

Zones (HUBZones).’’ 143

DOL has an unemployment rate floor so that the minimum unemployment rate 

used for identification of LSAs is at least six percent. DOL also has an unemployment rate ceiling; when national unemployment is high enough that 20 percent 

above the national average exceeds ten percent unemployment over 2 years, DOL 

will designate LSAs that have unemployment rates above ten percent.144 DOL also 

allows states to demonstrate that areas meet alternative criteria to demonstrate an 

exceptional circumstance, such as a recent 3 month unemployment rate at the 

threshold required for LSA designation. 

The Department established identification of Labor Surplus Areas as one of a nonexhaustive list of methods of demonstrating ‘‘insufficient jobs’’ in its original 1996 

guidance, and it was codified as an example in the final 2001 regulation.145 The 

guidance and final rule also allowed states to use similar data demonstrating unemployment rates that are 20 percent above the national average for a 24 month period. 

FNS decided, in its 1996 guidance and 2001 regulation, to include LSA designation as one of many ways that states can demonstrate that an area lacks sufficient 

jobs. This decision likely reflects the fact that unemployment rates are readily available on a monthly basis and are statistically reliable for sub-state areas. There are 

few alternative measures available at the state and local level that states can use 

to demonstrate a lack of jobs. For example, at the national and state level there are 

measures such as ‘‘alternative measures of labor underutilization,’’ a broader set of 

metrics that include ‘‘discouraged workers,’’ who are workers who want a job but 

have not recently searched for work because they believe no jobs are available to 

them, as well as others such as workers who would like to work full time but can 

only find a part-time job.146 Those metrics cannot be reliably calculated at the substate level. It is reasonable to use metrics developed by DOL for the express purposes of identifying areas with excess labor compared to jobs, given that these 

metrics can facilitate the process for states. It is also reasonable, however, to adapt 

these criteria to more accurately capture the intent of the law, which is to capture 

jobs available for a sub-population. Current regulations make such an adaptation 

by adopting the ‘‘20 percent standard’’ without a floor. 

201 

147 NPRM, p. 984. 148Department of Labor, ‘‘Labor Surplus Area Classification under Executive Orders 12073 

and 10582 2012,’’ https://www.doleta.gov/lsa/Archived/2011-2012/Federal_Register_ 

2012_Final.pdf. 149Department of Labor, ‘‘Labor Surplus Area Classification under Executive Orders 12073 

and 10582 2013’’ https://www.doleta.gov/lsa/Archived/2012-2013/Federal_Register_ 

2013_Final.pdf; Department of Labor, ‘‘Labor Surplus Area Classification under Executive Orders 12073 and 10582 2014,’’ https://www.doleta.gov/lsa/Archived/2013-2014/2013- 

2014_LSA_Federal_Register_Notice.pdf. 

In proposing to use a similar unemployment floor to that used by DOL in the LSA 

designation, the Department does not consider that while a specific floor may be appropriate for DOL’s purposes in establishing LSAs, the waiver criteria are meant 

to represent a fully distinct concept from LSAs and therefore adapting them to the 

different purpose of waiver criteria is necessary and appropriate. The Department 

correctly notes that waiver criteria do not currently require an area to meet a specific threshold if the area’s unemployment rate is above the national average, unlike 

the LSA criteria. 

These measures are meant to serve different purposes, however: 

• The suggested criteria for waivers of the time limit are meant to establish a 

lack of ‘‘sufficient jobs’’ for a specific sub-population, childless adult SNAP participants, which faces labor market disadvantages. As noted in section B above, 

childless adult SNAP participants belong to groups that have higher unemployment rates than their local area, which makes defining a specific unemployment 

rate at which those individuals have access to enough jobs difficult, if not impossible. For example, since this group may experience unemployment rates 

that are double the rates of their area, a six percent or seven percent unemployment rate ‘‘floor’’ would mean a 12 or 14 percent unemployment rate for this 

group of individuals. At any unemployment rate threshold, it is likely that large 

groups of childless adult SNAP participants would not have access to available 

jobs given their serious barriers to work. Given the uncertainty and difficulty 

in establishing whether there are jobs available for this population, not requiring a specific unemployment rate threshold appropriately allows for greater 

flexibility in determining areas with insufficient jobs. 

• LSAs, on the other hand, establish the economic condition of an area to enable 

prioritization of procurement contracts and economic development purposes. In 

creating the threshold for LSAs, DOL does not need to consider whether jobs 

are available for specific types of individuals, and instead is focused on understanding the macroeconomic conditions of an area in order to direct economic 

stimulus. It therefore may be reasonable for the Department of Labor to establish specific thresholds that meet those criteria for those purposes, given that 

the criteria attempt to establish levels at which economic stimulus is needed. 

In citing Labor Surplus Areas as a reason to implement an unemployment rate 

floor, the Department also fails to acknowledge the unemployment rate ceiling that 

DOL uses in LSA designation. Not only does DOL have an unemployment rate floor 

of six percent unemployment in its criteria for LSA designation, it also has an unemployment rate ceiling of ten percent unemployment. This means that when designating LSAs, the unemployment rate threshold DOL uses is 20 percent above the 

national average but not more than ten percent. The Department not only does not 

acknowledge this fact, it suggests this unemployment rate as a possible floor for the 

time limit: 

The Department would also like to receive comments on establishing a floor 

of ten percent for the 20 percent standard. A ten percent floor would allow for 

even fewer waivers than the other options and would result in the work requirements being applied in almost all areas of the country.147

DOL establishes this unemployment rate ceiling for LSA designation in recognition that a sustained level of unemployment at ten percent is adequately high to 

demonstrate that an area has severe labor market weakness. These criteria ensure 

that during times of widespread elevated unemployment, areas can qualify without 

having exceptionally high unemployment rates. For example, the LSA list in Fiscal 

Year 2012 was based on unemployment rates between January 2009 and December 

2010, during the height of the Great Recession when national unemployment was 

9.5 percent, and 20 percent above that would have been 11.4 percent.148 Areas were 

also eligible in Fiscal Year 2013 and Fiscal Year 2014 with ten percent unemployment for the same reason.149 Without a ceiling, many areas that were struggling 

202 

150 NPRM, p. 984. 

during the height of the recession and recovery would have been ineligible for LSA 

designation. 

FNS therefore is proposing to pick and choose which features of LSA designation 

to adapt to the proposed regulation without discussion of why it made this choice, 

or even acknowledgement of this choice. The Department proposes on one hand to 

implement an unemployment rate floor for an area to qualify under the ‘‘20 percent 

standard,’’ but does not propose a similar unemployment rate ceiling. In fact, the 

Department proposes what DOL recognizes as a sufficiently high unemployment 

rate to qualify for a ceiling, ten percent unemployment, as a possible unemployment 

rate floor. The Department therefore proposes to ensure that unemployment rates 

in an area must meet a standard to demonstrate they are high but is not proposing 

a means of limiting this threshold during a recession to ensure that the unemployment rate threshold does not provide too high a bar that it would substantially bar 

areas suffering from a recession. The Department does not explain why it chose to 

adopt an unemployment rate floor similar to that used in LSA criteria but not an 

unemployment rate ceiling, and it does not mention the LSA ceiling. This oversight 

is particularly perplexing given our research review which indicates if anything, the 

LSA criteria as is are very stringent for waiver criteria given the barriers to employment childless adult SNAP participants face, which would recommend no floor or 

a very low floor if any at all. 

Without any explanation, it appears that by imposing a floor and not a ceiling 

for the 20 percent standard, the Department considers for the purposes of measuring whether an area lacks adequate jobs for childless adult SNAP participants 

that there is a level of unemployment that is low enough to ensure that adequate 

jobs are available, but not a level high enough to signify that there likely are not 

enough jobs. Again, without this information, it is difficult to assess the evidence 

that the Department used in proposing an unemployment rate floor, especially given 

that the Department’s choice seems to contradict all available economic evidence indicating that unemployment rates are a poor proxy for jobs for this population. 

D. Citation of ‘‘Natural Rate of Unemployment’’ Incorrectly Assumes This Is a Fixed 

and Accurately Measurable Concept 

The Department uses the macroeconomic concept of the ‘‘natural rate of unemployment’’ to justify its proposed unemployment rate threshold. This use of this concept inappropriately applies a macroeconomic concept and inaccurately displays economic consensus. The preamble states: 

The Department believes a floor should be set for the 20 percent standard so 

that areas do not qualify for waivers when their unemployment rates are generally considered to be normal or low. The ‘‘natural rate of unemployment’’ is 

the rate of unemployment expected given normal churn in the labor market, 

with unemployment rates lower than the natural rate tending to result in inflationary pressure on prices. Thus, unemployment rates near or below the ‘‘natural rate of unemployment’’ are more indicative of the normal delay in unemployed workers filling the best existing job opening for them than a ‘‘lack of sufficient jobs’’ in an area. Generally, the ‘‘natural rate of unemployment’’ hovers 

around five percent. The Department believes that only areas with unemployment rates above the ‘‘natural rate of unemployment’’ should be considered for 

waivers.150

The Department appears to be suggesting that the natural rate of unemployment 

is a specific unemployment rate figure that can be used in setting a waiver floor 

to examine job opportunities for childless adult SNAP participants. This reasoning 

is deeply flawed. 

First, the so-called natural rate of unemployment is not a known or even an observable jobless rate. It is a concept that derives from the theoretical construct that 

there exists an unemployment rate that is consistent with stable inflation. If unemployment falls below this ‘‘natural rate,’’ inflation would rise, and vice versa. More 

colloquially, too low an unemployment rate, where ‘‘too low’’ means the actual rate 

is below the natural rate, and the economy will overheat; too high a jobless rate 

relative to the natural rate and inflation will fall. 

In theory, an estimate of the natural rate should be derivable from observing the 

(negative) correlation between changes in the rate of unemployment and that of inflation. However, because this correlation appears to have moved toward zero over 

time, our ability to reliably identify a policy-relevant natural rate, meaning one that 

could fruitfully be referenced as the Department suggests in terms of their proposal, 

is much diminished. 

203 

151 Neil Irwin, ‘‘How Low Can Unemployment Really Go? Economists Have No Idea,’’ New 

York Times, Feb. 28. 2018, https://www.nytimes.com/2018/02/28/upshot/how-low-can-unemployment-really-go-economists-have-no-idea.html. 

Note, for example, a recent article about this problem by economics journalist Neil 

Irwin. In the article, former Fed Vice-Chairman Alan Blinder notes that the ‘‘confidence interval’’—the band of statistical uncertainty around the estimate—is such 

that the concept cannot be usefully employed as a policy benchmark: ‘‘If your range 

is 2.5 to 7, that doesn’t tell you anything.’’ 151

Figure 3.3 below reveals the problem using a standard statistical procedure to 

measure the inflation/unemployment correlation. The figure represents the coefficient from a regression of core inflation on lagged inflation and the gap between the 

unemployment rate and the Congressional Budget Office’s estimate of the natural 

rate. The estimates are made using ‘‘rolling regressions,’’ meaning we estimate the 

model over 20 year periods, beginning with 1959–79, and advance the sample 1 year 

at a time. We then plot the coefficient on the unemployment gap variable. 

In this area of economics, the measure is considered to be the slope of the Phillips 

Curve, which is the curve that plots the unemployment/inflation tradeoff. The two 

lines surrounding the estimate represent the bounds of a 95 percent confidence interval around the estimate. When these lines include zero, as they do for most of 

the figure, the estimate of the slope is insignificant. In other words, in these years, 

the ‘‘natural rate’’ cannot be reliably distinguished from a range of rates that includes zero. 

Figure 3.3 

The ‘‘Natural Rate’’ of Unemployment Is Not Identifiable 

Source: CBPP Analysis of Congressional Budget Office, Bureau of Labor 

Statistics, and Bureau of Economic Analysis Data. 

In other words, at least by this conventional approach, the Department cannot reliably use five percent (or any other level) as an estimate of the natural rate, because the diminished correlation between unemployment and inflation renders such 

an estimate statistically insignificant. 

Department Proposes Arbitrary Unemployment Rate Floor 

Not only does the Department improperly support its proposed unemployment 

rate floor with a flawed discussion of the ‘‘natural rate of unemployment,’’ it proposes a floor that is arbitrarily and significantly higher than what it states is the 

unemployment rate consistent with the natural rate of unemployment. The Department proposes an unemployment rate floor that is 40 percent above what it states 

is ‘‘generally’’ considered the natural rate of unemployment, of five percent. This difference is not insignificant. With a labor force of about 160 million people, a difference of two percentage points is equivalent to more than three million people nationwide, employed or not. In a recent 24 month period of January 2017 through 

December 2018, 795 counties (or equivalent entities) had unemployment rates above 


11602066.eps
204 

152The results are very similar: blacks, 13.5 percent; Hispanics, ten percent—when looking 

at minority unemployment rates conditional on the 2 year average of overall unemployment centered on seven percent to more closely simulate the proposed rule. 

five percent, while only 155 counties had 24 month unemployment rates above seven 

percent. 

Considering the difference between those two metrics, it is not clear how the Department used the concept of the natural rate in developing this floor. These two 

unemployment rates, five and seven percent, are so different that it is difficult to 

understand how they are linked without more information. Furthermore, if the Department were actually basing the proposed unemployment rate floor on a concept 

that describes the level of unemployment at which inflation increases, it would need 

to demonstrate how this concept relates to the specific population or the purpose 

of establishing waiver criteria, which is to interpret the ‘‘insufficient jobs’’ criterion 

in the law targeted towards a disadvantaged group of individuals. 

The Department’s proposal for this seven percent unemployment floor therefore 

suggests that it did not in fact use the natural rate of unemployment to develop the 

seven percent unemployment rate floor proposal. Either the Department used economic data relating the goals of the unemployment rate floor to the natural rate, 

in which case it lacked transparency by not providing this research, or the rate is 

an arbitrary selection unrelated to the statute that the rule is interpreting, in which 

case the discussion of the natural rate is irrelevant to the actual proposal. Without 

an explanation of how and why the Department used the natural rate concept to 

come up with a seven percent unemployment rate floor that is related to the 

purposed of the underlying statute, it is impossible to meaningfully comment. 

E. Evidence Suggests That a Seven Percent Unemployment Floor Is Inappropriately 

High for This Population 

Not only does the Department not provide economic evidence to support its proposed seven percent floor, evidence shows why this floor would be inappropriate for 

this population. While this comment argues that we cannot assume that any particular unemployment floor will provide the necessary labor market opportunities to 

some groups of workers, the proposed floor of seven percent is surely too high. As 

Figure 3.4 below shows, using national BLS data, there were 106 months since 1972 

when the overall unemployment was between 6.5 and 7.5 percent. The average rate 

was 7.1 percent, about the level of the proposed floor. But unemployment for African 

American and Latino workers was a much higher 13.9 percent and 10.2 percent. 

White unemployment was 6.2 percent.152

Figure 3.4 

A 7 Percent Unemployment Floor Is Substantially Higher for Black and 

Latino Workers 

Unemployment rates by race/ethnicity when national unemployment is between 6.5 

and 7.5 percent 

Source: Bureau of Labor Statistics, 1972–2018. 


11602067.eps
205 

153 U.S. Census Bureau, American Community Survey Table S2201. The United States has 

389 metropolitan areas overall, without regard to unemployment rate. 154To further increase reliability, we impose two additional requirements on the comparisons. 

First, subgroup unemployment rates in a given metropolitan area are only included in our analysis if they are statistically significantly higher than the overall unemployment rate for the 

area. Second, we only include estimated unemployment rates that are at least twice as large 

as their margins of error. 

Consider that at the depth of the Great Recession (2009–10), broadly recognized 

as the deepest recession since the Depression, the overall unemployment rate hit 

ten percent. This was widely, and correctly, seen as evidence of a huge, negative 

demand shock, one requiring an aggressive response from both fiscal and monetary 

authorities. And yet, the proposal suggests an unemployment floor that corresponds 

historically to a black unemployment rate well above the overall rate at the worst 

of the recession. 

Other rates that have been floated suffer from the same problem that even in the 

best of overall labor markets, certain groups face a much less welcoming set of job 

opportunities. Table 3.1 below shows the results from a simple regression of total 

rates on a constant and rates for black and Latino workers. Even at five percent 

unemployment, the African American jobless rate is predicted to be almost ten percent, and the Latino rate is at seven percent. At rates above seven percent, both 

black and Latino workers have jobless rates close to and in double digits. 

Table 3.1 

Unemployment Rates and Predicted Black and Latino Unemployment 

Unemployment 

Predicted Unemployment Rates 

Black Latino 

5% 9.6% 7.0% 

7% 13.2% 9.8% 

10% 18.5% 13.9% 

Note: Black and Latino unemployment rates are predicted by regressing total unemployment 

rate on race-specific rates. 

Turning from minorities to other less advantaged groups in the labor market reveals similarly wide disparities between their unemployment rates and the floor in 

the proposed rule. 

• Since 2008, the BLS has tracked unemployment among those who self-report 

as disabled. In months when the unemployment rate averaged seven percent, 

the disabled rate was 13 percent. 

• Doing the same comparison by education level (for job seekers 25 and older, per 

BLS published data), yields jobless rates of 11 percent for those with less than 

high school degrees. 

F. Local Areas With High Unemployment Rates for Sub-Groups 

We can also see how in local areas, when the overall unemployment rate is five, 

six, or seven percent, some sub-groups face much higher unemployment rates. Of 

the 239 large labor market areas (metropolitan areas) with average overall unemployment rates below seven percent,153 85 have unemployment rates that are at 

least 14 percent for particularly vulnerable groups, such as adults ages 25 to 64 

with very low education, people with self-reported disabilities, and/or black and 

Latino residents. The data this analysis includes are published Census Bureau figures from the American Community Survey and average together 5 years of data 

from 2013 through 2017 in order to increase reliability.154

15 metropolitan areas in 2013–2017 had unemployment rates of seven percent or less overall but at least 14 percent for the least educated workers. 

For example, in the Springfield, IL metro area, for example, the overall unemployment rate was 6.7 percent, but was 21.2 percent for those with less than a highschool diploma. (Table 3.2.) 

206 

Table 3.2 

Metropolitan Areas With 5 Year Average Unemployment Rates Less Than 7 

Percent Overall but Greater Than or Equal to 14 Percent for Workers 

With Less Than a High School Education 

State Metropolitan Area 

Overall 

Unemployment Rate 

for Population 16 

Years and Over 

Unemployment Rate 

for Workers With 

Less Than High 

School 

Education 

FL Pensacola-Ferry Pass-Brent, FL 6 .9 16 .3 

ID Pocatello, ID 6 .3 15 .2 

IL Springfield, IL 6 .7 21 .2 

IL Peoria, IL 6 .6 15 .6 

IN Kokomo, IN 6 .5 14 .2 

KY Elizabethtown-Fort Knox, KY 6 .7 16 

MI Kalamazoo-Portage, MI 6 .6 17 .2 

MI Monroe, MI 5 .9 16 .7 

MO–IL St. Louis, MO–IL 6 .3 14 .7 

NY Syracuse, NY 6 .6 14 .4 

NY Elmira, NY 5 .3 14 .5 

OH Canton-Massillon, OH 6 .6 15 .7 

OH–PA Youngstown-Warren-Boardman, OH–PA 6 .9 14 .1 

VA Blacksburg-Christiansburg-Radford, VA 5 .2 15 .5 

WV Parkersburg-Vienna, WV 6 .1 17 .3 

59 metro areas in 2013–2017 had unemployment rates of seven percent or 

less overall but at least 14 percent for workers with any disability. For example, in the Peoria, IL metro area, the overall unemployment rate was 6.6 percent, but was 18.4 percent for those with any disability. (Table 3.3.) 

Table 3.3 

Metropolitan Areas With 5 Year Average Unemployment Rates Less Than 7 

Percent Overall but Greater Than or Equal to 14 Percent for Workers 

With Any Disability 

State Metropolitan Area 

Overall 

Unemployment Rate 

for Population 16 

Years and Over 

Unemployment Rate 

for Workers With a 

Disability 

AL Florence-Muscle Shoals, AL 6 .7 16 .3 

AL Decatur, AL 6 .6 17 .6 

AL Birmingham-Hoover, AL 6 .8 15 .4 

AL Daphne-Fairhope-Foley, AL 5 .5 14 .3 

CA Santa Maria-Santa Barbara, CA 6 .6 14 .5 

CA Salinas, CA 6 14 .4 

CA Napa, CA 5 .4 16 

CT Hartford-West Hartford-East Hartford, 

CT 6 .8 15 .6 

DE Dover, DE 6 .7 14 .9 

FL Deltona-Daytona Beach-Ormond Beach, 

FL 6 .7 15 .6 

FL Gainesville, FL 6 .7 14 .4 

FL Pensacola-Ferry Pass-Brent, FL 6 .9 15 .1 

FL Tampa-St. Petersburg-Clearwater, FL 6 .8 16 .2 

FL Orlando-Kissimmee-Sanford, FL 6 .8 15 .1 

FL North Port-Sarasota-Bradenton, FL 6 .1 14 .9 

ID Pocatello, ID 6 .3 15 .3 

IL Springfield, IL 6 .7 17 .4 

IL Peoria, IL 6 .6 18 .4 

IL Champaign-Urbana, IL 5 .2 14 .2 

IN Fort Wayne, IN 5 .9 14 

KY–IN Louisville/Jefferson County, KY–IN 6 14 

LA Houma-Thibodaux, LA 6 .5 16 .2 

LA Shreveport-Bossier City, LA 6 .8 15 .6 

LA Baton Rouge, LA 6 .7 14 .9 

MA–CT Worcester, MA–CT 6 .3 14 .5 

MD Baltimore-Columbia-Towson, MD 6 14 .8 

ME Lewiston-Auburn, ME 5 .2 15 .2 

ME Bangor, ME 6 .5 18 .1 

MO Springfield, MO 5 .2 14 

MO–IL St. Louis, MO–IL 6 .3 14 .2 

207 

Table 3.3—Continued 

Metropolitan Areas With 5 Year Average Unemployment Rates Less Than 7 

Percent Overall but Greater Than or Equal to 14 Percent for Workers 

With Any Disability 

State Metropolitan Area 

Overall 

Unemployment Rate 

for Population 16 

Years and Over 

Unemployment Rate 

for Workers With a 

Disability 

MO–IL Cape Girardeau, MO–IL 5 .4 14 .7 

NC Burlington, NC 6 15 .2 

NC Greensboro-High Point, NC 6 .6 15 .2 

NC Durham-Chapel Hill, NC 6 14 .1 

NY Utica-Rome, NY 6 .5 17 .2 

NY Syracuse, NY 6 .6 15 .4 

NY Rochester, NY 6 .3 14 .8 

NY Ithaca, NY 4 .8 14 

NY–NJ–PA New York-Newark-Jersey City, NY–NJ– 

PA 6 .9 14 .5 

OH Canton-Massillon, OH 6 .6 14 .9 

OH–KY–IN Cincinnati, OH–KY–IN 5 .8 14 

OH–PA Youngstown-Warren-Boardman, OH–PA 6 .9 14 .5 

OR Corvallis, OR 6 .7 14 .1 

OR–WA Portland-Vancouver-Hillsboro, OR–WA 6 .2 14 .5 

PA Pittsburgh, PA 5 .7 14 .4 

PA–NJ Allentown-Bethlehem-Easton, PA–NJ 6 .7 14 .1 

RI–MA Providence-Warwick, RI–MA 6 .9 15 .9 

TX Sherman-Denison, TX 6 .5 14 .7 

TX Tyler, TX 6 .5 15 .8 

TX Waco, TX 5 .2 14 .7 

VA Richmond, VA 6 .3 14 .3 

VA Roanoke, VA 5 .4 14 .6 

VA Blacksburg-Christiansburg-Radford, VA 5 .2 16 .1 

WA Walla Walla, WA 6 .1 14 

WA Kennewick-Richland, WA 5 .9 15 .1 

WI Sheboygan, WI 4 .4 15 .4 

WI Janesville-Beloit, WI 6 .4 14 .1 

WI–MN La Crosse-Onalaska, WI–MN 4 .4 14 .9 

WV–KY–OH Huntington-Ashland, WV–KY–OH 6 .6 16 

29 metro areas in 2013–2017 had unemployment rates of seven percent or 

less overall but at least 14 percent for African American residents. For example, in the Canton-Massillon, OH metro area, the overall unemployment rate 

was 6.6 percent, but was 16.9 percent for black workers. (Table 3.4.) 

Table 3.4 

Metropolitan Areas with 5 Year Average Unemployment Rates Less Than 7 

Percent Overall but Greater Than or Equal to 14 Percent for Black/African American Subgroup 

State Metropolitan Area 

Overall 

Unemployment 

Rate for Population 

16 Years and Over 

Black/African 

American 

Unemployment Rate 

AR Jonesboro, AR 5.9 14 .3 

IA Dubuque, IA 3.9 17 

IA Waterloo-Cedar Falls, IA 4.9 19 .7 

IL Springfield, IL 6.7 16 .4 

IL Peoria, IL 6.6 18 .1 

IN Elkhart-Goshen, IN 5.6 15 

IN Terre Haute, IN 6.9 16 .9 

IN Fort Wayne, IN 5.9 15 .2 

IN–MI South Bend-Mishawaka, IN–MI 6.6 14 .3 

KY Owensboro, KY 6.1 15 .6 

MA Pittsfield, MA 6.8 19 .6 

ME Lewiston-Auburn, ME 5.2 17 .7 

ME Bangor, ME 6.5 28 .9 

MI Kalamazoo-Portage, MI 6.6 15 .3 

MN Mankato-North Mankato, MN 4.2 23 .3 

MN Rochester, MN 3.9 20 .2 

MN St. Cloud, MN 4.5 17 .2 

NY Utica-Rome, NY 6.5 15 .2 

208 

155The U.S. Department of Labor estimates 7.7 million persons (or about 14.2 percent) were 

unemployed in 1937 out of a labor force of 54.0 million. U.S. Department of Labor, ‘‘Labor Force, 

Employment, and Unemployment, 1929–39: Estimating Methods,’’ Technical Note, Monthly 

Labor Review, July 1948, https://www.bls.gov/opub/mlr/1948/article/pdf/labor-force-employment-and-unemployment-1929-39-estimating-methods.pdf. 

Table 3.4—Continued 

Metropolitan Areas with 5 Year Average Unemployment Rates Less Than 7 

Percent Overall but Greater Than or Equal to 14 Percent for Black/African American Subgroup 

State Metropolitan Area 

Overall 

Unemployment 

Rate for Population 

16 Years and Over 

Black/African 

American 

Unemployment Rate 

NY Syracuse, NY 6.6 15 .1 

NY Rochester, NY 6.3 14 .8 

OH Canton-Massillon, OH 6.6 16 .9 

OH–PA Youngstown-Warren-Boardman, OH–PA 6.9 17 .2 

PA Altoona, PA 5.2 18 .7 

PA Scranton-Wilkes-Barre-Hazleton, PA 6.4 19 .2 

PA Pittsburgh, PA 5.7 14 .1 

PA Williamsport, PA 6.2 23 

WI Janesville-Beloit, WI 6.4 17 

WI Green Bay, WI 4.4 18 .1 

WV–OH Wheeling, WV–OH 6.1 15 .8 

Six metro areas had unemployment rates of seven percent or less overall 

but at least 14 percent for Hispanic or Latino adults. For example, in the 

Bloomsburg-Berwick, PA metro area, the overall unemployment rate was 4.9 percent, but it was 26.9 percent for Hispanic/Latino workers (who may be of any race). 

(Table 3.5.) 

Table 3.5 

Metropolitan Areas With 5 Year Average Unemployment Rates Less Than 7 

Percent Overall but Greater or Equal to 14 Percent for Latino/Hispanic 

Subgroup 

State Metropolitan Area 

Overall 

Unemployment 

Rate for Population 

16 Years and Over 

Hispanic or Latino 

Unemployment 

Rate 

NY Utica-Rome, NY 6.5 15.5 

OH Canton-Massillon, OH 6.6 20.1 

PA Bloomsburg-Berwick, PA 4.9 26.9 

PA Erie, PA 6.5 15.8 

PA Chambersburg-Waynesboro, PA 5.7 14.8 

PA Lebanon, PA 5.8 14.2 

Fourteen percent unemployment, averaged over 5 years, is a strikingly high rate 

that matches the unemployment rate estimated for the overall labor force in 1937 

during the Great Depression.155 Under the proposed rule, some communities would 

be ineligible for a waiver where some individuals subject to the time limit are likely 

to face unemployment rates of this level. 

A recent analysis by the Center on Poverty and Social Policy at Columbia University also demonstrates how sub-populations face significantly higher unemployment 

rates than the area average. This analysis looked at over 200 metropolitan areas 

that could potentially lose waiver eligibility: areas with unemployment rates 20 percent above the national average, but below seven percent unemployment rates. As 

the authors stated: 

The median unemployment rate for non-white individuals is closer to ten percent, and in some metro areas the unemployment rate is greater than 20 percent for non-white individuals. For those with a high school education or less, 

over 3⁄4 of all metropolitan areas have a higher unemployment rate than the 

seven percent floor, which is a particularly dire statistic for the relevant population of ‘‘lower-skilled’’ workers. Given that close to 3⁄4 of ‘‘ABAWDs’’ have a 

high school education or less and close to 1⁄2 are non-white, this evidence suggests that the proposed rule would disqualify many areas where the individuals 

209 

156 Robert Paul Hartley, Christopher Wimer, and Jane Waldfogel, ‘‘Limiting States’ Ability to 

Waive Federal SNAP Work Requirements: A Closer Look at the Potential Implications,’’ Columbia University Center on Poverty and Social Policy Research Brief, Vol. 3 No. 4, March 25, 2019. 

https://static1.squarespace.com/static/5743308460b5e922a25a6dc7/t/5c9a2d43652dea22023c 

9492/1553608003521/Poverty+%26+Social+Policy+Brief+3_4_+SNAP+Work+Requirements+ 

and+Unemployment.pdf. 157 Economic Innovation Group, ‘‘From Great Recession to Great Reshuffling: Charting a Decade of Change Across American Communities,’’ October 2018, https://eig.org/wp-content/ 

uploads/2018/10/2018-DCI.pdf. 

subject to the time limit face substantially higher unemployment rates than 

seven percent. 

This analysis also looked at complementary labor force metrics, finding that nonwhite individuals and workers with a high school education or less had significantly 

lower employment-population ratios, with over 1⁄2 of individuals with less education 

living in areas with employment-population ratios lower than 50 percent. This research shows how the unemployment rate hides the variation for sub-groups.156 We 

strongly encourage FNS to review these data. 

Given this evidence, the proposal to restrict states’ ability to waive areas except 

with very high overall unemployment rates will have a disproportionate impact on 

subgroups with rates much higher than overall unemployment, including groups belonging to protected classes under 7 U.S.C. § 2020(c). 

Many ‘‘Distressed Communities’’ Have Relatively Low Unemployment 

Another way of considering how areas with relatively low unemployment may provide insufficient jobs for individuals subject to the time limit is to look at other economic indicators, which provide other information that could indicate a paucity of 

jobs. The nonprofit organization Economic Innovation Group calculates a measure 

of community well-being called the ‘‘Distressed Community Index’’ that combines 

seven metrics for the 2012–2016 period: the share of adults ages 25 and up without 

a high school diploma; the percent of habitable housing that is unoccupied; the 

share of the prime-age (25–64) population that is not employed; the poverty rate; 

median household income as a percent of the state’s median households income; the 

change in employment; and the change in business establishments. 

While these measures do not strictly measure job availability, they do provide a 

snapshot of economic health, and present a snapshot of how divergent the economic 

conditions are, and recovery from the Great Recession has been, at the local level. 

For example, most of the job growth from 2007 to 2016 has occurred in the [ZIP 

C]odes in the top quintile of the index. Over 2⁄3 of [ZIP C]odes in that quintile, 

termed ‘‘prosperous,’’ added jobs since 2007 (adding an average of 1,300 jobs); meanwhile, over 2⁄3 of [ZIP C]odes in the lowest quintile, called ‘‘distressed,’’ have fewer 

jobs since 2007, and those that did add jobs only added an average of 400 over the 

period studied. While about 1⁄5 of prime-age adults were out of work in ‘‘prosperous’’ 

[ZIP C]odes, that share was double for adults in ‘‘distressed’’ [ZIP C]odes.157

We looked at counties that had a waiver in 2018 but would not have qualified 

if the proposed rule were in place because they did not meet the seven percent unemployment rate threshold. Of these over 600 counties, over 100 were considered 

‘‘distressed.’’ Todd County, South Dakota, for example, had a 6.6 unemployment rate 

for the January 2016–December 2017 period. According to this index, nearly 1⁄2 of 

the residents in this county lived in poverty in the 2012–2016 period, and close to 

1⁄2 of prime-age adults were not employed. The number of jobs in this county declined by over 2⁄5 from 2012 to 2016, and the number of business establishments 

also declined by over five percent. Another example is Stewart County, Georgia, 

where over 1⁄3 of adults have less than a college degree, household median income 

is only about 2⁄5 of the state’s median income, and over 2⁄3 of prime-age adults are 

not employed. Stewart County also lost both jobs and business establishments between 2012 and 2016. 

While an area’s unemployment rate may mask differences between unemployment 

rates within that area, it also may fail to reflect economic conditions more broadly, 

which may contribute to job availability for the individuals potentially subject to the 

time limit. Here again, we are concerned that FNS did not appear to offer any evidence to support its contention that unemployment rates are a reliable predictor of 

jobs available for low-income individuals. 

Underemployment Rates Also Higher For Sub-Groups 

Along with the impossibility of identifying an unemployment rate that reliably implies the absence of available jobs, it is also the case that the unemployment rate 

is an insufficient indicator of labor market slack. For one, it leaves out those who 

210 

158 ‘‘National Bureau of Labor Statistics, U.S. Business Cycle Contractions and Expansions,’’ 

https://www.nber.org/cycles.html. Monthly unemployment rates are from BLS. 159 NPRM, p. 992. 

have left the labor market, in some cases due to slack labor demand or to personal 

labor market barriers, including skill deficits and discrimination. Second, the unemployment rate leaves out a significant group of part-time workers who would prefer 

to be full-timers. Such workers are literally under-employed, as they want to work 

more hours than their current job offers them. For families with low incomes, working too few hours can put pressure on family budgets and lead to nutritional hardship. 

Table 3.6 shows underemployment rates associated with unemployment rates of 

five, seven, and ten percent for all workers and by race/ethnicity (see note under 

the table for methodology). At the proposed rule’s suggested level of seven percent 

unemployment, overall underemployment is predicted to be 12.5 percent, with rates 

of about 20 and 18 percent for African American and Latino workers, respectively. 

In other words, the rule suggests that SNAP waivers should be disallowed in places 

where about 1⁄5 of black and Latino workers could be un- or underemployed. 

Higher unemployment of course corresponds to even higher underemployment 

rates, but even at five percent unemployment, black and Latino underemployment 

is around 15 and 13 percent, respectively. 

Table 3.6 

Predicted Underemployment Rates at Different Unemployment Rates, by 

Race/Ethnicity 

Unemployment 

Predicted Underemployment 

All White Black Hispanic 

5% 9.1% 7.4% 14.9% 13.0% 

7% 12.5% 10.2% 20.4% 17.9% 

10% 17.7% 14.4% 28.8% 25.2% 

Note: Rates for ‘‘all’’ are derived from regression of U–6 underemployment rate on the overall 

unemployment rate. Racial underemployment rates are then derived from ratios of the overall 

unemployment to underemployment rates by race using Economic Policy Institute data from 

1994–2018. 

While the ‘‘20 percent standard’’ currently uses unemployment rates, which do not 

capture aspects such as labor force participation or part-time work, FNS proposes 

making these criteria even less responsive to economic conditions by requiring a 

specific unemployment rate. Given the severe racial disparities that exist in labor 

force measures, the fact the Department did not address whether it considered how 

an unemployment rate varies in relation to other labor force metrics is another reason why we cannot comment on how it supported this rule. 

G. Unemployment Rate Floor of Seven Percent Fails to Protect Areas During Recessions 

The Department does not discuss how the seven percent unemployment rate floor 

would affect waiver eligibility during an economic downturn, or at any other point 

in the business cycle besides a time of relatively low unemployment. An unemployment rate of seven percent is relatively high for any area; for example, during the 

2001 recession, the national unemployment rate never reached seven percent.158 An 

area with a 24 month unemployment rate averaging at least seven percent signifies 

that an area has experienced a prolonged depression. The Department does not acknowledge the unemployment rate of seven percent in relation to other economic indicators, but also does not discuss how the length of time its proposal would require 

such a high unemployment rate to qualify for a waiver would affect states entering 

an economic recession. 

When unemployment rates rise rapidly when the economy is entering into a recession and jobs are quickly declining, individuals likely face many challenges finding 

or keeping work. By requiring a very high 2 year average unemployment rate, the 

proposed rule, however, would keep many areas from qualifying for a waiver during 

this time. The proposed rule would continue to allow an area to qualify for a waiver 

when it qualifies under any of the criteria (including optional criteria) for Extended 

Benefits (EB) in the Unemployment Insurance program, which would often allow 

states with rapidly rising unemployment to qualify for a waiver.159 Among other criteria, under EB, states can qualify for a waiver if they meet optional indicators that 

211 

160While the criteria mentioned are the criteria to establish additional weeks of Extended 

Benefits under an optional trigger (called the Total Unemployment Rate trigger), FNS guidance 

establishes that states only have to qualify based on the unemployment measures, even if the 

state chooses not to provide EB benefits under these criteria. 161Oregon would not have qualified for a 2008 waiver. 162 In November 2008, Congress passed a temporary expansion of Extended Benefits, called 

the Emergency Unemployment Compensation program, that in January 2009 the Bush Administration stated could qualify states for a 1 year statewide waiver. These states would have qualified for statewide waivers immediately then, as both qualified beginning with the first EUC trigger notice November 23, 2008 (https://oui.doleta.gov/unemploy/euc_trigger/2008/euc_ 112308.pdf). In addition, Congress passed the American Recovery and Reinvestment Act 

(ARRA), which waived all states statewide beginning in April 2009. Because these are both temporary measures requiring action by Congress, there is no guarantee under the proposed rule 

that they would be available in the future, and as we note, they weren’t available in the beginning of the recession in early 2008. 163 NPRM, p. 981. 

include a 3 month unemployment rate of 6.5 percent that is at least 110 percent 

of the same 3 month period in either of the previous 2 years.160 We agree with the 

Department’s proposal to continue to allow states to request waivers when they 

qualify for EB, as these are times when unemployment rates are high and rising 

and individuals likely have difficulty finding jobs. Because the seven percent unemployment rate floor is so high and because the NPRM would prohibit states from 

requesting statewide waivers based on the 20 percent standard, many states would 

experience a gap between when their unemployment rates begin to rise during a recession and when they qualify for a waiver based on meeting the EB criteria. 

For example, consider the experience of two states, South Carolina and Oregon, 

who would have been left with a gap between their unemployment rates rising and 

their qualification for a waiver based on the EB criteria in the beginning of the 

Great Recession. During the beginning of the Great Recession, which officially started in December 2007, these states both had unemployment rates that were rising 

and would have qualified for 2007 statewide waivers under the existing 20 percent 

standard (as in, without the seven percent unemployment rate floor).161 These 

states, like others, would have had to wait several months before they would have 

qualified for a waiver under Extended Benefits: South Carolina qualified for a waiver based on Extended Benefits beginning in August 2008 and Oregon qualified for 

a waiver based on Extended Benefits in November 2008.162 Under the proposed 

rule, they could not have requested statewide waivers based on the ‘‘20 percent 

standard,’’ as we discuss in Chapter 5, as the rule would only allow statewide waivers based on EB. Even if they could have requested statewide waivers, however, 

these states would have been well into the recession before they qualified for a waiver based on having 24 month unemployment rates above seven percent. Therefore, 

under the proposed rule, at least some areas in both states would have been ineligible for a waiver at a time when unemployment was high and rising. 

The Department repeatedly explains how its rulemaking would prevent states 

from requesting waivers when unemployment is low. For example, it states: 

Right now, nearly 1⁄2 of ABAWDs live in areas that are covered by waivers 

despite a strong economy. The Department believes waiver criteria need to be 

strengthened to better align with economic reality. These changes would ensure 

that such a large percentage of the country can no longer be waived when the 

economy is booming and unemployment is low.163

The Department has clearly considered the role of waivers at a time when national unemployment is low, though this analysis of course does not take into account the fact that unemployment rates can vary across the country and even with 

low unemployment rates, individuals subject to the time limit may lack available 

jobs. Even more concerning, however, is that the Department did not indicate 

whether it considered the effect of the proposed rule at different parts of the business cycle, such as entering into a recession, and how climbing unemployment rates 

affect job availability. (The Regulatory Impact Analysis also fails to include analyses 

of the impact of the provision using historical data to assess how it would fare differently in different economic times.) Without such a discussion, it is impossible to 

assess the economic considerations it made in proposing a policy that would result 

in many areas remaining ineligible for waivers at a time of rising unemployment. 

H. Department Does Not Explain Claim That Suggested Floor Is ‘‘Designed Specifically for ABAWDS’’ 

The Department proposes a seven percent unemployment floor for areas to qualify 

for a waiver under the 20 percent standard, significantly higher than the floor used 

by Labor Surplus Areas. The Department suggests this floor would be more ‘‘tarVerDate Aug 31 2005 11:16 Jun 14, 2019 Jkt 041481 PO 00000 Frm 00217 Fmt 6621 Sfmt 6621 P:\DOCS\116-02\36188.TXT BRIAN
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164 NPRM, p. 984. 165 NPRM, p. 984. 

geted’’ towards the specific individuals subject to the time limit, but provides no evidence to support this assertion. The preamble states: 

The Department believes that amending the waiver regulations to include an 

unemployment floor is a critical step in achieving more targeted criteria. While 

the 20 percent standard is similar to the calculation of an LSA, the Department 

believes it is appropriate to request public comment to explore a floor that is 

designed specifically for ABAWD waivers.164

The Department suggests that having a higher unemployment rate floor than that 

used by DOL in its identification of LSAs would be more appropriate for this population than the general LSA floor of six percent unemployment. Evidence shows that 

the childless adult SNAP participants face labor market disadvantages, and likely 

experience higher unemployment rates than their area. This evidence would recommend against a specific unemployment rate floor, given the difficulty in assessing 

a specific rate that would reflect available jobs for this population. For example, a 

city or county may have an unemployment rate of seven percent, but the unemployment rate for childless adult SNAP participants is 12 or 14 percent. The difficulty 

in establishing available jobs is especially true in local areas where local labor market conditions may yield differing opportunities for this population for different levels of unemployment. For example, even if two areas had the same unemployment 

rate, an area where individuals live close to jobs that match their skills will have 

more opportunities than an area where there is considerable spatial mismatch. 

Given this evidence, if the Department did want a floor ‘‘designed specifically for 

ABAWD waivers,’’ it would follow that they would want to explore a floor that is 

considerably lower than that used by the Department of Labor in designating Labor 

Surplus Areas. By suggesting that a higher floor would be ‘‘designed specifically for 

ABAWD waivers,’’ the Department is suggesting that unless unemployment is at a 

relatively high level, substantially higher than what the Department of Labor considers sufficiently high in designating Labor Surplus Areas, there are sufficient jobs 

available for childless adult SNAP participants. All available evidence suggests the 

opposite is true: unemployment has to fall to very low levels before more disadvantaged workers can find jobs. The Department does not provide any evidence to support its conclusion that a seven percent unemployment rate bears any relationship 

to available jobs for this specific population. By referencing that such a floor would 

be ‘‘targeted,’’ the Department indicates that there are considerations that it took 

when establishing a floor substantially higher than the LSA floor. Without any discussion of those considerations, however, it is impossible to follow the Department’s 

logic and thus meaningfully comment on it. The robust review we did to understand 

the availability of jobs as related to the unemployment rate finds that the unemployment substantially overstates job opportunities for the individuals subject to the 

time limit, which would recommend flexibility, not imposing a specific unemployment rate floor. The Department is claiming an opposite finding without providing 

any evidence to support its conclusions. 

I. Reasoning for Specific Unemployment Rate Floor Not Consistent With Congressional Intent 

The Department’s stated rationale for proposing the seven percent unemployment 

rate floor for waivers for areas with unemployment rates 20 percent above the national average is to ensure that time limit waivers cover a reduced population compared to current standards. This rationale is inconsistent with the intent of Congress. Congress intended for FNS to develop criteria to measure a lack of jobs, and 

did not specify intended limits to the usage of waivers, provided they reflect economic conditions. 

In the preamble, the Department establishes that the justification for the proposed rule is not based on an analysis of the relationship of the unemployment rate 

floor to job availability for childless adult SNAP participants. The Department 

states it instead weighed the effect of the proposal on the breadth of waiver coverage: 

The Department seeks to establish a floor that is in line with the Administration’s effort to encourage greater engagement in work and work activities. The 

Department believes that the seven percent floor for the 20 percent standard 

would strengthen the standards for waivers so that the ABAWD work requirement would be applied more broadly and fully consider the ‘‘lack of sufficient 

jobs’’ criteria in the statute.165

213 

166 Congressional Research Service, ‘‘Tax Incentives for Opportunity Zones: In Brief,’’ R45152, 

November 20, 2018, https://fas.org/sgp/crs/misc/R45152.pdf. 167 NPRM, p. 984. 

The Department therefore states that the goal of the NPRM is to apply the time 

limit to more childless adults. The Department states that applying the time limit 

to more unemployed adults would ‘‘fully consider the ‘lack of sufficient jobs’ criteria 

in the statute,’’ but does not explain how restricting areas and would better reflect 

employment opportunities for this population. Moreover, this reasoning is completely contrary to Congressional intent, which was to allow states to waive areas 

with insufficient jobs without imposing limits on the share of areas covered by waivers by state or nationally. We are confused as to why FNS believes it has the authority to purposefully expose more people to the time limit as a rationale. 

Available evidence suggests that restricting waivers to only areas with very high 

unemployment would actually make waivers less likely to reflect available jobs for 

this population, given that it would exclude from eligibility many areas where these 

individuals lack jobs (such as an area with an unemployment rate of 6.7 percent, 

but unemployment rates well above ten percent for childless adult SNAP participants). 

Congress intended for the Administration to develop economic criteria to measure 

job opportunities for childless adult SNAP participants. Congress did not propose 

any measure to limit waivers based on the number or share of individuals subject 

to the time limit. If Congress had intended for waivers to be limited so that a specific share of childless adults live in an area with a waiver, it could have written 

legislation to achieve that goal. For example, in the 2017 Tax Cuts and Jobs Act 

(P.L. 115–97), Congress created Opportunity Zones, which are low-income Census 

tracts designated by the chief executive of a state that are eligible for tax incentives 

for investment. While Congress created several criteria to identify areas that are 

nominated, such as the poverty rate or median family income, Congress also limited 

the number of potential eligible Opportunity Zones each state is allowed to designate based on the total number of low-income communities in the state. For example, in areas with over 100 low-income census tracts, no more than 25 percent of 

the number of those low-income tracts can be designated as Opportunity Zones.166

This law serves as an example of one way that Congress can establish criteria to 

limit a particular sub-state designation, if that is indeed its intent. In establishing 

waiver criteria in the welfare reform law, Congress did not establish any mechanism 

to limit the scope of waivers, which it could have done by various means, had that 

been its goal. Instead, the law allows for the Department to develop measures to 

evaluate available jobs for childless adult SNAP participants, which are not limited 

in scope. The number of areas lacking jobs can expand or contract with economic 

conditions, and Congress allowed for states to waive areas in response to these 

changing economic conditions. Congress has not changed this approach since the 

original 1996 legislation. 

Furthermore, the Department uses provisions of the House-passed version of H.R. 

2 to support its proposed unemployment rate floor, ignoring that Congress ultimately rejected such provisions. In providing support for the seven percent unemployment rate floor, the preamble states, ‘‘Furthermore, this aligns with the proposal in the Agriculture and Nutrition Act of 2018, H.R. 2, 115th Cong. § 4015 (as 

passed by House, June 21, 2018).’’ 167 While this bill did contain a similar provision, 

the Senate bill did not include this provision, and the Conference Committee chose 

to align with the Senate version, passing both chambers without any restrictions on 

waivers. While the Department may consider Congressional bills, offering this as 

support while ignoring that these provisions were ultimately excluded from the final 

bill, the Department is offering an incomplete interpretation of Congressional intent. 

Department Provides Little Explanation to Support Stated Goal to Limit Waiver 

Coverage 

The Department establishes that its intent is to limit waiver coverage and therefore expand the time limit to the extent possible. The Department does not explain 

how this goal is related to the intent of the statute to identify areas that lack jobs 

for childless adults. Even if it had clarified how its stated goal related to the underlying statute it is interpreting, the Department also does not provide clear explanation of the assumptions used in determining the metric used repeatedly to support its conclusions, the share of ‘‘ABAWDs’’ living in a waived area. Without any 

explanation of the analysis used to understand what it believes the relationship between the unemployment rate floor and waiver coverage is, and how waiver covVerDate Aug 31 2005 11:16 Jun 14, 2019 Jkt 041481 PO 00000 Frm 00219 Fmt 6621 Sfmt 6621 P:\DOCS\116-02\36188.TXT BRIAN
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168 NPRM, p. 984. 169 NPRM, p. 984. 

erage relates to the ‘‘insufficient jobs’’ law, the Department has limited our ability 

to comment on these specific assertions. 

The Department explains that the principal criteria it considered when proposing 

the specific seven percent unemployment rate floor was not based on an economic 

argument about the relationship between the general unemployment rate and jobs 

available for disadvantaged individuals, but rather a desire to limit waivers of the 

time limit: 

As stated previously, the Department seeks to make the work requirements 

the norm rather than the exception to the rule because of excessive use of 

ABAWD time limit waivers to date. Using the proposed rule’s seven percent 

floor for this criterion and eliminating waiver approvals based on an LSA designation (as well as utilizing the proposed limit on combining areas discussed 

below), an estimated 11 percent of ABAWDs would live in areas subject to a 

waiver. Currently, approximately 44 percent of ABAWDs live in a waived area. 

The Department views the proposal as more suitable for achieving a more comprehensive application of work requirements so that ABAWDs in areas that 

have sufficient number of jobs have a greater level of engagement in work and 

work activities, including job training.168

The Department suggests that not only would limiting waivers be preferable to 

keeping the current regulations, but also suggests that the more the rules result in 

limited waivers, the more SNAP participants will be led towards self-sufficiency. 

(The Department also makes the claim that current waiver coverage is ‘‘excessive 

without providing explanation of the criteria used to judge appropriate waiver coverage.’’) It states that a seven percent floor, which it indicates would result in a decline from 44 percent of ‘‘ABAWDs’’ living in a waived area to 11 percent, would 

be ‘‘more suitable’’ than the current rules. In the proposed rule, the Department 

asks for feedback on alternative floors to the seven percent unemployment rate floor 

of six percent or ten percent (see Section I, below), explaining how the higher the 

unemployment rate floor, the more preferable according to their standards: 

Based on the Department’s analysis, nearly 90 percent of ABAWDs would live 

in areas without waivers and would be encouraged to take steps towards selfsufficiency if a floor of seven percent was established. In comparison, a six percent floor would mean that 76 percent of ABAWDs would live in areas without 

waivers and a ten percent floor would mean that 98 percent of ABAWDs would 

live in areas without waivers. A higher floor allows for the broader application 

of the time limit to encourage self-sufficiency.169

The Department therefore believes that expanding the time limit to more people 

is a desirable outcome. The Department states that the greater the unemployment 

rate threshold, the fewer childless adults will live in waived areas, suggesting that 

its goal is to minimize waiver coverage to the extent possible. Setting aside the issue 

that there is no evidence that applying the time limit more broadly encourages selfsufficiency, which we address comprehensively in Chapters 6 and 11, the Department leaves several unanswered questions with regards to how this rulemaking will 

further the intent of the law in defining areas with insufficient jobs: 

• The Department does not explain how imposing a higher unemployment rate 

floor would better approximate a lack of jobs. The purpose of the regulation is 

to define areas that lack ‘‘a sufficient number of jobs to provide employment’’ 

to childless adult SNAP participants. To interpret this regulation, it would follow that the specific waiver criteria the Department develops would best allow 

states to identify areas lacking jobs, and best enable the Department to approve 

those waivers based on consistent criteria. Operating under the framework that 

these regulations interpret the statute, the appropriate amount of waiver coverage is related to the share of this population facing limited employment opportunities (i.e., a lack of sufficient jobs) in their area. For example, if about 1⁄3 of counties did not have sufficient job opportunities for childless adults, then 

about 1⁄3 of counties would be eligible for a waiver, if there were a way to perfectly capture job availability for this population. If this share rises during a 

recession to 75 percent, then the share of the country eligible for a time limit 

waiver could also rise accordingly. 

The Department is therefore proposing an alternative interpretation of the 

statute, though it is not clear what this interpretation is or what the authority 

it has to drastically change this interpretation. The Department does not exVerDate Aug 31 2005 11:16 Jun 14, 2019 Jkt 041481 PO 00000 Frm 00220 Fmt 6621 Sfmt 6621 P:\DOCS\116-02\36188.TXT BRIAN
215 

170 NPRM, p. 984. 

plain whether it believes that there is an economic argument supporting limiting waivers, or instead if it believes that the goal of limiting waivers is separate from establishing areas with insufficient jobs, and if so, the authority 

under which it can establish new criteria for waivers that are not found in the 

statute. Without more explanation as to why its goal for limiting waivers is relevant to this rulemaking, it is difficult to assess the merits of the underlying 

arguments. 

• The Department does not explain whether there are any parameters to its stated goal of limited waivers, and under what criteria it judges the appropriate 

level of waiver coverage. In regard to the proposed six percent unemployment 

rate floor, the preamble states that ‘‘the Department is concerned that too many 

areas would qualify for a waiver of the ABAWD time limit with a six percent 

floor and that too few individuals would be subject to the ABAWD work requirements.’’ 170 The language of ‘‘too many’’ or ‘‘too few’’ implies that there is a desired level of waiver coverage, and that the waiver coverage that they estimate 

a six percent unemployment rate floor would yield (24 percent of ‘‘ABAWDs’’ living in waived areas) is too high. The Department therefore has implicit criteria 

by which it is judging an appropriate share of individuals living in a waived 

county that it does not explain. While it is not clear how the share of 

‘‘ABAWDs’’ living in a waived area is relevant to the rulemaking, even if it 

were, the Department does not allow commenters the ability to provide input 

on this metric without establishing the criteria it is using to judge the appropriate level. 

• Relatedly, the Department does not explain if it believes that limiting waivers 

would be an equally important goal during an economic recession, when the 

share of areas with limited jobs would expand considerably. Again, if the Department states that 24 percent of ‘‘ABAWDs’’ in waived areas is ‘‘too high,’’ 

would that also be true during an economic recession, if most areas of the country offered few jobs to those individuals, and a majority of childless adults lived 

in an area covered by a waiver? Without explaining how its stated goal of limiting waivers is related to assessing the economic conditions in an area, it is 

impossible to tell if the Department considers this goal to be a relative goal (as 

in, it believes it is acceptable to expand the time limit in response to higher 

unemployment), or if it believes there is a desired percentage of ‘‘ABAWDs’’ living in waived areas regardless of economic conditions. 

• Finally, the Department’s calculation of the share of ‘‘ABAWDs’’ living in a 

waived area does not take several important factors into account. 

» When the Department calculates the share of what it terms ‘‘ABAWDs’’ living in waived areas under the different scenarios it lays out, it is not clear 

if it is considering how this share will change as the overall denominator 

changes and what other assumptions are embedded in its analysis. In a time 

when fewer areas are waived, childless adults will be more disproportionately 

concentrated in waived areas, as they will lose benefits in non-waived areas. 

At any time, childless adults include a combination of participants who are 

living in waived areas; exempt from the time limit (but who the data does 

not allow us to identify as exempt); in their first 3 months of SNAP participation; or working or complying with the requirements through training. Other 

variables at the local level, such as state or county implementation of the 

time limit, the composition of childless adults (for example, in some areas, 

there may be proportionately more disadvantaged individuals), and the 

amount of job or training opportunities that are suitable for childless adults, 

will also affect how likely childless adults are to continue participating in 

SNAP in non-waived areas. Therefore, what share of childless adult SNAP 

participants living in waived areas is not just a function of the share of counties covered by a waiver, but also how they are distributed among those counties. It is not clear if the Department is using this statistic as a proxy for 

measuring overall waiver coverage, or if it is meant to convey an analysis 

modeling these dynamic variables. 

Consider a simplified example. Here, we will look to see how the distribution of childless adults living in certain waived areas changes as overall nationwide waiver coverage changes, using eight states, Guam and Virgin Islands that had statewide waivers in 2017, and 13 states that had statewide 

waivers at least from 2010 through 2013 but had dropped them by 2017. 

(This illustrative analysis therefore is not looking at childless adults living in 

216 

171 Center on Budget and Policy Priorities, ‘‘States Have Requested Waivers from SNAP’s 

Time Limit in High Unemployment Areas for the Past Two Decades,’’ https://www.cbpp.org/ 

research/food-assistance/states-have-requested-waivers-from-snaps-time-limit-in-high-unemployment. 172 Ibid. 

all waived areas, but rather choosing to look at states when they had a statewide waiver or no waiver in 2017 to simplify the analysis.) In 2010, almost 

all areas of the country were waived in the aftermath of the Great Recession, 

which prompted Congress to include a provision in the Recovery Act (P.L. 

111–5) that waived the time limit nationwide. (About five states continued to 

implement the time limit in parts of their state, but they offered work opportunities for individuals subject to the time limit.) About 89 percent of the general population lived in an area that was waived.171

Because of this widespread waiver coverage, the share of childless adult 

SNAP participants living in waived areas would be expected to be very similar to the share of all SNAP participants living in those areas. To the extent 

that this distribution differed, it would likely be due to compositional differences, such as areas with greater shares of children or elderly individuals. 

Waiver coverage would not be the main driver of differences, as waiver coverage was similar nationwide. Indeed, in 2010, about 20 percent of the total 

U.S. population lived in states that had statewide waivers continuously 

through 2017, and a slightly smaller share, 17 percent, of SNAP participants 

lived in those states. (This may be because these states’ populations had 

slightly smaller shares of individuals with income below SNAP’s income eligibility limits, reduced access to SNAP, or increased barriers for eligible people, 

or other reasons.) The share of all adults ages 18–49 in childless households 

who lived in those states in 2010 was similar to the distribution of SNAP participants; about 18 percent of childless adults lived in those eight states. Similarly, for states that had earlier had statewide waivers, but dropped them by 

2017, the share of childless adults living in those states was similar to the 

share of SNAP participants living in those states in 2010. Those states had 

about 24 percent of the total U.S. population, but a slightly higher share of 

SNAP participants (26 percent), and a slightly higher share of childless adults 

(28 percent). (Table 3.7.) 

Table 3.7 

Distribution of Childless Adults Living in Waived Areas Changes as Overall 

Waiver Coverage Changes 

Total Population 

(millions) 

Share of 

Total Population 

SNAP Participants 

(program 

data, 

millions) 

Share of 

SNAP Participants 

SNAP Participants 

Ages 18–49, 

Without 

Disabilities, 

in Childless 

Households 

(millions) 

Share of 

Participants 

Ages 18–49, 

Without 

Disabilities, 

in Childless 

Households 

Fiscal Year 2010: 89% of U.S. Population Lives in Waived Area 

States with statewide waivers in at least 2010–2013 and no 

waivers 2017 72.9 24% 10.4 26% 1.1 28% 

States with statewide waivers in at least 2010–2013 and 

2017 62.1 20% 6.7 17% 0.7 18% 

Total all states 309.3 100% 40.3 100% 3.9 100% 

Fiscal Year 2017: 36% of U.S. Population Lives in Waived Area 

States with statewide waivers in at least 2010–2013 and no 

waivers 2017 77.0 24% 10.6 25% 0.6 19% 

States with statewide waivers in at least 2010–2013 and 

2017 64.7 20% 8.3 20% 0.9 29% 

Total all states 325.1 100% 42.1 100% 3.2 100% 

Notes: The states with statewide waivers from the time limit in 2013 but no waivers at all in 2017 (which represented about 1⁄4 of SNAP 

participants in 2013) were Alabama, Arkansas, Florida, Indiana, Iowa, Kansas, Maine, Mississippi, Missouri, North Carolina, Oklahoma, 

South Carolina, and Wisconsin. The states with statewide waivers in both 2013 and 2017 (which represented about 20 percent of SNAP 

participants) included Alaska, California, District of Columbia, Illinois, Louisiana, Nevada, New Mexico, Rhode Island, Guam, and Virgin 

Islands. Sources: CBPP analysis of FY 2010 and FY 2017 SNAP household characteristics data; USDA program data; Census population estimates as of July 1st 2010 and 2017. 

By 2017, the share of waived areas had declined dramatically as the economy improved. About 36 percent of the U.S. population lived in an area that 

was waived.172 Given that the eight states who continued to waive the time 

limit statewide were the only states remaining with statewide waivers and 

overall waiver coverage was much lower, it would be likely that childless 

adults would be disproportionately living in states that continued to be 

217 

waived statewide, as they would be more likely to be subject to the time limit 

in other states with partial or no waivers. Similarly, we would expect the 

share of childless adults living in states without waivers to have declined relative to the share of all SNAP participants in those states. As Table 3.7 

shows, the share of childless adult SNAP participants who lived in states 

with statewide waivers (29 percent) was about 50 percent greater than the 

share of overall SNAP participants who lived in those areas (19 percent). This 

share also represents a significant increase from the 2010 share of 18 percent. 

We see the opposite trend for states that had no waiver by 2017: while in 

2010, states that had no waivers by 2017 had a slightly greater share of 

SNAP participants and childless adults than they did of overall U.S. population, by 2017, proportionately fewer childless adults lived in those states. 

While about 25 percent of SNAP participants lived in those states in 2017, 

only 19 percent of childless adults lived in states with the time limit statewide in 2017. 

The distribution of childless adults essentially flipped between these two 

groups of states between 2010 and 2017, as the overall number of areas 

waived declined and childless adults became more concentrated in states with 

waivers and much less so in areas without waivers. 

It is not clear if the Department incorporated these factors into its analysis, 

or assumed a more static relationship. The complexity of analyzing childless 

adults in waived areas raises the question of why the Department chose this 

particular statistic to measure waiver coverage, particularly given that it provided little explanation of some of these assumptions behind this calculation. 

Without more information, it is difficult to evaluate how relevant this statistic 

is to their overall point, which is to measure childless adults in a waived area 

as a measure of the proposed rule’s effect. 

» Similarly, as we explain in our comments on the Regulatory Impact Analysis 

in Chapter 11, the term ‘‘ABAWD’’ lacks specificity, particularly when describing changes in waiver coverage. The data do not allow us to tell which of the 

larger group of adults without dependent children, ages 18 to 49, without disabilities, might be exempt from the time limit, so many of these adults are 

not subject to the time limit. Others are only subject to the time limit if they 

live in an area without a waiver. When fewer areas are waived, more of these 

adults will be subject to the time limit and lose benefits, and the overall number of these adults participating in SNAP will decline. Therefore, when the 

Department describes how 11 percent of ‘‘ABAWDs’’ would live in a waived 

area with a seven percent floor and 24 percent would live in a waived area 

with a six percent floor, it is unclear if the Department is considering the decline in overall childless adults participating in SNAP that would occur with 

the reduction in waivers. 

» As we also discuss in our comments on the Regulatory Impact Analysis in 

Chapter 11, it is unclear why the Department used the number of participants in non-public assistance households in the FNS–388 form as a proxy 

for childless adults in estimating the share of ‘‘ABAWDs’’ living in waived 

areas under different scenarios. 

Instead of providing evidence that the Department’s proposal will interpret the 

statute in a more effective manner by improving on the measurement of jobs available for low-income childless adult SNAP participants, the Department instead uses 

a confusing and unexplained metric to support its proposal, the share of childless 

adults living in an area covered by a waiver. This metric is seemingly unrelated to 

the intent of the statute. Because the Department provided little evidence to support the assumptions made in estimating this metric and to explain why it is relevant to the underlying law, it is impossible to provide more detailed discussion. 

J. Proposed Alternative Unemployment Rate Floors Also Problematic 

In addition to the Department’s preferred unemployment rate floor of seven percent, the Department also sought comment on unemployment rate floors of six or 

ten percent. Both of these proposals are flawed, demonstrating why selecting a specific unemployment rate floor to reflect available jobs for this population is a misguided approach. 

Department’s Proposed Six Percent Floor Demonstrates Why No Specific Unemployment Rate Floor Is Appropriate 

The Department explains that a six percent unemployment rate floor would both 

be consistent with Labor Surplus Areas and bears a similar relationship to what it 

erroneously considers to be the natural rate of unemployment, stating ‘‘As preVerDate Aug 31 2005 11:16 Jun 14, 2019 Jkt 041481 PO 00000 Frm 00223 Fmt 6621 Sfmt 6621 P:\DOCS\116-02\36188.TXT BRIAN
218 

173 NPRM, p. 984. 174 NPRM, p. 984. 

viously noted, the ‘‘natural rate of unemployment’’ generally hovers around five percent, meaning that 20 percent above that rate is 6.0 percent.’’ 173 The Department 

therefore at least provides evidence that is somewhat more consistent with current 

standards such as relying on Department of Labor criteria, though undermines its 

seven percent unemployment rate proposal, for which it does not provide any such 

evidence. 

This unemployment rate floor would still exclude many areas where childless 

adult SNAP participants face considerably higher unemployment or underemployment rates and where they will not have access to jobs, however. As stated above, 

even at five percent unemployment rates, black and Latino workers nationally face 

unemployment rates of 9.6 percent and seven percent, respectively, and underemployment rates of 14.9 percent and 13 percent, respectively. Some local metropolitan areas had 2013–2017 average unemployment rates below six percent, but unemployment rates for sub-populations well above 14 percent, the unemployment rate 

of the Great Depression. (See Tables in Section E above.) For example, Monroe, MI, 

had an unemployment rate of 5.9 percent, but workers without a high school degree 

faced unemployment rates of 16.7. In Fort Wayne, Indiana, the area unemployment 

rate was 5.9 percent, but workers with a disability had unemployment rates of 14 

percent. In the Pittsburgh, PA metro area, while the unemployment rate was 5.7 

percent, the unemployment rate among African American workers was 14.1 percent. 

Again, these figures demonstrate why it is impossible to set a specific unemployment rate threshold at which it can be reasonably assured that childless adults subject to the time limit can readily find a job with steady hours. Evidence shows that 

this group is likely to face unemployment rates much higher than their local area, 

and the unemployment rate floor is an inadequate proxy to measure jobs available 

to them. 

The Department’s suggestion that a ten percent unemployment rate floor is in any 

way a reasonable proposal highlights many of the internal inconsistencies and inadequate explanations in this proposed rule. 

Ten Percent Floor Inconsistent with Congressional Intent and Based on Obscure 

and Inconsistent Reasoning 

Congress clearly designated a ten percent unemployment rate as one way for a 

state to qualify for a waiver, and a second, more flexible and targeted criterion of 

‘‘insufficient jobs’’ as an alternative to demonstrating a ten percent unemployment 

rate. Had Congress intended for ten percent unemployment to be the only way for 

a state to qualify for a waiver, it would not have included an alternative. This proposal therefore runs afoul of Congressional intent. 

The Department also ignores the LSA standard’s ten percent ceiling, demonstrating how its reasoning is inconsistent. As explained elsewhere, the Department picks and chooses when and how it will aim to be consistent with the DOL’s 

approach in assessing unemployment. The Department of Labor clearly considers 

ten percent to be a sufficiently high level of unemployment that an area with ten 

percent unemployment over 24 months demonstrates a surplus of labor. The Department ignores this fact by proposing a ten percent unemployment rate floor for the 

20 percent standard, while also citing the LSA standard as support for the unemployment rate floor concept in general. 

As with the proposed seven percent floor, the Department suggests that the ten 

percent standard would achieve its goal of greatly curtailing waiver coverage, which 

as explained above, is a goal not aligned with the intent of the underlying statute 

and for which it does not offer a transparent rationale. The Department states, ‘‘the 

Department estimates that a ten percent floor would reduce waivers to the extent 

that approximately two percent of ABAWDs would live in waived areas.’’ 174 While 

the Department may consider reducing the population of ‘‘ABAWDs’’ living in 

waived areas a priority, the Department provides little explanation of how this priority relates to the underlying statute and identifies areas lacking jobs for childless 

adults. It also provides little transparency with regards to the assumptions used in 

estimating the effects of these unemployment rate floors on the population living in 

waived areas. 

Ten Percent Floor Would be Duplicative of Existing Ten Percent Criteria 

This proposal would also be largely duplicative of existing criteria. The Department does discuss how the time frame used would be different from the existing regulations regarding waivers based on ten percent unemployment rates: ‘‘the ten percent unemployment floor would be attached to the 20 percent standard, which would 

219 

175 NPRM, p. 984. 176 NPRM, p. 984. 

mean an area would require an average unemployment rate 20 percent above the 

national average for a recent 24 month period and at least ten percent for the same 

period; the other similar, but separate standard requires an area to have an average 

unemployment rate of over ten percent for a 12 month period.’’ 175 Ten percent unemployment is extremely high at the national level. Only during a deep recession, 

such as immediately following the Great Recession, would 20 percent above the national average be close to or above ten percent, which would require the national 

average to be at least 8.4 percent for a 24 month period. Since the BLS began tracking monthly unemployment statistics since 1948, out of 830 total 24 month periods 

there have been only 64 24 month periods when the national average would have 

met this standard. There were 28 periods from November 1980 through January 

1985, during and following the 1981–1982 recession, and 36 24 month periods 

around the Great Recession of 2007–2009 and its long, slow recovery, from May 

2008 through March 2013. 

For most of the time barring these prolonged economic crises, then, this regulation would simply extend the time frame for demonstrating ten percent unemployment, essentially eliminating the 20 percent standard most of the time. There may 

be some areas that are recovering from a deep economic shock that have more recent unemployment rates just below ten percent, but unemployment over the past 

2 years high enough over that rate to nudge the average up above ten percent. Because ten percent is such a high level of unemployment, however, it is unlikely that 

many areas would qualify that would not have otherwise qualified under the ten 

percent criterion. 

For example, we analyzed all 12 month time periods that a state could use to examine waiver eligibility based on either having a 12 month unemployment rate over 

ten percent or a 24 month unemployment rate 20 percent above the national average but at least ten percent from 2008 to 2019. With the exception of the years capturing peak unemployment rates immediately following the Great Recession, from 

2014 to 2016, when capturing a longer time frame allowed for more months during 

peak unemployment, only a handful of counties would qualify under the 24 month 

average but not the 12 month average. (Even during those years from 2014–2016, 

fewer than 150 counties, or less than five percent of counties, would have qualified 

under the 24 month but not the 12 month standard.) 

It is not clear if the Department more fully considered the practical differences 

between these measures, such as comparing how many areas would have qualified 

in past years based on having 12 months of ten percent unemployment or 24 

months of ten percent unemployment. Its rationale for essentially replacing the 20 

percent standard, which measures high unemployment relative to the national average, with additional criteria for the ten percent standard, is therefore not transparent. 

Department’s Alternative Floors Highlight Arbitrary Choice of Seven Percent Floor 

The Department’s discussion of alternate unemployment rate floors also demonstrates how its proposed floor of seven percent is an arbitrary figure. When proposing the six percent and ten percent floors as alternatives to the seven percent 

floor, the Department gives little discussion of the relevance to these floors to the 

underlying statute, which is to identify areas where individuals subject to the time 

limit do not have access to enough jobs. For example, the Department could have 

provided economic evidence that indicates how these specific unemployment rates 

relate to job availability for childless adult SNAP participants. The only such discussion Department includes is when it explains a relationship between the natural 

rate of unemployment and the six percent floor by stating that it the six percent 

floor is roughly 20 percent above five percent, which the Department inaccurately 

states is consistent with the ‘‘natural rate of unemployment’’ concept.176 The Department therefore uses no economic discussion to support its proposed seven percent floor but gives some discussion to explain the six percent floor, which is its alternate proposal. The discussion of the relationship of the six percent floor to the 

natural rate of unemployment therefore undermines the Department’s proposal for 

the seven percent floor, as it demonstrates that the Department either did not consider any economic evidence, or did not provide any evidence to allow us to meaningfully comment. 

The only discussion the Department gives to justify choosing the seven percent 

floor (or to support the alternative of ten percent) is to limit the share of the population covered by a waiver, which as discussed above, is not what Congress intended 

when creating the waiver authority. Without any discussion to explain how the 

220 

seven percent unemployment rate is an appropriate measure of available jobs for 

the individuals subject to the time limit, the seven percent floor appears to be a 

completely arbitrary choice. 

The Department proposes alternative unemployment rate floors for the ‘‘20 percent standard.’’ These proposed floors would also be problematic, as would any specific unemployment floor, because it is impossible to demonstrate that an area with 

an unemployment rate below a specific threshold lacks jobs for the individuals subject to the time limit. 

K. Conclusion: Proposal for Unemployment Rate Floor Is Deeply Flawed 

The Department proposes to change one of the most frequently used standards 

for waiver approval, the ‘‘20 percent standard,’’ to require a minimum unemployment rate. With this proposal, a state could request a waiver with an unemployment 

rate 20 percent above the national average for a 24 month period only if it was 

above this unemployment rate floor. The Department proposed an unemployment 

rate floor of seven percent, but also sought input on proposed floors of six or ten 

percent. 

The Department provides little economic evidence to support the claim that imposing this floor would better interpret the statute, which allows states to request 

waivers for areas that lack ‘‘a sufficient number of jobs to provide employment’’ for 

the individuals subject to the time limit. The Department instead appears to work 

backwards from its stated goal of applying the time limit to more SNAP participants 

by limiting waivers, and proposes an unemployment rate floor as a means of achieving this goal. The Department does not explain how this goal relates to the purpose 

of the law it is interpreting, or how the specific floors it proposes would better reflect available jobs for participants. 

Research shows that the childless adults who may be subject to the time limit if 

they are not exempt or living in a waived area tend to have many characteristics 

that are associated with higher unemployment rates. The majority have lower levels 

of educational attainment, they are disproportionately people of color, many have 

health conditions or barriers such as unstable housing that limit their ability to 

work, and many likely experience spatial mismatch and lack access to the jobs that 

are available in their communities. Because of these features, it is difficult to find 

a labor force metric that accurately portrays the job opportunities available to these 

individuals. Current regulations allow states to show that an area has elevated unemployment compared to the national average. The current ‘‘20 percent standard’’ 

therefore already disqualifies many areas with unemployment similar to or below 

the national average where there are not enough jobs for these individuals to find 

employment that are not reflected in the unemployment rate. 

While current regulations could be improved, this proposal would substantially 

worsen the existing inadequacies. The proposal would require an area has an unemployment rate consistent with weak labor markets for the overall labor force, seven 

percent, to qualify for a waiver. Given that the unemployment rates for the group 

of these individuals are likely substantially higher than their area, this proposal 

would disqualify many areas where individuals face much higher rates than six or 

seven percent unemployment. The proposal would not align with Congressional intent, which purposefully did not specify a specific unemployment rate to signify that 

an area lacks jobs in recognition that the unemployment rate cannot capture job 

availability for this specific group. 

States frequently request waivers based on the current ‘‘20 percent standard,’’ 

given that data are readily available and consistent across states, and FNS standards for approval are transparent and consistently applied. While the current standard falls short of accurately reflecting jobs available for this population, we believe 

the proposed unemployment rate floor would be inconsistent with the intent of Congress and would make the current criteria substantially less effective at measuring 

insufficient jobs. We therefore urge FNS to drop the unemployment rate floor proposal, keep the 20 percent standard as it is, and explore metrics based on evidence 

that would more effectively reflect jobs available to the population in recognition of 

the likely substantially higher unemployment rates they face. 

Chapter 4. Dropping Several Key Criteria From Waiver Criteria Is Inconsistent With the Statute 

The NPRM proposes several significant changes to longstanding SNAP policy that 

would restrict states to one limited measure of labor market conditions, the unemployment rate, when providing evidence of lack of sufficient jobs. It would eliminate 

the ability of states to use valuable, readily available labor market indicators, such 

as a low and declining employment-to-population ratio, a lack of jobs in a declining 

industry, or an academic study or other publication(s) that describes an area’s lack 

221 

177 USDA, ‘‘Guidance for states Seeking Waivers for Food Stamp Limits,’’ December 3, 1996. 

of jobs. The NPRM fails to provide reasons for limiting states’ ability to use widely 

accepted labor market measures to support requests for waivers, to discuss the implications of relying on a single measure of labor market conditions, or to acknowledge the valuable information provided by other measures. Without knowing what 

evidence justifies this change in longstanding policy and an adequate discussion of 

alternative methods for assessing labor market conditions, it is impossible to assess 

the potential impact of the changes on SNAP participants and their ability to 

achieve self-sufficiency. The sections below provide an overview of existing statutes, 

regulations, and guidance, address limitations of the general unemployment rate, 

and discuss alternative measures of labor market conditions. 

A. Current Statute, Regulations, and Guidance Acknowledge That There Is No Perfect Measure of an Area’s ‘‘Lack of Sufficient Jobs’’ 

According to the statute, a state may waive the applicability of the work requirement ‘‘to any group of individuals in the state if the Secretary makes a determination that the area in which the individuals reside has an unemployment rate above 

10% or does not have a sufficient number of jobs to provide employment for the individuals.’’ The statute does not limit the type of information that can be used to support a claim of lack of sufficient jobs. 

According to the current rule (7 CFR § 273.24 (f)(2)(ii)), states are not limited to 

using unemployment rates to support a claim of lack of sufficient jobs. States may 

provide evidence that an area has a low and declining employment-to-population 

ratio, has a lack of jobs in declining occupations or industries, or is described in an 

academic study or other publications as an area where there are lack of jobs. In the 

preamble to the current rule, FNS stated that ‘‘State agencies could submit requests 

with no limit on the supporting documentation, and every request would be weighed 

on its own individual merits.’’ The final rule included a non-exhaustive list of the 

kinds of information a state agency may submit to support a claim of ‘‘lack of sufficient jobs.’’ 

Below are excerpts from FNS guidance and rulemaking that give states flexibility 

in using other types of data to provide evidence of a lack of sufficient jobs, acknowledging that unemployment rates may not adequately capture the local labor market 

prospects of individuals subject to the time limit. 

• December 3, 1996 guidance: According to FNS, the statute ‘‘recognizes that 

the unemployment rate alone is an imperfect measure of the employment prospects of individuals with little work history and diminished opportunities. It 

provides states with the option to seek waivers for areas in which there are not 

enough jobs for groups of individuals who may be affected by the new time limits.’’ 177

‘‘Lack of jobs due to lagging job growth. Job seekers may have a harder time 

finding work in an area where job growth lags behind population growth. A falling ratio of employment-to-population may be an indicator of an adverse job 

growth rate. When the number of jobs in an area grows more slowly than the 

working age population, the local economy is not generating enough jobs. 

‘‘The employment-to-population ratio complements measures of unemployment by taking into account working age persons who may have dropped out 

of the labor force altogether. The ratio can be computed by dividing the number 

of employed persons in an area by the area’s total population. A decline in this 

ratio over a period of months could indicate an adverse job growth rate for the 

area . . . 

‘‘Lack of jobs in declining occupations or industries. Employment markets 

dominated by declining industries could lead to the presence of large numbers 

of people whose current job skills are no longer in demand. This can be especially true in smaller, rural areas where the loss of a single employer can immediately have a major effect on local job prospects and unemployment rates.’’ 

• 1999 proposed rule: In the preamble, FNS noted that ‘‘the legislative history 

does not provide guidance on what types of waivers the Department should approve under this standard, and there are no standard data or methods to make 

the determination of the sufficiency of jobs. States requesting waivers are therefore free to compile evidence and construct arguments to show that in a particular area, there are not enough jobs for individuals who are affected by the 

222 

178Food Stamp Program: Personal Responsibility Provisions of the Personal Responsibility and 

Work Opportunity Reconciliation Act of 1996; 64 FEDERAL REGISTER 242, p. 70946 (December 

17, 1999) (to be codified at 7 CFR pts. 272 and 273). 179 USDA, ‘‘Guidance on Requesting ABAWD Waivers,’’ August 2006. 180 USDA, ‘‘Guide to Supporting Requests to Waive the Time Limit for Able-Bodied Adults 

without Dependents (ABAWD),’’ December 2, 2016. 

time limit.’’ 178 FNS reiterated that one possible indicator that an area has insufficient jobs is a falling ratio of employment-to-population, but that ‘‘no particular approach is required.’’ 

• August 2006 guidance: ‘‘Waivers may also be submitted based on the following criteria: (1) areas having a low and declining employment-to-population 

ratio; (2) areas having a lack of jobs in declining occupations or industries; (3) 

areas described in an academic study or other publications as an area where 

there is a lack of jobs. The state may submit whatever data it deems appropriate to support requests based on this data. FNS will evaluate the data and 

determine if it is acceptable to justify a waiver.’’ 179

• December 2016 guidance: FNS provided additional detail on ‘‘other potential 

types of waiver requests’’ beyond those based on the LSA designation or unemployment rates: 180

A low and declining employment-to-population ratio. Employment-to-population (ETP) ratio can be a meaningful economic indicator for an area where the 

unemployment rate may not provide a complete picture of the labor market due 

to people leaving the workforce—but demographic changes, such as an aging 

population, can influence these data. Historically, low and declining ETP data 

have been used successfully to waive Indian reservations or Tribal lands where 

unemployment statistics and other economic data are limited or unavailable. 

ETP data can also be used to request waivers for non-Tribal areas, such as 

counties, but it is uncommon because BLS unemployment data is readily available for these areas. Therefore, FNS has approved requests based on ETP data 

for non-Tribal areas, such as rural counties, on a limited basis when the state 

has demonstrated that the area’s ETP ratio is: 

» Low: at least one percentage point below the national average for the most 

recent year of the reference period; 

» Declining: best demonstrated by a decline year after year; 

» Covering at least a 4 year reference period, ending no earlier than 2 years 

prior to the year in which the waiver is effective; and 

» Complemented by a recent 24 month unemployment rate at least ten percent 

above the national average in the requested area. 

A lack of jobs in declining occupations or industries. Employment markets 

dominated by declining industries could impact large numbers of people whose 

current job skills are no longer in demand. This can be especially true in smaller, rural areas in which the loss of a single job provider, such a major manufacturing plant or mining industry, can have a major effect on local job availability. The state might consider providing studies, reports, or other analysis 

from credible sources in demonstrating that an area has a lack of jobs in declining occupations or industries. 

Description in an academic study or other publication as an area where there 

is a lack of jobs. The state might consider providing an academic study or other 

credible publication that documents a lack of sufficient jobs in an area. 

The state may submit whatever data or evidence it deems appropriate to support these types of requests. FNS will evaluate such requests on a case-by-case 

basis and will approve those that provide compelling support of a lack of sufficient jobs in the area. FNS strongly encourages the state to work closely with 

its regional offices for technical assistance if it is considering requesting a waiver based on the less common support mentioned above. 

B. The Proposed Rule Would Restrict the Evidence to Support Lack of Sufficient Jobs 

to a Single, Imperfect Measure of Labor Market Conditions 

The NPRM says the proposed core standards would not include other labor market information, such as a low and declining employment-to-population ratio, a lack 

of jobs in a declining industry, or an academic study or other publication(s) that describes an area’s lack of jobs. It would eliminate the ability of states to support a 

waiver request using other available information about the labor market, unless 

BLS unemployment data for the area is limited or unavailable, such as a reservation area or U.S. territory. FNS proposes to eliminate these other criteria on the 

223 

181See for instance: https://www.bls.gov/news.release/srgune.nr0.htm. 182See for instance ‘‘How the Government Measures Unemployment,’’ Bureau of Labor Statistics, online at https://www.bls.gov/cps/cps_htgm.htm#unemployed. 

grounds that they are ‘‘rarely used, sometimes subjective, and not appropriate when 

other more specific and robust data are available,’’ but does not provide further substantiation of this claim. 

The proposed rule would replace an approach that allows for multiple measures 

to capture labor market conditions experienced by individuals subject to the time 

limit with a single, limited, and imperfect measure, the unemployment rate. FNS 

has stated in its guidance that using the unemployment rate is an imperfect measure for the job prospects for individuals subject to the time limit. Labor market researchers routinely use other labor market measures in addition to, or instead of, 

the unemployment rate, such as the employment-to-population ratio. 

Other Measures, Including the Employment-To-Population Ratio, Provide Important 

Information About Labor Market Conditions That the General Unemployment 

Rate Does Not 

The employment-to-population ratio is a well-defined and widely used measure 

that is far from subjective. The employment-to-population ratio is the proportion of 

the civilian noninstitutional population aged 16 and over that is employed. As the 

1996 guidance describes, employment data for areas is available from BLS. Population estimates for areas are available from the Bureau of Census. The calculation 

of the employment-to-population ratio is a standard BLS procedure, which is a 

measure it reports on a regular basis at the regional and state level.181 In many 

instances, researchers use employment-to-population ratio as a more appropriate 

measure for labor market conditions for low-skill workers who face serious barriers 

to employment. 

Current regulations allow states to demonstrate that an area lacks sufficient jobs 

by showing that it has a low and declining employment-to-population ratio. The rule 

proposes eliminating this criterion as a means for an area to qualify for a waiver. 

This would be a mistake, as it would throw away valuable information about the 

state of the labor market and the likely availability of jobs that cannot be gleaned 

from the unemployment rate alone. The unemployment rate is the number of people 

actively looking for a job as a percentage of the labor force (the number of people 

who have a job plus the number of people who don’t have a job but are actively looking for one). In a job market with limited job opportunities for any of a number of 

reasons, such as weak demand due to a national economic recession, a local business 

slump, or the closing of a major plant, there could be a number of people who would 

like to work but for reasons such as discouragement due to a failed job search, experience with discrimination, or a general sense that their job prospects are limited 

haven’t looked recently enough to be counted as in the labor force but unemployed. 

These individuals are classified as ‘‘marginally attached to the labor force’’ and 

are included in broader measures of labor market underutilization, including the U– 

6 measure, which includes the unemployed, the marginally attached to the labor 

force, and those who are working part-time but want to be working more hours.182

224 

183The unemployment rate can be derived from the employment to labor force ratio by subtracting the latter from 1. 184Timothy J. Bartik, ‘‘How Do the Effects of Local Growth on Employment Rates Vary with 

Initial Labor Market Conditions,’’ Upjohn Institute Staff Working Paper 09–148 (Nov. 4, 2006), 

pp. 1–35, https://www.econstor.eu/bitstream/10419/64401/1/607052678.pdf. 

Figure 4.1 

Job Market Indicators in the Great Recession 

In a national recession, a local economic slump, or in localities with limited job 

opportunities, the unemployment rate can paint a very incomplete picture of the 

availability of jobs. This was illustrated dramatically at the national level in the 

Great Recession. Between the start of the recession in December 2007 and early 

2010, the share of the population with a job (the employment-to-population ratio) 

fell sharply. That was mostly due to the sharp rise in the unemployment rate, but 

some of it reflected a drop in labor force participation as the number of people marginally attached or otherwise not in the labor force rose. 

The unemployment rate then began a long decline but the labor force participation rate continued to fall as well. As a result, the share of the population with a 

job remained depressed and did not begin to rise again until 2014 (see Figure 4.1, 

above). 

The U–6 measure of unemployment came down more slowly than the official unemployment rate as jobs, especially full-time jobs, remained scarce. Even as the unemployment rate dropped below seven percent, the employment-to-population ratio 

remained well below where it was at the start of the recession. 

Researchers Routinely Use Employment-to-Population Ratio to Measure Local Labor 

Market Conditions 

Researchers routinely use the employment-to-population ratio in addition to, or 

instead of, the unemployment rate to measure labor market conditions. According 

to Bartik, it is ‘‘unclear whether the availability of labor is best measured by employment-to-population ratios or employment to labor force ratios.’’ 183 Bartik finds 

that employment-to-population ratios are more strongly related to job growth than 

employment to labor force ratios.184

For individuals subject to the time limit, the employment-to-population ratio may 

be more appropriate than the unemployment rate. According to Western and Pettit, 

for groups who are weakly attached to the labor market and who face significant 

barriers to labor force participation, like young men with little education, economic 

status is often measured by the employment-to-population ratio. This measure 

counts as jobless those who have dropped out of the labor market altogether. The 

unemployment rate is more restrictive and does not account for individuals who are 


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185 Bruce Western and Becky Pettit, ‘‘Incarceration and Social Inequality,’’ D#dalus Journal 

of the American Academy of Arts & Sciences (Summer 2010), pp. 8–19, https:// 

www.mitpressjournals.org/doi/pdf/10.1162/DAED_a_00019%20. 186 Brian C. Cadena and Brian K. Kovak, ‘‘Immigrants Equilibrate Local Labor Markets: Evidence From the Great Recession,’’ National Bureau of Economic Research (August 2013), 

https://www.nber.org/papers/w19272.pdf. 187 Ian Watson, ‘‘Beyond the Unemployment Rate: Building a Set Indices to Measure the 

Health of the Labour Market,’’ Australian Bulletin of Labour (September 2000), pp. 175–190, 

http://www.ianwatson.com.au/pubs/health%20of%20labour%20market.pdf. 188 Hilary W. Hoynes, ‘‘Local Labor Markets and Welfare Spells: Do Demand Conditions Matter?’’ The Review of Economics and Statistics (August 2000), pp. 351–368, https:// 

gspp.berkeley.edu/assets/uploads/research/pdf/Hoynes-RESTAT-2000.pdf. 189David Dranove, Craig Garthwaite, and Christopher Ody, ‘‘Health Spending Slowdown is 

Mostly Due to Economic Factors, not Structural Change in the Health Care Sector,’’ Health Affairs (Aug. 2014), pp. 1399–1406, https://www.healthaffairs.org/doi/pdf/10.1377/ 

hlthaff.2013.1416. 190 Janet Yellen, ‘‘Addressing Workforce Development Challenges in Low-Income Communities,’’ Federal Reserve Board of Governors, March 28, 2017, https://www.federalreserve.gov/ 

newsevents/speech/files/yellen20170328a.pdf. 

not currently in the labor force.185 A study by Cadena and Kovak illustrates this 

approach, using employment-to-population ratios to estimate the probability of employment in the less-skilled labor market.186

An improved (or deteriorating) unemployment rate does not directly correspond to 

an improvement (or deterioration) of the employment situation, because it does not 

take into account changes in the labor force participation rate due to the movement 

of discouraged jobseekers in and out of the labor market. Only a stable participation 

rate allows for unambiguous conclusions from a rising (or falling) unemployment 

rate. Unemployed people who have been adversely affected by economic restructuring may give up hope of working again and withdraw from the labor force. Job 

booms may only be a boom for certain kinds of workers. Watson argues that a more 

useful indication of the quantity of employment in the economy is provided by employment-to-population ratios, which remove the confounding influence of labor force 

participation and give a more accurate indication of the amount of employment 

available to the population.187

Hoynes estimated the effect of local labor markets on Aid to Families with Dependent Children participation in California using several measures of labor market 

conditions, including unemployment rates, log of employment, employment-to-population ratios, and earnings. Results showed that higher unemployment rates, lower 

employment growth, lower employment-to-population ratios, and lower wage growth 

are associated with longer welfare spells and shorter periods off welfare. Models 

that controlled for labor market conditions using employment-based measures, such 

as employment-to-population ratios, performed better than unemployment rates. 

‘‘Unemployment rates are less desirable measures of labor market opportunities because they fluctuate not only with employment but also with changes in labor force 

participation.’’ 188

Dranove, Garthwaite, and Ody used employment-to-population ratio to examine 

the impact of the economic slowdown that began in 2007 on the rate of growth in 

health spending. They used the employment-to-population ratio, rather than unemployment rate, because it is not affected by decisions to enter the labor force and 

instead provides a local measure of changes in economic activity resulting from the 

slowdown. Their results were broadly consistent with results using the local unemployment rate instead of employment-to-population ratio.189

The General Unemployment Rate May Not Adequately Measure Weak Labor Demand at the State and Sub-State Level 

During this period when the national employment-population ratio was flat, there 

were many local and regional labor markets where labor market conditions remained weak even as the general unemployment rate fell. 

In a 2017 speech that partially focused on the geographical variance of labor markets across the country (and on policies to ameliorate such differences), then Federal 

Reserve Chair Janet Yellen, pointed out the following: 190

While the job market for the United States as a whole has improved markedly since the depths of the financial crisis, the persistently higher unemployment rates in lower-income and minority communities show why workforce development is so essential. For instance, unemployment rates averaged 13 percent in low- and moderate-income communities from 2011 through 2015, compared with 7.3 percent in higher-income communities . . . . The challenges for 

workers in minority communities are even greater. The average unemployment 

226 

191Danny Yagan, ‘‘Employment Hysteresis from the Great Recession,’’ NBER Working Paper 

No. 23844, August 2018, https://www.nber.org/papers/w23844. 192 Ibid. 

rate across all census tracts where minorities made up a majority of the population averaged 14.3 percent from 2011 through 2015. 

Labor economist Danny Yagan added an important insight about the geographical 

dispersion of employment conditions following the historically large, negative demand shock from the Great Recession.191 As Figure 4.2 below shows, states that 

were harder hit by the downturn saw significantly larger losses in employment 

rates, even years after the recession was over. Yagan argues that his findings provide evidence of ‘‘hysteresis,’’ meaning lasting economic damage to persons and communities from periods of economic weakness. As he summarizes, ‘‘These findings reveal that the Great Recession imposed long-term employment and income losses 

even after unemployment rates signaled recovery.’’ 192

As shown in the next section, even at low rates of national and regional unemployment (meaning rates well below seven percent), there are areas of the country 

where economic weakness persists. Yagan’s findings suggest that these areas may 

suffer from more lasting damage to workers’ ability to find gainful jobs. In the context of the proposed rule, such dynamics speak to the importance of taking a much 

more nuanced approach to the waiver process, examining local labor markets from 

both the demand side (i.e., the extent of job availability, both quantity and quality) 

and the supply side (i.e., the skills and abilities of members of the local workforce 

to respond to labor demand). 

Figure 4.2 

State-Level Great Recession Employment Shocks and 2007–2015 Employment Rate Changes 

Note: Yagan defines employment shocks as the sum of state-level employment growth forecast errors for 2008 and 2009. These forecast errors represent the difference between each state’s actual employment growth and 

its predicted employment growth based on pre-recession trends. Values on 

the x-axis represent the inverse of 2007–2009 employment growth forecast 

errors. 

Geographical Variation of Weak Labor Demand, Even at Low Unemployment 

Echoing the Yagan findings referenced above, a recent paper by Austin, et al., illustrates that labor demand, particularly for low-wage workers, varies significantly 


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227 

193 Benjamin Austin, Edward Glaeser, and Lawrence Summers, ‘‘Jobs for the Heartland: 

Place-Based Policies in 21st Century America,’’ March 8, 2018, https://www.brookings.edu/wpcontent/uploads/2018/03/AustinEtAl_Text.pdf. 194To be clear, employment (and non-employment) rates are mechanically correlated as higher 

unemployment means lower employment. Our focus here, however, is on the levels of these variables and what they imply for labor demand. 195 EIG and BLS have slightly different definitions for ‘‘prime-age’’—BLS uses adults 25–54, 

and EIG uses adults 25–64. 

from place to place.193 In their recent analysis of regional disparities, these authors 

find pockets of persistently weak labor markets across America, citing what they 

label: ‘‘a hardening of America’s geographic divisions.’’ Their paper identifies three 

findings particularly germane to the shortcomings of the new rule: ‘‘the decline of 

geographic mobility,’’ ‘‘increased sorting by skills across space,’’ and ‘‘persistent 

pockets of non-employment.’’ The combination of these three negative developments 

imply a larger share of lower-wage workers stuck in various locations without 

enough work. We find these disparities very much present in the labor market over 

the current expansion, even at historically low rates of unemployment. 

Many labor economists consider the prime-age employment rate to be a proxy for 

labor demand. As part of their ‘‘Distressed Community Index,’’ the Economic Innovation Group (EIG) provides county-level data on non-employment rates, or 1 ¥ the 

employment rate. Thus, higher non-employment rates correspond to weaker labor 

demand. 

Between 2012 and 2016, the average national non-employment rate for prime-age 

workers was 23 percent, meaning 77 percent of such workers had jobs. EIG’s data, 

to which we appended county-level unemployment data from the BLS, reveal that 

in counties with unemployment rates between 6.5 and 7.5 percent, the average nonemployment rate for prime-age adults was about 34 percent, more than ten percentage points above the national average.194 Note that even at the worst of the Great 

Recession, the non-employment rate peaked at about 25 percent.195

The scatterplot in Figure 4.3 below shows the correlation between un- and nonemployment at the county level. Note that the scatterplot expands at higher unemployment, implying greater dispersion of labor demand across counties at higher 

rates of unemployment. For example, the plot shows that at ten percent county unemployment, there are some counties with quite low non-employment rates and 

some with very high rates. This dispersion further underscores the need to avoid 

the single number approach proposed in the rule. Second, the scatterplot shows that 

at seven percent unemployment, as noted above, non-employment is above 30 percent. 

Figure 4.2 

County-Level Unemployment and Non-Employment 


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228 

196https://www.bls.gov/opub/ee/home.htm. 197 NPRM, p. 985, 987. 

Using the same procedure employed in the previous section, a regression of county-level non-employment rates on the county’s unemployment rate, predicts that at 

five, seven, and ten percent unemployment rates, county-level non-employment 

rates would range from 27 to 41 percent. (Table 4.1.) In other words, such high levels of non-employment demonstrate significant labor market slack at the jobless 

rates proposed by the Department. 

Table 4.1 

Predicted County-Level Prime-Age Non-Employment Rate 

Unemployment Rate Predicted Prime-Age Non-Employment 

Rate 

5% 27% 

7% 33% 

10% 41% 

Note: County-level prime-age non-employment rates are predicted by regressing 

county-level unemployment rates on non-employment rates. 

The Federal Reserve recognized that there was still considerable ‘‘slack’’ in the 

labor market not captured by the unemployment rate and kept short-term interest 

rates effectively at zero until December 2015 before it began to raise them cautiously in small increments. 

C. Information About Declining Occupations or Industries Can Help Identify Smaller 

Areas Experiencing a Lack of Sufficient Jobs 

According to current regulations and guidance, states can support a claim of lack 

of sufficient jobs by providing evidence of a lack of jobs in declining occupations or 

industries. This can be especially true in smaller, rural areas in which the loss of 

a single job provider, such a major manufacturing plant or mining industry, can 

have a major effect on local job availability. In the December 1996 guidance, FNS 

suggested that states could use BLS monthly data published in the ‘‘Employment 

and Earnings’’ report on state and sub-state employment figures by major industry.196 A declining trend within a particular industry or sector may be taken as evidence of declining employment prospects for persons with experience in or skills appropriate to that sector. 

Although states have not frequently used occupation or industry employment data 

to support claims of lack of sufficient jobs, FNS has approved them on a limited 

case-by-case basis. For example, FNS approved waivers for a county (Polk) in Arkansas and a county (Coos) in New Hampshire that were significantly affected by 

plant closures during the recession that started in 2001. The state agencies provided 

evidence of the adverse labor force impacts due to a major factory or plant closing, 

such as the number of workers affected by layoffs and rapidly increasing unemployment rates (ten percent and higher) over a short period of time. The impact of a 

plant closure may not show up in 24 month unemployment rates until several 

months, or even a year, have passed. Information indicating the decline of particular 

industries, such as significant plant closures, gives states the ability to quickly 

adapt their waiver policy to respond to rapidly deteriorating labor market conditions. 

D. Eliminating Criteria of Three-Month Average Unemployment Rate Over Ten Percent and Historical Seasonal Unemployment Rate Over Ten Percent Is Inconsistent With the Statute 

The proposed rule would restrict states’ ability to use an unemployment rate over 

ten percent as the basis for waiver approval. It would limit the use of the criterion 

of a recent 3 month average unemployment rate over ten percent to ‘‘exceptional circumstances’’ and eliminate the criterion of an historical seasonal unemployment 

rate over ten percent.197 This would leave just one criterion—having a 12 month average unemployment rate over ten percent—as the basis for approval using an average unemployment rate over ten percent. These changes are inconsistent with the 

statute and regulations that clearly establish that areas with an unemployment rate 

over ten percent qualify for a waiver. If the Department proceeds to publish a final 

rule it must reject these changes to be consistent with the statute. 

229 

198Food and Nutrition Act, 7 U.S.C. § 2015(o)(4). This language is identical to the language 

in P.L. 104–193, PRWORA. 199 USDA, ‘‘Guidance for states Seeking Waivers for Food Stamp Limits,’’ December 3, 1996. 200Food Stamp Program: Personal Responsibility Provisions of the Personal Responsibility and 

Work Opportunity Reconciliation Act of 1996; 64 FEDERAL REGISTER 242 (December 17, 1999) 

(to be codified at 7 CFR pts. 272 and 273). 201 USDA, ‘‘Guidance for states Seeking Waivers for Food Stamp Limits,’’ December 3, 1996. 202 NPRM, p. 986. 203 USDA, ‘‘Guidance for states Seeking Waivers for Food Stamp Limits,’’ December 3, 1996. 204Food Stamp Program: Personal Responsibility Provisions of the Personal Responsibility and 

Work Opportunity Reconciliation Act of 1996; 64 FEDERAL REGISTER 242 (December 17, 1999) 

(to be codified at 7 CFR pts. 272 and 273). 

According to the statute, a state may waive the applicability of the work requirement ‘‘to any group of individuals in the state if the Secretary makes a determination that the area in which the individuals reside has an unemployment rate above 

10% or does not have a sufficient number of jobs to provide employment for the individuals.’’ 198 The statute clearly establishes the ten percent unemployment rate criterion as a basis for approval. The statute does not specify requirements regarding 

the duration of time that an area must have an unemployment rate above ten percent. 

Three-Month Average Unemployment 

In guidance issued in December 1996 and then reinforced in the preamble of the 

1999 proposed rule,199–200 the Department stated that it would not require a 12 

month average to approve a waiver because of two shortcomings. ‘‘A 12 month average will mask portions of the year when the unemployment rate rises above or falls 

below ten percent. In addition, requiring a 12 month average before a waiver could 

be approved would necessitate a sustained period of high unemployment before an 

area became eligible for a waiver.’’ To address these shortcomings and to ensure 

that waivers are granted as quickly as possible where needed, the Department explained that ‘‘states have several options. First, a state might opt to use a shorter 

moving average. A moving average of at least 3 months is preferred. In periods of 

rising unemployment, a 3 month average provides a reliable and relatively early signal of a labor market with high unemployment. A state might also consider using 

historical unemployment trends to show that such an increase is not part of a predictable seasonal pattern to support a waiver for an extended period (up to 1 

year).’’ 201

In the preamble to the proposed rule, the Department expressed its preference 

that waivers reflect current economic conditions.202 Yet by eliminating the ability 

of states to use a recent 3 month average unemployment rate over ten percent as 

the basis for waiver approval, it is eliminating one of the criteria that most closely 

aligns with current economic conditions and signals deteriorating labor market conditions in an area. 

Historical Seasonal Unemployment 

In guidance issued in December 1996 and in the preamble of the 1999 proposed 

rule,203–204 the Department confirmed the applicability of waivers to ‘‘areas with predictable seasonal variations in unemployment.’’ The Department provided a detailed 

example: 

States may use historical trends to anticipate the need for waivers for certain 

periods. For example, if the pattern of seasonal unemployment is such that an 

area’s unemployment rate typically increases by two percentage points in January, February, and March, and the area’s unemployment rate is currently nine 

percent, a state may request a waiver for this area based on its current rate 

and historical trends. The period covered by the waiver will then coincide with 

the period of high unemployment. 

Aligning the Period Covered by the Waiver and the Period of Projected High Unemployment Does Not Require Data of a Particular Duration 

The 2001 final rule codified criteria related to unemployment rates over ten percent at 7 CFR § 273.24(f)(2)(i) and provided flexibility to meet these criteria using 

data of varying duration. ‘‘To support a claim of unemployment over ten percent, 

a state agency may submit evidence that an area has a recent 12 month average 

unemployment rate over ten percent; a recent 3 month average unemployment rate 

over ten percent; or an historical seasonal unemployment rate over ten percent.’’ 

The intent of current regulations was to align the period covered by the waiver 

to the period when unemployment is high, rather than designate an arbitrary duration requirement: 

230 

205Food Stamp Program: Personal Responsibility Provisions of the Personal Responsibility and 

Work Opportunity Reconciliation Act of 1996; 64 FEDERAL REGISTER 242 (December 17, 1999) 

(to be codified at 7 CFR pts. 272 and 273). 206 NPRM, p. 983. 207 NPRM, p. 985, 992. 208 NPRM, p. 987. 

Therefore, the Department is proposing that in general, the duration of a 

waiver should bear some relationship to the documentation provided in support 

of the waiver request. FNS will consider approving waivers for up to 1 year 

based on documentation covering a shorter period, but the state must show that 

the basis for the waiver is not a seasonal or short term aberration.205

In the preamble of the NPRM, the Department arbitrarily adds a duration requirement of 12 months to the ten percent criterion.206 Only areas with a recent, 

12 month average unemployment rate over ten percent would be considered for approval. Under the proposed rules, the Department may approve a waiver for an area 

with a recent 3 month average unemployment rate over ten percent only if an ‘‘exceptional circumstance has caused a lack of sufficient number of jobs.’’ 207

The Department does not discuss the rationale for restricting the ten percent criterion to a 12 month duration. It does not adequately explain what represents an 

exceptional circumstance and what economic measures might signal this circumstance. It does not discuss what economic measures a state might be able to use 

as an alternative to the 3 month average unemployment rate, which it has described 

as a ‘‘reliable and relatively early signal of a labor market with high unemployment’’ 

in past guidance. 

The Department argues for eliminating the historical unemployment rate criterion 

because it does not demonstrate ‘‘prolonged’’ lack of sufficient jobs, that it is ‘‘limited 

to a relatively short period of time each year,’’ and that it is ‘‘cyclical rather than 

indicative of declining conditions.’’ 208 The Department acknowledges that, by definition, historical seasonal unemployment is contradictory with prolonged duration. 

Rather than drop the newly introduced and contradictory requirement on duration 

(which is inconsistent with existing statute and regulation), the Department argues 

for the elimination of the historical seasonal unemployment criterion (which is 

upheld in existing statute and regulations). 

The Department also proposes to eliminate the historical seasonal unemployment 

criterion because it has not approved a waiver using this criterion. This is not sufficient ground for the proposed change, as the Department has no way of knowing 

if states intend to use this criterion in the future. To maintain consistency with the 

statute, we urge the Department to leave the regulation as is and retain the 3 

month average unemployment rate over ten percent and historical seasonal unemployment rate over ten percent as criteria for waiver approvals. 

E. We Recommend Rejecting Proposed Changes That Would Ignore Important Information About Labor Market Conditions Not Captured by the General Unemployment Rate 

These studies and analyses illustrate how the unemployment rate alone may not 

tell the full story of how abundant or scarce jobs are in the labor market. FNS 

would be mistaken to rely solely on unemployment rates as the basis for demonstrating that an area has a lack of sufficient jobs. The unemployment rate does 

not account working-age persons who may have dropped out of the labor force altogether. Other labor force measures, such as the employment-to-population ratio or 

industry-specific employment data, complement unemployment rates in capturing 

the labor market conditions faced by individuals subject to the time limit, who often 

face significant barriers to labor force participation. In the Great Recession a low 

or depressed employment-to-population ratio was often a better measure of labor 

market slack and lack of job opportunities than the unemployment rate. Thus, a low 

or falling employment-to-population ratio is a valuable indicator and data are available for local areas. 

The proposed rule is based on insufficient reasons to change current regulations 

by prohibiting states from using average unemployment rates over ten percent and 

other available information about labor market conditions, except for areas that 

have limited or unavailable unemployment data from BLS or a BLS-cooperating 

agency. It fails to discuss the reasons why it is restricting the use of average unemployment rates over ten percent during periods of acute or seasonal high unemployment or the limitations of the general unemployment rate in assessing the labor 

market conditions, particularly those faced by individuals subject to the time limit. 

It does not acknowledge the valuable information that will be lost if measures such 

as the employment-to-population ratio are excluded as evidence of lack of sufficient 

231 

209 In 2000, FNS approved a waiver requested by Florida for the combined area of Broward 

and Dade Counties, which belong to the same Metropolitan Statistical Area. 

jobs. Given the lack of supporting information, the public has an insufficient opportunity to comment meaningfully on the proposed rule and we recommend rejecting 

the proposed changes to the rules. 

Chapter 5. Restricting State Flexibility on Grouping Areas Is Counter to 

Evidence 

The NPRM proposes several significant changes to longstanding SNAP policy that 

would significantly restrict state flexibility to develop and implement waiver policy 

that aligns with state operations, priorities, and resources. The NPRM fails to provide reasons for limiting states’ ability to consider relevant factors when grouping 

areas covered by waivers, fails to acknowledge decades of state discretion in grouping areas (including statewide areas) for waivers, and fails to identify the data and 

evidence that justify the elimination of statewide waivers and the use of one narrow, 

inflexible, federally prescribed method for grouping areas. Without knowing what 

evidence justifies such a drastic change in longstanding policy and an adequate discussion of alternative methods for grouping, it is impossible to assess the potential 

impact of the changes on SNAP participants and their ability to achieve self-sufficiency. The sections below provide an overview of existing statutes, regulations, and 

guidance, and discuss factors that states consider when grouping areas, alternative 

grouping methods used by states to group areas, and limitations of the method for 

grouping proposed by the Department. 

A. States Have Had Broad Discretion to Define Areas for More Than Two Decades 

Since the passage of the 1996 welfare law (P.L. 104–193) and the 3 month time 

limit, FNS has given states broad discretion to determine which geographic areas 

the state would like to waive from the 3 month time limit, including an area spanning the entire state or sub-state areas. While every state-defined area as a whole 

must meet the waiver eligibility criteria as set forth in 7 CFR § 273.24(f), states may 

define areas that best align with local and regional labor force conditions, resources, 

and administrative needs. The Federal rules do not limit waivers to specific substate areas, such as cities or counties. As states define areas to request waivers for, 

they often consider a range of factors within geographic regions, such as labor market characteristics, job opportunities, availability of SNAP Employment and Training (E&T) services, housing and transportation, workforce and economic development resources and strategies, and SNAP agency administrative capacity. 

States have had discretion to define areas in accordance with the law, regulation, 

and guidance over the past 22 years. For nearly as long, USDA has approved waivers for entire states or those that group sub-state areas.209 The proposed rule would 

take flexibility away from states to define what areas they wish to waive and restrict states to one narrow, inflexible, federally prescribed criteria. The proposed criteria are likely outdated and disconnected from local and regional factors that states 

consider when developing and implementing policies to connect low-skilled workers 

to job and training opportunities. By prohibiting states from grouping areas according to their needs, FNS would hamper their ability to deliver integrated support to 

SNAP participants in gaining the skills and work experience needed to secure jobs 

leading to self-sufficiency. The proposed rule would severely restrict, and potentially 

eliminate, state flexibility to define areas for waivers, without providing evidence 

that the changes would help increase self-sufficiency among SNAP participants. 

According to the statute, a state may waive the applicability of the work requirement ‘‘to any group of individuals in the state if the Secretary makes a determination that the area in which the individuals reside has an unemployment rate above 

10% or does not have a sufficient number of jobs to provide employment for the individuals.’’ The statute does not identify or require a geographic definition of ’’area.’’ 

The 2018 Farm Bill did not change this and the House bill proposal that sought 

to limit states’ ability to define areas was rejected. 

According to the current rule (7 CFR § 273.24(f)(6)), ‘‘States may define areas to 

be covered by waivers. We encourage state agencies to submit data and analyses 

that correspond to the defined area. If corresponding data does not exist, state agencies should submit data that corresponds as closely to the area as possible.’’ The current rule gives states broad discretion in defining regions, requiring only that the 

data and analysis that states submit to support the waiver request correspond to 

the defined area. 

Below are excerpts from USDA guidance and rulemaking that uphold state flexibility in defining areas: 

232 

210 USDA, ‘‘Guidance for states Seeking Waivers for Food Stamp Limits,’’ December 3, 1996. 211Food Stamp Program: Personal Responsibility Provisions of the Personal Responsibility and 

Work Opportunity Reconciliation Act of 1996; 64 FEDERAL REGISTER 242 (December 17, 1999) 

(to be codified at 7 CFR pts. 272 and 273). 212Food Stamp Program: Personal Responsibility Provisions of the Personal Responsibility and 

Work Opportunity Reconciliation Act of 1996; 66 FEDERAL REGISTER 11 (January 17, 2001). (to 

be codified at 7 CFR pts. 272 and 273). 213 USDA, ‘‘Guidance on Requesting ABAWD Waivers,’’ August 2006. 

• December 3, 1996 guidance: The initial USDA guidance on waivers from the 

3 month time limit gives states flexibility to define areas and goes a step further by encouraging states to consider combining sub-state areas. ‘‘USDA will 

give states broad discretion in defining areas that best reflect the labor market 

prospects of program participants and state administrative needs.’’ 210 While 

USDA encouraged states to consider sub-state waivers over statewide, the flexibility was left completely to states. 

• 1999 proposed rule: In the preamble, USDA noted its intent to ‘‘balance the 

competing goals of ensuring consistent national application of these requirements, and providing state agencies with appropriate implementation flexibility’’ to implement the time limit.211 ‘‘The Department is allowing states broad 

discretion in defining areas that best reflect the labor market prospects of Program participants and state administrative needs. In general, the Department 

encourages states to consider requesting waivers for areas smaller than the entire state. Statewide averages may mask slack job markets in some counties, 

cities, or towns. Accordingly, states should consider areas within, or combinations of, counties, cities, and towns. The Department also urges states to consider the particular needs of rural areas and Indian reservations. Although the 

Department is proposing to allow states flexibility in defining areas to be covered by waivers, the supporting data must correspond to the requested area 

(e.g., a county-wide waiver must be supported by county-wide data). In other 

words, states may define areas to be covered by waivers, but the data 

and analysis used to support the waiver must correspond to the defined 

area.’’ [Emphasis added.] 

• 2001 final rule: In the preamble of the final rule, USDA noted that it had ‘‘proposed that state agencies have complete discretion to define the geographic 

areas covered by waivers so long as they provide data for the corresponding 

area’’ and that most of the comments received supported this proposal. USDA 

explained that, ‘‘for simplicity sake, we encourage states to define areas for 

which corresponding data exists. We believe this is very easily done, especially 

since unemployment data goes down to the census tract level.’’ 212

• August 2006 guidance: ‘‘Jurisdictions or a cluster of areas or counties may be 

combined to waive an area larger than one county. States have authority to define the cluster of areas to be combined. If a state defines its own jurisdiction 

or cluster of areas, the boundaries or clusters must be thoroughly documented 

to expedite review of the waiver request. The Department of Commerce, Bureau 

of Economic Analysis (BEA) is one source that can be used to identify economic 

areas. This data may be found at the website www.bea.gov/bea/regional/docs/ 

econlist.cfm. These areas define the relevant regional markets surrounding metropolitan or micropolitan statistical areas. They consist of one or more economic 

nodes—metropolitan or micropolitan statistical areas that serve as regional centers of economic activity—and the surrounding counties that are economically 

related to the nodes. Other sources or methods may be used to combine a cluster of areas.’’ 213 The guidance also provided an example illustrating the use of 

the Department of Commerce economic areas to create groups of counties in 

Montana. It also explained that ‘‘the state could request a waiver for all counties or a sub-area of the economic areas as long as the data for the combined 

area meets the waiver criteria.’’ 

• December 2, 2016 guidance: In its most recent guidance on waivers, USDA 

repeated that ‘‘the state agency has discretion to define the area(s) in which it 

requests to waive the time limit.’’ According to this latest guidance, ‘‘the state 

can request that a waiver apply statewide or at the sub-state level, as statewide 

averages may mask slack job markets in some counties, cities, or towns. However, in order to receive FNS approval to waive the ABAWD time limit the state 

must support its request with evidence that corresponds to the requested area 

(e.g., a county-wide waiver must be supported by county-wide data). The state 

must also clearly identify which areas are being requested and under which criteria. Unemployed and labor force data from individual areas can be combined 

233 

214 USDA, ‘‘Guide to Supporting Requests to Waive the Time Limit for Able-Bodied Adults 

without Dependents (ABAWD),’’ December 2, 2016. 

to waive a larger group of areas, whether based upon a recent unemployment 

rate over ten percent or a 24 month unemployment rate 20 percent above the 

national average.’’ 214

USDA provided guidance on how states could combine areas. The guidance 

requires that combined areas must be contiguous or must belong to an economic 

region. The guidance provides flexibility in defining an economic region. ‘‘In 

order to be combined, the areas must be contiguous or considered parts of the 

same economic region. For example, two or more contiguous counties could be 

grouped together in order to consider their aggregate average unemployment 

rate. If the counties in the sub-area all belong to the same region, they do not 

need to be contiguous to be defined as an area. The state has discretion to define the group of areas to be combined, provided that the areas are contiguous 

or can be considered to be part of an economic region. If the state defines its 

own group, the rationale for the boundaries of the group must be thoroughly 

documented. For example, state or local labor departments often have defined 

economic regions based upon shared industries or other factors. Other sources, 

methods, or rationale to support that areas share an economic region may also 

be considered.’’ The guidance repeated the example from the August 2006 guidance of using BEA economic areas as a guide for grouping counties. 

Without providing justification or rationale, the proposed rule would end over 2 

decades of consistent guidance and support for state flexibility to determine the geographic scope of waivers that best aligns with state SNAP policies and capacity, 

training and workforce service delivery, funding and resources, and regional planning and strategies. The Department did not discuss or reference over 2 decades of 

consistent regulation and guidance it has issued on grouping areas. The Department 

did not go back to review the comments it received on the 1999 proposed rule supporting the proposal to give states complete discretion to define areas. The Department did not elaborate on any shortcomings it believes exist with the current flexibility that states have to define geographic areas. This makes it difficult for people 

who wish to comment to critique the Department’s proposal to restrict the ability 

of states to define areas they would like to waive from the 3 month time limit. 

The proposed rule significantly restricts the ability of states to waive groups of 

areas. Without providing a discussion, the Department arbitrarily eliminates the 

ability of states to waive the entire state even when statewide unemployment rates 

have risen significantly during an economic downturn, except for situations when 

the state qualifies for extended unemployment benefits. 

The Department introduces a specific definition of labor market areas as the only 

acceptable method for grouping areas and does not acknowledge past guidance it 

has issued that encouraged states to explore different sources and methods for 

grouping areas. It proposes these labor market areas to ensure that grouped areas 

are economically tied, yet this approach only captures one way (commuting patterns) that areas might be economically tied. This proposal ignores all the other 

ways areas may be economically integrated, such as through workforce development 

initiatives, economic development investments, employer recruiting practices, and 

migration patterns. 

For example, guidance issued in 2006 and 2016 both use the BEA economic areas 

(either entire economic areas or sub-areas) to illustrate how a state can combine unemployment data to support a waiver for grouped areas. The guidance suggests that 

states explore other sources or methods for combining areas, including economic regions defined by state or local labor departments. Even if the Department had provided reasons for requiring a very specific method for combining areas, it is difficult 

for the public to understand why the Department would disregard or minimize other 

economic or administrative factors, such as SNAP E&T service provision, that it 

currently gives great consideration to in other aspects of program operations. 

B. States Use the Current Flexibility to Align SNAP Policies With Administrative 

Needs, Job Opportunities, Training Funding and Resources, and Economic and 

Workforce Development Strategies 

States consider multiple factors when grouping areas for waivers to align resources, administrative policies and capacity, and service delivery. A state may consider a range of local, sub-state (regional), and statewide factors: 

• SNAP E&T service delivery 

• TANF work programs 

234 

215Maryland Department of Human Resources, ‘‘Maryland Supplemental Nutrition Assistance 

Program (SNAP) Employment and Training (E&T) Program: state Plan of Operations,’’ Revised 

September 22, 2015, https://dhr.maryland.gov/documents/Data%20and%20Reports/FIA/ 

YR2016%20SNAP%20E&T%20State%20Plan%20of%20Operations%20(revised).pdf. 216 Colorado Department of Human Services, ‘‘Colorado SNAP E&T State Plan: Federal Fiscal 

Year 2017,’’ 2016, http://coemploymentfirst.org/wp-content/uploads/2017/01/Colorado-SNAPE_T-State-Plan-FFY17.pdf. 217 U.S. Department of Agriculture and U.S. Department of Labor, ‘‘Partnering to Help Connect Low-Income Able-bodied Adults to the Public Workforce System,’’ March 31, 2016, https:// 

fns-prod.azureedge.net/sites/default/files/snap/USDA-DOL-joint-ABAWD-letter.pdf. 218 U.S. Department of Agriculture, ‘‘SNAP to Skills: Policy Brief 8,’’ June 2018, https:// 

snaptoskills.fns.usda.gov/sites/default/files/2018-06/Brief_June2018_508comp.pdf. 

• Workforce Innovation and Opportunity Act (WIOA) regional workforce development funding and strategies 

• Office locations (SNAP, workforce development centers) 

• Community college locations 

• Employer and industry recruiting patterns 

• Regional economic development funding and strategies 

• Commuting patterns 

• Housing and transportation patterns 

Aligning With SNAP E&T Coverage 

By limiting state flexibility to define areas, the proposed rule would restrict a 

state’s ability to allocate and coordinate SNAP E&T resources and service delivery 

to meet the needs of its SNAP participants. States have used their discretion to define areas to help align the geographic scope of waivers with areas where they are 

unable to provide sufficient work or training opportunities to work registrants, including those subject to the time limit. A state that can only provide SNAP E&T 

slots in certain counties may request waivers for (eligible) counties where SNAP 

E&T slots are not available or guaranteed. As Maryland was preparing to lose its 

statewide waiver in January 2016, the state agency requested a waiver for multiple 

sub-state areas, including the nine-county Eastern Shore recognized by the state as 

an economic region. In areas not covered by waivers, Maryland offered SNAP E&T 

services to individuals subject to the time limit.215 Similarly, Colorado operated a 

mandatory SNAP E&T program for all work registrants, including individuals subject to the time limit, in 40 of its 64 counties. Individuals in the remaining counties 

were not subject to the time limit because of waivers or the use of individual exemptions, but could still participate in the E&T program on a voluntary basis.216

Aligning With Workforce and Economic Development Regions 

Restricting or eliminating waivers for grouped areas would deny states the ability 

to align SNAP and Workforce Innovation and Opportunity Act (WIOA) regional 

service delivery, funding, and planning efforts. Coordinating service delivery with 

WIOA can help SNAP agencies make more qualified work activities available to 

SNAP participants because participation in a WIOA program is considered a qualifying activity for purposes of meeting work requirements for individuals subject to 

the time limit. 

Both USDA and the Department of Labor (DOL) recognize the opportunity to coordinate these two programs to integrate services and resources and avoid duplication. In a joint letter issued in March 2016, USDA and DOL encouraged SNAP and 

the workforce system to work together to develop shared strategies to better connect 

SNAP participants, specifically individuals subject to the time limit, to job and 

training services through WIOA American Job Centers (AJCs).217 The letter cited 

the shared goal of helping low-skilled, low-income, or low-wage individuals find 

work through training activities and workforce programs. 

A state may want to align its waivers and SNAP E&T service delivery with WIOA 

regions, workforce development regions, or economic development regions in order 

to best plan and coordinate service delivery related to training and job opportunities 

for the population subject to the time limit. States may be able to maximize administrative capacity by aligning service delivery, case management, and data tracking 

by multi-county regions, such as WIOA Local Workforce Development Areas. 

For example, Tennessee SNAP E&T services are delivered through the workforce 

system. SNAP E&T participants are referred to the WIOA program for training provided through partnerships with technical and community colleges. SNAP participants have access to on-the-job training (OJT) opportunities not available outside 

of the WIOA–SNAP E&T partnership.218 Tennessee organizes its workforce activities into three regions: East, Middle, and West. These regions are further broken 

235 

219Tennessee Department of Labor and Workforce Development, ‘‘Map of Realignment of 

Local Workforce Development Areas,’’ 2018, https://www.tn.gov/content/dam/tn/workforce/ 

documents/ProgramManagement/RealignmentMaps.pdf. 220 ‘‘TN Realigns Workforce Development Areas,’’ The Chattanoogan, June 28, 2018, https:// 

www.chattanoogan.com/2018/6/28/371092/TN-Realigns-Workforce-Development-Areas.aspx. 221 U.S. Department of Agriculture, ‘‘SNAP to Skills: Policy Brief 8,’’ June 2018, https:// 

snaptoskills.fns.usda.gov/sites/default/files/2018-06/Brief_June2018_508comp.pdf. 222 U.S. Department of Agriculture, Office of Inspector General. ‘‘FNS Controls Over SNAP 

Benefits for Able-Bodied Adults Without Dependents,’’ Audit Report 27601–0002–31, https:// 

www.usda.gov/oig/webdocs/27601-0002-31.pdf. 223 U.S. Department of Agriculture, ‘‘State Highlights: California,’’ Retrieved Feb. 15, 2019, 

https://snaptoskills.fns.usda.gov/state-highlights/state-highlights-california. 

down into Local Workforce Development Areas (LWDAs). In 2007, before Tennessee 

eventually became eligible for a statewide waiver during the most recent recession, 

the state requested waivers for groups of counties belonging to the same LWDAs 

(known as Local Workforce Investment Areas before the passage of WIOA in 2014). 

States sometimes adjust the regional alignment of programs to reflect changes to 

the labor force, resources, service delivery, and administrative capacity. Federal 

agencies may not be aware of these changing circumstances or be able to make adjustments in a timely manner. In 2018, Tennessee realigned its LWDAs by consolidating 13 areas into nine.219 The Tennessee Workforce Development Board realigned the LWDAs to match the regional organization of other programs, such as 

the Tennessee Department of Economic and Community Development base camps, 

Tennessee Reconnect Communities, and Tennessee Pathways regions.220

Alignment With Other Regional Factors 

Beyond the alignment opportunities between SNAP E&T and WIOA, there are 

many other reasons why a state might group sub-state areas. States may combine 

different streams of funding to delivery SNAP E&T services regionally. Some funding opportunities may be available as regional grants, such as some CDBG grants 

or workforce development grants. In Portland, Oregon, the regional Workforce Development Board integrates WIOA, SNAP E&T, Community Development Block 

Grant, and other funding streams, to provide workforce development activities serving SNAP recipients and others in the Portland region.221

States may have administrative reasons for grouping areas. According to a 2016 

report by the USDA Office of Inspector General, the requirements related to the 

time limit are difficult to implement.222 Some state officials said that waivers can 

help reduce the burden of tracking individuals subject to the time limit. A state may 

request a waiver to cover areas that have reduced administrative capacity and give 

areas more time to acquire staff, training, or upgrade case management or data systems. For example, San Francisco County in California used the time while it was 

covered by the waiver to upgrade its data systems and secure new E&T partnerships.223

States may want to align waivers with the geographic scope of other resources. 

A state may align Information Technology (IT) systems, such as eligibility, case 

management, or data tracking systems within geographic regions. Counties in California are grouped into eligibility system consortia (with 40 counties belong to the 

CalACES consortium and 18 counties belonging to the CalWIN consortium). Within 

each consortium, counties are further organized into regions (eight CalACES regions 

and four CalWIN regions). Each of these consortia systems support TANF work programs, SNAP E&T activities, and county-specific employment programs. Waivers for 

groups of counties could be organized by consortia regions to help align service delivery, case management, and data tracking. 

The Department did not explain why it was eliminating states’ ability to use relevant methods for grouping areas, such as workforce development service delivery, 

to inform how they group areas covered by waivers. From 2 decades of experience 

reviewing state waiver requests, the Department is aware of how states use their 

existing flexibility to balance multiple priorities, resources, and policies, such as 

SNAP E&T policies and services, housing and transportation planning, and workforce and economic development strategies. The Department did not provide reasons 

for ignoring these other considerations, making it difficult for the public to comment 

on the proposed changes. As a Federal agency, USDA may not be aware of all the 

local and sub-state factors that impact the development and delivery of employment 

and training services. The proposed rule makes sweeping and arbitrary changes 

that will hamper states’ ability to integrate and coordinate resources to provide employment and training to SNAP recipients. By prohibiting states from grouping substate areas, the agency would limit states’ ability to coordinate and align SNAP 

236 

224South Carolina had a 2 year statewide waiver that expired in February 2009. 225Oregon was waived under a 2 year statewide waiver that ended in April 2008. 

ABAWD policies with training opportunities and resources, workforce and economic 

development strategies, and other factors within the state. 

C. Eliminating a State’s Ability to Adjust to Rising Unemployment Across the State 

The proposed rule would eliminate statewide waivers when sub-state unemployment data is available, except for situations when a state qualifies for extended unemployment benefits. The Department provides no discussion of the rationale for 

eliminating this flexibility, other than asserting that the use of sub-state unemployment data helps target particular areas with high unemployment. This ignores the 

statistical principle of weighted averages—in order for an entire state to qualify 

under current rules, unemployment rates throughout the states must have risen 

dramatically, particularly in the most populous areas of the state. 

While we commend the Department for retaining the qualification of a state for 

extended unemployment benefits (EB) as a core standard for approval, this criterion 

does not adequately detect states with high unemployment rates that are not rising 

rapidly. States must meet both the minimum 3 month unemployment threshold of 

6.5 percent and have rising unemployment over at least 1 year in order to qualify 

for extended benefits. States that only meet one of these conditions would not be 

able to obtain a waiver. For example, a state with a consistent unemployment rate 

of eight percent over time would not qualify for extended benefits because its rate, 

by definition, is not rising. Similarly, a state with rapidly rising unemployment, but 

whose rate has not yet reached 6.5 percent, would also not qualify. In both examples, states can have high or worsening unemployment and would not be able to obtain a waiver to help SNAP participants working in these economic conditions. 

To illustrate this, consider the experience of South Carolina and Oregon in 2007, 

prior to the Great Recession. These states had high unemployment in the months 

preceding the recession, but under the proposed rule would have had no options for 

statewide waivers until well into the recession. South Carolina qualified for extended benefits in August 2008, 8 months into the recession that started in December 2007. Had the state sought a waiver for 2007 based on statewide unemployment 

rates,224 it would have qualified based on 24 month average unemployment rates 

that ranged between 6.6 and 6.8 percent for the various periods relevant for such 

a waiver. Similarly, the state would have qualified for a 2008 statewide waiver 

under existing rules, based on 24 month average unemployment rates that ranged 

between 6.1 and 6.6 percent for the various periods relevant for such a waiver. 

Oregon qualified for extended benefits in November 2008, 11 months after the 

start of the recession. Had Oregon sought a waiver for 2007 based on statewide unemployment rates,225 it would have qualified based on 24 month average unemployment rates that hovered between 5.8 and 6.7 percent for the relevant period. 

The proposed rule only allows waivers for sub-state geographies, and not the entire state, until statewide labor market conditions become so dire that the state 

qualifies for extended benefits. The Department argues that statewide unemployment figures may include areas in which unemployment rates are relatively low and 

that eliminating statewide waivers will help target areas in which unemployment 

rates are high. The Department does not discuss the dynamic nature of labor market conditions across time and across geographic areas. Unemployment rates do not 

change uniformly within a state. A state may include areas with persistently high 

unemployment, areas with relatively low but rapidly rising unemployment rates, 

areas with high unemployment rates that are slowly creeping higher, as well as 

areas with relatively low unemployment rates. 

Current rules allow a state to detect deteriorating economic conditions across the 

state even before it qualifies for extended unemployment benefits. The Department 

makes an arbitrary decision to eliminate statewide unemployment analysis because 

of potential variation in unemployment rates within the state. Variation in unemployment rates exists at all geographic levels, including at small scale Census tract 

and Census block group levels. The Department’s failure to provide a robust assessment of the impact of this change on the ability of states to cushion the blow of 

deteriorating economic conditions across their borders makes it difficult to comment 

on the proposed rule. 

Arbitrary Standard for Grouping Areas 

The proposed rule would limit the ability of states to request waivers for groups 

of geographic areas, such as multi-county areas, except for areas that are ‘‘economically tied.’’ The Department provides a limited definition of an ‘‘economically tied’’ 

area based on commuting patterns—an area within which individuals can reside 

237 

226 Bureau of Labor Statistics, ‘‘Local Area Unemployment Statistics Geographic Concepts: 

Labor Market Areas,’’ 2018, https://www.bls.gov/lau/laugeo.htm#geolma. 

and find employment within a reasonable distance or can readily change employment without changing their place of residence. The preamble says that ‘‘existing 

general conditions for grouping of areas—that the areas must be either contiguous 

and/or share the same economic region—were intended to ensure that the areas 

grouped together are economically tied.’’ Yet in statutes, regulations, and guidance 

over the past 2 decades, USDA has given states broad discretion to define areas and 

has never expressed the requirement of that grouped areas be ‘‘economically tied’’ 

based solely on commuting patterns. The proposed rule arbitrarily imposes this requirement without providing justification or acknowledging the many other ways 

areas can be economically tied apart from commuting patterns, such as employer 

recruiting practices, regional workforce development strategies, and regional economic development and investment patterns. 

More specifically, the proposed rule would limit grouping to areas that are designated labor market areas (LMAs) based on a narrow statistical definition used by 

the Bureau of Labor Statistics (BLS). USDA has requested public comment on 

whether it should be even more restrictive and prohibit grouping entirely. USDA 

proposes taking away state discretion to define areas, arguing that the application 

of waivers on a more limited basis will encourage more individuals subject to the 

time limit to take steps towards self-sufficiency, but does not explain how restricting 

the grouping of areas will help achieve this goal. USDA did not offer any other alternative frameworks for grouping areas for discussion, even the Bureau of Economic Analysis economic areas that it has used as an example for grouping in past 

guidance. 

D. Using a Narrow, Statistical Definition of Labor Market Areas 

The Department uses the BLS definition of a labor market area, which is an area 

within which individuals can reside and find employment within a reasonable distance or can readily change employment without changing their place of residence.226 It defines an ‘‘economically tied area’’ the same way. By using the same 

definition for ‘‘labor market area’’ and ‘‘economically tied area,’’ the Department is 

conflating the two concepts and makes it confusing and challenging for the public 

to respond. The Department appears to be taking the BLS definition of labor market 

areas and applying it to the more general concept of ‘‘economically tied’’ areas. 

Using the relatively narrow definition of labor markets to also define economically 

tied areas ignores the various ways areas can be connected economically beyond 

commuting patterns. For example, areas can share economic ties through investment patterns, service delivery models, and migration patterns. 

The proposed rule establishes BLS labor market areas as the only standard by 

which sub-state areas may be grouped together and covered by a waiver from the 

3 month time limit. To delineate the entire United States into mutually exhaustive 

and exclusive labor market areas, BLS uses a narrow operational definition that relies solely on measures of population size and commuting flows between counties. 

BLS LMAs include both the metropolitan and micropolitan areas defined by the Office of Management and Budget (OMB) and the small labor market areas maintained by the BLS Local Area Unemployment Statistics (LAUS) program. 

Major labor market areas include Core Based Statistical Areas (CBSAs), which 

can be either Metropolitan Statistical Areas or Micropolitan Statistical Areas. Metropolitan Statistical Areas have at least one urbanized area with a population of 

50,000 or more, along with adjacent territory that has a high degree of social and 

economic integration with the core (as measured by commuting patterns). 

Micropolitan Statistical Areas have at least one urban cluster with a population of 

at least 10,000 but less than 50,000, along with adjacent territory that has a high 

degree of social and economic integration with the core (as measured by commuting 

patterns). 

An outlying county is combined with the central county or counties of the CBSA 

if it meets the following commuting requirements: 

• At least 25 percent of the workers living in the county work in the central county or counties of the CBSA; or 

• At least 25 percent of the employment in the county is accounted for by workers 

who reside in the central county or counties of the CBSA. 

238 

227Office of Management and Budget, Revised Delineations of Metropolitan Statistical Areas, 

Micropolitan Statistical Areas, and Combined Statistical Areas, and Guidance on Uses of the Delineations of These Areas, 2015. https://www.whitehouse.gov/sites/whitehouse.gov/files/omb/ 

bulletins/2015/15-01.pdf. 228 Bureau of Labor Statistics, ‘‘Local Area Unemployment Statistics Geographic Concepts: 

Labor Market Areas,’’ 2018, https://www.bls.gov/lau/laugeo.htm#geolma. 229Office of Management and Budget, ‘‘Revised Delineations of Metropolitan Statistical Areas, 

Micropolitan Statistical Areas, and Combined Statistical Areas, and Guidance on Uses of the 

Delineations of These Areas,’’ 2015, https://www.whitehouse.gov/sites/whitehouse.gov/files/ 

omb/bulletins/2015/15-01.pdf. 230Office of Management and Budget, ‘‘Revised Delineations of Metropolitan Statistical Areas, 

Micropolitan Statistical Areas, and Combined Statistical Areas, and Guidance on Uses of the 

Delineations of These Areas,’’ 2013, https://www.whitehouse.gov/sites/whitehouse.gov/files/ 

omb/bulletins/2013/b13-01.pdf. 

Metropolitan and Micropolitan Statistical Areas are delineated in terms of whole 

counties (or equivalent entities) and counties can only belong to one CBSA.227

For counties that do not belong to metropolitan or micropolitan areas, counties are 

combined into a small LMA if either or both of the following conditions are met: 228

• At least 25 percent of the employed residents of one county commute to work 

in another county; and 

• At least 25 percent of the employment (persons working) in one county are accounted for by workers commuting from another county. 

Labor market areas can vary in geographic scope, ranging from a single county 

to multi-county metropolitan areas. LMAs can also span multiple states and in New 

England, they are composed of cities and towns. The proposed rule requires states 

to group all areas within an LMA together (leaving no areas out), but multi-state 

LMAs would require states to treat areas within their state borders separately from 

the rest of its LMA. 

Based on the conditions described earlier, the BLS labor market area definition 

only considers aggregated commuting patterns between county of residence and 

county of employment—and does not take into account sub-county variations by industry or by an individual’s socioeconomic and demographic characteristics. It also 

does not take into account the many other dynamics beyond commuting patterns 

that may impact an individual’s ability to find and secure a job, such as housing 

and transportation, the location of new or future employment opportunities, the location of training providers (such as community colleges), industry-specific recruitment practices, or regional workforce or economic development strategies. It also 

does not reflect the ability of some individuals to relocate within a state to pursue 

a job opportunity. 

According to OMB guidance, the purpose of the Metropolitan and Micropolitan 

Statistical Area standards is to provide nationally consistent delineations for collecting, tabulating, and publishing Federal statistics for a set of geographic areas. 

OMB establishes and maintains these areas solely for statistical purposes and does 

not take into account or attempt to anticipate any non-statistical uses that may be 

made of the delineations, nor will OMB modify the delineations to meet the requirements of any non-statistical program. OMB cautions that Metropolitan Statistical 

Area and Micropolitan Statistical Area delineations should not be used to develop 

and implement Federal, state, and local non-statistical programs and policies without full consideration of the effects of using these delineations for such purposes.229

While this does not preclude the Department or states from using LMAs to inform 

the grouping of areas covered by waivers, the Department did not explain the rationale for, and effect of, using LMAs as the only framework for grouping areas and 

its reasons for excluding other methods for grouping. 

In the following section, we discuss some of the other approaches for grouping 

areas that capture regional dynamics that BLS LMAs don’t account for and that 

FNS did not explain whether it considered. We also discuss how FNS failed to address why it believes LMAs are preferable to the many possible alternatives. 

BLS LMA Definition Based on Outdated Data 

BLS LMAs are limited in their ability to capture current and local workforce dynamics. They are relatively static and do not account for sub-county variation. The 

BLS LMAs are revised each decade following the census. The current list of BLS 

LMAs are based on population data from the 2010 Census and commuting data 

from the American Community Survey 5 year dataset for 2006–2010 (issued on February 28, 2013, through OMB Bulletin No. 13–01 (https://www.whitehouse.gov/ 

sites/whitehouse.gov/files/omb/bulletins/2013/b13-01.pdf)).230 In other words, current BLS LMAs reflect population data from 9 years ago and commuting data from 

239 

231Stephan J. Goetz and Yicheol Han, ‘‘Identifying Labor Market Areas Based on Link Communities,’’ paper prepared for presentation at the 2015 Agricultural & Applied Economics Association and Western Agricultural Economics Association Annual Meeting, San Francisco, CA, 

July 26–28, 2015, https://aese.psu.edu/nercrd/publications/published-papers/identifying-labormarket-areas-based-on-link-communities. 232 NPRM, p. 992. 233 Andrew Foote, Mark J. Kutzbach, and Lars Vilhuber, ‘‘Recalculating . . . How Uncertainty 

in Local Labor Market Definitions Affects Empirical Findings,’’ Center for Economic Studies 

Working Paper CES 17–49, August 2017, https://www2.census.gov/ces/wp/2017/CES-WP-17- 

49.pdf. 234 Erik Scherpf, et al., ‘‘Participation in USDA’s Supplemental Nutrition Assistance Program 

(SNAP): Effect of Local Labor Market Conditions in Oregon,’’ United [S]tates Department of Agriculture (September 2018), pp. 1–50, https://www.ers.usda.gov/webdocs/publications/90038/ 

err-257.pdf?v=0. 235 Charles M. Tolbert and Molly Sizer, ‘‘U.S. Commuting Zones and Labor Market Areas: A 

1990 Update, AGES–9614,’’ U.S. Department of Agriculture, Economic Research Service, 1996, 

https://usa.ipums.org/usa/resources/volii/cmz90.pdf. 236 Hierarchical cluster analysis is a method for exploring similarities between objects. An algorithm is used to group similar objects into a cluster. Each cluster is distinct from other cluster 

and the objects within each cluster share similar features. 

9 to 14 years ago. The BLS LMAs are not updated frequently enough to capture 

current or recent labor market trends and may not line up with more current labor 

force patterns. 

The BLS LMAs are based on population and commuting data aggregated at the 

county level. The commuting patterns between counties may vary depending on the 

industry or type of occupation. For instance, commuting flows for workers working 

at an automotive assembly plant (which may be relatively focused around the plant 

location) will tend to vary from commuting flows for workers in food retail (relatively dispersed). Goetz and Han note that a given county may belong to multiple 

commuting sheds and give the example of a commuter county on the east coast with 

residents who commute to Washington, D.C., Philadelphia, and Baltimore and may 

be located in the border region between the cores of multiple LMAs.231 Another example is Mercer County, Pennsylvania, which could be considered part of Philadelphia’s LMA or New York’s LMA based on the commuting patterns of residents. In 

these situations, it is not obvious which commuting regions or labor market areas 

the county should be considered a part of and will vary depending on the industry 

or type of worker. 

Some BLS LMAs include areas from more than one state. For example, the Philadelphia LMA includes counties belonging to Pennsylvania, New Jersey, Delaware, 

and Maryland. The proposed regulatory language says that ‘‘the state agency may 

only combine data from individual areas that are collectively considered to be a 

Labor Market Area by DOL.’’ 232 The Department did not discuss how states should 

handle multi-state LMAs, making it difficult for the public to comment on the implications of using only BLS LMAs to group areas. Consider an LMA that spans two 

states, but with 90 percent of its population residing in one state. Suppose the county with ten percent of the population has an unemployment rate that is slightly 

lower than the threshold needed to qualify for a waiver, but the unemployment rate 

for the entire LMA exceeds the threshold needed to qualify. Would that county qualify for a waiver, recognizing that the LMA that it belongs to may lack sufficient 

jobs? 

Alternative Definitions of Labor Market Areas 

Unlike a county or state, which are political and administrative units with defined 

borders, a labor market area is an analytical concept and the definition used by BLS 

is only one of several ways that labor economists and other researchers approximate 

labor market areas. ‘‘Researchers examining labor markets in the United States 

often turn to one of several standard geographic definitions that are widely known 

and compatible with publicly available economic data, including: states, metropolitan areas, and counties.’’ 233 Definitions of labor market areas that are based on single or multiple counties, such as the one used by BLS, have the advantage of having 

unemployment data readily available. However, the political or administrative 

boundaries that are used to delineate labor market areas may not always align well 

with the notion of a labor market as ‘‘a set of relationships between employers and 

workers that are spatially bounded by places of work and residence.’’234–235

For example, a definition of a local labor market area that attempts to better capture an area in which individuals both live and work is the Commuting Zone (CZ). 

CZs group counties based on commuting flow data and hierarchical cluster analysis.236 Noting that there is no consensus definition of LMAs, economists at the EcoVerDate Aug 31 2005 11:16 Jun 14, 2019 Jkt 041481 PO 00000 Frm 00245 Fmt 6621 Sfmt 6621 P:\DOCS\116-02\36188.TXT BRIAN
240 

237 Erik Scherpf, et al., ‘‘Participation in USDA’s Supplemental Nutrition Assistance Program 

(SNAP): Effect of Local Labor Market Conditions in Oregon,’’ United [S]tates Department of Agriculture (September 2018), pp. 1–50, https://www.ers.usda.gov/webdocs/publications/90038/ 

err-257.pdf?v=0. 238 Alessandra Fogli, Enoch Hill, and Fabrizio Perri, ‘‘The Geography of the Great Recession,’’ 

National Bureau of Economic Research Working Paper 18447, October 2012, https:// 

www.nber.org/papers/w18447.pdf. 

nomic Research Service, Scherpf, et al., tested multiple definitions of LMAs (BLS 

LMAs, Commuting Zones, and Workforce Innovation Areas) in their examination of 

the relationship between labor market area conditions and length of SNAP participation spell.237 Their preferred definition of LMAs used the CZ definition and had 

the largest estimated effects. They found that a ten percent increase in county-level 

employment raised the share of recipients who finished their SNAP spell in 12 

months or less by about 5.3 percentage points (or about 8.8 percent). Using alternative definitions of labor market areas resulted in smaller, but still positive, estimated effects: a ten percent increase in county-level employment raised the probability that a SNAP recipient would finish a spell in 12 months or less by between 

1.5 and 2 percentage points (or between two and three percent). 

Although CZs are delineated using more sophisticated analytical methods, they 

share a similar limitation to BLS LMAs. Like BLS LMAs, CZs are based on commuting patterns and do not account for other administrative or economic factors a 

state would like to consider when grouping areas covered by waivers. In proposing 

the BLS LMAs as the only acceptable framework for grouping areas, the Department did not discuss alternative frameworks for grouping and the implications of 

using a framework based on commuting data to shape SNAP policy. 

Commuting Patterns Are Not the Only Factor Connecting Labor Markets 

BLS LMAs only look at commuting patterns and ignore other economic factors 

that may be related to spatial correlation of unemployment. Spatial correlation is 

a measure of the relationship between ‘‘close’’ spatial units, such as neighboring 

counties. Using county-level monthly price data from the real estate service Zillow, 

Fogli, Hill, and Perri examined trends in housing prices across geographic areas. 

They observed that the housing price decline from early 2007 to early 2009 appeared to follow the same spatial patterns as unemployment.238 Looking at the example of Florida, they show that early 2007 prices fell in scattered locations around 

the coasts and over time prices fell in nearby locations until they reached a uniformly low level across the state. Spatial diffusion of housing prices and unemployment were strikingly similar across the whole period of housing boom and bust, suggesting that housing prices might be one of the factors that states may implicitly 

or explicitly consider when grouping areas. 

The Department did not provide an explanation why it is restricting states from 

considering other rationale that might be relevant to their SNAP population when 

requesting waivers. We strongly encourage the Department to review the research 

we have outlined in this chapter related to commuting patterns and to explain its 

rationale relative to the evidence that demonstrates the flaws of this approach. 

WIOA Regions 

As discussed earlier, states may seek to align SNAP waivers with workforce development regions. Under WIOA, states are required to identify regions for regional 

workforce planning. States shall identify regions after consultation with elected officials and Local Workforce Development Boards and take into account the following 

factors: 

1. The extent to which regions are consistent with labor market areas in the 

state; 

2. The extent to which regions are consistent with regional economic development areas in the state; and 

3. An assurance that regions have available the Federal and non-Federal resources necessary to effectively administer activities under subtitle B and 

other applicable provisions of the WIOA, including whether the areas have 

the appropriate education and training providers, such as institutions of higher education and area career and technical education schools. 

Under WIOA, states have discretion to define regions and are encouraged to take 

an integrated approach to account for a range of different factors. States are encouraged to use LMAs as the starting point for determining workforce development regions, but also need to consider workforce and economic development framework, 

funding streams, and service (training) delivery. 

241 

239 Virginia Board of Workforce Development, ‘‘Designation of Regions and Planning Requirements,’’ June 2016, https://virginiacareerworks.com/wp-content/uploads/Policy-200-06-Designation-of-Regions-and-Planning-Requirements-FINAL-Signed.pdf. 240 Rhode Island, Governor’s Workforce Board, ‘‘Regional Planning Policy,’’ March 16, 2017, 

https://gwb.ri.gov/wp-content/uploads/2017/06/17-01-3-16-2017.pdf?189db0. 241 USDA, ‘‘Guidance on Requesting ABAWD Waivers,’’ August 2006. 242 USDA, ‘‘Guide to Supporting Requests to Waive the Time Limit for Able-Bodied Adults 

without Dependents (ABAWD),’’ December 2, 2016. 

E. States Have Used Their Discretion to Create Groupings Informed by Multiple Factors 

States use grouping methods, such as BLS LMAs and WIOA Local Workforce Development Areas, as the starting point for developing workforce development plans 

and policy, but modify them based on multiple additional factors. Below are some 

examples of how and why states group areas using a variety of factors. 

• When designating areas for workforce development planning, the Virginia 

Board of Workforce Development considers the BLS LMAs, regional economic 

development areas, funding streams and service providers for training, community college regions, and industry- and sector-specific strategies.239

• Rhode Island has treated the entire state as a region for the purposes of workforce development planning. The state considered geographic boundaries, LMA 

analysis, and funding and resource realities in determining the geographic 

scope of its workforce development plan. From its labor market area analysis, 

it found that of the 39 cities and towns in Rhode Island, 36 fell within the 

‘‘Providence-Warwick, RI–MA Metropolitan NECTA’’ LMA as determined by the 

Bureau of Labor Statistics. One additional community was its own LMA due to 

the fact it is an island, and two additional communities fall outside of the Providence-Warwick, RI–MA Metropolitan NECTA. The governor concluded that the 

entire state will be a single planning region for workforce development purposes.240

• As discussed earlier, Tennessee implements SNAP E&T in coordination with 

WIOA and Local Workforce Development Areas. The delineation of these areas 

is different from the BLS LMAs. For instance, Lauderdale County, located on 

the western border of Tennessee north of Memphis, is its own BLS LMA, but 

is grouped with Shelby, Fayette, and Tipton Counties into the Greater Memphis 

Local Workforce Development Area. 

The Department did not explain why it was taking away states’ ability to consider 

multiple factors when grouping areas covered by waivers. It did not discuss how the 

use of BLS LMAs would improve states’ ability to meet the needs of individuals subject to the time limit and help move them to self-sufficiency. 

BEA Economic Areas 

In two separate guidance memoranda (August 2006,241 December 2016 242), the 

Department provided an example of grouping based on BEA economic areas, yet the 

2019 NPRM preamble did not offer this framework for grouping areas for consideration. In the example provided, the Department explained that Montana could 

group the counties of Blaine, Cascade, Chouteau, Glacier, Hill, Liberty, Phillips, 

Pondera, Teton, and Toole that comprise the North Central Montana Economic Area 

(or Area 65: Great Falls, MT Economic Area) and analyze the data to see if the 

grouped area would qualify for a waiver. The guidance also suggested that the state 

could consider grouping a sub-area such as Glacier, Liberty, and Toole. The Department did not explain why it is eliminating this grouping approach, even though this 

was a grouping policy it has suggested that states could use in the past. 

Requiring Areas to Be Contiguous Ignores the Reality That Proximity to Job Opportunities Is Decreasing 

The proposed rule establishes BLS LMAs as the only scenario where states can 

request waivers for combined geographic areas (counties). In doing so, the agency 

seeks to limit waivers that combine areas that are not contiguous. This suggests an 

assumption that individuals will only respond to job opportunities in their county 

or in counties adjacent to their county of residence. From the perspective of workers 

in search of job opportunities, requiring contiguity of geographic areas is an assumption that does not hold up under empirical scrutiny. Using county-level data for 

eight states between 1969 to 1994, Khan, Orazem, and Otto found that local county 

population responded to economic growth within the county, in adjacent counties, 

242 

243 Romana Khan, Peter F. Orazem, and Daniel M. Otto, ‘‘Deriving Empirical Definitions of 

Spatial Labor Markets: The Roles of Competing Versus Complementary Growth,’’ Journal of Regional Science (2001), pp. 735–756. 244 Elizabeth Kneebone and Natalie Holmes, ‘‘The Growing Distance Between People and Jobs 

in Metropolitan America,’’ Metropolitan Policy Program at Brookings (March 2015), pp. 1–24, 

https://www.brookings.edu/research/the-growing-distance-between-people-and-jobs-in-metropolitan-america/. 245 Alessandra Fogli, Enoch Hill, and Fabrizio Perri, ‘‘The Geography of the Great Recession,’’ 

National Bureau of Economic Research Working Paper 18447, October 2012, https:// 

www.nber.org/papers/w18447.pdf. 

and even two counties away.243 The effect decreased as the distance from the reference county increased. Workers look beyond their county and adjacent counties for 

job opportunities. 

Other research has found that proximity to jobs has decreased in metropolitan 

areas in recent years and that poor, minority residents experienced a bigger decline 

in proximity to jobs compared to non-poor white resident. Kneebone and Holmes 

looked at the number of jobs within a typical commuting distance (median withinmetro commuting distance) for residents of the 96 largest metropolitan areas and 

found that the number of jobs within a typical commuting distance declined by 

seven percent between 2000 and 2012.244 Poor residents experienced a 17 percent 

decline in nearby jobs compared to six percent for non-poor residents. Hispanic residents had a 17 percent decline and black residents had a 14 percent decline compared to six percent for white residents. Individuals have to look farther from their 

local neighborhoods for job opportunities, requiring longer commutes. 

Requiring Areas to Be Contiguous or to Comprise Entire LMAs Ignores the Reality 

That Unemployment Rates Rise and Fall at Different Rates Even in Neighboring Areas 

The general unemployment rate does not account for variations in unemployment 

rates for sub-populations and for variations in the increase or decrease in unemployment rates across geographic areas. The proposed rule would require that states request waivers for BLS LMAs in their entirety, without omitting certain areas. The 

Department offers no rationale for proposing this and no discussion of the implications of this arbitrary requirement. This requirement prevents states from responding to variations in unemployment patterns within an LMA. 

Fogli, Hill, and Perri examined how the relationship in unemployment in neighboring areas changes over time as a recession starts and ends.245 The relationship 

in unemployment between neighboring areas (spatial correlation) is high overall, 

falls at the start of the recession, increases sharply during the recession, and then 

stabilizes at the end of the recession. They found that unemployment does not increase in all counties simultaneously, but initially increases in a few specific counties, not necessarily located close to each other. As the recession deepens, the geographic distribution of unemployment follows an epidemic pattern, with unemployment tending to increase in counties that are closer to counties initially hit with 

high unemployment, so that unemployment is high in some concentrated areas and 

relatively low in others, and this results in an increase in the degree of spatial correlation and of spatial dispersion. As the recession reaches its peak, high unemployment is spread all over the country and both the degree of spatial correlation and 

spatial dispersion stabilize (and eventually decline). 

The Department does not discuss the implications of requiring that states request 

waivers for BLS LMAs in their entirety, without omitting areas. This requirement 

ignores variations in labor market conditions within a labor market area. Consider 

an LMA that does not qualify for a waiver, but has high unemployment everywhere 

except for one county. The proposed rules would prevent a state from requesting a 

waiver for a sub-area of the LMA that lacks sufficient jobs, even if most of the residents in that LMA reside in that sub-area and the sub-area had unemployment 

rates that met or exceeded the threshold to qualify for a waiver. Even if the LMA 

qualified for a waiver, the state may have reasons why it only wants to waive a 

sub-area of the LMA. For instance, the state may be able to guarantee SNAP E&T 

slots in most areas of the LMA, but wants to request a waiver to cover counties in 

the LMA where it cannot guarantee enough slots. Even if the areas the state wants 

to waive qualified for a waiver based on unemployment rates, because it comprises 

only a part of the LMA, it would not be eligible for a waiver. 

F. Conclusion: We Recommend Rejecting Proposed Changes That Restrict State Flexibility to Waive Groups of Areas 

The proposed rule is based on insufficient reasons to change current regulations 

by prohibiting states from seeking statewide waivers and from grouping areas, exVerDate Aug 31 2005 11:16 Jun 14, 2019 Jkt 041481 PO 00000 Frm 00248 Fmt 6621 Sfmt 6621 P:\DOCS\116-02\36188.TXT BRIAN
243 

246 NPRM p. 984. 

cept for areas that are designated as BLS labor market areas. It fails to discuss the 

ways that states have used existing flexibility to align waiver policy with state operations, policy, and resources. It does not discuss the implications and limitations of 

its proposed framework for grouping, nor does it address alternative methods for 

grouping, including those suggested by the Department in past guidance. Given the 

lack of supporting information, the public has an insufficient opportunity to comment meaningfully on the proposed rule and we recommend rejecting the proposed 

changes to the rules. 

Chapter 6. Taking Away Food Benefits from Individuals Who Cannot Document 20 Hours a Week of Work Will Not Increase Labor Force Participation for This Population 

USDA offered little rational for changing the decades-old criteria for requesting 

waivers of the time limit. The primary reasoning it provided is that fewer waivers 

will result in more individuals subject to the time limit. The agency believes that 

if the state threatens to withhold food benefits from these individuals, they will 

work more and have higher participation rates in meaningful work activities. The 

NPRM often describes this as a ‘‘belief.’’ For example, the NPRM states, ‘‘the Department believes the local unemployment floor should be set at seven percent to 

best meet its goals of promoting self-sufficiency’’ 246 (emphasis added). But the 

NPRM provides no evidence to support the belief that taking away food from unemployed individuals will result in higher labor force attachment or greater participation in job training. Because the NPRM includes no supporting data or research, 

commentators are left to accept as unequivocally true that the time limit has an 

instrumental role in moving ‘‘ABAWDs’’ from non-work to work. 

Yet the claim that subjecting additional individuals to the time limit will result 

in more meaningful work activities is wildly out of synch with what we know from 

the evidence. Research shows that a significant share of individuals subject to the 

time limit work when they can find employment (including while on SNAP) and will 

work after leaving SNAP even in the absence of the time limit. The claim also ignores research showing that time limits generally fail to encourage employment. 

And, the NPRM does not account for the particular challenges facing this population—barriers and challenges to employment that differ from those faced by the 

general public and justify the current approach to providing waivers and individual 

exemptions to unemployed childless adults. Because the agency did not provide any 

evidence that would demonstrate the time limit is likely to increase employment, 

earnings, or self-sufficiency, the agency’s claim that the time limit should be applied 

to more individuals in order to increase labor force attachment is without merit. We 

offer findings from numerous studies to illustrate our points. We strongly recommend that the Department review and reflect on each of these studies before 

moving forward with a final rule. 

A. Individuals Subject to the Time Limit Already Have Significant Work Effort, 

Raising Doubt as to Whether the Rate Can Be Increased by Withholding Food 

The NPRM repeatedly claims that a primary goal of the proposed changes is to 

subject more individuals to the time limit. Terminating food assistance to more people (some 755,000 more, by the agency’s own estimates), the NPRM argues, will increase work effort, job placement, and earnings among those subject to the rule. But 

it fails to include any information about the employment of individuals subject, or 

potentially subject, to the time limit either while on SNAP or before or after participation in the program. The absence of any information is striking because research 

shows that many low-income adults without children who receive SNAP in any 

given month work while on SNAP or soon after, regardless of the existence of the 

time limit. Other factors, such as personal circumstances and local economic conditions, play important roles in an individual’s employment, but are not taken into 

account by FNS in this proposed change. 

In this section, we review the research that describes both the significant work 

effort of childless adults without disabilities, as well as the unique challenges they 

face in the labor market. Because workers turn to SNAP during periods of unemployment, employment rates among childless adults while receiving SNAP might be 

expected to be relatively low. Still, in a typical month, almost 1⁄3 and perhaps as 

many as 1⁄2 of all SNAP households with childless adults work. USDA’s administrative data show that 31 percent of all SNAP households with non-disabled childless 

244 

247Food and Nutrition Service, Characteristics of Supplemental Nutrition Assistance Program 

Households: Fiscal Year 2017, Tables A.14 and A.16. 248 Center on Budget and Policy Priorities, ‘‘Unemployed adults without children who need 

help buying food only get SNAP for three months,’’ https://www.cbpp.org/unemployed-adultswithout-children-who-need-help-buying-food-only-get-snap-for-three-months. 249See Food and Nutrition Service, Characteristics of Supplemental Nutrition Assistance Program Households: Fiscal Year 2014, Table A.16. 250 Center on Budget and Policy Priorities, ‘‘Unemployed adults without children who need 

help buying food only get SNAP for three months,’’ https://www.cbpp.org/unemployed-adultswithout-children-who-need-help-buying-food-only-get-snap-for-three-months. 251See Stephen Bell and Jerome Gallagher, ‘‘Prime-Age Adults without Children or Disabilities: The ‘Least Deserving of the Poor’—or Are They? Assessing the New Federalism Policy,’’ 

Urban Institute, February 2001, https://www.urban.org/sites/default/files/publication/61286/ 

310269-Prime-Age-Adults-without-Children-or-Disabilities.PDF. 

adults worked in a typical month of 2017.247 USDA’s administrative data may underestimate earnings because some work may not be required to be reported for 

SNAP, either because it is irregular or not expected to continue or because, under 

SNAP’s ‘‘simplified reporting’’ rules, changes in circumstances need only be reported 

at 6 month intervals unless they raise household income above 130 percent of the 

poverty level. Work that households aren’t required to report for SNAP purposes 

may be captured by the other data but not the SNAP data. 

In fact, data from other sources suggest the work rate could be closer to 50 percent. Tabulations generated by CBPP from the Census Bureau’s 2008 Panel of the 

Survey of Income and Program Participation (SIPP) show employment rates for 

SNAP households with non-disabled childless adults close to 50 percent in a typical 

month between 2011 and 2013.248

The 2017 data from USDA does not identify whether a childless adult is subject 

to the time limit or not (because he or she is exempt or living in a waived area). 

But work rates among this population have been consistent, even as the percentage 

of the country covered by waivers has varied widely. Comparing 2017 data (when 

37 percent of the population lived in a waived area) to 2014 data (when 75 percent 

of the population did) shows very similar levels of employment. In 2014, when the 

national unemployment rate was over six percent, 35 states had statewide waivers 

and nine had areas waived. That year, 27 percent of all SNAP households with nondisabled adults and no children worked in a typical month.249 That is close to the 

31 percent of non-disabled adults without children who were working in 2017, when 

far more of the country had the time limit in place. This suggests factors other than 

waivers or the time limit itself play a more important role in the ability of adults 

without children to find work. 

Even more important, childless adults have high work rates prior to and after a 

spell on SNAP, but the NPRM fails to account for how subjecting more individuals 

to the time limit would impact this. About 72 percent of SNAP households with a 

childless, working-age adult worked in the year before or after receiving SNAP.250

And many of those not working while receiving SNAP were actively looking for 

work. USDA’s administrative data suggest that, in a typical month in 2017, close 

to 1⁄2 (46 percent) of all childless adults on SNAP who were not working were looking for work (and of those who reported not participating in the labor force, many 

likely had health conditions or other barriers to employment that prohibited labor 

force participation). Although this statistic should be viewed with caution as the 

data may not be sufficiently reliable to draw firm conclusions, it’s noteworthy that 

Urban Institute researchers, using National Survey of American Families data, 

found that 3⁄4 of all low-income, able-bodied adults without dependents (not just 

those on SNAP) worked in 1997 and 86 percent were in the labor force (that is, either working or actively looking for work).251

Given the consistent evidence of work among individuals likely to be subject to 

the time limit regardless of waiver status or general unemployment rates, the claim 

that the time limit itself leads to increased employment is not supported. Instead, 

it suggests that the rule’s sole purpose is to take away food assistance from struggling unemployed or underemployed workers. 

Further undermining the assertion that the time limit is necessary to increase 

work effort among SNAP participants, most childless adults on SNAP who work 

have substantial work. Among SNAP households that worked in a typical month 

while receiving SNAP or worked at some point during the following year, nearly 1⁄2

(49 percent) worked full time (at least 35 hours a week) for 6 months or more of 

the following year. Twelve percent worked at least 20 hours per week for 6 or more 

months. Another 24 percent worked full time in at least 1 month over that period. 

245 

252Steven Carlson, et al., ‘‘Who Are the Low Income Childless Adults Facing the Loss of SNAP 

in 2016?’’ Center on Budget and Policy Priorities, February 8, 2016, p. 9, https://www.cbpp.org/ 

sites/default/files/atoms/files/2-8-16fa.pdf. An updated analysis that looked at all SNAP 

households with an adult without disabilities (with and without children), found similar rates 

of full- and part-time work among the broader group that the earlier analysis found. See Brynne 

Keith-Jennings and Raheem Chaudhry, ‘‘Most Working-Age SNAP Participants Work, But Often 

in Unstable Jobs,’’ March 15, 2018, https://www.cbpp.org/research/food-assistance/most-working-age-snap-participants-work-but-often-in-unstable-jobs. 253 ‘‘Food Stamp Employment and Training Program,’’ United States General Accounting Office (GAO–3–388), March 2003, p. 17, http://www.gao.gov/assets/240/237571.pdf. 254See ‘‘A Comprehensive Assessment of Able-Bodied Adults Without Dependents and Their 

Participation in the Work Experience Program in Franklin County, Ohio,’’ Ohio Association of 

Foodbanks, 2014, http://admin.ohiofoodbanks.org/uploads/news/WEP-2013-2014-report.pdf. 255Stephen Bell and Jerome Gallagher, ‘‘Prime-Age Adults without Children or Disabilities: 

The ‘Least Deserving of the Poor’—or Are They? Assessing the New Federalism Policy,’’ Urban 

Institute, February 2001, https://www.urban.org/sites/default/files/publication/61286/ 

310269-Prime-Age-Adults-without-Children-or-Disabilities.PDF. 

Only about 15 percent worked 20 or more hours per week for less than 6 months 

or worked fewer hours than that.252

Nonetheless, childless adults participating in SNAP are generally low-income, 

low-skill workers with limited job prospects. More than 80 percent have no more 

than a high school education or GED. They are more likely than other SNAP participants to lack basic job skills like reading, writing, and basic mathematics.253 A 

work experience program in Ohio designed to help individuals subject to the time 

limit find work or qualifying work activities found signs of functional illiteracy even 

among those with a high school degree.254 As a result, wages of childless workingage adults on SNAP are quite low: one study found that 90 percent of those aged 

25–49 earned less than twice the minimum wage, compared to 47 percent of all 

workers aged 25–49.255

USDA did not provide any information or analysis in the NPRM that suggested 

it had reviewed this evidence. Nor did it offer any research to the contrary—and 

we believe no such research exists. That leaves us to wonder whether the Department was aware that the work rates for individuals subject to the time limit appear 

to be similar whether or not they live in a waived area. 

B. The NPRM Fails to Account for the Distinct Characteristics of Unemployment 

Childless Adults on SNAP 

Because the group of individuals subject to the rule are, when compared to the 

general public, poorer, less educated, and more likely to have medical conditions or 

other factors affecting their ability to find employment, states have long found the 

3 month time limit in statute harsh and unfair. To mitigate the harm caused by 

taking food assistance away from this group, states have routinely relied on the option to request a waiver based on demonstrating a lack of sufficient jobs for the individuals affected by the time limit. 

The NPRM seeks to restrict this state option in order to end food assistance for 

unemployed adults without children in the hope that this will result in increased 

employment among this group. The NPRM offers no information about the individuals affected by the rule—whether they have the skills, training, and support to find 

and keep employment, and whether they disproportionately face barriers to work 

like undiagnosed health conditions, a lack of transportation, or a criminal history. 

The NPRM neglects to address research findings from multiple sources, including 

USDA itself, showing that this population does face a different labor market environment than the general public. We are surprised that USDA did not draw upon 

this wide body of research and urge the agency to review the studies we cite—all 

of which are included in the appendix. 

We review the research to show that the job prospects for these individuals are 

not accurately captured by the general unemployment rate. Even when unemployment is low due to a strong economy, adult SNAP participants without children face 

a very different labor market than higher-income adults. This population is also 

under-served by other support programs, often lacks stable housing, and struggles 

to be hired into stable jobs. States wisely use the flexibility provided by law to assess the availability of jobs for this population and request waivers when there are 

insufficient jobs. 

Childless adults on SNAP are extremely poor. Like many others, childless adults 

often turn to SNAP for assistance when they are no longer able to make ends meet, 

especially if their jobs are lost, hours are cut, or wages hover at the Federal minimum. While participating in SNAP, their income averages 33 percent of the poverty 

line, the equivalent of about $4,000 per year for a single person in 2019. Average 

246 

256 CBPP analysis of FY 2017 USDA SNAP Household Characteristics data adjusted to FY 

2019 dollars. 257Kathryn J. Edin and H. Luke Shaefer, $2.00 a Day: Living on Almost Nothing in America, 

2015, Houghton Mifflin Harcourt. We especially highlight descriptions of the struggles of finding 

and keeping work (pp. 42–47 and 112–114), the challenges facing people of color in the job market (pp.52–56), and barriers to employment like transportation (pp. 51–52, 138–139). 258 Chuck Marr, et al., ‘‘Lone Group Taxed Into Poverty Should Receive a Larger EITC,’’ Center on Budget and Policy Priorities, April 19, 2016, https://www.cbpp.org/research/federal-tax/ 

childless-adults-are-lone-group-taxed-into-poverty. 259See ‘‘Comprehensive Report on Able-Bodied Adults Without Dependents, Franklin County 

Ohio Work Experience Program,’’ Ohio Association of Foodbanks, 2015, http:// 

admin.ohiofoodbanks.org/uploads/news/ABAWD_Report_2014-2015-v3.pdf. The Ohio Association of Foodbanks gathered the information for the report as a result of a partnership with the 

county SNAP agency to help place individuals identified as subject to the time limit in qualifying work activities after screening them. 

incomes are even lower—just 18 percent of poverty—for those not working 20 or 

more hours a week, who are most likely to be cut off due to the 3 month limit.256

The struggles of poor adults are vividly portrayed in $2.00 a Day: Living on Almost Nothing in America, which draws detailed portraits of households with little 

access to substantial employment and public benefits.257 The descriptions illustrate 

the complexities of poverty—the psychological and emotional costs, the uncertainty 

and lack of options available, and the work effort of those in poverty. We strongly 

urge the Department to familiarize itself with the real lived experiences of those 

portrayed in the book. 

Unemployed childless adults have few resources other than SNAP to rely on while 

looking for work. In general, adults without children are not eligible for most government assistance. In the past, state General Assistance programs have provided 

small monthly cash allotments to singe adults to meet basic shelter and other needs, 

but these programs have weakened considerably. Few childless adults qualify for 

unemployment insurance, and childless adults are ineligible for Medicaid in states 

that haven’t adopted the Affordable Care Act’s Medicaid expansion. In addition, 

childless workers are the only demographic group that the Federal tax system taxes 

into, or deeper into, poverty, in part because they are eligible only for a tiny Earned 

Income Tax Credit (EITC). Federal income and payroll taxes pushed about 7.5 million childless workers into or deeper into poverty in 2015.258 Given how little Federal support is available to the group subject to the time limit, it is surprising that 

USDA believes the group is able to survive while avoiding work. Their SNAP benefits are minimal to meet basic food needs, let alone housing, health, and other basic 

expenses. 

Many childless adults have disabilities that make working difficult or impossible 

but don’t meet the severe disability standard for receiving Supplemental Security 

Income (SSI) or Social Security Disability Insurance (SSDI). If not identified as having a physical or mental condition that prevents them from working 20 or more 

hours per week, they would be subject to the time limit, yet unable to realistically 

find work in many cases. 

There’s more evidence that people subject to the time limit face multiple challenges to independence and self-sufficiency, including homelessness, physical and 

mental health limitations, language barriers, unstable employment histories, and 

criminal records. A detailed study of individuals identified by the local SNAP agency 

as ABAWDs subject to the time limit who were referred to a work experience program in Franklin County (Columbus), Ohio found that: 259

• Many have extremely unstable living situations, evidenced by residence in 

short-term shelters or with friends and family and limited telephone service. 

• One-third have a mental or physical limitation, including depression, post-traumatic stress disorders, mental or learning disabilities, or physical injuries. Some 

of these disabilities, though not severe enough to qualify for Federal disability 

benefits, may still limit a person’s ability to work more than 20 hours a week. 

• Nearly 1⁄4 are non-custodial parents, and 13 percent are caregivers for a parent, 

relative, or friend. 

• More than 40 percent lack access to reliable private or public transportation; 

60 percent lack a valid driver’s license. 

• Fifteen percent need supportive services like language interpretation or help 

with transportation to obtain employment. 

• Nearly 1⁄4 have been dismissed from a job in the past and others have gaps in 

their employment records—both of which can deter potential employers. More 

than 1⁄3 have felony convictions, making it hard to find jobs and pass background checks. 

247 

260Michael Stavrianos and Lucia Nixon, The Effect of Welfare Reform on Able-Bodied Food 

Stamp Recipients, Mathematica Policy Research, Inc., July 1998, pp. 56–57. 261Michael Stavrianos and Lucia Nixon, The Effect of Welfare Reform on Able-Bodied Food 

Stamp Recipients, Mathematica Policy Research, Inc., July 1998, p. 56–57. 262See Exhibit ES–1, page ES–4, Philip Richardson, et al., Food Stamp Leavers Research 

Study—Study of ABAWDs Leaving the Food Stamp Program in South Carolina, https:// 

naldc.nal.usda.gov/download/45220/PDF. 

These individuals face daunting challenges in finding employment even when general unemployment rates are low. The Ohio study illustrates why Congress gave 

states the option to waive the time limit in areas where there are insufficient jobs 

for those subject to the rule. Without providing any evidence to the contrary, the 

NPRM proposes to limit the ways in which a state can demonstrate a lack of sufficient jobs for the individuals subject to the time limit. It does this by eliminating 

Labor Surplus Areas, low and declining employment-to-population ratios, seasonal 

unemployment and requiring recent unemployment rates to be at least seven percent. But the Department fails to explain how it determined that the proposed new 

standards relate to employment opportunities for those subject to the rule, particularly given the characteristics outlined in the list above. 

One reason states were given flexibility to define the areas which could be waived 

due to a lack of sufficient jobs for the individuals subject to the rule is that even 

in the late 1990s, a growing body of research showed that the labor market situation for low-skilled workers had grown worse over time, and that low-skill workers 

faced limited employment options. As summarized by a report commissioned by 

USDA in 1998, ‘‘a relatively large body of research indicates that the labor market 

situation of the low-skilled has become considerably worse in recent decades and 

that their current employment prospects are limited. This suggests that even if 

ABAWDs are willing to work, they may be unable to do so because there are not 

enough jobs for low-skilled workers.’’ 260 The report, which reviewed studies on the 

employment prospects of low-income adults fitting the ‘‘ABAWD’’ description (but 

not necessarily participating in SNAP), also found that: 

• Job prospects for ABAWDs do not look promising, due to changes in the U.S. 

economy that have resulted in the decline of industries and skill types in which 

ABAWDs are concentrated. 

• Many ABAWDs face a spatial mismatch between their residence and the location of low-skill jobs, as well as a skills mismatch, especially for urban residents. 

• The job prospects of ABAWDs depend significantly on local economic conditions, 

tied not to county-level unemployment but to the location of employers needing 

low-skill workers and the quality and availability of local institutions supporting workforce development.261

The Department’s commissioned reports as well as other research paint a clear 

picture of individuals in this targeted group who have common characteristics that 

distinguish the group from other unemployed adults. These characteristics—including high poverty rates, health issues, and few supports—make finding and keeping 

employment a unique challenge. The Department simply asserts that the time limit 

will increase employment for this population but does not acknowledge its own research showing that this is not the case. While all aspects of the rule strike us as 

arbitrary, this disconnect between the agency’s basic knowledge of the affected population and the assertions about how the proposed policy would increase employment 

is particularly surprising. This is one of numerous reasons why the proposed rule 

should be withdrawn. 

C. Reports Commissioned by USDA Show Subjecting More Individuals to the Time 

Limit Will Not Increase Their Likelihood of Gaining Employment 

In order to understand the impact of the time limit on individuals’ well-being, 

USDA, along with the U.S. Department of Health and Human Services, funded 

studies in four states: Arizona, Illinois, Iowa, and South Carolina. While the studies 

varied in scope and focus and were not able to identify individuals who left SNAP 

because of the time limit, they do reveal the policy’s limited impact on employment 

outcomes, coupled with low earnings and increased hardship. 

A 2001 study of individuals leaving SNAP in Illinois showed that far more families than ABAWDs left SNAP due to increased earnings, even though the time limit 

was in effect. The study found that the percentage of ABAWDs who left SNAP and 

remained off the program and employed did not vary between counties that had 

waivers and counties that did not.262

248 

263See Exhibit IV–I, Philip Richardson, et al., Food Stamp Leavers Research Study—Study of 

ABAWDs Leaving the Food Stamp Program in South Carolina Final Report, page IV–2, https:// 

naldc.nal.usda.gov/download/45220/PDF. 264See Exhibit 2–6, Covered Employment, in Gregory Mills and Robert Kornfeld, Study of Arizona Adults Leaving the Food Stamp Program, Final Report, Dec. 2000, page 36, https:// 

naldc.nal.usda.gov/download/45673/PDF. 265Gregory Mills and Robert Kornfeld, Study of Arizona Adults Leaving the Food Stamp Program, Final Report, Dec. 2000, page 51, https://naldc.nal.usda.gov/download/45673/PDF. Individuals with a medically certified physical or mental condition that prevents them from working are exempt from the 3 month time limit, but states have struggled with correctly identifying 

these individuals. The study did not look at whether some of the ABAWDs who left SNAP 

should have been exempt from the time limit. 266 Elizabeth Dagata, ‘‘Assessing the Self-Sufficiency of Food Stamp Leavers,’’ Economic Research Service, USDA, September 2002, https://www.ers.usda.gov/publications/pub-details/ 

?pubid=46645. 267 Elizabeth Dagata, ‘‘Assessing the Self-Sufficiency of Food Stamp Leavers,’’ Economic Research Service, USDA, September 2002, https://www.ers.usda.gov/publications/pub-details/ 

?pubid=46645. 268 Anu Rangarajan and Philip M. Gleason, Food Stamp Leavers in Illinois: How Are They 

Doing Two Years Later?, Mathematica Policy Research, Inc., January 2001, p. 21, https:// 

www.mathematica-mpr.com/our-publications-and-findings/publications/food-stamp-leavers-inillinois-how-are-they-doing-two-years-later. 269 NPRM, p. 990. 

The study looked at those who left SNAP in areas where the time limit was in 

effect and areas where it was not (due to a waiver). It found that in the sample 

who left SNAP in 1998–1999, a majority of individuals (53 percent) were off SNAP 

in 2001 and not working or back on SNAP. Of those that were working after leaving 

SNAP, the study did not attempt to identify the role of the time limit in employment gains. In fact, the study shows that employment rates among ABAWDs leaving SNAP were highest in areas exempt from the time limit due to high unemployment rates—higher than the employment rates in areas using the individual exemptions and areas in which the time limit was in effect.263 This shows that factors 

other than the time limit have more impact on employment outcomes for ABAWDs. 

FNS fails to address this in the NPRM. Here we again recommend that FNS review 

and consider this research. 

The Arizona study commissioned by USDA to understand the outcomes of people 

leaving SNAP showed that ABAWDs had worse outcomes on a number of employment-based metrics. They were less likely to have achieved self-sufficiency, less likely to have improved their employment situation, and more likely to be at risk of 

hardship or deprivation. The study grouped SNAP participants in Arizona in 1997 

into three categories: ABAWDs, non-ABAWD individuals on TANF, and nonABAWD, non-TANF adults. Upon leaving SNAP, employment rates for each subgroup were over 50 percent, but by one year later, ABAWDs who had been cut off 

SNAP had experienced the greatest drop in employment.264 This suggests that: (1) 

the 3 month time limit may not be an important factor in causing employment, 

since SNAP participants not subject to the time limit had similar levels of employment as those subject to the time limit when leaving SNAP; and (2) ABAWDs struggle to maintain employment. The report identifies several reasons why the ABAWD 

group might see a sharp decline in employment. In a survey of ABAWDs who were 

no longer on SNAP and not working, more than 60 percent reported being ill or having health problems or a disability—circumstances not identified by the SNAP agency as qualifying an individual to an exemption.265

Across all four studies, many who lost SNAP benefits were employed but had low 

earnings. Between 41 and 76 percent of the former recipients in the four states were 

working after leaving SNAP, but earnings were low and many remained in poverty.266 Most of those who were not working in Arizona and Illinois were in poor 

health or caring for a family member in poor health. Given the complexity of 

SNAP’s rules governing work effort, disability, and time limits, some may not have 

realized that they may again qualify for SNAP and failed to reapply for benefits.267

While the studies of individuals leaving SNAP looked at all types of individuals, 

the studies yielded important results for ABAWDs that are relevant to this proposed 

rule but do not appear in the Department’s rationale for the NPRM. For example, 

in Illinois in 1997, the single largest category of individuals losing benefits was 

ABAWDs. The impact varied widely among groups. For example, 2⁄3 of the ABAWDs 

leaving the program were African American, well above the percentage of all leavers 

(which was 50 percent).268 As discussed more fully in Chapter 12, the NPRM acknowledges the proposed rule would have a disparate impact by noting the ‘‘potential for disparately impacting certain protected groups due to factors affecting rates 

of employment of members of these groups.’’ 269 But the Food and Nutrition Act 

249 

270 Elizabeth M. Dagata, ‘‘Assessing the Self-Sufficiency of Food Stamp Leavers,’’ Economic 

Research Service, USDA, September 2002, https://ageconsearch.umn.edu/record/262256/files/ 

31106_fanrr26-8_002.pdf. This is a summary of in-depth studies in Arizona, Illinois, Iowa, and 

South Carolina. 271Gregory Mills and Robert Kornfeld, Study of Arizona Adults Leaving the Food Stamp Program, Final Report, Dec. 2000, page 85, https://naldc.nal.usda.gov/download/45673/PDF. 272Gregory Mills and Robert Kornfeld, Study of Arizona Adults Leaving the Food Stamp Program, Final Report, Dec. 2000, page 94, https://naldc.nal.usda.gov/download/45673/PDF. 

makes clear that the regulations implementing Title VI and other civil rights statutes are fully applicable to SNAP. These regulations prohibit actions in Federal programs that have disparate impacts on members of protected groups as well as intentional discriminatory acts. Therefore, the proposed rule’s disparate impact on these 

individuals, as demonstrated by the research and acknowledged in the NPRM itself, 

is inconsistent with the Act. Given the requirement under 7 U.S.C. § 2020(c)(2)(D) 

that the Department ensure the protections of Title VI of the Civil Rights Act of 

1964 apply to all SNAP households, we are stunned that the Department did not 

review its own research results that clearly suggest that the proposed policy would 

have widely disparate impacts on African Americans. 

D. The Loss of SNAP Due to the Time Limit Fails to Raise Income and Increases 

Hardship 

Childless adults who lose SNAP benefits struggle without food assistance benefits. 

As noted, USDA’s most comprehensive assessment of former SNAP recipients in 

four states in the early 2000s suggests that their life circumstances are quite difficult.270 A significant minority don’t find work, and among those who are employed 

after leaving SNAP, earnings are low. Most remain poor. Many struggle to acquire 

enough food to meet their needs, lack health insurance, experience housing problems, and/or have trouble paying their bills. (These studies include people who leave 

SNAP because of the 3 month time limit or for other reasons, for example, because 

they found a job or mistakenly believed they were no longer eligible.) 

Despite relatively high levels of work effort, between 1⁄3 and roughly 2⁄3 of SNAP 

leavers in the four states had household incomes below the poverty line—well above 

the overall poverty rate of 13 percent. Many of these households experienced severe 

poverty after leaving SNAP: about 40 percent of the leavers in two states were 

below half of the poverty line. 

Many struggled to acquire adequate food. Between 17 and 34 percent of the SNAP 

leavers in the four states reported very low food security (meaning they had to skip 

or reduce the size of their meals or otherwise disrupt their eating patterns at times 

during the year because they couldn’t afford enough food), compared with three percent of all households without children. 

USDA’s study of adults in Arizona leaving SNAP found that the incidence of moderate or severe hunger was greatest among the ABAWD subgroup, at 34 percent, 

compared to 23 percent for the TANF subgroup and 18 percent for the non-TANF 

subgroup.271 By comparison, 3.5 percent of all Arizona households were classified 

as facing moderate or severe hunger. The Arizona study concludes by pointing out 

that individuals who might appear to be self-sufficient or better off after leaving 

SNAP, because they receive fewer public benefits and report less private support, 

might still be facing significant hardship: 

The high rate of food insecurity with hunger found among ABAWD exiters— 

34 percent—is noteworthy. This incidence is more than twice the 1999 national 

rate of 14 percent estimated by USDA for households at or below 50 percent 

of the poverty level, even though most ABAWDs have incomes above the poverty level. The ABAWD finding highlights the importance of considering (in this 

and other exit studies) whether exiters who appear self-sufficient, in terms of 

their reduced reliance on public and private support, are able to avoid hardship 

and deprivation.272

This cautionary note is not found in the NPRM. The agency simply asserts that 

it believes expanding the number of individuals subject to the time limit will improve their self-sufficiency, without acknowledging what the agency-funded research 

revealed—that the outcome for ABAWDs leaving because of the time limit may be 

increased hunger and hardship. 

The studies also showed that many lacked health insurance, had housing problems, or had trouble paying their utility bills. About 30 to 40 percent of the SNAP 

leavers in the four states faced housing issues, including falling behind on rent, 

moving in with relatives, or becoming homeless. Between 20 and 65 percent reported problems paying for utilities. Just over 1⁄2 of the SNAP leavers in two of the 

250 

273 Elizabeth M. Dagata, ‘‘Assessing the Self-Sufficiency of Food Stamp Leavers,’’ Economic 

Research Service, USDA, September 2002, https://www.ers.usda.gov/publications/pub-details/ 

?pubid=46645. This is a summary of in-depth studies in Arizona, Illinois, Iowa, and South Carolina. 274LaDonna Pavetti, Michelle K. Derr, and Heather Hesketh, ‘‘Review of Sanction Policies and 

Research Studies,’’ Mathematica Policy Research (March 2003). 275 Richard C. Fording, Joe Soss, and Sanford F. Schram, ‘‘Devolution, Discretion, and the Effect of Local Political Values on TANF Sanctioning,’’ Social Service Review (June 2007), pp. 285– 

316. 

states were uninsured.273 These are all characteristics, as we illustrate elsewhere 

in the comments, associated with much higher rates of unemployment. We continue 

to be baffled about how or whether USDA factored its own research into the NPRM. 

It would appear that the Department ignored its own studies. 

E. Evidence From Other Benefit Programs Shows That Time Limits Do Not Increase 

Employment and Have a Disproportionate Impact on Certain Populations 

The stated rationale for proposing a change to the long-standing waiver process 

is to expose more individuals to the time limit, in the belief that this will result 

in increased labor market attachment. The NPRM provides no evidence to support 

this assertion. But, research on the Temporary Assistance for Needy Families 

(TANF) program, which imposes both work requirements and a time limit for benefits, undermines the claim that work requirements and time-limited benefits increase employment. 

A review of the many studies on families whose TANF monthly direct financial 

support was reduced or taken away due to work requirements shows that these policies harm individuals and families, most of whom face significant obstacles to employment, while producing few lasting gains in employment. While the studies described in this section are about families with children—often single-mother-headed 

households—the findings are relevant because they review the circumstances of very 

poor households, similar in important respects to households on SNAP. In addition, 

many ABAWDs are parents of non-minor children or have children not in the SNAP 

household. TANF and SNAP households live in similar circumstances and face similar challenges finding employment, so the outcomes from one group can inform the 

likely outcomes for the other. 

A time limit ignores the fact that public assistance recipients often vary in their 

needs and circumstances; many often live with one or multiple significant barriers 

to employment. Those barriers range from low cognitive functioning, to mental and 

physical health problems, to criminal justice issues, to low measures of human capital. These barriers make it hard to find or keep a job or fulfill other work requirements. Extensive research on the effect of time limits in TANF, which provides modest cash assistance and requires a portion of the caseload to engage in work activities, shows that the time limit did not notably increase employment, but it did result in increased hardship. We strongly recommend that USDA read these studies 

and consider the findings when developing final regulations. We are confident the 

results demonstrate the problems with the proposed policy. 

F. Most Low-Income People Sanctioned From Public Assistance Due to Work Requirements Face Barriers Finding Employment 

Studies show that many parents who lose TANF benefits due to work requirements have significant employment barriers. Those losing benefits are more likely 

than other TANF parents to have physical, mental health, or substance use issues; 

to be fleeing domestic violence; to have low levels of education and limited work experience; or to face significant logistical challenges, such as lack of access to or 

funds to pay for child care and transportation.274 Below are summaries of several 

TANF studies finding that many adults losing assistance due to sanctions face significant employment barriers: 

• A 2007 study of regional variation of full-family sanctioning practices in Florida’s TANF cash assistance program gives evidence that sanctions are significantly related to various barriers to employment. TANF parents with lower income and lower levels of education were more likely to be sanctioned than those 

with higher income and education levels. For example, recipients with a high 

school degree were more likely to be sanctioned than those with more education—however, sanctions were the most common among those with less than 

a high school degree. Community traits can matter too: families were more likely to be sanctioned in counties with higher poverty rates than other counties, 

after controlling for other characteristics.275

251 

276 Chi-Fang Wu, et al., ‘‘How Do Welfare Sanctions Work?,’’ Social Work Research (March 

2006), pp. 33–50. 277 Andrew J. Cherlin, et al., ‘‘Operating within the Rules: Welfare Recipients’ Experience with 

Sanctions and Case Closings,’’ Social Service Review (September 2002), pp. 387–662. 278 Ariel Kalil, Kristin S. Seefeldt, and Hui-chen Wang, ‘‘Sanctions and Material Hardship 

under TANF,’’ Social Service Review (December 2002), pp. 642–662. 279 Ariel Kalil, Kristin S. Seefeldt, and Hui-chen Wang, ‘‘Sanctions and Material Hardship 

under TANF,’’ Social Service Review (December 2002), pp. 642–662. 280 Yeheskel Hasenfeld, Toorjo Ghose, and Kandyce Larson, ‘‘The Logic of Sanctioning Welfare 

Recipients: An Empirical Assessment,’’ Social Science Review (June 2004), Vol. 78, No. 2, pp. 

304–319, http://repository.upenn.edu/spp_papers/88/. 281LaDonna Pavetti, et al., ‘‘The Use of TANF Work-Oriented Sanctions in Illinois, New Jersey, and South Carolina,’’ Mathematica Policy Research (April 2004). 

• A 2006 study of women in Wisconsin receiving TANF found that the state was 

more likely to sanction mothers with lower levels of education. Specifically, 

mothers with at least a high school diploma or equivalent were less likely to 

be sanctioned than mothers with less than a high school diploma, and those 

with education beyond high school were even less likely to be sanctioned, even 

when controlling for how long each individual received TANF grants. The study 

also concluded that those ‘‘who may be least able to succeed in the labor market 

are most likely to be sanctioned.’’ Specifically, the authors examined sanction 

activity against the mothers’ employment status in the 2 years preceding entry 

to the TANF program. The authors’ estimates show a monotonic trend with the 

number of quarters of work: those with no work in the past 2 years were most 

likely to be sanctioned, those with 1–4 quarters of employment were less likely 

to be sanctioned, those with 5–7 quarters of employment were even less likely 

to be sanctioned, and mothers who had been employed for all eight quarters 

were the least likely to be sanctioned.276

• A 2002 comparison of sanctioned and non-sanctioned TANF recipients in Boston, Chicago, and San Antonio found sanctioned recipients were less likely than 

other TANF recipients to have a high school degree or its equivalent, a working 

telephone at home, or a car. They were more likely to report being in fair or 

poor health, have a substance use issue, or have a partner who interfered with 

their employment, training, or schooling. They also had less work experience, 

lived in neighborhoods with undesirable qualities (such as abandoned houses, 

assaults and muggings, gangs, and open drug dealing), and reported living in 

housing of poor quality.277

• A study of women in Michigan receiving TANF shows that those with educational barriers to employment were more likely to be sanctioned than those 

without such barriers. Women with less than a high school education were 2.06 

times more likely to be sanctioned than women with higher levels of formal education.278

• The same study of women in Michigan receiving TANF shows those with transportation-related barriers to employment were more likely to be sanctioned than 

those without such barriers. Specifically, recipients who lacked either a car or 

a driver’s license were disproportionately sanctioned relative to recipients without these transportation barriers. In addition, those with trauma-related barriers to employment were more likely to be sanctioned than those without such 

barriers. Specifically, women who reported experiencing severe domestic violence (being hit, kicked, shoved, etc.) within the past year were disproportionately sanctioned relative to recipients who did not report experiences of that 

type.279

• A California study of a random sample of [CalWORKs] (TANF) recipients in 

four counties (two large urban counties and two large semi-rural counties) found 

that recipients without a car were roughly 1.5 times more likely to incur sanctions than recipients who owned a car. Recipients who were sanctioned were 

less likely to own a car (39 percent of respondents) in comparison to non-sanctioned recipients (52 percent of respondents).280

• In Illinois, parents who had ever been sanctioned were significantly less likely 

than those never sanctioned to have a high school diploma or its equivalent and 

more likely to have limited recent work experience. They also were significantly 

more likely to be dealing with a physical or mental health issue, to have been 

arrested multiple times, and to have experienced a child care issue. In South 

Carolina, parents ever sanctioned were significantly more likely to have a physical health problem, show signs of a learning disability, and have a family member or friend with a health care issue or special need. 281

252 

282Kyoung Hag Lee, ‘‘Effect on Lifetime Limits and Differences between TANF Leavers Who 

Had Reached Their Lifetime Limits and Those Who Had Exited Voluntarily,’’ Poverty & Public 

Policy (2010), pp. 1–22. 283Dean Herd, Ernie Lightman, and Andrew Mitchell, ‘‘Welfare Time Limits: Symbolism and 

Practice’’, U-Toronto: Social Assistance in the New Economy (SANE) Project (2008), pp. 1–26. 284LaDonna Pavetti and Jacqueline Kauff, ‘‘When Five Years Is Not Enough: Identifying and 

Addressing the needs of Families Nearing the TANF Time Limit in Ramsey County, Minnesota,’’ 

Mathematica Policy Research (March 2006), pp. 1–24, https://www.mathematica-mpr.com/ourpublications-and-findings/publications/when-five-years-is-not-enough-identifying-and-addressing-the-needs-of-families-nearing-the-tanf-time-limit-in-ramsey-county-minnesota. 285Dana DeMaster, ‘‘At the Limit: December 2006 Minnesota Family Investment Program 

(MFIP) Cases that Reached the 60 Month Time Limit,’’ Minnesota Department of Human Services (January 2008), pp. 1–18, https://edocs.dhs.state.mn.us/lfserver/Legacy/DHS-5092B-ENG. 286 Christina McHugh and J. Taylor Danielson, ‘‘TANF Time Limit Analysis Comparing Cases 

Closed Due to Time Limits with Other Case Closures,’’ Washington State Department of Social 

and Health Services (February 2019). 287 Robert Jay Dilger, et al., ‘‘WV WORKS 2003: Perspectives of Former Recipients Who Have 

Exhausted Their 60 Months of Program Eligibility,’’ West Virginia University Interdisciplinary 

Task Force on Welfare Reform (Summer 2004), pp. 1–24. 

• A study of 656 TANF leavers from the 1999 and 2002 data of the National Survey of America’s Family (NSAF) found that TANF leavers who reached their 

lifetime limits had a higher chance of having problems with employment due 

to work barriers or vulnerable characteristics such as old age, physical or mental health problems. They experienced greater hardship because they had less 

income and less EITC receipt, most had experienced a cutoff of SNAP, and 

fewer received child care assistance. The author concluded that time limits can 

lead low-income families to endure greater economic hardships.282

• A study that examined time limits on the receipt of welfare in both the United 

States and British Columbia, Canada found that time limits are an ineffective 

policy tool as they increase barriers to employment and result in recipients 

needing more support and access to specific programs. Recipients who exhausted their benefits struggled financially and had a difficult time finding a 

job. While some recipients had several barriers to work, others who had fewer 

barriers were still unable to find a job. Low cognitive functioning, limited education, and physical and mental health problems were some of the barriers that 

recipients faced.283

• A 2006 study of Minnesota’s TANF program explored in detail the circumstances of those at or near 60 months, the Federal time limit. It found 

about 16 percent of cases had a case head with an IQ of less than 80, about 

20 percent were caring for ill or incapacitated family members, and about 21 

percent were ill or incapacitated themselves for 30 days or more. Long-term 

TANF recipients also had mental illness (which is often untreated or inadequately treated), were developmentally disabled or learning disabled, were 

leaving domestic violence situations, or were otherwise ‘‘unemployable.’’ Some 

recipients suffered from chronic and debilitating health problems because they 

had worked physically demanding jobs.284

• Another report on Minnesota’s TANF program shows the percent of persons 

with a severe mental health diagnosis at 60 months, the Federal time limit, to 

be about 52 percent and those with a chemical dependency diagnosis to be 27 

percent. Among American Indian recipients, about 60 percent of those near the 

time limit had a mental health diagnosis and/or a chemical dependency diagnosis.285

• A more recent Washington State study compared families who left TANF due 

to time limits and those who left for other reasons. The state found that timelimited families were more likely to be unstably housed in the year prior to losing assistance. They were also more likely to have chronic health issues and 

visit the emergency room. And, they were more likely to have a range of behavioral health needs, from mental health issues to substance abuse disorders.286

• In a survey of 276 West Virginia TANF recipients cut off due to time limits, 

respondents identified several barriers to employment. Most of the respondents 

were unemployed after leaving TANF. More than 1⁄2 (56.2 percent) of respondents were not working because of a physical or mental illness or disability problem; more than 1⁄3 (37.1 percent) had no transportation; 1⁄3 (32.6 percent) did 

not have the right education; and a little less than 1⁄3 (29.8 percent) simply 

could not find a job. Most of these respondents had multiple barriers to employment.287

253 

288 Rebecca A. London and Jane G. Mauldon, ‘‘Time Running Out: A Portrait of California 

Families Reaching the CalWORKs 60-Month Time Limit in 2004,’’ Welfare Policy Research 

Project (November 2006), pp. 1–6. http://escholarship.ucop.edu/uc/item/37g3510z. 289LaDonna Pavetti, Michelle K. Derr, and Heather Hesketh, ‘‘Review of Sanction Policies and 

Research Studies,’’ Mathematica Policy Research (March 2003). 290 Anita M. Larson, Shweta Singh, and Crystal Lewis, ‘‘Sanctions and Education Outcomes 

for Children in TANF Families,’’ Child & Youth Services (September 2011), pp. 180–199. 291 Richard C. Fording, Joe Soss, and Sanford F. Schram, ‘‘Devolution, Discretion, and the Effect of Local Political Values on TANF Sanctioning,’’ Social Service Review (June 2007), pp. 285– 

316. 292 Chi-Fang Wu, et al., ‘‘How Do Welfare Sanctions Work?,’’ Social Work Research (March 

2006), pp. 33–50. 293 Ariel Kalil, Kristin S. Seefeldt, and Hui-chen Wang, ‘‘Sanctions and Material Hardship 

under TANF,’’ Social Service Review (December 2002), pp. 642–662. 

• A California study of the cases that reach the time limit found families often 

struggle with one major barrier to work and often multiple barriers. One-third 

of respondents cited major health issues as a big barrier to work. A smaller 

share said they were caring for a family member with a major health issue. 

More than 1⁄5 of respondents said they suffered from depression or anxiety or 

had experienced at least one stressful event in the past year. About 11 percent 

experienced a domestic violence situation. More than 1⁄2 of all respondents noted 

having at least one barrier and 28 percent cited having two or more barriers. 

Forty-three percent said they had trouble paying rent; 54 percent said they had 

trouble paying utility bills; 39 percent reported having trouble paying for food; 

and 40 percent noted they had to use a food bank.288

G. Imposing Time Limits and Sanctions for Failure to Meet Work Requirements Has 

a Disparate Impact on Communities of Color 

States’ application of work requirements in the TANF cash assistance program 

has exacerbated racial inequities, research shows. On the whole, research on TANF 

suggests that policies to take away SNAP from individuals who are not working or 

participating in work activities for a specific number of hours each month will hurt, 

not help, the individuals most in need of assistance. Nearly every study comparing 

the race and ethnicity of sanctioned and non-sanctioned TANF recipients finds that 

African Americans are significantly more likely to be sanctioned than their white 

counterparts.289 For example: 

• A 2011 study of Minnesota TANF recipients found that the state sanctioned a 

disproportionate number of American Indian or Alaskan Native recipients and 

sanctioned them more often than other racial groups during a 24 month observation period. While American Indian or Alaskan Natives only comprised 

around 10.9 percent of the families receiving TANF in Minnesota, they made 

up 12.2 percent of all families that the state sanctioned. Further, the average 

number of sanctions was 3.54 for American Indian and Alaskan Native families, 

while it was only 3.18 for White, non-Hispanic families.290

• A 2007 study of Florida’s TANF program showed black families were more likely to be sanctioned than White families after several months of continuous 

TANF receipt. Specifically, the study estimated that among families who received TANF benefits for at least 9 months continuously, black families were 

22 to 35 percent more likely to be sanctioned than White families.291

• A 2006 study of women in Wisconsin receiving TANF found that black women 

were more likely to be sanctioned than their white counterparts. This result 

was statistically significant under both a simple analysis and an analysis that 

took into account the duration of each individual’s receipt of TANF grants.292

• A 2002 study of women receiving TANF in Michigan found that black women 

were disproportionately sanctioned compared to white women. The authors 

found similar results under two different specifications. One analysis, looking 

at mean differences, found that black women made up a disproportionate number of the total number of women that the state sanctioned. The other model, 

a multivariate logistic regression, provided similar evidence: African American 

women were 1.73 times more likely to be sanctioned than White women.293

• A 2011 study of TANF recipients in Maryland found evidence that African 

Americans were more likely to lose benefits due to sanctions compared to other 

recipients. The study found that African Americans were disproportionately repVerDate Aug 31 2005 11:16 Jun 14, 2019 Jkt 041481 PO 00000 Frm 00259 Fmt 6621 Sfmt 6621 P:\DOCS\116-02\36188.TXT BRIAN
254 

294Sarah Williamson, ‘‘Full-Family Sanctions & Economic Recession,’’ University of Maryland 

Family Research and Training Group (January 2011). https://familywelfare.umaryland.edu/ 

reports1/sanctionsbrief.pdf. 295LaDonna Pavetti, et al., ‘‘The Use of TANF Work-Oriented Sanctions in Illinois, New Jersey, and South Carolina,’’ Mathematica Policy Research (April 2004). 296Wisconsin Department of Workforce Development, ‘‘Wisconsin Works (W–2) Sanctions 

Study,’’ (December 2004). 297Dana DeMaster, ‘‘At the Limit: December 2006 Minnesota Family Investment Program 

(MFIP) Cases that Reached the 60 Month Time Limit,’’ Minnesota Department of Human Services (January 2008), pp. 1–18, https://edocs.dhs.state.mn.us/lfserver/Legacy/DHS-5092B-ENG. 298Pamela Ovwigho, Kathryn Patterson, and Catherine E. Born, ‘‘The TANF Time Limit: Barriers & Outcomes among Families Reaching the Limit,’’ Family Welfare Research and Training 

Group (November 2007), pp. 1–34, https://familywelfare.umaryland.edu/reports1/ 

tl_barriers.pdf. 299 Anne Gordon, et al., ‘‘Experiences of Virginia Time Limit Families After Case Closure: An 

Interim Report,’’ Mathematica (2002), pp. 1–177, https://www.mathematica-mpr.com/-/media/ 

publications/pdfs/expvafinal.pdf. 300 Christina McHugh and J. Taylor Danielson, ‘‘TANF Time Limit Analysis Comparing Cases 

Closed Due to Time Limits with Other Case Closures,’’ Washington State Department of Social 

and Health Services (February 2019). 301Kristin S. Seefeldt and Sean M. Orzol, ‘‘Watching the Clock Tick: Factors Associated with 

TANF Accumulation,’’ National Poverty Center Working Paper Series (May 2005), http:// 

www.npc.umich.edu/publications/workingpaper04/paper9/04-09.pdf. 

resented among families that had been sanctioned as a result of work requirements relative to respondents of other races.294

• A New Jersey study found that among TANF recipients entering the program 

between July 2000 and June 2001, 36 percent of African American recipients 

had their TANF grants reduced and 16 percent had their grant eliminated due 

to a work-related sanction; the comparable figures for white recipients were 27 

percent and ten percent, respectively.295

Data from the Wisconsin Department of Workforce Development shows a consistent pattern of racial and ethnic discrepancies in TANF sanctions. Statewide, 42 

percent of African American participants and 45 percent of Hispanic participants 

were sanctioned, compared to just 24 percent of white participants.296 Researchers 

in several states have looked at the demographics of the share of their caseload approaching or at the time limit. In a number of examples, including a national survey, families and recipients of color—and particularly black recipients—are more 

likely to lose benefits due to the time limit. This evidence suggests that expanding 

time limits in other programs will disproportionally affect black recipients. Other research cited below highlight the unique challenges African Americans face in the 

labor market. Loss of assistance, paired with the difficulty of securing or maintaining a job, could make the hardship experienced by this group even worse. 

• The Minnesota TANF agency found that black women, including African Americans, Somali immigrants, and other African immigrants, made up about 1⁄2 of 

the adult recipients who reached 60 months, the Federal time limit. African 

Americans in particular were the most likely to reach the Federal time limit.297

• A study in Maryland found most of the caseload consisted of black women and 

they were the most likely of any racial group to reach the time limit.298

• In Virginia, black families were more likely to reach the limit than white families.299

• In Washington State, families cut off by the time limit tended to be black or 

American Indian.300

• Using the Women’s Employment Study for one Michigan urban county, researchers analyzed factors associated with increased time on TANF. They found 

that black women were far more likely to have accumulated more months, and 

thus be closer to the time limit, than white women.301

SNAP participants of color also face discrimination when looking for work. Investigations in job discrimination uncovered strong employer preferences for white candidates over candidates of color. One study found that re ́sume ́s with white-sounding 

names are more likely to get call-backs than re ́sume ́s with equal qualifications but 

with black-sounding names. Other research shows that generally, those with a 

criminal record are less likely to get call-backs or requests for interviews from employers. Furthermore, black applicants without criminal records are less likely to receive favorable treatment than white applicants without criminal records, but white 

255 

302Devah Pager, ‘‘The Mark of a Criminal Record,’’ American Journal of Sociology (2003), pp. 

937–975. 303 Bong Joo Lee, Kristen S. Slack, and Dan A. Lewis, ‘‘Are Welfare Sanctions Working as Intended? Welfare Receipt, Work Activity, and Material Hardship among TANF-Recipient Families,’’ Social Service Review (September 2004), pp. 370–403. 304 Bong Joo Lee, Kristen S. Slack, and Dan A. Lewis, ‘‘Are Welfare Sanctions Working as Intended? Welfare Receipt, Work Activity, and Material Hardship among TANF-Recipient Families,’’ Social Service Review (September 2004), pp. 370–403. 305 Ariel Kalil, Kristin S. Seefeldt, and Hui-chen Wang, ‘‘Sanctions and Material Hardship 

under TANF,’’ Social Service Review (December 2002), pp. 642–662. 306 Ariel Kalil, Kristin S. Seefeldt, and Hui-chen Wang, ‘‘Sanctions and Material Hardship 

under TANF,’’ Social Service Review (December 2002), pp. 642–662. 307 Ariel Kalil, Kristin S. Seefeldt, and Hui-chen Wang, ‘‘Sanctions and Material Hardship 

under TANF,’’ Social Service Review (December 2002), pp. 642–662. 

applicants with a criminal record are more likely to receive favorable treatment 

than black applicants with no criminal history.302

H. Households That Lose TANF Benefits Because of Sanctions or Time Limits Experience Higher Levels of Material Hardship and Increased Hardship 

People with incomes low enough to qualify for SNAP also often have few or no 

assets to lean on in difficult times and a limited amount of cash to meet basic needs 

like rent and utilities, clothes, personal care items, and gas or bus fare, among other 

things. SNAP helps meet food costs, but when that assistance is taken away, individuals struggle to make ends meet and some are unable to avoid a downward spiral. Studies examining sanctioned TANF families show that many people experience 

increased hardships after facing a sanction: a 2004 longitudinal study of TANF recipients in Illinois found that sanctioned families who faced grant reductions had 

higher levels of food hardship after being sanctioned than those who did not have 

their grants reduced by sanctions. Researchers defined food hardship as sometimes 

or often not having enough to eat. Recipients who had sanctions in the period January 1999 to March 2001 reported between February 2002 and September 2002 a 

higher incidence of food hardship and perceived overall hardship than other TANF 

recipients who did not experience grant reductions resulting from sanctions during 

the period. A multivariate analysis conducted with the same data indicated respondents who had their grants reduced due to sanctions were over three times more likely to report food hardship in the final period of the study (after the sanction) compared to those who were never sanctioned during the study, after controlling for demographic and other factors.303

A 2004 longitudinal study of TANF recipients in Illinois found those who had 

their grants reduced due to sanctions reported higher levels of perceived overall 

hardship. Perceived overall hardship was determined by the extent to which respondents agreed with statements like, ‘‘I worry about having enough money in the 

future.’’ Respondents who saw grant reductions as a result of sanctions between 

January 1999 and March 2001 showed more perceived overall hardship following 

the sanctions (between February and September 2002) than those who were never 

sanctioned during the former, 51 month period.304

A 2002 study of women in Michigan receiving TANF suggests those who were 

sanctioned were more likely to experience hardship and have to prioritize hardshipmediating activities than those who were not sanctioned. Specifically, 21 percent of 

sanctioned families (compared to nine percent of non-sanctioned families) reported 

having their gas or electricity turned off in the previous year because they could not 

afford to make their utility payments.305 Researchers found that 34 percent of sanctioned families (compared to 14 percent of non-sanctioned families) had resorted to 

hardship-mitigating activities such as pawning, stealing food, searching in trash 

cans, or begging.306

The 2002 study of Michigan TANF households suggests women who were sanctioned are more likely to expect future hardship—such as inadequate housing, food, 

or medical care in the next 2 months—than those who were not sanctioned. Women 

who were sanctioned were 2.41 times more likely to expect future hardship compared to women who were not sanctioned, the researchers found.307

There is evidence from a study of people who frequented a food pantry in upstate 

New York that people who lost TANF benefits due to sanctions were more likely 

to experience hardship than others. Specifically, it was more common for people who 

had been sanctioned—relative to those who had not been sanctioned—to report having more difficulty in the past 6 months paying for food, rent, adult health care, 

and other bills. Similarly, the number of sanctioned respondents who indicated they 

had moved within the past 6 months due to inability to pay rent was disproportionately high relative to the responses from those who were not sanctioned. Access to 

256 

308 Jean Oggins and Amy Fleming, ‘‘Welfare Reform Sanctions and Financial Strain in a FoodPantry Sample,’’ The Journal of Sociology & Social Welfare (June 2001), pp. 101–123, https:// 

scholarworks.wmich.edu/cgi/viewcontent.cgi?article=2725&context=jssw. 309 Nancy E. Reichman, et al., ‘‘TANF Sanctioning and Hardship,’’ Social Service Review (June 

2005) Vol. 79 No. 2, pp. 215–236. 310Melissa Ford Shah, et al., ‘‘Predicting Homelessness among Low-Income Parents on 

TANF,’’ Washington State Department of Social & Health Services (August 2015). 311Melissa Ford Shah, et al., ‘‘Predicting Homelessness among Low-Income Parents on 

TANF,’’ Washington State Department of Social & Health Services (August 2015). 312 Robert Jay Dilger, et al., ‘‘WV WORKS 2003: Perspectives of Former Recipients Who Have 

Exhausted Their 60 Months of Program Eligibility,’’ West Virginia University Interdisciplinary 

Task Force on Welfare Reform (Summer 2004), pp. 1–24. 313Sandra Butler, ‘‘TANF Time Limits and Maine Families: Consequences of Withdrawing the 

Safety Net,’’ Maine Equal Justice Partners (April 2013), pp. 1–16, http://www.mejp.org/sites/ 

default/files/TANF-Study-SButler-Feb2013.pdf. 

a telephone told a similar story of increased hardship, with a disproportionate number of sanctioned people lacking access to a phone, relative to those who were not 

sanctioned.308

A study using data from the Fragile Families and Child Wellbeing survey, which 

surveys mothers from 20 cities in 15 states, evaluated the level of hardship among 

those who had been sanctioned in the prior 12 months and non-sanctioned mothers 

who received TANF. Researchers found that those who had been sanctioned in the 

prior 12 months were 85 percent more likely to report any material hardship compared to non-sanctioned mothers receiving TANF (42 percent of those sanctioned reported one or more material hardships, compared to 27 percent of those not sanctioned). Researchers found that those sanctioned were 63 percent more likely than 

non-sanctioned mothers to report maternal or child hunger and 76 percent more 

likely to report having their utilities shut off in the 12 months prior to the interview. The study also found that sanctioned mothers were 79 percent more likely to 

report being unable to receive medical care, for either themselves or a child, due 

to cost. The study controlled for sociodemographic factors known to be associated 

with being sanctioned and controlled for hardship levels mothers faced prior to 

being sanctioned.309

A Washington State study using predictive modeling to identify the factors 

likeliest to cause a new spell of homelessness for TANF parents found that sanctioned recipients were about 20 percent more likely than non-sanctioned parents to 

begin a new spell of homelessness in the next month.310

Underlying the NPRM’s proposal to restrict waivers is the claim that subjecting 

more individuals to the 3 month time limit will increase employment. But research 

on public benefit programs that have time limits demonstrates that arbitrary time 

limits do not lead to self-sufficiency. Instead, some research finds families cut off 

TANF because of time limits have significant barriers to employment and experience hardship. Without cash, the challenge for parents to support their children becomes even harder and a downward spiral emerges. Finding employment becomes 

even harder when parents need to scramble to make ends meet. The studies below 

offer examples of time-limited families unable to maintain stable housing and/or pay 

their bills and, in some instances, afford enough food. 

• A Washington State study comparing families who left TANF due to time limits 

and those who left for other reasons found that time-limited families were more 

likely to be unstably housed 1 month after losing assistance.311

• According to a survey of 276 former West Virginia TANF recipients cut off because of time limits, 59 percent reported that they were either worse off or 

much worse off financially since leaving WV WORKS; 65 percent did not have 

enough money to pay the electric, gas, or water bill; and 51 percent did not have 

enough money to pay for heat. These percentages were much lower when the 

recipients were on WV WORKS. After losing assistance because of the time 

limit, 61 percent of respondents reported that the amount of stress in their lives 

was either worse or much worse since being removed from WV WORKS. They 

were also more pessimistic about their own personal and financial futures. 

These financial burdens stem from their very low level of employment: only 26.9 

percent of recipients were employed and more than 1⁄2 of the employed were 

working part-time.312

• A survey of dozens of Maine TANF recipients cut off by the time limit found 

that families experienced increased reliance on food banks, inability to pay utilities and other bills, and overcrowded housing conditions or reliance on homeless 

shelters.313

257 

314 Bong Joo Lee, Kristen S. Slack, and Dan A. Lewis, ‘‘Are Welfare Sanctions Working as Intended? Welfare Receipt, Work Activity, and Material Hardship among TANF-Recipient Families,’’ Social Service Review (September 2004), pp. 370–403. 315 Bong Joo Lee, Kristen S. Slack, and Dan A. Lewis, ‘‘Are Welfare Sanctions Working as Intended? Welfare Receipt, Work Activity, and Material Hardship among TANF-Recipient Families,’’ Social Service Review (September 2004), pp. 370–403. 316Sarah Williamson, ‘‘Full-Family Sanctions & Economic Recession,’’ University of Maryland 

Family Research and Training Group (January 2011), https://familywelfare.umaryland.edu/ 

reports1/sanctionsbrief.pdf. 

I. Work Requirements in TANF Do Not Work 

The rationale for reducing or eliminating benefits for not meeting a work requirement is that this will compel unemployed adults to find work. Evidence suggests 

that work requirements (along with other policy changes that accompanied TANF’s 

implementation) contributed to a modest increase in employment during the late 

1990s, but that work often was not steady, a pattern reflected in recent studies as 

well. 

Research on adults who lost TANF due to sanctions for failure to meet a work 

requirement found that these individuals have trouble finding employment after 

their exit. The personal, family, or community barriers that kept them from finding 

a job while on TANF also prevent these parents from finding work after TANF. 

Findings from TANF suggest that even if the NPRM intends to impose work requirements only on ‘‘work able’’ individuals, substantial numbers of SNAP recipients 

who face personal or family challenges would likely fall through the cracks and have 

their benefits reduced or taken away. Evidence from studies that show that employment rates tend to be lower for these populations include the following: 

• A 2004 longitudinal study of TANF recipients in Illinois found that those respondents who were sanctioned during the study period were more likely to be 

unemployed after the study period than those who were not sanctioned and had, 

on average, significantly lower levels of earnings post-sanction than those who 

were not sanctioned. More specifically, respondents who received sanctions that 

reduced cash grants between January 1999 and March 2001 were 44 percent 

less likely to be engaged in formal work during the period April 2001 through 

September 2001 than the respondents who did not receive sanctions during the 

preceding period, even after controlling for previous work experience and other 

characteristics associated with employment. And, TANF families receiving sanctions that were carried out through grant reductions between January 1999 and 

March 2001 had lower average earnings during the next 6 months than those 

respondents who were not sanctioned.314

The study also helps explain why those sanctioned had worse outcomes and 

were less likely to be working. Working-age adults who have their grants reduced due to sanctions had higher barriers to employment than those who were 

not sanctioned. The group had higher levels of engagement in job training and 

other work activities and had a higher incidence of participation in informal 

work such as babysitting and odd jobs in the final period of the study than 

those with no grant reductions due to sanctions. This indicates the lower levels 

of formal employment among sanctioned respondents is not easily attributed to 

an unwillingness to work, since this population engages more heavily than 

those who did not experience grant reductions from sanctions in job training 

and informal work. A stronger explanation is that those who are sanctioned 

have more significant barriers to formal employment than those who are not.315

• A 2011 study of Maryland TANF recipients who were sanctioned found that 

these recipients had consistently lower post-exit employment rates relative to 

those who left TANF for reasons other than work sanctions, throughout the 9 

year post-exit period that the study covered. Similarly, the average earnings for 

the group that left due to work sanctions was lower than the average earnings 

of those who left for other reasons.316

• A 2018 study of state-collected data on the employment of Kansas parents leaving TANF cash assistance due to work-related sanctions and time limits between October 2011 and March 2015 indicates that a lower share of these parents worked in the year after their exit compared to families exiting TANF for 

other reasons. They also found it more difficult to find steady work compared 

to the other families exiting the program. In the average quarter of the year 

after exiting, only 49 percent and 47 percent of the sanctioned and time-limited 

families, respectively, were working, compared to 72 percent of families exiting 

due to the income limit and 53 percent for all other reasons. Moreover, only 

about a quarter of the sanctioned and time-limited families worked between 

258 

317Tazra Mitchell, LaDonna Pavetti, and Yixuan Huang, ‘‘Life After TANF in Kansas: For 

Most, Unsteady Work and Earnings Below Half the Poverty Line,’’ Center on Budget and Policy 

Priorities (February 2018), https://www.cbpp.org/research/family-income-support/life-aftertanf-in-kansas-for-most-unsteady-work-and-earnings-below. 318 Jean Oggins and Amy Fleming, ‘‘Welfare Reform Sanctions and Financial Strain in a FoodPantry Sample,’’ The Journal of Sociology & Social Welfare (June 2001), pp. 101–123, https:// 

scholarworks.wmich.edu/cgi/viewcontent.cgi?article=2725&context=jssw. 319Daniel Chandler, et al., ‘‘Mental Health, Employment, and Welfare Tenure,’’ Journal of 

Community Psychology (September 2005), pp. 578–609. 320 Yeheskel Hasenfeld, Toorjo Ghose, and Kandyce Larson, ‘‘The Logic of Sanctioning Welfare 

Recipients: An Empirical Assessment,’’ Social Science Review (June 2004), Vol. 78, No. 2, pp. 

304–319, http://repository.upenn.edu/spp_papers/88/. 321Karen L. Westra and John Routley, ‘‘Arizona Cash Assistance Exit Study,’’ Arizona Department of Economic Security Office of Evaluation (January 2000). 322 Catherine Born, Pamela Caudill, and Melinda Cordero, ‘‘Life After Welfare: A Look at 

Sanctioned Families,’’ University of Maryland School or Social Work (November 1999). 

seven and nine quarters in the year before and after their exit, compared to 1⁄3

of families overall.317

• A 2001 study of people who frequented a food pantry in upstate New York 

found that employment rates were lower for people who had lost TANF benefits 

due to sanctions. Among those surveyed in 1997, 13 percent of those sanctioned 

reported having had wage earnings in the previous 6 months, while 22 percent 

of unsanctioned respondents reported earnings over the same period. Moreover, 

because of the effects of sanctions, sanctioned respondents were far more likely 

to report being disconnected both from work and from TANF benefits. A full 

quarter of the sanctioned sample in 1997 reported no work and no TANF benefits, compared with three percent reporting the same in the unsanctioned sample.318

• A 3 year study of TANF recipients in two California counties provides evidence 

that employment rates are lower for those with significant barriers to employment. The study excluded individuals who received disability benefits and focused on mental health issues such as major depression, generalized anxiety 

disorder, panic attacks, social phobia, or posttraumatic stress disorder. Those 

who reported functional impairment over the previous month were far more 

likely not to have worked over the previous year. In the first follow-up year, 

54.2 percent of functionally impaired respondents had worked in the previous 

year, compared to 75.2 percent of those without such difficulties. In the second 

follow-up year, 58.5 percent of those with functional impairments worked in the 

previous year, compared to 79.2 percent of those without such difficulties. The 

researchers found a statistically significant association between having a mental health issue and having no earned income over the previous year. The most 

reasonable interpretation of this result is not that the respondents who were 

not working had some other source of support, but that they were unable to secure work due to their significant barrier to employment.319

• A California study of CALWORKS recipients found that recipients who had 

been sanctioned were much less likely to report obtaining full-time employment 

over 3 years (38 percent of respondents) compared to non-sanctioned clients (60 

percent of respondents). Researchers measured employment history by asking 

respondents about previous full- or part-time employment, and whether they 

were without work throughout the 3 years prior to the survey.320

• Studies consistently find lower employment rates among TANF leavers whose 

cases were closed due to a work-oriented sanction than among families that left 

TANF for other reasons. For example, in Arizona, 40 percent of sanctioned leavers were working in the first quarter after exit, compared to 55 percent of nonsanctioned leavers.321

• In Maryland, 6 months after exit, 38 percent of sanctioned leavers were employed, compared to 58 percent of non-sanctioned leavers.322

• A study of TANF recipients nationwide using the Census Bureau’s Survey of 

Income and Program Participation indicates those who are disconnected from 

both work and cash assistance are more likely to have a significant barrier to 

employment than those who either work or receive cash assistance. Those who 

had both no household earned income or any cash assistance during the survey 

month were about twice as likely to report having a physical or mental health 

condition that limits one’s ability to work compared to those who either worked 

or received cash assistance. Results were consistent across geographic regions. 

In southern states, 15.8 percent of disconnected respondents reported a physical 

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323 Andrea Hetling, ‘‘The Importance of Region and State Welfare Rules for Disconnected Single Mothers,’’ University of Kentucky Center for Poverty Research Discussion Paper Series (September 2011). 324 Christina McHugh and J. Taylor Danielson, ‘‘TANF Time Limit Analysis Comparing Cases 

Closed Due to Time Limits with Other Case Closures,’’ Washington State Department of Social 

and Health Services (February 2019). 325 Andrea Hetling, Kathryn Patterson, and Catherine Born, ‘‘The TANF Time Limit: Comparing Long-Term and Other Welfare Leavers,’’ Family Welfare Research and Training Group 

(February 2006) pp. 1–19, https://familywelfare.umaryland.edu/reports1/timelimitleavers.pdf. 326 Valerie Head, Catherine Born, and Pamela Ovwigho, ‘‘Criminal History as an Employment 

Barrier for TANF Recipients,’’ Family Welfare Research Training Group (March 2009), pp. 1– 

39. https://pdfs.semanticscholar.org/2c12/a0663bd8249586c000a82122cc2e6c796e23.pdf?_ga= 

2.3188080.1987654092.1552314136-1225174621.1551994502. 327Seth L. Welles, Falguni Patel, and Mariana Chilton, ‘‘Does Employment-Related Resilience 

Affect the Relationship between Childhood Adversity, Community Violence, and Depression?’’ 

Journal of Urban Health (2017), Vol. 94, pg. 233–243, https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5391326/. 

nected respondents had such a condition; in non-southern states, 24.3 percent 

of disconnected respondents had a work-limiting condition, while among nondisconnected respondents, 10.4 percent reported having such a condition. It 

should be noted that these respondents with physical and mental health conditions were not receiving support from SSI; SSI recipients (and those who reported school as their major activity) were excluded from the sample.323

Most TANF Recipients Who Lose Benefits Due to Time Limits Do Not Find Steady 

Employment 

Cutting off families because they have reached some arbitrary time limit ignores 

whether they can actually support themselves or if the job market is welcoming to 

them. Several studies have found that parents cut off of TANF due to the time limits have trouble finding employment. The health, familial, and behavioral circumstances that kept them from finding a job while on TANF also prevent these 

parents from finding work after TANF. Black families are not only the most likely 

to be cut off by time limits, but also very likely to be discriminated against in the 

job market, the evidence shows. In some instances, parents who can find work may 

be working inconsistently and thus still fall short of a stable income. 

• In Washington State, time-limited parents were less likely to be employed in 

the year before leaving TANF.324

• Researchers from the University of Maryland’s School of Social Work found that 

compared to other people leaving TANF, those leaving because they reached the 

time limit had less employment history while on TANF and worked fewer quarters in the year after leaving assistance.325

• Other researchers of Maryland’s TANF program found that recipients who reported having a criminal record were more likely to reach the time limit than 

those who did not report having a criminal background. While recipients with 

a criminal conviction are as likely to be employed as other recipients, their employment is more unstable. These women are often more likely to have other 

barriers as well, such as human capital deficits and situational barriers.326

• An analysis of the Building Wealth and Health Network pilot program found 

depression is often a barrier to employment among TANF recipients, and that 

adverse childhood experiences (ACEs) and exposure to community violence are 

often associated with depression. The study investigated how resilience affects 

the relationship between ACEs, community violence, and depression. TANF 

families have a high prevalence of health impediments and significant barriers 

to employment, such as domestic violence, food insecurity, utility shut offs, 

homelessness, child hospitalizations, and child developmental risks.327

Most TANF Recipients Who Lose Benefits Due to Sanctions Do Not Find Steady 

Employment 

The rationale for reducing or eliminating benefits for not meeting a work requirement is that this will compel parents to find work. Evidence suggests that work requirements (along with other policy changes that accompanied TANF’s implementation) contributed to a modest increase in employment during the late 1990s, but 

that work often was not steady[,] a pattern reflected in recent studies as well. 

Another consequence of work requirements in TANF raises concerns about the 

NPRM’s goal of subjecting more unemployed adults to SNAP’s time limit. As it has 

become harder for single mothers to get direct financial assistance when they cannot 

find work, the number with neither jobs nor TANF has grown substantially over 

time. In 1995, the number of families receiving cash assistance in an average month 

260 

328 In 2018, non-disabled adult beneficiaries ages 30 through 49 who do not have minor children in their homes were subject to the work requirement in Arkansas. The state has begun 

phasing in the requirement for beneficiaries 19 through 29 in 2019. 329 Jennifer Wagner, ‘‘Commentary: As Predicted, Eligible Arkansas Medicaid Beneficiaries 

Struggling to Meet Rigid Work Requirements,’’ Center on Budget and Policy Priorities, July 30, 

2018, https://www.cbpp.org/health/commentary-as-predicted-eligible-arkansas-medicaid-beneficiaries-struggling-to-meet-rigid. 330 Jennifer Wagner, ‘‘Medicaid Coverage Losses Mounting in Arkansas From Work Requirement,’’ Center on Budget and Policy Priorities, January 17, 2019, https://www.cbpp.org/blog/ 

medicaid-coverage-losses-mounting-in-arkansas-from-work-requirement. 331 Jennifer Wagner, ‘‘4,109 More Arkansans Lost Medicaid in October for not Meeting Rigid 

Work Requirement,’’ Center on Budget and Policy Priorities, October 16, 2018, https:// 

www.cbpp.org/blog/4109-more-arkansans-lost-medicaid-in-october-for-not-meeting-rigid-work-requirements. 332 Jennifer Wagner, ‘‘Fact Checking Arkansas Governor’s Claims About Jobs and Medicaid 

Waiver,’’ Center on Budget and Policy Priorities, January 28, 2019, https://www.cbpp.org/blog/ 

fact-checking-arkansas-governors-claims-about-jobs-and-medicaid-waiver. 333 Ibid. 334 Ibid. 

exceeded the number of jobless single mothers by about a million. By 2016, the 

number of families receiving cash assistance in an average month was roughly two 

million below the number of jobless single mothers. As a result, work requirements 

in TANF fueled an increase in deep poverty (measured as income at or below 1⁄2

of the poverty line). 

J. Evidence from Medicaid Work Requirements Shows Beneficiaries Lose Benefits 

But Don’t Gain Employment 

Additional evidence that taking benefits away from individuals who are unable to 

meet strict work requirements does not lead to increased work rates comes from the 

recent state waivers to apply such policies in Medicaid. In June 2018, Arkansas became the first state to condition receipt of Medicaid benefits on meeting a work requirement. Certain beneficiaries must participate in and report 80 hours of work or 

work-like activity each month.328 Those that fail to meet the requirement for 3 

months in a calendar year lose coverage.329

In 2018, over 18,000 Arkansas Medicaid beneficiaries—nearly 25 percent of the 

total population the state identified as potentially subject to the work requirement— 

lost coverage for failing to meet the requirement.330 This far exceeds the population 

that the state’s articulated policy intended to target with the requirement: beneficiaries who were able to work but were not working. Many individuals who qualified for an exemption for being unable to work or who were working are among 

those who lost coverage. Many beneficiaries were unaware of the requirement, did 

not understand what they had to do to meet the requirement, or were unable to 

navigate the reporting requirement.331

Moreover, there is no evidence that the work requirement has led to increased 

employment. Although the state has cited data from the New Hire Database as evidence that beneficiaries are starting new jobs, it has not provided any evidence that 

the work requirement caused these new hires; low-income workers frequently begin 

new jobs or change jobs. Further, the data source includes individuals who worked 

for only a few hours or 1 day, doesn’t show if the job is temporary (such as seasonal 

work around the holidays), and doesn’t indicate if the employee had been previously 

unemployed as opposed to just recently changed jobs.332

In fact, other evidence from state Medicaid administrative data indicates that at 

most a few hundred people may have found jobs due to the Federal waiver. Most 

Medicaid beneficiaries don’t face monthly reporting requirements, mainly because 

they’re already working or qualified for exemptions. Only the remaining group, 

which has to report hours of work each month, faces any new work incentive due 

to the new policy. And of that group, only a few hundred each month have met the 

requirement by reporting some work hours, the state reports. What’s more, many 

of them likely would have found jobs anyway.333

These data are consistent with focus group interviews showing that the work requirement isn’t changing Medicaid beneficiaries’ behavior. Beneficiaries already had 

enough reasons to work: they need to pay their bills. But they often struggle with 

unstable work hours, live in rural areas with few jobs, or face other barriers to employment—and the state hasn’t invested any new money in job training programs, 

services to address barriers, or supports like transportation to help beneficiaries 

connect to jobs.334

Meanwhile, the work requirement has even proved counterproductive for some. 

News reports describe working beneficiaries who struggled with the reporting requirement and lost Medicaid coverage. Consequently, some have gone without needVerDate Aug 31 2005 11:16 Jun 14, 2019 Jkt 041481 PO 00000 Frm 00266 Fmt 6621 Sfmt 6621 P:\DOCS\116-02\36188.TXT BRIAN
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335 Ibid. 336 Cindy Mann and April Grady, ‘‘Potential Enrollment Impacts of Michigan’s Medicaid Work 

Requirement,’’ Manatt Health, February 6, 2019, https://www.manatt.com/Manatt/media/ 

Media/Images/White%20Papers/Manatt_MI-Work-Req-Estimates_20190206-Final.pdf. 337Phil Galewitz, ‘‘Judge Blocks Kentucky Medicaid Work Requirement,’’ Kaiser Health News, 

June 29, 2018, https://khn.org/news/judge-blocks-kentucky-medicaid-work-requirement/. 338Steward v. Azar amicus brief, January 24, 2019, https://www.psychiatry.org/ 

File%20Library/Psychiatrists/Directories/Library-and-Archive/amicus-briefs/amicus-2019- 

Stewart-v-Azar-DC-No18-152.pdf. 339 NPRM, p. 992. 340 7 CFR § 273.24(f). 341Section 4015 of House-passed H.R. 2, https://www.congress.gov/115/bills/hr2/BILLS115hr2eh.pdf. 342Section 4005 of H.R. 2 as enacted, https://www.congress.gov/115/bills/hr2/BILLS115hr2enr.pdf. 

ed medication, worsening their health and in some cases costing them their jobs. 

Moreover, any small increase in employment must be viewed in light of the 18,000 

beneficiaries who lost coverage.335

Numerous other states are in the process of implementing Medicaid work requirements, and estimates show similar coverage losses are likely. For example, the 

waiver in Michigan may lead up to 27 percent of the state’s Medicaid expansion population to lose coverage the first year.336 Kentucky’s own projections say its work 

requirement, which has been challenged in court, would cause 95,000 enrollees to 

lose coverage in 5 years.337 A group of health care providers and advocates filed an 

amicus brief in the Kentucky litigation pointing out that its work requirement will 

worsen health and won’t promote work.338

The experience thus far with Medicaid work requirements demonstrates that such 

policies take coverage away from large portions of beneficiaries, including those who 

are working or qualify for an exemption but cannot navigate the red tape of the requirement. At the same time, they fail to lead to increased work activity or employment. 

Chapter 7: Proposed Rule’s Requirement That State Waiver Requests Have 

the Governor’s ‘‘Endorsement’’ Violates Congressional Intent 

The proposed rule would require that state requests to waive the time limit in 

areas with insufficient jobs ‘‘be endorsed by the State’s Governor’’ 339 (emphasis 

added). This change is in direct violation of Congressional intent, as clearly expressed less than 2 months before publication of the proposed rule. If FNS proceeds 

to publish a final rule it must reject this change and conform to the intent of Congress. 

Current regulations regarding state requests to waive the 3 month time limit say 

simply that such requests are made to FNS ‘‘on the request of the state agency.’’ 340

The presumption is that state agencies will be acting under the direction of their 

political leadership, including the Governor. CBPP has worked with states on their 

waiver requests for more than 20 years. We cannot remember ever working with 

a state agency that knowingly sought a waiver against the wishes of the Governor. 

It is true, however, that Governors are not typically aware of every detailed policy 

option and choice that their cabinet Secretaries adopt for SNAP. Similarly, Governors do not typically sign waivers, review nutrition education plans, or even personally review large scale procurements. Governors serve as chief executives rather 

than detailed policy implementers. 

The House-passed 2018 Farm Bill sought to require the ‘‘approval of the chief executive officer of the state’’ 341 for waiver requests (emphasis added). The final conference agreement on the 2018 Farm Bill rejected the House approach, and instead 

requires ‘‘the support of the chief executive officer of the state’’342 (emphasis added). 

The 2018 Farm Bill, The Agriculture Improvement Act of 2018, passed the Congress 

in mid-December and was signed by the President on December 20, 2018. 

The conferees in the conference report that accompanied the bill were very clear 

about their intent in making this change: 

The Managers intend to maintain the practice that bestows authority on the 

state agency responsible for administering SNAP to determine when and how 

waiver requests for ABAWDs are submitted. In response to concerns that have 

been raised by some Members that state agencies have not fully communicated 

to the chief executive their intent to request a waiver under section 6(o), the 

Managers have included a provision to encourage communication between the 

state agency and the chief executive officer of the state. The Managers agree 

that state agencies should have the support of these officials in their application 

for waiver, ensuring maximum state coordination. It is not the Managers’ intent 

262 

343 Conference Report to accompany H.R. 2, pp. 616–617, https://www.congress.gov/115/crpt/ 

hrpt1072/CRPT-115hrpt1072.pdf. 344 NPRM, p. 983. 345See, for example, p. 987 of the NPRM: ‘‘The proposed rule would end the unlimited carryover and accumulation of ABAWD percentage exemptions, previously referred to as 15 percent 

exemptions before the enactment of the Agriculture Improvement Act of 2018. Upon enactment, 

Section 6(o)(6) of the Act provides that each state agency be allotted exemptions equal to an 

estimated 12 percent of ‘‘covered individuals . . .’’ 346 66 Fed. Reg., No. 11, 4438 (January 17, 2001). 

that USDA undertake any new rulemaking in order to facilitate support for requests from state agencies, nor should the language result in any additional paperwork or administrative steps under the waiver process.343 (Emphasis added.) 

Thus, the conferees were clear that they did not intend for FNS to engage in new 

rule-making based on the change and did not want to introduce any new ‘‘paperwork or administrative steps.’’ State Administrators are left on their own to ensure 

that they have the support of their Governor. The change in statute simply clarifies 

this practice for those who were unduly concerned that state agencies were acting 

against the wishes of the Governor. 

By requiring the ‘‘endorsement’’ of the state’s governor in the proposed rule, FNS 

ignored this expressed intent of Congress and went too far. The only explanation 

FNS gives in the NPRM is a short sentence in the preamble: 

The Department proposes clarifying that any state agency’s waiver request 

must have the Governor’s endorsement to ensure that such a critical request 

is supported at the highest levels of state government.344

The Merriam Webster’s Collegiate Dictionary definition of ‘‘endorsement’’ suggests 

that the term implies a signature, which would necessarily require additional paperwork. Such a step would directly contradict Congressional intent. From other aspects of the NPRM it is clear that FNS was aware of the passage of the 2018 Farm 

Bill.345 So the only reasonable conclusion is that FNS chose to ignore Congressional 

intent and intends to add paperwork burden and steps to the process. 

Chapter 8: Proposed Rule Would Make Implementing The Time Limit Harder by Removing Provisions That Give States Certainty Around Approval 

The proposed rule would eliminate the ability of states to implement a waiver at 

the time a request is submitted, requiring FNS approval prior to any waiver implementation. The proposed rule would also remove language that identifies waivers 

that meet certain standards as ‘‘readily approvable.’’ Currently, these two provisions 

give states certainty of approval that enables them to better plan for waiver implementation while waiting for approval. Given that FNS can substantially delay approval (and recently has done so), this proposal would put an undue burden on 

states preparing for the complex and error-prone process of implementing the time 

limit. FNS also failed to articulate a need for these changes, making it difficult for 

commenters to weigh in on any potential benefit. We therefore urge the Department 

to keep current regulations at 7 CFR § 273.24(f)(3) and 7 CFR § 273.24(f)(4), which 

establish the ‘‘readily approvable’’ standard and allow states to implement waivers 

upon submission of the waiver request in some instances. 

Current regulations have two provisions that give states more certainty in the 

waiver approval process. These provisions allow them time to prepare for implementation of the time limit while waiting for FNS approval. The first provision, at 7 

CFR § 273.24(f)(3), establishes that waivers that meet certain standards are ‘‘readily 

approvable.’’ A readily approvable waiver includes data from the Bureau of Labor 

Statistics showing a 12 month unemployment rate of ten percent, a 24 month unemployment rate 20 percent above the national average, or designation as a Labor Surplus Area (LSA) by the Department of Labor’s Employment and Training Agency. 

The final rule, published in 2001, stated that the Department decided to designate 

that it would approve those waivers ‘‘to facilitate the waiver process.’’ 346 The second 

provision, at 7 CFR § 273.24(f)(4), allows states to implement waivers based on having either a 12 month unemployment rate of ten percent or LSA designation for the 

current fiscal year upon waiver submission, rather than waiting for FNS approval. 

With those two provisions, states can plan on implementing the waiver submitted 

under the first provision while awaiting FNS approval, and can actually implement 

prior to approval if it is one of the waivers specified in 7 CFR § 273.24(f)(4). (FNS 

can contact the state to modify the waiver if needed.) 

263 

347 U.S. Department of Agriculture, Food and Nutrition Service, ‘‘Supplemental Nutrition Assistance Program—Expiration of Statewide ABAWD Time Limit Waivers,’’ March 4, 2015, 

https://fns-prod.azureedge.net/sites/default/files/snap/SNAP-Expiration-of-Statewide-ABAWDTime-Limit-Waivers.pdf. 348 U.S. Department of Agriculture, Food and Nutrition Service, ‘‘SNAP—Requirements for Informing Households of ABAWD Rules,’’ April 17, 2017, https://fns-prod.azureedge.net/sites/default/files/snap/Requirements_for_Informing_Households_of_ABAWD_Rules.pdf. 349 U.S. Department of Agriculture, Food and Nutrition Service, ‘‘SNAP—Best Practices and 

Resources for Informing Households of ABAWD Rules,’’ May 25, 2018, https://fnsprod.azureedge.net/sites/default/files/snap/BestPracticesforInformingABAWDS.pdf. 350 USDA Office of Inspector General, FNS Controls Over SNAP Benefits For Able-Bodied 

Adults Without Dependents, September 2016, https://www.usda.gov/oig/webdocs/27601-0002- 

31.pdf; U.S. Department of Agriculture, Food and Nutrition Service, ‘‘Supplemental Nutrition 

Assistance Program—Expiration of Statewide ABAWD Time Limit Waivers,’’ March 4, 2015, 

https://fns-prod.azureedge.net/sites/default/files/snap/SNAP-Expiration-of-Statewide-ABAWDTime-Limit-Waivers.pdf; https://fns-prod.azureedge.net/sites/default/files/snap/SNAP-Expiration-of-Statewide-ABAWD-Time-Limit-Waivers.pdf; U.S. Department of Agriculture, Food and 

Nutrition Service, ‘‘Guide to Serving ABAWDs Subject to Time-limited Participation,’’ 2015 

https://fns-prod.azureedge.net/sites/default/files/Guide_to_Serving_ABAWDs_Subject_to_Time_ Limit.pdf; U.S. Department of Agriculture, Food and Nutrition Service, ‘‘Supplemental Nutrition 

Assistance Program—ABAWD Time Limit Policy and Program Access,’’ November 19, 2015, 

https://fns-prod.azureedge.net/sites/default/files/snap/ABAWD-Time-Limit-Policy-and-Program-Access-Memo-Nov2015.pdf. 

A. Certainty About Waiver Approval Process Is Crucial Due to Lengthy State Implementation Process 

With a reasonable amount of certainty about FNS waiver approval, states can 

begin to plan earlier than if they had to wait for FNS to process waiver approval, 

which can take months and substantially delay planning. Having time to plan for 

implementation is crucial for states because of the demands of thoroughly implementing the time limit. As several documents from USDA—including memos, guidance, and a report from USDA’s Office of the Inspector General (OIG)—make clear, 

before a state can implement the time limit in a new area, states must: 

• Identify individuals subject to the time limit: as one FNS memo explains, ‘‘Prior 

to waiver expiration, states must review case file information to identify individual ABAWDs and determine whether or not the ABAWD is subject to the 

time limit.’’ 347

• Inform individuals subject to the time limit: state agencies have minimum requirements for notifying people who are subject or potentially subject to the 

time limit (such as an individual a state has identified as likely subject to the 

time limit based on age and other characteristics, but who may be eligible for 

an exemption). As one memo explains, states must ‘‘inform ABAWD and potential ABAWD households of the time limit, exemption criteria (including exemptions from the general work requirements), and how to fulfill the ABAWD work 

requirement,’’ as well as the requirement to report when work hours fall below 

20 hours per week.348 The law requires caseworkers to explain these rules during the individual’s eligibility interview, but given the complexity of the policy, 

FNS recommends providing written notice to clients at least 30 days before the 

waiver ends. FNS encourages states to write notices in clear, understandable 

language, develop public information materials for websites and waiting rooms, 

and leverage partnerships in the community such as service providers.349 To 

properly implement the time limit, states must therefore train staff to ensure 

they can effectively explain the requirements to individuals subject to the time 

limit, develop written notifications, and use other resources such as community 

partnerships—all well before a waiver ends. 

• Develop policies: States must develop policies for many aspects of the time 

limit, such as whether they will use a fixed or rolling clock, what procedures 

they will use to screen individuals for exemptions and what verifications are required, whether they will count unpaid or volunteer work towards the requirement, and how they will use 15 percent exemptions, among many others.350

States must also communicate these policies to caseworkers and other relevant 

staff, and ensure that computer systems reflect their policy choices. While some 

of these policy decisions may not change depending on the waiver outcome if 

the state has developed these policies for areas that already have the time limit, 

states or counties preparing to implement the time limit for the first time will 

need time to ensure that policies are ready for implementation prior to the expiration of a waiver. 

• Ready computer systems for tracking: as the OIG report explains, ‘‘Each month, 

the states are responsible for tracking an ABAWD’s status; countable months; 

264 

351 USDA Office of Inspector General, FNS Controls Over SNAP Benefits For Able-Bodied 

Adults Without Dependents, September 2016, https://www.usda.gov/oig/webdocs/27601-0002- 

31.pdf. 352 USDA Office of Inspector General, Supplemental Nutrition Assistance Program—Able-Bodied Adults without Dependents (ABAWD) Questions and Answers—June, 2015, https://fnsprod.azureedge.net/sites/default/files/snap/ABAWD-Questions-and-Answers-June%202015.pdf. 353 U.S. Department of Agriculture, Food and Nutrition Service, ‘‘SNAP—Requirements for Informing Households of ABAWD Rules,’’ April 17, 2017, https://fns-prod.azureedge.net/sites/default/files/snap/Requirements_for_Informing_Households_of_ABAWD_Rules.pdf. 354 USDA Office of Inspector General, FNS Controls Over SNAP Benefits For Able-Bodied 

Adults Without Dependents, September 2016, https://www.usda.gov/oig/webdocs/27601-0002- 

31.pdf. 355 U.S. Department of Agriculture, Food and Nutrition Service, ‘‘Supplemental Nutrition Assistance Program—ABAWD Time Limit Policy and Program Access,’’ November 19, 2015, 

https://fns-prod.azureedge.net/sites/default/files/snap/ABAWD-Time-Limit-Policy-and-Program-Access-Memo-Nov2015.pdf. 356 U.S. Department of Agriculture, Food and Nutrition Service, ‘‘Guide to Serving ABAWDs 

Subject to Time-limited Participation,’’ 2015, https://fns-prod.azureedge.net/sites/default/files/ 

Guide_to_Serving_ABAWDs_Subject_to_Time_Limit.pdf. 357 NPRM, p. 983. 

fulfillment of the work requirement; exemption status with respect to age, pregnancy, and mental or physical capacity to perform work; 15 percent exemption 

status; and good cause for not meeting the work requirement.’’ 351 Setting up 

computer systems to accurately perform this complex monthly tracking, which 

may require states to work with contractors to re-program systems and test for 

errors, can be a time-consuming process. 

• Train caseworkers: states must build in adequate time to ensure that eligibility 

workers thoroughly understand and can implement related policies, which may 

take months. For example, workers must be prepared to follow procedures to 

assess individuals’ fitness for work in order to screen for exemptions from the 

time limit 352 and must be prepared to explain the requirements to those individuals during the eligibility interview,353 among other tasks instrumental to 

implementing the time limit. The OIG report states, ‘‘FNS national officials informed us that the ABAWD provisions were very complex and that it takes 

months of extensive training for new staff to fully understand the ABAWD requirements. A state official said the ABAWD laws and regulations are the ‘most 

complicated SNAP policy in existence’ and are ‘fraught with the potential for 

case errors.’ ’’ 354

• Identify providers for qualifying work activities: Most states are not required 

to provide individuals subject to the time limit with spots in work programs 

that can fulfill the 20 hour a week requirement (called ‘‘qualifying activities’’). 

The exceptions are ‘‘pledge states,’’ which receive additional funding for employment and training (E&T) programs if they commit to providing a work training 

spot to individuals subject to the time limit in their last month of SNAP benefits. FNS has in the past encouraged states to provide qualifying activities to 

individuals subject to the time limit.355 States that do wish to provide these 

services must identify current E&T providers that can offer work placements 

for participants, and/or develop new relationships with providers to offer placements.356

Preparing for implementation is therefore a lengthy and difficulty process, given 

that states must identify and notify individuals subject to the time limit, develop 

policies and guidance to support implementation, train workers, ready computer 

systems, and (if they choose) develop slots in work programs. Ensuring that local 

offices are ready to implement when a waiver changes or when a state or county 

implements the time limit for the first time is important not only to ensure that 

needy individuals don’t mistakenly lose access to food assistance, but also to prevent 

incorrect implementation of the time limit from causing case errors. 

Unclear if Proposed Rule’s Core Standards Are Different From ‘‘Readily Approvable’’ 

Standard 

The proposed rule would weaken both provisions that currently provide states 

with more certainty of FNS approval. First, the NPRM would remove the language 

establishing that waivers with certain criteria are ‘‘readily approvable.’’ The preamble to the NPRM explains that the waivers requested under the ‘‘core standards’’ 

are likely to be approved, stating: ‘‘These revisions would include the establishment 

of core standards that would allow a state to reasonably anticipate whether it would 

receive approval from the Department.’’ 357 While the preamble therefore suggests 

that states may understand that waivers requested under the ‘‘core standards’’ can 

265 

358 NPRM, p. 987. 359 U.S. Department of Agriculture, Food and Nutrition Service, ‘‘Guide to Supporting Requests to Waive the Time Limit for Able-Bodied Adults without Dependents (ABAWD),’’ December 2, 2016, https://fns-prod.azureedge.net/sites/default/files/snap/SNAP-Guide-to-SupportingRequests-to-Waive-the-Time-Limit-for-ABAWDs.pdf. 360For reference, on March 15, 2019, the BLS website stated it would release February 2019 

state data on March 22 and local data (such as counties and metropolitan areas) on April 3, 

2019, a typical lag of around 2 months for local unemployment data. https://www.bls.gov/ 

lau/, accessed March 15, 2019. 

be reasonably be expected to be approved (provided they include the correct data 

and are calculated accurately), the actual rule lacks the specificity of the ‘‘readily 

approvable’’ language in current regulations at 7 CFR § 273.24(f)(3). The proposed 

rule states: ‘‘(2) Core standards. FNS will approve waiver requests under (1)(i) and 

(ii) that are supported by any one of the following.’’ If these core standards are indeed ‘‘readily approvable,’’ then clarifying that USDA will approve waiver based on 

those standards would enable states to continue to plan for implementation. 

The proposed rule would also eliminate the current provision at 7 CFR 

§ 273.24(f)(4) that allows states to implement the waiver upon submission. The preamble states: 

The proposed rule would bar states from implementing a waiver prior to its 

approval. Though rarely used, current regulations allow a state to implement 

an ABAWD waiver as soon as the state submits the waiver request based on 

certain criteria. By removing the current pertinent text in 273.24(f)(4), the proposed rule would require states to request and receive approval before implementing a waiver. This would allow the Department to have a more accurate 

understanding of the status of existing waivers and would provide better oversight in the waiver process. It would also prevent waivers from being implemented until the Department explicitly reviewed and approved the waiver.358

The Department’s rationale for eliminating this provision is unclear given that 

the proposed rule also establishes ‘‘core standards’’ and current regulations require 

states to submit a detailed waiver request before implementing. The Department 

claims that eliminating the provision would allow the Department to ‘‘have a more 

accurate understanding of the status of existing waivers,’’ but the Department does 

not explain why it lacks this clarity under current rules (given that states must submit waiver requests with the proposed waiver date of implementation) and cannot 

instead clarify requirements around informing FNS about implementation, rather 

than limit states’ ability to implement a waiver while waiting for FNS approval. The 

Department also states that removing this provision would allow the Department 

to ‘‘provide better oversight in the waiver process,’’ but again does not explain what 

current issue this proposal would address. If states can only submit waivers based 

on very clear criteria with clear methods, and FNS has the ability to modify the 

waiver, why does the Department suggest it currently lacks oversight in this process? The provision does not remove the ability of FNS to review and approve waivers, but instead moves up the timeline to give states the ability to more effectively 

implement waivers they know will be approved. FNS does not explain what need 

or deficit this proposal seeks to remedy, which makes it very difficult for comments 

to respond. 

Department Does Not Address Impact of Its New, Lengthy Approval Process on 

State Implementation 

The most problematic aspect of the Department’s proposal to remove the ability 

of states to implement waivers prior to approval is that the Department does not 

make any proposal that will ensure that the Department approves waivers in a 

timely enough fashion to give states the certainty they need to properly implement 

the time limit. Current regulations and guidelines require waivers to be based on 

recent economic data, which by definition narrows the window of time between a 

state’s waiver submission and the implementation date. 

For example, as recent guidance explains, for waivers based on a 12 month unemployment rate of ten percent, the data must include at least 1 month in the year 

prior to implementation; therefore the ‘‘furthest a state could look back in requesting a waiver for January 1, 2018, implementation would be the 12 month period 

of February 2016 through January 2017.’’ 359 Local unemployment data is generally 

available with a lag of about 2 months, so January 2017 data would be available 

in early March 2017 or so.360 In addition, annual revisions from BLS that typically 

occur in April can substantially change recent estimates of unemployment and thus 

substantially alter waiver eligibility, so states often have to confirm waiver requests 

submitted before the April revision to ensure that the waiver request reflects the 

266 

361 BLS updates sub-state data annually, typically in April. https://www.bls.gov/lau/ 

launews1.htm. 362 NPRM, p. 983. 

most up-to-date data.361 The state would therefore have at most 10 months total 

(or 9 months if waiting for the BLS update) to: analyze the data, prepare a waiver 

request, receive approval through the state’s internal process (a process that the 

deeply flawed proposal to require the Governor’s endorsement could substantially 

lengthen), submit the waiver request to FNS (including through the regional office, 

which must review and then forward it to the national office), receive approval from 

FNS after its review, and prepare for implementation of the waiver by taken the 

steps outlined above, such as identifying and notifying participants, programming 

computer systems, and training caseworkers. 

Given that the waiver preparation and internal review process may take at least 

a month or 2 within a state, if FNS review extends into several months, that can 

leave states with very little time for preparation given the complexities of implementation outlined above. The certainty that they can implement the requested 

waiver allows states to plan more effectively, while also allowing FNS time to review and issue an approval, knowing that its review does not hinder the state from 

preparing for implementation. Given that FNS seeks to eliminate the provisions 

that currently allow states this certainty without committing to approval within a 

certain timeframe, this proposed rule will instead make it harder for states to plan 

effectively. 

One recent example of why this ability helps states is California’s experience with 

its 2018 waiver, which the state began to implement prior to approval when waiting 

for an extensive and lengthy FNS review process. As mentioned in Chapter 2, any 

uncertainty has arisen due to the most recent Administration substantially delaying 

the waiver review process. In September 2017, California submitted a waiver request for areas with unemployment rates 20 percent above the national average 

(one of the categories of ‘‘readily approvable’’ areas), with an implementation date 

of September 2018. Given that California was transitioning off a statewide waiver 

and implementing the time limit for the first time in several years in some counties, 

and given the complexities with a large, county-administered state, the state needed 

at least 6 months to prepare for waiver implementation. By February 2018, about 

5 months after the state had submitted the request, FNS still had neither approved 

nor denied the request. California wrote FNS that it would prepare to implement 

based on its waiver request, given that the request was based on data that fit the 

‘‘readily approvable’’ standard, and requested that FNS advise the state by March 

2018 if it wished to modify the waiver. Though FNS approval took over 5 months 

in this instance, the ‘‘readily approvable’’ standard enabled the state to properly 

plan for implementation. Unless FNS plans to impose deadlines on its own review 

and approval process that will ensure a timely response to states via the regulation, 

taking away these provisions will result in substantially less certainty for states as 

they await FNS approval. 

The Department claims that the NPRM would improve consistency in the waiver 

approval process, but eliminating these provisions would introduce more uncertainty 

and inconsistency. The Department several times makes clear that one of the motivating factors for the NPRM is to improve consistency, such as stating, when introducing ‘‘core standards,’’ that ‘‘The Department proposes updating criteria for 

ABAWD time limit waivers to improve consistency across states.’’ 362 Reducing the 

ability of states to predict approvals and await FNS approval, therefore cutting into 

implementation planning time, would result in states’ planning becoming more contingent on the length of time that various steps in the waiver preparation and approval process take. Factors such as the length of the approval process within the 

state and the length of FNS approval would have even more weight on the length 

of time states have to implement. A state waiting 6 months for approval would have 

significantly less effective implementation time than a state waiting 3 months. It 

is not clear if the Department considered the effect of the elimination of these provisions on the consistency of time limit implementation outcomes. If so, the Department did not explain how eliminating these provisions could affect implementation 

and how it weighed those costs against what it perceived to be the benefits of improved oversight, for which it did not articulate a need. 

FNS proposes substantially limiting the ability of states to plan for implementation while waiting for waiver review. In proposing this change, FNS makes statements about the intended effect of the proposal to increase oversight without explaining why this change is necessary or acknowledging the substantial burden it 

could impose on states and clients subject to the time limit. We recommend that 

267 

363 NPRM, p. 983. 

FNS keep the current language in regulation that gives states more certainty 

around approval, which lets states better plan for waivers. 

B. Proposed Implementation Date Would Cause Severe Burden for States 

The Department also proposes that the rule take effect in October 2019, only 6 

months after the end of the comment period for the NPRM—an extremely short period following the final rule’s publication. The preamble states: 

The Department proposes that the rule, once finalized, would go into effect 

on October 1, 2019, which is the beginning of Federal Fiscal Year 2020. All 

waivers in effect on October 1, 2019, or thereafter, would need to be approvable 

according to the new rule at that time. Any approved waiver that does not meet 

the criteria established in the new rule would be terminated on October 1, 2019. 

States would be able to request new waivers if the state’s waiver is expected 

to be terminated.363

The Department clearly is not considering the length of time states need to prepare a waiver request, the time it takes states and FNS to review and approve 

waivers, or the substantial time it takes states to ensure that they can prepare for 

implementation and properly notify individuals subject to the time limit. Given that 

the comment period ends in April 2019, it is not plausible that there would be anywhere near enough time for any one step of this process, let alone all of them. In 

the past, when many states have waivers due at the same time, this has substantially delayed FNS review; with this rule implementation, at least 30 states would 

likely attempt to submit a waiver request at the same time. FNS does not acknowledge the additional resources it would need to designate to review these requests, 

which would need to happen within a very short time frame. Nor does FNS acknowledge the burden this proposal would place on states, which would need to devote resources to quickly analyzing the data to put forward new requests and to implementing the time limit in new areas, and on the participants who would be 

harmed by a likely chaotic implementation in many states. 

In addition, FNS does not put forward any need that would justify this short 

timeline. As we have explained, the current regulations changed little since the 

1996 guidelines; in practice, then, states have been operating under current waiver 

criteria for more than 20 years. FNS proposes to make significant changes to longstanding policy without articulating a need for this change, but also proposes an extremely short timeline that it does not attempt to justify. The lack of explanation 

for the proposed implementation date suggests that in proposing this rule, the Department did not fully grapple with the realities of implementing these changes. 

Without any explanation of why such a drastic change would be necessary under 

such a short timeline, and without any consideration of the downside of forcing 

states to implement the time limit in new areas with very little preparation time, 

the Department leaves us with little opportunity to address the unstated need motivating this change. Withdrawing the proposed rule would be the best solution to 

avoid a rushed implementation of an ill-considered and harmful policy. 

C. Limiting the Duration of Certain Waivers to the Fiscal Year in Which They Are 

Implemented is Unnecessarily Restrictive 

The Department proposes that waivers based on the 20 percent standard outlined 

in paragraph (f)(2)(ii) would not be approved beyond the fiscal year in which the 

waiver is implemented. Since most waivers are currently and likely would continue 

to be requested under the criteria specified in 7 CFR § 273.24(f)(2)(ii), it’s likely that 

this shift would mandate that most waivers shift to a fiscal year cycle. 

As of March 2019, 36 states (including Guam and the Virgin Islands) have 

ABAWD time limit waivers. Nine states are on the Federal Fiscal Year 2019 cycle, 

19 states are on the calendar year 2019 cycle, and eight states are covering parts 

of both Fiscal Year 2018 and 2019. This grouping of waivers around calendar year 

and fiscal year is a relatively new phenomenon that is an outgrowth of two pieces 

of legislation that motivated states to pursue waivers along those time cycles: 

• The American Recovery and Reinvestment Act (ARRA) of 2009. That legislation 

suspended the time limit, with a state opt out, through FY 2010. 

• The Emergency Unemployment Compensation program (EUC) that operated 

through December 2015. Many states sought statewide waivers through their 

eligibility for Extended Benefits (EB) under EUC. 

As the statutory suspension of the time limit (set under a fiscal year cycle) expired and as state eligibility for waivers under EUC phased out in 2016 (set under 

268 

364 Bureau of Labor Statistics, Annual Revisions, https://www.bls.gov/lau/launews1.htm. 

a calendar year cycle), states sought to renew their waivers using alternative criteria but according to the new time cycles. Prior to the passage of ARRA and EUC, 

states waiver cycles were spread throughout the year with many running from April 

to May. 

In the NPRM, FNS claims that the proposed rule would prioritize recent data by 

preventing states from requesting to implement waivers late in the Federal fiscal 

year. This proposal would actually have a different outcome because states would 

have fewer recent periods of data available to use under this criterion. Under the 

proposed rule waivers beginning in Fiscal Year 2020 can use unemployment data 

starting no earlier than January 2017, so approximately five 24 month time periods 

would be available to states. In contrast, for a waiver starting in January 2020, 

states would have eight 24 month time periods of unemployment data to use (including three more recent than under the fiscal year calendar scenario). Shifting 

states to a fiscal year waiver calendar removes the current option that states have 

to avail themselves of the most recent data. 

For example, states typically submit waiver requests 3 to 6 months prior to the 

waiver implementation date to give FNS sufficient time to process waiver requests. 

For a waiver to begin on October 1, states are recommended to submit the waiver 

in June, when approximately five 24 month time periods would be available. For 

a waiver to begin on January 1, states would have about three additional and more 

recent time periods to use. 

The proposed rule would also force states to have short waivers under some circumstances. States are permitted to submit a waiver at any point during the year. 

This is an important feature in times of rising unemployment when states may wish 

to submit new waivers for newly eligible areas. If a state wants to request a new 

waiver or modify a waiver after October 1 based on more recent unemployment 

data, a waiver would need to be approved for less than a year under the proposed 

rule. This would impose addition paperwork for waiver renewals on states during 

an economic downturn because states that submit new waivers during the fiscal 

year would not get a 12 month approval regardless of how distressed their local 

labor market is. 

Also, this limitation does not give states sufficient time to plan and implement 

waivers. As noted above, states typically submit waiver requests well in advance of 

their start date to allow for needed implementation planning as well as FNS’ slow 

processing. States do not know their eligible areas until late April when BLS revises 

historical estimates for sub-state areas from the Local Area Unemployment Statistics (LAUS) program. These revisions reflect new population estimates from the 

Census Bureau, updated input data, and estimation.364 If states need to submit a 

waiver in June (for an October 1 start), they would only have 1 to 2 months to plan 

and request the subsequent waivers. This would likely be particularly challenging 

for states pursuing a thoughtful and thorough implementation of the new waiver. 

Consider states that have to shift from a statewide waiver using the EB criteria 

(which would not be limited to a fiscal year cycle under the proposed rule) to a 20 

percent above the national average criterion (which would operate on a fiscal year 

cycle only under the proposed rule). For example, consider a state that has a statewide waiver based on the EB criteria running from September to August. For the 

next waiver (which would likely be based on the criteria listed in paragraph 

(f)(2)(ii)), the waiver could only be for 1 month because the fiscal year runs through 

September. If the state wanted continuous waiver coverage, it would have to request 

a one 1 month waiver for the month of September, then a 1 year waiver starting 

in October. These multiple requests would create additional administrative work for 

states and FNS. 

Moreover, FNS does not have enough capacity to process waivers if they are all 

on the fiscal year cycle. And, as we comment elsewhere, the Department is not imposing a timely review on itself which has resulted in delayed approvals. These 

delays would only grow worse if virtually all waivers were on the same cycle for 

review. 

This proposal is flawed and should not be included in the final rule. 

D. Limiting Waivers to One Year Would Impose an Unnecessary Administrative Burden on states 

The proposed rule would limit the duration of waiver approvals to 1 year. We believe this would impose an additional administrative burden on states that is unjustified and unnecessary. In the NPRM, the Department asserts that limiting waivers to 1 year would ensure that the waiver request reflects current economic conditions, but it provides no evidence or discussion to support this assertion. This makes 

269 

365 7 CFR § 273.24(f)(5). 366 USDA, ‘‘2-Year Approvals of Waivers of the Work Requirements for ABAWDs under 7 CFR 

273.24,’’ February 3, 2006. USDA, ‘‘Guidance on Requesting ABAWD Waivers,’’ August 2006. 

USDA, ‘‘Guide to Supporting Requests to Waive the Time Limit for Able-Bodied Adults without 

Dependents (ABAWD),’’ December 2, 2016. 367 A waiver request includes one or more jurisdictions in a state and may even cover the entire state. Each approved waiver request is given a distinct waiver serial number by FNS. States 

may not implement waivers in all areas approved by FNS. 368 A waiver request includes one or more jurisdictions in a state and may even cover the entire state. Each approved waiver request is given a distinct waiver serial number by FNS. Based 

on CBPP internal records and summary of 2 year waivers from SNAP 3 month time limit. Prepared in March 2019. 

it difficult to comment on the proposed change and its potential impact on both the 

alignment of waivers with current labor market conditions and state agencies. This 

section provides an overview of existing requirements for 2 year waivers and explains why the proposed change is unnecessary. 

Existing Requirements for Two-Year Waivers Are Already Restrictive 

The Department generally approves waivers for 1 year. Existing regulations state 

that the Department reserves the right to approve a waiver for a longer period if 

the reasons are compelling.365 In previous guidance, the Department acknowledged 

the role of 2 year waivers in minimizing administrative burdens on states from preparing annual requests for waivers covering areas with chronic high unemployment.366 Areas that qualify for 2 year waivers are those that have had chronic high 

unemployment and are likely to continue to experience high unemployment. Twoyear waivers have also been used to cover states and sub-state areas hit hard by 

the Great Recession of 2007 to 2009. 

The data requirements to support a request for a 2 year waiver are much more 

restrictive than those required for a 1 year waiver. The area must satisfy at least 

one of the following: 

• Have an unemployment rate above ten percent for the 2 year period immediately prior to request; 

• Be designated as a Labor Surplus Area for at least 2 consecutive years; or 

• Have an unemployment rate more than 20 percent above the national average 

for a 36 month period ending no earlier than 3 months prior to the request. 

The data requirements are more restrictive in several ways. First, an area eligible 

for a 2 year waiver must have evidence of high unemployment sustained over a significantly longer period of time than that required for a 1 year waiver. For instance, 

under the third criterion above, the area must have elevated unemployment over 

a period that is 50 percent longer than that required to support a 1 year waiver 

(36 months compared to 24 months). These are areas with persistent, chronic high 

unemployment and are likely to continue to experience adverse labor market conditions. As we saw during the Great Recession, areas eligible for 2 year waivers included those that experienced a rapid rise in unemployment rates before the rest 

of the country or experienced slower recovery. 

Second, a request for a 2 year waiver must be supported by very recent data. To 

be eligible under the third criterion above, the 36 month period must end no earlier 

than 3 months prior to the request. Given that there already is a time lag of 1 to 

2 months before BLS Local Area Unemployment Statistics becomes available at the 

sub-state level, this is a very restrictive requirement. 

To support a 1 year waiver requested on October 2018, for example, a state could 

submit data for the period January 2016 to December 2017. This corresponds with 

the time period used to compile the LSA list for FY 2019. To request a 2 year waiver, the state would have to submit data no older than June 2018 and the 35 previous months, a period that starts July 2015. Data supporting a 2 year waiver incorporates data both earlier and later than what is required for a 1 year waiver. To 

qualify, the area would have to have chronic high unemployment and be likely to 

continue having it within the time frame of a 2 year waiver. 

Use of Two-Year Waivers Has Been Very Limited 

Under existing rules and guidance, waivers longer than 1 year in duration have 

only been requested and approved under limited circumstances, reflecting their 

more restrictive and extensive data requirements. Over the 2 decades of waiver approvals, FNS has approved approximately 900 waiver requests.367 Of those approved requests, only about six percent (50 waiver requests) were based on the 36 

month unemployment rate criteria.368 Nearly 1⁄2 of the 50 waiver approvals were in 

270 

369 A table with the states that have had 2 year waivers from the time limit is included in 

Appendix B as, Center on Budget and Policy Priorities. ‘‘Summary of 2-Year Waivers from SNAP 

Three-Month Time Limit.’’ 370The American Recovery and Reinvestment Act went into effect April 1, 2009, suspending 

the time limit in all states through September 30, 2010 unless state agencies chose to impose 

specific work requirements. 371The Department approved 2 year waivers covering 19 jurisdictions (seven states, one island, and eleven Indian reservations) in Federal Fiscal Years 2016 and 2017. Of the 19 jurisdictions, 17 would have been eligible for back-to-back 1 year waivers. 

effect during Federal Fiscal Years 2007 to 2009, helping states that were hit hard 

by the Great Recession, like Alaska, Mississippi, Oregon, and South Carolina, 

weather the economic downturn.369

States have also requested 2 year waivers to cover jurisdictions and Native American Tribal areas that have had chronic high unemployment. For example, Nebraska 

prepared, applied for, and received 2 year waivers for Tribal areas in FFY 2002 

(waiver in effect May 2002 to April 2004), FFY 2004 (waiver in effect May 2004 to 

April 2006), FFY 2006 (waiver in effect May 2006 to April 2008), and FFY 2008 

(waiver in effect May 2008 to April 2010). Had the proposed rule been in effect, Nebraska would have had to apply for 1 year waivers for these Tribal areas every year. 

The Nebraska state agency only had to apply four times instead of eight times to 

cover these areas with chronic high unemployment from May 2002 to April 2010.370

The Department has also approved waivers longer than a year on a case-by-case 

basis to accommodate states facing unusual administrative constraints. For example, it approved a 17 month waiver (from May 2007 to September 2008) for Utah 

to ease administrative burdens while the state was transitioning to a new eligibility 

system. 

Limiting Waiver Duration to One Year Is Inefficient 

Given the more restrictive data requirements, areas eligible for a 2 year waiver 

are experiencing chronic high unemployment and would likely be eligible for 1 year 

waivers in 2 or more consecutive years. By prohibiting waivers longer than a year, 

the Department would be requiring states to prepare and submit waiver requests 

twice over the course of a 2 year period, instead of submitting a request once. Our 

analysis finds that most areas approved for 2 year waivers in FFY16–17 would have 

qualified for the second year,371 so requiring the state to submit—and FNS to review—the information would have been inefficient and burdensome. 

The existing data requirements for a 2 year waiver capture high unemployment 

using data that is very current. The Department did not substantiate its assertion 

that a 1 year time frame would ensure that waiver requests reflect current economic 

conditions. Nor did it discuss why the proposed change is warranted given that it 

would add administrative burdens both to state agencies preparing waiver requests 

and the Department itself. The option to request a 2 year waiver is already very 

restrictive and limited in use. We therefore recommend that the Department abandon its proposal to limit waivers to 1 year and keep the existing rules allowing 2 

year waivers as they are. 

Chapter 9. Eliminating the Carryover of Unused Individual Exemptions 

Would Cause Hardship and Exceeds Agency Authority 

In addition to significantly restricting the ability of states to request waivers of 

the 3 month time limit, the NPRM proposes to eliminate the accrual of unused individual exemptions for more than 1 fiscal year. As a result, some individuals who 

might otherwise be exempted from the time limit would lose SNAP benefits and the 

program’s integrity would be undermined as states would be less able to judiciously 

exempt particularly vulnerable individuals. The NPRM fails to define a problem it 

is addressing with this proposal, incorrectly reads the intent of Congress, and proposes a less effective alternative. 

Under current law, states can exempt a limited number of individuals who are, 

or would be, subject to the time limit. Each year, FNS is required to estimate the 

number of exemptions available to each state, based on a percentage (currently 12 

percent as revised from 15 percent in the 2018 Agricultural Improvement Act) of 

‘‘covered individuals.’’ These ‘‘covered individuals’’ are SNAP participants subject to 

the time limit during the fiscal year or individuals denied eligibility in SNAP because of the time limit. 

It is disconcerting to note that the NPRM incorrectly describes the way in which 

exemptions are calculated. The preamble describes ‘‘covered individuals’’ as ‘‘the 

ABAWDs who are subject to the ABAWD time limit in the state in Fiscal Year 2020 

and each subsequent fiscal year.’’ But this is not a correct description of ‘‘covered 

individuals.’’ Section 6(o)(6)(A)(ii) of the Food and Nutrition Act (7 U.S.C. 

271 

372 NPRM, p. 987. 373Section 1001 of P.L. 105–33. 374 U.S. Department of Agriculture, Food and Nutrition Service, ‘‘Implementation of the Provisions of the Balanced Budget Act of 1997 Relating to Exemptions for Able-Bodied Adults without 

Dependents (ABAWDs),’’ October 27, 1997. 375 House of Representatives, Conference Report to Accompany H.R. 2, December 10, 2018, p. 

616, https://www.agriculture.senate.gov/imo/media/doc/CRPT-115hrpt1072.pdf. 

§ 2015(o)(6)(A)(ii)) defines a ‘‘covered individual’’ as ‘‘a member of a household that 

receives [SNAP], or an individual denied eligibility for [SNAP] benefits solely due 

to paragraph (2)’’ (emphasis added), with several additional clarifications. As we discuss in our comments on the Regulatory Impact Analysis, the imprecise use of 

‘‘ABAWD’’ makes it unclear whether the NPRM is accurately describing the group 

of SNAP participants who form part of the pool that is used to determine the number of exemptions, but the NPRM also fails to include individuals denied eligibility 

due to failure to meet the time limit requirements. As most ‘‘ABAWDs’’ subject to 

the rule lose benefits over time, this can be a significant number of individuals. 

A. There Is No Statutory or Legislative Support for the Claim That Unused Exemptions Cannot Be Kept By States 

The NPRM suggests that Congress did not explicitly intend for states to maintain 

and accrue unused exemptions, but this is not supported by the record. The NPRM 

describes the accrual of unused exemptions as an ‘‘unintended outcome of the current regulations.’’ 372 It further expresses concern that ‘‘such an outcome is inconsistent with Congressional intent to limit the number of exemptions available to 

states each year.’’ The NPRM does not provide any evidence supporting this claim 

of Congressional intent. We are unable to find any record of Congressional intent 

to limit the carryover of unused exemptions. The historical evidence and recent actions by Congress show the opposite. 

Congressional history shows that exemptions were enacted in legislation approximately 1 year after the time limit was enacted precisely due to concerns that the 

policy was too harsh and states did not have enough tools to mitigate the impact 

of the time limit for vulnerable individuals living outside of waived areas. Adding 

this resource gave states an additional way to protect vulnerable residents not specifically identified in the exemptions from the time limit provided under 7 U.S.C. 

§ 2015(o)(3), based on the priorities and concerns of the state or local agency. 

The Balanced Budget Act of 1997 contained two major changes in SNAP to ameliorate the impact of the 3 month time limit. One was an increase in funding for 

ABAWD training slots in the Employment and Training (E&T) program. The other 

was providing states with the authority to exempt a limited number of individuals 

from the time limit.373 Commonly referred to as hardship exemptions, these gave 

states the ability to continue to provide SNAP to individuals subject to the time 

limit who could not find jobs or training slots after 3 months of participation. Just 

after passage of this change, FNS clarified in an October 1997 guidance to states 

that unused exemptions could be carried over or saved for future use.374

The current individual exemption policy has been in place for over 20 years. Congress did recently intend to limit exemptions, but not in the way proposed in the 

NPRM. Instead Congress reduced the percentage of exemptions created each year, 

but explicitly left the longstanding accrual policy in place. In the 2018 Farm Bill, 

Congress reduced the annual percentage of exemptions from 15 percent to 12 percent, but notably did not propose ending the practice of accruing unused exemptions. 

In fact, the Conference Report to accompany H.R. 2, the Agricultural Improvement 

Act, clarified that ‘‘States will maintain the ability to exempt up to 12% of their 

SNAP population subject to ABAWD work requirements, down from 15%, and con- tinue to accrue exemptions and retain any carryover exemptions from previous years, 

consistent with current law.’’ 375 (emphasis added). Congressional intent as recently 

as several months ago shows a deliberate expectation that states can carryover an 

unlimited number of unused exemptions. 

The Statute Clearly Allows States to Accrue Unused Exemptions 

By drastically reducing the way in which states that choose not to use exemptions 

in the year in which they are issued are able to accrue these exemptions, the NPRM 

suggests that the current policy is an interpretation of the intent of the underlying 

statute. However, the statute is less confusing than it appears. It authorizes states 

to exempt up to 12 percent of the caseload (formerly 15 percent) but does not mandate that states use the exemptions over any particular time period. It then, separately, authorizes the Secretary to adjust the number of exemptions based on the 

state’s use of exemptions in the prior fiscal year. Under the provision, if a state does 

not use all exemptions, the Secretary increases the number of exemptions available 

272 

376 U.S. Department of Agriculture, Food and Nutrition Service, ‘‘Food Stamp Program: Food 

Stamp Provisions of the Balanced Budget Act of 1997,’’ Interim rule, Federal Register Vol. 64, 

No. 171, Sept. 3, 1999, p. 48246, https://www.govinfo.gov/content/pkg/FR-1999-09-03/pdf/99- 

23017.pdf. 377 U.S. Department of Agriculture, Food and Nutrition Service, ‘‘Food Stamp Program: Food 

Stamp Provisions of the Balanced Budget Act of 1997,’’ Interim rule, Federal Register Vol. 64, 

No. 171, Sept. 3, 1999, p. 48249, https://www.govinfo.gov/content/pkg/FR-1999-09-03/pdf/99- 

23017.pdf. 

in the current year. If the state overuses exemptions, then the Secretary reduces 

the number of exemptions available in the current year. The statute reads: 

. . . the Secretary shall increase or decrease the number of individuals who 

may be granted an exemption by a state agency under this paragraph to the 

extent that the average monthly number of exemptions in effect in the state for 

the preceding fiscal year under this paragraph is lesser or greater than the average monthly number of exemptions estimated for the state agency for such 

preceding fiscal year under this paragraph. 

The language sets out that the Secretary adjusts one way for one circumstance 

(too many exemptions used), and in another way for the other condition (fewer exemptions used than issued). The Secretary shall increase the number of individual 

exemptions to the extent that the average monthly number used in the previous 

year is less than then number estimated for that year. Similarly, the Secretary shall 

decrease the number of individual exemptions to the extent that the average monthly number used in the previous year is more than the number estimated for that 

year. 

Note that the Secretary is required to adjust the number of exemptions, but that 

the use of exemptions remains a state option (‘‘individuals who may be granted an 

exemption’’). And, if the state uses fewer exemptions than allotted in the previous 

fiscal year, the Secretary should increase the number of exemptions in the following 

year. The provision requires the Secretary to ‘‘increase or decrease’’ exemptions depending on whether the state’s use of exemptions is ‘‘lesser or greater than’’ the allotment for the previous year. So, it’s an increase if the state uses fewer exemptions 

and a decrease if the state uses more exemptions than allotted. This makes sense. 

By decreasing the allotment to a state that overuses the exemptions, the statute ensures that states cannot routinely use more than the yearly allotted amount. But 

that means that a state does increase its allotment each year that it does not use 

that year’s amount. States that repeatedly under-use allotments will accrue a bank 

of exemptions. This approach, codified in the current regulations, is a straightforward and fair reading of the statute’s directive. 

The proposed rule, in contrast, makes several unsupported assertions. First, it 

claims without support, that the intent was not to accrue exemptions for more than 

1 year. Second, by eliminating the existing supply of unused exemptions, it treats 

them as having no value to the state even though many states have accessed these 

accrued exemptions for a variety of allowable and sensible reasons. Third, it fails 

to explain why the current procedure to adjust exemptions each year is a flawed 

reading of the underlying statute. 

Legislative History Demonstrates That Congress Fully Understood and Approved of 

the Uncapped Accrual of Exemptions 

The guidelines explaining the calculation and use of individual exemptions were 

first promulgated in the September 3, 1999 interim rule implementing two SNAP 

provisions in the Balanced Budget Act of 1997.376 In that interim rule, the Department outlined how it would comply with the statutory requirement that the Secretary adjust the number of individuals who may be granted an exemption to account for any difference between the average of exemption used and the number estimated by the Agency for the preceding fiscal year. If a state uses more exemptions 

than estimated, the state’s subsequent allocation is reduced. Likewise, if a state 

uses fewer exemptions than estimated in the previous year, the state’s subsequent 

allocation is increased by the amount not used. As the Department explained ‘‘if this 

level of exemptions is not used by the end of the fiscal year, the state may carry 

over the balance.’’ 377

This longstanding implementation of the statutory directive is clear, reasonable, 

and fair to states. It addresses the reasonable concern that an annual allotment of 

exemptions could be either overused or underused. The continual overuse of individual exemptions has an impact on overall program integrity because individuals 

not eligible under an exemption are issued benefits, which is an over-issuance and 

error. To address this, the regulation treats this issue in a sensible way, by reducing 

273 

378 U.S. Department of Agriculture, Food and Nutrition Service, ‘‘SNAP—FY 2017 Allocations 

of 15 Percent Exemptions for ABAWDs—Totals Adjusted for Carryover,’’ March 15, 2017, 

https://fns-prod.azureedge.net/sites/default/files/snap/FY2017-ABAWD-15%25-Exemption-Totals.pdf. 

future exemptions. The continual under-use of individual exemptions does not create 

the same problem, and the regulation’s treatment is similarly reasonable. 

The statute does not direct the Secretary to make adjustments beyond a 1 year 

period. In other words, the statute does not give the Secretary the authority to adjust the number of exemptions issued more than 1 year prior ago. Combining the 

requirement that the Secretary adjust exemptions from the previous fiscal year with 

the limitation on looking further back to adjust exemptions based on use means that 

a state can accrue unused exemptions in multiple years, and these exemptions can 

accrue over multiple years. 

States Have Relied on Current Policy: USDA Has Never Emphasized the Need to 

Use Exemptions Each Year 

The Department has not, in the past, suggested that unused exemptions would 

not accrue. Developing a reasonable exemption policy is difficult—states must identify the circumstances when an individual exemption should be used, the procedures 

for identifying when that circumstance has occurred, and a tracking mechanism to 

ensure that the usage does not exceed the allotment. This implementation challenge 

has discouraged states from experimenting with ways of using the exemptions. But 

it does not indicate that states have no need for them. Instead of eliminating 

earned-but-unused exemptions, the Department could provide guidance to states on 

effective ways to use them. The Department could take steps to understand states’ 

concerns or problems with using exemptions. Such a response would be much more 

in keeping with Congressional intent and the law. Instead, via the NPRM, the Department has taken sweeping measures to curtail a state resource counter to the 

law. 

States Have Compelling Reasons to Accrue Individual Exemptions 

The recent statutory change from 15 percent to 12 percent makes the banked or 

unused exemptions more important for some states. While not every state uses its 

annual allotment of exemptions, some states do or come close to doing so. Many 

states use the ability to rollover exemptions to build a ‘‘bank’’ that gives states options that would be unavailable if exemptions expired. 

States use individual exemptions for a variety of purposes, as the original provision intended. Some identify certain vulnerable populations, such as victims of domestic violence, veterans, young adults aging out of foster care, or those with acute 

barriers to employment like a lack of education or limited proficiency in English. 

States have also used exemptions to allow individuals in limited areas to remain 

eligible for SNAP, often because of circumstances that are not reflected in a way 

that qualifies the area for a waiver or due to administrative demands. In all cases, 

states must estimate the number of individuals who would receive an exemption 

and for how long in order to ensure that the state does not exceed the number of 

available exemptions. Building up some unused exemptions gives states important 

flexibility and confidence to implement these targeted approaches without running 

afoul of over-issuing exemptions. The buffer provided by accrued exemptions is critical in that process. 

Because of the recent change in the percentage of exemptions made available to 

states, these states that are using exemptions would be at risk of exceeding their 

allotment and being subject to error determinations and overpayments under the 

NPRM. Between 2014 and 2017, 28 states used more exemptions than they had 

been issued for the fiscal year, meaning they used at least some of the exemptions 

they had accrued in previous years. During that time period, some states did so for 

more than 1 year. Several of the states used all of their multi-year exemptions 

which demonstrates the importance of accruing exemptions over several years. 

For example, Washington used 28,886 exemptions in Fiscal Year 2016.378 It had 

earned no exemptions in the prior year (because it had a statewide waiver in 2015). 

It had accrued 11,530 exemptions in previous years. It did not overuse exemptions 

because it was allocated 26,784 exemptions that year (meaning that it started 2017 

with over 9,000 unused exemptions). The state relied on exemptions that year because it was transitioning off of the statewide waiver and was developing training 

programs and operational procedures for childless adults subject to the rule. Other 

states used banked exemptions in a similar way. For example, in 2016, Maryland 

earned no exemptions for the year (based on having a statewide waiver in 2015) but 

issued 18,871 exemptions to aid in its transition to the time limit. It could do so 

274 

379 U.S. Department of Agriculture, Office of Inspector General, ‘‘FNS Controls Over SNAP 

Benefits for Able-Bodied Adults Without Dependents,’’ September 2016. 380Section 6(o) (7 U.S.C. § 2015(o)) of the Act does direct the Secretary to make limited adjustments to exemptions each year, but these are limited to changes in caseload and not based on 

whether or not a state used the exemptions issued. The E&T funding, by contrast, is adjusted 

based on state decisions to spend the allocation. 381 USDA Office of Inspector General, FNS Controls Over SNAP Benefits For Able-Bodied 

Adults Without Dependents, September 2016, p. 11. 

only because it had a ‘‘bank’’ of unused exemptions from prior years of 18,915. 

Under the proposed rule, neither state would have had been able to take this approach. 

The 3 month time limit is complex and difficult to administer, as is documented 

in the USDA Inspector General’s report.379 A majority of states have used individual exemptions to ensure that particularly vulnerable individuals are not inappropriately terminated from the program. Allowing states to keep unused exemptions enables states to plan in advance and prepare for major events affecting the 

unemployed childless adult population on SNAP (such as an area transitioning from 

waived to unwaived status). 

Congress Knows How to Limit Carryover and Has Repeatedly Declined to Do So for 

Unused Exemptions 

Congress has the authority and ability to limit the carryover of allocated resources in the legislation it crafts. This authority is exercised frequently, in order 

to prevent unused funds or resources from accruing. In fact, the Food and Nutrition 

Act demonstrates that Congress, when it deems it appropriate, can limit or reallocate resources, though it has not done so for individual exemptions. For example, 

in allocating funding for SNAP Employment and Training program, Section 16(h) 

(7 U.S.C. § 2025(h)) reads: 

(C) Reallocation.— 

(i) In General.—If a state agency will not expend all of the funds allocated 

to the state agency for a fiscal year under subparagraph (B), the Secretary 

shall reallocate the unexpended funds to other states (during the fiscal year 

or the subsequent fiscal year) as the Secretary considers appropriate and 

equitable. 

Here, Congress not only directs the Secretary to reallocate unspent funds but indicates when such reallocation occurs. Further subsections provide more detail on the 

mechanics of the reallocation. 

There is no similar provision in the Food and Nutrition Act indicating that Congress intended to limit the accrual of unused exemptions, or indeed, any directive 

for the states once exemptions are provided.380

B. The Proposed Rule Change Fails to Provide a Legitimate Reason for the Change 

The NPRM states that the change would result in administering the program 

more efficiently and to further the Department’s goal to promote self-sufficiency. 

However, the NPRM provides no explanation or information on how the proposed 

change would achieve either goal. The current exemption policy has worked well for 

20 years and FNS has never identified issues with the efficiency of the policy. Nothing in the proposed replacement policy would make it easier for state to administer. 

Indeed, because the safety valve of a bank of exemptions is eliminated, states will 

find it more difficult to fine-tune policies that authorize the use of exemptions. 

For example, a state may decide to provide an exemption to any individual who 

is working, but not enough hours to meet the 20 hour per week requirement for 

those subject to the time limit. It can estimate the number of individuals, and hence 

the number of exemptions. But inaccuracies in the calculation of the estimate or 

changes in the composition of the group can significantly change the number of exemptions needed. The existing policy provides states with a pool of unused exemptions a way to adjust; the proposed rule almost completely eliminates this ability 

to adjust. As a result, every state would be more at risk of exceeding its annual allocation of individual exemptions. 

In the NPRM, the Department references the September 2016 report from the Office of Inspector General to support the proposed change in the accrual of unused 

exemptions. While it is true that the report notes the large number of accrued exemptions, the report very explicitly declines to recommend any change in current 

policy. The report states ‘‘OIG generally agrees that FNS has the discretion to interpret and implement the exemption provisions as it has done, so we do not have a 

recommendation for FNS with respect to exemptions.’’ 381

275 

382 NPRM, p. 988. 

The Proposed Method of Calculating Exemptions and Adjusting From Prior Years 

Will Discourage States From Using Them and Increase the Potential for Errors 

The proposed adjustment procedure in the NPRM is needlessly confusing, will discourage the use of exemptions and is likely to increase errors. The varied exemption 

use example provided in the NPRM (Example 2 on page 988) shows how this proposed approach would discourage the use of allocated exemptions and contradicts 

the statutory requirements. In 2021, the state uses eight exemptions.382 In 2022, 

use plummets to two. In 2023, use quadruples to eight, and in 2024, it drops again 

to two. While the math works out to meet the proposed rule, the implementation 

of a policy that varies this widely in scope is hard to conceive. The state must be 

able to estimate the number of exemptions that would be used each year, design 

a policy and the procedures to implement to meet that target number, correctly 

train staff, and actually implement and track. Then, the following year, the state 

must design a policy that uses four times fewer (or greater) the number of exemptions, retrain staff, and properly implement. The NPRM offers no assurance that a 

state could successfully resdesign important program elements on a yearly basis. 

The history of state administration of SNAP also offers no assurance. 

In 2022, the state does not have its yearly allocation available, because in the 

prior year it tapped into previously earned exemptions. The state is paying back exemptions despite not overusing the total available exemptions in any year in the example. That conflicts with the statutory authority granting states exemptions in 

each year in which individuals are subject to the time limit or ineligible because 

of it. And, averaging over 2 years so that the average is equal to 12 percent of the 

‘‘ABAWDs’’ does not fulfill the statutory requirement that states can allocate an average of 12 percent per year. 

Chapter 10. The Proposed Rule Fails to Provide Sufficient Rationale or 

Supporting Evidence for the Proposed Policy Change 

The NPRM proposes several significant changes to long-standing SNAP policy 

that would affect an estimated 1.1 million low-income Americans, including 755,000 

who would lose food assistance and face increased financial and food insecurity. Despite the far-reaching impact of the proposed rule, and contrary to requirements in 

the rulemaking process, the NPRM fails to provide a meaningful rationale for most 

of the proposed changes and fails to identify or summarize any research and data 

to support the rationale for such sweeping and consequential changes. Without 

knowing what evidence justifies such a drastic change in long-standing policy, it is 

impossible to assess the validity of the claim or the soundness of the evidence used 

to support it. 

The goal of the Department’s proposed changes in policy appears to be to subject 

more people to the time limit by shrinking the portion of the country that can request waivers from it. To achieve this goal, the proposed rule would prohibit waivers 

of the time limit to those that are based on a general unemployment rate of at least 

seven percent and at least 20 percent above the national average and would restrict 

the ways in which a state can define the area it seeks to waive. In addition, the 

NPRM eliminates several ways in which a state can demonstrate a locale has an 

insufficient number of jobs for those subject to the rule and ends the ability of states 

to save unused exemptions to the time limit. In each case, the Department fails to 

identify a desired goal or outcome (such as a certain percentage of the target group 

gaining employment) or explain how the proposed rule would lead to the desired 

goal, and consistently fails to provide any empirical support for the proposal. These 

failures prevent the public from understanding why the existing rule needs to be 

modified so drastically. 

A. The Proposed Rule Fails to Support the Justification for New Rulemaking—That 

Too Many Unemployed Adults on SNAP Are Not Subject to the Time Limit 

The preamble to the proposed rule states that the Department now believes that 

the time limit for unemployed adults was intended to apply to more individuals 

than it currently does. The Department thus believes that too many individuals live 

in areas that are waived by states and not subject to the rule. But the Department 

fails to make several important connections to justify the need for new rulemaking. 

The Department fails to show that the intent of Congress was to subject the Department’s preferred number of individuals to the time limit. In fact, the NPRM 

fails to establish that Congress had any interest in subjecting a target number of 

individuals to the rule. Rather, the goal was to allow states to protect individuals 

in areas without a sufficient number of jobs, regardless of how many individuals 

276 

383 142 Congressional Record, H7904 (daily ed. July 18, 1996). 

that would be. We are unable to identify any statutory reference to a policy goal 

of protecting only a certain percentage of individuals subject to the rule. 

The legislative record does not reveal Congressional debate over the appropriate 

percentage of individuals subject to the rule. In fact, the Members of Congress introducing the proposed time limit emphasized that adequate protections were included 

to ensure that individuals were not cut off of SNAP if opportunities for work or 

workfare were not available. Representative Robert Ney, one of the authors, stated 

on the floor of the House of Representatives that his amendment ‘‘provides some 

safety; it provides a course of a safety net [sic], it has the ability to have waivers 

from the state department of human services.’’ 383 Representative John Kasich clarified that the key was that the time limit applied only in areas where jobs were 

available to those subject to the time limit—otherwise, the time limit would not 

apply. ‘‘It is only if you are able-bodied, if you are childless, and you live in an area 

where you are getting food stamps, and there are jobs available, then it applies.’’ 

The key issue, of course, is whether jobs are available for these individuals, as the 

statute requires. 

We address the serious concerns with the way in which the NPRM incorrectly interprets the standard that waivers are available in places with insufficient jobs for 

the individuals subject to the rule in Chapter 3. Here, we simply note that the authors of the original legislation did not have a targeted number of individuals they 

thought should be subject to the rule; nor did Congress establish, or even debate, 

a targeted percentage of individuals to be subject to the rule. Instead, the co-authors 

of the original legislation were careful to point out that there were adequate protections for all individuals if jobs were not available. Given this clear history, it is incumbent upon the Department to substantiate its claim that the legislative history 

somehow suggests that the current regulations must be changed because too many 

individuals live in waived areas. Without explaining the underlying claim, the rule 

leaves commenters with little ability to meaningfully respond. 

We would also note that the temporary nature of setting such a coverage goal 

strongly suggests such a goal is not intended or practical. As economic circumstances change, the ability of ABAWDs subject to the time limit to find work 

will change, meaning that at different points in the economic cycle, the portion of 

individuals subject to the rule who are able to find 20 hours of work per week will 

change significantly, as will the portion of individuals living in areas eligible for 

waivers under any set of criteria. And other factors, besides the existence of a waiver, affect an individual’s participation in SNAP, such as the accessibility of the application process, other eligibility rules and processes, and the availability of training opportunities for unemployed adults. 

B. Despite Claiming That General Unemployment Rates Are the Best Available 

Measure of Job Sufficiency for Low-Income Adults on SNAP, the Proposed Rule 

Fails to Support the Claim with Evidence 

The proposed rule asserts that low general unemployment rates indicate sufficient 

jobs are available for those subject to the time limit. But it offers no reason why 

a general unemployment rate of seven percent is a good proxy measure for establishing that there are sufficient jobs for the individuals subject to the rule. This lack 

of an explanation makes it difficult for interested parties to critique the Department’s conclusion that no waivers should be permitted below seven percent. In contrast, as discussed in Chapter 3, there is a deep body of research that shows unemployment rates are much higher for groups that make up SNAP’s ABAWD caseload. 

Current regulations allow waiver requests that demonstrate a recent local unemployment rate significantly above the national average but do not set a minimum 

unemployment rate. The NPRM fails to explain why the reasoning behind the current rule no longer applies, and why it believes another rulemaking process would 

result in a justifiable change. Indeed, for the most substantial proposed change— 

to prohibit waivers for areas with unemployment below seven percent—the NPRM 

seeks input for changing the number to six or ten percent but does not explain why 

those thresholds are of particular importance, aside from noting that a larger or 

smaller group of individuals might be protected at the different levels. It does not 

explicitly seek input on other levels, such as five or eight percent. The rule offers 

a very weak explanation, unsupported by research, for the seven percent that is proposed or the alternatives for which it seeks comment. Since interested stakeholders 

do not have adequate information to determine why the unemployment rate floor 

is set where it is, it is difficult to provide useful feedback on the appropriateness 

of the proposed threshold. In the rulemaking process, an agency that promulgates 

277 

384 U.S. Department of Agriculture, Food and Nutrition Service, ‘‘Guidance for States Seeking 

Waivers for Food Stamp Limits,’’ Dec. 3, 1996. 385 U.S. Department of Agriculture, Food and Nutrition Service, ‘‘Guidance for States Seeking 

Waivers for Food Stamp Limits,’’ Dec. 3, 1996. 386 66 Fed. Reg., No. 11, 4438, ‘‘Food Stamp Program: Personal Responsibility Provision of the 

Personal Responsibility and Work Opportunity Reconciliation Act of 1996,’’ January 17, 2001, 

p. 4463. 

a rule change needs to explain why the original rationale is no longer sufficient 

when proposing to change the rule. 

The Proposed Rule Makes Arbitrary Changes to Long-Standing Regulations That 

Were Initially Promulgated Based on Sound Reasons 

Until this proposed rule, FNS has always acknowledged that the statute requires 

several different ways for states to document a lack of sufficient jobs for the individuals subject to the time limit. In its original guidance, the Department noted, ‘‘[t]he 

statute recognizes that the unemployment rate alone is an imperfect measure of the 

employment prospects of individuals with little work history and diminished opportunities.’’ 384 It then proceeds to describe the use of Labor Surplus Areas (LSAs) as 

a reliable waiver criteria. However, without providing a reason or evidence that 

LSAs are not a useful measure, the proposed rule eliminates LSAs as a possible way 

of qualifying for a waiver. We are at a loss as to why a measure relied upon for 

so long by so many states is simply eliminated. 

Areas designated as LSAs by the Department of Labor have been eligible for 

waivers because in order to qualify as an LSA, an area must have sufficiently high 

unemployment (120 percent of the national average so long as the area rate is at 

least six percent). LSAs are recognized as weak labor markets. Federal, state, and 

local government use LSAs to target contracts and allocate employment-related assistance and training. LSAs provide a reasonable indicator that there is a lack of 

sufficient jobs for unemployed SNAP participants, who disproportionately struggle 

to overcome barriers to employment. 

To support the inclusion of LSAs as a way to demonstrate a lack of sufficient jobs 

for the unemployed adults subject to the rule, the original 1999 rulemaking process 

established that LSAs were a reasonable measure of labor market weakness and 

were based on sound and relevant data from a trusted source (the Bureau of Labor 

Statistics). The original 1996 guidance explained one reason why: 

Labor surplus areas are classified on the basis of civil jurisdictions rather 

than on a metropolitan area or labor market area basis. By classifying labor 

surplus areas in this way, specific localities with high unemployment rather 

than all civil jurisdictions within a metropolitan area, (not all of which may suffer from the same degree of unemployment) can be identified. This feature also 

makes the classification potentially useful to identify areas for which to seek 

waivers [emphasis added].385

The original rulemaking process emphasized the importance of relying on BLS 

data (much as the NPRM does). But the original rulemaking identified LSA status 

as a reliable indicator of insufficient jobs based on BLS data and as recent enough 

to be used to meet the waiver criteria. In fact, the preamble to the final rule noted 

that an LSA designation was reliable enough to allow for ‘‘immediate implementation of waivers for areas where the Employment and Training Administration, U.S. 

Department of Labor (ETA), has designated such areas as LSAs.’’ 386 In other words, 

the Department made a reasoned decision to allow states to immediately implement 

(before approval by FNS) any waiver based on an area’s designation as an LSA. The 

proposed rule both eliminates the LSA criteria and the immediate implementation 

of certain waivers without explaining why the current process is flawed or could be 

improved. 

The proposed rule drops LSAs but provides no explanation for why this change 

is needed; nor does it identify deficiencies in the current criteria (aside from determining that there should be a seven percent unemployment floor). Because we do 

not know what faults the Department now believes exist with the use of LSAs as 

credible indicator of a lack of sufficient jobs for the individuals subject to the time 

limit, we are unable to assess the validity of the claim. It is unclear what information the Department now has that invalidates its decision of more than 20 years 

ago—a decision the Department has followed and subscribed to until very recently. 

This prevents the public from providing relevant information that supports or refutes the reasons behind the proposed rule. 

278 

387Food and Nutrition Service, 2018 Explanatory Notes for the FY 2018 President’s Budget, 

pages 32–92 to 32–93 https://www.obpa.usda.gov/32fnsexnotes2018.pdf. 388 Emily Birnbaum and Julie Grace Brufke, ‘‘Trump Attacks Dems on farm bill’’, The Hill, 

September 13, 2018, https://thehill.com/homenews/administration/406561-trump-calls-outdems-for-opposing-farm-bill-over-work-requirements; Phillip Brasher, ‘‘Farm Bill Delayed, but 

Perdue signals administration support’’, Agripulse, December 3, 2019, https://www.agripulse.com/articles/11703-farm-bill-delayed-but-perdue-signals-administration-support. 389 Remarks by President Trump at Signing of H.R. 2, the Agriculture Improvement A[c]t of 

2018. https://www.whitehouse.gov/briefings-statements/remarks-president-trump-signing-h-r-2- 

agriculture-improvement-act-2018/. 

The Proposed Rule Attempts to Achieve Through Regulation a Policy That Congress 

Explicitly Rejected 

The Administration’s aim with this rule appears to be to do through rule-making 

what Congress rejected through legislation. The Trump Administration proposed restricting waivers from the time limit through legislation in its Fiscal Year 2018 

budget proposal and promoted exposing more people to the time limit throughout 

the 2018 Farm Bill process.387 In the budget, the Administration proposed restricting waivers to just areas with an average unemployment rate of ten percent. In that 

proposal, the Administration described current policy as, ‘‘States can request waivers from the ABAWD time limit that cover the entire state, or only parts of the state 

where unemployment is particularly high. States decide whether or not to request 

a time limit waiver, and generally make this assessment annually.’’ The proposed 

policy was described as, ‘‘This proposal limits ABAWD waivers to counties with an 

unemployment rate greater than ten percent averaged over 12 months.’’ While this 

proposed legislative policy would be stricter than the policy in the proposed rule, 

the actual near-term impact of a seven percent floor would be similar as there are 

very few counties in the country with average unemployment rates between seven 

and ten percent. 

Throughout the farm bill process, the President and Secretary Perdue were 

quoted in the press as saying that they were frustrated that Congress would not 

expose more individuals to the time limit or ‘‘work requirement.’’ 388 At the 2018 

Farm Bill signing ceremony, the President remarked that he wanted to implement 

policy counter to what Congress had decided. He said, ‘‘Therefore, I have directed 

Secretary Perdue to use his authority under the law to close work requirement loopholes in the food stamp program. Under this new rule, able-bodied adults without 

dependents will have to work, or look for work, in order to receive their food stamps. 

Today’s action will help Americans transition from welfare to gainful employment, 

strengthening families and uplifting communities. And that was a difficult thing to 

get done, but the farmers wanted it done; we all wanted it done. And I think, in 

the end, it’s going to make a lot of people very happy. It’s called ‘work rules.’ And 

Sonny is able, under this bill, to implement them through regulation.’’ 389 As noted, 

the farm bill legislation which the President refers to as ‘‘the bill’’, did not provide 

any new authority to the Secretary to change waiver policy. 

Congress expressly rejected the Administration’s proposal to substantially limit 

waivers in favor of the Senate approach, demonstrating intent to keep the current 

interpretation of the ‘‘insufficient jobs’’ criterion intact. Given that the agency did 

not put forward a coherent evidenced-based argument, we are left to believe that 

the goal of this rule is to defy Congressional intent and the agency’s own rulemaking to achieve a failed legislative effort. 

C. The Failure to Provide a Relevant Explanation or Supporting Data to Justify a 

Change in Current Regulations Occurs Repeatedly Throughout the Proposed 

Rule 

Under the NPRM, USDA would simply eliminate several existing criteria for requesting waivers because the Department claims they are ‘‘rarely used, sometimes 

subjective and not appropriate when more specific and robust data is available.’’ 

Under the proposed rule, waivers would not be available for areas with low and declining employment-to-population ratios, a lack of jobs in declining occupations or 

industries, or a lack of jobs as demonstrated by an academic study or other publication. The claim that the data available is not rigorous enough to support a request 

is not explained, given that states can submit a wide range of data to support a 

request. 

Especially concerning is the elimination of the employment-to-population (E:P) 

ratio standard. It is a well-established metric that has several features that make 

it preferable to general unemployment rates in assessing the health of the labor 

market. In some ways and under some circumstances, particularly in rural areas, 

the E:P ratio may be a better measure of the availability of sufficient jobs for lowincome adults participating in SNAP. The Department fails to establish that the E:P 

279 

390 Carol Boyd Leon, The employment-population ratio: its value in labor force analysis, Bureau of Labor Statistics, MONTHLY LABOR REVIEW, February 1981, pp. 36–45, https:// 

www.bls.gov/opub/mlr/1981/02/art4full.pdf. 391Fed. Reg., Vol. 83, No. 37, ‘‘Supplemental Nutrition Assistance Program: Requirements and 

Services for Able-Bodied Adults Without Dependents; Advance Notice of Proposed Rulemaking,’’ 

February 23, 2018, p. 8013. 

ratio relies on questionable or non-specific data. The proposed rule insists that 

sound data be used in supporting waiver requests, emphasizing that data from BLS 

is the standard to be used in requesting waivers. 

The employment-to-population ratio has not been widely used, but that, by itself, 

is not a sufficient reason to eliminate the option for states. As BLS itself notes, the 

ratio is ‘‘especially useful for evaluating demographic employment trends.’’ 390 In 

particular, it is important to rural areas, which often have less dynamic job creation 

and fewer resources available for the types of training activities that allow ABAWDs 

subject to the time limit to meet the 20 hour requirement. For example, South Dakota has waived both whole counties and reservations under the employment-topopulation criteria. Even in the last few years, other states, like New York and 

Maryland have waived counties. The option may not be frequently used, but it represents an important measure of labor market weaknesses in some areas and should 

remain available to states. The NPRM does not explain why frequency of request 

is a meaningful reason to keep or drop criteria. 

Finally, the Department offers no insight into whether it considers the employment-to-population ratio to be ‘‘sometimes subjective.’’ Under each of the listed concerns used to justify dropping the employment-to-population criterion (that it is 

rarely used, sometimes subjective, and not appropriate if more specific and robust 

data is available), the NPRM provides no explanation or information that allows the 

general public to respond to the proposal. 

D. The Public Input Resulting From Last Year’s Advanced Notice of Proposed Rulemaking Does Not Appear to Inform This Proposed Rule 

In March 2018, the Department issued an Advanced Notice of Proposed Rule 

Making (ANPRM), seeking public input on ‘‘potential regulatory changes or other 

changes that might better support states in accurately identifying ABAWDs subject 

to the time limit and providing meaningful opportunities for them to move towards 

self-sufficiency.’’ 391 Tens of thousands of comments were submitted, but the agency 

makes only a cursory reference to a subset of the comments and does not adequately 

recognize or summarize the public input. While the preamble of the NPRM contains 

a brief and inconclusive summary of the submitted comments, the Department provides no explanation for how the ANPRM informed the policy making process or 

whether the Department chose to ignore input provided through the public process. 

Potential commenters are at a loss for how the ANPRM informed the development 

of the proposed rule, what the public response to the ANPRM was, or how to engage 

without any information about the comments. 

The failure to respond to ANPRM raises serious concerns about the current rulemaking proposal. We are left to wonder whether the bulk of the comments sought, 

or did not seek, a change in policy. There is no summary of the reasons for supporting a change. Nor is there a summary of the input from commentators who opposed a change in policy, or a response from the agency as to why it concluded that 

these commentators were incorrect. 

The ANPRM asked numerous questions about helping ABAWDs gain work. But 

the NPRM only references the questions about waivers. This is deeply misleading 

as it suggests comments were focused only on that question. 

The failure to adequately respond to the ANPRM also raises concerns that the 

current rulemaking process will fail to take the comments on the NPRM into account as the Department decides whether to proceed with the current proposed rule 

or change or withdraw it. If the public’s input was ignored or outright dismissed 

in the previous process, why should the public have confidence that the NPRM will 

not yield the same result? 

E. Alternatives to the Proposed Rule Are Not Discussed 

Under the rulemaking process, USDA is obligated to explain why the particular 

policy is proposed and why alternative approaches are inadequate. Given that the 

agency estimates 755,000 people will lose benefits and provides no estimate for how 

many will gain employment, less harmful alternatives exist and the Department has 

an obligation to consider these alternatives. 

In establishing seven percent unemployment as a floor under which no area can 

qualify for a waiver, the Department claims this is ‘‘more suitable for achieving a 

more comprehensive application of work requirements so that ABAWDs in areas 

280 

392 NPRM, p. 984. 393The Regulatory Impact Analysis (RIA), which includes the detailed cost-benefit analysis 

and information about the methodology, is included in a separate online document here: https:// 

www.regulations.gov/document?D=FNS-2018-0004-6000, p. 4–7 and 18–31. The NPRM includes 

only a short summary of the analysis. Hereafter in citations we will refer to the Regulatory Impact Analysis as the ‘‘RIA.’’ 394 NPRM, p. 989; RIA, pp. 4, 26, 27. 

that have sufficient number of jobs have a greater level of engagement in work and 

work activities, including job training.’’ 392 No information is provided as to why current policies are not comprehensive and what the current level of engagement in 

work and work activities is, much less what a ‘‘greater level of engagement’’ would 

look like. This makes it difficult for commenters to provide input on these unsupported assertions. 

The claim that a seven percent floor strengthens the work requirement is repeated throughout the preamble. As discussed in detail [below], the NPRM fails to 

adequately support the proposed floor. Without knowing what research or data the 

Department relied upon to conclude that seven percent was the appropriate floor, 

the public is unable to directly comment on the validity of the Department’s action. 

The Department does seek input on setting the unemployment floor—at seven, 

six, or ten percent—but offers no explanation why six or ten percent are the two 

alternatives rather than, say, five or eight percent. Aside from a cursory mention 

of the natural rate of unemployment, no discussion or information is provided to inform the public’s comments. 

Other alternatives to grouping areas together also exist. For example, the proposed rule limits waiver requests that group sub-state areas together to those based 

entirely on BLS Labor Market Areas (LMAs). There are serious limitations to relying solely on LMAs as the basis of such waivers, as discussed in more detail in 

Chapter 5. LMAs rely on older data, use a narrow definition of a labor market area 

that does not reflect the challenges facing low-income SNAP participants, and do not 

account for other factors relevant to ABAWDs subject to a 3 month time limit—such 

as the availability of training programs. In fact, one of the key components of the 

current grouping policy—that states largely define the area of the waiver request— 

is largely eliminated with no explanation or evidentiary support. Other alternatives 

do exist, but the NPRM fails to provide any reason why these alternatives are not 

appropriate and why the proposed grouping change is the best available option. 

The proposed rule is based on insufficient reasons to change current regulations, 

fails to provide evidence supporting the change, and lacks any discussions of alternatives considered in developing the proposed rule. Given this lack of supporting information, the public has an insufficient opportunity to comment meaningfully on 

the proposed rule. 

Chapter 11. The Proposed Rule’s ‘‘Regulatory Impact Analysis’’ Highlights 

FNS’ Faulty Justification and Includes Numerous Unclear or Flawed 

Assumptions 

The Regulatory Impact Analysis (RIA) 393 that accompanies the proposed rule contradicts the Department’s justification for the proposed rule. The Department repeatedly asserts in the preamble that the proposed rule would ‘‘encourage more 

ABAWDs to engage in work’’ and would ‘‘promote self-sufficiency.’’ But the RIA finds 

instead that 755,000 individuals would be cut from SNAP in 2020 for ‘‘failure to engage meaningfully in work or work training,’’ 394 and it provides no evidence or estimates that other individuals would be induced to work because of the proposed 

changes or would experience any benefit from the changes. 

In addition, the methodology for deriving the impact of the proposed rule ignores 

available research evidence, uses imprecise terms, includes numerous unclear or inappropriate assumptions, and excludes all together any explanations for several 

other key assumptions. The information that is provided in the RIA is fundamentally flawed, imprecise, incomplete, and incoherent. 

The result is that the proposed rule does not provide the analytical or conceptual 

information needed to justify the policy change and to evaluate the proposed rule’s 

likely impacts. Because of the deficiencies in reasoning and analysis of the RIA, the 

proposed rule fails to answer basic questions related to the impact of the change 

and the people whom the proposed rule would affect, and so does not contain the 

information and data necessary to fully evaluate the proposed rule or to comment 

on key aspects on the Department’s justification for the rule. 

No agency could explain every nuance and assumption, but the RIA that accompanies the proposed changes in this NPRM is so deeply flawed that we cannot comprehend the basic reasoning behind it. Because individuals who wish to comment 

281 

395 NPRM, pp. 981, 982, 987. 396 NPRM, p. 989. 397 RIA, pp. 4, 26. 398 RIA, p. 28. 399 NPRM, p. 989. 400 NPRM, p. 990. 401 RIA, p. 28. 

on the changes cannot understand or follow the agency’s justification, this rulemaking and comment process is compromised. 

A. The RIA Does Not Provide Any Evidence to Support the Proposed Rule’s Stated 

Rationale 

The NPRM argues repeatedly that ‘‘the Department is confident that these 

changes would encourage more ABAWDs to engage in work or work activities,’’ 395

implying that, as a result of the changes proposed, individuals newly subject to 

SNAP’s 3 month time limit in areas no longer qualifying for waivers would be likely 

to work more, have higher earnings, or otherwise be better off. But the NPRM provides no evidence to support these assertions, and no estimates of any quantifiable 

benefits for any individuals resulting from the changes. The NPRM’s failure to justify the stated rationale is a serious deficiency and makes it impossible for commenters to assess the impact of the proposed rule or to comment on the Department’s justification. 

The RIA, which is included as supplementary materials accompanying the NPRM, 

contradicts the Department’s stated rationale. The analysis in the RIA provides that 

the only benefit of the rule is budgetary savings from lower SNAP benefits resulting 

from 755,000 individuals ‘‘not meeting the requirements for failure to engage meaningfully in work or work training.’’ 396 The RIA does not claim that any individuals 

would be induced to find work or have increased earnings as a result of the proposed rule. The RIA does provide a confusing assertion that a higher share of 

‘‘ABAWDs’’ would be working in 2020 (34 percent) than in 2016 (26 percent), and 

estimates the impact under a different scenario where that increase does not 

occur.397 According to the RIA, however, the assumed increase in employment (from 

26 percent with any earnings to 34 percent working at least 20 hours a week) is 

‘‘based on the projected decline in the unemployment rate’’ in the President’s 2019 

budget forecast, not on more work among low-income households because of the regulatory change. 

The loss of SNAP benefits as a result of fewer areas qualifying for waivers from 

the time limit is included in the RIA as a benefit because of the reduction in Federal 

spending, but the RIA does not quantify any benefits to individuals from the change. 

There is only a small mention in the RIA of the harm, or cost that might occur for 

low-income individuals who lose SNAP: 

To the extent that ABAWDs newly subject to the time limit are unable to find 

work or otherwise meet work requirements, and thus lose SNAP there may be 

increases in poverty and food insecurity for this group. However, those 

ABAWDs who become employed will likely see increased self-sufficiency and an 

overall improvement in their economic well-being. The Department believes that 

a number of those affected by strengthened work requirements are able to secure employment in a wide range of different industries.398 [Emphasis added.] 

Thus, the analysis included in the RIA asserts that the Department believes people are likely to get jobs because of the rule, but provides no evidence to support 

that belief and quantifies only the Federal budgetary savings from the estimated reduction in SNAP benefits associated with individuals’ ‘‘failure to engage meaningfully in work or work training.’’ 399 It further mentions, but does not quantify, the 

secondary effects on SNAP retailers from lower SNAP redemptions,400 and on community-based organizations (i.e., food banks and others that provide emergency assistance) from increased demand for food and services.401

Because the RIA and its cost-benefit analysis are lacking in internal logic or 

transparency, the public cannot see clearly how the Department arrived at its conclusions about the need for the proposed regulation or its impact. 

B. Available Research Evidence Contradicts the Articulated Aims of the Proposed 

Rule 

The research evidence that is available on the question of the effects of policies 

that take food assistance or other benefits away from individuals who don’t meet 

rigid work requirements is not mentioned in the RIA. This is a serious omission and 

constrains the public from being able to adequately assess and comment on the potential impacts of the proposed rule. 

282 

402Kristen F. Butcher and Diane Whitmore Schanzenbach, ‘‘Most Workers in Low-Wage Labor 

Market Work Substantial Hours, in Volatile Jobs,’’ Center on Budget and Policy Priorities, July 

24, 2018, https://www.cbpp.org/research/poverty-and-inequality/most-workers-in-low-wagelabor-market-work-substantial-hours-in. 403 Brynne Keith-Jennings and Vincent Palacios, ‘‘SNAP Helps Millions of Low-Wage Workers,’’ Center on Budget and Policy Priorities, May 10, 2017, https://www.cbpp.org/research/ 

food-assistance/snap-helps-millions-of-low-wage-workers. 404David Cooper, Lawrence Mishel, and Ben Zipperer, Economic Policy Institute, April 2018, 

https://www.epi.org/publication/bold-increases-in-the-minimum-wage-should-be-evaluated-forThe loss in benefits, and the related increase in poverty and hardship that results 

from policies that take away food assistance or other benefits from individuals who 

do not meet rigid work requirements is well-documented in the research. The research also finds very little gain in longer-term employment as a result of such policies. In other words, the research supports the findings of the RIA that many individuals would be cut off SNAP as a result of fewer areas qualifying for waivers from 

the time limit under the proposed rule, but does not support the overall stated purpose of the regulatory change. 

The proposed rule ignores strong research evidence from independent researchers 

that contradicts the stated justification for the proposed change. Below we discuss 

the available relevant research on the impact of taking benefits away from individuals who are unable to meet rigid work requirements. 

The NPRM Ignores Research That Finds That the Characteristics of the Low-Wage 

Labor Market Contribute to Periods of Unemployment 

The proposed rule implicitly assumes that taking away food assistance will cause 

people not currently working to get jobs. But this assumption ignores research evidence about the realities of the low-wage labor market that contribute to periods 

of unemployment and mischaracterizes the work patterns of many people who need 

and receive assistance. 

Features of the Labor Market Contribute to Periods of Unemployment 

The basic characteristics of low-wage jobs are well-documented: low-paid jobs 

often don’t last; low-wage industries that employ workers with limited education or 

work experience tend to expand and shrink their workforces frequently based on demand, resulting in part-time jobs that have unstable hours and high turnover; and 

low-paid workers often lack the health coverage, paid leave, and reliable child care 

that can help a worker keep her job. These realities help explain why many workers 

in low-wage jobs need assistance while they are working and when they are in between jobs. The nature of low-wage jobs can make it hard for a worker to meet rigid 

work requirements. 

Recent work by economists Kristen F. Butcher and Diane Whitmore 

Schanzenbach used the Census Bureau’s Current Population Survey to show that 

the occupations of SNAP or Medicaid recipients who work at least part of the year 

feature instability and low wages overall (not just for SNAP or Medicaid recipients). 

These occupations include personal care and home health aides, maids and housekeepers, dishwashers, food preparers, and laundry and dry cleaning workers. Looking at all workers in the ten occupations most prevalent among SNAP recipients, 

the researchers found that these workers faced more periods of joblessness and were 

less likely to be stably employed from year to year than better-paid workers in other 

occupations. The researchers conclude, ‘‘Together, these results suggest that it will 

be difficult for individuals who work and participate in benefit programs to meet 

proposed work requirements in the private sector alone. Although employment levels are high among many of these types of workers, employment volatility is also 

quite high. Much of this volatility reflects characteristics of these types of occupations and is not necessarily due to decisions made by the workers.’’ 402

Another study of the jobs that are common among SNAP participants found that, 

‘‘because SNAP participants work in many industries (such as retail and hospitality) 

and occupations (such as service and sales) where features such as involuntary parttime work and irregular scheduling are common, they may participate in SNAP to 

supplement their low incomes due to insufficient or fluctuating hours. Similarly, because workers often cycle in and out of these jobs, workers may participate in SNAP 

during periods of unemployment or underemployment.’’ 403

In addition, there is evidence that low-wage jobs have higher turnover and are 

far less likely to have access to paid sick leave or paid family leave. 

• According to a 2018 study by the Economic Policy Institute, ‘‘the monthly rate 

of churn into and out of employment for low-wage workers is roughly twice as 

high as it is for the typical worker in the middle of the wage distribution.’’ 404

283 

the-benefits-of-raising-low-wage-workers-total-earnings-critics-who-cite-claims-of-job-loss-areusing-a-distorted-frame/. 405 Bureau of Labor Statistics, ‘‘National Compensation Survey: Employee Benefits in the 

United States, March 2017,’’ Bulletin 2787, September 2017. 406 NPRM, p. 981. 407 ‘‘Perdue Reiterates Need to Restore Original Intent of SNAP: A Second Chance, Not a Way 

of Life,’’ Food and Nutrition Service, USDA, Press Release USDA 0025.19, February 28, 2019, 

https://www.fns.usda.gov/pressrelease/2019/usda-002519. 408For similar households with just childless adults, 46 percent were working in a typical 

month and 72 percent worked within a year before or after that month. https://www.cbpp.org/ 

unemployed-adults-without-children-who-need-help-buying-food-only-get-snap-for-three-months. 409 Brynne Keith-Jennings and Raheem Chaudhry, ‘‘Most Working-Age SNAP Participants 

Work, But Often in Unstable Jobs,’’ Center on Budget and Policy Priorities, March 15, 2018. 

• Data from the Bureau of Labor Statistics shows that low-wage workers are far 

less likely to have access to paid sick leave or paid family leave.405

The Rationale of the NPRM Ignores Research on The Work Patterns of 

People Who Are Low-Skilled, Low-Wage Workers Subject to The Time Limit 

The NPRM states that ‘‘The application of waivers on a more limited basis would 

encourage more ABAWDs to take steps towards self-sufficiency.’’ 406 Secretary of Agriculture Sonny Perdue on February 28, 2019 in testimony before the Senate Agriculture Committee defended the proposed rule, saying that ‘‘We think the purpose 

is to help people move to independency . . . . We should help people when they are 

down but that should not be interminably.’’ 407

The belief that unemployed adults who participate in SNAP are dependent on 

SNAP for long periods ignores research that finds that large numbers of recipients 

who are not working at a point in time have recently worked or will work soon. A 

CBPP analysis of SNAP recipients shows that in a typical month in mid-2012, some 

52 percent of adult recipients not receiving disability benefits were working, but 

that 74 percent worked in the year before or after that month.408

The analysis examined adults who weren’t receiving disability benefits and who 

participated in SNAP for at least a month in a period of almost 3.5 years. This allowed us to observe their work both while they participated in SNAP and in the 

months when they did not, and to observe employment among SNAP recipients over 

a longer period. 

The adults in the analysis worked the majority of the months in the analysis, but 

they were more likely to participate in SNAP in the months when they were out 

of work and their income was lowest. They participated in SNAP in about 44 percent of the months that they were working and in 62 percent of the months in which 

they were not working. This helps explain why an analysis that only looks at work 

in a single point-in-time month while people are receiving SNAP will show them 

working less than they do over time: many of them are workers who temporarily 

receive SNAP when they are between jobs.409

While these figures apply to all adults, not just those without children in the 

household, the research finding about the difference between point-in-time employment and employment over several years is still relevant and the NPRM does not 

address it. While individuals subject to the time limit may, in any given month, not 

have sufficient work hours to pass a rigid work test, many will be working (or working more hours) within a short time, with or without a work requirement. Moreover, 

when SNAP participants are working, it’s often unstable work with low wages that 

does not lead to self-sufficiency, contrary to the framing included in the NPRM. 

Research From the TANF Program Found That Employment Impacts Are Modest 

and Fade Over Time 

The rigorous random-assignment evaluations of programs that imposed work requirements on cash assistance (AFDC/TANF) recipients in the late 1990s contradicts the stated rationale for the proposed rule, but supports the finding from the 

RIA that under the proposed rule one would not expect to see increased employment 

or earnings. While these evaluations generally found modest, statistically significant 

increases in employment early on, the effects faded over time, and people with significant barriers to employment were not helped. In fact, many were hurt. 

• In Portland, Oregon, the site of the largest earnings impact among the evaluations, the share of recipients with stable employment (defined as being emVerDate Aug 31 2005 11:16 Jun 14, 2019 Jkt 041481 PO 00000 Frm 00289 Fmt 6621 Sfmt 6621 P:\DOCS\116-02\36188.TXT BRIAN
284 

410Gayle Hamilton, et al., ‘‘National Evaluation of Welfare-to-Work Strategies: How Effective 

Are Different Welfare-to-Work Approaches? Five-Year Adult and Child Impacts for Eleven Programs,’’ Manpower Demonstration Research Corporation, December 2001, Appendix Table C–6. 411 Ibid., Table C.1. 412Dan Bloom, Cynthia Miller, and Gilda Azurdia, ‘‘Results from the Personal Roads to Individual Development and Employment (PRIDE) Program in New York City,’’ MDRC, July 2007. 413 V. Joseph Hotz, Guido Imbens, and Jacob Klerman, ‘‘Evaluating the Differential Effects of 

Alternative Welfare-to-Work Training Components: A Reanalysis of the California GAIN Program,’’ Journal of Labor Economics, Volume 24 Number 3, 2006, pp. 521–566. 414Peter Germanis, ‘‘Who Killed Work Requirements for SNAP in the Farm Bill? Answer: 

Conservative Ideologues,’’ January 1, 2019, https://mlwiseman.com/wp-content/uploads/2019/ 

01/Farmbill.120118.pdf. 415 Rachel Garfield, Robin Rudowitz, and Anthony Damico, ‘‘Understanding the Intersection 

of Medicaid and Work,’’ Kaiser Family Foundation, January 5, 2018; MaryBeth Musumeci, Julia 

Foutz, and Rachel Garfield, ‘‘How Might Medicaid Adults with Disabilities Be Affected By Work 

Requirements in Section 1115 Waiver Programs?’’ Kaiser Family Foundation, January 26, 2018; 

Bauer, Schanzenbach, and Shambaugh; Keith-Jennings and Chaudhry. 416LaDonna Pavetti, Michelle K. Derr, and Heather Hesketh, ‘‘Review of Sanction Policies and 

Research Studies: Final Literature Review,’’ Mathematica Policy Research, March 10, 2003. 417Stephen Freedman, et al., ‘‘National Evaluation of Welfare-to-Work Strategies—Evaluating 

Alternative Welfare-to-Work Approaches: Two-Year Impacts for Eleven Programs,’’ Manpower 

ployed in 75 percent of the calendar quarters in years 3 through 5 after the 

pilot project began) rose only from 31.2 to 38.6 percent.410

• Within 5 years, employment among people subject to and not subject to work 

requirements was about the same in nearly all the programs evaluated.411

• Even when the programs provided specially tailored services, the vast majority 

of participants facing significant employment barriers did not find employment 

as a result of work requirements.412

• The California GAIN program, the so-called ‘‘Riverside Miracle,’’ which focused 

on getting recipients into any job as quickly as possible, was outperformed in 

the long run by programs that focused on increasing participants’ skills and 

building their human capital.413

One TANF expert researcher commented on the House Agriculture Committee’s 

work requirement proposals from the 2014 Farm Bill, which would have expanded 

the existing approach for SNAP for childless adults to adults with children, that, 

‘‘[t]here is no credible evidence to suggest that the specific work requirements developed by the House Agriculture Committee would ‘work.’ In fact, they are not likely 

to do much in the way of promoting employment and could push millions of families/ 

individuals deeper into poverty.’’ 414

On balance, as we discuss in more detail in Chapter 6, this rigorous research supports the findings of the RIA that many people lose benefits when required to comply with work requirements, but contradicts the stated purpose of the proposed rule 

to increase self-sufficiency. 

Strong Evidence That Many Subject to the Time Limit Face Employment Barriers 

and Would Lose Needed Help 

Based on the TANF experience from the 1990s, as well as the existing experience 

with the time limit in SNAP and the early experience from Arkansas (the only state 

so far to terminate Medicaid for individuals who fail to document that they are 

meeting Medicaid work requirements), many people subject to work requirements 

would lose benefits, and poverty and hardship would increase. This, again, is consistent with the analysis in the RIA, but not with the justification for the proposed 

rule. 

• Research shows that many of the people who would be newly subject to the time 

limit have circumstances that may limit the amount or kind of work that they 

can do. A large share face physical or mental health conditions or a cognitive 

impairment that would be difficult for state agencies to identify or for individuals to obtain paperwork to prove.415

• Research shows that many TANF recipients who lost financial assistance due 

to work requirements had serious barriers to employment. They were likelier 

than other recipients to have physical or mental health issues, have substance 

use disorders, be victims of domestic violence, have low education and skill levels, have prior criminal justice records, or lack affordable child care.416

• The rigorous experiments from the 1990s that required cash assistance recipients to participate in work-related activities found that the resulting loss in 

benefits raised ‘‘deep poverty’’ rates (the share of households with income below 

1⁄2 the poverty line).417 Similar results were found with careful non-experiVerDate Aug 31 2005 11:16 Jun 14, 2019 Jkt 041481 PO 00000 Frm 00290 Fmt 6621 Sfmt 6621 P:\DOCS\116-02\36188.TXT BRIAN
285 

Demonstration Research Corporation, June 2000; Pavetti, Derr, and Hesketh; Marianne Bitler, 

Hilary Hoynes, and Jonah Gelbach, ‘‘What Mean Impacts Miss: Distributional Effects of Welfare 

Reform Experiments,’’ American Economic Review, Volume 96, Number 4, 2006, pp. 988–1012. 418 Ariel Kalil, Kristin Seefeldt, and Hui-chen Wang, ‘‘Sanctions and Material Hardship under 

TANF,’’ Social Service Review, December 2002, pp. 642–662; Melissa Ford Shah, et al., ‘‘Predicting Homelessness among Low-Income Parents on TANF,’’ Washington State Department of 

Social and Health Services, August 2015, https://www.dshs.wa.gov/sites/default/files/SESA/ 

rda/documents/research-11-224.pdf; Andrew Cherlin, et al., ‘‘Sanctions and Case Closings for 

Noncompliance: Who Is Affected and Why,’’ Johns Hopkins University, Policy Brief 01–1, 2001. 419Gene Falk, ‘‘Temporary Assistance for Needy Families (TANF): Size of the Population Eligible for and Receiving Cash Assistance,’’ CRS Report No. R44724, Congressional Research Service, Washington, D.C., January 3, 2017. 420 Ron Haskins, ‘‘Welfare Reform at 20: Work Still Works,’’ Journal of Policy and Management 35(1), 2016, 223–224; Robert A. Moffitt, ‘‘The Deserving Poor, the Family, and the U.S. 

Welfare System,’’ Demography 52(3), 2015, 729–749; Hilary W. Hoynes and Diane W. 

Schanzenbach, ‘‘Safety Net Investments in Children,’’ March 8, 2018, Brookings BPEA Article, 

https://www.brookings.edu/bpea-articles/safety-net-investments-in-children/; James P. Ziliak, 

‘‘Temporary Assistance for Needy Families,’’ 2015 NBER Working Paper 21038; Kristin S. 

Seefeldt and Heather Sandstrom, ‘‘When There Is No Welfare: The Income Packaging Strategies 

of Mothers Without Earnings or Cash Assistance Following an Economic Downturn,’’ 2015. Russell Sage Foundation Journal of the Social Sciences 1(1), 139–158; H. Luke Shaefer, Kathryn 

Edin, and Elizabeth Talbert, ‘‘Understanding the Dynamics of $2-a-Day Poverty in the United 

States.’’ (2015) Russell Sage Foundation Journal of the Social Sciences 1(1), 120–138; Christina 

Paxson and Jane Waldfogel, ‘‘Welfare Reforms, Family Resources, and Child Maltreatment,’’ 

Journal of Policy Analysis and Management 22(1), 2003, 85–113. 421Sanford F. Schram, et al., ‘‘Deciding to Discipline: Race, Choice, and Punishment on the 

Frontlines of Welfare Reform,’’ American Sociological Review, January 2009; Kalil, et al.; Richard C. Fording, Joe Soss, and Sanford F. Schram, ‘‘Devolution, Discretion, and the Effect of 

Local Political Values on TANF Sanctioning,’’ Social Service Review, June 2007, pp. 285–316; 

Chi-Fang Wu, Maria Cancian, and Daniel R. Meyers, ‘‘Sanction Policies and Outcomes in Wisconsin,’’ Focus, Volume 23, Number 1, Winter 2004, https://www.irp.wisc.edu/publications/ 

focus/pdfs/foc231f.pdf; Pavetti 2004. 422 Rachel Garfield, Robin Rudowitz, and MaryBeth Musumeci, ‘‘Implications of a Medicaid 

Work Requirement: National Estimates of Potential Coverage Losses,’’ Kaiser Family Foundation, June 27, 2018; Nader S. Kabbani and Parke E. Wilde, ‘‘Short Recertification Periods in 

the U.S. Food Stamp Program,’’ Journal of Human Resources, Volume 38, 2003; David Ribar, 

Marilyn Edelhoch, and Qiduan Liu, ‘‘Watching the Clocks: The Role of Food Stamp Recertification and TANF Time Limits in Caseload Dynamics,’’ Journal of Human Resources, Volume 

43, Number 1, 2008, pp. 208–238; Mark Edwards, et al., ‘‘The Great Recession and SNAP Caseloads: A Tale of Two States,’’ Journal of Poverty, Volume 20 Issue 3, December 11, 2015; Colin 

Gray, ‘‘Why Leave Benefits on the Table? Evidence from SNAP,’’ Upjohn Institute Working 

Paper 18–288, May 21, 2018; Food and Nutrition Service, U.S. Department of Agriculture, ‘‘Understanding the Rates, Causes, and Costs of Churning in the Supplemental Nutrition Assistance 

Program (SNAP),’’ November 2014. 

mental analyses of leaver studies and household survey data. Moreover, studies 

of TANF recipients whose assistance was taken away found that they were 

likelier to experience serious hardship, such as seeing their utilities shut off, becoming homeless, or lacking adequate food.418 In line with these findings, numerous scholars using a variety of data and methods have concluded that cash 

assistance has weakened as a guard against deep poverty under TANF,419 and 

that some families are worse off as a result.420

• Research has shown that African American TANF recipients are far likelier to 

have their benefits taken away than white recipients.421 Caseworkers’ decisions 

about when to impose a sanction involve some discretion; one study, using fictitious case examples, showed that caseworkers were likelier to sanction African 

American recipients than white recipients. Recipients of color may also be 

likelier to be sanctioned because they face greater challenges in the labor market, including discrimination. 

• Evidence from SNAP and Medicaid shows that administrative hurdles can lead 

people to lose assistance even when they are working or may qualify for an exemption, because they do not understand or cannot comply with the requirement or because the state agency fails to properly process the paperwork.422

• Recent evidence from Arkansas’s implementation of work requirements for Medicaid is sobering. Arkansas is taking Medicaid coverage away from certain adult 

beneficiaries who fail to report at least 80 hours of work or work-related activities per month for 3 months. More than 18,000 Arkansans have lost coverage 

after just 7 months of implementation, and thousands more are at risk over the 

coming months. Data from the state show that a very small share of those required to report hours of participation (many beneficiaries are exempt from the 

286 

423 Jennifer Wagner, ‘‘Commentary: As Predicted, Arkansas’ Medicaid Waiver Is Taking Coverage Away From Eligible People,’’ Center on Budget and Policy Priorities, updated March 12, 

2019, https://www.cbpp.org/health/commentary-as-predicted-arkansas-medicaid-waiver-is-taking-coverage-away-from-eligible-people. 424Katharine G. Abraham, et al., ‘‘The Consequences of Long-term Unemployment: Evidence 

from Linked Survey and Administrative Data,’’ National Bureau of Economic Research, Working 

Paper 22665, September 2016, http://www.nber.org/papers/w22665. The citation appears on p. 

3 of the RIA. 425Ohio Association of Food Banks, ‘‘Franklin County Comprehensive Report on Able-Bodied 

Adults Without Dependents, 2014–2015,’’ October 14, 2015, p. 15, http:// 

admin.ohiofoodbanks.org/uploads/news/ABAWD_Report_2014-2015-v3.pdf. 

reporting requirement) have reported their hours, with very few successfully 

navigating the exemption and ‘‘good cause’’ processes.423

The RIA Cites Only One Study, Which Does Not Support the Proposed Rule 

As mentioned, the NPRM cites no research to support that the proposed rule 

would achieve its purported goal: i.e., that taking food assistance away from certain 

low-income childless adults would encourage more self-sufficiency and employment. 

The one study referenced in the entire RIA document instead examines the relationship between the duration of unemployment and future employment and earnings.424 The study finds that long-term unemployment has a negative effect on the 

likelihood of future employment and that the fact that someone experiences longterm unemployment is the main reason (as opposed to inherent characteristics of 

individuals who experience long-term unemployment.) Strangely, the study offers 

little support for the NPRM and raises important cautionary notes suggesting that 

the proposed rule would worsen, not improve, outcomes for the targeted population. 

• The one study cited in the RIA does not support the proposed rule. The 

RIA suggests that because longer unemployment spells are associated with a 

lower likelihood of future employment, the proposed rule is justified. But the 

study does not mention SNAP and does not address whether taking food assistance away from low-income individuals would either decrease unemployment 

spells or directly increase the likelihood of future employment. In fact, it is difficult to understand what connection could be made. The RIA estimates that 

755,000 individuals would lose SNAP under the proposed rule, but provides no 

estimate for increased employment. Much of the research in this area shows 

that those individuals will face increased hardship and may have a more difficult time finding work. 

• The population studied is not the population subject to the SNAP policy. The study cited looked at long-term bouts of unemployment by looking at 

a sample of all workers in state unemployment insurance systems. But the 

childless adult population subject to the SNAP time limit is a distinct group 

that includes many individuals not included in the study group because many 

adults who participate in SNAP do not receive unemployment compensation, 

even if they are working or had worked. A study of ABAWDs subject to the time 

limit in Ohio found that nearly 80 percent had never been eligible for unemployment benefits.425 More importantly, as discussed in detail elsewhere in these 

comments, other research shows that most childless adults who receive SNAP 

work when they can find employment. Based on Census Bureau SIPP data, 

about 75 percent of SNAP households with a childless, working-age adults 

worked in the year before or after receiving SNAP. Many of these individuals 

would not be in the pool of adults considered long-term unemployed in the 

study, so the conclusions drawn in the cited study do not directly apply to 

ABAWDs as a group and do not justify a policy change directed at them. 

• Finally, the study’s findings suggest that support for individuals to improve their skills or participate in work programs would be a better approach. The study finds that ‘‘the longer-term unemployed experience substantially worse employment and earnings losses than the short term unemployed.’’ 

The methodology, ‘‘allows us to rule out the ‘bad apple’ explanation for why the 

long-term unemployed fare worse . . . and [is] consistent with duration dependence as the explanation for their poorer outcomes.’’ This means that it is not 

the characteristics of the individuals that cause them to be long-term unemployed that are behind the results, but rather the fact of their long-term unemployment. So, if FNS were serious about wanting to help improve the longerterm outcomes for individuals who experience long-term unemployment, it 

would focus on helping to improve their education and skills or providing slots 

in work experience programs that allow them to demonstrate their desire to 

work, rather than cut their food assistance. 

287 

426Dottie Rosenbaum and Ed Bolen, ‘‘SNAP Reports Present Misleading Findings on Impact 

of Three-Month Time Limit,’’ Center on Budget and Policy Priorities, December 14, 2016; Tazra 

Mitchell, LaDonna Pavetti, and Yixuan Huang, ‘‘Study Praising Kansas’ Harsh TANF Work 

Penalties Is Fundamentally Flawed,’’ Center on Budget and Policy Priorities, updated February 

20, 2018. 427See Jonathan Ingram and Nic Horton, ‘‘The Power of Work, How Kansas’ Welfare Reform 

is Lifting Americans Out of Poverty,’’ The Foundation for Government Accountability, February 

16, 2016, https://thefga.org/wp-content/uploads/2016/02/Kansas-study-paper.pdf; Maine Office of Policy and Management, ‘‘Preliminary analysis of work requirement policy on the wage 

and employment experiences of ABAWDs in Maine,’’ April 19, 2016, http://www.maine.gov/ 

economist/opm/pub/ABAWD_analysis_final.pdf; and accompanying Maine Department of 

Health and Human Services May 11, 2016 press release and other related materials. 

C. Reports That Purport to Find Positive Effects From the Time Limit Are Deeply 

Flawed 

The only studies that claim to find substantial positive impacts when low-income 

individuals are faced with losing food assistance or other benefits if they do not 

meet rigid work requirements are deeply flawed. FNS does not cite this research 

either, but we include here some discussion of why FNS should not rely on these 

kinds of assertions in any future policy development. The faulty results come from 

the researchers making causal claims without a random-assignment design (or other 

analytically sound comparison-group methods), ignoring program participants’ work 

experience prior to receiving assistance, and excluding the impact on households of 

losing benefits.426 Below we explain how two such reports, citing data from Kansas 

and Maine, have inaccurately touted the alleged success of reimposing a 3 month 

time limit on SNAP participation for childless adults.427

When the recession decimated the labor market and unemployment spiked, most 

states, including Kansas and Maine, requested the time limit be waived statewide. 

Kansas reimposed the time limit statewide beginning in October 2013 and Maine 

reinstated the time limit statewide in October 2014, even though both states qualified for a statewide waiver at the time the time limit returned. 

In both states total SNAP caseloads already were declining, but they dropped significantly 4 months after the time limit was put in place, as Figure 11.1 shows. 

Data from Kansas and Maine that are limited to the childless adults who were potentially subject to the time limit show that SNAP participation fell among that 

group by 70 to 80 percent after the time limit returned. 

Figure 11.1 

States Implementing SNAP Time Limit Experienced Sudden Drops in SNAP 

Participation 

Kansas 

SNAP Participants (in thousands) 


11602071.eps
288 

428Peter Germanis has also written extensively on the methodological shortcomings of these 

types of studies. Peter Germanis, ‘‘How Do the Foundation for Government Accountability’s 

Evaluations of Welfare Reform Measure Up? A Report Card (Hint: The FGA Fails),’’ June 24, 

2018, https://mlwiseman.com/wp-content/uploads/2016/05/Evaluating-Welfare-Reform.pdf. 

Maine 

SNAP Participants (in thousands) 

Source: Agriculture Department SNAP participation data. 

The reports assert that, as a result of the SNAP time limit, work rates and wages 

have increased dramatically and the individuals subject to the time limit are better 

off. The reports, however, misrepresent or omit data and, as a result, make claims 

about the impact of the time limit on work and earnings that the facts do not support.428 The analyses also rest on faulty assumptions about why some childless 

adults receiving SNAP are not working. 

The reports’ three largest problems are: 

• They do not take into account that many SNAP recipients already 

work, or would work soon even without the time limit. The studies attribute rising work rates and earnings to the return of the time limit even 

though most, if not all, of the changes would have happened without it. The authors fail to acknowledge that many SNAP recipients who are subject to the 

time limit were working already, or would soon be working, and as a result, 

their work rates and wages would likely have risen without the time limit. They 

make claims that can only be identified through a rigorous evaluation that isolates the impacts of the time limit from what would have happened without it 

(see box below). 

• They do not consider the potentially severe impact of the time limit on 

those cut off SNAP. The studies fail to discuss the circumstances of the individuals who are subject to the time limit and the consequences for increased 

hardship and food insecurity when they lose SNAP benefits. Without addressing 

this side of the equation, the studies misrepresent the effect of reinstating the 

time limit on the well-being of those cut off SNAP. Their figures on the average 

income of those cut off SNAP are highly misleading because they do not include 

the loss of SNAP benefits. They do not discuss or attempt to assess what happens to individuals who lose their food assistance and are unable to find employment, who are a large share of those cut off. 

• They do not adequately consider the likely explanations for why childless SNAP participants may not work. The authors advance the theory that 

individuals are avoiding work and remaining in poverty in order to qualify for 

modest SNAP benefits of only about $5 a day. But research and experience in 

states with the time limit in effect offer evidence of alternative explanations. 

Many such individuals do work when they can, but they often face significant 


11602072.eps
289 

429 Ingram and Horton, op. cit., p. 2. 

barriers to work, such as low education and skills or physical or mental health 

issues. 

A careful look at the data presented in the reports, taking these factors into account, strongly suggests that not much changed related to work and earnings when 

the time limit took effect, but the time limit did cause thousands of the states’ poorest residents to lose essential SNAP benefits. 

Conventional Evidence-Based Research Uses a ‘‘Comparison Group’’ 

One of the central tenets of sound, evidence-based research is the need to 

have a ‘‘comparison group’’ so that the results can properly account for what 

would have happened in the absence of a change. 

For example, consider researchers who are testing the efficacy of a new medicine designed to speed recovery from the common cold. The researchers would 

need to know how fast people would have gotten better without the medicine. 

Without a comparison group there would be no way to know what to make of 

results that showed, for example, that 30 percent were better after 2 days and 

85 percent were better after 5 days. Many, perhaps all, of these people would 

have gotten better without the medicine. 

The gold standard for comparison groups is ‘‘random assignment,’’ an experimental approach where people who are otherwise the same are randomly assigned to different ‘‘treatment’’ groups and the effects of the change are measured on each group so the study can isolate the effect of the ‘‘treatment.’’ These 

types of studies are expensive, though some are underway in SNAP, funded by 

the 2014 Farm Bill. 

In the case of low-income childless adults, two important factors are critical 

for interpreting the information in the Kansas and Maine reports. First, many 

low-skill, low-wage workers do work, but they work in high-turnover jobs with 

low job security and often experience sporadic employment. SNAP acts as a 

safety net, providing assistance during periods of unemployment or when work 

hours are cut. It is common for SNAP recipients to have higher employment 

and wages in the future. Second, both Kansas’ and Maine’s economies were improving between 2013 and 2015, the period in which the two states implemented the time limit and purport to measure the results. Without controlling 

for these factors, it is difficult to isolate the effects of the time limit on employment. 

The authors of the reports for Kansas and Maine could have established less 

complicated and less costly alternative ‘‘comparison groups’’ by conducting the 

same analysis in the year before the cutoff to observe the work rates and earnings for similar SNAP recipients during a period when the time limit was not 

in effect. Such an approach would not have been perfect—it would be impossible to take the differences in the labor market and all other factors into account—but it would have been a more informative comparison than these reports provide. 

Reports Don’t Acknowledge That Many SNAP Recipients Subject to the Time Limit 

Already Work 

The studies from Kansas and Maine assert that reimposition of the time limit resulted in higher work rates and earnings for individuals who lost SNAP benefits 

after exhausting 3 months of eligibility. 

• For Kansas, the authors claim, ‘‘These reforms immediately freed nearly 13,000 

Kansans from welfare on December 31, 2013. Nearly 60 percent of those leaving 

food stamps found employment within 12 months and their incomes rose by an 

average of 127 percent per year.’’ 429

• For Maine, the Department of Health and Human Services’ press release reported that among the individuals whose SNAP was cut off, ‘‘Incomes rose 114 

percent within a year of leaving the program,’’ and ‘‘nearly 1⁄2 (48%) worked at 

least one quarter in 2015.’’ 

290 

430 In Kansas, where the time limit went into effect in October 2013, the overall unemployment rate fell from 5.3 percent in 2013 to 4.6 percent in 2014 and 4.2 percent in 2015. In Maine, 

where the time limit was reimposed 1 year later, the unemployment rate fell from 5.6 percent 

in calendar year 2014 to 4.4 percent in calendar year 2015. For SNAP recipients, especially 

those with the lowest education and skills, employment opportunities are highly sensitive to economic conditions and the availability of jobs. See Hilary Hoynes, Douglas Miller, and Jessamyn 

Schaller, ‘‘Who Suffers During Recessions?’’ NBER Working Paper No. 17591, March 2012, 

http://www.nber.org/papers/w17951.pdf. 431 CBPP calculates that almost 40 percent of the people who left the program on December 

31, 2013 worked in the two quarters just before the cutoff based on data on average wages per 

person from table 8 of the Kansas report. (The same calculation is used to estimate the shares 

working in the later quarters as well.) Instead of reporting these accurate data, the authors 

misleadingly report lower rates from national data sources as though they applied to the Kansas 

group. See p. 6: ‘‘Currently few able-bodied adults receiving food stamps actually work. . . . In 

2013 just 1⁄4 of childless adult households receiving food stamps had any earned income. . . . 

An analysis of food stamp recipients conducted when work requirements first went into effect 

found that fewer than five percent of all able-bodied childless adults on the program were meeting those requirements.’’ This latter five percent is extremely misleading because it excludes a 

large number of individuals who were working more than 30 hours a week as ‘‘exempt’’ from 

the time limit. If the authors included the share of non-disabled childless adults who were working, the figure would be larger. 

These reports, however, dramatically overstate the increase in work rates and 

wages that resulted from the reimposition of the time limit because many of the 

SNAP recipients affected were working, or would have started working anyway, albeit mostly in low-wage jobs with high turnover. Moreover, both states reimposed 

the time limit when their unemployment rates were dropping and unemployed individuals were somewhat more likely to be able to find work or higher wages as a 

result.430

Kansas Report Misrepresents Several Key Indicators 

The authors of the Kansas report overstate the degree to which work rates increased after the time limit and misrepresent the effect of the time limit on numerous outcomes for SNAP recipients while they are receiving SNAP. 

Work Rates Were Essentially Unchanged Before and After the Time Limit 

Returned 

The Kansas authors claim that ‘‘nearly 60 percent of those leaving [SNAP after 

the 3 month time limit went into effect] found employment within 12 months.’’ (The 

authors’ estimate of 60 percent is the share who had ever worked in any quarter 

of 2014.) The claim implies that the policy change reimposing the time limit was 

the reason that these people found work, but it’s misleading, as explained below. 

However, work rates before and after the time limit were very similar, as Figure 

11.2 shows. Almost 40 percent of those whose SNAP was cut off already worked in 

each of the last two quarters before the time limit returned (the third and fourth 

quarters of 2013).431 The share working each quarter in the year after the time 

limit was implemented rose slightly, to just over 40 percent. This modest increase 

could be explained by two factors: (1) low-wage workers are more likely to apply for 

and participate in SNAP when they lose a job or their incomes drop, so they often 

experience improvements in the future as their employment situation improves; and 

(2) Kansas’ economy was improving during 2014, so a slightly larger share of recipients may have been able to find jobs or higher pay. The time limit does not appear 

to have dramatically affected work rates for the group subject to it. 

291 

432 Ingram and Horton, op. cit., p. 8. 

Figure 11.2 

Kansas Work Rates Nearly the Same Before and After Time Limit 

Share of non-disabled childless adults cut off SNAP who earned wages in each quarter (Q) of a calendar year 

Note: CBPP derived the share with wages from information on average 

quarterly wages among those cut off SNAP from table 8 of Ingram and Horton. 

Source: Jonathan Ingram and Nic Horton, ‘‘The Power of Work, How 

Kansas’ Welfare Reform is Lifting Americans Out of Poverty.’’ The Foundation for Government Accountability. February 16, 20106; Table 8. 

The authors, however, reached the opposite conclusion—that work rates grew significantly after the time limit returned. Instead of comparing the average work 

rates in each quarter for this population before and after the policy change, they 

report the share of individuals whose SNAP was ended after December 2013 who 

ever worked in a quarter over the following year. This captures typical movement 

in and out of the labor force—given that this group tends to work in high-turnover 

jobs, in any quarter some people lose jobs and some get new jobs, so the share that 

ever worked increases—rather than an isolated impact of the policy change. The 

trends in the share who ever worked likely followed a very similar pattern in earlier 

years when the time limit was not in effect (though the authors do not present such 

data). As discussed below, other research about labor force participation among 

childless adults who receive SNAP finds work rates over time similar to those in 

the Kansas report. 

Improvements for SNAP Recipients Reflect SNAP Caseload Changes, Not Improved 

Circumstances 

The Kansas report presents highly misleading information about other changes 

among individuals subject to the time limit who receive SNAP. For example: 

[S]ince restoring work requirements, the employment rate among able-bodied 

adults on food stamps has doubled. As a result their incomes have more than 

doubled on average, they are spending less time on welfare, and the need for 

assistance has significantly declined.432

These claims, which the report makes across a range of measures, are misleading 

because the childless adults who remained as SNAP participants after the time 

limit went into effect were significantly different from those who participated before 

because of the policy change. The state cut off SNAP those participants who were 

not working at least 20 hours a week, so the work rates, average earnings, and 

other characteristics of those who remained SNAP participants after the return of 

the time limit were better, not because those individuals became better off, but because they were better off to begin with and were the only ones still eligible for and 

participating in SNAP. 


11602073.eps
292 

433The drop in the number of childless adults who worked at least 20 hours a week and received SNAP could have occurred because those individuals who qualified for SNAP (because 

they were working at least 20 hours a week) had recently been cut off SNAP (at a time when 

they were not working at least 20 hours a week) and did not know they would be eligible if 

they reapplied. 434 Ingram and Horton, op. cit., p. 9. 

Those who may still participate in SNAP are more likely to have earnings and, 

as a result, lower SNAP benefits and appear better off on a range of other characteristics. In fact, the number of childless adult SNAP recipients working at least 20 

hours a week, and thus the only non-exempt childless adult SNAP recipients eligible 

for the program, dropped modestly in the year after the time limit took effect.433

As an example of this misleading representation, consider the authors’ assertion 

that, ‘‘[p]rior to restoring work requirements, just 21 percent of childless adults on 

food stamps were working at all. Two-fifths were working less than 20 hours per 

week. But since work requirements have gone back into effect, that employment 

rate has risen to nearly 43 percent.’’ 434 The change was driven by a drop in the 

number of SNAP recipients who are childless adults subject to the time limit, not 

an increase in the number of recipients who are working. The number of such SNAP 

recipients who were working fell by more than 40 percent (from 6,300 to 3,600), as 

those who were working less than 20 hours a week were cut off, while the total 

number of non-disabled childless adults receiving SNAP dropped by more than 70 

percent (from almost 30,000 to 8,500). (See Figure 11.3.) 

Figure 11.3 

Kansas SNAP Benefit Cutoff Did Not Boost Work 

Non-disabled childless adult SNAP participants before and after January 2014 cutoff of those not working 20+ hours per week 

Number of such SNAP participants who worked fell . . . 


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293 

. . . but the work rate rose only because there were fewer such SNAP participants 

overall 

Source: Jonathan Ingram and Nic Horton, ‘‘The Power of Work, How 

Kansas’ Welfare Reform is Lifting Americans Out of Poverty.’’ The Foundation for Government Accountability. February 16, 20106; Tables 1–3. 

Maine Also Inappropriately Attributes Changes to the Policy Change That Likely 

Would Have Occurred Anyway 

Maine’s data on work rates and wages among individuals who lost SNAP are 

similar in magnitude to Kansas, and, as in the Kansas report, the authors of the 

Maine report and the accompanying materials from the state’s Department of 

Health and Human Services overstate the impact of the time limit by failing to take 

into account the fact that changes would have occurred even without it. 

As Figure 11.4 shows, before the reimposition of the time limit in October 2014, 

about 30 percent of the childless adults whose SNAP was cut off were working. That 

proportion peaked in the months after the time limit went back into effect at 36 

percent in the third quarter (the summer, a time when employment in Maine tends 

to be higher). But, though the report includes these quarterly rates, like for Kansas, 

the Maine report and accompanying materials emphasize a different figure: that 48 

percent had wages some time in 2015 and 58 percent had wages at some time ever 

in 2014 or 2015. But again, like for Kansas, the higher numbers count any time 

anyone had worked in any quarter, and thus largely reflect employment instability 

at a time that the state’s economy was improving, rather than a change that could 

be attributed to the reimposition of the time limit. 


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294 

435 Elizabeth M. Dagata, ‘‘Assessing the Self-Sufficiency of Food Stamp Leavers,’’ Economic 

Research Service, USDA, September 2002, https://www.ers.usda.gov/publications/pub-details/ 

?pubid=46645, a summary of in-depth studies in Arizona, Illinois, Iowa, and South Carolina. 

These studies include people who leave SNAP because of the 3 month time limit or for other 

reasons, for example, because they found a job or mistakenly believe they are no longer eligible. 436 Robert Rector, Rachel Sheffield, and Kevin D. Dayaratna, ‘‘Maine Food Stamp Work Requirement Cuts Non-Parent Caseload by 80 percent,’’ The Heritage Foundation, Backgrounder 

No. 3091, February 8, 2016, http://www.heritage.org/research/reports/2016/02/maine-foodstamp-work-requirement-cuts-non-parent-caseload-by-80-percent. 

Figure 11.4 

Maine Work Rates Nearly the Same Before and After Time Limit 

Share of non-disabled childless adults cut off SNAP who earned wages in each quarter (Q) of a calendar year 

Source: Maine Office of Policy Management, ‘‘Preliminary analysis of 

work requirement policy on the wage and employment experiences of 

ABAWDs in Maine of Health and Human Services,’’ April 19, 2016; figure 

1. 

No Consideration of the Well-Being of Those Cut Off or the Support SNAP Provides 

The one-sided pictures in these reports fail to discuss the well-being of the individuals whose SNAP benefits were cut off. But research suggests that many childless adults who lose SNAP as a result of the time limit continue to struggle after 

losing SNAP, in contrast to the reports’ portrayals of circumstances for recipients 

who lost benefits. The most comprehensive assessment of former SNAP recipients 

in four states in the early 2000s suggests that their life circumstances are quite difficult. A significant minority don’t find work, and among those who are employed 

after leaving SNAP, earnings are low. Most remain poor. Many struggle to acquire 

enough food to meet their needs, lack health insurance, experience housing problems, and/or have trouble paying their bills.435

In a serious omission the Kansas and Maine reports do not consider the impact 

of the time limit on the large number of people who lost SNAP and are among the 

nation’s very poorest adults. 

• In Kansas the number of non-disabled childless adults receiving SNAP dropped 

by 75 percent (from about 30,000 in late 2013 to about 7,500 in late 2015). 

• The Maine report does not present comparable numbers, but an earlier Heritage Foundation report cited Maine Department of Health and Human Services 

data showing that the number of ‘‘able-bodied adults without dependents on 

food stamps’’ dropped by 80 percent (from about 13,300 in late 2014 to 2,700 

in March 2015).436

The individuals whose SNAP was cut off lost about $5 a day, or $150 to $170 per 

person per month in SNAP benefits for purchasing food. Many of them worked in 

the year after losing benefits, but for some their wages were low enough that they 

could have continued to qualify for SNAP benefits, which could have helped them 


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437The Maine report does not include information about the average SNAP benefits received by childless adults who were cut off, so the ten to 20 percent range reflects a lower ($150 a 

month) and higher ($180 a month) assumption. As with Kansas, we cannot account for the large 

portion of the effect that would have happened anyway and we are not including any SNAP 

benefits for the workers who would have income low enough to continue participating in SNAP 

were there no time limit. 438 Brynne Keith-Jennings and Raheem Chaudhry, ‘‘Most Working-Age SNAP Participants 

Work, But Often in Unstable Jobs,’’ Center on Budget and Policy Priorities, March 15, 2018. 

As mentioned above, for similar households with just childless adults, 46 percent were working 

in a typical month and 72 percent worked within a year before or after that month. https:// 

Continued 

make ends meet. Some others with no earnings for some or all of the subsequent 

year may have had virtually no resources available for food after they were cut off 

SNAP. 

The Kansas and Maine reports cite average income figures for the year after recipients lost SNAP, but they fail to account for the lost SNAP benefits. To accurately 

compare income for a household that used to be on SNAP to income after losing 

SNAP, the lost value of the SNAP benefits must be included. When they are accounted for, total income does not increase substantially (or actually decreases 

slightly). 

In Kansas, the authors rest their claim that SNAP recipients were better off after 

the cutoff on a point that the group’s income rose by 127 percent between before 

the time limit took effect and 1 year later. There are three problems with this claim: 

• First, as discussed above, it implies that the time limit was responsible for the 

earnings increase, when most, if not all, of it likely would have occurred anyway; 

• Second, it excludes the value of SNAP benefits from the calculation. Total resources available to the household were higher before the time limit because the 

household received SNAP benefits; and, 

• Third, the authors picked a low comparison quarter prior to the time limit returning to exaggerate the increase—wages for the group cut off were more than 

30 percent lower two quarters before the cutoff (third quarter of 2013, the quarter used in the report) than they were in the quarter immediately preceding the 

cutoff (the fourth quarter of 2013). They do not explain why they chose this particular quarter as the baseline. 

It is not possible to adjust for the first issue without a rigorous evaluation (see 

above box), but even adjusting only for the other two issues makes a large difference. If $178 a month in SNAP benefits (the average SNAP benefit among those 

cut off in December 2013) is included in the base period, and if we compare the 

quarter immediately before the cutoff (the fourth quarter of 2013) as the base period 

instead of the quarter earlier, the total resources (including earnings and SNAP 

benefits) available to SNAP participants who were cut off was three percent lower 

a year after the cutoff, rather than 127 percent higher. 

Had the SNAP recipients who remained income-eligible been able to keep receiving SNAP (rather than being cut off by the time limit) more of them would be better 

off because they could have received SNAP while working (though their SNAP benefits would be lower because income counts in determining SNAP benefit levels). 

A similar contrast applies to the Maine report. The press release that accompanied the report claims that total income for those cut off rose by 114 percent within a year. However, if the state had included the value of SNAP benefits in the base, 

the increase would be much smaller—only about ten to 20 percent.437

No Consideration of Factors Affecting SNAP Participants’ Ability to Work 

If a better picture of the data shows that the time limit doesn’t have a strong role 

getting people into work, what do we know about why this group struggles to find 

employment? The research that exists on this population shows that adults who participate in SNAP work when they can, but often in jobs with high turnover and low 

job security, and most struggle with multiple barriers to employment, as discussed 

above. 

Adults on SNAP work when they can. However, the work tends to be low wage 

and unstable, with individuals cycling through periods of work and unemployment. 

Nearly 3⁄4 of non-disabled adults who participate in SNAP in a typical month work 

either that month or within a year of that month. Over 1⁄2 of individuals who were 

participating in SNAP in a typical month in mid-2012 were working in that month. 

Furthermore, 74 percent worked in the year before or after that month.438 (See FigVerDate Aug 31 2005 11:16 Jun 14, 2019 Jkt 041481 PO 00000 Frm 00301 Fmt 6621 Sfmt 6621 P:\DOCS\116-02\36188.TXT BRIAN
296 

www.cbpp.org/unemployed-adults-without-children-who-need-help-buying-food-only-get-snap-forthree-months. 439See ‘‘Comprehensive Report on Able-Bodied Adults Without Dependents, Franklin County 

Ohio Work Experience Program,’’ Ohio Association of Foodbanks, 2015, http:// 

admin.ohiofoodbanks.org/uploads/news/ABAWD_Report_2014-2015-v3.pdf. The Ohio Association of Foodbanks gathered the information for the report as a result of a partnership with the 

county SNAP agency to help place individuals identified as subject to the time limit in qualifying work activities after screening them. 

ure 11.5.) Limited education, lack of training, and a sporadic work history make it 

difficult to compete for anything other than low-skill, low-wage jobs that do not lift 

them out of poverty. 

Figure 11.5 

Most SNAP Participants and Households Work 

Note: Individuals and households include those who were participating in 

SNAP in a typical month in mid-2012. A working household refers to a 

household in which either the household head or spouse worked. Individuals include any non-disabled adult who reported participating in SNAP. 

Source: CBPP analysis of SIPP data from 2011–2013. 

Childless adults on SNAP face barriers. Many low-income childless adults face 

multiple challenges to independence and self-sufficiency, including homelessness, 

physical and mental health limitations, language barriers, unstable employment histories, and criminal records. A detailed study of childless adults who were referred 

to a work experience program in Franklin County (Columbus), Ohio found that: 439

• Many have extremely unstable living situations, illustrated by residence in 

short-term shelters or with friends and family and limited telephone service. 

• One-third have a mental or physical limitation, including depression, post-traumatic stress disorder, mental or learning disabilities, or physical injuries. Some 

of these disabilities, though not severe enough to qualify for Federal disability 

benefits, may still limit a person’s ability to work at least 20 hours a week. 

• About 1⁄4 have less than a high school education, and more than 1⁄2 have only 

a high school diploma or GED. 

• Nearly 1⁄4 are non-custodial parents, and 13 percent are caregivers for a parent, 

relative, or friend. 

• More than 40 percent lack access to reliable private or public transportation; 

60 percent lack a valid driver’s license. 


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297 

440Michael Stavrianos and Lucia Nixon, ‘‘The Effect of Welfare Reform on Able-Bodied Food 

Stamp Recipients,’’ prepared by Mathematica Policy Research for the USDA, Food and Nutrition 

Service, July 23, 1998, https://fns-prod.azureedge.net/sites/default/files/finalrep.pdf. 441 Ibid, p. xii and pp. 51–69. 442 Ibid, p. 56–57. 443 NPRM, p. 981, 982, 983; RIA, p. 2, 10. 

• Fifteen percent need supportive services like language interpretation or help 

with transportation to obtain employment. 

• More than 1⁄3 have felony convictions, making it hard to find jobs and pass 

background checks. 

D. FNS’ Research, Policies, and Practices Show FNS Knows but Ignored That Impact of the Proposed Rule Is Out of Line With the Stated Rationale 

FNS’ Own Research from 1998 on the Employment Prospects of ‘‘ABAWDs’’ Contradicts the Stated Justification of the NPRM 

In 1998 FNS published a study called, ‘‘The Effect of Welfare Reform on Able-Bodied Food Stamp Recipients’’ to provide information that ‘‘[I]s critical to informing 

policy decisions, issuing guidance to states, implementing new policies, as well as 

estimating effects of the [new provisions.]’’ It concluded in the forward to the study, 

‘‘the report offers a sound picture of what able-bodied adult recipients without children look like and what will happen to them—they are an extremely poor population with limited employment prospects and few sources of support outside the 

Food Stamp Program.’’ 440 This research directly contradicts the stated justification 

for the proposed rule. 

The study used SNAP QC household characteristics data and the Census Bureau’s 

Survey of Income and Program Participants (SIPP) to describe the characteristics 

of individuals subject to the time limit, including their limited educational attainment and workplace skills, their high poverty rates, and their patterns of SNAP 

participation prior to the time limit going into effect. It also estimated how many 

at that time had likely hit the time limit and been cut off SNAP. 

The study also included information about the research available at that time on 

the employment prospects of ‘‘ABAWD’’ SNAP participants, which is summarized as 

follows: 

Research indicates that the employment prospects of adults who are demographically similar to ABAWDs are not promising, and so we can assume the 

same to be true for ABAWDs. Largely for two reasons, job opportunities for lesseducated job seekers are severely limited, especially for non-whites and in 

urban areas, where most ABAWDs live. First, recent research suggests that 

many large employers of low-skill workers have moved out of the cities to the 

suburbs. Therefore, many ABAWDs will face a ‘‘spatial mismatch’’ between the 

location of their residence and the location of low-skill jobs. Second, since employment in inner cities has become increasingly concentrated in high-skill jobs, 

ABAWDs will also likely face a ‘‘skills mismatch’’ between what employers require and what ABAWDs can offer.441

As we review in Chapter 3, while the nature of spatial mismatch has changed, 

more recent literature has found that there still exists mismatch between low-wage 

jobs and where low-wage workers live, particularly with regards to transportation 

access. 

The 1998 FNS study also points out that low-skilled job seekers in many places 

may have difficulty finding employment even when the national unemployment rate 

is low: 

Implicit in PRWORA’s work requirement is the assumption that there are 

enough employment opportunities for ABAWDs—that is, they can find work if 

they seek it. . . . However, a relatively large body of research indicates that the 

labor market situation of the low-skilled has become considerably worse in recent decades and that their current employment prospects are limited. This suggests that even if ABAWDs are willing to work, they may be unable to do so 

because there are not enough jobs for low-skilled workers.442

Despite arguing repeatedly in the preamble and RIA that the low national unemployment rate justifies the proposed rule,443 FNS does not refute this earlier research it published in 1998, nor address whether the landscape has changed in the 

intervening 20 years to justify the change in waiver policy. 

298 

444 Elizabeth Dagata, ‘‘Assessing the Self-Sufficiency of Food Stamp Leavers,’’ Economic Research Service, USDA, September 2002, https://www.ers.usda.gov/publications/pub-details/ 

?pubid=46645, a summary of in-depth studies in Arizona, Illinois, Iowa, and South Carolina. 

https://lib.dr.iastate.edu/cgi/viewcontent.cgi?referer=https://www.google.com/&httpsredir=1& 

article=1013&context=card_staffreports—Iowa. https://www.mathematica-mpr.com/our-publications-and-findings/publications/food-stamp-leavers-in-illinois-how-are-they-doing-two-yearslater—Illinois. https://naldc.nal.usda.gov/download/45220/PDF—South Carolina. 445Dagata, p. 2. 446Dagata, p. 4. Food insecurity ‘‘with hunger’’ was how USDA then referred to the most severe form of food insecurity where households had to skip or reduce the size or their meals or 

otherwise disrupt their eating patterns at times during the year because they couldn’t afford 

sufficient food. 447Dagata, p. 5. 448The Food and Nutrition Act of 2008, as amended, 7 U.S.C. § 2015(d)(4)(A)(i). 

USDA Research on Individuals Who May Have Been Cut off SNAP Because of the 

Time Limit Does Not Support the Assertion That the Time Limit Improves SelfSufficiency 

After the 3 month time limit was enacted in 1996, USDA’s Economic Research 

Service (ERS) joined with the U.S. Department of Health and Human Services to 

fund studies in four states (Arizona, Illinois, Iowa, and South Carolina) that examined the well-being of people who exited SNAP in the late 1990s after the time limit 

went into effect.444 The studies included people who had left SNAP because of the 

3 month time limit or for other reasons, for example, because the found a job or 

mistakenly believe they no longer are eligible. Even though the studies were not 

able to isolate the individuals who left SNAP because of the time limit, the picture 

they offer of the hardship such individuals face suggest that the time limit has not 

spurred many to self-sufficiency, or even resulted in their life circumstances improving modestly, and contradict the stated rationale behind the proposed rule. 

• Many were employed but had very low earnings. In the four states, employment rates among the individuals who were unemployed childless adults 

potentially subject to the time limit who left SNAP (or ‘‘leavers’’) ranged from 

41 percent in Illinois to 76 percent in Iowa, ‘‘but earnings and incomes are low 

and their poverty rates are high.’’ 445

• Most remain poor. Despite relatively high levels of work effort, between 1⁄3

and 2⁄3 of SNAP leavers in the four states had household incomes below the poverty line—well above the overall poverty rate of 13 percent at the time. About 

40 percent of the Illinois and Iowa SNAP leavers had income below 1⁄2 the poverty line. 

• Many struggled to afford adequate food. ‘‘Between 17 and 34 percent of the 

[SNAP leavers in the four states] reported food insecurity with hunger, compared with 11 percent of U.S. low-income childless households.’’ 446

• Many had housing problems, or had trouble paying their utility bills. 

About 20 to 40 percent of SNAP leavers faced housing issues, including falling 

behind on the rent, moving in with relatives, or becoming homeless. Between 

20 and 65 percent reported problems paying for utilities. 

Finally, the studies raise an important question about exemptions from the time 

limit. ‘‘In two of the studies, the majority of nonworking [SNAP leavers] cited health 

problems as the reason they were not working . . . it is important to know whether 

the standards for being categorized as ‘able-bodied’ are set appropriately.’’ 447

FNS’ SNAP Employment and Training Best Practices and the Department’s SNAP 

to Skills Initiative Do Not Promote Cutting People Off SNAP 

FNS’ position that taking food assistance away from people who do not meet rigid 

work requirements will lead to stable employment and self-sufficiency also conflicts 

with the agency’s approach to employment and training (E&T). For more than 30 

years, since the mid-1980s, SNAP has included an employment and training (E&T) 

component, ‘‘for the purpose of assisting members of households participating in the 

supplemental nutrition assistance program in gaining skills, training, work or experience that will . . . increase the ability of the household members to obtain regular 

employment.’’ 448 States operate the program within Federal rules and FNS oversight, but have substantial flexibility about which non-exempt SNAP recipients they 

serve in the program, the services they offer participants, and whether the program 

primarily recruits volunteers who are interested in help finding a job or improving 

their education and skills, or whether the program is mandatory, meaning individuals will lose SNAP benefits (i.e., be subject to sanction) if they do not comply with 

the state’s assigned E&T activity. 

299 

449Deborah Kogan, et al., ‘‘Supplemental Nutrition Assistance Program (SNAP) Employment 

and Training (E&T) Best Practices Study: Final Report,’’ prepared by Social Policy Research Associates for the U.S. Department of Agriculture, Food and Nutrition Service, November 2016, 

https://www.fns.usda.gov/snap/snap-employment-and-training-et-best-practices-study-final-report. 450 Ibid, p. III–1. 451 Ibid, p. ES–1. 

E&T Best Practices Research Review Does Not Include Sanctions or Cutting People Off SNAP 

While over the years Congress has amended and modified the focus of SNAP E&T 

somewhat, it has always included a state option for programs that are mandatory 

and include sanctions for non-compliance. According to a 2016 FNS-sponsored literature review of SNAP E&T best practices, the only time FNS conducted a rigorous 

study of the effectiveness of SNAP E&T, was in the late 1980s and early 1990s. At 

the time, SNAP E&T was primarily ‘‘a high-volume, ‘light-touch’ program to encourage mandatory work registrants to find jobs quickly, primarily by requiring participation in job search and job-search training components,’’ 449 that is, it consisted primarily of components that included taking SNAP benefits away from individuals 

who did not meet the program’s requirements. The 2016 literature review described 

the findings from the study that was published in 1994 as follows: 

[T]here was no evidence that the SNAP E&T program—in its high participation/low investment per-participant model—increased the likelihood of participants finding jobs. It also found the program had no significant effects on the 

hourly wages, hours worked per week, or length of job retention for those who 

did find employment . . . 

The observed effect of a statistically significant decrease in the level of food 

stamp benefits receipt was described as most likely the result of ‘voluntary 

withdrawals and administrative sanctions’ rather than of any increase in household income or earnings . . . 

[A]lthough some members of the treatment group did find jobs, members of 

the control group were also able to obtain similar job search assistance and find 

employment.450

Thus, the only rigorous evaluation FNS has ever conducted of policies that take 

food assistance away from individuals who are unable to meet work requirements 

found no improvement in participants finding jobs or increases in wages or hours 

worked, but did find a significant decrease in food assistance benefits. The literature 

review quoted here was published in 2016, so was certainly available to FNS as it 

formulated the proposed rule, but FNS ignored its findings. FNS promulgated the 

proposed rule that would take food assistance away from people who do not comply 

with rigid work requirements without ever again testing or studying the effectiveness of such an approach in a rigorous random assignment study. Moreover, the 

E&T pilots from the 2014 Farm Bill, which do incorporate a rigorous random assignment evaluation, include three states with mandatory SNAP E&T approaches, 

but FNS promulgated this regulation without waiting for the results of those pilots. 

Overall, the 2016 SNAP E&T best practices report had as its objective providing 

‘‘Congress, FNS, and individual states with information that can be used to shape 

the services provided by the SNAP E&T program and thereby improve the employability, self-sufficiency, and well-being of individuals receiving nutrition support 

from SNAP.’’ 451 These are the very same goals as the stated intention and justification of the proposed rule in the NPRM, and yet the SNAP E&T best practices report 

does not mention taking SNAP benefits away from individuals who are unable to 

meet work requirements as an effective strategy. The report includes an annotated 

bibliography of 160 relevant studies from the literature review. The best practices 

report recommendations are summarized in the executive summary: 

The findings from the research synthesized in this report suggest that SNAP recipients will benefit most from SNAP E&T-funded services if the services offered by 

state programs 

• Are based on an individualized assessment of the workforce-related strengths 

and weaknesses of SNAP clients; 

• Comprehensively address an individual’s need for skills training, basic skills 

education, and overcoming barriers to employment; 

• Help participant earn credentials valued by employers in their chose industry 

or sector; and 

• Develop skills that are closely linked to labor market demands in the local area. 

300 

452 Ibid, p. ES–4. 453 U.S. Department of Agriculture, ‘‘Why SNAP to Skills,’’ https://snaptoskills.fns.usda.gov/ 

why-snap-to-skills. 454 Ibid. 

In view of these findings . . . States that enroll a relatively large number of 

mandatory work registrants in SNAP E&T services or that emphasize self-reported job search as the most frequently prescribed program activity are less 

likely to see an increase in self-sufficiency among SNAP participants.452

Thus, the most recent research available to FNS about what works for SNAP E&T 

for meeting the objectives of increasing employment, self-sufficiency, and well-being 

does not include sanctions or cutting people off SNAP. But FNS ignored this evidence in promulgating the regulation. We urge FNS to consider its own best practices study. 

FNS’ Most Recent E&T Efforts Also Have Not Promoted Sanctions or Cutting People Off SNAP 

Moreover, in the past several years FNS has placed a new emphasis on SNAP 

E&T. It has created an Office of Employment and Training with several additional 

staff members, brought on consultants and collaborated with other partners, formed 

a ‘‘learning academy,’’ produced new training materials, and provided additional 

technical assistance to select states. The cornerstone of the E&T efforts has been 

a ‘‘SNAP to Skills’’ initiative that follows closely the recommendations from the 

SNAP E&T best practices report cited above. 

Under a ‘‘Why SNAP to Skills’’ section of its website, FNS makes the following 

case for its SNAP to Skills approach: 453

The need of Supplemental Nutrition Assistance Program (SNAP) participants 

to secure the education and training required to transition to economic self-sufficiency is growing increasingly urgent. The vast majority of jobs in the future 

will require at least some education beyond high school . . . yet many SNAP 

participants have not reached this level of educational attainment. Without the 

skills to meet rapidly changing labor market demand, the chances of SNAP participants getting a good job and reducing their need for SNAP are extremely 

low . . . 

The SNAP Employment & Training (SNAP E&T) program, a skills and job 

training program for SNAP participants administered by the U.S. Department 

of Agriculture’s Food and Nutrition Service (FNS), is a key resource states and 

their partners can utilize to help SNAP participants meet this urgent need for 

skills and better jobs. SNAP E&T has historically been under-utilized, but a renewed focus on the program amid greater urgency for job training for SNAP 

participants has created new momentum for states seeking to build bigger, better, and stronger E&T programs. 

There is no more opportune, or critical, time for states to build robust, jobdriven SNAP E&T programs. ‘‘Job-driven’’ means that programs are responsive 

to employer demand so that they place ready-to-work participants in good, 

available jobs or provide skills training and credentials participants require to 

obtain these jobs. SNAP E&T is increasingly recognized as a critical part of 

each state’s skilled workforce strategy. USDA and other policy makers herald 

SNAP E&T as an important part of the national conversation about the need 

to invest in building a skilled workforce while addressing the nation’s growing 

economic inequality.454

Like the best practices report cited earlier, FNS’ signature Employment and 

Training initiative does not include sanctions or cutting individuals off of SNAP as 

an effective strategy for increasing employment or earnings. 

E. FNS Knows That Research and Experience Shows That People Newly Subject to 

the Time Limit Won’t Get a Job or Be Better Off, But It Promulgated the Proposed Rule Nonetheless 

As we have laid out in this section, there is a large body of research evidence that 

finds that policies that take benefits away from individuals who do not meet rigid 

work requirements result in lost benefits and increased poverty and hardship, but 

very little gain in longer-term employment. The realities of the low-wage labor market, including high turnover and lack of sick time and other benefits contribute to 

individuals’ turning to SNAP during temporary periods of unemployment. Many 

other individuals face various employment barriers. 

FNS has for more than 20 years supported the waiver policy currently in regulation, and there is no new research that contradicts or provides new information. The 

301 

455 Individuals who have been cut off SNAP can qualify for a second 3 months of eligibility 

if they work at least 80 hours (or participate in a qualifying program) for a month and reapply 

for SNAP. 456 In the 2016 paper CBPP used this methodology and included a box explaining the difference between the larger number potentially subject to the time limit and the smaller number 

affected by the time limit in practice. See, Steven Carlson, Dorothy Rosenbaum, Brynne KeithContinued 

RIA conspicuously lacks any countervailing research evidence to justify that the 

narrowing of waivers will improve individuals’ work rates or earnings, and the impact analysis included in the RIA assumes that 755,000 individuals will lose SNAP 

benefits under the change, but there will be no quantifiable increases in earnings 

or work. 

We believe that the only conclusion one can draw is that contrary to the stated 

rationale in the NPRM, FNS knows that the primary effect of the regulatory 

change, if it were finalized, would be that a large number of individuals would lose 

SNAP assistance, with no, or very little positive impact. We strongly urge FNS to 

review the research summarized here and included in the Appendix B. 

F. The Proposed Rule Uses an Imprecise Definition of ‘‘ABAWDs,’’ and the RIA Includes Numerous other Unsubstantiated Assumptions 

In addition to the fact that the proposed rule is not supported by available research, the analysis that is included in the RIA includes numerous imprecise, illogical, and unsubstantiated assumptions, starting with the use of the term ‘‘ABAWDs.’’ 

Since shortly after the passage of the 1996 welfare law, FNS has described the 

group of SNAP participants whose eligibility is at issue because of the 3 month time 

limit as ‘‘ABAWDs,’’ or able-bodied adults without dependents. The proposed rule 

uses this term throughout, but never defines it, and seems to include in it many 

individuals who are exempt from the time limit, who live in an area that is under 

a waiver, or who are participating in SNAP during periods when they are eligible 

(for example, in their first 3 months or when they are working or participating in 

a qualifying employment and training program.) The methodology for assessing the 

impact of the proposed rule indefensibly treats everyone who is an ‘‘ABAWD’’ by this 

broad definition as though they would be subject to the time limit under the proposed rule (i.e., that they live in an area that would no longer qualify for a waiver.) 

The rule also excludes from the analysis individuals who are ‘‘ABAWDs’’ subject to 

the time limit, but who are no longer SNAP recipients because they have been cut 

off. 

The imprecise use of the undefined term ‘‘ABAWD’’ is confusing and makes it difficult for readers to understand and comment on the described impacts of the proposed rule. It also appears that the Department in its estimates of the impact of 

the regulation has derived percentages for this entire population of SNAP recipients 

potentially subject to the time limit and then applied those percentages to individuals who would be newly subject to the time limit under the proposed rule, resulting 

in a methodology that cannot be substantiated. 

This section will first explain the analytical problem in the way the RIA defines 

and categorizes ‘‘ABAWDs,’’ and then provide additional examples of specific assumptions in the methodology that cannot be substantiated, often because of the imprecise use of the term ‘‘ABAWD.’’ 

Use of the Undefined Term ‘‘ABAWD’’ Is Confusing and Misleading 

Section 6(o) (7 U.S.C. § 2015(o)) of the Food and Nutrition Act limits SNAP eligibility for certain non-exempt adults who are aged 18–49 to 3 months of SNAP benefits in any 36 month period if they are not working 20 hours a week or participating 

in a qualifying employment and training program, and if the area they live in is 

not waived from the rule because of insufficient jobs.455 Because of the rule’s complexity, the individuals subject to the time limit cannot be identified in SNAP or 

Census Bureau data because much of the information that would need to be known 

is not available in the data. Analysts often have modeled SNAP eligibility for these 

individuals to the best of their ability and then described the individuals as ‘‘potentially subject to the time limit,’’ because only state eligibility workers have access 

to the information that is needed to make a full assessment. In a 2016 paper we 

explained: 

About 4.7 million non-elderly, non-disabled adults aged 18–49 in childless 

households participated in SNAP in Fiscal Year 2014. All were ‘‘subject’’ to the 

time limit in the sense that all could, in theory, have lost benefits after 3 

months of participation. The number affected by the time limit in practice, however, is much smaller.456

302 

Jennings, ‘‘Who are the Low-Income Childless Adults Facing the Loss of SNAP in 2016,’’ February 8, 2016, https://www.cbpp.org/sites/default/files/atoms/files/2-8-16fa.pdf, p. 4. 457 Ibid. 458Mike Stavrianos, et al., ‘‘Characteristics of Childless Unemployed Adult and Legal Immigrant Food Stamp Participants: Fiscal Year 1995,’’ prepared by Mathematica Policy Research 

for the USDA, Food and Nutrition Service, February 13, 1997, p. 6. 459 Ibid, Stavrianos, p. 6. 460 U.S. Department of Agriculture, ‘‘Regulatory Reform at a Glance, Proposed Rule: SNAP Requirements for ABAWDs,’’ December 2018, https://fns-prod.azureedge.net/sites/default/files/ 

snap/ABAWDSFactSheet.pdf. We believe this 3.8 million is the starting point for all of the estimates in the RIA regarding the number of ‘‘ABAWDs,’’ but the RIA does not make that clear, 

as we discuss later in our comments. 461The 2016 public use Quality Control Data are available at https://host76.mathematicampr.com/fns/. All figures we cite based on this data are for an average month in the fiscal year. 

We also explained in the 2016 paper the various reasons why the larger figure, 

which we represent as individuals potentially subject to the time limit based on existing data, applies to ‘‘the characteristics of the larger group of childless adults, all 

of whom would face the time limit if their circumstances or local labor market conditions change.’’ 457

In estimates that FNS published in the years immediately following passage of 

the 1996 welfare law, it is clear that the agency understood both the limitations in 

the data (‘‘The QC database does not contain all the information needed to determine whether an individual loses eligibility under the able-bodied provisions of 

PRWORA’’ 458) and the distinction between those potentially subject to the time 

limit and those who would actually be affected (‘‘the QC-based estimates presented 

in this chapter may overstate the number of people subject to the 3 month time 

limit.’’ 459) 

But the NPRM, RIA, and Agriculture Department materials that accompanied the 

December posting of the proposed rule portray this larger group that is potentially 

subject to the time limit as the number who actually would be newly subject under 

the proposed rule. This misidentification is confusing and results in unsubstantiated 

assumptions. It identifies as newly subject to the time limit many individuals who 

are exempt, complying with the time limit, or living in an area that is under a waiver from the time limit, and it excludes individuals who would qualify for SNAP but 

have been cut off after 3 months in areas that are not under a waiver from the time 

limit. 

The Department asserts that ‘‘[i]n 2016 there were 3.8 million individual 

ABAWDs on the SNAP rolls.’’ 460 We are able to reproduce this number using the 

public use 2016 SNAP Household Characteristics Quality Control (QC) file,461 and 

below recreate how we believe FNS derived the number. (See Table 11.1) 

Table 11.1 

CBPP Understanding of FNS’ Estimate That 3.8 million SNAP Recipients 

Were ‘‘ABAWDs’’ in 2016 

FNS’ 3.8 million ‘‘ABAWD’’ estimate Number 

Percent of Total 

SNAP 

Participants 

Total SNAP Participants 43.5 million 100% 

Age 18–49 15.0 million 34.4% 

Not receiving disability benefits a 12.8 million 29.5% 

No minor children in household 3.8 million 8.8% 

Other factors that need to be taken into account for an 

individual to be subject to the time limit that were not 

factored into FNS’ estimate: 

Is this information available in the 

QC data? 

Is the individual: 

• in his or her first 3 months of SNAP participation out of 36? Variable not reliable b

• physically or mentally unfit for employment? Variable not reliable c

• living in a waived area? Variable not reliable b

But may be knowable if state was 

under a statewide waiver 

• working 20 hours a week or more? Can be estimated using earnings or 

other variables 

• participating in a qualifying E&T activity? Variable not reliable d

303 

462Stavrianos and Nixon (1998, p. 4) and Czajka, et al., (2001, p. 30) both include flow charts 

that makes clear FNS had information available that made clear which ‘‘ABAWDs’’ would be 

subject to the time limit and the various reasons individuals who might be identified in the data 

as ‘‘ABAWDs’’ might not be affected by the time limit. 463The states with statewide waivers from the time limit in 2013 but no waivers at all in 

2017 (which represented about a quarter of SNAP participants in 2013) were Alabama, Arkansas, Florida, Indiana, Iowa, Kansas, Maine, Mississippi, Missouri, North Carolina, Oklahoma, 

Continued 

Other factors that need to be taken into account for an 

individual to be subject to the time limit that were not 

factored into FNS’ estimate: 

Is this information available in the 

QC data? 

• pregnant? Not available 

• otherwise exempt from employment and training? Variable not reliable c

• exempted by an individual exemption? Variable not reliable b

• in a second 3 month period after requalifying? Variable not reliable b

Sources: CBPP analysis of FY 2016 USDA SNAP Household Characteristics data and 

Mathematica Policy Research, ‘‘Technical Documentation for the Fiscal year 2016 [or other year] 

Supplemental Nutrition Assistance Program Quality Control Database and the QC Minimodel,’’ 

October 2017. aThe SNAP QC data set includes a personal-level disability variable (DISi). An algorithm is 

used to identify individuals with disabilities based on SSI receipt, medical expenses, age, work 

registration status, and other factors. The technical documentation flags that ‘‘DISi likely underestimates the number of non-elderly individuals with disabilities’’ and therefore, the 3.8 million 

likely overestimates the number of adults without disabilities. bThe SNAP QC data includes an individual-level variable called ‘‘ABWDSTi’’ that is intended 

to collect this information, but the technical documentation ‘‘[recommends] caution when 

using . . . due to inconsistencies.’’ 

cFor the variable intended to capture exemptions for disability and other factors 

(‘‘WRKREGi’’) the documentation states, ‘‘we found continued evidence . . . of likely miscoding 

of this variable.’’ dThe variable intended to capture participation in employment and training (‘‘EMPRGi’’) is 

also among the variables the documentation ‘‘recommend[s] using with caution.’’ 

As Table 11.1 shows, there are many eligibility factors that the Department’s 

analysis did not take into account when estimating the number of people who are 

subject to the time limit. As a result, the 3.8 million individuals the Department 

classifies as ‘‘ABAWDs’’ includes many individuals who, in fact, are not subject to 

the time limit. The Department’s analysis also excludes many individuals who 

would be SNAP recipients except they have been cut off because of the time limit, 

so they do not appear in SNAP data because they are not SNAP recipients.462 These 

are individuals who do not live in waived areas but are subject to the time limit 

because they did not meet any of the other criteria in Table 11.1. 

The Department’s imprecise use of the term ‘‘ABAWD’’ results in a lack of transparency. It is difficult to determine what point FNS (in the NPRM and RIA), and 

the Administration more broadly, in its materials about the proposed rule, are making when they call individuals ‘‘ABAWDs’’ when they are not, in fact, subject to the 

time limit, or when they are complying with the time limit. They are implying that 

far more SNAP participants are subject to the time limit and not in compliance with 

it than in fact is the case, and they are not counting people who have been cut off 

because of the time limit. 

In addition, several of the major assumptions in the RIA’s methodology for assessing the impact of the proposed rule rely on shares of this larger ‘‘ABAWD’’ group, 

as defined nationwide using the 2016 data, but apply those shares to individuals 

who would be newly subject to the time limit because of the proposed changes in 

the rules for areas to qualify for waivers. For example, the RIA’s assumption about 

the share of ‘‘ABAWDs’’ who are working is derived from the SNAP data for 2016 

including both waived areas and not-waived areas. Using shares that are derived 

from a group that includes many individuals who are not subject to the time limit, 

and that excludes many individuals who have been cut off SNAP in areas that were 

not waived in 2016 is extremely misleading and illogical. The denominator for these 

percentages matters for assessing the soundness of using certain percentages for deriving or estimating the impact of the proposed changes. 

To help elucidate the problem, we conducted an analysis comparing the number 

and share of SNAP participants for two different categories of states regarding 

waivers from the time limit in 2 different fiscal years. The two types of states were 

those with statewide waivers in Fiscal Year 2013, but no waivers in Fiscal Year 

2017 and those with statewide waivers in both years.463 The difference between the 

304 

South Carolina, and Wisconsin. The states with statewide waivers in both 2013 and 2017 (which 

represented about 20 percent of SNAP participants) included Alaska, California, District of Columbia, Illinois, Louisiana, Nevada, New Mexico, Rhode Island, Guam, and Virgin Islands. 

2 years for the two types of states can help explain how the denominator changes 

when many people are cut off as a result of the time limit. We will use figures from 

this analysis to help explain some of the serious methodological problems with the 

RIA’s analysis of the impact of the proposed rule. It is easier to see the issue when 

considering these two types of states, but it is present in other states that have had 

different patterns and scope of waivers. 

We use fiscal 2017 instead of Fiscal Year 2016 for this analysis because many 

states reimplemented the time limit beginning on January 1, 2016, which means 

that for Fiscal Year 2016 the time limit was in effect for just the latter 6 months 

of the fiscal year (April through September, once the 3 months of eligibility for January to March are taken into account.) By Fiscal Year 2017 those states had no 

waiver the entire fiscal year. Under the definition of ‘‘ABAWD’’ that FNS appears 

to use, the 3.8 million national figure cited in the FNS materials and that we recreate above in Table 11.1 fell to 3.2 million in Fiscal Year 2017. 

Table 11.2, shows the number of SNAP participants in the two types of state in 

each year and the number and share that are ‘‘ABAWDs’’ under our understanding 

of how FNS is defining ABAWDs for purposes of the RIA—as SNAP participants 

aged 18–49, with no disability benefits and no minor children in the household. 

Table 11.2 

Waivers Affect the Number and Share of SNAP ‘‘ABAWDs’’ 

Fiscal Years 2013 and 2017 by whether the state had a statewide waiver 

Total SNAP 

Participants 

(in 000s) 

Total 

‘‘ABAWDs’’ (in 

000s) 

ABAWDs as a 

Share of Total 

Participants 

Fiscal Year 2013 

Participants residing in states with statewide waivers in 2013 and no waivers in 2017 12,439 1,496 12% 

Participants residing in states with statewide waivers in both 2013 and 2017 8,346 953 11% 

Total participants all states a 47,098 4,943 10% 

Fiscal Year 2017 

Participants residing in states with statewide waivers in 2013 and no waivers in 2017 10,325 609 6% 

% change 2013 to 2017 ¥17% ¥59% 

Participants residing in states with statewide 

waivers in both 2013 and 2017 8,164 927 11% 

% change 2013 to 2017 ¥2% ¥3% 

Total participants all states a 41,491 3,221 8% 

% change 2013 to 2017 ¥12% ¥35% 

Source: CBPP analysis of FY 2013 and FY 2017 USDA SNAP Household Characteristics data 

a Includes participants in the two types of states identified above, as well as participants residing in other states. 

Table 11.2 shows: 

• The number of both SNAP recipients and ‘‘ABAWDs’’ declined in both types of 

states between 2013 and 2017 but fell substantially more in states that had reimposed the time limit by 2017. The number of ‘‘ABAWDs’’ potentially subject 

to the time limit fell by 59 percent in states that reimposed the time limit, from 

1.5 million in 2013 to 600,000 in 2017. The economy may have been stronger 

in these states, and there may be other reasons for a larger drop, but the fact 

that eligibility rules changed and many people in this group could not participate for more than 3 months was likely a major factor in the larger drop. 

• The share of total SNAP participants who were ‘‘ABAWDs’’ in the states that 

reimposed the time limit by 2017 fell from 12 percent to six percent but was 

flat at 11 percent in the states that had a statewide waiver in both years. So, 

although the number and share of ‘‘ABAWDs’’ fell substantially in states that 

reimposed the time limit by 2017, six percent of SNAP participants still fit into 

305 

464Dorothy Rosenbaum and Ed Bolen, ‘‘SNAP Reports Present Misleading Findings on Impact 

of Three-Month Time Limit,’’ Center on Budget and Policy Priorities, December 14, 2016, 

https://www.cbpp.org/sites/default/files/atoms/files/12-14-16fa.pdf. 

the ‘‘ABAWD’’ category as defined by the RIA. These individuals likely meet one 

of the eligibility criteria in Table 11.1 and so were not cut off. 

The share of ‘‘ABAWDs’’ working also changes as the denominator changes when 

individuals are cut off SNAP. In Table 11.3 we compare the work rates among 

SNAP participants who were ‘‘ABAWDs’’ under the FNS’ definition in the same two 

types of states as above for the same 2 years. 

Table 11.3 

Waivers Affect the Number and Share of SNAP ‘‘ABAWDs’’ Who Are Working Fiscal Years 2013 and 2017 by whether the state had a statewide 

waiver 

Total 

‘‘ABAWDs’’ 

(in 000s) 

‘‘ABAWDs’’ 

working (in 

000s) 

Share of 

‘‘ABAWDs’’ 

working 

‘‘ABAWDs’’ 

working at 

least 20 hrs/ 

wk (in 000s) 

Share of 

‘‘ABAWDs’’ 

working at 

least 20 hrs/ 

wk 

Fiscal Year 2013 

States with statewide waivers in 2013 and 

no waivers in 2017 1,496 331 22% 187 13% 

States with statewide waivers in both 2013 

and 2017 953 165 17% 63 7% 

Total all states a 4,943 1,087 22% 587 12% 

Fiscal Year 2017 

States with statewide waivers in 2013 and 

no waivers in 2017 609 207 34% 138 23% 

States with statewide waivers in both 2013 

and 2017 926 219 24% 111 12% 

Total all states a 3,221 897 28% 534 17% 

Source: CBPP analysis of FY 2013 and FY 2017 USDA SNAP Household Characteristics data. 

a Includes participants in the two types of states identified above, as well as participants residing in other states. 

In the states that had reimposed the time limit by 2017, although the number 

of ABAWDs dropped between 2013 and 2017, the share of ‘‘ABAWDs’’ working went 

up substantially, from 22 percent in 2013 to 34 percent in 2016, and the share estimated to be working at least 20 hours a week nearly doubled, from 13 percent to 

23 percent. In part this could be a function of a stronger economy in these states, 

or other factors, but the fact that many people who were not working were cut off 

also contributed significantly to the change in work rate. In the states that had 

statewide waivers both years, the share working went up, but by less, from 17 percent to 24 percent, and the share estimated to be working at least 20 hours a week 

went from seven percent to 12 percent. 

Between 2013 and 2017 the number of ‘‘ABAWDs’’ in areas without waivers went 

down in large part because individuals were cut off of SNAP in areas without waivers. And because individuals could continue to receive SNAP if they were working 

more than 20 hours a week, the share of ABAWDs working at least 20 hours a week 

went up in areas without waivers, in large part because the denominator used in 

calculating the share (the number of ABAWDs who received SNAP) went down. In 

a 2016 report responding to a misleading report that claimed the circumstances of 

SNAP recipients in Kansas improved after they reinstated the time limit we explained this math as follows: 

. . . the childless adults who remained as SNAP participants after the time 

limit went into effect were significantly different from those who participated 

before because of the policy change. The state cut off SNAP those participants 

who were not working at least 20 hours a week, so the work rates, average 

earnings, and other characteristics of those who remained SNAP participants 

after the return of the time limit were better, not because those individuals became better off, but because they were better off to begin with and were the 

only ones still eligible and participating in SNAP.464

The RIA methodology includes numerous imprecise, confusing, inaccurate, or misleading assumptions, some that push in opposite directions. We cannot tell if FNS 

has intentionally produced an analysis that inflates (or deflates) the results or if the 

306 

465 U.S. Department of Agriculture, Supplemental Nutrition Assistance Program Data, 

https://www.fns.usda.gov/pd/supplemental-nutrition-assistance-program-snap. 

individuals charged with producing the RIA do not understand the policy and therefore were unable to produce a coherent analysis of the population subject to the current policy and what the impact of the proposal would be. Either way, the lack of 

transparency and coherency in the RIA raises serious questions about the validity 

of the NPRM process. 

The RIA Does Not Explain the Claim That There Would Be 3.4 Million ‘‘ABAWDs’’ 

in 2020 

The methodology evidently assumes that there would be 3.4 million ‘‘ABAWDs’’ 

in 2020 under current law, but never explains where that figure comes from. This 

is a serious omission because this is the starting point FNS uses for all of the subsequent assumptions about the number of individuals who would be affected by the 

proposed changes in waiver rules. Excluding information on this foundational point 

compromises all that follows. 

The only time the 3.4 million figure is mentioned, on page 25 of the RIA, the document says, ‘‘As noted previously, the Department estimated that approximately 44 

percent of the projected 3.4 million ABAWDs . . . would live in waived areas in FY 

2020 if waiver authority were unchanged.’’ It is possible that the figure comes from 

the 3.8 million from the SNAP QC data for 2016 cited above, adjusted to reflect the 

FNS’ baseline number of participants for 2020 compared to the number of participants in 2020, but we cannot comment on this figure as the RIA provides no justification for it whatsoever. 

If the 3.4 million is the 3.8 million from 2016 adjusted only for baseline changes, 

then the FNS has made no further adjustments to account for the fact that states 

qualified for and applied for waivers for fewer areas in 2018 and 2019 than in 2016 

and will likely qualify for still fewer waivers in 2020 even without any changes to 

the waiver rules. 

The RIA Assumption That 44 Percent of ‘‘ABAWDs’’ Are in Waived Areas Is Based 

on a Proxy That Is Indefensible 

As one step in its estimate of the impact of the proposed rule, the analysis in the 

RIA assumes that 44 percent of the 3.4 million ‘‘ABAWDs,’’ or 1.5 million individuals, would live in waived areas in FY 2020 if the regulation were unchanged. According to RIA (page 19): 

The Department used state-reported data from form FNS–388A to estimate 

the number of non-public assistance SNAP participants living in currently 

waived areas. Since the FNS–388A does not report ABAWD participation separately, non-public assistance SNAP participants are used as a proxy when estimating the proportion of ABAWDs living in waived areas. 

The RIA does not explain what the form FNS–388A is or why it is appropriate 

to use it and what its shortcomings might be. Based on a review of the July 2018 

data that states submitted, it appears that the 388A does not include all SNAP participants (Oregon and Vermont are missing) and that there are no county-level data 

for several states, including all of New England, Alaska, Idaho, Missouri, Montana, 

Nebraska, New York, Utah, Washington, and Wisconsin.465

But even if the 388A included county data for all states, it does not make sense 

to use the number of participants in non-public assistance households (those that 

do not receive TANF cash assistance, Supplemental Security Income, or General Assistance) as a proxy for the number of ABAWDs. ABAWDs are much more likely 

to be subject to the time limit and cut off SNAP than non-public assistance households overall. ABAWDs are a small fraction of non-public assistance households 

(less than 15 percent) and their distribution across counties will depend on whether 

the time limit is in effect. 

To show that the time limit matters for the distribution of ABAWDs across counties, we again used the SNAP QC data for 2013 and 2017 and again compared the 

states that had a statewide waiver in 2013 and not in 2017 to states that had a 

statewide waiver in both years. As can be seen in Table 11.4, in 2013 when both 

types of states had statewide waivers, the share of non-public assistance participants was not a bad proxy for the share of ABAWDs—their shares differed by only 

two to three percentage points. But in 2017 using the share of non-public assistance 

individuals as a proxy for ABAWDs would overstate the share in areas that were 

not waived—because many ABAWDs had been cut off in 2017—and understate the 

number in waived areas. The share of ABAWDs in states with statewide waivers 

in 2017 was ten percentage points higher in 2017 than the share of non-public asVerDate Aug 31 2005 11:16 Jun 14, 2019 Jkt 041481 PO 00000 Frm 00312 Fmt 6621 Sfmt 6621 P:\DOCS\116-02\36188.TXT BRIAN
307 

466 USDA, ‘‘Guide to Supporting Requests to Waive the Time Limit for Able-Bodied Adults 

without Dependents (ABAWD),’’ December 2, 2016, page 10. 467 7 CFR § 273.24(f)(2), and FNS guidance, ‘‘Supporting Requests to Waive the Time Limit 

for Able-Bodied Adults Without Dependents,’’ December 2016, https://fns-prod.azureedge.net/ 

Continued 

sistance SNAP participants (29 percent vs. 19 percent.) Thus, the methodology in 

the RIA is likely to have substantially underestimated the share of ABAWDs living 

in waived areas in 2016, and projected to live in waived areas in 2020. 

Table 11.4 

Waivers Affect the Number and Share of Non-PA SNAP Participants Fiscal 

Years 2013 and 2017 by whether the state had a statewide waiver 

Non-PA 

Participants 

(in millions) 

Share of 

National 

Non-PA 

Participants 

ABAWDs 

(in millions) 

Share of 

ABAWDs 

Fiscal Year 2013 

States with statewide waivers in 2013 and no waivers in 2017 10.9 28% 1.5 30% 

States with statewide waivers in both 2013 and 2017 6.4 16% 1.0 19% 

Total all states 39.0 100% 4.9 100% 

Fiscal Year 2017 

States with statewide waivers in 2013 and no waivers in 2017 9.1 26% 0.6 19% 

States with statewide waivers in both 2013 and 2017 6.6 19% 0.9 29% 

Total all states 35.2 100% 3.2 100% 

Source: CBPP analysis of FY 2013 and FY 2017 USDA SNAP Household Characteristics data. 

Note: ‘‘Non-PA’’ means not pure public assistance (PA) household. A household is considered to be pure PA if 

each member of the household receives Supplemental Security Income, a cash TANF benefit, or General Assistance income. 

FNS’ Methodology for Determining the Share of Areas That Would Lose Eligibility 

for Waivers Is Incomplete and Confusing 

The RIA includes FNS’ estimate of the number and share of currently waived 

areas that would no longer qualify for a waiver under the proposed rule (755 areas, 

representing 76 percent of areas currently waived), and the share of the impact that 

is attributable to each of the major proposed changes to waiver rules. It also provides an explanation of its methodology for deriving these estimates. However, the 

explanations are incomplete, confusing, and misleading. FNS omits fundamental information needed to assess the integrity of its analysis. For example, it bases the 

analysis on inconsistent periods of time, and provides unclear explanations of its 

methodological assumptions. Understanding which areas and how many areas 

would lose waivers under the proposal is central to understanding the impact of the 

proposed changes, but the analysis FNS included in the RIA has significant flaws 

and lacks sufficient explanation to allow commenters to understand the analysis. 

The proposed rule makes three major changes to the existing rules for determining waiver eligibility: 

1. It sets a minimum unemployment rate of seven percent as a floor for 

waiver eligibility. It makes areas with average unemployment rates below 

this floor ineligible for a waiver, even if their unemployment rates are 20 percent above the national average unemployment rate. In contrast, there is no 

floor under current Federal regulations. (See Chapter 3 for more.) 

2. It restricts states’ flexibility to define combined areas, making federally designated labor market areas the only geographical groups that 

can be eligible for a waiver. In contrast, under current regulations states 

have the discretion to combine areas into larger geographic regions that are 

eligible for a waiver if the regional unemployment rates still meet the eligibility thresholds.466 (See Chapter 5 for more.) 

3. It narrows the allowable criteria for states to request statewide waivers. Under current Federal regulations and FNS guidance, states can request 

statewide waivers based on average state-level unemployment rates that are 

20 percent above the national average over a recent 24 month period; average 

statewide unemployment rates above ten percent for a recent 3 month or 12 

month period; or based on qualifying as a state for extended unemployment 

benefits.467 In contrast, the proposed rule permits to states to request stateVerDate Aug 31 2005 11:16 Jun 14, 2019 Jkt 041481 PO 00000 Frm 00313 Fmt 6621 Sfmt 6621 P:\DOCS\116-02\36188.TXT BRIAN
308 

sites/default/files/snap/SNAP-Guide-to-Supporting-Requests-to-Waive-the-Time-Limit-forABAWDs.pdf. 468 RIA, p. 20. 469 RIA, p. 29. 470 7 CFR § 273.24(f)(2)(ii). 471The proposed rule would add the additional condition that the area’s unemployment rate 

under this calculation be at least seven percent. 472 USDA, ‘‘Guide to Supporting Requests to Waive the Time Limit for Able-Bodied Adults 

without Dependents (ABAWD), December 2, 2016,’’ page 7. 

wide waivers only when they qualify for extended unemployment benefits. 

(See Chapter 4 for more.) 

The problems with FNS’ estimates fall into two main categories: first, the methodology is confusing and incomplete, and second, the discussion of the relative impact 

of the different changes on areas’ eligibility for waivers is misleading. 

The Methodology Is Confusing and Incomplete 

Below are specific problems with the RIA’s methodology that call into question the 

reliability of its estimated impact of the rule provisions on waived counties. 

• FNS’ use of the term ‘‘currently’’ is inconsistent; as a result it is not 

clear what year FNS used for the analysis. Under both current law and the 

proposed rule an area’s eligibility for a waiver for a given fiscal year is based 

on whether the area’s unemployment rate for a specific earlier time period exceeds a threshold that applies to that same time period. Throughout the RIA’s 

discussion of the methodology for determining the impact of the proposed 

changes, FNS uses the term ‘‘currently’’ to refer to the year on which it is basing its estimates. For example, on page 20, where FNS discusses its estimates 

of the number of areas that would lose eligibility for waivers under the proposed 

rule, FNS asserts that ‘‘975 counties and county-equivalents currently have a 

time limit waiver’’ (emphasis added).468 Since FNS issued the NPRM on February 1, 2019, the start of the fifth month of Fiscal Year 2019, it would be reasonable to assume that the term ‘‘currently’’ refers to Fiscal Year 2019. However, nine pages later in a discussion of ‘‘uncertainties’’ associated with all the 

estimates in the RIA, FNS notes that ‘‘these estimates are based on current 

waiver eligibility as of FY 2018.’’ 469 Moreover, as discussed below, it appears 

that the time period FNS used for the data on local area unemployment rates 

is the time period that applies to waiver eligibility for FY 2019. 

FNS’ lack of clarity about the year for which it estimated the change in waiver eligibility calls into question whether it is assessing accurately the impact 

of the proposed changes. 

• There are inconsistencies in FNS’ methodology to estimate of the number of counties that would lose waivers under the proposed rule. The 

analysis reveals inconsistencies in the methodology: 

1. According to current and proposed waiver rules,470 the calculation to determine whether an area is eligible for a waiver for a given fiscal year looks 

at the area’s 24 month average unemployment rate over a defined 

earlier time period and compares it to 20 percent above the national average for the same earlier 24 month period.471 States have to compare 

their areas’ unemployment rates for a 24 month period to an unemployment 

threshold calculated over the same 24 month period. In addition, states 

need to use a 24 month time period that falls within an earlier window that 

is consistent with the year for which the waiver will be implemented.472

Contrary to its own guidance, FNS fails to use consistent periods in its 

analysis: 

a. The 24 month period FNS says it used for the unemployment data 

is inconsistent with the year FNS says it calculated the number of 

waived areas. On page 21, FNS notes that it obtained data ‘‘for the 24 

month period from January 2016 to December 2017 for 3,077 counties 

and county-equivalents.’’ As mentioned, elsewhere the RIA asserts that 

it based its estimates on eligibility for waivers in 2018, but the 24 

month period used for the unemployment data is not the correct period 

for a waiver implemented in 2018. The January 2016 through December 2017 period that the Department used applies to waivers implemented in 2019. The correct period of unemployment data that applied 

to areas eligible for 2018 waivers is January 2015 through December 

309 

473 U.S. Census Bureau, ‘‘New England City and Town Areas (NECTA) Maps,’’ https:// 

www.census.gov/geo/maps-data/maps/nectas.html. 

2016. If FNS is estimating eligibility for waivers in 2018, it should have 

used unemployment data that is applicable to that year. 

b. The Department notes on page 21 that it used unemployment data ‘‘to 

identify currently-waived counties [that] did not have a 24 month [unemployment rate] that exceeds the current waiver threshold.’’ This 

threshold is calculated as 20 percent above the national average unemployment rate for a 24 month period. FNS did not specify which 24 

month period it used to calculate this ‘‘current’’ threshold. This creates 

additional confusion, given that it is already unclear which year the 

Department is using for waived counties and the potential inconsistency with the period for which the unemployment data were collected. 

This also matters because the thresholds are different depending on the 

waiver year FNS is analyzing. For the 24 month period of January 

2016 through December 2017, which corresponds to a 2019 waiver, the 

threshold is 5.5 percent. For the 24 month period of January 2015 

through December 2016, which corresponds to a 2018 waiver, the 

threshold is higher at 6.1 percent. If FNS is comparing county unemployment data that apply to a 2019 waiver to the threshold for a 2018 

waiver, instead of the lower threshold for a 2019 waiver, then it is potentially underestimating the number of waived counties that would 

lose eligibility as a result of restricting area combinations. Although as 

mentioned above, it should have been using data for a 2018 waiver if 

it is evaluating eligibility for 2018. 

2. FNS only collected unemployment data for a single 24 month period, but 

states are allowed to use any 24 month period that is later than the 24 

month period FNS used. FNS’ estimate assumes that all states would use 

the same period of data as the basis of their requests, and that this period 

is representative of the other periods of data that states could use. This is 

unlikely to be the case as unemployment trends change over the course of 

a year, and the first 24 month period is unlikely to accurately represent 

unemployment conditions in other periods that states could use for a waiver 

request. In addition, the decline in unemployment rates in recent years 

means that the threshold for eligibility in subsequent 24 month periods 

generally decreased over the course of 2018. As a result, the restriction 

of area combinations would result in fewer waived counties losing eligibility 

than would be estimated under a single 24 month period. The Department’s 

omission of multiple periods means that it is potentially overestimating the 

number of waived counties that would lose eligibility as a result of restricting area combinations. 

3. Both inconsistencies create opposite biases, the net effect of which FNS 

could demonstrate if it had taken into them into account. The fact that it 

ignores these factors and does not provide a rationale for doing so shows 

the serious lack of rigor in its analysis. 

• FNS fails to adequately explain its exclusion of certain areas from its 

analysis. Footnote 8 on page 21 indicates that FNS excluded five New England 

states (Connecticut, Maine, Massachusetts, New Hampshire, and Vermont) 

when it compiled the unemployment data from the Bureau of Labor Statistics 

(BLS), but FNS does not indicate if it also excluded these states from the list 

of areas that it is counting as currently waived. FNS also does not mention 

these states in the rest of its analysis. As a result of these exclusions, its estimate of the number of currently waived areas is too low. 

The same footnote further explains that FNS excluded these five states because New England counties (also known as NECTAs) are conceptually dissimilar to counties in the rest of the United States. However, Rhode Island, 

which contains the Providence-Warwick, RI–MA NECTA, does not appear on 

the list of excluded states. The Department fails to mention why it included 

Rhode Island, which shares the same New England dissimilarities with the 

other states.473 It briefly notes that ‘‘some NECTAs are quite small’’ and ‘‘BLS 

data was not consistently available for these areas,’’ which appears to be a reference to the BLS’ discontinuation in 2018 of unemployment data for all cities 

310 

474 U.S. Bureau of Labor Statistics, ‘‘Local Area Unemployment Statistics,’’ https:// 

www.bls.gov/lau/laugeo.htm. 475 RIA, p. 21. 476 USDA, ‘‘Guide to Supporting Requests to Waive the Time Limit for Able-Bodied Adults 

without Dependents (ABAWD),’’ December 2, 2016, page 3. 

and towns with populations below 1,000 for all New England states.474 As 

Rhode Island does not contain towns with populations below 1,000, BLS data 

would be available for all areas. If this were the reason for its inclusion in the 

FNS analysis, this would be consistent with its rationale. But FNS provides no 

information to help understand its rationale. 

In addition, the Department does not explain how it treats Guam and the Virgin Islands in its analysis. Although the Bureau of Labor Statistics does not 

produce employment data for these U.S. territories, these areas were also 

waived in 2018 but it is unclear if they are included in the number of currently 

waived areas or in the number that would lose waivers under the proposed rule. 

• FNS fails to adjust the number of waived areas for 2020, the year in 

which the proposed rule would be in effect if implemented. FNS unrealistically assumes no changes in waivers in future years. It fails to adjust for 

the fact that the number of areas is likely to be lower in FY 2020, the year in 

which the proposed rule would first apply if implemented. As unemployment 

rates have declined, states have applied and qualified for fewer areas in 2017, 

2018, and 2019. It would be realistic to assume a decline in waived areas in 

2020 and later years as well. 

• FNS only examined the impact of the proposal in a year when unemployment rates declined. FNS only examined the impact of its proposal in 

2018, a year in which the unemployment rates declined. It did not analyze the 

proposal’s impact during a time of rising unemployment rates, such as prior to 

or during a recession. FNS did not offer any rationale for this exclusion. Expanding its analysis to many periods with rising and decreasing unemployment 

trends would have provided a fuller understanding of the impact of the proposed rule in different economic conditions. 

• FNS does not explain its estimation of the number of areas losing eligibility due to the narrowing of statewide waivers. FNS provided no details 

about its methodology for estimating the effect of narrowing the criteria that 

can be used for statewide waivers, beyond noting that it ‘‘estimated the number 

of counties and county-equivalents that would lose waiver eligibility due to the 

elimination of statewide waivers.’’ 475 It identified an additional 39 counties eligible only because of a statewide waiver and subtracted those from its total of 

waived areas that would still be eligible under the rule after already eliminating the areas that were eligible only based on states’ ability to combine data. 

Based on the explanations in the analysis, it is unclear why FNS needed to subtract out these 39 counties since all of them would already be ineligible for 

waivers under the rule because their data could not be combined with the data 

of other areas in the state. The description of the methodology is confusing. It 

is possible that FNS was estimating the impact of the narrowing of statewide 

waivers separately from the impact of combining data or the seven percent 

threshold. Table 3 on page 22 of the RIA presents the results as if FNS included 

the narrowing of statewide waivers as one step within the estimation. If that 

is not the case, then the methodology is poorly explained. 

On the other hand, if the narrowing of statewide waivers is a step in its overall estimation, then it appears that FNS subtracted the same counties twice. 

The elimination of counties that did not meet the waiver threshold (described 

in the second paragraph on page 21) would already have removed counties that 

are ineligible based on their own unemployment rates. This would not leave any 

counties that are eligible based only on being in a state with a statewide waiver. This additional subtraction would inflate FNS’ estimate of counties that 

would lose their waivers due to narrowing of statewide waivers. 

• FNS ignores extended benefits as a standard for qualifying for statewide waivers. FNS does not mention that some states would remain eligible 

for statewide waivers under the proposed rule, based on qualifying for extended 

unemployment benefits (EB). Under current FNS guidance on qualifying for a 

waiver based on qualifying for EB, which the proposed rule does not change, 

states can request statewide waivers that start no later than 1 year after the 

date that the state qualified for EB.476 Alaska and the District of Columbia 

qualified for EB in January 2018, and therefore would have been able to reVerDate Aug 31 2005 11:16 Jun 14, 2019 Jkt 041481 PO 00000 Frm 00316 Fmt 6621 Sfmt 6621 P:\DOCS\116-02\36188.TXT BRIAN
311 

477 RIA, p. 22. 

quest statewide waivers in 2018 (and 2019). For either year these two areas 

count as an additional nine county-equivalents. FNS omission of this factor also 

inflates the estimate of counties that would lose their waiver under the proposed rule because these two areas would not have lost their waivers. 

• FNS does not analyze the impact of its rules on Native American reservations or on New England towns. FNS does not provide any analysis of 

the impact of the proposed rule on Native American reservations or on New 

England towns and cities. This is a glaring omission, because Native American 

reservations tend to have high poverty rates well above the national average, 

and over 200 reservations were waived or were located inside a waived area in 

2018. This is an important segment of the population that FNS analysis ignores 

completely. 

Similarly, 281 towns and cities in the New England states of Connecticut, 

Massachusetts, New Hampshire, Vermont, and Rhode Island were waived in 

2018, constituting nearly a quarter of all towns in these states. Although the 

Bureau of Labor Statistics has stopped publishing unemployment data for New 

England towns with populations below 1,000 people, it continues to provide data 

for towns above 1,000 people. It is unclear why the Department does not examine the rule’s impact on those towns with higher populations. 

The methodological problems listed above cast serious doubt on the reliability of 

the FNS overall estimate of the impact of the proposed rule on ‘‘currently waived’’ 

areas. 

FNS’ Estimates of the Relative Impacts of the Rule Provisions on Waived 

Areas Is Misleading 

In Table 3 on page 22 of the RIA, FNS indicates that the three different changes 

in the proposed rule result in a cumulative 76 percent reduction in the number of 

waived areas. FNS then describes the relative impact of the three different changes 

in the proposed rule, asserting that the change to restrict area combinations reduces 

the number of areas waived by 36 percentage points, the change to statewide waivers reduces the number by four percentage points, and the seven percent unemployment rate floor reduces the number by 37 percentage points. However, the order 

FNS uses for these calculations presents misleading results. 

FNS’ presentation suggests that the proposed change to restrict area combinations 

and the seven percent floor have a roughly equal impact. The presentation is misleading, however, because, although restricting the ability to combine areas would 

have a substantial impact by itself relative to current rules, the seven percent floor 

has a far larger effect on areas’ eligibility for waivers because seven percent is substantially higher than the national average unemployment threshold. As a result, 

all of the areas that would lose because they cannot be combined with adjacent 

areas would also lose under a seven percent floor. An example using FNS’ own numbers (despite their flaws) can be helpful to understand why: 

Under FNS’ estimates, out of 975 counties currently waived, 220 have ‘‘a 24 

month [unemployment average] of at least seven percent and would continue to 

qualify for a waiver under the proposed waiver criteria.’’ 477 That means 755 waived 

counties, or 76 percent of all counties currently waived would lose their waiver due 

solely to the seven percent floor. The additional impact of restricting area combinations would be zero at that point. 

This occurs because seven percent is higher than the 20 percent above the national 24 month average threshold (which would be 6.1 percent for 2018 or 5.5 percent for 2019, though as discussed above, it’s not clear which year FNS used for the 

analysis.) Implementing a seven percent minimum unemployment rate automatically eliminates any waived counties with rates below 5.5 and 6.1 percent, and the 

waived counties with rates above 5.5 and 6.1 percent but below seven percent. The 

impact of the floor is therefore greater, as it eliminates counties that are eligible 

based on their own 24 month average unemployment rates but do not meet the 

floor, in addition to the counties waived through area combinations. 

The RIA Assumes That All ABAWDs in Areas That Lose Waivers Will Lose SNAP; 

An Assumption That Ignores That Many Will Be Exempt or Able to Participate 

for Other Reasons 

As mentioned above, in determining the impact of the change in waivers on SNAP 

participants, the RIA assumes that 1.5 million ABAWDs would live in areas that 

would be waived under current rules. Under the proposed changes, the RIA assumes 

that: 

312 

478 RIA, p. 25. 479 RIA, p. 26. 

Because waived areas are estimated to be reduced by 76 percent under the 

revised waiver criteria, the department assumes that 76 percent of currentlywaived ABAWDs would be newly subject to the time limit. This equals approximately 1.1 million of the estimated 1.5 million currently waived individuals.478

Under this assumption, no individuals who are defined as ‘‘ABAWDs’’ (using the 

Department’s definition) in the areas that lose waivers would be: 

• exempted from the time limit because of being physically or mentally unfit; 

• pregnant; 

• participating because they are eligible during the first 3 months of participation 

or qualify for a second 3 month period; 

• exempt using individual ‘‘percentage’’ exemptions; 

• participating in a qualifying work program; or 

• working (or complying with a qualifying work program), for less than the required 20 hours per week. 

This assumption defies logic and ignores the evidence from other states that have 

a time limit in effect. In every state without waivers there are ‘‘ABAWDs’’ who are 

able to continue to participate for these reasons. As we showed above, in Tables 11.1 

and 11.2, in the states that reinstated the time limit by 2017, the number of 

‘‘ABAWDs’’ declined substantially, from 1.5 million in 2013 to 600,000 in 2017, but 

even if we subtract out the number of ‘‘ABAWDs’’ who were working at least 20 

hours a week (138,000), that still leaves almost 1⁄2 million ‘‘ABAWDs’’ participating 

in SNAP in 2017 after the time limit went back into effect. 

The assumption that none would continue to participate for any of these reasons 

is a glaring error in the RIA methodology. As a result, the public is left not knowing 

how many people who are potentially subject to the time limit will be able to continue to participate and for which reasons, and whether the Department knows or 

cares. 

The RIA’s Assumption That One-Third (34 Percent) of ABAWDs Subject to the Time 

Limit in Areas That Lose Waivers Will Remain Eligible Because They Would 

Be Working 20 Hours a Week Is Flawed 

Of the 1.1 million ‘‘ABAWDs’’ the Department estimates would be newly subject 

to the time limit under the proposed rule, the RIA assumes 1⁄3 would be working 

and 2⁄3 would ‘‘lose their eligibility for SNAP for failure to engage meaningfully in 

work or work training:’’ 

Using FY 2016 QC data, approximately 26 percent of ABAWDs were working. 

The Department assumes that this proportion would increase to about 34 percent in FY 2020 if the UR [unemployment rate] declines as projected in the 

2019 President’s Budget and that these individuals will work at least 20 hours 

per week. Under this scenario, the Department estimates that approximately 1⁄3

of ABAWDs newly subject to the time limit will work and maintain their SNAP 

eligibility. The remaining 2⁄3 (755,000 individuals) would lose their eligibility for 

SNAP for failure to engage meaningfully in work or work training.479

This assumption is flawed for several reasons: 

• First, the assumption being used (the 26 percent working in 2016, rising to 34 

percent in 2020) was derived from the entire SNAP population of ‘‘ABAWDs’’ 

nationally, including both areas that currently are waived and those that are 

not waived. As we demonstrated above, the work rates of SNAP participants 

who live in areas without waivers are higher simply because many people who 

are not able to find jobs or document their work have been cut off. It is confusing to apply a percentage derived from the entire caseload, where many 

states have a large share of individuals who live in area without waivers, to 

areas with waivers. 

• Second, in 2017 only 12 percent of ‘‘ABAWDs’’ in states that had statewide 

waivers in 2017 were working at least 20 hours a week—the threshold for individuals subject to the time limit to remain eligible for SNAP. The RIA assumes 

a share almost triple that (34 percent) would be able to meet the 20 hours a 

week threshold, with no explanation for why or how that would occur. 

313 

480 John L. Czajka, et al., ‘‘Imposing a Time Limit on Food Stamp Receipt: Implementation 

of the Provisions and Effects on Food Stamp Program Participation: Final Report,’’ prepared by 

Mathematica Policy Research for the USDA, Food and Nutrition Service, September 4, 2001, 

https://fns-prod.azureedge.net/sites/default/files/abawd.pdf, p. xxv. 481 NPRM, p. 981. 482 NPRM, p. 981. 483 U.S. Department of Agriculture, Food and Nutrition Service, ‘‘Supplemental Nutrition Assistance Program—ABAWD Time Limit Policy and Program Access,’’ November 19, 2015, 

https://fns-prod.azureedge.net/sites/default/files/snap/ABAWD-Time-Limit-Policy-and-Program-Access-Memo-Nov2015.pdf. 

The RIA’s Assumes That All Individuals Who Lose Eligibility Will Reapply Every 

Three Years 

When estimating the effect of the change on Federal spending the RIA assumes 

the impact will be felt over only 9 months in 2020 and 2023, presumably based on 

an assumption that people who have been cut off because of the 3 month time limit 

will reapply immediately when they become eligible again after 3 years, but it provides no evidence that this occurs. To the contrary, a study FNS published in 2001 

of state implementation of the time limit found: 

Many ABAWDs who left the program have not returned. ABAWDs who 

used up their time-limited benefits in 1997 became eligible again in 2000, creating the potential for a sharp upswing in participation, yet the trend in participation shows no such change.480 (Bold emphasis in original.) 

G. The RIA Lacks Transparency About the Reasons Individuals May Lose SNAP and 

Other Possible Impacts If Waivers Are Narrowed 

As noted, the proposed rule’s fundamental rationale is that taking away (or 

threatening to take away) food assistance will cause people not currently working 

to get jobs. The NPRM asserts that ‘‘these changes would encourage more ABAWDs 

to engage in work or work activities if they wish to continue to receive SNAP benefits,’’ 481 and, ‘‘[t]he application of waivers on a more limited basis would encourage 

more ABAWDs to take steps towards self-sufficiency.’’ 482

However, the only impact that FNS quantifies in the RIA comes from the estimated, ‘‘755,000 individuals . . . [who] would not meet the requirements for failure 

to engage meaningfully in work or work training.’’ The rationale and the estimated 

impact are inconsistent. Moreover, the assessment lacks transparency about what 

the impact would be and it over-simplifies the possibilities. Other FNS materials indicate that FNS is aware that when the time limit is in effect it results in different 

outcomes for different groups of people. Many people participate in SNAP for a period of time and then leave when their circumstances change. But, when faced with 

a time limit there are a range of possible outcomes and impacts. For example: 

• Some individuals may find work or additional hours and as a result their SNAP 

benefits may go down as a result of income they would not have otherwise had. 

• Others may wish to comply but be unable to find a job. For these individuals 

there is a question of whether a qualifying slot in an Employment and Training 

program would be available. If there is no slot then that individual would likely 

lose SNAP. If there is, FNS and states would potentially incur a cost for the 

E&T services. FNS does not contemplate any changes in E&T that might be 

caused by the proposed rule. 

• Other individuals may qualify for an exemption for ‘‘unfitness for work,’’ or another reason, but may lose SNAP if they don’t realize they could qualify for an 

exemption because it was not properly explained to them, or if they are unable 

to get documentation of their health issue because they lack medical coverage. 

• Others may actually be working, but not comply with paperwork requirements 

to document their hours of work. 

• And, although unlikely, other individuals who are able to work may intentionally choose not to comply with the time limit and lose SNAP benefits. 

This list is not exhaustive. But FNS guidance in recent years makes clear that 

it is aware of both the range of possible outcomes and the fact that the distribution 

of outcomes can be influenced by state implementation choices. For example, in November 2015, FNS issued guidance that reminded states that in addition to tracking 

months of participation, ‘‘States must also carefully screen for exemption from the 

time limit and connect ABAWDs to the information and resources necessary to 

maintain eligibility consistent with Federal requirements.’’ 483 The guidance covered 

314 

484 U.S. Department of Agriculture, Food and Nutrition Service, ‘‘SNAP—Requirements for Informing Households of ABAWD Rules,’’ April 17, 2017, https://fns-prod.azureedge.net/sites/default/files/snap/Requirements_for_Informing_Households_of_ABAWD_Rules.pdf. 485 U.S. Department of Agriculture, Food and Nutrition Service, ‘‘SNAP—Best Practices and 

Resources for Informing Households of ABAWD Rules,’’ May 25, 2018, https://fnsprod.azureedge.net/sites/default/files/snap/BestPracticesforInformingABAWDS.pdf. 486 U.S. Department of Agriculture, ABAWD 15 Percent Exemptions Data, https:// 

www.fns.usda.gov/snap/abawd-15-percent-exemptions. 

several areas where state implementation could affect individuals’ eligibility, for example: 

• ‘‘Screening for Exemptions and Fitness for Work’’; 

• ‘‘Maintaining Eligibility through Work Programs and Workfare’’: 

• ‘‘Maintaining Eligibility through Unpaid or Volunteer Work’’; and 

• ‘‘Good Cause for Failure to Meet the ABAWD Work Requirement.’’ 

Another FNS guidance focused on states’ responsibilities to adequately notify individuals who are potential ABAWDs on the details of the time limit, work requirement, exemptions, and their responsibility to report changes in work hours.484 FNS 

followed this with another guidance that outlined best practices and provided model 

language to ‘‘help state agencies effectively inform Supplemental Nutrition Assistance Program (SNAP) households of the requirements for able-bodied adults without 

dependents (ABAWD) and to enrich training for eligibility workers.’’ 485

The RIA oversimplifies the various impacts of the rule. Research has found, and 

FNS is aware, that in practice work requirements result in individuals experiencing 

benefit cuts for a variety of reasons, including when they cannot find jobs, when 

they should have been found exempt from the requirement, and when they are 

working but fail to comply with paperwork requirements. FNS failed to adequately 

reflect the various possible reasons why individuals would lose SNAP under the proposed rule and as a result failed to adequately explain or consider its impact. 

H. The RIA’s Estimate of No Impact From Eliminating the Carryover of Exemptions 

Is Confusing and Misleading 

The proposed rule would eliminate states’ ability to ‘‘carry over’’ exemptions that 

go unused in 1 year into future years. The RIA includes two confusing and misleading assumptions about state use of exemptions—one about current state use of 

exemptions and the other about how states would use exemptions under the proposed rule. 

The RIA dramatically overstates the number of exemptions states have 

used in recent years. The RIA methodology includes an assumption that ‘‘states 

use approximately 65 percent of their earned exemptions in an average year.’’ This 

assumption implies that many states use a large share of their annual exemptions 

each year. This is a significant misrepresentation of the pattern of state use of exemptions. 

A closer look at the data FNS posts about the pattern of state use and accrual 

of exemptions 486 shows that the actual pattern is that: 

• many states have not used any exemptions in most years; 

• some states have used a small share of the exemptions they earned for that 

year; 

• a few states have used the majority of the exemptions they earned for that year; 

• a few states have not earned exemptions for a year but have dipped into their 

accrued exemptions; and 

• a handful of states have used more exemptions than they earned in a given 

year. 

The last two categories result in the number of used exemptions as a share of 

earned exemptions for that year exceeding 100 percent in that state. Across all 

states this will raise the total share of exemptions used because the denominator 

for the percentage is the number of exemptions earned for that year (as it appears 

to be for the FNS assumption.) See Table 11.5, below, for the distribution of states 

across these categories. You can see that the small number of states in the last two 

categories is playing an outsized role in raising the total share across all the states. 

315 

487 RIA, p. 24. 

Table 11.5 

State use of exemptions 2014–2018 

Number of States 2014 2015 2016 2017 2018 a

Using no exemptions 43 41 21 19 N/A 

Using less than 50% of earned exemptions 4 7 15 26 N/A 

Using 51–100% of earned exemptions 1 2 0 5 N/A 

Using more than 100% of earned exemptions 2 0 2 1 N/A 

Used exemptions but earned none for that year 3 3 15 2 N/A 

Average exemptions used as a share of earned 93% 27% 149% 23% N/A 

Total exemptions used 230,000 115,000 730,000 300,000 1,300,000 

Source: CBPP analysis of FNS-posted data on exemptions https://www.fns.usda.gov/snap/abawd-15-percentexemptions. a According to the RIA (p. 23), ‘‘In FY 2019 state carried over approximately 6.1 million unused exemptions from 

the prior year.’’ Since, according to FNS data, states carried 7.4 million exemptions into FY2018 they must have 

used about 1.3 million exemptions in FY 2018 (7.4 million¥1.3 million = 6.1 million.) 

Thus, FNS’ statement that ‘‘States use approximately 65 percent of their earned 

exemptions in an average year’’ is highly misleading. In fact, across all states and 

the 4 years between 2014 and 2017 only eight states used between 51 and 100 percent of their exemptions. The vast majority used none, some used less than 50 percent, and a handful used more than 100 percent. 

FNS’ assumption that eliminating the exemption carryover would have 

no impact is indefensible. FNS estimates the number of exemptions that would 

be taken away from states and concludes that the rule would eliminate 6.6 million 

case-months of carryover exemptions the first year (FY 2020) and 160,000 to 

180,000 a year in later years. 

FNS estimates no impact from the proposed change to eliminate states’ past and 

future exemptions from prior years, saying: 

It is difficult to estimate the impact of such a change on transfer spending 

because there is no historical record to support an estimate of if and when such 

a ‘‘run on the bank’’ may occur. Current practice by the states suggests that 

elimination of the carryover will have no change on transfers as the exemptions 

that will expire represent exemptions that were not distributed to covered individuals (i.e., no transfer is occurring, so no transfer can be reduced.) However, 

elimination of the carryover will give the Federal Government greater predictability over potential spending requirements because the number of exemptions 

subject to the sole discretion of the states is smaller.487

The assumption of no change in Federal spending from eliminating so many exemptions is highly misleading and contrary to the experience of the last 23 years. 

Virtually every state has used waivers at some point since 1996, and most states 

have used exemptions in some years, making clear that in some economic situations 

and under some political leadership states wish to shield some SNAP recipients who 

are subject to the time limit from losing SNAP. 

Some states have used exemptions to suspend the time limit in areas where no 

E&T services are available or to transition counties from waiver status to non-waiver status and give the area time to establish or expand employment and training 

opportunities to meet the needs of individuals subject to the time limit. Other states 

have used exemptions to continue to provide SNAP to certain SNAP participants 

who would be cut off because of the time limit but who they determine should continue to receive SNAP, such as individuals who are working, but less than 20 hours 

in a particular month, or individuals who recently have been released from incarceration. 

The information that FNS makes public about exemption usage in recent years 

shows that as many areas have no longer been waived in recent years, states have 

increased their use of exemptions. It seems highly likely that if the rule went into 

effect and states faced losing waivers for a large share of the counties in their state 

with the highest unemployment rates, many would opt to draw down more exemptions, and, over time, to draw down the balances of their exemptions that they have 

been allowed to carry over. 

Another example of when states may use exemptions is when the political leadership in a state changes to be more sympathetic to the harshness of the time limit. 

In that case states might establish a policy that begins to use exemptions and use 

them at a higher rate than the number that are accrued each year. The carryover 

exemptions would allow such a state to sustain a larger exemption policy for several 

years. 

316 

488State Medicaid Director Letter, January 11, 2018, https://www.medicaid.gov/federal-policy-guidance/downloads/smd18002.pdf. 489Steven Carlson and Brynne Keith-Jennings, ‘‘SNAP is Linked with Improved Nutritional 

Outcomes and Loer Health Care Costs,’’ Center on Budget and Policy Priorities, January 17, 

2018, https://www.cbpp.org/research/food-assistance/snap-is-linked-with-improved-nutritionaloutcomes-and-lower-health-care. 490 NPRM, p. 989. 491 NPRM, p. 990. 

The assumption that no carried over exemptions would ever be used is indefensible, especially in combination with the changes the proposed rule would make to 

the share of the United States that could qualify for waiver. 

I. The RIA Fails to Accurately Reflect the Impact of the Proposed Rule on Medicaid 

and Health Coverage and Other Secondary Impacts 

The Centers for Medicare and Medicaid Services of the Department of Health and 

Human Services, the agency that administers the Medicaid program, has required 

some alignment between SNAP and Medicaid work requirements. Specifically, 

states must count enrollment in SNAP as an automatic exemption from Medicaid 

work requirements since individuals enrolled in SNAP are either exempt from or 

complying with SNAP work requirements.488

As a result, the proposed rule’s changes to SNAP waiver and exemption policy 

would have a direct ripple effect on individuals’ Medicaid eligibility and coverage. 

More people in states with Medicaid work requirements would be subject to those 

work requirements, and a large number would very likely lose Medicaid coverage. 

The per-person cost of health coverage often is higher than the monthly SNAP benefit. The Federal budget savings and the impact on individual’s health coverage 

from this direct link between SNAP and Medicaid under the Administration’s policies should have been reflected in the RIA’s cost-benefit analysis. The RIA’s failure 

to mention and quantify these effects is a serious oversight that fails to accurately 

reflect the full impact of the proposed rule. 

Moreover, the RIA does not mention nor quantify several secondary effects that 

SNAP benefit cuts could have. For example: 

• SNAP benefits are one of the fastest, most effective forms of economic 

stimulus when the economy is weak. Low-income individuals generally 

spend all of their income meeting daily needs such as shelter, food, and transportation, so every dollar in SNAP that a low-income family receives enables 

the family to spend an additional dollar on food or other items. Moody’s Analytics estimated that every $1 increase in SNAP benefits during 2009, when the 

economy was in a recession, generated about $1.70 in economic activity. 

• SNAP has been found to improve some recipients’ health outcomes. 

SNAP is associated with better health and lower health care costs, according 

to a growing body of evidence.489

Chapter 12. The Proposed Rule Would Disproportionately Impact Individuals Protected by Civil Rights Laws, Violating the Food and Nutrition 

Act’s Civil Rights Protections 

According to FNS estimates, under the proposed rule some 755,000 individuals 

would lose eligibility for SNAP because of a ‘‘failure to engage meaningfully in work 

or work training.’’ 490 As described in detail in Chapter 3, evidence from the research 

on the impact of work requirements and time limits, as well as the disparities in 

unemployment in the labor market make clear that the cuts to SNAP eligibility 

from the proposed rule would fall disproportionately on African Americans, Latinos, 

and people with disabilities. In addition, Native Americans also would experience 

a disproportionate impact from the proposed rule because individuals who are Native American, whether or not they reside on Indian reservations, also have poverty 

and unemployment rates well above the national average, and many of the over 200 

reservations that were waived or were located inside a waived area in 2018 would 

likely lose their waivers under the proposed rule. 

In the civil rights impact analysis included in the NPRM, FNS recognizes the disproportionate impact, citing the rule’s ‘‘potential for disparately impacting certain 

protected groups due to factors affecting rates of employment of members of these 

groups.’’ 491 But the analysis finds that ‘‘the implementation of mitigation strategies 

and monitoring by the Civil Rights Division of FNS will lessen these impacts,’’ without providing any evidence or examples of how that mitigation could occur. It is not 

clear how the Civil Rights Division of FNS could mitigate an eligibility policy that 

inherently results in a disproportionate impact on certain groups. We cannot comment on the potential effectiveness of such efforts when the NPRM does not provide 

317 

492The Food, Conservation, and Energy Act of 2008 (P.L. 110–246), section 4117. 493Section 11(c) of the Food and Nutrition Act of 2008, 7 U.S.C. § 2020(c). 494 Congressional Record, May 22, 2008, p. H3814, https://www.govinfo.gov/content/pkg/ 

CREC-2008-05-14/pdf/CREC-2008-05-14-pt1-PgH3801-3.pdf#page=13. 495 Congressional Record, May 22, 2008, p. S4747, https://www.congress.gov/crec/2008/05/ 

22/CREC-2008-05-22-pt1-PgS4743-3.pdf. 

any information about what they might be and no similar interventions have occurred in the history of the program. If FNS envisions giving the Civil Rights Division a role in determining eligibility for waivers—which the Division apparently has 

not had to date—it says nothing about that in the NPRM and we cannot readily 

imagine how that would work. Even if it did, without anything in the rule varying 

the effects of the new standards it imposes, states would be unlikely to request the 

kinds of waivers that might mitigate the rule’s disparate impact on members of protected groups. 

Moreover, even if mitigation of the disparate impact were possible, the fact that 

the proposed rule still would have a disproportionate impact on these protected 

groups directly violates Section 11(c)(2) of the Food and Nutrition Act (7 U.S.C. 

§ 2020(c)(2)). In the 2008 Farm Bill Congress reasserted its commitment to nondiscrimination and made clear that certain civil rights laws apply to SNAP: 492

(c) CIVIL RIGHTS COMPLIANCE.— 

(1) IN GENERAL.—In the certification of applicant households for the supplemental nutrition assistance program, there shall be no discrimination by 

reason of race, sex, religious creed, national origin, or political affiliation. 

(2) RELATION TO OTHER LAWS.—The administration of the program by a 

state agency shall be consistent with the rights of households under the following laws (including implementing regulations): 

(A) The Age Discrimination Act of 1975 (42 U.S.C. 6101 et seq.). 

(B) Section 504 of the Rehabilitation Act of 1973 (29 U.S.C. 794). 

(C) The Americans with Disabilities Act of 1990 (42 U.S.C. 12101 et 

seq.). 

(D) Title VI of the Civil Rights Act of 1964 (42 U.S.C. 2000d et 

seq.).493

Of particular note is that, under this amended language, the regulations implementing Title VI and other civil rights statutes are fully applicable to SNAP. These 

regulations prohibit actions in Federal programs that have disparate impacts on 

members of protected groups as well as intentional discriminatory acts. Therefore, 

the proposed rules’ disparate impact on these individuals, as demonstrated by the 

research and conceded in the NPRM itself, is inconsistent with the Act. Key Members of Congress made unmistakably clear that this is what the 2008 amendments 

sought to accomplish. 

In his floor statement on the 2008 Farm Bill, Representative Joe Baca, who at 

the time was the Ranking Member of the House Agriculture Subcommittee on Departmental Operations, Oversight, Nutrition and Forestry, explained: 

. . . this legislation makes clear that the [Agriculture] Department’s civil 

rights regulations are among those which have the full force of law and which 

households have the right to enforce. Discrimination is not acceptable in any 

form or at any point in the food stamp certification process. Households should 

not be assisted, or not assisted, approved or denied for any reason other than 

an individual assessment of their need for help or their eligibility by the 

state.494

Senator Dick Durbin, a leading Member of the Senate Judiciary Committee, in 

his floor statement on the 2008 Farm Bill similarly stated that ‘‘This legislation also 

makes explicit that various civil rights laws are binding in the Food Stamp Program. This is not a change—these laws and their regulations have applied since 

they were written, and both have been intended to be fully enforceable.’’ 495

Given this clear expression of Congressional intent, FNS may not by regulation 

exacerbate discrimination within SNAP based on race, ethnicity, or disability. Since 

FNS recognizes that the proposed rule would have discriminatory effects, it must 

withdraw the rule. 

Chapter 13. The Proposed Rule Fails to Adequately Estimate the Impact on 

Small Entities 

The Regulatory Flexibility Act (5 U.S.C. § 601–612) requires agencies to analyze 

the impact of a proposed rule specifically on small businesses and entities through 

318 

496 Regulatory Flexibility Act, 5 U.S.C. § 603, https://www.sba.gov/advocacy/regulatory-flexibility-act. 497 Center on Budget and Policy Priorities, ‘‘Unemployed adults without children who need 

help buying food only get SNAP for three months,’’ https://www.cbpp.org/unemployed-adultswithout-children-who-need-help-buying-food-only-get-snap-for-three-months. 498Dottie Rosenbaum, ‘‘Many SNAP Households Will Experience Long Gap Between Monthly 

Benefits Despite End of Shutdown,’’ Center on Budget and Policy Priorities, revised February 

4, 2019, https://www.cbpp.org/research/food-assistance/many-snap-households-will-experiencelong-gap-between-monthly-benefits. 499 Ibid. 500 Regulatory Flexibility Act, 5 U.S.C. § 603, https://www.sba.gov/advocacy/regulatory-flexibility-act. 501 Ibid. 

an initial regulatory flexibility analysis. The Regulatory Flexibility Act specifically 

mandates that the analysis must contain a series of arguments including, but not 

limited to: why action by the agency is being considered, what the legal basis is for 

the proposed rule, and an estimate to the number of small entities to which the rule 

would apply.496 The FNS failed to undertake the necessary research regarding the 

impact of this rule on all small entities, with the proposed rule offering only a brief 

impact report with minimal analysis that fails to accurately or adequately assess 

the impact of the proposed rule. 

The FNS claims that aside from program participants, the proposed rule would 

primarily impact state agencies. This assessment leaves out a key group of impacted 

stakeholders—small SNAP retailers, who rely on SNAP purchases for consistent 

and dependable revenue. The Department incorrectly assumes that after losing benefits, people would replace their monthly SNAP allotment with cash. The individuals impacted by this NPRM are a very low-income group, as approximately 70 percent of all ‘‘ABAWD’s’’ are below 1⁄2 of the Federal poverty line.497 They do not tend 

to have disposable income, and taking away their SNAP benefits would take away 

their ability to purchase food. Additionally, SNAP benefits normally run out for 

most households before the end of the month.498 Many households spend their benefits rapidly because they are funds designated specifically for food. Cash cannot be 

used to replace SNAP because these dollars are needed to pay other expenses such 

as rent, clothing, gasoline, and many other necessities.499 The Department’s primary and false assumption that SNAP is supplemental rather than essential lays 

an untrue foundation for the argument that small retailers would not be disproportionately impacted. 

Additionally, the NPRM includes an inaccurate estimate of the number of small 

retailers that would be impacted. This leaves the public and stakeholder groups illinformed about the potential implications of the rule. A small retailer at risk of 

being significantly harmed by the proposed rule would not understand the importance of the issue solely by reading the NPRM and Regulatory Impact Analysis due 

to the failure to scale the estimation exclusively to the impacted areas. This section 

will review which pieces of the Regulatory Flexibility Act were not adequately covered, the impact and magnitude of the inaccurate estimation of impacted small businesses in the NPRM, and which areas would be disproportionately or significantly 

impacted across the United States. 

A. Inadequately Addressed Sections of the Regulatory Flexibility Act 

The primary area of concern within the Regulatory Flexibility Act (R.F.A.) is 

§ 603—Initial regulatory flexibility analysis.500 According to the R.F.A. § 603, an 

agency publishing an NPRM is required to do the following: 501

(b) Each initial regulatory flexibility analysis required under this section shall 

contain— 

(1) a description of the reasons why action by the agency is being considered; 

(2) a succinct statement of the objectives of, and legal basis for, the proposed rule; 

(3) a description of and, where feasible, an estimate of the number of 

small entities to which the proposed rule will apply; 

(4) a description of the projected reporting, recordkeeping and other compliance requirements of the proposed rule, including an estimate of the 

classes of small entities which will be subject to the requirement and the 

type of professional skills necessary for preparation of the report or record; 

(5) an identification, to the extent practicable, of all relevant Federal 

rules which may duplicate, overlap or conflict with the proposed rule. 

319 

502 CBPP Internal Analysis of U.S. Department of Agriculture, Food Environment Atlas Data 

2018. 503 Regulatory Flexibility Act, 5 U.S.C. § 609(a)(1) https://www.sba.gov/advocacy/regulatoryflexibility-act. 504 NPRM, Regulatory Flexibility Act https://www.federalregister.gov/d/2018-28059/p-118. 505 CBPP Analysis of BLS Unemployment data, 2019. 506 U.S. Department of Agriculture, Food Environment Atlas Data 2018 https:// 

www.ers.usda.gov/data-products/food-environment-atlas/data-access-and-documentationdownloads/. 507 CBPP Internal Analysis of U.S. Department of Agriculture, Food Environment Atlas Data 

2018. 508 CBPP Internal Analysis of U.S. Department of Agriculture, Food Environment Atlas Data 

2018. 

(c) Each initial regulatory flexibility analysis shall also contain a description 

of any significant alternatives to the proposed rule which accomplish the stated 

objectives of applicable statutes and which minimize any significant economic 

impact of the proposed rule on small entities. Consistent with the stated objectives of applicable statutes, the analysis shall discuss significant alternatives 

such as— 

(1) the establishment of differing compliance or reporting requirements or 

timetables that take into account the resources available to small entities; 

(2) the clarification, consolidation, or simplification of compliance and reporting requirements under the rule for such small entities; 

(3) the use of performance rather than design standards; and 

(4) an exemption from coverage of the rule, or any part thereof, for such 

small entities. 

The provided regulatory flexibility analysis in the NPRM fails to include a detailed description required by § 603(b)(1) and § 603(b)(2), as the analysis includes no 

legal basis for the proposed rule or why the agency is considering the action. Additionally, § 603(b)(3) mandates an estimate of the number of small entities impacted. 

The agency provides an estimate, but that estimate is flawed as we show below.502

By inaccurately estimating the number of small entities that would be impacted 

by the proposed rule, the Department assumed it was not required to satisfy other 

requirements in the Act. For example, § 609(a)(1) states that when a rule is introduced that will have a significant economic impact on small entities; the respective 

agency must provide a statement or notice to the effect on small entities.503 Providing an imprecise estimate, the Agency is able to argue that no significant impact 

will be made, keeping small entities uninvolved with the rulemaking process. In addition, § 603(c) of the RFA requires a description of potential alternatives to the proposed rule. The NPRM fails to provide any possible alternatives because the proposed rule inaccurately asserts that there is no disproportionate impact on small entities, falsely excusing them from additional requirements. Incorrectly estimating 

the number of small businesses not only represents a lack of specificity, it more importantly exempts the Agency from providing an advanced notice to small entities, 

allowing them to submit comments and address concerns in the NPRM. 

B. Impact of the NPRM on Small SNAP Retailers 

Perhaps the most troubling of the agency’s regulatory flexibility analysis is the 

inadequate estimate of the total number of small SNAP retailers. The NPRM does 

accurately estimate that there are nearly 200,000 retailers that fall under the Small 

Business Administration’s gross sales threshold, but it is imprecise to assume that 

all of these stores would be impacted by the proposed rule.504 As a result, the lost 

sales per store are too low, failing to signal to small entities the magnitude of their 

losses from the NPRM. An internal analysis at the Center on Budget and Policy Priorities has shown that a total of 639 counties across 28 states would be impacted 

by the proposed rule.505 Within these counties, there are only a total of about 67,000 

SNAP retailers of all sizes.506 If the same percentage of these businesses were considered to be small entities under the Small Business Administration gross sales 

threshold used in the NPRM (76 percent), then it can be estimated that a total of 

nearly 51,000 small entities would be impacted, significantly less than the NPRM’s 

estimate of 200,000.507

By making an estimate based off the total number of small SNAP retailers in the 

United States (200,000) versus the number of small retailers impacted by the NPRM 

(51,000), FNS has artificially lowered the average of the sales lost by four times.508

FNS has conducted a cursory analysis regarding the impact of the proposed rule on 

small businesses. Using an estimate of nearly four times the true number of stores 

320 

509 NPRM, Regulatory Flexibility Act https://www.federalregister.gov/d/2018-28059/p-118. 510 Ibid. 511 Ibid. 512 Ibid. 513 CBPP Analysis of BLS Unemployment data, 2019. 514 U.S. Department of Agriculture, Food Environment Atlas Data 2018, https:// 

www.ers.usda.gov/data-products/food-environment-atlas/data-access-and-documentationdownloads/. 515Michael Ratcliffe, et al., ‘‘Defining Rural at the U.S. Census Bureau,’’ United States Census 

Bureau, U.S. Department of Commerce, Dec 2016, pp. 1–8, https://www2.census.gov/geo/pdfs/ 

reference/ua/Defining_Rural.pdf. 516 Joseph Sharkey, et al., ‘‘Association between neighborhood need and spatial access to food 

stores and fast food restaurants in neighborhoods of Colonias,’’ International Journal of Health 

Geographics, 2009, pp. 1–17. 517 Joseph Sharkey, ‘‘Measuring Potential Access to Food Stores and Food-Service Places in 

Rural Areas in the U.S.,’’ American Journal of Preventive Medicine, April 2009, pp. S151–S155. 518 Renee Walker, Christopher Keane, and Jessica Burke, ‘‘Disparities and access to healthy 

food in the United States: A review of food deserts literature,’’ Health & Place, 2010, pp. 876– 

884. 519 James Mabli, ‘‘SNAP Participation, Food Security, and Geographic Access to Food,’’ Food 

and Nutrition Service, Office of Policy Support—U.S. Department of Agriculture, March 2014, 

pp. 1–50. 520Kevin Matthews, et al., ‘‘Health-Related Behaviors by Urban-Rural county Classification— 

United States, 2013,’’ Morbidity and Mortality Weekly Report, Centers for Disease Control and 

Prevention, February 2017, pp. 1–12. 

potentially impacted minimizes the reality that small SNAP retailers would face 

from the NPRM. 

According to the NPRM, SNAP benefit payments are expected to be reduced by 

about $1.7 billion per year.509 By conducting the same calculation as FNS in the 

NPRM while including a more accurate estimate of the amount of impacted small 

businesses ($1.7 billion × 15% redeemed at small retailers / 51,000 stores losing 

waivers / 12 months), we can estimate that the loss of revenue per small store on 

average each month would be $417, compared to the NPRM estimate of $106.510

The NPRM subsequently states that the average small store redeemed $3,800 in 

SNAP each month in 2017, making the NPRM estimate representative of three percent of monthly store sales.511 In evaluating the impact on small stores with the 

true loss of revenue per store ($417/month), the average small store would realistically face an 11 percent reduction in the amount of SNAP benefits redeemed at each 

store. Not only is 11 percent a significant portion of a store’s SNAP revenue, more 

importantly it is nearly four times greater than the estimated impact from the initial regulatory flexibility analysis of three percent in the NPRM.512 Using the more 

accurate estimate would have properly signaled the implications of the rule to small 

entities, allowing them the opportunity to comment on the proposed rule. 

Small Businesses Located in Rural Areas Will Be Disproportionately Impacted 

The small business impact assessment in the NPRM claims that small retailers 

are not expected to be disproportionately impacted by the proposed rule. This is not 

correct. Using 2018 as an illustrative year, a total of 639 counties or county-equivalents would have lost access to the waiver across 28 states.513 Of those impacted 

areas (which include counties, reservations, and small cities), 405 areas have a population of fewer than 50,000 people, where the Census Bureau defines the cutoff for 

urbanized areas.514–515 Research has shown that rural areas with lower population 

levels often rely on corner and convenience stores for food, many of which are individually owned small businesses.516 When nearly 2⁄3 of the counties impacted by an 

arbitrary rule depend on small businesses for SNAP purchases, the rule is certain 

to have a substantial impact on small business in the impacted areas. As a result, 

the claim that small entities will not be substantially impacted is incorrect. 

Individuals living in rural areas must travel longer distances to supermarkets and 

grocery stores than their urban or suburban counterparts.517 As a result, they visit 

corner and convenience stores frequently for their daily food and nutrition needs.518

A study conducted by USDA found that new-entrant SNAP households along with 

SNAP households that had participated in the program for less than 6 months lived, 

on average, 4 miles from a grocery store and 1.6–1.8 miles from a convenience 

store.519 While this may not appear to be a substantial difference in distance, individuals living in rural areas are less likely to have access to public transportation 

and a private vehicle.520 Because lack of transportation is a common issue across 

low-income rural areas, residents rely on the closest store to spend their monthly 

321 

521 C. Pinard, et al., ‘‘An integrative literature review of small food store research across urban 

and rural communities in the U.S.,’’ Preventive Medicine Reports, April 2016, pp. 324–332. 522Lisa Powell, et al., ‘‘Food store availability and neighborhood characteristics in the United 

States,’’ Preventive Medicine (2007), pp. 189–195. 523 CBPP Internal Analysis of U.S. Department of Agriculture, Food Environment Atlas Data 

2018. 524 C. Pinard, et al., ‘‘An integrative literature review of small food store research across urban 

and rural communities in the U.S.,’’ Preventive Medicine Reports, April 2016, pp. 324–332. 525 U.S. Department of Agriculture, SNAP State Issuance and Participation Estimates (FNS– 

388 & FNS–388A), data as of July 2018, https://www.fns.usda.gov/sites/default/files/pd/ 

SNAP-FNS388A.zip. 526 USDA, Food Environment Atlas, last updated on March 27, 2018, https:// 

www.ers.usda.gov/data-products/food-environment-atlas/data-access-and-documentationdownloads/. 

SNAP benefits.521 As mentioned, these closest stores are typically convenience 

stores or small businesses, offering a limited selection of foods. 

In addition to many of the impacted counties being rural and facing issues around 

food access, a significant portion of the impacted counties suffer from extremely low 

access to food.522 Sixty-three counties (ten percent of those impacted by the proposed rule) have five or less SNAP retailers across the county.523 While the impact 

of the proposed rule on retailers across all rural counties would be considerable, 

these 63 counties with such few SNAP vendors would be disproportionately impacted. In these cases particularly, rural residents are often required to travel 

longer than the previously mentioned average distances to access a supermarket or 

superstore.524 Table 13.1 shows some of the impacted rural counties with few or 

lone SNAP retailers: 

Table 13.1 

Examples of Rural Counties Disproportionately Impacted by the NPRM 

State County 

SNAP 

Participants as 

of July 2018 525

Average 

Monthly SNAP 

Retailers in 

2016 526

North Dakota Eddy County 167 1 

Kentucky Robertson County 290 2 

Virginia Charles City County 827 2 

South Dakota Mellette County 655 3 

Nevada White Pine County 1,131 5 

West Virginia Doddridge County 1,187 5 

Source: CBPP Internal Analysis of U.S. Department of Agriculture, Food Environment Atlas 

Data, 2018. 

Table 13.1 shows that rural counties impacted by the NPRM with few SNAP retailers, or a single SNAP retailer, would face significant harm if sales were lost. 

These are solely a few illustrative examples of the counties impacted. These examples validate the potential of the NPRM on rural counties with minimal SNAP retailers. A loss of sales for any of these isolated SNAP retailers would inhibit their 

ability to provide for the surrounding community. A much more robust nationwide 

assessment ought to have been included in the NPRM in order to meet the requirements of the law and to allow small entities the opportunity to meaningfully engage 

on what the proposed rule might mean to their sales and business. It is not representative of the Department to ignore its own research and knowledge of the location of small businesses impacted by the rule. This failure and lack of discussion 

on the impact of small businesses leaves that constituency and others unable to 

comment effectively on the proposed rule. 

Small Retailers in Urban Areas Will Be Significantly Impacted 

While many of the counties that will lose waivers under the proposed rule are 

rural, a noteworthy portion of the counties that would no longer be eligible to be 

waived is considered urban. Some of the counties with the highest population in the 

country would be impacted, subjecting a great number of recipients in a condensed 

area to the proposed rule. The following are a few of the impacted urban counties 

and cities: 

322 

527 U.S. Department of Agriculture, FNS 2018 County level SNAP data. 528 ‘‘Characteristics of Able-bodied Adults without Dependents,’’ Food and Nutrition Services, 

United States Department of Agriculture, 2016, https://fns-prod.azureedge.net/sites/default/ 

files/snap/nondisabled-adults.pdf. 529Melissa Nelson Laska, et al., ‘‘Healthy food availability in small urban food stores: a comparison of four U.S. cities,’’ Public Health Nutrition, December 2009, pp. 1031–1035. 530 Nicole Larson, Mary Story, and Melissa Nelson, ‘‘Neighborhood Environments: Disparities 

in Access to healthy Foods in the U.S.,’’ American Journal of Preventive Medicine, 2009, pp. 74– 

81. 531 Carolyn Cannuscio, et al., ‘‘The social dynamics of healthy food shopping and store choice 

in an urban environment,’’ Social Science & Medicine, October 2014, pp. 13–20. 

Table 13.2 

Examples of Urban Locales Significantly Impacted by the NPRM 

State County Primary City 

SNAP 

Participants 

as of July 

2018 527

Statewide 

Share of 

‘‘ABAWD’’ 

Population 

Estimated 

‘‘ABAWD’’ 

Population * 

Estimated 

Monthly 

‘‘ABAWD’’ 

Benefits ** 

CA Los Angeles County Los Angeles 1,055,314 11.3% 120,000 $19,444,000 

IL Cook County Chicago 813,465 12.3% 100,000 $16,295,000 

MI Wayne County Detroit 416,321 11.4% 47,000 $7,685,000 

NV Clark County Las Vegas 352,675 13.9% 49,000 $7,984,000 

PA Philadelphia County Philadelphia 473,269 6.6% 31,000 $5,040,590 

Source: CBPP analysis of USDA SNAP Household Characteristics data, FY 2017, where the average monthly 

‘‘ABAWD’’ benefit is $162.4. 

* Estimated ‘‘ABAWD’’ Population is derived from share of ‘‘ABAWDs’’ in each state applied to county caseload. 

** Estimated Monthly ‘‘ABAWD’’ Benefit is calculated from average ‘‘ABAWD’’ benefit and ABAWD share of 

population. 

The cities shown in Table 13.2 represent some of the largest cities impacted by 

the proposed rule. Across the five cities listed, an internal analysis estimates a total 

of 347,000 ‘‘ABAWDs’’ residing within these cities. While not all of these individuals 

are necessarily subject to the proposed rule due to exemptions and other factors, it 

is critical to recognize that the average ‘‘ABAWD’’ SNAP monthly benefit in FY2017 

was $162.4, or an estimated annual contribution of $677,383,000 in SNAP benefits 

from ‘‘ABAWDs’’ to the combined economies of these cities.528

Similar to rural residents, individuals living in low-income urban areas often depend on convenience stores for groceries because of the lack of accessibility to fullsized supermarkets and grocery stores.529 In 2009, a study found that ‘‘ZIP [C]odes 

representing low-income areas had only 75% as many chain supermarkets available 

as ZIP [C]odes representing middle-income areas.’’ 530 With some urban-dwelling 

SNAP recipients essentially being forced to redeem benefits at small retailers because of the lack of access, the argument that urban small retailers would not be 

impacted by the proposed rule is representative of the lack of consideration that 

FNS has presented. 

There have been additional studies conducted concerning food access in individual 

cities that would be impacted by the proposed rule. For example, the food environment of Philadelphia has a wealth of research demonstrating food access issues 

across the city. A study from 2014 interviewed hundreds of low-income individuals 

in Philadelphia and found that residents often shopped at convenience stores because of ‘‘easy parking, accommodation of physical disabilities or special needs, and 

the integration of food shopping into other daily activities.’’ 531 With potentially impacted cities having published information about how their residents rely on small 

food retailers, it is remiss of the literature that exists in the field to argue that 

small retailers would not be unduly impacted by the proposed rule. 

Conclusion 

As demonstrated, the NPRM fails to adequately address the disproportionate and 

significant impact on small entities across the country. First, significant portions of 

the Regulatory Flexibility Analysis were either not completed or completed incorrectly, failing to signal to small entities the importance of the NPRM. Second, the 

analysis in the proposed rule incorrectly calculates the number of impacted small 

entities, suggesting that small entities would face an impact four times smaller than 

the reality of what the NPRM would prescribe. Lastly, both the rural and urban 

areas impacted by the rule would see significant losses. Rural small retailers would 

see disproportionate losses in sales, while urban small retailers would experience 

substantial losses in sales. Until FNS conducts further research regarding the impact of the proposed rule on small entities and the communities that house these 

businesses, implementation of this rule would be unwarrantable and detrimental to 

those who reside within the impacted areas. 

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Appendix A: Center on Budget and Policy Priorities’ Contributors to Our 

Public Comments 

For more than 3 decades, the Center on Budget and Policy Priorities has been 

at the forefront of national and state debates to protect and strengthen programs 

that reduce poverty and inequality and increase opportunity for people trying to 

gain a foothold on the economic ladder. The Center is a high-caliber strategic policy 

organization that shapes critical policies for low-income families and individuals. To 

these ends, we conduct highly skilled strategic and analytic work to develop and advance specific, actionable proposals, to achieve the maximum possible policy gains, 

and to ensure their effective implementation on the ground. We also build effective 

partnerships and help a diverse array of organizations and constituencies to engage 

more effectively in these debates. 

As part of this overall mission, we work to strengthen policies and programs that 

reduce hunger and poverty and improve the lives of the nation’s poorest families 

and individuals. Since our founding in 1981, we have worked on Federal nutrition 

programs, most notably the Supplemental Nutrition Assistance Program (SNAP), 

formerly known as food stamps. We have extensive experience in and knowledge of 

SNAP’s 3 month time limit and state waiver authority within that rule. Examples 

of our efforts on this front include: 

• Issuing reports and analyses on the time limit and the population impacted by 

the rule, as well as policy options available to states via waiver and individual 

exemption policies; 

• Assisting states in assessing which areas of their states are eligible for waivers 

and developing waiver requests that meet the Federal criteria. The Center has 

supported an average of 30–40 states each year, completing or assisting with 

a total of over 600 waiver applications since the late 1990s; 

• Educating anti-hunger nonprofits and other community organizations about the 

time limit rule, including about the availability of waivers based on the underlying unemployment trends in the state and individual exemptions; and 

• Training state agency officials as well as local anti-hunger and poverty advocates about judicious practices in implementing the time limit policy. For years 

we have worked to help state officials implement the time limit in a way that 

conforms with Federal law and protects as many individuals with low incomes 

as possible and avoids (to the degree possible) cutting off individuals who are 

not actually subject to the limit. 

Over time, the Center’s work on waivers and time limit policy has evolved into 

a multi-faceted and complex approach. The Center has provided in-person trainings 

and direct supervision to state officials in nearly ten states, while providing support 

to advocates and working on issues of implementation for many more. The Center 

has also given multiple presentations to FNS staff at several regional meetings 

across the United States regarding waivers, along with a series of annual presentations to the American Association of SNAP Directors. Additional support from the 

Center has included assistance regarding program integrity and payment accuracy 

implications, writing of manuals for dozens of states, and constantly monitoring all 

50 states’ statuses and ability to apply for ‘‘ABAWD’’ waivers. The food assistance 

team’s experience in combination with the economic expertise of other members of 

the Center provides CBPP with the greatest amount of experience and knowledge 

concerning ‘‘ABAWD’’ waivers and the implications of the proposed rule. 

Below is a listing of the individuals at CBPP who contributed to these comments: 

Jared Bernstein joined the Center on Budget and Policy Priorities in 2011 as 

a Senior Fellow. From 2009 to 2011, Bernstein was the Chief Economist and Economic Adviser to Vice President Joe Biden, Executive Director of the White House 

Task Force on the Middle Class, and a member of President Obama’s economic 

team. Bernstein’s areas of expertise include Federal and state economic and fiscal 

policies, income inequality and mobility, trends in employment and earnings, international comparisons, and the analysis of financial and housing markets. 

Prior to joining the Obama Administration, Bernstein was a senior economist and 

the director of the Living Standards Program at the Economic Policy Institute in 

Washington, D.C. Between 1995 and 1996, he held the post of Deputy Chief Economist at the U.S. Department of Labor. Bernstein holds a Ph.D. in Social Welfare 

from Columbia University. 

He is the author and coauthor of numerous books for both popular and academic 

audiences, including Getting Back to Full Employment: A Better Bargain for Working People, Crunch: Why Do I Feel So Squeezed?, nine editions of The State of Working America, and his latest book, The Reconnection Agenda: Reuniting Growth and 

Prosperity. Bernstein has published extensively in various venues, including the 

324 

New York Times and Washington Post. He is an on-air commentator for the cable 

stations CNBC and MSNBC, contributes to the WASHINGTON POST’s PostEverything 

blog, and hosts On The Economy (jaredbernsteinblog.com). 

Thompson Bertschy received his Master’s in Social Work from the University 

of North Carolina and began working with the Center as an intern in 2019. In 

North Carolina, Thompson worked with the Carolina Farm Stewardship Association 

to advocate for sustainable and equitable food policy while organizing food policy 

councils across the state. At CBPP, Thompson focuses on research and analysis regarding ‘‘ABAWD’’ exemptions and state legislative proposals around SNAP, TANF, 

and Medicaid. 

Ed Bolen joined the Center in 2010 as a Senior Policy Analyst. At the Center, 

Ed focuses on SNAP Employment & Training and ‘‘ABAWD’’ waivers. He has provided trainings to multiple states regarding their loss of waivers, including Alabama, California, Michigan, Illinois, Alaska, and Mississippi. Additionally, Ed has 

given presentations to Food and Nutrition Service staff at the Northeast and MidAtlantic regional meetings. Since 2011, Ed has consistently worked with advocates 

and state officials concerning implementation issues in Georgia, Illinois, Michigan, 

California, and other states. He has also presented to the American Association of 

SNAP Directors for 4 consecutive years and created a toolkit on implementing the 

‘‘ABAWD’’ time limit including technical writing on implementation issues. He has 

had many interactions with media and has written multiple blog posts and papers 

concerning ‘‘ABAWDs.’’ Throughout his time at the Center, Ed has written multiple 

pieces concerning Employment and Training for SNAP recipients. 

Prior to joining the Center, Bolen was a Senior Policy Analyst at California Food 

Policy Advocates. While there, he advocated for administrative and legislative improvements to food assistance programs and provided training and technical assistance to community-based organizations. He also has worked in public health law, 

most recently consulting on legal strategies to combat childhood obesity with the 

National Policy and Legal Analysis Network. Prior to that, Bolen was senior staff 

attorney at the Child Care Law Center, specializing on licensing, subsidy and legislative issues affecting low-income families in child care and early education settings. 

Kathleen Bryant is a Research Assistant in the Federal Fiscal team at the Center on Budget and Policy Priorities. Previously, she interned for EMILY’s List, the 

Economic Policy Institute, and the Center’s Legislative Affairs team. She also conducted independent research on school segregation for her honors thesis and was 

selected as a fellow in the Advanced Empirical Research on Politics for Undergraduates Program for this research by the Society for Political Methodology. Kathleen 

has a B.A. in Public Policy from The College of William & Mary. 

Ashley Burnside is a Research Assistant with the Center’s Family Income Support division. Before joining the Center, she was an Emerson National Hunger Fellow with the Congressional Hunger Center, where she advocated for anti-hunger 

and anti-poverty solutions, led voter registration and community engagement efforts 

for food pantry clients, and conducted research on tax credit programs. Burnside has 

also served as a public policy fellow at AIDS United, a national HIV/AIDS advocacy 

organization. She holds a B.A. in Social Theory and Practice from the University 

of Michigan. 

Lexin Cai is a Research Analyst with the Center’s Food Assistance Division, 

where she focuses on data analysis for nutrition assistance programs. Lexin first 

joined the Center in May 2015 as an intern. Prior to joining the Center, she interned with the World Wildlife Fund, focusing on international agricultural trade. 

At the Center, Lexin conducts analyses, compiles historical data and records, and 

uses mapping and modeling to support states with the waiver application process. 

Over the last several years, Lexin has worked with Catlin Nchako in completing 

waiver applications for multiple states and providing assistance with the process to 

others, helping an average of 32 states per year. She holds a Master of Science in 

Social Policy from the University of Pennsylvania and a Bachelor of Management 

from Renmin University of China. 

Steven Carlson provided background research for these comments as a consultant to CBPP. He was a Federal employee at the Food and Nutrition Service for 37 

years. During his time there, he led their Office of Analysis and Evaluation and 

oversaw research studies and analysis on SNAP. 

Maritzelena Chirinos is a recent graduate of Meredith College and began working with The Center as an intern in 2019 on The State Fiscal Project Team. She 

holds a B.A. in Criminology and Sociology. She previously worked at The Indivisible 

Project and Democrats For Education Reform. 

Stacy Dean is the Vice President for Food Assistance Policy at the Center on 

Budget and Policy Priorities. She directs CBPP’s food assistance team, which publishes frequent reports on how Federal nutrition programs affect families and comVerDate Aug 31 2005 11:16 Jun 14, 2019 Jkt 041481 PO 00000 Frm 00330 Fmt 6621 Sfmt 6621 P:\DOCS\116-02\36188.TXT BRIAN
325 

munities and develops policies to improve them. Dean’s team also works closely with 

program administrators, policymakers, and nonprofit organizations to improve Federal nutrition programs and provide eligible low-income families with easier access 

to benefits. She brings her deep programmatic and operational knowledge along 

with a strong strategic sense to help advance CBPP’s priorities. 

Dean has over 20 years of experience in working in great detail with the USDA 

and dozens of states concerning ‘‘ABAWD’’ waivers. In 1997, she began writing and 

distributing information to a majority states regarding specific Labor Surplus Areas 

in the state and their ability to apply for a waiver. She has written multiple papers 

on ‘‘ABAWDs’’ and waiver requests dating back to the early 2000s. In addition to 

writing the papers, Dean has worked closely with many states providing supervision, training, and general policy support for both application and implementation. 

In addition to her work on Federal nutrition programs, Dean directs CBPP efforts 

to integrate the delivery of health and human services programs at the state and 

local levels. Dean has testified before Congress and spoken extensively to national 

and state nonprofit groups. She has been quoted in such publications as the New 

York Times, Washington Post, Wall Street Journal, and Politico, as well as the Associated Press. Dean joined CBPP in 1997 as a Senior Policy Analyst working on national policy issues such as the Federal budget, SNAP, and benefits for immigrants. 

Previously, at the Office of Management and Budget, Dean served as a budget analyst for food stamps. In this role, she staffed the White House work on the 1996 

food stamp program changes, reviewed and cleared the ABAWD waiver guidance, 

and worked on policy development, regulatory and legislative review, and budgetary 

process and execution for a variety of income support programs. 

Ife Floyd joined the Center in June 2011 as a Research Associate with the Family Income Support Division, and is now Senior Policy Analyst. 

Prior to joining the Center, Floyd served as an AmeriCorp VISTA with Culture 

Connect, Inc. and developed a cultural competency workshop series for professional 

workplaces in the Atlanta area. In addition, she also worked with the Atlanta Community Food Bank’s Prosperity Campaign as a benefits screener to increase access 

to programs like SNAP, TANF, and Medicaid for low-income families. Floyd holds 

a B.A. in Sociology from Northwestern University and a M.P.P. degree from Georgia 

State University. 

Brynne Keith-Jennings obtained her Master’s in Public Policy from the University of Southern California and joined the Center in June 2011. Her work focuses 

on Federal and state SNAP policies and research. As a Senior Policy Analyst, 

Brynne works closely with the USDA and regularly offers guidance with ABAWD 

waiver policy. She provides states with technical assistance regarding waiver requests and has developed a suite of products around the farm bill, SNAP, and employment. Since 2013, Keith-Jennings has been one of the primary food assistance 

team members concerned with ‘‘ABAWD’’ waivers, assisting with the process of completing or assisting with 30–40 waivers each year. 

Prior to joining the Center, she worked as an educator and policy analyst for Witness for Peace and as a consultant for other NGOs in Nicaragua. She has also 

worked at the Public Welfare Foundation supporting human rights and criminal justice reform organizations, at the Government Accountability Office, and at the 

Tomas Rivera Policy Institute, where she analyzed language access policies and 

other issues affecting Latino communities in Southern California. 

Joseph Llobrera is a Senior Policy Analyst on the Food Assistance team. As a 

research associate at the Center between 2002 and 2007, Llobrera supported the 

Food Assistance, State Fiscal, and Housing Policy teams. During these years, Joseph managed the Center’s ‘‘ABAWD’’ waiver support process through data analysis 

and extraction, assisting nearly 150 states with the waiver process. He also 

interacted with and provided operational support to state advocates and agencies. 

Before returning to the Center in 2019, he served as an Associate Director of Learning and Improvement at Insight Policy Research, providing technical assistance and 

training to Federal, state, and local human service agencies that administer SNAP 

and the Temporary Assistance for Needy Families program. During this time, 

Llobrera reviewed notices that states would send to SNAP recipients who were subject to the time limit. He also worked as a researcher at IMPAQ International and 

the Urban Institute, focusing on food assistance policy, workforce development, and 

health policy. 

Currently at the Center, Llobrera provides operational support and technical assistance to advocates and state agencies in an effort to streamline the SNAP and 

Medicaid enrollment process. Llobrera holds a Ph.D. in Nutrition from the Friedman 

School of Nutrition Science and Policy at Tufts University, a master’s degree in Geography from the University of Washington (Seattle), and a bachelor’s degree in 

Mathematics and Urban Studies from Brown University. 

326 

Rachel Mbassa is an intern with the Data team. She graduated with a Master 

of Public Health in Biostatistics from Loma Linda University. She then went on to 

work at the University of California San Francisco Medical Center, conducting epidemiological/clinical research centered on the effects of cumulative psychosocial 

stressors on cardiovascular disease outcomes. She recently moved to Washington, 

D.C. to transition into a career in policy data analysis. She has a strong interest 

in health economics and policy and hopes to pursue a terminal degree in this field. 

Tazra Mitchell joined the Center in 2016 as a Policy Analyst in the Family Income Support Division. Previously she worked as a State Policy Fellow and Policy 

Analyst with the North Carolina Budget & Tax Center, where she conducted analysis of work and income supports as well as fiscal and economic policies that enable 

low-income people and disadvantaged communities to thrive. In addition, she 

worked as a Research Assistant in the nonpartisan Fiscal Research Division of the 

North Carolina General Assembly where she analyzed legislative proposals to determine the fiscal impact on state government resources and worked directly with legislators to develop the state budget. 

Mitchell holds a B.A. in Political Science from North Carolina State University 

and an M.P.P. from the Sanford School of Public Policy at Duke University. 

Catlin Nchako joined the Food Assistance Division as a Research Associate in 

November 2013. His work focuses on data analysis and research for the food stamp, 

school meals, and WIC programs. Over the last several years, Nchako has worked 

with Lexin Cai in completing waiver applications for multiple states and aiding with 

the process to others, helping an average of 32 states per year. He has also tracked 

employment benefit trigger notices for all states and territories, notifying areas 

when they qualify for an exemption. He has completed multiple analyses and contributed to many of the Center’s papers concerning ‘‘ABAWDs.’’ 

Nchako worked for the Center as a Food Assistance intern prior to joining the organization on a full-time basis. He previously interned for the Center for Law and 

Social Policy. He also worked for several years as a labor researcher for the United 

Food and Commercial Workers Union, where he evaluated wage proposals during 

labor contract negotiations, analyzed companies’ financial performance, and provided campaign research support. He holds a Master’s in Public Policy from Georgetown University and a B.A. in Africana Studies from Cornell University. 

LaDonna Pavetti is the Vice President for Family Income Support Policy at the 

Center on Budget and Policy Priorities. In this capacity, she oversees the Center’s 

work analyzing poverty trends and assessing the nation’s income support programs, 

including the Temporary Assistance for Needy Families (TANF) program. For the 

last several years, she has been working on a special initiative to identify opportunities to build executive function and self-regulation skills in TANF and other work 

programs. 

Before joining the Center in 2009, Dr. Pavetti spent 12 years as a researcher at 

Mathematica Policy Research, Inc., where she directed numerous research projects 

examining various aspects of TANF implementation and strategies to address the 

needs of the hard-to-employ. She has also served as a researcher at the Urban Institute, a consultant to the U.S. Department of Health and Human Services on welfare 

reform issues, and a policy analyst for the District of Columbia’s Commission on Social Services. Across these positions, Dr. Pavetti conducted research on how states 

were implementing TANF, how sanctions were implemented, and conducted a study 

in St. Paul, Minnesota analyzing which populations were primarily impacted by 

TANF work requirements. In recent years, she has worked with Vermont, New 

York, Minnesota, Colorado, California, Connecticut, New Jersey, Pennsylvania, and 

Oregon. 

In addition, for several years she was a social worker in Chicago and Washington, 

D.C. Dr. Pavetti has an A.M. in social work from the University of Chicago and a 

Ph.D. in public policy from Harvard University’s Kennedy School of Government. 

Dottie Rosenbaum is a Senior Fellow who joined the Center in 2000. She has 

worked extensively on Federal and state issues in SNAP as well as issues that involve the coordination of SNAP and other state-administered health and income security programs, such as Medicaid, TANF, and child care. In addition, Rosenbaum 

has expertise on the Federal budget and budget process. With over more than 20 

years of experience with SNAP, she written multiple papers regarding SNAP and 

SNAP Employment and Training. 

Before joining the Center, Rosenbaum was a budget analyst at the Congressional 

Budget Office. In this role, she conducted the cost estimate of the 1996 Personal Responsibility and Work Opportunity Reconciliation Act which included the time limit. 

She projected Federal spending and provided Congress with cost estimates for a variety of programs including: SNAP, Medicaid, the State Children’s Health Insurance 

Program, Child Nutrition, and Elementary and Secondary Education. Rosenbaum 

327 

holds a Master’s in Public Policy from Harvard University’s Kennedy School of Government. 

Andrew Scanlan is a recent graduate of Brown University and began working 

with the Center as an intern in 2019 on the Family Income Security team. At 

Brown, he worked as a research assistant in the political science department and 

received a combined degree in philosophy and mechanical engineering. He previously worked in the Rhode Island state government and the New York City government. 

Arloc Sherman’s work focuses on family income trends, income support policies, 

and the causes and consequences of poverty. He has written extensively about the 

effectiveness of government poverty-reduction policies, the influence of economic security programs on children’s healthy development, the depth of poverty, tax policy 

for low-income families, welfare reform, economic inequality, material hardship, parental employment, and the special challenges affecting rural areas. 

He is a member of the National Academy of Sciences Committee on National Statistics Panel to Review and Evaluate the 2014 Survey of Income and Program Participation’s Content and Design. Prior to joining the Center in 2004, Sherman 

worked for 14 years at the Children’s Defense Fund and was previously at the Center for Law and Social Policy. His book Wasting America’s Future was nominated 

for the 1994 Robert F. Kennedy Book Award. 

Chad Stone is Chief Economist at the Center on Budget and Policy Priorities, 

where he specializes in the economic analysis of budget and policy issues. Stone has 

conducted notable research around measures of economic slack that are indicative 

of a weaker labor market, primarily concerning labor force participation and the employment population ratio. He was the acting executive director of the Joint Economic Committee of the Congress in 2007 and before that staff director and chief 

economist for the Democratic staff of the Committee from 2002 to 2006. He was 

chief economist for the Senate Budget Committee in 2001–02 and a senior economist 

and then chief economist at the President’s Council of Economic Advisers from 1996 

to 2001. 

Stone has been a senior researcher at the Urban Institute and taught for several 

years at Swarthmore College. His other Congressional experience includes two previous stints with the Joint Economic Committee and a year as chief economist at 

the House Science Committee. He has also worked at the Federal Trade Commission, the Federal Communications Commission, and the Office of Management and 

Budget. Stone is co-author, with Isabel Sawhill, of Economic Policy in the Reagan 

Years. He holds a B.A. from Swarthmore College and a Ph.D. in economics from 

Yale University. 

Jennifer Wagner joined the Center in 2015 as a Senior Policy Analyst with the 

health team. She focuses primarily on Medicaid eligibility and implementation of 

the Affordable Care Act (ACA), including analyzing opportunities to align Medicaid 

with other low-income support programs for greater access and efficiency. 

Before joining the Center, Wagner served for 5 years as an Associate Director 

with the Illinois Department of Human Services. In that capacity, she oversaw 

SNAP and cash assistance policy as well as the local offices throughout the state 

that determined eligibility for cash, SNAP, and medical assistance. She assisted Illinois with Medicaid expansion under the ACA and improved customer service 

through business process re-engineering in the local offices. Prior to that, she was 

a staff attorney at the Sargent Shriver National Center on Poverty Law, where she 

focused on public benefits. 

Wagner received her B.S. from the University of Wisconsin—Madison and her 

J.D. from the Northwestern University School of Law. 

Appendix B: Materials Cited in Comments 

Appendix B includes all of the resources and materials cited in these comments 

to help ensure that the Department will have complete and simple access to the relevant research. The documents in Appendix B are listed in alphabetical order by 

first author’s last name or entity where appropriate. 

[The documents are retained in Committee file.] 

1. 5 U.S.C., Chapter 6, The Analysis of Regulatory Functions (Regulatory Flexibility Act) (https://www.govinfo.gov/content/pkg/USCODE-2017-title5/pdf/ 

USCODE-2017-title5-partI-chap6.pdf) 

328 

1This includes 7 CFR § 273.24. 2This includes Table 1. Employment status of the civilian noninstitutional population by disability status and selected characteristics, 2018 annual averages. 

2. 7 CFR, Part 273, Certification of Eligible Households (https:// 

www.govinfo.gov/content/pkg/CFR-2018-title7-vol4/pdf/CFR-2018-title7- 

vol4-part273.pdf) 1

3. Regulatory Impact Analysis, 7 CFR Part 273 for Supplemental Nutrition Assistance Program: Requirements for Able-Bodied Adults Without Dependents, 

FNS–2018–0004 (https://www.regulations.gov/document?D=FNS-2018-0004- 

6000) 

4. Abraham, Katharine G., John C. Haltiwanger, Kristin Sandusky, James 

Spletzer, The Consequences of Long-Term Unemployment: Evidence from 

Linked Survey and Administrative Data, National Bureau of Economic Research, NBER Working Paper 22665, September 2016 (https://www.nber.org/ 

papers/w22665) 

5. Andersson, Fredrik, John C. Haltiwanger, Mark J. Kutzbach, Henry O. 

Pollakowski, Daniel H. Weinberg, Job Displacement and the Duration of Joblessness: The Role of Spatial Mismatch, National Bureau of Economic Research, NBER Working Paper 20066, April 2014 (https://www.nber.org/papers/w20066) 

6. Austin, Benjamin, Edward Glaeser, Lawrence Summers, Jobs for the Heartland: Place-Based Policies in 21st-Century America BROOKINGS PAPERS ON

ECONOMIC ACTIVITY, Spring 2018, p. 151–255 (https://www.brookings.edu/ 

wp-content/uploads/2018/03/AustinEtAl_Text.pdf) 

7. Bartik, Timothy J., How Do the Effects of Local Growth on Employment Rates 

Vary With Initial Labor Market Conditions? Upjohn Institute Staff Working 

Paper 09–148, November 4, 2006 (https://research.upjohn.org/ 

up_workingpapers/148/) 

8. Bauer, Lauren, The Hamilton Project, Workers Could Lose SNAP Benefits 

Under Trump’s Proposed Rule, BROOKINGS UP FRONT, December 12, 2018 

(https://www.brookings.edu/blog/up-front/2018/12/20/workers-could-losesnap-benefits-under-trumps-proposed-rule/) 

9. Bauer, Lauren, Jay Shambaugh, The Hamilton Project, Workers with Low 

Levels of Education Still Haven’t Recovered From the Recession, September 6, 

2018 (http://www.hamiltonproject.org/blog/employment_rate_gap_workers_ with_low_levels_of_education_still_havent_recov) 

10. Bell, Stephen H., and L. Jerome Gallagher, Prime-Age Adults without Children or Disabilities: The ‘‘Least Deserving of the Poor’’—or Are They? The 

Urban Institute, Series B, No. B–26, February 2001 (https://www.urban.org/ 

research/publication/prime-age-adults-without-children-or-disabilities) 

11. Bertrand, Marianne, Sendhil Mullainathan, Are Emily and Greg More Employable than Lakisha and Jamal? A Field Experiment on Labor Market Discrimination, National Bureau of Economic Research, NBER Working Paper 

9873, July 2003 (https://www.nber.org/papers/w9873) 

12. Bitler, Marianne P., Jonah B. Gelbach, and Hilary W. Hoynes, What Mean 

Impacts Miss: Distributional Effects of Welfare Reform Experiments, AMER- ICAN ECONOMIC REVIEW Vol. 96 No. 4, 2006, p. 988–1012 (https:// 

www.ssc.wisc.edu/∼scholz/Teaching_742/Bitler_Gelbach_Hoynes.pdf) 

13. Bloom, Dan, Cynthia Miller, Gilda Azurdia, Results from the Personal Roads 

to Individual Development and Employment (PRIDE) Program in New York 

City, MDRC, (https://www.mdrc.org/sites/default/files/full_547.pdf) 

14. U.S. Bureau of Labor Statistics, U.S. Department of Labor, Americans at Age 

31: Labor Market Activity, Education and Partner Status Summary, ECO- NOMIC NEWS RELEASE, April 17, 2018 (https://www.bls.gov/news.release/ 

nlsyth.nr0.htm) 

15. U.S. Bureau of Labor Statistics, U.S. Department of Labor, Regional and 

State Unemployment, 2018 Annual Average Summary, ECONOMIC NEWS RE- LEASE, February 28, 2019 (https://www.bls.gov/news.release/srgune.nr0.htm) 

16. U.S. Bureau of Labor Statistics, U.S. Department of Labor, Persons with a 

Disability: Labor Force Characteristics, ECONOMIC NEWS RELEASE, February 

26, 2019 (https://www.bls.gov/news.release/disabl.htm) 2

17. U.S. Bureau of Labor Statistics, U.S. Department of Labor, Leave benefits: 

AccessTable 32. Leave benefits: Access, private industry workers, EMPLOYEE

329 

3This includes Household Data Table A–4. Employment status of the civilian population 25 

years and over by educational attainment. 4 Note: the table on the webpage has been subsequently updated as of April 5, 2019. 5 Note: the table on the webpage has been subsequently updated as of April 26, 2019. 6 Note: the webpage has been subsequently updated as of April 19, 2019. 

BENEFITS SURVEY, March 2017 (https://www.bls.gov/ncs/ebs/benefits/2017/ 

ownership/private/table32a.htm) 

18. U.S. Bureau of Labor Statistics, U.S. Department of Labor, Employee Tenure 

in 2018, ECONOMIC NEWS RELEASE, September 20, 2018 (https:// 

www.bls.gov/news.release/tenure.nr0.htm) 

19. U.S. Bureau of Labor Statistics, U.S. Department of Labor, The Employment 

Situation—March 2019, ECONOMIC NEWS RELEASE, April 5, 2019 (https:// 

www.bls.gov/news.release/empsit.htm) 3

20. Birnbaum Emily, and Juliegrace Brufke, Trump attacks Dems on farm bill, 

THE HILL, September 13, 2018 (https://thehill.com/homenews/administration/406561-trump-calls-out-dems-for-opposing-farm-bill-over-work-requirements) 

21. Brasher, Philip, Farm bill delayed, but Perdue signals administration support, AGRIPULSE, December 3, 2018 (https://www.agri-pulse.com/articles/ 

11703-farm-bill-delayed-but-perdue-signals-administration-support) 

22. U.S. Bureau of Labor Statistics, U.S. Department of Labor, Household 

Data, Annual Averages, 7. Employment status of the civilian noninstitutional population 25 years and over by educational attainment, sex, race, and 

Hispanic or Latino ethnicity, LABOR FORCE STATISTICS FROM THE CURRENT

POPULATION SURVEY, January 18, 2019 (https://www.bls.gov/cps/ 

cpsaat07.htm) 

23. U.S. Bureau of Labor Statistics, U.S. Department of Labor, Household 

Data, Not Seasonally Adjusted, Quarterly Averages, E–16. Unemployment rates by age, sex, race, and Hispanic or Latino ethnicity, LABOR FORCE

STATISTICS FROM THE CURRENT POPULATION SURVEY, January 4, 2019 

(https://www.bls.gov/web/empsit/cpsee_e16.htm) 4

24. U.S. Bureau of Labor Statistics, U.S. Department of Labor, Labor Market Activity, Education, and Partner Status Among America’s Young Adults at 29: 

Results From a Longitudinal Survey, ECONOMIC NEWS RELEASE, April 8, 2016 

(https://www.bls.gov/news.release/archives/nlsyth_04082016.pdf) 

25. U.S. Bureau of Labor Statistics, U.S. Department of Labor, Local Area Unemployment Statistics, (https://www.bls.gov/lau/) 

26. U.S. Bureau of Labor Statistics, U.S. Department of Labor, Alternative Measures of Labor Underutilization for States, 2018 Annual Averages, LOCAL AREA

UNEMPLOYMENT STATISTICS, (https://www.bls.gov/lau/stalt.htm) 5

27. U.S. Bureau of Labor Statistics, U.S. Department of Labor, Geographic Concepts, LOCAL AREA UNEMPLOYMENT STATISTICS, March 15, 2019 (https:// 

www.bls.gov/lau/laugeo.htm) 

28. U.S. Bureau of Labor Statistics, U.S. Department of Labor, Important Information, LOCAL AREA UNEMPLOYMENT STATISTICS, March 15, 2019 (https:// 

www.bls.gov/lau/launews1.htm) 6

29. U.S. Bureau of Labor Statistics, U.S. Department of Labor, National Compensation Survey: Employee Benefits in the United States, March 2017, September 2017, Bulletin 2787 (https://www.bls.gov/ncs/ebs/benefits/2017/ 

ebbl0061.pdf) 

30. U.S. Bureau of Labor Statistics, U.S. Department of Labor, Number of Jobs 

Held, Labor Market Activity, and Earnings Growth Among the Youngest Baby 

Boomers: Results from a Longitudinal Survey Summary, ECONOMIC NEWS RELEASE, August 24, 2017 (https://www.bls.gov/news.release/nlsoy.nr0.htm) 

31. U.S. Bureau of Labor Statistics, U.S. Department of Labor, Employment & 

Earnings Online, OFFICE OF PUBLICATIONS & SPECIAL STUDIES, February 28, 

2019 (https://www.bls.gov/opub/ee/home.htm) 

32. U.S. Bureau of Labor Statistics, U.S. Department of Labor, Persons With a 

Disability: Barriers to Employment, Types of Assistance, and Other Labor-Related Issues—May 2012, ECONOMIC NEWS RELEASE, April 24, 2013 (https:// 

www.bls.gov/news.release/archives/dissup_04242013.pdf) 

33. Bolen, Ed, Dorothy Rosenbaum, Stacy Dean, and Brynne-Keith Jennings, 

More Than 500,000 Adults Will Lose SNAP Benefits in 2016 as Waivers ExVerDate Aug 31 2005 11:16 Jun 14, 2019 Jkt 041481 PO 00000 Frm 00335 Fmt 6621 Sfmt 6621 P:\DOCS\116-02\36188.TXT BRIAN
330 

pire Affected Unemployed Childless Individuals Are Very Poor; Few Qualify 

for Other Help, Center on Budget and Policy Priorities, March 18, 2016 

(https://www.cbpp.org/research/food-assistance/more-than-500000-adultswill-lose-snap-benefits-in-2016-as-waivers-expire) 

34. Bolen and Stacy Dean, Ed, Waivers Add Key State Flexibility to SNAP’s 

Three-Month Time Limit, Center on Budget and Policy Priorities, February 6, 

2018 (https://www.cbpp.org/research/food-assistance/waivers-add-key-stateflexibility-to-snaps-three-month-time-limit) 

35. Born, Catherine E., Pamela J. Caudill, Melinda L. Cordero, Life After Welfare: A Look At Sanctioned Families, University of Maryland School of Social 

Work, November 1999 

36. Breitwieser, Audrey, Ryan Nunn, Jay Shambaugh, The Hamilton Project, 

The recent rebound in prime-age labor force participation, BROOKINGS UP

FRONT, August 2, 2018 (https://www.brookings.edu/blog/up-front/2018/08/ 

02/the-recent-rebound-in-prime-age-labor-force-participation/) 

37. Butcher, Kristin F. and Diane Whitmore Schanzenbach, Most Workers in 

Low-Wage Labor Market Work Substantial Hours, in Volatile Jobs SNAP or 

Medicaid Work Requirements Would Be Difficult for Many Low-Wage Workers 

to Meet, Center on Budget and Policy Priorities, July 24, 2018 (https:// 

www.cbpp.org/research/poverty-and-inequality/most-workers-in-low-wagelabor-market-work-substantial-hours-in) 

38. Butler, Sandra, TANF Time Limits and Maine Families: Consequences of 

Withdrawing the Safety Net, Maine Equal Justice Partners, March 2013 

39. Cadena, Brian C., Brian K. Kovak, Immigrants Equilibrate Local Labor Markets: Evidence From the Great Recession, National Bureau of Economic Research, NBER Working Paper 19272, August 2013 (https://www.nber.org/papers/w19272) 

40. Cajner, Tomaz, Tyler Radler, David Ratner, and Ivan Vidangos, Racial Gaps 

in Labor Market Outcomes in the Last Four Decades and over the Business 

Cycle, Finance and Economics Discussion Series, 2017–071, Divisions of Research & Statistics and Monetary Affairs, Federal Reserve Board 2017 

(https://www.federalreserve.gov/econres/feds/files/2017071pap.pdf) 

41. Cannuscio, Carolyn C., Amy Hillier, Allison Karpyn, Karen Glanz, The social 

dynamics of healthy food shopping and store choice in an urban environment, 

SOCIAL SCIENCE & MEDICINE, Volume 122, December 2014, p. 13–20 (https:// 

www.sciencedirect.com/science/article/abs/pii/S0277953614006510) 

42. Canon, Maria E., Marianna Kudlyak, Guannan Luo, and Marisa Reed, Flows 

To and From Working Part Time for Economic Reasons and the Labor Market 

Aggregates During and After the 2007–09 Recession, ECONOMIC QUARTERLY, 

Volume 100, Number 2, Second Quarter 2014, p. 87–111 (https:// 

www.richmondfed.org/-/media/richmondfedorg/publications/research/economic_quarterly/2014/q2/kudlyak.pdf) 

43. Carlson, Steven, and Brynne Keith-Jennings, SNAP Is Linked with Improved 

Nutritional Outcomes and Lower Health Care Costs, Center on Budget and 

Policy Priorities, January 17, 2018 (https://www.cbpp.org/research/food-assistance/snap-is-linked-with-improved-nutritional-outcomes-and-lower-healthcare) 

44. Carlson, Steven, Dorothy Rosenbaum, and Brynne Keith-Jennings, Who Are 

the Low-Income Childless Adults Facing the Loss of SNAP in 2016?, Center 

on Budget and Policy Priorities, February 8, 2016 (https://www.cbpp.org/research/food-assistance/who-are-the-low-income-childless-adults-facing-theloss-of-snap-in-2016) 

45. Letter from Robert Greenstein, Executive Director, CBPP and attached comments, Comments on Rules Proposed to Implement the Food Stamp Penalty 

Provisions of the 1996 Welfare Law, February 17, 2000, in response to 64 Fed. 

Reg. No. 242, page 70920 

46. Center on Budget and Policy Priorities, SNAP Helps 1 in 10 Workers in the 

United States Put Food on the Table, November 2018, Fact Sheet (https:// 

www.cbpp.org/snap-helps-low-wage-workers-in-every-state#National) 

47. Center on Budget and Policy Priorities, SNAP Time Limits: Waivers from the 

Time Limit Are Back to Historic Norms, March 24, 2017, Fact Sheet (http:// 

www.cbpp.org/sites/default/files/atoms/files/3-24-17fa1.pdf) 

48. Center on Budget and Policy Priorities, States Have Requested Waivers from 

SNAP’s Time Limit in High Unemployment Areas for the Past Two Decades, 

331 

7 Note: the submission is an excerpt from the conference report, p. 616–617. 8 Note: the submission is an excerpt from the Congressional Record, p. H7904 and H7905. 9 Note: the submission is an excerpt from the Congressional Record, p. H10149. 10 Note: the submission is an excerpt from the Congressional Record, p. H3814 and S4747. 

May 12, 2017, Interactive Map (https://www.cbpp.org/research/food-assistance/states-have-requested-waivers-from-snaps-time-limit-in-high-unemployment) 

49. Center on Budget and Policy Priorities, CBPP Summary of Two-Year Waivers 

from SNAP Three-Month Time Limit, March 2019 

50. Center on Budget and Policy Priorities, CBPP Summary of Areas That 

Would Have Lost Their Waivers from the SNAP Three-Month Time Limit in 

2018 if the Proposed Rule Were Implemented in 2018, March 2019 

51. Center on Budget and Policy Priorities, Taking Away Medicaid for Not Meeting Work Requirements Harms People Experiencing Homelessness, March 14, 

2019, Fact Sheet (https://www.cbpp.org/research/health/taking-away-medicaid-for-not-meeting-work-requirements-harms-people-experiencing) 

52. Center on Budget and Policy Priorities, Unemployed adults without children 

who need help buying food only get SNAP for three months, April 6, 2018 

Infographic (https://www.cbpp.org/unemployed-adults-without-children-whoneed-help-buying-food-only-get-snap-for-three-months) 

53. Chandler, Daniel, Joan Meisel, Pat Jordan, Beth Menees Rienzi, Sandra 

Naylor Goodwin, Mental Health, Employment, and Welfare Tenure, JOURNAL

OF COMMUNITY PSYCHOLOGY, Vol. 33, No. 5, p. 587–609 (https:// 

onlinelibrary.wiley.com/doi/abs/10.1002/jcop.20070) 

54. Cherlin, Andrew J., Karen Bogen, James M. Quane, Linda Burton, Operating 

within the Rules: Welfare Recipients’ Experiences with Sanctions and Case 

Closings, SOCIAL SERVICE REVIEW, Vol. 76, No. 3 (September 2002), p. 387– 

405 (https://www.jstor.org/stable/10.1086/341181) 

55. Cherlin, Andrew, Linda Burton, Judith Francis, Jane Henrici, Laura Lein, 

James Quane, and Karen Bogen, Sanctions and Case Closings for Noncompliance: Who Is Affected and Why, Policy Brief 01–1, Johns Hopkins University 

(http://web.jhu.edu/threecitystudy/images/publications/09_18058_Welfare_ 

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146. Matthews, MS, Kevin A., Janet B. Croft, Ph.D., Yong Liu, MD, MS, Hua 

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147. McHugh, M.A., M.P.P., Christina, J. Taylor Danielson, Ph.D., TANF Time 

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150. Mitchell, Tazra, LaDonna Pavetti, and Yixuan Huang, Life After TANF in 

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338 

20 Note: the submission is a pdf of the National Archives webpage (https://www.archives.gov/ 

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23 Note: the submission is an excerpt from the Public Law, p. 122 Stat. 1872–122 Stat. 1873. 

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24 Note: the submission is an excerpt from the webpage posting the Governor’s letter (https:// 

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195. Seefeldt, Kristin S., Sean M. Orzol, Watching the Clock Tick: Factors Associated with TANF Accumulation, National Poverty Center Working Paper Series, No. 04–9, NPC, University of Michigan, May 2004 (Revised May 2005) 

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204. Steadman, Ph.D., Henry J., Fred C. Osher, M.D., Pamela Clark Robbins, 

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207. ____, TN Realigns Workforce Development Areas, THE CHATANOOGAN.COM, 

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342 

25 Note: the submission does not include the attached appendicies, the copy retained in Committee file does. 26 Note: this document was included in the 27th attachment for Appendix B, as well as in 

the 28th attachment. However, it was not listed in the table of contents for attachment 27. 27 Note: the submission is an excerpt from the report Table A.14. Distribution of participating 

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213. Letter from Mary Ann Ferris, Chief, State Program Improvement, Food 

Stamp Program, Northeast Region, Food and Nutrition Service, USDA, April 

28, 2004, Re: ABAWD Waivers—New Method for Calculating Average Unemployment Rates 

214. Letter from Lizbeth Silbermann, Director, Program Development Division, 

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215. Gray, Kelsey Farson, Shivani Kochhar, Characteristics of Supplemental Nutrition Assistance Program Households: Fiscal Year 2014, Report No. SNAP– 

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216. Office of the Inspector General, USDA, FNS Controls Over SNAP Benefits 

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217. Facsimile from Office of Advocacy and Enterprise, Food and Nutrition Service, USDA, April 23, 1997, Re: Time Limit Waivers for Able-Bodied Food 

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218. Cronquist, Kathryn, Sarah Lauffer, Characteristics of Supplemental Nutrition Assistance Program Households: Fiscal Year 2017, Report No. SNAP–18– 

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219. Letter from Arthur T. Foley, Director, Program Development Division, Food 

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(https://www.fns.usda.gov/sites/default/files/snap/2-Year%20Approval%20 

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ABAWDs.pdf) 

220. Letter from Sasha Gersten-Paal, Chief, Certification Policy Branch, Program Development Division, Food and Nutrition Service, USDA, March 15, 

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221. Food and Nutrition Service, USDA, Guidance for States Seeking Waivers for 

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222. Food and Nutrition Service, USDA, Guidance on Requesting ABAWD Waivers, August 2006 

223. Food and Nutrition Service, USDA, Guide to Serving ABAWDs Subject to 

Time-limited Participation: A Guide on Serving Able-Bodied Adults without 

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343 

29 Note: this submission was duplicated in attachment 29. 30 Note: the submission is a ‘‘snapshot’’ of the webpage. 31 Note: the submission is a ‘‘snapshot’’ of the webpage. 

224. Letter from Arthur T. Foley, Director, Program Development Division, Food 

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225. Food and Nutrition Service, USDA, Perdue Reiterates Need to Restore Original Intent of SNAP: A Second Chance, Not A Way of Life, Press Release, February 28, 2019 (https://www.fns.usda.gov/pressrelease/2019/usda-002519) 

226. Food and Nutrition Service, USDA, Regulatory Reform at a Glance Proposed 

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227. Letter from Lizbeth Silbermann, Director, Program Development Division, 

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for Informing Households of ABAWD Rules (https://fns-prod.azureedge.net/ 

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228. Cromartie, John Rural America At A Glance, 2017 Edition, Economic Information Bulletin No. EIB–182, Economic Research Service, USDA, November 

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229. Letter from Lizbeth Silbermann, Director, Program Development Division, 

Food and Nutrition Service, USDA, June 26, 2015, Re: Supplemental Nutrition Assistance Program—Able-Bodied Adults without Dependents (ABAWD) 

Questions and Answers—June 2015 (https://fns-prod.azureedge.net/sites/default/files/snap/ABAWD-Questions-and-Answers-June%202015.pdf) 

230. Letter from Lizbeth Silbermann, Director, Program Development Division, 

Food and Nutrition Service, USDA, March 4, 2015, Re: Supplemental Nutrition Assistance Program—Expiration of Statewide ABAWD Time Limit Waivers (https://fns-prod.azureedge.net/sites/default/files/snap/SNAP-Expiration-of-Statewide-ABAWD-Time-Limit-Waivers.pdf) 

231. Letter from Lizbeth Silbermann, Director, Program Development Division, 

Food and Nutrition Service, USDA, and attached Guidance, December 2, 

2016, Re: Supplemental Nutrition Assistance Program—Guide to Supporting 

Requests to Waive the Time Limit for Able-Bodied Adults without Dependents 

(ABAWD) (https://fns-prod.azureedge.net/sites/default/files/snap/SNAPGuide-to-Supporting-Requests-to-Waive-the-Time-Limit-for-ABAWDs.pdf) 29

232. Food and Nutrition Service, USDA, SNAP E&T and WIOA: Partnering to 

Raise Skills and Employment, Policy Brief 8, June 8, 2018 (https:// 

snaptoskills.fns.usda.gov/sites/default/files/2018-06/Brief_June2018_508 

comp.pdf) 

233. Food and Nutrition Service, USDA, Why SNAP To Skills? (https:// 

snaptoskills.fns.usda.gov/why-snap-to-skills) 30

234. Letter from Lizbeth Silbermann, Director, Program Development Division, 

Food and Nutrition Service, USDA, November 19, 2015, Re: Supplemental 

Nutrition Assistance Program—ABAWD Time Limit Policy and Program Access (https://fns-prod.azureedge.net/sites/default/files/snap/ABAWD-TimeLimit-Policy-and-Program-Access-Memo-Nov2015.pdf) 

235. Food and Nutrition Service, USDA, State Highlights: California (https:// 

snaptoskills.fns.usda.gov/state-highlights/state-highlights-california) 31

236. Letter from Hon. Kevin W. Concannon, Under Secretary, Food, Nutrition 

and Consumer Service, USDA; and Portia Wu, Assistant Secretary, Employment & Training Administration, U.S. DOL, March 31, 2016, Re: Partnering 

to Help Connect Low-Income Able-bodied Adults to the Public Workforce System (https://fns-prod.azureedge.net/sites/default/files/snap/USDA-DOLjoint-ABAWD-letter.pdf) 

237. Food and Nutrition Service, USDA, February 26, 2018, Fact Sheet, Characteristics of Able-bodied Adults without Dependents (https://fnsprod.azureedge.net/sites/default/files/snap/nondisabled-adults.pdf) 

238. Mills, Gregory, Tracy Vericker, Heather Koball, Kye Lippold, Laura Wheaton; Sam Elkin,* Understanding the Rates, Causes, and Costs of Churning in 

344 

32 Note: the submission is a ‘‘snapshot’’ of the webpage. 33 Note: the webpage has been subsequently updated as of October 5, 2018. Note: the submission is a ‘‘snapshot’’ of the webpage. 

the Supplemental Nutrition Assistance Program (SNAP) Final Report, Urban 

Institute (* MEF Associates), November 4, 2014 (https://fnsprod.azureedge.net/sites/default/files/ops/SNAPChurning.pdf) 

239. Employment and Training Administration, U.S. DOL, Conformity Requirements for State UI Laws, Fact Sheet, January 6, 2016 (https://oui.doleta.gov/ 

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oui.doleta.gov/unemploy/supp_act.asp) 32

241. Employment and Training Administration, U.S. DOL, EUC 2008 Trigger 

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euc_112308.pdf) 

242. Leberg, Stanley, Labor Force, Employment, and Unemployment, 1929–39: 

Estimating Methods, MONTHY LABOR REVIEW, July 1948 (https:// 

www.bls.gov/opub/mlr/1948/article/pdf/labor-force-employment-and-unemployment-1929-39-estimating-methods.pdf) 

243. Employment and Training Administration, U.S. DOL, Labor Surplus Area 

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content/pkg/FR-2011-08-29/pdf/2011-22003.pdf) 

244. Employment and Training Administration, U.S. DOL, Labor Surplus Area: 

Frequently Asked Questions, April 5, 2018 (https://www.doleta.gov/lsa/ 

lsa_faq.cfm) 33

245. Nilsen, Sigurd R., Director, Education, Workforce, Income Security Issues, 

U.S. General Accounting Office, Food Stamp Employment and Training Program: Better Data Needed to Understand Who Is Served and What the Program Achieves, No. 03–388, March 12, 2003 (https://www.gao.gov/assets/ 

240/237571.pdf) 

246. Virginia Board of Workforce Development, Designation of Regions and Planning Requirements, Policy Memorandum No. 200–06 (2016), July 1, 2016 

(https://virginiacareerworks.com/wp-content/uploads/Policy-200-06-Designation-of-Regions-and-Planning-Requirements-FINAL-Signed.pdf) 

247. Vornholt, Katharina, Patrizia Villotti, Beate Muschalla, Jana Bauer, Adrienne Colella, Fred Zijlstra, Gemma Van Ruitenbeek, Sjir Uitdewilligen & 

Marc Corbie`re, Disability and employment—overview and highlights, EUROPEAN JOURNAL OF WORK AND ORGANIZATIONAL PSYCHOLOGY, Vol. 27 No. 1, 

October 10, 2017, p. 40–55 (https://www.tandfonline.com/doi/full/10.1080/ 

1359432X.2017.1387536) 

248. Wagner, Jennifer, 4,109 More Arkansans Lost Medicaid in October for Not 

Meeting Rigid Work Requirements, OFF THE CHARTS Blog, Center on Budget 

and Policy Priorities, October 16, 2018 (https://www.cbpp.org/blog/4109- 

more-arkansans-lost-medicaid-in-october-for-not-meeting-rigid-work-requirements) 

249. Wagner, Jennifer, Center on Budget and Policy Priorities, Commentary: As 

Predicted, Eligible Arkansas Medicaid Beneficiaries Struggling to Meet Rigid 

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(https://www.cbpp.org/health/commentary-as-predicted-eligible-arkansasmedicaid-beneficiaries-struggling-to-meet-rigid) 

250. Wagner, Jennifer, Commentary: As Predicted, Arkansas’ Medicaid Waiver Is 

Taking Coverage Away From Eligible People, Center on Budget and Policy 

Priorities, March 12, 2019 (https://www.cbpp.org/health/commentary-as-predicted-arkansas-medicaid-waiver-is-taking-coverage-away-from-eligible-people) 

251. Wagner, Jennifer, Fact Checking Arkansas Governor’s Claims About Jobs 

and Medicaid Waiver, OFF THE CHARTS Blog, Center on Budget and Policy 

Priorities, January 28, 2019 (https://www.cbpp.org/blog/fact-checking-arkansas-governors-claims-about-jobs-and-medicaid-waiver) 

252. Wagner, Jennifer,Medicaid Coverage Losses Mounting in Arkansas From 

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345 

34 Note: this submission consists of two sub-articles. The full article entitled, How do welfare 

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ities, January 17, 2019 (https://www.cbpp.org/blog/medicaid-coverage-lossesmounting-in-arkansas-from-work-requirement) 

253. Walker, Renee E., Christopher R. Keane, Jessica G. Burke, Disparities and 

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254. Watson, Ian, Beyond the Unemployment Rate: Building a Set Indicies to 

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pubs/beyond%20the%20unemployment%20rate.pdf) 

255. Welles, Seth L., Falguni Patel, Mariana Chilton, Does Employment-Related 

Resilience Affect the Relationship between Childhood Adversity, Community 

Violence, and Depression?, JOURNAL OF URBAN HEALTH, April 2017, 94(2): p. 

233–243 (https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5391326/) 

256. The Pew Charitable Trusts, Collateral Costs: Incarceration’s Effect on Economic Mobility, September 28, 2010 (https://www.pewtrusts.org/en/researchand-analysis/reports/0001/01/01/collateral-costs) 

257. Western, Bruce, Becky Pettit, Incarceration & social inequality, D#DALUS

Summer 2010, p. 8–19 

258. Westra, Ph.D., Karen L., John Routley, Arizona Cash Assistance Exit Study, 

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259. Williamson, MPP, Sarah, Full-Family Sanctions & Economic Recession, 

Family Welfare Research and Training Group, University of Maryland School 

of Social Work, January 2011 (https://familywelfare.umaryland.edu/ 

reports1/sanctionsbrief.pdf) 

260. Wilson, Claire, Brian Estes, Examining the Growth of the Zero-Income 

SNAP Caseload: Characteristics, Circumstances, and Dynamics of Zero-Income SNAP Participants, Volume II: In-Depth Interview Findings, Insight Policy Research, Inc., October 2014 (https://fns-prod.azureedge.net/sites/default/files/ops/ZeroIncome-Vol2.pdf) 

261. Wilson, Valerie, Before the State of the Union, a fact check on black unemployment, WORKING ECONOMICS Blog, February 1, 2019 (https:// 

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262. Department of Workforce Development, State of Wisconsin, Wisconsin 

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default/files/ocr/civilrights/activities/examples/TANF/wi_tanf_w2study.pdf) 

263. Wolkomir, Elizabeth, How SNAP Can Better Serve the Formerly Incarcerated, Center on Budget and Policy Priorities, March 16, 2018 (https:// 

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264. Wu, Chi-Fang, Maria Cancian, Daniel R. Meyer, Sanction policies and outcomes in Wisconsin, p. 38–40; and Lee, Bong Joo, Kristen Shook Slack, Dan 

A. Lewis, Sanctions policies and outcomes in Illinois, p. 41–43: FOCUS Vol. 23, 

No. 1, Winter 2004 (https://www.irp.wisc.edu/publications/focus/pdfs/ 

foc231f.pdf) 34

265. Wu, Chi-Fang, Maria Cancian, Daniel R. Meyer, Geoffrey L. Wallace, How 

Do Welfare Sanctions Work?, SOCIAL WORK RESEARCH, Volume 30, Number 

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267. Yellen, Janet L., Chair, Board of Governors of the Federal Reserve System, 

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346 

35 Note: this submission consists of one policy memo in the report Expanding Economic Opportunity for More Americans: Bipartisan Policies to Increase Work, Wages, and Skills (https:// 

assets.aspeninstitute.org/content/uploads/2019/01/ESG_Report_Expanding-Economic-Opportunity-for-More-Americans.pdf). The full report is retained in the Committee file. 

268. Ziliak, James P., Restoring Economic Opportunity for ‘‘The People Left Behind’’: Employment Strategies for Rural America, in Part II: Increasing PrimeAge Labor Force Participation, of EXPANDING ECONOMIC OPPORTUNITY FOR

MORE AMERICANS: BIPARTISAN POLICIES TO INCREASE WORK, WAGES, AND

SKILLS, Aspen Institute Economic Strategy Group, February 2019, p. 100–126 

(https://assets.aspeninstitute.org/content/uploads/2019/01/2.2-Pgs.-100-126- 

Restoring-Economic-Opportunity....pdf) 35

269. Ziliak, James P., Temporary Assistance For Needy Families, National Bureau of Economic Research, NBER Working Paper No. 21038 (https:// 

www.nber.org/papers/w21038) 

SUBMITTED COMMENT LETTER BY HON. JEFFERSON VAN DREW, A REPRESENTATIVE

IN CONGRESS FROM NEW JERSEY; AUTHORED BY KATE LEONE, CHIEF GOVERNMENT

RELATIONS OFFICER, FEEDING AMERICA

April 2, 2019 

Ms. SASHA GERSTAN-PAAL, Chief, 

Certification Policy Branch, 

SNAP Program Development Division, 

Food and Nutrition Service, USDA, 

Alexandria, Virginia 

RE: Proposed Rule: Supplemental Nutrition Assistance Program (SNAP): 

Requirements for Able-Bodied Adults without Dependents RIN 0584– 

AE57 

Dear Ms. Gerstan-Paal: 

We appreciate the opportunity to comment on USDA’s Proposed Rulemaking on 

requirements and services for Able-Bodied Adults Without Dependents (ABAWDs). 

The proposed changes would make it harder for individuals facing food insecurity 

to have the resources they need to purchase healthy food. The changes would harm 

those individuals and their community, putting an unnecessary burden on food 

banks and other service providers. We strongly encourage USDA to rescind this 

rule. 

Feeding America is the nationwide network of 200 food banks that leads the fight 

against hunger in the United States. Together, we provide food to more than 46 million people through 60,000 food pantries and meal programs in communities across 

America. Feeding America also supports programs that improve food security among 

the people we serve; educates the public about the problem of hunger; and advocates 

for legislation that protects people from going hungry. This includes working to ensure people understand and are able to access Federal nutrition assistance programs like SNAP, through education and outreach, and related support services 

such as nutrition education and work support services, including SNAP Employment and Training. 

Feeding America cares about the 3 month time limit for ABAWDs because this 

policy has cut off food assistance to so many in communities across the country who 

are in need just because they are unable to find a reliable 20 hour a week job or 

otherwise document their 20 hours of qualifying activities. Feeding America released a statement in April 2016 (online here (http://www.feedingamerica.org/ 

about-us/press-room/feeding-america-food-banks.html) and below) expressing our 

concern as the state waivers were going away, either naturally or due to state decisions, that policies like these that take important food resources away from vulnerable individuals will only make it harder to ensure community members are nourished and ready for the workforce. We subsequently released statements in December 2018 (online here (https://www.feedingamerica.org/about-us/press-room/feeding-america-statement-able-bodied-adults-without-dependents-proposed-rule) and 

below) and February 2019 (online here (https://www.feedingamerica.org/about-us/ 

press-room/feeding-america-opposes-harmful-snap-proposed-rule-released-usda) and 

below) expressing concerns about this notice of proposed rulemaking which we are 

commenting on today. 

We strongly encourage USDA to rescind this rule. 

347 

1World Health Organization, https://www.who.int/hia/evidence/doh/en/index3.html, see 

also Craig Gundersen and James P. Ziliak, ‘‘Food Insecurity and Health Outcomes,’’ Health Affairs, November 2015, https://www.healthaffairs.org/doi/10.1377/hlthaff.2015.0645. 2 Christian A. Gregory and Alisha Coleman-Jenson, ‘‘Food Insecurity, Chronic Disease, and 

Health Among Working-Age Adults,’’ United States Department of Agriculture, July 2017, 

https://nopren.org/wp-content/uploads/2017/08/ERS-Report-Food-Insecurity-Chronic-Diseaseand-Health-Among-Working-Age-Adults.pdf. 3Pamela L. Loprest and Elaine Maag, ‘‘Disabilities among TANF Recipients: Evidence from 

the NHIS,’’ Urban Institute, May 2009, http://www.urban.org/research/publication/disabilities-among-tanf-recipients-evidence-nhis. 4 Hartline-Grafton, H. (2017). The Impact of Poverty, Food Insecurity, & Poor Nutrition on 

Health and Well-Being. Washington, D.C.: Food Research & Action Center. 5 Economic Research Service, U.S. Department of Agriculture. (2018). Definitions of Food Security. Available at https://www.ers.usda.gov/topics/food-nutrition-assistance/food-security-inthe-us/definitions-of-food-security.aspx Accessed October 3, 2018. 6Franklin B. Jones, A., Love, D., Puckett, S., Macklin, J., & White-Means, S. (2012). Exploring mediators of food insecurity and obesity: a review of recent literature. JOURNAL OF COMMUNITY HEALTH. 37(1), 253–264. 7 Berkowitz, S., A., Karter, A., J., Corbie-Smith, G., Seligman, H. K., Ackroyd, S.A., Barnard, 

L.S., Atlas, S.J., & Wexler, D.J. (2018). Food insecurity, food ‘‘deserts,’’ and glycemic control in 

patients with diabetes: a longitudinal analysis. DIABETES CARE, 19, 171981. 8Gregory, C., A., & Coleman-Jensen, A. (2017). Food insecurity, chronic disease, and health 

among working-age adults. Economic Research Report, 235. Washington, D.C.: U.S. Department 

of Agriculture, Economic Research Service. 

SNAP Matters 

SNAP plays a critical role in addressing hunger and food insecurity in our community. It is the first line of defense against hunger. 

Based on USDA Economic Research Service analysis, it is estimated that each $1 

in Federal SNAP benefits generates $1.79 in economic activity. Those dollars help 

many food retailers operating on thin margins to remain in business; something 

that improves food access for all residents. 

Access to healthy food is a critical social determinant of health and food insecurity 

is associated with poorer health outcomes.1 Food insecurity is associated with higher 

rates of some of the most serious and costly chronic conditions, including hypertension, coronary heart disease, cancer, asthma, diabetes, and many other serious 

health conditions. Adults who experience food insecurity are also more likely to report lower health status overall.2

SNAP plays a critical role in addressing hunger and food insecurity in our communities: it is the first line of defense against hunger for low-income residents. Research shows that SNAP reduces poverty and food insecurity, and that over the 

long-term, these impacts lead to improved health and economic outcomes, especially 

for those who receive SNAP as children. 

Limiting access to nutrition assistance could be particularly harmful for people 

with significant health care needs, such as diabetes or hypertension, who may also 

have trouble maintaining their health while keeping a job. Many people turn to public assistance programs because they face significant health or family challenges 

that limit their ability to work or reduce their ability to compete for a limited supply 

of jobs. Physical and mental health conditions that limit an individual’s ability to 

work or limit the amount or kind of work the individual can do are much more common among public benefit recipients than among the general population, research 

shows.3 Taking access to nutrition assistance away from people with serious health 

conditions could negatively affect their health, which could make it even more difficult for them to maintain employment. 

Food insecurity increases the risk of negative physical and mental health outcomes 

Food insecurity is a risk factor for negative psychological and health outcomes.4

(The U.S. Department of Agriculture defines food insecurity as a ‘‘lack of consistent 

access to enough food for an active, healthy life.’’ 5) Food insecurity has deleterious 

impacts on health through increases in the prevalence and severity of diet-related 

disease, such as obesity, type 2 diabetes, heart disease, stroke, and some cancers.6–8

In addition, because of limited financial resources, those who are food-insecure— 

with our without existing disease—may use coping strategies to stretch budgets that 

are harmful for health, such as engaging in cost-related medication underuse or 

348 

9 Herman, D., Afulani, P., Coleman-Jensen, A., & Harrison, G.G. (2015). Food insecurity and 

cost-related medication underuse among nonelderly adults in a nationally representative sample: 

AMERICAN JOURNAL OF PUBLIC HEALTH, 105(10), 48–59. 10 Afulani, P., Herman, D., Coleman-Jensen, A., & Harrison G.G. (2015). Food insecurity and 

health outcomes among older adults: The role of cost-related medication underuse. JOURNAL OF

NUTRITION IN GERONTOLOGY AND GERIATRICS, 34(3), 319–343. 11Knight, C.K., Probst, J.C., Liese, A., D., Sercy, E., & Jones, S.J. (2016). Household food insecurity and medication ‘‘scrimping’’ among U.S. adults with diabetes. PUBLIC HEALTH [NUTRI- TION], 19(6), 1103–1111. 12Mayer, V.L., McDonough, K., Seligman, H., Mitra, N., & Long, J.A. (2016). Food insecurity, 

coping strategies and glucose control in low-income patients with diabetes. PUBLIC HEALTH NU- TRITION, 19(6), 1103–1111. 13Kushel, M.B., Gupta, R., Gee, L., & Haas, J.S. (2006). Housing instability and food insecurity as barriers to health care among low-income Americans. JOURNAL OF GENERAL INTERNAL

MEDICINE, 21, 71–77. 14Seligman, H.K., Jacobs, E.A., Lopez, A., Tschann, J., & Fernandez, A. (2012). Food insecurity and glycemic control among low-income patients with type 2 diabetes. DIABETES CARE, 35(2), 

233–238. 15Tarasuk, V., Cheng, J., de Oliveira, D., Dachner, N., Gundersen, C., & Kurdyak, P. (2015). 

Association between household food insecurity and annual health care costs. CANADIAN MEDICAL

ASSOCIATION JOURNAL, 187 (14), E429–436. 16 Berkowitz, S.A., Basu, S., Meigs, J.B., & Seligman, H. (2017). Food insecurity and health 

expenditures in the United States, 2011–2013. HEALTH SERVICES RESEARCH, 53(3), 1600–1620. 17Mabli, J., & Worthington, J. (2014). Supplemental Nutrition Assistance Program participation and child food security. PEDIATRICS, 133(4), 1–10. 18 Ratcliffe, C., McKernan, S.M., & Zhang, S. (2011). How much does the Supplemental Nutrition Assistance Program reduce food insecurity? AMERICAN JOURNAL OF AGRICULTURAL ECONOM- ICS, 93(4), 1082–1098. 

19 Nord, M. (2012). How much does the Supplemental Nutrition Assistance Program alleviate 

food insecurity? Evidence from recent programme leavers. PUBLIC HEALTH NUTRITION, 15(5), 

811–817. 20 Ratcliffe, C., McKernan, S.M., & Zhang, S. (2011). How much does the Supplemental Nutrition Assistance Program reduce food insecurity? AMERICAN JOURNAL OF AGRICULTURAL ECONOM- ICS, 93(4), 1082–1098. 

21 Coleman-Jensen, A., Rabbit, M.P., Gregory, C.A. & Singh, A. (2018). Household food insecurity in the United States in 2017. Economic Research Service Report, 256, Washington, D.C.: 

U.S. Department of Agriculture, Economic Research Service. 22Gregory, C.A., & Deb, P. (2015). Does SNAP improve your health? FOOD POLICY, 50, 11– 

19. 23 Berkowitz, S.A., Seligman, H.K., Rigdon, J., Meigs, J.B., & Basu, S. (2017). Supplemental 

Nutrition Assistance Program (SNAP) participation and health care expenditures among low-income adults. JAMA INTERNAL MEDICINE, 177(11), 1642–1649. 24Seligman, H.K., Bolger, A.F., Guzman, D., Lopez, A., & Bibbins-Domingo, K. (2014). Exhaustion of food budgets at month’s end and hospital admissions for hyperglycemia. HEALTH AF- FAIRS, 33(1), 116–123. 25 Berkowitz, S.A., Seligman, H.K., Rigdon, J., Meigs, J.B., & Basu, S. (2017). Supplemental 

Nutrition Assistance Program (SNAP) participation and health care expenditures among low-income adults. JAMA INTERNAL MEDICINE, 177(11), 1642–1649. 26 Hartline-Grafton, H. (2017). SNAP and Public Health: The Role of the Supplemental Nutrition Assistance Program in Improving the Health and Well-Being of Americans. Washington, 

D.C.: Food Research & Action Center. 

non-adherence; 9–11 postponing or forgoing preventives or needed medical care; 12–13

and forgoing the foods needed for special medical diets (e.g., diabetic diets).14 Not 

surprisingly, research shows that household food insecurity is a strong predictor of 

higher health care utilization and increased health care costs.15–16

SNAP decreases food insecurity 

Overall, research shows that SNAP is effective at reducing food insecurity.17–19

According to one estimate, SNAP reduces food insecurity by approximately 30 percent.20 SNAP, therefore, is an effective anti-hunger program, and more eligible people need to be connected to the program given the current high rates of food insecurity in the nation. Nearly one in eight American households experience food insecurity during the year.21

SNAP is associated with decreased health care costs 

Research demonstrates that SNAP reduces health care utilization and costs.22–24

For example, a national study revealed that SNAP participation was associated with 

lower health care costs.25 On average, low-income adults participating in SNAP incurred nearly 25 percent less in health care costs in 12 month, including those paid 

by private or public insurance, than low-income adults not participating in SNAP. 

SNAP is associated with improved physical and mental health 

SNAP improves children, adult, and senior health outcomes, including physical 

and mental health.26 For instance, SNAP increases the probability of self-reporting 

349 

27Gregory, C.A., & Deb, P. (2015). Does SNAP improve your health? FOOD POLICY, 50, 11– 

19. 28Mayer, V.L., McDonough, K., Seligman, H., Mitra, N., & Long, J.A. (2016). Food insecurity, 

coping strategies and glucose control in low-income patients with diabetes. PUBLIC HEALTH NU- TRITION, 19(6), 1103–1111. 29Leung, C.W., Epel, E.S., Willett, W.C., Rimm, E.B., & Laraia, B.A. (2015). Household food 

insecurity is positively associated with depression among low-income Supplemental Nutrition Assistance Program participants and income-eligible nonparticipants. JOURNAL OF NUTRITION, 145(3), 622–627. 30 Juster, R.-P., McEwen, B.S., & Lupien, S.J. (2010). Allostatic load biomarkers of chronic 

stress and impact on health and cognition. NEUROSCIENCE AND BIOBEHAVIORAL REVIEWS, 35(1), 

2–16. 31 A 2002 study that looked at recipients after leaving SNAP found that while many were employed, they had low earnings, and between 1⁄3 and roughly 2⁄3 of SNAP leavers had household 

incomes below the poverty line. (This study did not examine the effects of the time limit on employment.) See Elizabeth M. Dagata, ‘‘Assessing the Self-Sufficiency of Food Stamp Leavers,’’ 

Economic Research Service, USDA, September 2002 , https://www.ers.usda.gov/publications/ 

pub-details/?pubid=46645. More recent research finds small increases in employment, but much 

larger decreases in SNAP participation. For example, one recent working paper found that the 

time limit increased work by two percentage points, but decreased participation by ten percentage points. (Timothy Harris, ‘‘Do SNAP Work Requirements Work?’’ Upjohn Institute Working 

Paper, 19–297, https://research.upjohn.org/cgi/viewcontent.cgi?article=1315&context= 

up_workingpapers.) 

‘‘excellent’’ or ‘‘good health,’’ 27 lowers the risk of poor glucose control (for those with 

diabetes),28 and has a protective effect on mental health.29 Journal SNAP also helps 

reduce stress for struggling individuals and families worried about finances, and 

stress is highly correlated with poor health outcomes.30

Area Waivers and Individual Exemptions Provide Ways to Modestly Ameliorate the Harsh Impact of Arbitrary Time Limits 

Federal law limits SNAP eligibility for childless unemployed and underemployed 

adults age 18–50 (except for those who are exempt) to just 3 months out of every 

3 years unless they are able to obtain and maintain an average of 20 hours a week 

of employment. This rule in its current form is harsh and unfair. It harms vulnerable people by denying them food benefits at a time when they most need it and 

it does not result in increased employment and earnings.31 At least 500,000 low-income individuals nationwide lost SNAP in 2016 due to the time limit. This put their 

food security at risk. And, by time-limiting food assistance to this group, Federal 

law has shifted the burden of providing food to these unemployed individuals from 

SNAP to local charities, states, and cities. 

Under the law, states have some flexibility to ameliorate the impact of the cutoff. 

They can request a waiver of the time limit for areas within the state that have 

ten percent or higher unemployment rates or, based on other economic indicators, 

have ‘‘insufficient jobs.’’ Moreover, states have discretion to exempt individuals from 

the time limit by utilizing a pool of exemptions (referred to as ‘‘15 percent’’ exemptions). While the 2018 Farm Bill modified the number of exemptions that states can 

receive each year from 15 percent to 12 percent, it did not change their ability to 

carry over unused exemptions forward. 

Proposed Rule Undermining Law’s Safety Valves Should Be Rejected 

Feeding America strongly opposes the proposed rule changes that would expose 

even more people to the arbitrary food cutoff policy by limiting state flexibility regarding area waivers and individual exemptions. By the Administration’s own calculations, the proposed rule would take food away from 755,000 low-income Americans, cutting food benefits by $15 billion over 10 years. This is the equivalent of 

around 8.5 billion meals lost from the tables of individuals. The Administration does 

not estimate any improvements in health or employment among the affected population. 

The proposed rule would make it harder for areas with elevated unemployment 

rates to qualify for waivers of the time limit by adding a seven percent unemployment rate floor as a condition. 

The proposed rule would make it harder for states to obtain and implement area 

waivers by dropping statewide waivers except when a state triggers extended benefits under Unemployment Insurance. It would unduly limit the economic factors considered in assessing an area’s eligibility for a waiver (e.g., by no longer allowing employment to population ratios that demonstrate economic weakness to qualify areas 

for waivers). It would undermine efficient state implementation of area waivers by 

limiting their duration to 12 months and delaying their start dates until after 

USDA processes the request. In addition, the proposed rule would remove states’ 

ability to use exemptions accumulated prior to the rule’s implementation as well 

350 

32 Nune Phillips, ‘‘SNAP and Work,’’ Center for Law and Social Policy, January 2018, https:// 

www.clasp.org/sites/default/files/publications/2018/01/2018_snapandwork.pdf. 33Ladonna Pavetti, Work Requirements Don’t Cut Poverty, Evidence Shows, Center on Budget 

and Policy Priorities, June 2016, https://www.cbpp.org/research/poverty-and-inequality/workrequirements-dont-cut-poverty-evidence-shows. 34 Ibid. 

limit the time states’ have to use exemptions they receive in the future. [Add any 

examples or details about how these proposals would affect your state, or a region 

in your state.] 

The Department provides little analysis to explain its conclusions about the impacts the changes would have on individuals and population groups nor of realistic 

plans to avert harm from those changes. USDA merely asserts its expectation that 

2⁄3 of those individuals made newly subject to the time limit ‘‘would not meet the 

requirements for failure to engage meaningfully in work or work training.’’ Moreover, while the Department concedes that the proposed changes ‘‘have the potential 

for disparately impacting certain protected groups due to factors affecting rates of 

employment of these groups, [it] find[s] that implementation of mitigation strategies 

and monitoring by the Civil Rights Division of FNS will lessen these impacts.’’ But 

no explanation of the mitigation strategies and monitoring is provided, so there is 

no opportunity for us to comment on whether the acknowledged disparate impact 

will in fact be mitigated. 

Proposal Does Not Improve Employment Outcomes—and Would Undermine 

Investments in Programs that Do 

Time Limits and Work Reporting Requirements Do Not Encourage Employment 

The proposed rule does not require states to offer any work opportunities or employment and training activities to individuals subject to the time limit. Historically, 

many states have chosen not to help people subject to the time limit find qualifying 

work or training activities.32 Many people who are willing to participate in such activities will lose SNAP if they cannot find a countable activity—which does not include job search—on their own. 

Some state and local leaders have worked hard over the past decade to intentionally engage SNAP participants in high-quality programs and develop partnerships for SNAP Employment & Training (E&T). However, these efforts, still in early 

stages, require substantial resources and capacity to deliver outcomes. This investment in quality, high-intensity programs will likely shift as some states seek to 

spread limited SNAP E&T resources thinly to help more people meet SNAP time 

limit rules. The resulting low-intensity SNAP E&T programs have proven to be ineffective in moving SNAP recipients into jobs that will allow them to achieve economic 

security. 

If SNAP recipients do manage to find low-wage jobs to meet work reporting requirements, they do not fare any better in the long run than those in low-intensity 

SNAP E&T programs. Lessons learned from TANF, SNAP, and other programs 

demonstrate that work reporting requirements are not effective in connecting people 

to living-wage jobs.33 As laid out by the Center on Budget and Policy Priorities in 

a review of rigorous evaluations, research shows that employment increases among 

individuals subject to work reporting requirements were modest and faded over 

time. In nearly all of the approximately dozen programs evaluated, employment 

among recipients not subject to work reporting requirements was the same as or 

higher than employment among individuals subject to work reporting requirements 

within 5 years.34

Work reporting requirements are not only ineffectual but have opportunity costs: 

the time that a SNAP recipient loses in low-intensity programs or low-wage jobs 

simply to meet requirements could have been spent obtaining skills and credentials, 

finding a quality job, and increasing their earnings. A much better focus for public 

policy is to invest in strategies that support people to develop skills and access 

training that prepares them for jobs that pay living wages and foster an economy 

that creates more quality jobs with fair wages. 

Workforce Systems to Serve those Subject to the Time Limit are Underfunded 

Even if states offer services to individuals newly subject to the time limits, many 

will offer low-intensity services, aimed primarily at providing recipients with enough 

hours of participation to meet the requirements, rather than high quality services. 

Existing workforce systems, which are chronically under-funded, are not often designed to serve the range of needs of all those subject to the time limit. Some struggling workers will have substantial stabilization needs, e.g., emergency housing, 

transportation, and dependent care. As people surmount those barriers, meeting a 

351 

35Food Stamp Employment and Training Program: Better Data Needed to Understand Who 

Is Served and What The Program Achieves, U.S. Government Accountability Office, March 2003, 

https://www.gao.gov/assets/240/237571.pdf. 36 Ibid., 9. 37 ‘‘Worst Case Housing Needs 2017 Report to Congress,’’ U.S. Department of Housing and 

Urban Development, August 9, 2017, https://www.huduser.gov/portal/sites/default/files/pdf/ 

Worst-Case-Housing-Needs.pdf. 38 ‘‘The State of the Nation’s Housing 2018,’’ Joint Center for Housing Studies of Harvard University, 2018, 31, https://www.jchs.harvard.edu/sites/default/files/Harvard_JCHS_ 

State_of_the_Nations_Housing_2018.pdf. 39 ‘‘Three Out of Four Low-Income At-Risk Renters Do Not Receive Federal Rental Assistance,’’ Center on Budget and Policy Priorities, August 8, 2017, https://www.cbpp.org/three-outof-four-low-income-at-risk-renters-do-not-receive-federal-rental-assistance. 

need as basic as food is paramount. The Government Accountability Office (GAO) 

found that SNAP participants subject to the time limit are more likely than other 

SNAP participants to lack basic job skills like reading, writing, and basic math.35

People should not be punished for grappling with hardship. 

Instead of penalizing people for needing assistance to put food on the table, USDA 

should consider ways to create a foundation for long-term economic success. Voluntary SNAP E&T programs, for instance, do not subject individuals to sanctions 

that increase food insecurity. In fact, research shows that voluntary programs can 

significantly increase employment, while mandatory SNAP E&T programs withhold 

basic assistance if individuals cannot meet participation requirements in a given 

month.36 To attract SNAP recipients to voluntary SNAP E&T programs, states can 

partner with trusted service providers that operate programs with a successful track 

record. Furthermore, mandating participation in employment or training programs 

requires participating organizations to spend time tracking attendance and not serving clients with the programs they need to succeed. 

The Proposed Rule Would Harm People Who Already Struggle to Afford 

Housing 

The lack of affordable housing is a nationwide crisis, with more than eight million 

households paying more than 1⁄2 of their income on rent.37 People whose rent is 

unaffordable have less money to spend on other necessities, such as food, 

healthcare, and transportation. For example, families that spend more than 1⁄2 of 

their income on rent in order to avoid eviction and homelessness spend on average 

$190 less per month on food compared to families that spend less than 30 percent 

of their income on rent.38 In fact, from 2001 to 2016, many low-income households 

across the country saw their rents increase as their incomes stagnated or decreased, 

meaning they have less money left over each month and are likely at higher risk 

of food insecurity. People experiencing homelessness also face difficulty affording 

food, which is often compounded by not having places to safely store and prepare 

food items. For people struggling to afford a place to live, SNAP is a vital lifeline 

that helps prevent food insecurity. 

The proposed rule would limit states’ flexibility to mitigate the harmful effects of 

the time limit. Without this flexibility, it’s likely that many people could lose access 

to nutrition assistance. For people with severe housing cost burden—or those who 

spend 50 percent or more of their income on rent—limiting access to nutrition assistance could have serious repercussions for their housing stability, food security, 

and health. 

Limiting access to nutrition assistance could be particularly harmful for people 

who face housing instability or homelessness. Many people turn to public assistance 

programs such as SNAP because they face significant challenges with affording everyday necessities, including a safe place to live. Three in four people who qualify 

for Federal rental assistance that would make rent affordable don’t receive it because of limited funding, making SNAP even more vital.39 In addition, low-income 

individuals with poor health are oftentimes one injury or illness away from falling 

into homelessness. Without food assistance, people who were already struggling to 

pay rent may have to choose between paying rent or putting food on the table, increasing their risk of eviction and homelessness. 

Homelessness—which is primarily caused by the lack of affordable housing—can 

contribute to new health issues and worsen existing ones. For example, people who 

live outdoors or in a homeless shelter oftentimes don’t have a secure place to store 

medication or prepare the foods needed to manage health conditions, such as diabetes. Furthermore, soup kitchens and shelters are often not conducive to maintaining 

352 

40 ‘‘Homelessness and Health: What’s the Connection?’’ National Health Care for the Homeless 

Council, 2011, https://www.nhchc.org/wp-content/uploads/2011/09/Hln_health_fact 

sheet_Jan10.pdf. 41 Nat’l Women’s Law Ctr., Interactive Map: Women And Men In The Low-Wage Workforce 

(July 20, 2018), https://nwlc.org/resources/interactive-map-women-and-men-low-wage-workforce/. 42See generally Nat’l Women’s Law Ctr., Collateral Damage: Scheduling Challenges for Workers in Low-Wage Jobs and Their Consequences (Apr. 2017), available at https://nwlcciw49tixgw5lbab.stackpathdns.com/wp-content/uploads/2017/04/Collateral-Damage.pdf (hereinafter ‘‘Collateral Damage’’). 43 Nat’l Women’s Law Ctr. calculations based on IPUMS 2018, supra note 4. 44 Id. 45 Andrea Johnson, et al., Stepping Up: New Policies and Strategies Supporting Parents in 

Low-Wage Jobs and Their Children 22 (Aug. 2018), available at https://nwlcciw49tixgw5lbab.stackpathdns.com/wp-content/uploads/2018/08/v2_final_nwlc_SteppingUp 

KelloggReport.pdf. 46Women perform the majority of caregiving. See Bureau of Labor Statistics, U.S. Dep’t of 

Labor, American Time Use Survey, Table A–1. Time spent in detailed primary activities and percent of the civilian population engaging in each activity, averages per day by sex, 2017 annual 

averages (2018), available at https://www.bls.gov/tus/a1_2017.pdf. 47 Collateral Damage, supra note 19, at 2. 48 Collateral Damage, supra note 19, at 1. 49See, e.g., Rest. Opportunities Ctrs. United & Forward Together, The Glass Floor: Sexual 

Harassment in the Restaurant Industry 5 (2014), available at http://rocunited.org/wp-content/ 

uploads/2014/10/REPORT_The-Glass-Floor-Sexual-Harassment-in-the-Restaurant-Industry 

2.pdf; Human Rights Watch, Cultivating Fear: The Vulnerability of Immigrant Farmworkers in 

the U.S. to Sexual Violence and Sexual Harassment (May 2012), available at https:// 

www.hrw.org/report/2012/05/15/cultivating-fear/vulnerability-immigrant-farmworkers-us-sexual-violence-and-sexual (documenting pervasive sexual harassment and violence among immigrant farmworker women); Irma Morales Waugh, Examining the Sexual Harassment Experiences 

of Mexican Immigrant Farmworking Women, 16 VIOLENCE AGAINST WOMEN 237, 241 (Jan. 

2010), available at http://vaw.sagepub.com/content/16/3/237.abstract (80% of female farmworkers in California’s Central Valley reported experiencing some form of sexual harassment); 

Unite Here Local 1, Hands Off, Pants On: Sexual Harassment In Chicago’s Hospitality Industry 

(July 2016), available at https://www.handsoffpantson.org/wp-content/uploads/ 

HandsOffReportWeb.pdf (58% of hotel workers and 77% of casino workers surveyed reported 

being sexually harassed by a guest); Hart Res. Assoc., Key Findings From a Survey of Women 

Fast Food Workers (Oct. 5, 2016), available at http://hartresearch.com/wp-content/uploads/ 

2016/10/Fast-Food-Worker-Survey-Memo-10-5-16.pdf (nationwide survey of workers in the fast 

food industry found nearly 40% of the women reported experiencing unwanted sexual behaviors 

on the job, and 21% of those workers reported that they suffered negative workplaces consequences after raising the harassment with their employer). 50 Amanda Rossie, Jasmine Tucker & Kayla Patrick, Nat’l Women’s Law Ctr., Out of the 

Shadows: An Analysis of Sexual Harassment Charges Filed By Working Women 8 (Aug. 2018), 

a healthy diet since many offer meals with high sugar, salt, and starch content.40

Homelessness itself also creates additional barriers to employment, because individuals do not have easy access to computers and phones to apply for jobs, or showers 

and laundry facilities to maintain personal hygiene. Taking nutrition assistance 

away from people experiencing homelessness could therefore make it even more difficult to find and maintain employment and become stably housed. 

Restricting a state’s waiver authority and use of individual exemptions 

will harm women who want to work but face challenges in receiving and 

reporting 20 hours of work each week. 

Women with low incomes may face particular barriers to consistently working 

(and reporting) 20 hours of work per week. Women are over-represented in the lowwage workforce,41 which is plagued by unstable and unpredictable work schedules.42

Compared to women’s representation in the overall workforce, women of virtually 

all races and ethnicities are over-represented in low-wage jobs (typically paying less 

than $11.50 per hour).43 Of the nearly 22.6 million people working in low-wage jobs, 2⁄3 are women.44

The unpredictable and unstable work schedules that are common in retail, food 

service, and other low-wage jobs can prevent women from working 20 hours per 

week, every week. Many low-wage jobs lack paid leave,45 which presents another 

obstacle for women with caregiving responsibilities 46 for people outside of the narrow time limit caregiving exemption. In addition, many low-wage jobs offer only 

part-time work, despite many workers’ need and desire for full-time hours.47 And 

the combination of insufficient hours and variable schedules can impede women 

from working more than one job to make ends meet.48

In addition, many women, particularly those in low-wage jobs, face discrimination 

and harassment at work.49 Between 2012 and 2016, 36 percent of women who filed 

sexual harassment charges also alleged retaliation, such as lost hours or job loss.50

353 

available at https://nwlc-ciw49tixgw5lbab.stackpathdns.com/wp-content/uploads/2018/08/ 

SexualHarassmentReport.pdf. 51See Robin Fudowitz, MaryBeth Musumeci & Cornelia Hall, Kaiser Family Found., Year End 

Review: December State Data for Medicaid Work Requirements in Arkansas (Jan. 17, 2019), 

https://www.kff.org/medicaid/issue-brief/state-data-for-medicaid-work-requirements-in-arkansas/ (noting that nearly all of the Arkansas Medicaid enrollees not exempt from the reporting 

requirement did not report any work activities, which could result from difficulty accessing the 

online reporting portal). 52Samantha Artiga, et al., ‘‘Key Facts on Health and Health care By Race and Ethnicity,’’ Kaiser Family Found[a]tion, June 07, 2016, https://www.kff.org/disparities-policy/report/key-factson-health-and-health-care-by-race-and-ethnicity/. 53 Bureau of Labor Statistics, https://www.bls.gov/opub/ted/2017/unemployment-rate-andemployment-population-ratio-vary-by-race-and-ethnicity.htm. 54 ‘‘People in the Labor Force and Not in the Labor Force by Selected Characteristics, 2017 

Annual Averages,’’ U.S. Bureau of Labor Statistics, https://www.bls.gov/opub/reports/raceand-ethnicity/2017/home.htm; ‘‘Employed and Unemployed Full- and Part-time Workers by 

Age, [Sex], Race, and Hispanic or Latino Ethnicity,’’ U.S. Bureau of Labor Statistics, December 

2018, https://www.bls.gov/cps/cpsaat08.htm. 

All of these factors can make it difficult for low-income working women to satisfy 

SNAP’s 20 hour per week reporting requirement. As a result, women struggling 

with underemployment face a double risk: if their employer schedules them for 

fewer hours, then their wages decrease, and they are at risk of losing SNAP benefits. Even women who happen to receive enough hours to meet the time limit reporting requirement are still at risk of losing benefits if they are unable to meet burdensome administrative requirements to document their hours of work.51

The Proposed Rule Is Likely to Have a Disparate Impact on People of Color 

People of color face significant disparities in access to and utilization of care, and 

often fare worse than white people on measures of health status and health outcomes.52 In the Notice of Proposed Rulemaking, the Department concedes that the 

proposed changes ‘‘have the potential for disparately impacting certain protected 

groups due to factors affecting rates of employment of these groups, [it] find[s] that 

implementation of mitigation strategies and monitoring by the Civil Rights Division 

of FNS will lessen these impacts.’’ The Department is correct in noting that a consequence of restricting the ability of states to request waivers will disproportionately 

affect certain groups, because people of color have far higher unemployment rates 

than white adults.53 But no explanation of the mitigation strategies and monitoring 

is provided, so there is no opportunity for us to comment on whether the acknowledged disparate impact will in fact be mitigated. However, if the proposed rule results in higher rates of people of color losing SNAP benefits, this could exacerbate 

existing racial and ethnic disparities in health status. 

Waivers Should Not Be Determined Predominantly by The Unemployment Rate 

The Department suggests that insufficient jobs are reflected in unemployment 

data, but that data excludes key evidence, such as unemployed persons who 

searched for work in the previous year but not in the past 4 weeks, and workers 

who are part-time for economic reasons. According to Bureau of Labor Statistics 

data, Blacks are twice as likely than Whites to have searched for work in the previous year but not in the past 4 weeks, and Latinos are 66 percent more likely than 

Whites to work part-time for economic reasons.54 These and other data points suggest that the proposed core standard for determining lack of sufficient jobs, unemployment data, disproportionately impacts protected classes. 

Conclusion 

The Administration proposed rule seeks to make changes explicitly not intended 

by Congress, which just concluded a review and reauthorization of SNAP in the 

2018 Farm Bill and did not make the changes proposed. 

We strongly oppose any administrative action by USDA that would expose more 

people to this time limit policy that cuts people from the program, thereby cutting 

their benefits, and putting them at greater risk for food insecurity and the host of 

associated negative consequences. Under the law, states have the flexibility to waive 

areas within the state that have experienced elevated unemployment. The rules governing areas’ eligibility for waivers have been in place for nearly 20 years and the 

waiver rules have proven to be reasonable, transparent, and manageable for states 

to operationalize. Adding additional barriers to accessing nutritious food will make 

it even more difficult for individuals already facing economic inequity to find and 

maintain employment. By failing to consider existing disparities, the proposed policy 

will only exacerbate food insecurity in our county. Any change that would restrict, 

354 

impede, or add uncertainty to states’ current ability to waive areas with elevated 

unemployment should not be pursued. 

Feeding America strongly opposes the proposed rule that would expose even more 

people to the arbitrary SNAP food cutoff policy and harm our individuals facing food 

insecurity. 

The only action we encourage USDA to take with respect to this time limit rule 

that impacts Able-Bodied Adults Without Dependents is to propose its elimination. 

Restoring SNAP’s ability to provide food assistance to impoverished unemployed 

people would be a powerful policy improvement that would reduce food insecurity 

among those seeking work. 

Sincerely, 

KATE LEONE, Chief Government Relations Officer, 

Feeding America. 

ATTACHMENT 1

Feeding America Food Banks Brace for Increased Need for Food Assistance 

As Up to One Million Americans Lose Access to Food Stamps 

April 8, 2016 

Feeding America, the nation’s largest domestic hunger-relief organization, today 

warned that many food banks across the country will struggle to meet a significant 

increase in the need for emergency food assistance as between 500,000 and one million Americans are cut from the Supplement Nutrition Assistance Program (http:// 

www.feedingamerica.org/about-us%20press-room%20feeding-america-foodbanks.html) (SNAP, commonly known as food stamps) due to the return in many 

states of a harsh 3 month time limit on SNAP benefits for certain SNAP recipients. 

‘‘This is the equivalent of approximately $75–150 million in lost SNAP benefits 

per month on average, which equates to between 27 and 54 million meals per month 

that SNAP recipients will lose,’’ said Diana Aviv, CEO of Feeding America. ‘‘These 

totally unnecessary cuts would increase demand on the nation’s charitable food system at a time when food banks and other hunger-relief groups are stretched to meet 

sustained high need.’’ 

These cuts will affect unemployed adults aged 18–49 who are not disabled or raising minor children, also known as ‘‘Able Bodied Adults Without Dependents’’ 

([ABAWDs]). [ABAWDs] are limited to 3 months of SNAP benefits in any 36 month 

period unless they are employed or participating in a training program for at least 

20 hours a week. Even SNAP beneficiaries who are diligently looking for work and 

whose state does not offer them a slot in a work or training program are faced with 

losing their benefits. 

This year 22 states chose to, or were required to, re-impose time limits in all or 

part of the state for the first time since 2008. 

States are not required to offer SNAP recipients a place in a work or training program and only five states have pledged to offer a qualifying work slot to every individual subject to the 3 month time limit. Those impacted by the time limit face significant barriers to finding work or enrolling in training programs—25 percent do 

not have a high school degree, 33 percent face physical and mental limitations, and 

38 percent were formerly incarcerated. They are also among the poorest SNAP recipients with an average income of about $2,000 per year. 

‘‘We are deeply concerned about the impact on some of the poorest and most vulnerable people in our communities. SNAP is often the only program providing benefits to unemployed adults without dependent children, and the loss of benefits will 

be catastrophic for those affected. The notion that we can readily make up for this 

unnecessary loss is just not realistic’’ Aviv said. 

The Supplemental Nutrition Assistance Program (SNAP) helps millions of low-income Americans put food on the table, providing benefits that are timely, targeted 

and temporary. SNAP responds quickly to changes in need, growing in response to 

increases in poverty and unemployment and shrinking as need abates. The nutrition 

assistance program is targeted at our most vulnerable citizens, predominantly serving households with children, elderly and disabled members. 

ATTACHMENT 2

Feeding America Statement On Able-Bodied Adults Without Dependents 

Proposed Rule 

Attributed to Kate Leone, Chief Government Relations Officer 

December 20, 2018 

355 

‘‘Today, the Administration released a Notice of Proposed Rulemaking regarding 

Able-Bodied Adults Without Dependents (ABAWDs) and their receipt of Supplemental Nutrition Assistance Program (SNAP) benefits. Feeding America, the nation’s largest domestic hunger-relief organization, is deeply dismayed by this proposal, which will force more adults into food insecurity by creating unreasonable restrictions on food assistance. 

‘‘According to recent reports, the United States Department of Agriculture (USDA) projects that the proposed rule would cut $15 billion in benefits from the program 

over a decade, which Feeding America calculates would result in a loss of more than 

8.5 billion meals from the tables of individuals facing hunger. USDA’s most recent 

figures cite 40 million Americans across the United States facing food insecurity. 

‘‘Presently, unemployed or underemployed adults without dependents face strict 

time limits for receiving benefits if they are unable to find work. Specifically, adults 

ages 18 to 50 who do not receive disability benefits and do not have children are 

only able to receive SNAP benefits for 3 months, over the course of a 3 year period, 

unless they are working at least 20 hours a week or taking part in a comparable 

workforce program or training. 

‘‘Current law permits states to waive this rule temporarily in areas with elevated 

unemployment. Nearly every state has opted to use these waivers at some time. The 

proposed rule would effectively do away with state waivers by restricting the underlying criteria upon which waiver requests can be granted and expanding the 

grounds upon which they can be denied. 

‘‘By restricting access to ABAWD waivers, this rule would increase the risk of food 

insecurity for nearly one million people. In turn, that puts pressure on hunger-relief 

organizations and it is unlikely that our network of food banks can shoulder this 

burden. For each meal provided by Feeding America, SNAP provides 12 meals. Private charity simply cannot compensate for the breadth of the impact of cuts to the 

program. 

‘‘This rule is aimed at individuals who are most in need of our help—people who 

without resources who are unemployed. While participating in SNAP, the average 

income of an unemployed or underemployed adult without a family is just 18 percent of the poverty line, or about $2,171, per year, for a single-person household in 

2018. On average, that person’s SNAP benefit equates to $170 per month. It is inconceivable that we would deny food assistance to a person trying to live on just 

over $2,000 annually. 

‘‘Today, we anticipate the farm bill being signed into law. During the years of debate and negotiations to develop that legislation, there were many ideas similar to 

the Administration’s proposed rule. Congress soundly rejected all of them, and the 

farm bill makes improvements to SNAP by increasing investments in job training 

and proven workforce management approaches. 

‘‘Once published in the Federal Register in the coming days, the public will have 

60 days to generate comments on this proposal, in which Feeding America will actively participate. It is imperative that the Administration hear just how dangerous 

this proposal is to the health and well-being of many Americans. We encourage the 

Administration to rescind this rule.’’ 

ATTACHMENT 3

Feeding America Opposes Harmful SNAP Proposed Rule Released by USDA 

Attributed to Kate Leone, Chief Government Relations Officer 

February 1, 2019 

‘‘Feeding America is disappointed that the United States Department of Agriculture (USDA) continues to push a policy that will take billions of meals away from 

people struggling with hunger with the publication of their proposed rule to restrict 

states’ ability to waive time limits on Supplemental Nutrition Assistance Program 

(SNAP) benefits in high unemployment areas. USDA projects that the proposed rule 

would cut $15 billion in benefits from the program over a decade. Feeding America, 

the nation’s largest domestic hunger-relief organization, calculates that this would 

result in a loss of more than 8.5 billion meals from the tables of people facing hunger. This rule would increase the risk of food insecurity for nearly one million people, which would put additional pressure on our network of 200 member food banks. 

Private charity simply cannot compensate for the breadth of the impact of cuts to 

the program, as SNAP provides 12 meals for each meal provided by Feeding America. 

‘‘Presently, unemployed or underemployed adults without dependents face strict 

time limits for receiving benefits if they are unable to find work. Specifically, adults 

ages 18 to 50 who do not receive disability benefits and do not have children are 

356 

only able to receive SNAP benefits for 3 months, over the course of a 3 year period, 

unless they are working at least 20 hours a week or taking part in a comparable 

workforce program or training. 

‘‘Current law permits states to waive this rule temporarily in areas with elevated 

unemployment. Nearly every state has opted to use these waivers at some time. The 

proposed rule would effectively do away with state waivers by restricting the underlying criteria upon which waiver requests can be granted and expanding the 

grounds upon which they can be denied. 

‘‘This rule is aimed at individuals who are in great need of our help—people without resources who are unemployed. While participating in SNAP, the average income of an unemployed or underemployed adult without dependents is just 18 percent of the poverty line or about $2,171 per year in 2018. On average, that person’s 

SNAP benefit equates to $170 per month. It is inconceivable that we would deny 

food assistance to a person trying to live on just over $2,000 annually. 

‘‘The reality of low-wage employment is that individuals often face volatile job 

schedules and insufficient work hours, even if they are willing to work more. Over 

the past several weeks, the government shutdown provided a stark illustration of 

the impact one missed paycheck can make, and how little control workers have over 

their schedules. Ironically, this rule poses a threat to low-income workers, including 

Federal employees and contractors, who in the event of another extended shutdown 

could find their hours insufficient to meet program rules, threatening access to critical nutrition they need. SNAP by increasing investments in job training and proven 

workforce management approaches. 

‘‘Once published in the Federal Register in the coming days, the public will have 

60 days to generate comments on this proposal, in which Feeding America will actively participate. It is imperative that the Administration hear just how dangerous 

this proposal is to the health and well-being of many Americans. We encourage the 

Administration to rescind this rule.’’ 

SUBMITTED COMMENT LETTER BY HON. AL LAWSON, JR., A REPRESENTATIVE IN

CONGRESS FROM FLORIDA; AUTHORED BY CENTER FOR LAW AND SOCIAL POLICY

March 29, 2019 

Ms. SASHA GERSTAN-PAAL, 

Chief, 

Certification Policy Branch, 

Program Development Division, 

Food and Nutrition Service, 

Alexandria, Virginia 

Re: Proposed Rule: Supplemental Nutrition Assistance Program (SNAP): 

Requirements for Able-Bodied Adults without Dependents RIN 0584– 

AE57 

Dear Ms. Gerstan-Paal: 

I am writing on behalf of the Center for Law and Social Policy (CLASP). CLASP 

is a national, nonpartisan, anti-poverty nonprofit advancing policy solutions for lowincome people. We work at both Federal and state levels, supporting policy and 

practice that makes a difference in the lives of people living in conditions of poverty. 

CLASP submits the following comments in opposition to the U.S. Department of 

Agriculture’s proposed regulation regarding the time limits within the Supplemental 

Nutrition Assistance Program (SNAP) that apply to working-age adults without 

minor children. We are deeply concerned by attempts to restrict food assistance to 

individuals for whom SNAP is essential to meeting their basic needs and providing 

a work support. While we strongly support the goal of helping SNAP recipients obtain and keep quality jobs that enable them to achieve economic security, we believe 

the proposed restrictions will not advance this goal. In fact, because the changes will 

result in more people losing their SNAP benefits, they will make it harder to 

achieve this goal. 

SNAP already has harsh time limits in place requiring states to limit food assistance to just 3 months out of every 3 years for most working-age adults without 

minor children, unless they have a documented disability or report 20 hours of work 

or related activities each week. This policy alone cuts off hundreds of thousands of 

unemployed people from food assistance when they need it most. The proposed rule 

would make the policy even harsher by taking away food from even more people 

struggling to find steady work. By the Trump Administration’s own estimates, apVerDate Aug 31 2005 11:16 Jun 14, 2019 Jkt 041481 PO 00000 Frm 00362 Fmt 6621 Sfmt 6621 P:\DOCS\116-02\36188.TXT BRIAN
357 

1 U.S. Department of Agriculture, ‘‘SNAP Participation,’’ Food and Nutrition Service, September 2018, https://fnsprod.azureedge.net/sites/default/files/pd/34SNAPmonthly.pdf. 2SNAP Helps Millions of African Americans, Center on Budget and Policy Priorities, updated 

February 2018, https://www.cbpp.org/research/food-assistance/snap-helps-millions-of-africanamericans. 3SNAP Helps Millions of Latinos, Center on Budget and Policy Priorities, updated February 

2018, https://www.cbpp.org/research/food-assistance/snap-helps-millions-of-latinos. 4 ‘‘Congressional Tri-Caucus Denounces Cuts to the Supplemental Nutrition Assistance Program (SNAP),’’ Congressional Asian Pacific American Caucus, September 2013, https://capacchu.house.gov/press-release/congressional-tri-caucus-denounces-cuts-supplemental-nutrition-assistance-program-snap. 5 Victoria Tran, ‘‘Asian Americans are Falling Through the Cracks in Data Representation and 

Social Services,’’ Urban Institute, June 2018, https://www.urban.org/urban-wire/asian-americans-are-falling-through-cracks-data-representation-and-social-services. 6 Nune Phillips, SNAP and Work, Center for Law and Social Policy, January 2018, https:// 

www.clasp.org/sites/default/files/publications/2018/01/2018_snapandwork.pdf. 7 Adrienne O’Neil, Shae E. Quirk, Siobhan Housden, et al., ‘‘Relationship Between Diet and 

Mental Health in Children and Adolescents: A Systematic Review,’’ American Journal of Public 

Health vol. 104, 10 (2014): e31–42, https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4167 

107/. 8Michael W. Green, Peter J. Rogers, Nicola A. Elliman, and Susan J. Gatenby, ‘‘Impairment 

of Cognitive Performance Associated with Dieting and High Levels of Dietary Restraint,’’ Physiology & Behavior 55.3 (1994): 447–452, http://www.seven-health.com/wp-content/uploads/ 

2018/08/Impairment-of-Cognitive-Performance-Associated-with-Dieting-and-High-Levels-of-Dietary-Restraint-.pdf. 9Dottie Rosenbaum, ‘‘The Facts on SNAP, Part 2: SNAP Supports Work,’’ Center on Budget 

and Policy Priorities, May 2013, https://www.cbpp.org/blog/the-facts-on-snap-part-2-snap-supports-work. 10 Ibid., 6. 

proximately 755,000 to 851,000 individuals are at risk of losing food assistance 

through SNAP under the proposed rule. 

In the general comments that follow, we explain in more detail the reasons why 

the Department should immediately withdraw this proposed regulation. At the close 

of our general comments, we address major elements of the proposed rule section 

by section. 

1. Background 

SNAP is our nation’s most important anti-hunger program. It provides food assistance to youth, working families, people with disabilities, seniors, and many more. 

SNAP helps approximately 39 million people in nearly 20 million households put 

food on the table.1 In 2015, SNAP lifted approximately 2.1 million Black people (including one million children) 2 and an estimated 2.5 million Latinos (including 1.2 

million children) out of poverty.3 More than ten percent of Asian American and Pacific Islander (AAPI) families receive SNAP benefits,4 while many more are likely 

eligible but unenrolled due to cultural stigma and insufficient program outreach to 

AAPI groups.5

In addition to fighting hunger, SNAP encourages work in several ways.6 First, 

SNAP’s structure encourages work because as earnings rise, benefits phase out 

gradually. And because of the earned income disregard, earnings are treated more 

favorably than other income when benefits are calculated. Second, SNAP promotes 

employment by ensuring people have their basic needs met. Those working and 

seeking work on SNAP do not have to worry about when they will get their next 

meal. Instead, they can focus their energy on finding and keeping a job. 

Access to SNAP Has Positive Effects on Individuals’ Long-Term Economic and Educational Attainment, Which in Turn Contribute to Self-Sufficiency 

The face of hunger in working-age adults is often hidden. It can look like a single 

mother denying herself her medication so she can buy groceries for her family, a 

college student unable to focus in his classes, a hungry young adult unsuccessfully 

trying to find a job in a competitive labor market without money for interview 

clothes, or even a veteran with Post-Traumatic Stress Syndrome choosing between 

rent, heating, and food after serving our country. Studies have shown that lack of 

access to food and proper nutrition exacerbates stress, anxiety, and depression,7

causes sleep disturbances and fatigue, and impairs cognitive functioning 8—conditions that are a significant barrier to finding a job, keeping a job, or getting training 

to improve wages. 

SNAP is the antidote that helps hungry people become more employable 9 and increase wages.10 The SNAP program has also been shown to stimulate economic 

358 

11 Nune Phillips, SNAP Contributes to a Strong Economy, Center for Law and Social Policy, 

August 2017, https://www.clasp.org/sites/default/files/SNAP-Contributes-to-a-Strong-Economy.pdf. 12 Nisha Beharie, Micaela Mercado, and Mary McKay, ‘‘A Protective Association between 

SNAP Participation and Educational Outcomes Among Children of Economically Strained 

Households,’’ Journal of Hunger & Environmental Nutrition vol. 12, 2 (2016): 181–192, https:// 

www.ncbi.nlm.nih.gov/pmc/articles/PMC5513186/. 13Steven Carlson and Brynne Keith-Jennings, SNAP Is Linked with Improved Nutritional 

Outcomes and Lower Health Care Costs, Center on Budget and Policy Priorities, January 2018, 

https://www.cbpp.org/research/food-assistance/snap-is-linked-with-improved-nutritional-outcomes-and-lower-health-care. 14 Centers for Disease Control and Prevention, ‘‘Before Pregnancy: Women’’ Centers for Disease Control and Prevention, https://www.cdc.gov/preconception/women.html. 15Douglas Almond, Hillary Hoynes, and Diane Schanzenbach, ‘‘Inside the War on Poverty: 

The Impact of Food Stamps on Birth Outcomes,’’ The Review of Economics and Statistics, 93(2), 

May 2011, https://www.mitpressjournals.org/doi/pdfplus/10.1162/REST_a_00089; and Hilary 

Hoynes, Diane Whitmore Schanzenbach, and Douglas Almond, ‘‘Long-Run Impacts of Childhood 

Access to the Safety Net,’’ American Economic Review, 106(4): 903–934, April 2016, https:// 

pdfs.semanticscholar.org/c94b/26c57bb565b566913d2af161e555edeb7f21.pdf. 16Sharon Parrot, et al., Trump ‘‘Public Charge’’ Rule Would Prove Particularly Harsh for Pregnant Women and Children, Center on Budget and Policy Priorities, (May 1, 2018), available at 

https://www.cbpp.org/research/poverty-and-inequality/trump-public-charge-rule-would-proveparticularly-harsh-for-pregnant. 17Tess Lefmann, Terri Combs-Orme, ‘‘Prenatal Stress, Poverty, and Child Outcomes,’’ Child 

and Adolescent Social Work Journal 31 (2014), https://link.springer.com/article/10.1007/ 

s10560-014-0340-x. 18Maternal and Child Health Bureau, Child Health USA 2014: Prenatal Care, Health Resources and Services Administration, 2014, https://mchb.hrsa.gov/chusa14/dl/chusa14.pdf; 

Maternal and Child Health Bureau, Child Health USA 2013: Barriers to Prenatal Care, Health 

Resources and Services Administration, 2014, https://mchb.hrsa.gov/sites/default/files/mchb/ 

Data/Chartbooks/childhealth2013.pdf; Centers for Disease Control and Prevention, Preterm 

Birth, 2016, https://www.cdc.gov/reproductivehealth/MaternalInfantHealth/PretermBirth.htm; 

Child Trends, Preterm Births, 2015, https://www.childtrends.org/wp-content/uploads/2015/ 

06/indicator_1434209915.291.html. 19 Center on Budget and Policy Priorities, ‘‘Unemployed Adults Without Children Who Need 

Help Buying Food Only Get SNAP For Three Months,’’ https://www.cbpp.org/unemployedadults-without-children-who-need-help-buying-food-only-get-snap-for-three-months. 20 Ed Bolen, Dottie Rosenbaum, Stacy Dean, et al., More Than 500,000 Adults Will Lose SNAP 

Benefits in 2016 as Waivers Expire, Center on Budget and Policy Priorities, March 2016, 

https://www.cbpp.org/research/food-assistance/more-than-500000-adults-will-lose-snap-benefits-in-2016-as-waivers-expire. 

growth,11 improve academic outcomes,12 and improve health outcomes.13 SNAP benefits allow recipients to spend less money on food and be better able to afford other 

basic needs such as medicine and housing. Subjecting SNAP recipients to time limits makes it harder, not easier, for them to become self-sufficient. 

Further, although pregnant woman are exempt from the time limit on SNAP benefits, the restrictions will still impact the health of pregnant women and babies, because they apply to women who do not yet know that they are pregnant, or who 

do not yet have medical documentation of their pregnancies. The U.S. Centers for 

Disease Control strongly recommends that even before conceiving, women achieve 

a healthy weight and nutritious diet in order to maximize their odds of a healthy 

pregnancy.14

Nutrition assistance has been documented to promote healthy birth outcomes as 

well as to have long-term benefits for the children of recipients. Researchers compared the long-term outcomes of individuals in different areas of the country when 

SNAP expanded nationwide in the 1960s and early 1970s and found that mothers 

exposed to SNAP during pregnancy gave birth to fewer low-birth-weight babies.15

If women in early pregnancy are cut off from nutrition services, the negative outcomes would extend decades into the future, diminishing their children’s opportunity to thrive in tangible and entirely preventable ways.16 Low-income women are 

already more likely to have poorer nutrition and greater stress, which can impair 

fetal brain development and health during pregnancy.17 Economic stressors, combined with inadequate prenatal care for low-income pregnant women, are associated 

with higher rates of pre-term births and infant mortality.18

SNAP Already Has Harsh Time Limits and Work Reporting Requirements in Place 

Federal law currently limits adults ages 18–49 without dependent children or documented disabilities to just 3 months of SNAP in a 36 month period unless they 

engage in work or work-related activities at least half time or participate in 

workfare.19 The current rule is harsh and unfair. When several states reinstated 

this time limit in 2016 after suspending it due to the Great Recession, at least 

500,000 people lost SNAP benefits.20 For instance, in a recent Urban Institute study 

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21 Elaine Waxman and Nathan Joo, Urban Institute, ‘‘Reinstating SNAP Work-Related Time 

Limits,’’ March 2019 https://www.urban.org/research/publication/reinstating-snap-work-related-time-limits. 22Steven Carlson, Dorothy Rosenbaum, and Brynne Keith-Jennings, Who Are the Low-Income 

Childless Adults Facing the Loss of SNAP in 2016?, Center on Budget and Policy Priorities, February 2016, https://www.cbpp.org/research/food-assistance/who-are-the-low-income-childlessadults-facing-the-loss-of-snap-in-2016. 23 Ibid. 24 United States Government Accountability Office ‘‘Supplemental Nutrition Assistance Program: More Complete and Accurate Information needed on Employment and Training Programs,’’ November 2018, https://www.gao.gov/assets/700/695632.pdf. 25Ladonna Pavetti, Work Requirements Don’t Cut Poverty, Evidence Shows, Center on Budget 

and Policy Priorities, June 2016, https://www.cbpp.org/research/poverty-and-inequality/workrequirements-dont-cut-poverty-evidence-shows. 26 Ibid. 

of the effects of Kentucky’s reinstatement of time limits, researchers found that at 

least 13,000 adults without dependent children or documented disabilities lost 

SNAP benefits because they reached the 3 month time limit, representing 20 to 22 

percent of the caseload subject to time limits.21 If the proposed rule goes into effect, 

many more geographic regions will now be required to reinstate the time limit. Time 

limits harm vulnerable people by denying them food benefits at a time when they 

most need it. 

People subject to the time limit are a demographically diverse population in terms 

of race, education, and geography. Nearly 1⁄2 (47 percent) of the individuals subject 

to the time limit are ages 18 to 29. Approximately 85 percent have at most a high 

school diploma or equivalent. Approximately 45 percent of the people subject to the 

time limit are women and, among those who report race, an estimated 48 percent 

are White, 35 percent are Black, and 13 percent are Latino.22 People subject to the 

time limit face particular employment challenges, including a lack of reliable transportation, unstable housing arrangements, engagement with the criminal justice 

system, unstable work histories, or undiagnosed physical or mental limitations.23 In 

particular, those who reside in states that have not expanded Medicaid are likely 

to have trouble getting access to a doctor to document their disability. 

2. Proposal Does Not Encourage Employment and Would Weaken Economy 

as a Whole 

Time Limits and Work Reporting Requirements Do Not Support Employment 

Unlike work reporting requirements in most public assistance programs, SNAP 

time limit rules do not require states to offer options for meeting work reporting 

requirements before cutting people off benefits. Historically, most states have chosen not to help people subject to the time limit find qualifying work or training activities.24 Many individuals will lose SNAP if they cannot find a qualifying activity—which does not include job search—on their own. 

Lessons learned from TANF, SNAP, and other programs demonstrate that work 

reporting requirements are not effective in connecting people to living-wage jobs.25

As laid out by the Center on Budget and Policy Priorities in a review of rigorous 

evaluations, research shows that employment increases among individuals subject 

to work reporting requirements were modest and faded over time. In nearly all of 

the approximately dozen programs evaluated, employment among recipients not 

subject to work reporting requirements was the same as or higher than employment 

among individuals subject to work reporting requirements within 5 years.26

Work reporting requirements are not only ineffectual but have opportunity costs: 

the time that a SNAP recipient loses in low-intensity programs or low-wage jobs 

simply to meet requirements could have been spent obtaining skills and credentials, 

finding a quality job, and increasing their earnings. A much better focus for public 

policy is to invest in strategies that support people to develop skills and access 

training that prepares them for jobs that pay living wages and foster an economy 

that creates more quality jobs with fair wages. 

Proposal Would Grow Government Bureaucracy 

Under the Work Support Strategies (WSS) project, CLASP worked closely with six 

states that sought to dramatically improve the delivery of key work support benefits 

to low-income families, including health coverage, nutrition benefits, and child care 

subsidies through more effective, streamlined, and integrated approaches. From this 

work, we learned that reducing unnecessary steps in the application and renewal 

process both reduced burden on caseworkers and made it easier for families to access and retain the full package of supports that they need to thrive in work and 

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27 Julia B. Isaacs, Michael Katz, Ria Amin, Improving the Efficiency of Benefit Delivery Outcomes from the Work Support Strategies Evaluation, Urban institute, November 2016, https:// 

www.urban.org/research/publication/improving-efficiency-benefit-delivery. 28 Ibid. 29 United States Department of Agriculture, Office of Inspector General ‘‘FNS Controls Over 

SNAP Benefits For Able-Bodied Adults Without Dependents’’ https://www.usda.gov/oig/ 

webdocs/27601-0002-31.pdf. 30 Julia B. Isaacs, Michael Katz, Ria Amin, Improving the Efficiency of Benefit Delivery Outcomes from the Work Support Strategies Evaluation, Urban institute, November 2016, https:// 

www.urban.org/research/publication/improving-efficiency-benefit-delivery. 31 Ibid. 

school. Conversely, additional steps are burdensome to both caseworkers and participants. 

In order to remain compliant with work reporting requirements, recipients must 

show proof of work. Failure to submit paperwork, even if the person meets work 

reporting requirements, can result in terminated SNAP benefits and increased caseload churn. For SNAP oversight agencies, tracking work hours, reviewing proof of 

work, and keeping track of who is and is not subject to the work reporting requirement every month is a considerable undertaking and is prone to caseworker error. 

Moreover, because the time limit rules are distinct from the work registration requirements, states may need to track compliance separately and provide participants with separate sets of notices informing them of the consequences for non-compliance, which further adds to the complexity of administration. 

The complexity of the processes and the ensuing churn will also impose administrative costs on social service offices. People who lose benefits may later re-apply, 

which consumes more staff time. One of the key lessons of the Work Support Strategies project is that every time that a client needs to bring in a verification or report 

a change adds to the administrative burden on caseworkers and increases the likelihood that clients will lose benefits due to failure to meet one of the requirements.27

The WSS states found that reducing administrative redundancies and barriers used 

caseworkers’ time more efficiently and helped with Federal timeliness requirements.28 These administrative requirements in the proposed rule are unnecessarily 

burdensome to SNAP agencies. 

In particular, USDA’s Office of Inspector General found that SNAP’s provisions 

regarding time limit rules are difficult to implement. The report finds that states 

have difficulty implementing time limit rules because the requirements are very 

complex. As a result, implementation of time limit rules can be error prone. The report also quoted state officials as using terms like ‘‘administrative nightmare’’ and 

‘‘operational nightmare’’ in describing the time limit rules. State officials also expressed concerns regarding the amount of time and resources spent implementing 

time limit provisions.29 Many states have chosen to waive the maximum areas from 

the time limits in order to simplify program administration and preserve resources 

for meaningful services for participants. 

Proposal Would Undermine Efforts to Provide Meaningful Training Through Voluntary E&T Programs 

Mandated work programs are harmful because they threaten to take away benefits from people who are unable to comply with arbitrary rules.30 Instead of spending time receiving necessary skills, resources, and education, recipients must spend 

time complying with regulations to keep food on their tables, and states must spend 

time and resources on government bureaucracy rather than serving clients with the 

programs needed to succeed. Furthermore, mandatory work programs encourage recipients to enter into the labor market sooner, with less necessary tools to be successful in finding a stable position with livable wages. 

Over the past decade, some state and local leaders have worked hard to intentionally engage SNAP recipients in high-quality, voluntary programs that give participants the skills and credentials to achieve lasting economic security and develop 

partnerships for SNAP Employment & Training (E&T). The effort to expand highquality SNAP E&T programs, still in early stages, require substantial resources and 

capacity to deliver outcomes. A recent Government Accountability Office (GAO) 

study notes that ‘‘many states have reported to [FNS] that offering employer-driven, 

skills-based, intensive employment and training services, such as vocational training 

or work experience, through voluntary programs yields more engaged participants 

with stronger outcomes.’’ FNS explained to GAO that ‘‘voluntary programs are less 

administratively burdensome than mandatory programs, as they allow states to 

focus on serving motivated participants rather than sanctioning non-compliant individuals.’’ 31 Under the proposed rules, this investment in quality, high-intensity proVerDate Aug 31 2005 11:16 Jun 14, 2019 Jkt 041481 PO 00000 Frm 00366 Fmt 6621 Sfmt 6621 P:\DOCS\116-02\36188.TXT BRIAN
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32 Ibid., 9. 33 United States Government Accountability Office ‘‘Supplemental Nutrition Assistance Program: More Complete and Accurate Information needed on Employment and Training Programs,’’ November 2018, https://www.gao.gov/assets/700/695632.pdf. 34Mark M. Zandi, Assessing the Macro Economic Impact of Fiscal Stimulus 2008, January 

2008, https://www.economy.com/markzandi/documents/Stimulus-Impact-2008.pdf; Kenneth 

Hanson, The Food Assistance National Input-Output Multiplier (FANIOM) Model and Stimulus 

Effects of SNAP, U.S. Department of Agriculture, October 2013, https://www.ers.usda.gov/ 

webdocs/publications/44748/7996_err103_1_.pdf?v=41056; ‘‘The Benefits of Increasing the Supplemental Nutrition Assistance Program Participation in Your State,’’ U.S. Department of Agriculture, December 2011, https://www.fns.usda.gov/sites/default/files/bc_facts.pdf; ‘‘Chart 

Book: SNAP Helps Struggling Families Put Food on the Table,’’ Center on Budget and Policy 

Priorities, March 2017, https://www.cbpp.org/research/food-assistance/chart-book-snap-helpsstruggling-families-put-food-on-the-table#part8. 35 Alisha Coleman-Jensen, Matthew P. Rabbitt, Christian A. Gregory, et al., Household Food 

Security in the United States in 2016, U.S. Department of Agriculture, September 2017, https:// 

www.ers.usda.gov/webdocs/publications/84973/err-237.pdf. 

grams will likely be reduced as some states will seek to spread limited SNAP E&T 

resources thinly to help more people meet SNAP time limit rules. 

Instead of penalizing people for being poor and requiring assistance to put food 

on the table, USDA should consider ways to create a foundation for long-term economic success. Voluntary SNAP E&T programs, for instance, do not subject individuals to sanctions that increase food insecurity. In fact, research shows that voluntary programs can significantly increase employment, while mandatory SNAP 

E&T programs withhold basic assistance if individuals cannot meet participation requirements in a given month.32 To attract SNAP recipients to voluntary SNAP E&T 

programs, states can partner with trusted service providers that operate programs 

with a successful track record. Given these outcomes, in recent years, states have 

increasingly moved from mandatory to voluntary SNAP E&T programs.33

Proposal Would Weaken the Economy as a Whole 

SNAP has historically served as an economic stabilizer in changing times. It helps 

to shorten recessions and dampen the effects of an economic cycle in downturn. 

Without the mitigating effects of SNAP, the impact of recessions can escalate. The 

proposed rule inhibits SNAP from rapidly responding to changing economic conditions, and the resulting impact on the economy will affect all job seekers. In addition, by the Administration’s own calculations, the proposed rule would take food 

away from 755,000 to 851,000 low-income Americans, resulting in a loss of at least 

$15 billion in SNAP benefits over 10 years. These cuts will also have negative economic ripple effects, as SNAP benefits have been shown to have positive multiplier 

effects on state and local economies and to create new agricultural jobs.34

3. Proposal Would Have a Disparate Impact on People Trying To Make 

Ends Meet 

We strongly oppose the proposed rule due to its disproportionate impact on certain protected classes, including communities of color, immigrants, and people with 

disabilities. The Department acknowledges that the rule will have a disparate impact on some populations. It notes that the proposed changes ‘‘have the potential 

for disparately impacting certain protected groups due to factors affecting rates of 

employment of these groups, [it] find[s] that implementation of mitigation strategies 

and monitoring by the Civil Rights Division of FNS will lessen these impacts.’’ But 

no explanation of the mitigation strategies and monitoring is provided, and we do 

not believe that mitigation strategies can be significant enough to fully address the 

disproportionate impact of increased food insecurity and poverty on protected classes. 

Harm to Communities of Color 

Many people of color face considerable employment challenges and, under the proposed rule, would be disadvantaged from accessing critical food assistance. Compared to the national average, rates of food insecurity are already higher for Black 

and Latino headed households.35 Work reporting requirements are also part of a 

long history of racially-motivated critiques of programs supporting basic needs, with 

direct harms to people of color. As discussed in more detail in the sections that follow, the proposed rule would disproportionately impact communities of color. 

Racial Income Disparities Persist in the United States 

Due to persisting racial economic disparities and discrimination in hiring practices, average hourly wages for Black and Latino workers are substantially lower 

362 

36 Eileen Patten, ‘‘Racial, Gender Wage Gaps Persist in U.S. Despite Some Progress,’’ Pew Research Center, July 2016, http://www.pewresearch.org/fact-tank/2016/07/01/racial-genderwage-gaps-persist-in-u-s-despite-some-progress/. 37 ‘‘POV–01. Age and Sex of All People, Family Members and Unrelated Individuals Iterated 

by Income-to-Poverty Ratio and Race,’’ U.S. Census Bureau, 2017, https://www.census.gov/ 

data/tables/time-series/demo/income-poverty/cps-pov/pov-01.html. 38 ‘‘American Community Survey 2015 Five Year Estimates, table DP03,’’ U.S. Census Bureau, 

2015, https://factfinder.census.gov/faces/tableservices/jsf/pages/productview.xhtml?src=bkmk. 39 Robert Manduca, Income Inequality and the Persistence of Racial Economic Disparities, SOCIOLOGICAL SCIENCE, March 2018, https://www.sociologicalscience.com/download/vol-5/ 

march/SocSci_v5_182to205.pdf. 40 Brett Arends, ‘‘In Hiring, Racial Bias is Still a Problem. But Not Always for Reasons You 

Think,’’ Fortune, November 2014, http://fortune.com/2014/11/04/hiring-racial-bias/. 41Lincoln Quillian, Devah Pager, Ole Hexel, et al., Meta-Analysis of Field Experiments Shows 

No Change in Racial Discrimination in Hiring over Time, PNAS October 10, 2017 114 (41) 

10870–10875, September 2017, https://doi.org/10.1073/pnas.1706255114. 42Lonnie Golden, ‘‘Still Falling Short on Hours and Pay,’’ Economic Policy Institute, December 

2016, http://www.epi.org/publication/still-falling-short-on-hours-and-pay-part-time-work-becoming-new-normal/. 43 Ibid. 44 Ibid. 

than their white counterparts.36 In 2017, for adults age 18–64, the poverty rate of 

the general population is 11%. That percentage is significantly higher for Latinos 

who have a poverty rate of 15% and even higher for Black Americans who have a 

poverty rate of 18%.37 This makes it more likely that Black and Latino individuals 

will benefit from programs that support work by helping them access nutritious 

food. The same is true for certain subgroups of Asian and Pacific Islanders that are 

particularly at risk of poverty, such as Marshallese (41% poverty rate), Burmese 

(38%), Hmong (26.1%) and Tongans (22.1%).38

Employment Discrimination Limits Access to the Workforce for Many Immigrants 

and People of Color 

Studies show that racial discrimination remains a key force in the labor market.39

In a 2004 study, researchers randomly assigned names and quality to re ́sume ́s and 

sent them to over 1,300 employment advertisements. Their results revealed significant differences in the number of callbacks each re ́sume ́ received based on whether 

the name sounded stereotypically White or Black. More recent research indicates 

that this racial bias persists. A study from 2013 submitted fake re ́sume ́s of nonexistent recent college graduates through online job applications for positions based 

in Atlanta, Baltimore, Portland, Oregon, Los Angeles, Boston, and Minneapolis. 

Black people were 16% less likely to get called in for an interview.40 Similarly, a 

2017 meta-analysis of field experiments on employment discrimination since 1989 

found that white Americans applying for jobs receive on average 36% more callbacks 

than Black people and 24% more callbacks than Latinos.41

Latino and Black Workers Have Been Hardest Hit by the Structural Shift Toward 

Involuntary Part-Time Work 

Despite wanting to work more, many low-wage workers struggle to receive enough 

hours from their employer to make ends meet. A report from the Economic Policy 

Institute found that 6.1 million workers were involuntary part-time; they preferred 

to work full-time but were only offered part-time hours. According to the report, ‘‘involuntary part-time work is increasing almost five times faster than part-time work 

and about 18 times faster than all work.’’ 42

Latino and Black workers are much more likely to be involuntarily part-time (6.8 

percent and 6.3 percent, respectively) than whites, of whom just 3.7 percent work 

part time involuntarily. And Black people and Latinos are a higher proportion of 

involuntary part-time workers, together representing 41.1 percent of all involuntary 

part-time workers. The greater amount of involuntary part-time employment among 

Black people and Latinos is primarily due to their having greater difficulty finding 

full-time work and more often facing work conditions in which hours are variable 

and can be reduced without notice.43 Historical racial bias and work conditions, in 

which hours are variable and can be reduced without notice, disparately impacts 

Black people and Latinos and increases their likelihood of experiencing involuntary 

part-time employment.44

People of Color Are More Likely to Live in Neighborhoods with Poor Access to Jobs 

In recent years, majority-minority neighborhoods have experienced particularly 

pronounced declines in job proximity. Proximity to jobs can affect the employment 

outcomes of residents and studies show that people who live closer to jobs are more 

363 

45Scott W. Allard and Sheldon Danziger, Proximity and Opportunity: How Residence and Race 

Affect the Employment of Welfare Recipients, Housing Policy Debate, September 2000, https:// 

pdfs.semanticscholar.org/4936/dfd925b78d9e81f8d5d44b95b6a15f8ba0ab.pdf. 46 Elizabeth Kneebone and Natalie Holmes, ‘‘The Growing Distance Between People and Jobs 

in Metropolitan America,’’ Brookings Institution, March 2015, https://www.brookings.edu/research/the-growing-distance-between-people-and-jobs-in-metropolitan-america/. 47 Ibid. 48 Jamal Hagler, ‘‘8 Facts You Should Know About the Criminal Justice System and People 

of Color.’’ Center for American Progress, May 2015, https://www.americanprogress.org/issues/ 

race/news/2015/05/28/113436/8-facts-you-should-know-about-the-criminal-justice-system-andpeople-of-color/. 49Lynn Langton, Matthew Durose, et al., Police Behavior during Traffic and Street Stops, 

2011, U.S. Department of Justice, October 2016, https://www.bjs.gov/content/pub/pdf/ 

pbtss11.pdf. 50 ‘‘United States profile,’’ Prison Policy Initiative, https://www.prisonpolicy.org/profiles/ 

US.html#disparities. 51 Adam Looney and Nicholas Turner, Work and Opportunity Before and After Incarceration, 

The Brookings Institution, March 2018, https://www.brookings.edu/research/work-and-opportunity-before-and-after-incarceration/; Joan Petersilia, When Prisoners Come Home: Parole and 

Prisoner Reentry, Chicago, Ill: University of Chicago Press, 2003, https://www.amazon.com/ 

When-Prisoners-Come-Home-Prisoner/dp/0195386124; Jeremy Travis, But They All Come Back: 

Facing the Challenges of Prisoner Reentry, Washington, D.C.: Urban Institute Press, 2005, 

https://www.amazon.com/But-They-All-Come-Back/dp/0877667500. 52 Ibid., 40. 53 Christy Visher, Sara Debus, and Jennifer Yahner, Employment after Prison: A Longitudinal 

Study of Releasees in Three States, The Urban Institute, October 2008, https://www.urban.org/ 

sites/default/files/publication/32106/411778-Employment-after-Prison-A-Longitudinal-Studyof-Releasees-in-Three-States.PDF. 54Marina Duane, Nancy La Vigne, Mathew Lynch, et al., Criminal Background Checks: Impact on Employment and Recidivism, Urban Institute, March 2017, https://www.urban.org/ 

sites/default/files/publication/88621/2017.02.28_criminal_background_checks_report_final 

ized_blue_dots_1.pdf. 55Thomas Ahearn, ‘‘Survey Finds 96 Percent of Employers Conduct Background Screening,’’ 

Employment Screening Resources, August 2017, http://www.esrcheck.com/wordpress/2017/08/ 

03/survey-finds-96-percent-of-employers-conduct-background-screening/. 

likely to work.45 They also face shorter job searches and fewer spells of jobless- ness.46 As residents from households with low-incomes and communities of color 

shifted toward suburbs in the 2000s, their proximity to jobs decreased. Between 

2000 and 2012, the number of jobs near the typical Latino and Black resident in 

major metropolitan areas declined much more steeply than for white residents.47

Due to Overcriminalization Of Neighborhoods of Color, People of Color Are More 

Likely to Have Previous Histories of Incarceration, Which in Turn Limits Their 

Job Opportunities 

People of color, particularly Black people and Latinos, are unfairly targeted by the 

police and face harsher prison sentences than their white counterparts.48 National 

data show that Black people and Latinos are three times more likely to be searched 

than whites 49 and people of color are significantly over-represented in the U.S. prison population, making up more than 60 percent of people behind bars.50

After release, formerly incarcerated individuals fare poorly in the labor market, 

with most experiencing difficulty finding a job after release. Research shows that 

roughly 1⁄2 of people formerly incarcerated are still unemployed 1 year after release.51 For those who do find work, it’s common to have annual earnings of less 

than $500.52 Further, during the time spent in prison, many lose work skills and 

are given little opportunity to gain useful work experience.53 People who have been 

involved in the justice system struggle to obtain a driver’s license, own a reliable 

means of transportation, acquire relatively stable housing, and maintain proper 

identification documents. These obstacles often prevent formerly incarcerated persons from successfully re-entering the job market and are compounded by criminal 

background checks, which further limits their access to employment.54 A recent survey found that 96 percent of employers conduct background checks on job applicants 

that include a criminal history search.55

People of Color May Be Less Likely to Receive Exemptions Based on Health Conditions 

Research suggests that people of color, in particular Black people, may be negatively impacted by racial bias in pain assessment and treatment recommendations, 

which would affect their ability to receive exemptions based on health conditions. 

One study found individuals with at least some medical training hold false beliefs 

about race that inform medical judgements, which may contribute to racial disparities in pain assessment and inadequate treatment recommendations for Black paVerDate Aug 31 2005 11:16 Jun 14, 2019 Jkt 041481 PO 00000 Frm 00369 Fmt 6621 Sfmt 6621 P:\DOCS\116-02\36188.TXT BRIAN
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56Kelly M. Hoffman, et al., ‘‘Racial bias in pain assessment and treatment recommendations, 

and false beliefs about biological differences between blacks and whites’’ https:// 

www.ncbi.nlm.nih.gov/pmc/articles/PMC4843483/. 57Stephen Labaton, ‘‘Benefits Are Refused More Often To Disabled Blacks, Study Finds’’ New 

York Times, May 1992, https://www.nytimes.com/1992/05/11/us/benefits-are-refused-moreoften-to-disabled-blacks-study-finds.html. 58 Josh Levin, ‘‘The Welfare Queen,’’ Slate, December 2013,http://www.slate.com/articles/ 

news_and_politics/history/2013/12/linda_taylor_welfare_queen_ronald_reagan_made_her_a_ 

notorious_american_villain.html. 59 Rachel Black and Aleta Sprague, ‘‘Republicans’ Fixation on Work Requirements is Fueled 

by White Racial Resentment,’’ Slate, June 2018, https://slate.com/human-interest/2018/06/ 

trump-administrations-fixation-on-work-requirements-for-snap-benefits-is-part-of-a-long-racistpolicy-history.html. 60Kali Grant, Funke Aderonmu, Sophie Khan, et al., Unworkable and Unwise: Conditioning 

Access to Programs that Ensure a Basic Foundation for Families on Work Requirements, Economic Security and Opportunity Initiative at Georgetown Law, February 2019, http:// 

www.georgetownpoverty.org/issues/tax-benefits/unworkable-unwise/. 61 Rachel Black and Aleta Sprague, ‘‘The Rise and Reign of the Welfare Queen,’’ New America, 

September 2016, https://www.newamerica.org/weekly/edition-135/rise-and-reign-welfarequeen/. 62Gene Demby, ‘‘The Truth Behind the Lies of the Original ’Welfare Queen’,’’ National Public 

Radio, December 2013, https://www.npr.org/sections/codeswitch/2013/12/20/255819681/thetruth-behind-the-lies-of-the-original-welfare-queen. 63 Rachel Wetts and Robb Willer, Privilege on the Precipice: Perceived Racial Status Threats 

Lead White Americans to Oppose Welfare Programs, SOCIAL FORCES, Volume 97, Issue 2, 1 December 2018, Pages 793–822, May 2018, https://academic.oup.com/sf/article/97/2/793/ 

5002999. 

tients’ pain.56 Further, the Government Accountability Office (GAO) found in the 

early-1990s that Black people with serious ailments were much more likely than 

White people to be rejected for benefits under Social Security disability programs.57

While this particular analysis has not been repeated recently, there remains widespread evidence of disparities in medical treatment. These findings suggest that 

people of color may be less likely to receive exemptions based on health conditions, 

potentially subjecting more people to time limit rules than would otherwise be the 

case. 

Work Reporting Requirements Are Part of a Long History of Racially-Motivated Critiques of Programs Supporting Basic Needs 

False race-based narratives have long surrounded people experiencing poverty, 

with direct harms to people of color. For decades these narratives have played a role 

in discussions around public assistance benefits—including SNAP—and have been 

employed to garner support from working-class White people.58 Below are a few examples of the relationship between poverty, racial bias, and access to basic needs 

programs. 

• When the ‘‘Mother’s Pension’’ program was first implemented in the early 

1900s, it primarily served white women and allowed mothers to meet their basic 

needs without working outside of the home. Only when more African American 

women began to participate were work reporting requirements implemented.59

• Between 1915 and 1970, over six million African American people fled the south 

in the hope of a better life. As more African Americans flowed north, northern 

states began to adopt some of the work reporting requirements already prevalent in assistance programs in the South.60

• As civil rights struggles intensified, the media’s portrayal of poverty became increasingly racialized. In 1964, only 27 percent of the photos accompanying stories about poverty in three of the country’s top weekly news magazines featured 

Black people; by 1967, 72 percent of photos accompanying stories about poverty 

featured Black people.61

• Many of Ronald Reagan’s presidential campaign speech anecdotes centered 

around a Black woman from Chicago who had defrauded the government. These 

speeches further embedded the idea of the Black ‘‘welfare queen’’ as a staple 

of dog whistle politics, suggesting that people of color are unwilling to work.62

• In 2018, prominent sociologists released a study looking at racial attitudes on 

welfare. They noted that white opposition to public assistance programs has increased since 2008—the year that Barack Obama was elected. The researchers 

also found that showing white Americans data suggesting that white privilege 

is diminishing led them to express more opposition to spending on programs 

like SNAP. They concluded that the ‘‘relationship between racial resentment 

and welfare opposition remains robust.’’ 63

365 

64 ‘‘People in the Labor Force and Not in the Labor Force by Selected Characteristics, 2017 

Annual Averages,’’ U.S. Bureau of Labor Statistics, https://www.bls.gov/opub/reports/raceand-ethnicity/2017/home.htm; ‘‘Employed and Unemployed Full- and Part-time Workers by 

Age, [Sex], Race, and Hispanic or Latino Ethnicity,’’ U.S. Bureau of Labor Statistics, December 

2018, https://www.bls.gov/cps/cpsaat08.htm. 65 Census Bureau, American FactFinder, 2017 American Community Survey 1-Year Estimates, 

Table S0201 https://factfinder.census.gov/faces/tableservices/jsf/pages/productview.xhtml?pid= 

ACS_17_1YR_S0201&prodType=table. 66 Ibid. 67 Ibid. 68 Helena Bottemiller Evich, ‘‘Immigrant Families Appear to be Dropping Out of Food 

Stamps,’’ POLITICO, November [2018], https://www.politico.com/story/2018/11/14/immigrant-families-dropping-out-food-stamps-966256. 69 Allison Bovell-Ammon, ‘‘Trends in Food Insecurity and SNAP Participation Among Immigrant Families of U.S. Born Young Children,’’ Children’s HealthWatch, November 2018, http:// 

childrenshealthwatch.org/study-following-10-year-gains-snap-participation-among-immigrantfamilies-dropped-in-2018/. 70Supplemental Nutrition Assistance Program: Guidance on Non-Citizen Eligibility, U.S. Department of Agriculture, June 2011, https://fns-prod.azureedge.net/sites/default/files/snap/ 

Non-Citizen_Guidance_063011.pdf. 71 ‘‘Study: Following 10-year gains, SNAP participation among immigrant families dropped in 

2018,’’ American Public Health Association, November 2018, https://www.apha.org/news-andmedia/news-releases/apha-news-releases/2018/annual-meeting-snap-participation. 

The Unemployment Rate Does Not Reflect Opportunities Available to People of 

Color and, Because of Barriers to Employment, there is a Disproportionate Rate 

of Employment for People of Color 

A reduction in time limit waivers and the resulting loss in SNAP benefits will disproportionately affect certain protected classes based on (a) an inadequate method 

for determining lack of sufficient jobs, a criterion for approving time limit waivers; 

and (b) the disproportionate rate of unemployment and underemployment for people 

of color. 

First, the Department suggests that insufficient jobs are reflected in unemployment data, but that data excludes key evidence, such as unemployed persons who 

searched for work in the previous year but not in the past 4 weeks, and workers 

who are part-time for economic reasons. According to Bureau of Labor Statistics 

data, Black people are twice as likely than White people to have searched for work 

in the previous year but not in the past 4 weeks, and Latinos are 66 percent more 

likely than White people to work part-time for economic reasons.64 These data 

points suggest that the proposed core standard for determining lack of sufficient 

jobs, unemployment data, disproportionately impacts protected classes. 

Second, because of the systemic barriers to employment facing communities of 

color described in detail above, there is a disproportionate rate of employment for 

people of color. For instance, nationwide, the unemployment rate for Black people 

was 9.5 percent and 6.0 percent for Latinos, compared to 4.5 percent for their White 

counterparts in 2017.65 Further, even within states, unemployment rates for Black 

people and Latinos are still relatively higher than their White counterparts. For example, in California—a state with a statewide time limit waiver in place—the unemployment rate was 5.9 percent in 2017.66 However, the unemployment rate was 

considerably higher for Black people and Latinos in California in 2017; 10.7 percent 

for Black people and 6.7 percent for Latinos, compared to 5.5 percent for their White 

counterparts.67

Harm to Immigrants 

Immigrant Eligibility for SNAP is Extremely Limited and Current SNAP Participation Is Already Declining 

The Trump Administration’s relentless anti-immigrant rhetoric and policies are 

driving low-income immigrant families away from SNAP.68 The requirements for eligibility in SNAP haven’t changed recently but immigrant households legally eligible 

for SNAP benefits stopped participating in the program at a higher-than-average 

rate in 2018.69 Following welfare reform in 1996, a person must be a U.S. citizen 

or an eligible, lawfully-present non-citizen to qualify for SNAP benefits.70 Recent 

data presented at the 2018 American Public Health Association Annual Conference 

shows that after a decade of steady increases, enrollment nationwide among immigrant families eligible for SNAP has dropped by ten percent.71 The study’s lead researcher said in a press release, ‘‘We believe the drop in participation may be related to more nuanced changes in national immigration rhetoric and increased Federal action to deport and detain immigrants. These findings demonstrate that rhetVerDate Aug 31 2005 11:16 Jun 14, 2019 Jkt 041481 PO 00000 Frm 00371 Fmt 6621 Sfmt 6621 P:\DOCS\116-02\36188.TXT BRIAN
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72Susan Bartlett, Nancy Burstein, William Hamilton, et al., Food Stamp Access Study: Final 

Report, U.S. Department of Agriculture, November 2004, https://naldc.nal.usda.gov/download/ 

45671/PDF. 73Krista M. Perreira, Robert Crosnoe, Karina Fortuny, et al., Barriers to Immigrants’ Access 

to Health and Human Services Programs, U.S. Department of Health and Human Services, May 

2012, https://aspe.hhs.gov/system/files/pdf/76471/rb.pdf. 74 Robert Crosnoe, Juan Manuel Pedroza, Kelly Purtell, et al., Promising Practices for Increasing Immigrants’ Access to Health and Human Services, U.S. Department of Health and Human 

Services, May 2012, https://aspe.hhs.gov/basic-report/promising-practices-increasing-immigrants-access-health-and-human-services. 75Franklin County Work Experience Program, Ohio Association of Foodbanks, 2015, http:// 

admin.ohiofoodbanks.org/uploads/news/ABAWD_Report_2014-2015-v3.pdf. 76 Ibid. 77 U.S. Department of Labor, ‘‘Persons with a Disability: Barriers to Employment, Types of 

Assistance, and Other Labor-Related Issues—May 2012,’’ Bureau of Labor Statistics, April 2013, 

https://www.bls.gov/news.release/archives/dissup_04242013.pdf. 78 U.S. Department of Labor, ‘‘Persons with a Disability: Labor Force Characteristics—2016,’’ 

Bureau of Labor Statistics, June 2017, https://www.bls.gov/news.release/pdf/disabl.pdf. 79 Rachel Garfield, Robin Rudowitz, and Anthony Damico, Understanding the Intersection of 

Medicaid and Work, February 2017, http://kff.org/medicaid/issue-brief/understanding-theintersection-of-medicaid-and-work/. 

oric and the threat of policy changes, even before changes are enacted, may be causing families to forego nutrition assistance.’’ 

In addition, immigrants are often unaware of the SNAP program or are confused 

about their eligibility for benefits.72 Many immigrants in mixed-status families are 

not aware that some of their family members are eligible for SNAP, and immigrants 

face complicated administrative burdens due to caseworkers’ lack of familiarity with 

foreign identity documents.73 In fact, most Federal agencies have been working to 

overcome the barriers immigrants face to enrolling in benefits rather than adopting 

policies such as this proposal, which will only exacerbate current disparities in immigrant access to the SNAP program.74 Given SNAP’s record of alleviating poverty 

and food insecurity and improving health and employment outcomes, the USDA 

should be working to remove the barriers immigrant families face in accessing 

SNAP rather than further restricting access. 

Harm to People with Disabilities 

People who are unable to work due to disability or illness are likely to lose food 

assistance under the proposal. Although the statute and regulations both provide for 

exemptions from the time limit for individuals with work limitations, the reality in 

practice is that many individuals with disabilities are not identified and granted exemptions. In many states, only individuals who are receiving government disability 

benefits are exempted from the time limit. 

Many individuals characterized as able-bodied adults have significant physical or 

mental barriers to employment. In a Franklin County, Ohio report, approximately 

1⁄3 of individuals characterized as able-bodied reported having a ‘‘physical or mental 

limitation.’’ 75 Of those, 25 percent indicated that the condition limited their daily 

activities, and nearly 20 percent had filed for Disability/SSI within the previous 2 

years.76 Although some conditions may not meet the stringent standard to qualify 

the individual for a Federal disability benefit, they still may have significant barriers to working 20 hours or more per week. For instance, BLS reported that 1⁄2 of 

working-age adults with a disability who were not working reported barriers to employment, including a lack of transportation and the need for accommodations in a 

workplace.77 Another BLS report shows that workers with disabilities are nearly 

twice as likely as workers with no disability to be employed part-time.78

Additionally, we know that many disabilities go undiagnosed either because they 

are difficult to diagnose or the person does not have the resources to seek out a diagnosis. Moreover, many people who are unable to work due to disability fail to receive an exemption because of the complexity of paperwork required for exemptions. 

A Kaiser Family Foundation study found that 36 percent of unemployed adults receiving Medicaid reported illness or disability as their primary reason for not working but were not receiving Disability/SSI.79 Because of the historic unemployment 

and underemployment of people with disabilities—which workforce and SNAP employment systems are not adequately structured or funded to solve—a reduction in 

time limit waivers would result in the loss of crucial nutrition assistance for large 

numbers of low-income people with disabilities. 

367 

80 ‘‘Measuring the Value of Education,’’ U.S. Bureau of Labor Statistics, April 2018, https:// 

www.bls.gov/careeroutlook/2018/data-on-display/education-pays.htm. 81Teresa Kroeger and Elise Gould, The Class of 2017, Economic Policy Institute, May 2017, 

https://www.epi.org/publication/the-class-of-2017/. 82 ‘‘Supplemental Nutrition Assistance Program (SNAP),’’ Food and Nutrition Service, n.d., 

https://www.fns.usda.gov/snap/students; Carrie Welton, SNAP and Students: Food Assistance 

Can Support College Success, Center for Law and Social Policy, January 2019, https:// 

www.clasp.org/publications/fact-sheet/snap-and-students-food-assistance-can-support-collegesuccess. 83Food Insecurity: Better Information Could Help Eligible College Students Access Federal 

Food Assistance Benefits, U.S. Government Accountability Office, December 2018, https:// 

www.gao.gov/assets/700/696254.pdf. 84 Noah Berger and Peter Fisher, A Well-Educated Workforce Is Key to State Prosperity, Economic Policy Institute, August 2013, https://www.epi.org/publication/states-education-productivity-growth-foundations/. 85 Ibid., 17. 86 Ibid. 

Harm to College Students 

Many Students Cannot Meet Requirements of Proposed Rule 

Students enrolled at least half-time are not subject to the time limit, and this will 

not change under the proposed rule. However, students enrolled less than half-time 

and not otherwise exempt will now be at increased risk of losing benefits under the 

proposed rule if they are unable to meet SNAP time limit rules. Many low-income 

students must work part-time to support themselves and their families, and therefore enroll in college less than half-time. However, an 80 hours per month requirement does not allow enough time for many students to be able to attend classes and 

complete their homework. 

Given these challenges, this rule stands in direct contradiction to its stated principle of ‘‘ . . . improv[ing] employment outcomes and economic independence.’’ This 

rule will limit the ability of students with low incomes to successfully maintain 

SNAP and complete a post-secondary education that can lead to quality employment 

with family-sustaining wages 80 and employer sponsored healthcare and retirement 

savings.81

Proposal Would Exacerbate Confusion about Students’ Eligibility for SNAP 

SNAP has specific rules that determine which low-income students can receive 

food assistance. Low-income post-secondary students who are enrolled at least halftime and not otherwise exempt must meet all of the standard SNAP eligibility rules, 

as well as one of several additional qualifications, such as working at least 80 hours 

a month, participating in work-study, or participating in an employment and training program.82 According to the Government Accountability Office (GAO), post-secondary officials and students report being confused by these student rules. This 

leads to misinformation about the availability of SNAP on campus and low SNAP 

enrollment. A reported 57 percent of potentially eligible students (those who have 

low incomes, and at least one additional risk factor for food insecurity) are not presently accessing SNAP.83 The proposed time limit rule will add to the confusion by 

imposing harsh restrictions on students who are enrolled less than half-time and 

trying to meet their basic need for food through SNAP. The proposed rule compounds the challenges of maintaining SNAP and undermines education activities 

that could lead to greater economic contributions and increased productivity.84

Proposed Rule Does Not Reflect Recent Changes in the Student Body 

Students who enroll full-time right after high school, receive help from their parents, and do not work during the school year are no longer the norm on college campuses.85 A recent report from the GAO demonstrated that 71 percent of undergraduate students now have at least one characteristic that complicates their ability 

to attend classes such as being financially independent from their parents. The additional financial strain of independence can contribute to lower retention and graduation rates as compared to their ‘‘traditional’’ counterparts, emphasizing the need 

for more robust and diverse supports. 

A reported 39 percent of all undergraduate students have a household income at 

or below 130 percent of the Federal poverty line. The GAO reported that the highest 

student risk of food insecurity is being low-income and the second is being a firstgeneration college student.86 In spite of the risk of food insecurity, low-income students are enrolling in college at rates that now exceed that of their middle-income 

368 

87Table 302.30. Percentage of Recent High School Completers Enrolled in College, by Income 

Level: 1975 through 2016, National Center for Education Statistics, July 2017, https:// 

nces.ed.gov/programs/digest/d17/tables/dt17_302.30.asp?current=yes. 88 Anthony P. Carnevale, Tamara Jayasundera, and Artem Gulish, America’s Divided Recovery 

College Haves and Have-Nots, Center on Education and the Workforce, 2016, https:// 

cew.georgetown.edu/wp-content/uploads/Americas-Divided-Recovery-web.pdf. 89Duy Pham, Benefits Access for College Completion: Lessons Learned from a Community College Initiative to Help Low-Income Students, Center for Law and Social Policy, July 2016, 

https://www.clasp.org/blog/benefits-access-college-completion-lessons-learned-community-college-initiative-help-low-income. 90 Ibid., 21. 91Sarah Burd-Sharps and Kristen Lewis, More than a Million Reasons for Hope Youth Disconnection in America Today, Measure of America, March 2018, http://measureofamerica.org/ 

youth-disconnection-2018/. 92Table 2. Employment Status of the Civilian Noninstitutional Population 16 to 24 Years of 

Age by Sex, Race, and Hispanic or Latino Ethnicity, July 2015–2018, U.S. Bureau of Labor Statistics, August 2018, https://www.bls.gov/news.release/youth.t02.htm; Household Data Annual 

Averages: 1. Employment Status of the Civilian Noninstitutional Population, 1948 to Date, U.S. 

Bureau of Labor Statistics, accessed March 2019, https://www.bls.gov/cps/cpsaat01.pdf. 93 Ibid., 83a. 94 Alleviating Poverty for Opportunity Youth, JFF, December 2018, https://www.jff.org/resources/alleviating-poverty-opportunity-youth/. 95 Ibid., 40. 96Susan J. Lambert, Peter J. Fugiel, and Julia R. Henly, Schedule Unpredictability Among 

Early Career Workers in the U.S. Labor Market: A National Snapshot, University of Chicago: 

Employment Instability, Family Well-being, and Social Policy Network, August 2014, http:// 

www.academia.edu/21504026/Schedule_Unpredictability_among_Early_Career_Workers_in_the_ 

US_Labor_Market_A_National_Snapshot. 

peers.87 But this proposed rule would increase food insecurity and interfere with 

students’ ability to attend and complete college. 

Proposal Would Undermine Students’ Completion of Post-Secondary Education 

Analyses of the labor market over the past decade illustrate the considerable barriers to getting and maintaining employment without some form of post-secondary 

education. Research shows workers with a high school diploma or less lost 5.6 of 

the 7.2 million jobs wiped out in the Great Recession. These workers have recovered 

less than 80,000 jobs in the decade since, while those with a bachelor’s degree 

gained 4.6 million jobs in the recovery. Ninety-nine percent of the jobs created since 

the Great Recession have gone to those with some form of post-secondary education.88 Workers with a post-secondary education also have the majority of jobs 

with livable wages and employer provided benefits. 

Low-income individuals continue to enroll in post-secondary programs at increasing rates because they understand that post-secondary education is the most reliable pathway to economic security. Without access to SNAP, low-income students 

who are food-insecure may struggle to persist in and successfully complete their 

post-secondary education.89 The proposed rule is therefore incredibly short-sighted 

in limiting student success in post-secondary education.90

Harm to Young Adults 

The proposed rule would have a disparate impact on youth and youth of color, 

given the considerable barriers they face in entering the labor market and maintaining employment. Nationwide, approximately 4.6 million young adults ages 16 to 24 

are out of school and unemployed.91 In 2018, the youth unemployment rate (9.2%) 

was more than double the overall unemployment rate of 3.9 percent.92

Among young adults, Black people (16.5 percent) and Latinos (10.8 percent) have 

considerably higher rates of unemployment.93

Even when employed, young adults are more likely than older workers to have 

jobs with low wages and no benefits.94 Some struggle to receive enough hours from 

their employer to make ends meet. According to the Economic Policy Institute, 

young workers 16 to 24 years of age are more likely to be working part-time involuntarily among all age groups and account for approximately 28 percent of all involuntary part time workers, despite comprising 13 percent of those at work.95

Furthermore, young adult workers are more likely to experience fluctuating work 

hours common to youth-hiring sectors such as retail, restaurants, agriculture, construction, and other services. For example, approximately 90 percent of young food 

service workers reported that their hours fluctuated in the last month by 68 percent, on average. In addition, 1⁄2 of retail workers reported that they know their 

work schedule just 1 week or less in advance, and 1⁄2 of janitors and housekeepers 

reported that their employer completely controls the timing of their work.96

369 

97Senator Stabenow and Senator Murkowski, U.S. Senate, Letter to Secretary P[e]rdue, 

March 28, 2019, http://www.frac.org/wp-content/uploads/19-03-28-Letter-to-Perdue-re-ABAWDRule.pdf. 

Young adults in these jobs use SNAP to help them cover basic needs, but many 

youths will lose SNAP under the proposed rule when their hours fall below 20 hours 

per week. The proposed rule penalizes young adults who struggle to find stable employment by increasing food insecurity. 

4. Analysis of Major Elements of the Proposed Rule 

The majority of our comments to this point have addressed the harmful impact 

of the rule as a whole because different sections interact in ways that have a greater 

impact than any individual section. In order to ensure that our input is fully captured in the Department’s analysis of the comments received, the following section 

addresses key elements of the proposed rule. 

Conformance with the Agriculture Improvement Act of 2018 (Farm Bill) 

The just enacted Agriculture Improvement Act of 2018 maintains current law regarding SNAP time limit rules. The explanation given by the Act’s Joint Explanatory Statement of the Committee of Conference is, ‘‘the Managers . . . acknowledge 

that waivers from the ABAWD time limit are necessary in times of recession and 

in areas with labor surpluses or higher rates of unemployment.’’ 

While the NPRM states that applying SNAP time limit rules more broadly is in 

alignment with the House-passed Agriculture and Nutrition Act of 2018, H.R. 2, 

that bill did not ultimately become law. The final Agriculture Improvement Act of 

2018 retains the SNAP time limit in current law and strikes the House bill modifications. In a letter to Secretary P[e]rdue requesting that the proposed rule be withdrawn, Senators Stabenow and Murkowski as well as 45 more Senators clarify Congressional intent. The letter from U.S. Senators states: 

In addition to being out line with Congressional intent related to waivers, this 

rule also directly contradicts Congressional direction related to waiver submissions and carry-over exemptions included in the 2018 Farm Bill report. This report, written by Chairman Pat Roberts, Ranking Member Debbie Stabenow, 

Chairman Mike Conaway and Ranking Member Collin Peterson and approved 

by the 369 Members of the House and 87 Members of the Senate, explicitly directs the Department not to make the changes made in this rule. This unilateral Administrative action is in direct contradiction to the will of Congress.97

In contrast to the new law, the NPRM often cites the goal of ensuring that more 

people are subject to SNAP time limits and work reporting requirements as a justification for policy changes. For example, in describing options for a six percent 

floor, the NPRM states that, ‘‘the Department is concerned that too many areas 

would qualify for a waiver of the ABAWD time limit and that too few individuals 

would be subject to the ABAWD work requirements.’’ The Department’s proposed 

floor of seven percent seems arbitrary and devised to produce the desired result of 

more individuals being subject to work reporting requirements, a goal that does not 

reflect the goals of Congress. 

Setting policy goals inconsistent with the intent of the final law is an over-reach 

of Departmental authority. The Department is expected to ensure that waivers for 

SNAP time limit rules are adequately responsive to nationwide recessions and relative areas of higher unemployment or labor surpluses. The three core standards 

proposed by the Department do not allow that role to be performed adequately. 

Federalism Summary Impact Statement 

The proposed rule has federalism implications that contradict the intent of both 

the 2018 Farm Bill and Executive Order 13132. The Joint Explanatory Statement 

of the Committee of Conference of the farm bill states that ‘‘the Managers intend 

to maintain the practice that bestows authority on the state agency responsible for 

administering SNAP to determine when and how waiver requests for ABAWDs are 

submitted.’’ 

Executive Order 13132 Section 7(b) states that, ‘‘Each agency shall, to the extent 

practicable and permitted by law, consider any application by a state for a waiver 

of statutory or regulatory requirements in connection with any program administered by that agency with a general view toward increasing opportunities for utilizing flexible policy approaches at the state or local level in cases in which the proposed waiver is consistent with applicable Federal policy objectives and is otherwise 

appropriate.’’ The Federal policy objectives stated above specifically maintain state 

agency responsibility for determining when and how waivers are submitted. 

370 

98 ‘‘The NBER’s Business Cycle Dating Committee,’’ The National Bureau of Economic Research, September 2010, https://www.nber.org/cycles/recessions.html. 99The Current Population Survey universe is the non-institutionalized civilian population at 

least 16 years of age. 100 Unlike the employment-population ratio (EPOP), the U–6 measure depends on an individual accurately defining what wanting and being available for a job means to them. While 

EPOP is less subjective, the U–6 data more accurately reflects the ABAWD population. EPOP 

includes longer-term discouraged workers but does not distinguish them from retired persons 

or others who are not available to work. 

State flexibility is critical to appropriate implementation of SNAP time limit 

rules. Consistent with the view of many researchers and agencies including the National Bureau of Economic Research, no single measure can truly identify economic 

downturns and a lack of sufficient jobs.98 Individual states have in-depth knowledge 

of their communities that allows them to identify qualitative data, Census Bureau 

data, Bureau of Labor Statistics employment-population data and U–6 measures, 

and other high-quality data to best make a case for the need for a waiver. The sections below highlight some of the strengths of these different measures. 

Use of Bureau of Labor Statistics Data for Core Standards 

The United States Bureau of Labor Statistics produces two measures of labor 

under-utilization based on the Current Population Survey that will be discussed in 

this section.99

1. U–3 measure: The U–3 measure is the official unemployment rate, which is 

proposed by the Department as the basis for two of three core standards: the 

fixed measure of unemployment rate over ten percent, and the relative measure of 20 percent over the average unemployment rate over a 24 month period. The U–3 calculates the unemployed as a percentage of the labor force. 

The labor force includes employed as well as unemployed, which is defined 

as those who have no job and have made an attempt to look for work in the 

past 4 weeks. 

2. U–6 measure: The U–6 is an alternative measure of labor underutilization 

that captures: 

i. the percentage of people who want and are available for full-time work but 

have had to settle for a part-time schedule for economic reasons, such as 

their hours being cut back or being unable to find full-time jobs (termed 

‘‘employed part-time for economic reasons’’). 

ii. the percentage of people who currently are neither working nor looking 

for work but indicate that they want and are available for a job and have 

looked for work sometime in the past 12 months (termed ‘‘marginally attached to the workforce.’’) Discouraged workers, a subset of the marginally attached, have given a job-market related reason for not currently 

looking for work. 

iii. The percentage of people who are unemployed, equivalent to the U–3 

measure. 

These components of the U–6 measure are calculated as a percent of the labor 

force plus all persons marginally attached to the labor force.100

We oppose the proposed rule’s heavy and exclusive reliance on the U–3 measure 

for two of its three core standards. The U–3 data tends to be biased downward as 

a reflection of available jobs, because it does not include those who are part-time 

due to a lack of available work or who are discouraged for a job-market related reason. Therefore, the U–3 measure overstates the degree of recovery in the job market. 

The U–6 measure is distinguished from the U–3 by just two subsets of workers: 

workers who are part-time for economic reasons and workers who are marginally 

attached to the workforce. The impact of including these two subsets can be demonstrated by calculating a ratio of the U–6 to U–3 measure: The U–6 measure of 

labor underutilization is significantly higher than the U–3 and the ratio varies geographically. As illustrated by graphic 1 in the appendix, some states have significantly lower numbers of workers who are part-time for economic reasons and/or 

marginally attached to the workforce than other states. 

Moreover, the U–3 measure does not accurately represent a large subset of individuals subject to the SNAP time limit. According to the USDA Food and Nutrition 

Service (FNS), more than 31 percent of nonelderly adult SNAP recipients were employed in an average month of 2016. Many of these SNAP recipients were subject 

to the time limit who were employed part-time for economic reasons. A portion of 

371 

101 EPOP uses the relationship between the ratio of the monthly Current Employment Statistics Survey (CES) employment to the population and the ratio of the Current Population Survey 

(CPS) employment to the population. EPOP also includes trend and seasonal components to account for movements in the CPS not captured in the CES series. The seasonal component accounts for the seasonality in the CPS not explained by the CES (for example, agricultural employment movement), while the trend component adjusts for long-run systematic differences between the two series (for example, during expansions, the CES grows faster than the CPS). 102More information is available at: ‘‘Notes on Using Current Population Survey (CPS) Subnational Data,’’ U.S. Bureau of Labor Statistics, June 2018, https://www.bls.gov/lau/ 

notescps.htm. 103More information is available at: ‘‘Fact Sheet: Differences Between the American Community Survey (ACS) and the Annual Social and Economic Supplement to the Current Population 

Survey (CPS ASEC),’’ U.S. Census Bureau, May 2016, https://www.census.gov/topics/incomepoverty/poverty/guidance/data-sources/acs-vs-cps.html. 104More information is available at: ‘‘American Community Survey (ACS) Questions and Answers,’’ U.S. Bureau of Labor Statistics, April 2017, https://www.bls.gov/lau/acsqa.htm. 

the remaining 69 percent of non-elderly adult SNAP recipients were discouraged 

workers who had not looked for work in the past 4 weeks for job-market related reasons. Both subsets of individuals subject to the time limit are directly captured in 

the U–6 measure, but not in the U–3. 

Exclusion of these subsets of individuals disproportionately impacts protected 

classes, who have higher rates of part-time employment for economic reasons and 

discouraged workers. Please see the Civil Rights Impact section below for a further 

discussion of this impact. 

If the Department bases waivers exclusively on U–3 unemployment rates, it will 

not count these individual subsets in a waiver review even though lack of sufficient 

jobs has impacted their employment status. If BLS data is to impact individuals’ 

access to SNAP, it is imperative to address the U–3 measure’s weaknesses. 

Development of Core Standards and Other Data and Evidence in Exceptional Circumstances 

While the 2018 Farm Bill requires waivers for SNAP time limit rules to be responsive to recessions and areas with labor surpluses and higher rates of unemployment, there are inherent challenges in defining these economic conditions, including 

weaknesses in existing data sets, complexities in defining recessions, and difficulty 

in using a single data set averaged across different categories of people, industries 

and geographic locations. As a result, many researchers use qualitative data to support an understanding of employment challenges. For example, the recognized agency for defining recessions, the National Bureau of Economic Research, does not use 

a single formula or data set for a definition of a recession. 

We oppose the proposed exclusion of additional data outside of the U–3. Additional data can support a picture of the strength of the labor market. For example, 

the BLS employment-population ratio, which measures employed persons as a percentage of the entire population,101 includes individuals who are employable but 

have not looked for a job in more than a year. In periods of severe and long-term 

economic recessions, the number of individuals in this category will grow and the 

employment-population ratio will paint a clearer picture of the strength of the labor 

market than other measures. 

In addition, Census Bureau data should be an option for waiver applications, particularly for sub-state areas. BLS has ‘‘concluded that data users often are better 

served by sub-state area data from the Census Bureau’s American Community Survey (ACS). Data from the ACS provide more extensive geographic and demographic 

coverage, and have smaller sampling errors.102 The Census Bureau’s ACS sample 

size is 30 times larger than that of BLS, which accounts in large part for its increased accuracy.103 In 2013, the numbers of persons the ACS classified as ‘employed,’ ‘unemployed,’ and ‘not in the labor force’ for the nation were all higher than 

the official CPS estimates. The ACS unemployment rate was 8.4 percent, compared 

to the CPS annual average of 7.4 percent.’’ 104 The variation in this one example reflects the challenge of standardizing the U–3 measure instead of allowing Census 

data to be used. 

Finally, data on lack of jobs in declining occupations or industries is critical in 

assessing whether there are enough jobs, and should continue to be considered in 

waiver determinations. While a population may as a whole remain employed, a 

large subset may be significantly affected by declining occupations. This is expected 

to be the case, for example, when transportation evolves toward self-driving vehicles. While participation in WIOA’s dislocated worker program meets SNAP time 

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105 A total of 406,407 were served from October 1, 2017 to September 30, 2018. More information is available, under quarterly reports, at: WIOA Performance Results, U.S. Department of 

Labor, February 2019, https://www.doleta.gov/performance/results/. 106Diane Whitmore Schanzenbach, Ryan Nunn, Lauren Bauer, et al., Nine Facts About the 

Great Recession and Tools for Fighting the Next Downturn, The Brookings Institution, May 

2016, https://www.brookings.edu/research/nine-facts-about-the-great-recession-and-tools-forfighting-the-next-downturn/. 107More information from 1948 to present is available at: Databases, Tables & Calculators 

by Subject, U.S. Bureau of Labor Statistics, accessed March 2019, https://data.bls.gov/ 

timeseries/lns14000000. The unemployment rate reached but did not exceed ten percent in just 

1 month of the Great Recession, October 2009. More information on GDP is available at: GDP 

& Personal Income, U.S. Bureau of Economic Analysis, accessed March 2019, https:// 

apps.bea.gov/iTable/index_nipa.cfm. 108 Julie M. Whittaker and Katelin P. Isaacs, Extending Unemployment Benefits During a Recession, Congressional Research Service, May 2013, https://fas.org/sgp/crs/misc/RL34340.pdf. 109 Unemployment Insurance Trigger 101: Is the Trigger System Working?, Center for American Progress, February 2010, https://www.americanprogress.org/wp-content/uploads/issues/ 

2010/02/pdf/ui_101.pdf. 

limit rules, there are inadequate opportunities for such participation in the United 

States, with only 400,000 people served nationwide in Federal Fiscal Year 2018.105

The proposed rules would restrain SNAP from rapidly responding to changing economic conditions. Notably, according to the Brookings Institution, the most 

simulative type of spending during the Great Recession was a temporary increase 

in the SNAP maximum benefit, which was quicker to respond to deteriorating economic conditions than Congressional action and more effective dollar for dollar than 

increased spending on infrastructure and defense.106 Without the mitigating effects 

of SNAP, the impact of recessions can escalate. The USDA’s Economic Research 

Service uses the Food Assistance National Input-Output Multiplier (FANIOM) 

model to estimate the multiplier effects from SNAP benefits at 1.79, which is a significant economic boost. We strongly oppose any changes that dilute the impact of 

SNAP benefits as an automatic stabilizer. 

Economic downturns are not exceptional circumstances and should not be treated 

as such. The exceptional circumstances floor of ten percent is far too high to reflect 

the lack of sufficient jobs in a community, region, or country. On a national basis, 

the only time in the past 70 years that the average unemployment rate was above 

ten percent was in 1982–83. Yet from December 2007 through June 2009 the United 

States experienced the most severe recession in the post-war period, with over a 

four percent decline in gross domestic product (GDP).107 A floor above ten percent 

is therefore highly unresponsive to nationwide recessions and depressions. The 20 

Percent Standard’s use of a data over a 24 month period is also unresponsive—the 

period is more an indication of chronic economic depression than a new recession. 

This lack of responsiveness limits SNAP’s ability to serve as an automatic stabilizer and is therefore inconsistent with the goals described in the Joint Explanatory Statement of the Committee of Conference to address times of recession. If a 

recession took effect tomorrow and the current unemployment rate of 3.9% (December 2018 BLS) doubled, the number of persons newly unemployed would be about 

five million across the United States. Many of these five million would be individuals unable to access SNAP beyond the time limit, and the loss of benefits would 

be detrimental to the economy. 

Retaining the Extended Unemployment Benefits Qualification Standard 

The Unemployment Insurance Extended Benefits (EB) program extends individual unemployment compensation for an additional 13 weeks when a state’s insured unemployment rate (IUR) or total unemployment rate (TUR) reaches at least 

5% and is 120% of the average of the rates for the same 13 week period in each 

of the 2 previous years. There are two other optional thresholds that states may 

choose. EBs may be triggered if the state’s IUR is at least 6%, or the TUR is at 

least 6.5% and is at least 110% of the state’s average TUR for the same 13 weeks 

in either of the previous 2 years. An additional 20 weeks of benefits may be triggered if the TUR is at least 8% and is at least 110% of the state’s average TUR 

for the same 13 weeks in either of the previous 2 years.108

While these triggers are lower than the standard proposed for waivers, many researchers have found that EB triggers are set too high, which prevents many states 

from activating the program for extra weeks of benefits above and beyond the standard 26 weeks.109 Moreover, the trigger requires ever increasing unemployment rates 

in order to remain triggered, which means that many states cycle out of the system 

too early. Congress has regularly passed legislation to provide extended UI benefits 

in states that do not meet the EB criteria, or else extended benefits nationwide. 

Congress established temporary programs of extended UI benefits in 1958, 1961, 

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110 Jared Bernstein, ‘‘I’ve Come to Believe That ‘Are We at Full Employment?’ Is the Wrong 

Question,’’ The Washington Post, May 2018, https://www.washingtonpost.com/news/ 

posteverything/wp/2018/05/24/ive-come-to-believe-that-are-we-at-full-employment-is-the-wrongquestion/?noredirect=on&utm_term=.c249a3003278. 

1971, 1974, 1982, 1991, 2002, and 2008. In the Great Recession, Congress created 

a temporary program nationwide. The need for actions of Congress demonstrate that 

EB qualification as a core standard for approval is not adequate for states with high 

unemployment rates that are not rising rapidly. 

Establishing a Floor for Waivers Based on the 20 Percent Standard 

We strongly oppose the use of a floor for waivers. The 20 percent standard is an 

adequate relative measure that demonstrates that an area of the country is in a 

more difficult economic position than the rest of the country. 

The Department seeks to create a fixed floor at seven percent, well above the natural rate of unemployment. We believe a floor at any level above the natural rate 

of unemployment is unnecessary, arbitrary and needlessly disadvantages members 

of protected classes, as described in the Civil Rights Impact section below. In addition, it would subvert the intent of the Agriculture Improvement Act of 2018 to permit waivers in labor surplus areas. 

Further, there is significant disagreement amongst respected economists about 

the exact number for the natural rate of unemployment. While a five percent natural rate of unemployment seemed to be the norm at one point, the evidence has 

shifted in the past twenty years. If the natural rate is defined in part by the point 

at which unemployment leads to inflation, then the current unemployment rate of 

3.9 percent is arguably above the natural unemployment rate, according to Jared 

Bernstein, President Clinton’s former economic advisor. ‘‘While inflation is picking 

up a bit, it has been very low for a very long time, unresponsive to falling unemployment, and no one is arguing that it is . . . spiraling up in response to a full-capacity 

economy.’’ 110 A selection of a five percent rate is arbitrary given the lack of consensus by experts. 

Restricting Statewide Waivers and Combined Areas 

We oppose elimination of the option of statewide waivers as well as waivers for 

areas that are not economically tied together, due to the administrative complexities 

of implementing this change. There are 63 counties or county equivalents on average per state; Texas has the most counties at 254. Some states have chosen to submit statewide waivers to avoid the administrative burden of creating dual systems 

for those SNAP recipients who are or are not subject to time limits. Under the proposed rules, states will need to collect data for each county or Labor Market Area 

in order to submit a waiver request. States will then have to set up dual systems 

and train caseworkers to treat SNAP recipients differently based on their county of 

residence. This adds to caseworker confusion and potential error. States will also 

need to train SNAP E&T service providers to treat SNAP recipients differently 

based on their residence. 

In addition, we oppose eliminating combined areas that fall outside of Labor Market Areas. The areas covered by Workforce Development Boards are not always consistent with Labor Market Areas; some include multiple counties, including some 

outside of Labor Market Areas, while others are smaller than a county. The proposed rules will make planning more difficult given the inability to group areas consistent with Workforce Development Boards. 

Finally, we oppose the elimination of waivers in sub-county areas. Many counties 

in the U.S. have extreme disparities in the labor market in different geographic 

areas. Traveling to jobs with an adequate labor supply may not be feasible for many 

low-income SNAP recipients. For example, traveling from rural Gorman to Long 

Beach in the most populous county in the United States, Los Angeles, takes about 

2 hours by car and is not possible via public transportation. The proposed rules do 

not account for the immense variety in local conditions that can make finding a job 

nearly impossible for many people. 

Ending ‘‘Carryover’’ Exemptions 

Current law allows unused exemptions to carry over and accumulate from one 

year to the next. Up until now, states understood these exemptions to be ‘‘earned’’ 

and made decisions about whether to use the exemptions in a given year based on 

a good faith assumption of FNS’ continued allowance of carryover exemptions. Past 

and recent FNS Memoranda on the subject, including the most recent ‘‘SNAP—FY 

2018 ABAWD 15 Percent Exemptions Totals, Adjusted for Carryover,’’ clearly demonstrates FNS approval of carryover exemptions to date. 

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111 Bureau of Labor Statistics, ‘‘Labor Force Statistics from the Current Population Survey, 

A–18. Employed and Unemployed Full- and part-time workers by age, sex, and Hispanic or 

Latino ethnicity’’ https://www.bls.gov/web/empsit/cpseea18.htm; and Bureau of Labor Statistics ‘‘Labor Force Characteristics by Race and Ethnicity, 2017, Table 15. People in the Labor 

Force and Not in the Labor Force by Selected Characteristics, 2017 annual averages’’ https:// 

www.bls.gov/opub/reports/race-and-ethnicity/2017/home.htm. 

We strongly oppose the use of a carryover formula in which the current year is 

adjusted based on the number of exemptions earned in the preceding fiscal year 

minus the number of exemptions used in the preceding fiscal year. The formula penalizes states for using carryover from the previous year by subtracting any used 

carryover amount from earned exemptions. We do not believe penalties for the use 

of carryover was the intent of the act. As can be seen in Example 2 (Varied Exemption Use) of the NPRM, the number of exemptions after adjustment becomes highly 

erratic as well as difficult to track under the proposed formula. The formula also 

incentivizes states to use their full amount in the year earned rather than prudently 

reserving exemptions for a downturn in the economy. Overall, we hold that the proposed method of calculating exemptions would create confusion, discourage the use 

of exemptions, and increase errors. 

Civil Rights Impacts under the Civil Rights Impact Analysis 

The Department has stated that in accordance with the Department Regulation 

4300–4 Civil Rights Impact Analysis, implementation of mitigation strategies and 

monitoring by the Civil Rights Division of FNS will lessen the disproportionate impacts of ‘‘certain protected groups due to factors affecting rates of employment of 

members of these groups.’’ 

There are two main CRIA challenges to the NPRM. A reduction in waivers and 

the resulting loss in SNAP benefits will disproportionately affect certain protected 

classes based on (a) their disproportionate rate of unemployment and under-employment, as stated in the NPRM; and (b) an inadequate method for determining lack 

of sufficient jobs, a criterion for approving waivers. 

Disproportionate Rate of Unemployment and Under-Employment 

We strongly oppose further restrictions to waivers due to their disproportionate 

impact on many protected classes including women, Black people, Latinos, and people with disabilities. We do not believe that mitigation strategies will be significant 

enough to address the impact of increased food insecurity and poverty on protected 

classes. 

Inadequate Methodology 

The NPRM not only impacts protected classes disproportionately due to unemployment factors, but it further impacts protected classes due to the use of the U– 

3 measure, which excludes certain employment statuses that are more common 

amongst certain protected classes. We strongly oppose the NPRM for these reasons. 

Data from the Bureau of Labor Statistics illustrate the disproportionate impact 

of the data excluded from the U–3 measure on selected protected groups. For instance, as illustrated by BLS data in graphics 2 and 3 in the appendix, Black individuals are more than twice as likely than their White counterparts to have 

searched for work in the previous year but not in the past 4 weeks (see graphic 2), 

and Latinos are 66 percent more likely than Whites to work part-time for economic 

reasons (see graphic 3). Also, women are 38 percent more likely than men to work 

part-time for economic reasons.111

5. Conclusion 

In conclusion, we urge the Department to withdraw the proposed regulation in its 

entirety. As anti-poverty experts, we believe that the proposed changes will not 

incentivize or equip people with what they need to seek and maintain work, and 

will also have profound and damaging consequences for the well-being and longterm success of struggling workers and their families. We encourage the Department to dedicate its efforts to advancing policies that truly support economic security, self-sufficiency, and a stronger future for the United States by promoting— 

rather than undermining—the ability of unemployed and underemployed workers, 

their families, and their communities to thrive. 

Further, the proposed rule does not provide the analytical information needed to 

justify the policy change and to evaluate the proposed rule’s likely impacts. Because 

of the deficiencies in reasoning and analysis, the proposed rule fails to answer basic 

questions related to the impact of the change and the people whom the proposed 

rule would affect. All in all, the proposed rule does not contain the information and 

375 

data necessary to fully evaluate the proposal or to comment on key aspects on the 

Department’s justification for the rule. 

Last, our comments include citations to supporting research and documents for 

the benefit of the Food and Nutrition Service in reviewing our comments. We direct 

FNS to each of the items cited and made available to the agency through active 

hyperlinks and as attachments, and we request that these, along with the full text 

of our comments, be considered part of the formal administrative record on this proposal. 

Thank you for the opportunity to submit these comments. Contact Elizabeth 

Lower-Basch (elowerbasch@clasp.org) and Renato Rocha (rrocha@clasp.org) with any 

questions. 

APPENDIX A: GRAPHICS REFERENCED IN COMMENT

Graphic 1: Ratio of U–6 to U–3 Measures by State 

Powered by Bing. 

©GeoNames, HERE, MSFT. 

Source: BLS, Alternative measures of labor under-utilization by state, 

fourth quarter of 2017 through third quarter of 2018 averages. 


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Graphic 2: Data Excluded from U–3 Measure and Included in U–6 Measure: 

Unemployed Who Searched for Work in Previous Year but Not in Past 

4 Week 

Source: BLS, People in the labor force and not in the labor force by selected characteristics, 2017 annual averages. 

Graphic 3: Data Excluded from U–3 Measure and Included in U–6 Measure: 

Part-Time for Economic Reasons 

Source: BLS, Employed and unemployed full- and part-time workers by 

age, sex, race, and Hispanic or Latino ethnicity, December 2018. 

APPENDIX B: CONTRIBUTORS TO CLASP’S PUBLIC COMMENT

Listed Alphabetically 

Kisha Bird is CLASP’s director of youth policy. Ms. Bird works to expand access 

to education, employment, and support services for low-income and opportunity 


11602059.eps 11602060.eps
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youth. She is an expert in Federal youth policy and helps ensure national legislation 

has maximum impact for youth of color. Before joining CLASP, Ms. Bird was director of the Pennsylvania Statewide Afterschool/Youth Development Network, working 

to make quality education and afterschool programs accessible to young people. 

Prior to that, she was a program officer at the Philadelphia Foundation, where she 

helped develop and manage the Fund for Children, Youth Advisory Board, and discretionary grants process. She also has direct service experience, working in various 

community settings with children, youth and families. Ms. Bird holds a master of 

social service and master of law and social policy from Bryn Mawr College Graduate 

School of Social Work and Social Research. Additionally, she earned a bachelor’s in 

sociology from Spelman College. 

Whitney Bunts is a policy analyst with CLASP’s youth policy team, with a focus 

on juvenile justice, mental health, racial equity, and Opportunity Youth. Whitney 

has a competence in education policy, opportunity, at-risk, LGBTQ+ youth, racial 

equity, system dynamics, and evaluation. Preceding her career at CLASP, Whitney 

was a graduate student at Washington University in St. Louis. During her time in 

grad school, she interned for the 22nd District Circuits Attorney Office as a Victim 

Services Advocate. In this role, she educated victims on the criminal and juvenile 

justice process, while partnering with prosecutors to advocate for their rights. Additionally, she served as Policy Associate Intern at Covenant House Missouri. As an 

intern she had the opportunity to update, revise, and align their policies with the 

Housing First Federal policy. Additionally, she facilitated workshops to build racial 

equity and inclusion within the organization using System Dynamic tools. As a student, Whitney was a Graduate Policy Scholar, served on the Student Coordinating 

Council and Graduate Professional Council, and was selected for the ‘‘Excellence 

Award for Activism.’’ Prior to attending graduate School, Whitney served as a City 

Year AmeriCorps member where she tutored and mentored hundreds of high school 

students in reading and writing. She holds a Master of Social Work, with a concentration in Children, Youth & Families, and a specialization in Policy and System 

Dynamics from Washington University in St. Louis. Additionally, she has a double 

bachelors in political science and psychology from Georgia State University. 

Aimee Chitayat is a consultant for CLASP’s Income and Work Supports team. 

As Principal of AC Strategic Solutions, she has led efforts to expand SNAP Employment and Training (E&T) since 2007. Aimee developed the first SNAP E&T thirdparty partner programs implemented in California—the Fresh Success intermediary 

model and the county-based Cal Success model—and designed innovative policies, 

procedures, tools, and templates for their implementation. She provides intensive 

training and technical assistance on SNAP E&T to community colleges, communitybased organizations, social enterprises, counties and statewide intermediaries 

throughout the country. She supported New Jersey in drafting successful legislation 

for a SNAP E&T program and provided oversight to the USDA’s SNAP E&T Pilot 

Project in Fresno County as a consultant to the California Department of Social 

Services. She developed, supported, or commented on numerous state and national 

bills and policy clarifications on SNAP and SNAP E&T. She earned her Master of 

Social Welfare from the University of California Berkeley and her undergraduate 

degree from Brown University. 

Parker Gilkesson is a policy analyst with CLASP’s Income and Work Support 

team. She works with low-income and work support programs with a focus on the 

Supplemental Nutrition Assistance Program (SNAP). Parker is a subject matter expert in social policy, benefit eligibility, human services delivery, racial equity, and 

state and local policy regarding SNAP, TANF, and Medicaid. Prior to joining 

CLASP, Parker began her career as a Human Services Specialist in Mecklenburg 

County, Charlotte, NC. In this role, she worked directly with recipients receiving 

Medicaid, TANF, and SNAP to determine their eligibility for low-income and work 

support programs. She has other experience including TANF policy research, cancer 

research, public health, public service, and nonprofits. Parker holds a Master of 

Public Policy, with a concentration in Public Administration from Liberty University 

and a Bachelors in Health Education, Maternal and Child Health from Howard University. Furthermore, Parker believes in the importance of bridging the gap between 

policy analysis and policy effectiveness. She is very passionate about social change 

taking place within our communities, therefore, Parker aspires to be a part of the 

equation to solve poverty and inequities in health and social welfare among citizens 

of the United States. 

Madison Hardee is a senior policy analyst/attorney at CLASP, where she focuses 

on issues affecting access to health care and public benefits for immigrants and 

mixed-status families. Ms. Hardee coleads the Protecting Immigrant Families, Advancing Our Future Campaign in collaboration with the National Immigration Law 

Center. Prior to joining CLASP, Ms. Hardee spent 5 years as an attorney with CharVerDate Aug 31 2005 11:16 Jun 14, 2019 Jkt 041481 PO 00000 Frm 00383 Fmt 6621 Sfmt 6621 P:\DOCS\116-02\36188.TXT BRIAN
378 

lotte Center for Legal Advocacy, where she provided direct legal representation to 

low-income clients across public benefit programs and saw first-hand how programs 

like Medicaid, SNAP and SSI reduce economic hardship, improve health, and increase stability. She successfully challenged state agency decisions and identified 

several areas for systemic advocacy. Working together with partner organizations, 

Ms. Hardee negotiated significant changes to Medicaid and ACA eligibility policies, 

providing access to health care for tens of thousands of low-income immigrants. Ms. 

Hardee holds a Juris Doctor from Tulane Law School and a bachelor’s degree in 

public health from George Washington University. In 2016, she was presented with 

the New Leader in Advocacy Award by the National Legal Aid and Defender Association. 

Elizabeth Lower-Basch is director of CLASP’s income and work supports team. 

Her expertise is Federal and state welfare (TANF) policy, other supports for lowincome working families (such as refundable tax credits), systems integration, and 

job quality. From 1996 to 2006, Ms. Lower-Basch worked for the Office of the Assistant Secretary for Planning and Evaluation at the U.S. Department of Health and 

Human Services. In this position, she was a lead welfare policy analyst, supporting 

legislative and regulatory processes and managing research projects. She received 

a Master of Public Policy from Harvard University’s Kennedy School of Government. 

Judy Mortrude is a senior policy analyst with CLASP’s Center for Postsecondary 

and Economic Success. Ms. Mortrude has more than 30 years’ experience developing, delivering, and evaluating workforce education, particularly with low-literacy 

and high-barrier populations. She has been a classroom teacher, school administrator, and state agency staff. Currently, Ms. Mortrude supports cross-agency state 

teams as they scale and sustain integrated education and training career pathway 

policies and practices; focus attention on racial and economic equity; and build twogenerational strategies. Additionally, she analyzes Federal adult and post-secondary 

education policy and supports organizations like the National Coalition for Literacy 

and the Open Door Collective. 

Renato Rocha is a policy analyst within CLASP’s Income and Work Supports 

team. He focuses on issues regarding work reporting requirements across benefit 

programs as well as access to public benefits for immigrant families. Prior to 

CLASP, Renato was an economic policy analyst at UnidosUS (formerly National 

Council of La Raza), where he conducted analysis of consumer protection, budget, 

tax, disaster relief, and labor issues that impact the well-being of Latino and immigrant communities. In graduate school, he also had the opportunity to work at the 

National Immigration Law Center, where he analyzed policy issues affecting deferred action recipients. Renato holds a Master in Public Affairs from Princeton University’s Woodrow Wilson School of Public and International Affairs and a B.A. in 

Politics from Occidental College. In 2013, Renato served as a Fulbright Public Policy 

Initiative Fellow to Mexico. 

Darrel Thompson is a research assistant with CLASP’s Income and Work Supports team. He provides research support and analysis on various low-income and 

work support programs. Prior to joining CLASP, Darrel interned at the Center on 

Budget and Policy Priorities and the Lou Frey Institute of Politics and Government. 

He holds a bachelor’s degree in political science from the University of Central Florida. 

Isha Weerasinghe is a senior policy analyst focused on mental health and sits 

in CLASP’s youth team. She works on how CLASP’s issue areas impact individuals’ 

mental health, with a specific focus on youth, young adults, and mothers. Ms. 

Weerasinghe previously worked as the Director of Policy and Advocacy at the Association for Asian Pacific Community Health Organizations (AAPCHO), where she focused on the intersections of how Asian Americans, Native Hawaiians, and Pacific 

Islanders (AA&NHPIs) can better access linguistically concordant and culturally appropriate care. She also did a great deal of coalition building and provided policy 

guidance nationally, for AA&NHPI-serving community health centers and 

AA&NHPI-serving organizations, in health access and equity. Ms. Weerasinghe has 

done community based participatory research, as well as local and state policy advocacy in her work at New York University’s Center for the Study of Asian American 

Health (CSAAH), working within New York City and New York state. Over the past 

8 years, she has done extensive coalition work and policy advocacy on the impacts 

of hepatitis B in the United States. Isha has a bachelor’s in arts degree in biology 

from Bryn Mawr College, and a master’s in science degree in health policy and demography from the London School of Economics and Political Science. 

Carrie Welton is a policy analyst on the income and work supports team. Her 

work focuses on advocating for policy reforms that improve the lives of people with 

low income and communities of color using a racial equity lens. This includes improving access to public benefit programs for post-secondary students and student 

379 

parents to advance their academic success. She also advocates for policy reforms 

that strengthen the Earned Income Tax Credit (EITC) and the Child Tax Credit 

(CTC). Previously, Ms. Welton spent 3 years at the W.K. Kellogg Foundation on the 

national Education and Learning team focused on early childhood systems alignment. In addition, she spent 4 years at the Kellogg Company conducting research 

and providing strategic direction to inform the organization’s government relations 

and lobbying efforts. Ms. Welton also served on the state board of the American 

Civil Liberties Union (ACLU) of Michigan, furthering the civil liberties and civil 

rights of residents. As a member of the executive committee, she provided fiduciary, 

strategic, and generative leadership to the organization. She earned her Master of 

Public Administration from the Gerald R. Ford School of Public Policy at the University of Michigan and her undergraduate degree in Public Law from Western 

Michigan University. 

SUBMITTED COMMENT LETTER BY HON. JIMMY PANETTA, A REPRESENTATIVE IN

CONGRESS FROM CALIFORNIA; AUTHORED BY ABBY J. LEIBMAN, PRESIDENT AND

CHIEF EXECUTIVE OFFICER, MAZON: A JEWISH RESPONSE TO HUNGER

March 19, 2019 

Chief, Certification Policy Branch, 

SNAP Program Development, USDA Food & Nutrition Services, 

Alexandria, VA 22302 

Re: Proposed Rule: Supplemental Nutrition Assistance Program (SNAP): Requirement for Able-Bodied Adults without Dependents RIN 0584–AE57 

To Whom It May Concern: 

On behalf of MAZON: A Jewish Response to Hunger, I am pleased to submit 

these comments in opposition to public notice FR Doc. 2018–28059. Based on our 

organization’s many years of expert involvement in anti-hunger related issues, we 

submit for your consideration these comments focused on whether USDA should reconsider certain rules that govern—and restrict—the current waiver standards for 

able-bodied adults without dependents (ABAWDs) who participate in the Supplemental Nutrition Assistance Program (SNAP). 

We unequivocally oppose the proposed rule change, which would restrict 

states’ flexibility to provide vital nutrition support to people who struggle 

to feed themselves and their families. 

Inspired by Jewish values and ideals, MAZON is a national advocacy organization 

working to end hunger among people of all faiths and backgrounds in the United 

States and Israel. For more than 30 years, MAZON has been committed to ensuring 

that vulnerable people have access to the resources they need to be able to put food 

on the table. MAZON is a leading voice throughout the country on anti-hunger 

issues, especially those that involve populations or problems that have been previously overlooked or ignored—this includes food insecurity among veterans, currently-serving military families, seniors, rural and Native American communities, 

and college students. In fact, MAZON has already commented on similar draconian 

proposals, as evidenced by the attached letter we submitted on April 4, 2018 regarding RIN 0584–AE57. 

It is with this experience and focus that we address the proposed rule. 

The Supplemental Nutrition Assistance Program (SNAP) is the cornerstone of our 

nation’s nutrition safety net, and most SNAP recipients who are able to work do, 

in fact, actually work. Under current law, childless adults ages 18 to 49 are restricted to only 90 days of SNAP benefits in 3 years unless they can prove they are 

working or participating in an employment and training program for 80 hours per 

month. States currently have flexibility to request waivers from this harsh and arbitrary time limit for communities that face high unemployment or insufficient job 

opportun[i]ties. USDA’s proposed rule change severely limits this critically important and common-sense flexibility that is utilized by the majority of states. 

Harsher limitations on accessing SNAP ignore the complex realities of low-income 

families. This decision to restrict waivers will exacerbate already difficult circumstances, not alleviate them. 

Needless and Egregious Harm to the American People 

This proposed rule change will have a devastating impact on Americans of all 

walks of life. Working-age adults without minor children are by no means a monolithic population. Approximately 45% are female, and of them, nearly 1⁄3 are over 

380 

1https://www.cbpp.org/research/food-assistance/who-are-the-low-income-childless-adults-facing-the-loss-of-snap-in-2016. 2https://www.ers.usda.gov/webdocs/publications/90556/eib-200.pdf. 3https://www.dailyyonder.com/geography-food-stamps/2018/12/31/25422/. 4https://www.mathematica-mpr.com/our-publications-and-findings/publications/proposedchanges-to-the-supplemental-nutrition-assistance-program-waivers-to-work-related-time. 5https://www.reuters.com/article/us-usa-fed-powell-analysis/in-rural-mississippi-still-waiting-on-recovery-idUSKCN1Q30JH. 6https://www.federalreserve.gov/newsevents/speech/powell20190212a.htm. 7https://www.cbpp.org/research/food-assistance/who-are-the-low-income-childless-adults-facing-the-loss-of-snap-in-2016. 8http://www.hamiltonproject.org/blog/workers_could_lose_snap_benefits_under_trumps_ 

proposed_rule. 9https://www.whitehouse.gov/presidential-actions/executive-order-reducing-poverty-americapromoting-opportunity-economic-mobility/. 10https://www.cbpp.org/research/poverty-and-inequality/work-requirements-dont-cut-povertyevidence-shows. 11https://mlwiseman.com/wp-content/uploads/2019/01/Farmbill.120118.pdf. 12https://www.cbpp.org/research/food-assistance/snap-helps-almost-15-million-low-incomeveterans-including-thousands-in. 13https://www.cbpp.org/research/food-assistance/snap-helps-almost-15-million-low-incomeveterans-including-thousands-in. 14https://www.ncbi.nlm.nih.gov/pubmed/24806818. 

the age of 40. Roughly 1⁄2 of ABAWDs are Caucasian, 1⁄3 African American, and 10% 

Latina.1

Rural Americans 

Rural areas often face unique barriers to achieving food security including a lack 

of public transportation, scarcity of childcare services, lower educational attainment, 

fewer economic opportunities and higher unemployment rates than urban areas.2

With the largest proportion of SNAP participants, rural counties and small metropolitan areas are more dependent on SNAP than urban counties. Of the top 100 

counties that participate in SNAP, 85 are rural.3 There is stunning evidence that 

this proposed rule change would cause extraordinary harm to rural communities in 

southern states.4

In a recent speech about the need for economic development in high-poverty rural 

communities, Chairman of the Federal Reserve Bank Jerome Powell explained that 

rural areas ‘‘generally lack diverse industries and employment options and often 

have suffered from decline in a traditional industry.’’ 5 While current data show a 

strong economy nationally, this is not true for rural America where poverty remains 

a persistent challenge.6

The Working Poor 

We also know that the majority of SNAP recipients who can work do work. Among 

those who would be harmed by this proposed rule, roughly 75% worked the year 

before and/or the year after receiving SNAP. Many of these people continuously experience periods of work and unemployment, stuck in a devastating cycle of inconsistent low-skill, low-wage jobs that are unable to lift anyone out of poverty.7 The 

individuals most at risk of losing SNAP benefits under the proposed rule are workers who experience normal labor market fluctuations and those who should be eligible for exemptions but often do not receive them.8

Ample evidence suggests that harsh SNAP time limits fail to ‘‘increase self-sufficiency, well-being, and economic mobility’’ as intended.9 In fact, we know that the 

vast majority of people subjected to these time limits remained poor or even became 

poorer.10 Even among conservative policy experts who support the principle of work 

requirements, poorly-designed policies like this proposed rule raise concerns and are 

considered to be unreasonable, unrealistic, untested, and clearly designed to cut 

caseloads and costs—not provide needed assistance and a pathway to self-improvement for those who are struggling.11

U.S. Veterans 

We are deeply concerned by the evidence that this proposed rule change would 

severely impact veterans who often face unique challenges in securing full-time 

work and may require more than 3 months to secure employment. 

An estimated 1.4 million veterans live in households that participate in SNAP.12

Evidence suggests that veteran households participate in SNAP at lower rates than 

non-veteran households, indicating that there are thousands who qualify but have 

not applied for this essential lifeline.13 Post-9/11 veterans have nearly double the 

average rate of food insecurity 14 and recent scholarship has raised concerns about 

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15https://www.whijournal.com/article/S1049-3867(17)30419-X/abstract. 16https://www.cbpp.org/research/food-assistance/snap-helps-almost-15-million-low-incomeveterans-including-thousands-in. 17https://bluestarfam.org/survey/. 18https://bangordailynews.com/2017/06/03/politics/i-felt-like-a-caveman-how-work-requirements-for-state-benefits-hurt-one-maine-man/. 19http://www.nativepartnership.org/site/DocServer/2017-PWNA-NPRA-Food-InsecurityProject-Grow.pdf?docID=7106. 

the high rate of food insecurity and resultant health impacts for women veterans.15

We know that many veterans return from combat with disabilities, sometimes 

undiagnosed or not fully recognized, that make it more difficult to maintain gainful 

employment and provide food for themselves and those who rely on them, even if 

they do not meet the definition of ‘‘dependent.’’ Households with a disabled veteran 

are nearly twice as likely to be food-insecure as households that do not have someone with a disability.16

The Blue Star Families 2018 Military Family Lifestyle Survey—the largest and 

most comprehensive survey of active duty service members, veterans, and their families—found employment to be one of the top three issues of primary concern among 

veterans.17 Veterans often struggle to find jobs that match their skills, especially 

if they have little work experience beyond military service. They might also face discrimination from employers, particularly if they have a mental or physical disability. Furthermore, many recently transitioning veterans take temporary jobs but 

struggle to find full-time sustained work that is a good fit for their skills and experience—these veterans will not be able to regularly report 20 hours of work per week 

in order to receive SNAP benefits. 

In addition to employment concerns, veterans who are awaiting a disability determination face enormous challenges in making claims through the U.S. Department 

of Veterans Affairs[’] (VA) daunting claims process, where delays and multiple appeals are commonplace. During this waiting period, many veterans who cannot work 

are also unable, or limited in their ability, to access Federal assistance. 

The State of Maine offers a deeply concerning example of the harmful impacts of 

this proposed rule change on veterans. In 2014, Governor Paul LePage chose not 

to request a SNAP waiver for working-age adults without minor children, for which 

the State of Maine was eligible. As a result of this action, many thousands of Maine 

residents were stripped of access to needed nutrition assistance from SNAP, including an estimated 2,800 veterans affected by these harsh time limits, many of whom 

continue to face unemployment and must turn to the charitable food sector to meet 

their basic needs. 

We urge USDA to consider the story of Tim Keefe, a veteran living in Maine 

whose story provides a personal and painful glimpse of the impact of this proposed 

rule change. When Governor Le Page decided not to seek a waiver for the ABAWD 

SNAP time limit, Tim lost his access to SNAP—one of the only supports that helped 

him get by as he was desperately trying to find employment. He became homeless 

and reported feeling ‘‘like a cave man.’’ 18 Tim resorted to eating squirrels that he 

caught to survive the brutal Maine winter, taking a great toll on his health and 

well-being. He eventually was able to qualify again for SNAP assistance when he 

turned 50. The SNAP benefits he receives now are a lifeline for Tim and enable him 

to regularly put food on the table once again. 

Sadly, Tim’s story is not unique to the veteran experience in America. Veterans 

regularly need temporary supplemental nutrition assistance precisely because they 

frequently find themselves in periods of transition. It does not matter whether they 

are recently returning from service or have already long contributed to our workforce. Nobody deserves to be destabilized by hunger while trying to get back on their 

feet. Ensuring that all veterans have access to adequate and nutritious food is critical, and providing such access to veterans is the least this nation owes to its returning servicemembers who have made such great sacrifices in service to our country. 

Exacerbated Hunger Among Native Americans 

As the first non-Native member of the Native Farm Bill Coalition, MAZON is 

deeply concerned about the profound harm this proposed rule change will have on 

American Indian and Alaska Native individuals. We know that one in four Native 

Americans is food-insecure (double the national average of one in eight), and this 

assault on SNAP eligibility clearly will exacerbate hunger and poverty in this particularly vulnerable and frequently overlooked population.19

Despite reports of high employment on a national scale, unemployment rates on 

reservations remain dangerously high, in some cases as high as 21%, and in some 

382 

20https://www.bloomberg.com/news/articles/2018-04-05/where-u-s-unemployment-is-stillsky-high-indian-reservations. 21https://fns-prod.azureedge.net/sites/default/files/pd/fdpart.pdf. 22https://fns-prod.azureedge.net/sites/default/files/ops/StudyofFDPIR.pdf. 23https://www.phi.org/uploads/files/FDPIR%20Module%20-%20CCRWF%20Nutrition%20 

Primer.pdf. 24https://naturalresources.house.gov/imo/media/doc/Mary%20Greene%20Trottier-Testimony.pdf. 25https://fns-prod.azureedge.net/sites/default/files/fdpir/pfs-fdpir.pdf. 26https://www.federalregister.gov/documents/2000/11/09/00-29003/consultation-and-coordination-with-indian-tribal-governments. 

communities much higher.20 For these communities, waivers for SNAP time limits 

literally save lives, especially considering the geographic isolation and the impact 

still felt today by historic violation of treaties with multiple Tribes, generations of 

discrimination, forced attempts of assimilation, and state-sponsored genocide. 

Denying states the ability to apply for waivers will further strain the Food Distribution Program on Indian Reservations (FDPIR) which serves American Indians 

and Alaska Natives living on reservations or in designated Tribal areas. In 2018, 

FDPIR served an average of 87,216 participants—mostly low-income individuals and 

families, working adults, children, people with disabilities, and seniors.21 FDPIR 

was designed as an alternative to SNAP and serves some overlapping populations 

on Tribal reservations, so changes to SNAP eligibility policies will impact FDPIR.22

Because FDPIR’s funding is capped at a fixed dollar amount, there is a real concern 

about the exhaustion of FDPIR funds in the event of a spike in participation caused 

by individuals cut off from SNAP benefits due to the proposed rule change.23

Mary Greene Trottier, a member of the Spirit Lake Sioux Nation and President 

of the National Association of FDPIR, recently testified before the U.S. House Committee on Natural Resources about the impacts of the recent partial government 

shutdown on Indian Country and the importance of FDPIR to Tribal members. In 

a compelling portion of her testimony, Ms. Trottier recounted how FDPIR was impacted by changes to SNAP benefits in 2013: 

We know from experience that any time SNAP benefits are reduced or taken 

away, our program [FDPIR] sees an immediate rise in applications as people 

seek to feed themselves and their families. In some cases there is a 25 percent 

increase in participation [ . . . ] when SNAP benefits are reduced. We saw this 

in October 2013, when the American Recovery and Reinvestment Act (ARRA) 

expired and SNAP benefits were reduced. In the month after ARRA’s expiration, we saw an immediate rise in participation across FDPIR sites in all our 

regions. Unfortunately, this rise in participation does not come with increased 

funding. We must try to do more with less.24

We cannot count on FDPIR to meet the needs of every food-insecure Native American. Of the 573 Tribes recognized by the Federal Government, FDPIR operates 

among only 276 Tribes. SNAP is the only option available to alleviate food insecurity in 297 Tribal communities.25 Furthermore, since FDPIR exclusively applies to 

Tribes recognized by the Federal Government, the hundreds of Tribes recognized by 

states alone and not by the Federal Government are already unable to utilize the 

limited amount of funding available that exists for FDPIR to supplement loss of access to SNAP. 

Finally, the Federal Government must adequately and appropriately consult with 

all federally-recognized Tribes to ensure meaningful and timely input on legislative 

proposals, policy matters and regulatory changes that have Tribal implications. Consultations and related efforts to improve operation and administration of Federal 

nutrition programs operating in Indian Country stem from a recognition that the 

U.S. has a solemn obligation to support Tribal sovereignty and protect the wellbeing of these communities at a level comparable to non-Natives. USDA’s proposed 

rule change will have a substantial direct and disproportionate impact on Native 

communities, on and off reservations. Accordingly, before moving forward with this 

rulemaking proposal, our government has a duty to consult with Tribal sovereigns 

about this proposed rule change and to consider their concerns and recommendations about how to mitigate potential negative impacts on Native communities.26

College Students 

The proposed rule change denies SNAP access to certain post-secondary students 

without dependents, as well as noncustodial student-parents who are enrolled less 

than part-time. When these students are denied the ability to document hours of 

countable work-related activities while otherwise not being exempt, the Federal 

Government will be harming one of the greatest sources of our workforce developVerDate Aug 31 2005 11:16 Jun 14, 2019 Jkt 041481 PO 00000 Frm 00388 Fmt 6621 Sfmt 6621 P:\DOCS\116-02\36188.TXT BRIAN
383 

27https://www.gao.gov/products/GA0-19-95. 28https://www.jff.org/resources/alleviating-poverty-opportunity-youth/. 29http://clerk.house.gov/evs/2018/roll434.xml. 30https://www.senate.gov/legislative/LIS/roll_call_lists/roll_call_vote_cfm.cfm?congress=115 

&session=2&vote=00259. 31https://www.washingtonpost.com/business/economy/trump-administration-aims-to-toughen-work-requirements-for-food-stamps-recipients/2018/12/20/cf687136-03e6-11e9-b6a9-0aa5c2 

fcc9e4_story.html 

ment by making students food-insecure and decreasing their ability to complete 

coursework. 

A new report from the Government Accountability Office (GAO) found that a 

shocking 39% of all undergraduate students in the country—almost 7.3 million—are 

at risk of hunger because of low household income.27 Unfortunately food insecurity 

often prevents students from completing degrees and credentials because they are 

too hungry to learn. Stable part-time work remains elusive to this student population, many of whom participate in SNAP to ensure that they can cover basic needs 

because of inconsistent schedules, low wages, and lack of benefits.28

There is already confusion about SNAP eligibility for students, and this proposed 

rule change will only worsen the situation. This confusion will also increase difficulty for higher education administrators and state regulators in identifying clear 

eligibility determinations for students. 

Subversion of Democracy 

Not only would this proposed rule cause unprecedented harm to already struggling populations in America, it is an unprecedented undermining of our democracy 

itself. 

At a time of unprecedented political polarization, it is notable that the Agriculture 

Improvement Act of 2018, commonly referred to as the farm bill, was reauthorized 

with historic bipartisan margins of support by votes of 369–47 in the House of Representatives 29 and 87–13 in the Senate.30 As a result of thoughtful and engaged debate and deliberation, Congress agreed that significant changes to the SNAP 

ABAWD waivers were unwarranted and unwise—the bill instead strengthens ten 

pilot programs that are currently examining best practices for SNAP employment 

and training. In stark contrast, this arbitrary new proposed rule change was announced on the same day that President Trump signed the farm bill into law. Designed to curtail SNAP participation, the Administration’s proposal contradicts express Congressional intent and is a callous and calculated attempt to circumvent the 

democratic process as evidenced clearly in the carefully-negotiated final farm bill. 

The proposed rule change could not be more out of touch with the reality of struggling American workers and families. USDA should focus on implementing the 2018 

Farm Bill provisions that will help Americans get back to work, not resort to rulemaking that is a slap in the face to Democracy and jeopardizes critical nutrition assistance for those who need help to put food on the table. 

By USDA’s own estimate, the proposed rule change would result in 755,000 people 

losing access to life-saving nutrition benefits.31 The proposal completely ignores the 

realities of people who are willing to work but face inconsistent work hours, lack 

access to reliable transportation, live in areas where the economy has been slow to 

recover from the Great Recession, or are unable to access employment and training 

programs—all of whom could fail to meet the burdernsome work reporting requirements imposed on SNAP recipients. 

The Administration’s stated goal of subjecting more working-age adults without 

minor children to time limits for SNAP benefits is a tactic designed to cause more 

hardship to the very people USDA claims to help. The current SNAP eligibility restrictions are already punitive as is, with waivers intended for parts of the country 

where jobs and training opportunities are not readily available. Restricting states’ 

ability to issue waivers will unrealistically penalize people and increase hunger— 

the very opposite of SNAP’s intended purpose. 

Importantly, the 2018 Farm Bill lowered the number of people that states can exempt from SNAP time limits. The new law limits states to exempting only up to 

12% (down from 15%) of adults subject to current SNAP time limits, which clearly 

marks the intent by Congress for policy adjustments concerning state waivers for 

SNAP time limits. However, the USDA proposed rule change would prohibit states 

from carrying over any unused percentages from year to year, which could result 

in penalizing those states in years when their economies take a downward turn and 

more families struggle to put food on the table. 

384 

32https://www.cbpp.org/research/food-assistance/waivers-add-key-state-flexibility-to-snapsthree-month-time-limit. 33https://www.cbpp.org/research/food-assistance/waivers-add-key-state-flexibility-to-snapsthree-month-time-limit. 34https://www.fns.usda.gov/snap/abawd-waivers. 35https://www.seattletimes.com/nation-world/private-charity-no-match-for-federal-povertyaid-experts-say/. 36https://www.cbpp.org/research/food-assistance/snap-boosts-retailers-and-local-economies. 37https://www.cbpp.org/research/food-assistance/snap-boosts-retailers-and-local-economies. 38https://www.cbpp.org/research/food-assistance/snap-boosts-retailers-and-local-economies. 39https://www.marketwatch.com/story/prolonged-shutdown-could-slash-gdp-along-with-foodstamps-economist-says-2019-01-07. 40https://www.cbpp.org/research/food-assistance/snap-boosts-retailers-and-localeconomies#ftn6. 

State Flexibility 

The proposed rule change directly assaults states’ flexibility and ability to devise 

meaningful workforce development programs that actually empower SNAP recipients to find and sustain stable work.32 Waivers help states provide reprieve for communities with high unemployment and limited capacity for civil society to support 

and empower SNAP recipients.33

Every state except Delaware has at some point requested to waive time limits on 

SNAP since the adoption of the 1996 welfare reform law—this fact demonstrates 

that states need a certain amount of flexibility in order to ensure that individuals 

and families can try to stave off hunger when they fall on hard times. In fact, 33 

states, the District of Columbia, Guam, and the Virgin Islands are currently approved for statewide or partial time limit waivers, again affirming that there is a 

genuine need for states to have the flexibility to address their unique economic circumstances.34

Charity Alone Cannot End Hunger 

The charitable food sector invests a mighty $5 billion per year to meet emergency 

hunger needs, however the Federal Government—mostly through SNAP—provides 

the vast majority of all food assistance in this country. Additionally, SNAP and similar programs pump $5.8 billion per month, or $70 billion per year, into the U.S. 

economy. 

Stripping people of critical SNAP benefits will directly impact the charitable food 

system, which is already strained. The recent unprecedented government shutdown 

revealed that many Americans are living paycheck to paycheck, with limited savings 

in the event of economic hardship. With thousands of people—including Federal 

workers—turning to the charitable food sector to meet their basic needs, the shutdown also illuminated the vital importance of our Federal nutrition safety net. What 

happens when 755,000 low-income people are kicked off the meager support SNAP 

currently provides? To expect an extraordinarily generous philanthropic sector to increase its expenditures by even a fraction of the twenty-fold difference it holds with 

our government’s ability to be a solution is woefully unrealistic and dangerous.35

Charities cannot make up the difference. 

SNAP Strengthens Our Economy 

We know that SNAP fuels economic growth in this country. Retailers of all sizes 

benefitted from the $63 billion redeemed in 2017 through SNAP funds.36 Based on 

the most recent data available, 10% of all food consumption dollars comes from 

SNAP.37 Firms that accept SNAP experienced an average 4% increase in business 

between 2013–2017.38

Without SNAP, our economy would lose between 0.53% and 1.03% of GDP.39 In 

fact, every SNAP dollar spent expands the economy by $1.70.40 By removing 

755,000 people from SNAP, USDA’s proposed rule change would result in a self-inflicted wound on our economy that would be felt in every state and the District of 

Columbia. 

Invest in Evidence-Based Solutions 

SNAP is first and foremost a food security program, not a catalyst for workforce 

development. It remains unclear how restricting SNAP benefits would help people 

find and sustain gainful employment. Placing more stringent restrictions on struggling Americans will not help anyone find gainful employment. A more meaningful 

way to encourage work among SNAP recipients would be to invest in effective job 

training programs with robust case management to help individuals successfully 

overcome barriers to employment—especially for people in rural areas, on or near 

Indian reservations, and in economically-distressed communities. 

385 

41https://fns-prod.azureedge.net/sites/default/files/snap/SNAP-ET-Pilot-Summaries.pdf. 42https://fns-prod.azureedge.net/sites/default/files/snap/SNAP-ET-Pilot-Summaries.pdf. 43https://www.nationalskillscoalition.org/resources/publications/file/Washington-SNAPbrief-web_FINAL.pdf 44https://www.nationalskillscoalition.org/resources/publications/file/Washington-SNAPbrief-web_FINAL.pdf 45https://www.whitehouse.gov/presidential-actions/executive-order-reducing-poverty-americapromoting-opportunity-economic-mobility/. 

USDA has already invested in pilot employment and training programs in ten 

socioeconomically and geographically diverse states.41 Among the most successful of 

these programs is the partnership with the Washington State Department of Social 

and Health Services Resources to Initiate Successful Employment (RISE) project. 

RISE empowers and serves individuals receiving SNAP who face significant barriers 

to employment—this includes veterans, people experiencing homelessness, individuals with limited English proficiency, and non-custodial parents with child support 

obligations. Case managers employed by community colleges and community-based 

organizations help lower barriers to employment by leveraging housing resources, 

working with the Division of Child Support for clients who are delinquent in child 

support payments, and creating accelerated training strategies and job placements 

within in-demand or high growth industries.42

Washington’s RISE program played a critical role in the state’s workforce development efforts, empowering over 40,000 people with employment, training, and support services in the Greater Seattle Area.43 Of the individuals enrolled in the program between 2009 and 2011, 71% were employed with a median hourly wage of 

$11 per hour and over $33 million was generated for the community-based organizations and community colleges to deliver the program training.44

The U.S. would be far better served by replicating this program’s success across 

the country instead of pulling the rug out from under vulnerable Americans while 

they are already experiencing hardship. 

Conclusion 

MAZON is deeply concerned that the Administration is going down a dangerous 

path of proposed rulemaking that seems intended to discourage SNAP use without 

any meaningful alternatives to economic empowerment. If adopted, this proposed 

rule change would hurt hundreds of thousands of SNAP recipients—veterans, Native Americans, college students, and people living in rural and remote communities, and other vulnerable sectors of our nation—all of whom are vital to our collective strength and success. MAZON urges USDA to rescind this proposed rule 

change and instead dedicate resources toward strengthening employment and training opportunities to help people find pathways to sustainable and meaningful employment. 

If the purported goal of this proposed rule change is to ‘‘increase self-sufficiency, 

well-being, and economic mobility,’’ this Administration’s actions are misguided and 

its priorities troubling.45 I would refer you to the comments submitted on behalf of 

MAZON on April 4, 2018 in response to the Advance Notice of Proposed Rulemaking 

regarding SNAP and requirements and services for ABAWDs (included with these 

comments), which included recommendations about how to improve SNAP and better help those who struggle with food insecurity in this country. 

We remain unwavering in our opposition to this proposed rule change, which 

makes an end-run around Congressional intent and would severely curtail states’ 

flexibility to provide life-saving nutrition support to their residents who struggle to 

feed themselves and their loved ones. 

Sincerely, 

ABBY J. LEIBMAN, President and Chief Executive Officer. 

ATTACHMENT

April 4, 2018 

Ms. SASHA GERSTEN-PAAL, 

Chief, Certification Policy Branch, 

SNAP Program Development, USDA Food & Nutrition Service, 

Alexandria, VA 


11602056.eps
386 

Re: Advanced Notice of Proposed Rulemaking: Supplemental Nutrition Assistance 

Program: Requirements and Services for Able-Bodied Adults Without Dependents RIN 0584–AE57 

Dear Ms. Gersten-Paal, 

On behalf of MAZON: A Jewish Response to Hunger, I am pleased to submit 

these comments regarding input requested about whether USDA should reconsider 

certain rules that govern the 3 month time limit on childless adults for the Supplemental Nutrition Assistance Program (SNAP). 

Inspired by Jewish values and ideals, MAZON is a national advocacy organization 

working to end hunger among people of all faiths and backgrounds in the United 

States and Israel. For more than 30 years, MAZON has been committed to ensuring 

that vulnerable people have access to the resources they need to be able to put food 

on the table. MAZON is a leading voice throughout the country on anti-hunger 

issues, especially those that involve populations or problems that have been previously overlooked or ignored—this includes food insecurity facing veterans, currently serving military families, seniors, Native Americans, and college students. 

The Jewish community has a rich tradition of asking questions and wrestling with 

different perspectives in order to discover the meaning and truth about an issue. 

However, asking the right questions is critical in the pursuit of understanding. We 

are concerned that the focus for USDA’s solicited input to inform the proposed rulemaking is misdirected, and the questions being asked will not advance the stated 

goals of addressing food insecurity and helping people move out of poverty. In short, 

they are not the right questions. 

SNAP is first and foremost a food security program, not a catalyst for workforce development. The framing of this request for public comments that links the 

goal of addressing food insecurity with ‘‘helping able-bodied SNAP recipients obtain 

and maintain employment and aligning program regulations with the President’s 

Budget proposals related to ABAWDs’’ misconstrues the purpose of the SNAP program and approaches the issue using an incorrect premise, ensuring that recommendations will not be responsive to the actual goals of this long-standing program. This request for comments does not inspire us to provide suggestions, input, 

and answers; instead, it has only provoked more questions: 

• How would placing more stringent time limits on able-bodied adults without dependents (ABAWDs) receiving SNAP actually help people to find and sustain 

gainful employment? What is the evidence and data to support this notion? 

What data exists to show how severe time-limits have contributed to employment for recipients of SNAP and other Federal assistance programs? 

• Why is the focus for USDA’s inquiry on processes and procedures affecting 

ABAWDs and not on additional investments to ensure access to employment 

and training opportunities to help move them towards self-sufficiency? Why 

does this inquiry not address the importance of case management and other 

supports that take into consideration the real circumstances and challenges 

faced by unemployed individuals that have not only demonstrated efficacy but 

are designed to make the transition to employment much more effective? 

• Why do states have the option to offer Employment and Training (E&T) on a 

voluntary basis to certain or all SNAP participants but are not mandated to do 

so, and why does this request for comments not seek insights about whether 

this policy should be reconsidered? 

• Does USDA recognize that ABAWDs are by no means a monolithic population, 

including veterans, college students, those suffering from mental health challenges, and individuals formerly in the foster care system? How does USDA envision ensuring the employment of this diverse and complex population in 3 

months or fewer? What considerations do USDA and states currently make to 

account for the diverse circumstances and challenges by unemployed ABAWDs 

trying to find employment? What more could USDA and states do to recognize 

and address the needs of this diverse population? 

• What is USDA doing to increase employment, training, and workforce participation among ABAWDs in collaboration with other Federal agencies that have 

more experience and expertise in these areas? Why is so much burden to increase employment being placed on SNAP, which is a nutrition assistance program not an employment training program? 

• Why is USDA seeking input on these questions now, when the results of the 

SNAP E&T pilot programs called for in the last farm bill are not yet available? 

Would it not be more prudent and helpful to consider the data, best practices, 

and lessons learned from those pilot programs before seeking to make policy 

387 

and programmatic changes? Would making such changes without the benefit of 

the results of these pilot programs be considered irresponsible and a disservice 

to the SNAP program and the millions of Americans who receive vital assistance from it? 

• Does USDA truly believe that the receipt of SNAP benefits prevents unemployed ABAWDs from seeking and securing gainful employment? Does USDA 

believe that revoking SNAP benefits after a 3 month time period will notably 

increase employment rates for ABAWDs? What is the evidence to support these 

beliefs? 

• Does USDA believe that hunger is the best motivator for self-improvement? Is 

government-imposed hunger—forcing people off needed benefits without adequate training or opportunities—an appropriate function of the Federal Government? What are the moral justifications for this policy? 

While we welcome the chance to address opportunities for improvement of the 

SNAP program, we fail to understand the singular focus on ABAWDs, which completely ignores the complex realities of their lives, the economic circumstances of the 

diverse regions of this country, and the lack of data to support cutting them off from 

nutrition assistance. The rhetorical framing of these proposals, and the proposals 

themselves, seek to punish struggling Americans with harsh penalties for conditions 

beyond their control. MAZON hopes that USDA can answer our questions to help 

provide greater clarity and vision to the proposed changes to SNAP. We hope that 

USDA can take a step back to ask the right questions about how to improve SNAP 

and better help those who struggle with food insecurity in this country. 

Sincerely, 

ABBY J. LEIBMAN, President and Chief Executive Officer. 

SUBMITTED COMMENT LETTER BY HON. JIMMY PANETTA, A REPRESENTATIVE IN

CONGRESS FROM CALIFORNIA; AUTHORED BY KEITH CARSON, VICE PRESIDENT, BOARD OF SUPERVISORS, DISTRICT 5; CHAIR, PERSONNEL, ADMINISTRATION AND

LEGISLATION (PAL) COMMITTEE

March 29, 2019 

Certification Policy Branch, 

SNAP Program Development Division, 

Food and Nutrition Service, USDA, 

Alexandria, Virginia 

RE: Proposed Rule: Supplemental Nutrition Assistance Program (SNAP): Requirements for Able-Bodied Adults without Dependents RIN 0584–AE57 

Dear Certification Policy Branch: 

The County of Alameda, California (‘‘Alameda County’’ or the ‘‘County’’) submits 

these comments in response to the February 1, 2019 Notice of Proposed Rulemaking 

(‘‘NPRM’’ or ‘‘proposed rule’’) from the Department of Agriculture’s Food and Nutrition Service (FNS) on the Supplemental Nutrition Assistance Program that proposes 

changes to the able-bodied adults without dependents (ABAWD) state waivers. This 

includes rejecting the proposed seven percent unemployment floor for the 20 percent 

standard, limitation of applicable data to only that provided by the Bureau of Labor 

Statistics (BLS), limitation of waiver applicability to only the fiscal year in which 

it is implemented, restriction on regions that can be combined for a waiver application, the elimination of historical seasonal unemployment as a criterion for approval, 

and restricted use of the 15 percent exemptions. The County of Alameda strongly opposes these proposed changes and urges FNS to immediately withdraw the proposed rule. 

The Alameda County Social Services Agency (ACSSA) administers eligibility for 

CalFresh (the Supplemental Nutrition Assistance Program, or SNAP) and the SNAP 

Employment and Training (SNAP E&T) programs. SNAP plays a critical role in addressing hunger and food insecurity in our community. It is the first line of defense 

against hunger for low-income residents. SNAP drives over $11 billion in total economic activity annually in California and the proposed rule would harm our local 

economies, retailers and agricultural producers by reducing the amount of SNAP 


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388 

dollars people have to spend on food. Approximately 99,180 individuals receive nutritional support through SNAP in Alameda County. 

Under the current rules, an Able-Bodied Adult Without Dependents (ABAWD) is 

a non-assistance CalFresh/SNAP recipient age 18 to 49 who is able-bodied without 

dependent children. ABAWD eligibility for CalFresh/SNAP is time limited to any 3 

full months of benefits in a 36 month period unless the individual: (1) satisfies the 

ABAWD work requirement; (2) is exempt from the ABAWD time limit; (3) qualifies 

for an additional 3 consecutive month period of eligibility; (4) receives a 15 percent 

exemption; or (5) lives in a county or area with a waiver of the ABAWD time limit. 

Many ABAWDs subject to the time limit face significant barriers and struggle to 

find and maintain employment. As a result, the work requirement functions more 

as a time limitation, and individuals categorized as ABAWDs simply lose nutritional 

support at the end of 3 months. 

A county, multi-county region, area within a county, or an entire state can be approved for a waiver of the ABAWD time limit if it meets federally established criteria regarding high unemployment or lack of sufficient jobs. Alameda Comity has 

had a waiver for ABAWD eligibility since May 2008, when a statewide waiver was 

approved at the start of the recession. The County previously operated under a 

waiver from December 1996 through August 1997. While the State of California no 

longer holds a statewide waiver, Alameda County is operating CalFresh/SNAP with 

a regional ABAWD waiver until August 31, 2019. The waiver has permitted 

ABAWD CalFresh/SNAP recipients to continue receiving nutritional support during 

times when jobs have been scarce, the unemployment rate [is] higher than the national average, and the job-to-employment ratio [is] historically low. The County 

also operated under a 15 percent exemption for ABAWDs for Fiscal Years 2000– 

2007. 

California has structured the use of exemptions such that exemptions can be used 

to encourage individuals to engage in employment and training activities. For example, exemptions could be used for individuals living in rural areas who may require 

additional time to engage in job search activities, or for those individuals who are 

engaged in employment and training but may happen to not meet the hours needed 

during a given month, for example if an individual falls ill for a day and therefore 

falls short of meeting the hourly requirement in the month. 

Establishing a Lower Unemployment Floor 

One of the proposals is to set a floor of seven percent unemployment for which 

the 20 percent standard for regional waivers would be considered. The NPRM requests comments on setting the floor at six, seven, or ten percent. Given that the 

‘‘natural rate of unemployment’’ cited in the NPRM is five percent, Alameda County 

is of the position that the proposed floors are higher than what is reasonable to 

meet the waiver’s intention: to provide relief for those areas where unemployment 

rates limit one’s ability to find a job and meet ABAWD work requirements. The theory of a natural rate of unemployment is debated by economists, and is impacted 

by the larger conditions of the economy—meaning it does not stand at a steady rate. 

There is not one agreed-upon steady figure for the current natural rate of unemployment, and of recent estimates, five percent is on the higher side. If the natural rate 

were actually closer to four percent, as some economists and Federal Reserve Banks 

have argued, then a seven percent floor for the 20 percent standard would require 

an unemployment rate 75 percent higher than the natural rate for waiver eligibility. 

This means that in an economic downturn, regions would need to lose more jobs 

than the market provides—leaving more workers out of work—before they may be 

potentially eligible for an ABAWD waiver. Because the natural rate of unemployment is one that fluctuates with the larger economy, Alameda County believes setting a constant floor in relation to a proposed constant estimate of the ‘‘natural rate’’ 

for the consideration of ABAWD waivers is inappropriate. It is potentially due to 

these fluctuations that the original ABAWD guidance following the 1996 Personal 

Responsibility and Work Opportunity Reconciliation Act (PRWORA) did not set a 

‘‘floor’’; rather, the regulations set regional waiver eligibility in relation to the national unemployment average. This relationship between a state or region and the 

national average better estimates the actual job losses or gains that impact individuals within the region as they seek employment. Alameda County believes the 20 

percent standard should maintain the relationship between the state/region unemployment rate and the national unemployment rate. 

The NPRM notes that with the current relational metric for the 20 percent standard, 44 percent of ABAWDs live in waived areas. A seven percent standard would 

reduce this to 11 percent of ABAWDs, six percent standard to 24 percent, and a ten 

percent standard to only two percent of ABAWDs. All proposed floors would result 

in a dramatic loss of nutritional support for individuals who are eligible for SNAP. 

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1State of California Employment Development Department, ‘‘County to County Commute Patterns,’’ https://www.labormarketinfo.edd.ca.gov/data/county-to-county-commute-patterns.html. 

According to the Bureau of Labor Statistics (BLS), the Oakland-Hayward-Berkeley 

division, which encompasses much of Alameda County, had a civilian labor force of 

1,449,098 in November 2018. To achieve a seven percent unemployment rate, more 

than 60,190 jobs would need to be lost. To achieve a ten percent unemployment rate, 

more than 103,660 jobs would need to be lost. These would be significant changes 

to the local economy, causing considerable harm to the most vulnerable as the economy loses jobs, and due to strict waiver requirements if the NPRM becomes finalized, ABAWDs would be ineligible for CalFresh/SNAP benefits appropriate to local 

and individual needs. If the intention is to remove beneficiaries from the program, 

then setting one of these floors would meet that intention. However, the goal stated 

in the Food and Nutrition Act of 2008 is ‘‘the policy of Congress, in order to promote 

the general welfare, [is] to safeguard the health and well-being of the Nation’s population by raising levels of nutrition among low-income households.’’ A proposal to 

restrict state ABAWD waivers, such as proposed by this NPRM, was rejected by 

Congress during the recent reauthorization of the farm bill in fall 2018; therefore, 

this NPRM exceeds Congressional intent. 

Limiting State Waiver Areas To Those Designated As a Labor Market Area 

(LMA) 

The NPRM includes a proposal to limit the areas states could group together for 

a state waiver to those that are [designated] as a Labor Market Area (LMA) by the 

Federal Government. The NPRM justifies this proposal by stating that the limitation ensures that only areas that are economically tied together are grouped together. Alameda County believes that this proposal is significantly too narrow. For 

example, the LMA that includes much of Alameda County is the San Francisco-Oakland-Hayward Metropolitan Statistical Area. Due to a jobs/housing imbalance 

throughout much of the San Francisco Bay Area, County to County Commute Estimates compiled by the Employment Development Department illustrate that the 

MSA is insufficient. These estimates show that 235,311 workers commute to jobs 

in Alameda County from—Contra Costa (92,797), Santa Clara (38,339), San Joaquin 

(26,121), San Francisco (22,009), San Mateo (13,417), Stanislaus (8,198), and nearly 

a dozen other counties in the vicinity. Similarly, 227,757 workers who reside in Alameda County commute to jobs outside the County to—San Francisco (71,861), Santa 

Clara (64,696), Contra Costa (39,883), San Mateo (34,369) and nearly a dozen other 

counties in the vicinity.1 The Bay Area is significantly larger than the traditional 

nine county Bay Area, as ‘‘super-commuters’’ from regional counties travel to 

polycentric urban centers throughout the region to reach their place of employment. 

Restricting ABAWD waivers to LMAs would significantly underestimate the impact 

of labor market shifts in Alameda County’s multi-county relationships. Job losses 

in any of the neighboring LMAs would directly impact workers who live in Alameda 

County. With the proposal in the NPRM, these workers would not have their job 

losses included in ABAWD waiver consideration. 

Limiting the Duration of Waivers 

Alameda County has concerns about the NPRM proposal to limit ABAWD waivers 

to the fiscal year in which they are implemented. Processing time for waiver applications could limit the applicability of the waiver. For example, the current ABAWD 

waiver under which Alameda County operates was submitted September 18, 2017. 

FNS action did not occur until July 2, 2018—nearly 10 months later, and into a new 

fiscal year—with the waiver applying to September 1, 2018 through August 31, 

2019. If the NPRM were finalized as written, this waiver may have only been applicable for 1 month: through September 2018. We are concerned that with lengthy 

processing timelines, ABAWD waivers may be approved only for a matter of months 

per application, rather than providing relief for a year, as has been regular practice. 

County processes would be considerably complicated by this move, as a new waiver 

or end of a waiver changes ABAWD eligibility practices for workers throughout the 

agency. Significant staff time would be used to update systems and practices for 

each time-restricted waiver. Eliminating statewide waivers would result in a significant administrative burden in California which will not help save or reduce costs. 

The elimination of the waiver would require additional staff time and training to 

engage the ABAWD caseload to encourage participation in employment and training 

activities. 

390 

2 Center on Budget and Policy Priorities, ‘‘More than 500,000 Adults Will Lose SNAP Benefits 

in 2016 as Waivers Expire,’’ March 2016. https://www.cbpp.org/research/food-assistance/morethan-500000-adults-will-lose-snap-benefits-in-2016-as-waiversexpire#_ftn3. 3 California Food Policy Advocates, ‘‘Nutrition & Food Insecurity Profile—Alameda County,’’ 

July 2016. https://cfpa.net/county-profiles/. 4 California Budget and Policy Center, ‘‘Making Ends Meet Fact Sheet: Alameda County 

Monthly Family Budget,’’ 2017. https://www.calbudgetcenter.org/wp-content/uploads/FactSheet_Making-Ends-Meet-2017_AlamedaCty.pdf. 5 Alameda County Community Food Bank, ‘‘2014 Hunger Alameda County Uncovered,’’ 2014. 

https://www.accfb.org/wp-content/uploads/2017/08/ACCFB-HungerStudy2014-smaller.pdf. 6 Bread for the World Institute, ‘‘The 2016 Hunger Report by the Numbers,’’ 2016. http:// 

hungerreport.org/2016/wp-content/uploads/2015/12/HR2016-Fact-Sheet.pdf. 7 U.S. Department of Health and Human Services Office of the Assistant Secretary for Planning and Evaluation, ‘‘How Many Families Might be Newly Reached By Child Support Cooperation Requirements in SNAP and Subsidized Child care, and What Are Their Characteristics?’’, 

July 2018, https://aspe.hhs.gov/pdf-report/how-many-families-might-be-newly-reached-childsupport-cooperation-requirements-snap-and-subsidized-child-care-and-what-are-their-characteristics. 

Harm to Individuals, Families and Children, and Impact to Local Economies 

The goal for SNAP recipients to achieve self-sufficiency is predicated on the ability 

of local economies to provide adequate opportunities for gainful employment. 

Though the national unemployment rate has recovered from the Great Recession, 

many individuals in a wide variety of regions continue to struggle finding steady 

work that makes ends meet. The employment-to-population ratio, as tracked by 

BLS, has not yet recovered to pre-recession levels. The ABAWD waivers provide relief for these individuals, so that their ability to purchase adequate food necessary 

for their well-being is not negatively impacted by factors outside of their control. Nationwide, USDA data show that the individuals impacted by ABAWD waivers have 

an average monthly income of approximately 17 percent of the poverty line.2 These 

individuals typically qualify for no other income support. This rule is harsh and unfair. It harms vulnerable people by denying them food benefits at a time when they 

most need it and, yet does not result in increased employment and earnings. By 

time-limiting food assistance to this group, Federal law has shifted the burden of 

providing food to these unemployed individuals from SNAP to states, cities, and 

local charities. Removing nutrition support does not enable these individuals to secure employment, or work more hours. It does not increase self-sufficiency; instead, 

the proposed policy change only causes harm to those most in need. 

In Alameda County, there are approximately 167,000 food-insecure-households.3

While a two-working-parent family with two children needs $97,000/year to make 

ends meet,4 the annual income of 40% of the households served by the Alameda 

County Community Food Bank is $10,000/year or less.5 It has been demonstrated 

that individual, household, and societal costs of food insecurity are high. Food-insecure households are sometimes unable to afford balanced, healthy meals, putting 

them at increased risk of diet-related disease such as diabetes and obesity. Further, 

food-insecure children are at higher risk of being hospitalized, iron deficient, obese, 

have lower tests scores than their peers, have greater difficulty getting along with 

other children, and may have impaired social development. Food insecurity also 

places a burden on our health care and safety net systems—systems in which millions of households run short of money for food at the end of each month. Being 

food-insecure is correlated to a nearly 50% increased likelihood of being in the top 

5% of health care users, and it is estimated that food insecurity costs the U.S. 

health system $160 billion per year in poor health outcomes and additional health 

care.6

Because SNAP is so important for low-income and food-insecure children, children 

under the age of 18 and the adults who live with them are technically exempt from 

the 3 month time limit for SNAP. However, though current rules around the SNAP 

time-limit explicitly exempt adults who have a dependent child under the age of 18 

or live in a household with children under 18, this definition may not allow for the 

complex financial arrangements that low-income families utilize to put food on the 

table. Alameda County represents the interests of vulnerable children who as a result of this rule will experience a reduction in important resources that help meet 

their basic needs, even though FNS does not account for this in its cost-benefit analysis. This includes: 

Children with non-custodial parents: Poverty is a troubling reality for custodial and noncustodial parents. The most recent available data from 2015 suggests 

that 3.5 million custodial parents live below the poverty line, making access to food 

assistance all the more important for them and their children.7 Thus, some 4.5 milVerDate Aug 31 2005 11:16 Jun 14, 2019 Jkt 041481 PO 00000 Frm 00396 Fmt 6621 Sfmt 6621 P:\DOCS\116-02\36188.TXT BRIAN
391 

8 U.S. Census Bureau, ‘‘Custodial Mothers and Fathers and Their Child Support: 2015 Current Population Survey,’’ April 2016, Table 4, https://www2.census.gov/programssurveys/demo/ 

tables/families/2015/chldsu15.pdf. 9 Ibid. at 7. 10 Heather Hahn, ‘‘Navigating Work Requirements in Safety Net Programs: Potential Pathways for Parents,’’ The Urban Institute, January 2019, https://www.urban.org/sites/default/ 

files/publication/99479/navigating_work_requirements_in_safety_net_programs_0.pdf. 11The Pew Charitable Trusts, ‘‘Extended Family Support and Household Balance Sheets: Getting by with a little help from friends and relatives,’’ March 2016, https://www.pewtrusts.org/ 

-/media/assets/2016/03/fsm_kinshipbrief.pdf. 12Megan Martin, Shadi Houshyar, Alexndra Citrin, DeQuendre Neeley-Bertrand, DeQuendre 

and Raquan Wedderburn, ‘‘Supporting Youth Aging Out of Poster Care through SNAP,’’ The 

Center for the Study of Social Policy, 2014, https://www.cssp.org/policy/2016/supportingyouth-aging-out-of-foster-care-through-SNAP.pdf. 

lion poor and low-income custodial parents who rely on child support payments from 

non-custodial parents (NCPs) also utilize SNAP to put food on the table for their 

children.8 Yet NCPs are often themselves low-income, with 2.1 million living below 

the poverty line in 2015, and 1.5 million accessing SNAP to supplement their resources to afford child support payments.9 Because NCPs are not exempt from the 

ABAWD time-limit, the proposed rule not only threatens them, but their children. 

An under-employed or unemployed NCP who loses SNAP may need to divert his or 

her income from child support payments in order to stay afloat financially, which 

would be particularly devastating given that child support represents more than 1⁄2

of the income of the families in poverty who receive it.10

Children whose extended family members provide financial support: 

Some low-income children may rely on food, financial assistance, or free childcare 

from extended family members, family friends, or a parent’s significant other who 

do not live with them but use SNAP to supplement their income. Households that 

are the most financially precarious are the most likely to rely on such transfers to 

make ends meet. Considering that financially precarious households are often embedded together within the same networks, they likely received money or assistance 

from others who are also struggling economically.11 If ABAWDs in these networks 

lose SNAP benefits due to tightened state waiver rules, it would disrupt their ability 

to lend that crucial assistance to low-income children. 

Youth aging out of foster care and unaccompanied homeless youth: Youth 

in foster care and unaccompanied homeless youth disproportionately experience significant barriers to obtaining a high school diploma, entering college, obtaining a 

driver’s license, accessing health insurance, maintaining housing stability, and obtaining steady employment. SNAP plays a significant role in the health and wellbeing of youth aging out of care and unaccompanied homeless youth with no support 

systems. Former foster youth often experience poor nutrition and food insecurity, 

and SNAP benefits help to address this problem and increase the likelihood of 

healthy adult outcomes.12 However, because former foster youth and unaccompanied 

homeless youth often meet the definition of an Able-Bodied Adult Without Dependents, they face obstacles accessing this critical assistance and would likely disproportionately suffer under tightened state waiver requirements. 

The Department provides little analysis to explain its conclusions about the impacts the changes would have on individuals and population groups nor of realistic 

plans to avert harm from those changes. USDA merely asserts its expectation that 

2⁄3 of those individuals made newly subject to the time limit ‘‘would not meet the 

requirements for failure to engage meaningfully in work or work training.’’ By the 

Administration’s own calculations, the proposed rule would take food away from 

755,000 low-income Americans, cutting food benefits by $15 billion over 10 years. 

The Administration does not estimate any improvements in health or employment 

among the affected population. Moreover, while the Department concedes that the 

proposed changes ‘‘have the potential for disparately impacting certain protected 

groups due to factors affecting rates of employment of these groups, [it] find[s] that 

implementation of mitigation strategies and monitoring by the Civil Rights Division 

of FNS will lessen these impacts.’’ But no explanation of the mitigation strategies 

and monitoring is provided, leaving no opportunity for the public to comment on 

whether the acknowledged disparate impact will in fact be mitigated. 

The economic impact of such a drastic change in ABAWD rules has an enormous 

economic impact not only on California as a state, but on local California communities and counties as well. Based on USDA Economic Research Service analysis, 

it is estimated that each $1 in Federal SNAP benefits generates $1.79 in economic 

activity. Those dollars help many food retailers operating on thin margins to remain 

in business; something that improves food access for all residents. 

392 

Conclusion 

For all of these reasons, Alameda County strongly opposes the proposed rule that 

would expose even more people to the arbitrary food cutoff policy by limiting state 

flexibility regarding area waivers and individual exemptions. Furthermore, we urge 

you to immediately withdraw the proposed rule. 

Sincerely, 

KEITH CARSON, 

Vice President, Board of Supervisors, District 5; 

Chair, Personnel, Administration and Legislation (PAL) Committee. 

CC: 

California Congressional Delegation; 

Members, Board of Supervisors; 

DONNA ZIEGLER, Alameda County Counsel; 

LORI COX, Director, Social Services Agency; 

COLLEEN CHAWLA, Director, Health Care Services Agency; 

C.J. Lake, LLC; 

County Welfare Directors Association of California. 

SUBMITTED COMMENT LETTER BY HON. TED S. YOHO, A REPRESENTATIVE IN

CONGRESS FROM FLORIDA

February 19, 2019 

Hon. SONNY PERDUE, 

Secretary of Agriculture, 

U.S. Department of Agriculture, 

Washington, D.C. 

Dear Secretary Perdue, 

We write to thank you for the United States Department of Agriculture’s (USDA) 

recent notice of proposed rulemaking regarding work requirements for able-bodied 

adults without dependents (ABAWD) recipients of the Supplemental Nutrition Assistance Program (SNAP), RIN 0584–AE57, and to urge our support for promulgation of the rule as proposed. At a time when our nation is seeing historic economic 

growth, including generationally-low unemployment rates, this proposed rule will 

allow our country to continue to thrive by restoring integrity to SNAP and by moving the American people toward complete self-sufficiency, thereby saving American 

taxpayers billions of dollars. 

As you may know, SNAP was originally intended to give hard-working Americans 

a second chance should they encounter a difficult stretch in life—it was never intended to become one’s livelihood, or their so-called ‘‘way of life.’’ In spite of this, 

since our last welfare reform legislation in 1996, the program has repeatedly shifted 

from these first intentions, and has continually been weakened by increased administrative flexibility. 

This flexibility has allowed state governments to abuse their power and evade the 

reasonable work requirements that SNAP utilizes to ensure that recipients don’t 

take advantage of the current system. These requirements obligate ABAWDs, who 

are non-disabled and between the ages of 18 and 49, to work or participate in an 

employment program for at least 20 hours a week to continue to receive benefits 

for more than 3 months over a 36 month period. 

However, under the current law, state governments may waive these requirements in areas where the unemployment rate is above the national average. Given 

our nation’s strong economy, this can include areas with unemployment rates under 

five percent—a rate that is conventionally considered as full employment. Additionally, states are allowed to grant partial state waivers by grouping together areas 

with similar labor markets, which allows a state to gerrymander areas for waiver 

purposes, thus potentially authorizing waivers for the entire state. 

Also, states may exempt up to 15 percent of their ABAWDs. However, should the 

states not use these exemptions, they are able to hoard them for use in future years, 

which has resulted in certain states accumulating hundreds of thousands of exemptions. All of this has led to an abdication of SNAP’s original purpose and has 

disincentivized self-sufficiency, which resulted in 3.8 million individual ABAWDs on 

SNAP in 2016, of which 2.8 million were not working at all. 


11602057.eps
393 

The USDA’s proposed rule would help to fix this significant problem by implementing several common-sense reforms to the current work requirement waiver 

laws. These include raising the necessary unemployment threshold for local area 

work requirement waivers to seven percent unemployment, ending the states’ ability 

to gerrymander waiver districts by only granting partial state waivers for areas that 

are ‘‘economically tied,’’ ending the states’ ability to accumulate and carryover work 

requirement exemptions for more than 1 year, and increasing SNAP administrative 

efficiency by setting clearer standards for allowable waivers. 

These reforms would save hard-working American taxpayers $15 billion over a 10 

year period and would help to reestablish the true goal of the SNAP program, to 

help hard-working Americans in their attempts to gain self-sufficiency. As such, we 

support the USDA’s proposed rule and urge you to promulgate this rule in its current proposed version, to ensure our nation’s continued success. 

Thank you, 

Hon. KEVIN HERN, 

Member of Congress; 

Hon. TOM COLE, Hon. MARKWAYNE MULLIN, 

Member of Congress; Member of Congress; 

Hon. TRENT KELLY, Hon. MARK MEADOWS, 

Member of Congress; Member of Congress; 

Hon. KEVIN BRADY, Hon. MIKE JOHNSON, 

Member of Congress; Member of Congress; 

Hon. BRIAN BABIN, Hon. GARY J. PALMER, 

Member of Congress; Member of Congress; 


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394 

Hon. DUSTY JOHNSON, Hon. VAN TAYLOR, 

Member of Congress; Member of Congress; 

Hon. JIM JORDAN, Hon. MATT GAETZ, 

Member of Congress; Member of Congress; 

Hon. ANDY HARRIS, Hon. JOHN JOYCE, 

Member of Congress; Member of Congress; 

Hon. MICHAEL C. BURGESS, Hon. BOB GIBBS, 

Member of Congress; Member of Congress; 

Hon. JOHN RATCLIFFE, Hon. KELLY ARMSTRONG, 

Member of Congress; Member of Congress; 

Hon. RALPH NORMAN, Hon. RON WRIGHT, 

Member of Congress; Member of Congress; 


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395 

Hon. SCOTT PERRY, Hon. ROGER W. MARSHALL, 

Member of Congress; Member of Congress; 

Hon. MO BROOKS, Hon. ALEXANDER X. MOONEY, 

Member of Congress; Member of Congress; 

Hon. JEFF DUNCAN, Hon. MIKE BOST, 

Member of Congress; Member of Congress; 

Hon. DAVID SCHWEIKERT, Hon. JASON SMITH, 

Member of Congress; Member of Congress; 

Hon. TIM BURCHETT, Hon. ANDY BARR, 

Member of Congress; Member of Congress; 

Hon. ROGER WILLIAMS, Hon. MICHAEL GUEST, 

Member of Congress; Member of Congress; 


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396 

Hon. BRADLEY BYRNE, Hon. RANDY K. WEBER, SR., 

Member of Congress; Member of Congress; 

Hon. STEVE KING, Hon. PAUL A. GOSAR, 

Member of Congress; Member of Congress; 

Hon. BRUCE WESTERMAN, Hon. ROBERT B. ADERHOLT, 

Member of Congress; Member of Congress; 

Hon. TED S. YOHO, Hon. LANCE GOODEN, 

Member of Congress; Member of Congress; 

Hon. GLENN GROTHMAN, Hon. FRANCIS ROONEY, 

Member of Congress; Member of Congress; 

Hon. W. GREGORY STEUBE, Hon. DANIEL MEUSER, 

Member of Congress; Member of Congress; 

Hon. BILL JOHNSON, Hon. BARRY LOUDERMILK, 

Member of Congress; Member of Congress; 


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397 

Hon. RON ESTES, Hon. MARK E. GREEN, 

Member of Congress; Member of Congress; 

Hon. JACKIE WALORSKI, Hon. VICKY HARTZLER, 

Member of Congress; Member of Congress; 

Hon. MARK WALKER, Hon. JOHN R. MOOLENAAR, 

Member of Congress; Member of Congress; 

Hon. JACK BERGMAN, Hon. CAROL D. MILLER, 

Member of Congress; Member of Congress; 

Hon. DAVID ROUZER, Hon. JIM HAGEDORN, 

Member of Congress; Member of Congress; 

Hon. BEN CLINE, Hon. WARREN DAVIDSON, 

Member of Congress; Member of Congress; 

Hon. STEVE CHABOT, Hon. ANTHONY GONZALEZ, 

Member of Congress; Member of Congress; 

Hon. PAUL MITCHELL, Hon. GARRET GRAVES, 

Member of Congress; Member of Congress; 


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Hon. GUY RESCHENTHALER, Hon. MICHAEL CLOUD, 

Member of Congress; Member of Congress; 

SUBMITTED QUESTIONS

Questions Submitted by Hon. Dusty Johnson, a Representative in Congress 

from South Dakota 

Response from Karen Cunnyngham, Associate Director, Mathematica Policy Research 

Question 1. Ms. Cunnyngham, does your analysis investigate the potential positive income, reduction in poverty, and overall quality of life improvement for individuals who newly obtain employment because of the rule change? If so, is this 

available as a supplement to your previously released analysis? 

Answer. My analysis relies on objective, rigorously derived estimates of the effects 

of changes to SNAP, and unfortunately, such data pertaining to people who newly 

gain employment as a result of changing ABAWD work requirements is not available. As such, my analysis does not address this issue directly. But these are important questions, and research on quality-of-life improvement using rigorously collected evidence would be an important contribution to the policy discussion. 

Question 2. Ms. Cunnyngham, your written testimony mentioned that access to 

a good SNAP employment and training program could help SNAP participants meet 

the work requirements. The 2018 Farm Bill clarified the programs that can count 

for meeting SNAP E&T. What estimates have you (or others) done on SNAP participants’ access to all types of E&T programs, and on the overall ability of those programs to help participants comply with any changes in the SNAP waiver rules? 

Answer. Under a contract for the U.S. Department of Agriculture, Mathematica 

is currently testing innovative strategies to increase employment and earnings 

among SNAP participants and reduce their dependence on SNAP and other public 

assistance programs. This study was mandated in the 2014 Farm Bill, which authorized grants for up to ten pilots (or demonstration projects). The ten pilots offer 

diverse services and target different groups of SNAP participants in various geographic locations. Mathematica’s random assignment impact analysis will give policymakers insight into effective strategies for increasing employment and earnings; 

decreasing public assistance; and positively influencing other outcomes of interest, 

including food security, health, and housing. The impact analysis will also help us 

understand whether any of these outcomes vary for different types of SNAP participants. In addition, the evaluation includes the following: (1) an implementation 

analysis that will document the operation of each pilot and provide context for interpreting and understanding observed impact both within and across pilots; (2) a participation analysis that will examine the characteristics and service paths of pilot 

participants and control group members and determine whether the pilots, the services they offer, and the requirements they impose affect individuals’ decisions about 

whether to apply for SNAP; and (3) a cost-benefit analysis that will estimate the 

return on each dollar invested in providing E&T services. Interim study findings are 

set to be released in late 2019, and we would be happy to provide your office a copy 

of our findings. 

On the question of what access participants have to SNAP E&T services, 

Mathematica studied the characteristics of SNAP E&T several years ago. This was 

a nationally representative study of E&T participants and providers that documented the services available and received. The full report, with an executive summary, can is available at https://fns-prod.azureedge.net/sites/default/files/ops/ 

SNAPEandTCharacteristics.pdf. 

Question 3. Ms. Cunnyngham, did the estimates of the number of individuals affected by the proposed ABAWD rule changes or any of your estimates attempt to 

differentiate the reasons an individual might be impacted? 

Answer. Drilling down on individual motivations, behavioral insights, or other 

reasons individuals might or might not be impacted by the proposed rule change is 

not possible with the data we used for our analysis. Currently, we can only speak 

to the circumstances, not the ‘‘why’’ behind the circumstances. Additional data, however, possibly provided at the state and local levels, could help explain why. 


11602110.eps
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1https://www.law.cornell.edu/cfr/text/7/subtitle-B/chapter-II/subchapter-C. 2https://www.law.cornell.edu/uscode/text/7/2015. 3https://fns-prod.azureedge.net/sites/default/files/snap/FY16-State-Activity-Report.pdf. 

Response from Sam Adolphsen, Vice President of Executive Affairs, Foundation for 

Government Accountability 

Question 1. Mr. Adolphsen, how is one declared able-bodied? Can you provide various state examples of the eligibility process that determines such a classification? 

Answer. The term ‘‘able-bodied’’ in relation to the Supplemental Nutrition Assistance Program (SNAP), or food stamps, is a term found in Federal Food Stamp regulations at 7 CFR, Subchapter C.1 The relevant portion of food stamp law, U.S. Code 

Title 7, Chapter 51, and Section 2015, contains a work requirement for able-bodied 

adults on the program and defines those individuals as between ages 15 and 60 who 

are ‘‘physically and mentally fit.’’ 2

During the eligibility process for receipt of the food stamp benefit, a state worker 

from the administering agency will use the application process to determine if the 

applicant is in fact an able-bodied adult subject to the work requirement in Section 

2015. They will further determine if they are an Able-Bodied Adult Without Dependents (ABAWD) subject to a separate requirement in Section 2015(o). In either 

case, the applicant or participant can demonstrate they are unable to meet the requirement through a note from a doctor or social worker at any point. Recent guidance from Food and Nutrition Services has also allowed eligibility workers to make 

this determination of unfitness in certain extreme cases. 

Question 2. Florida is one of many states focused on work-oriented reforms, and 

a new report shows the incredible impact they’re having on the state. Since the 

state implemented a food stamp work requirement in 2016, nearly 94 percent of 

able-bodied, childless adults have left Florida’s food stamp program. Those who left 

the program found work in over 1,104 industries—in nearly every corner of Florida’s 

economy. Even better, 70 percent of those who initially found work in the fast food 

industry or at a temp agency left those industries within 1 year. Work requirements 

aren’t just helping people climb out of dependency in Florida—they’re helping them 

climb the economic ladder to better opportunities and bigger paychecks. Mr. 

Adolphsen, how can we replicate this in other states who may find it difficult or 

not cost-efficient to enforce work requirements and engage recipients? 

Answer. The results of work requirements for ABAWDs in the food stamp program in Florida were outstanding, as noted in the question. However, we know this 

is impact is not isolated only to Florida. Both Kansas and Maine implemented the 

same work requirement in 2014, and in subsequent studies, each of those states 

found results similar to Florida—incomes of those former participants in the program more than doubled in just 1 year. Furthermore, Kansas and Maine did not 

report any additional administrative burden or cost as a result of implementing the 

work requirement. In all three states, enrollment in the program dropped significantly as a result of the reform, and since most administrative costs are driven by 

caseloads, there is strong evidence to believe this type of reform can actually drive 

down administration burden. 

In fact, California, which has not implemented the work requirement for 

ABAWDs in almost the entire state, has the second highest administrative cost per 

case in the country at $68.52 per case, per month. That is more than double the 

national average of $29.98. Meanwhile Florida’s cost per case, per month is the lowest in the nation.3

Additionally, most states’ systems are already set up to handle the ABAWD work 

requirement, since it has been a part of food stamp law since 1996, and until the 

mid-2000s, most states were enforcing the requirement in at least part of their 

state. This means that most states simply have to turn that feature back on within 

their computer systems. While there are significant Employment and Training funds 

available to states to assist ABAWDs with work activities or training, there is no 

required number of ‘‘slots’’ that must be funded or staffed, so states have flexibility 

in this area, ensuring that it is not a legitimate obstacle to re-instating the requirement. 

Question 3. Mr. Adolphsen, we know the Foundation for Government Accountability has written on these waiver abuses and the proposed rulemaking. Your written testimony stated this proposed rule would help address waiver abuse. Do you 

have additional recommendations to the Department’s solution? 

Answer. The proposed rulemaking is essential to ensuring that waivers are no 

longer abused. However, the rulemaking leaves in place some key loopholes that 

could easily be exploited by states that are more focused on keeping people on food 

400 

stamps than helping them get back to work. To ensure that this gaming of the system cannot take place, the rule should be adjusted in several key ways. 

The proposed rule will still allow for the combining of certain areas for the purposes of applying for a waiver. This could mean that some counties, for example, 

with low unemployment, can still be grouped with higher-unemployment counties in 

a way that would result in both receiving a waiver, even though the lower unemployment county would not qualify on its own. The rule should require each individual area, county, or city, to qualify on its own without combination with a separate area. 

Making sure that areas that are within commuting distance of available jobs do 

not qualify for a waiver could strengthen the rule further. The USDA has defined 

certain ‘‘commuting zones’’ that more accurately capture the commuting patterns 

within the country. The rule should require that, even if a county qualifies itself 

for a waiver, if the area is within commuting distance to available jobs in another 

county, it should not receive a waiver. 

The rule could also be strengthened by using a ten percent unemployment rate 

as the floor for any waiver. Congress very clearly set ten percent unemployment as 

the chosen mark for approval of the waivers in the original work requirement law, 

and it would return the waivers to their original intent of being employed only in 

truly economically disadvantaged areas. 

There are three final changes that could improve the rule: 

• First, current regulations exempt from the work requirement ABAWDs who reside in a household with a sibling under 18. The intent of the law is to exempt 

caretakers or parents of children under 18, not anyone who resides in the 

household. This loophole should be closed in this rule. 

• Second, regulations currently exempt 50 year olds from the work requirement. 

The law exempts those individuals ‘‘over 50 years old’’ but regulations exempt 

anyone over 49 years old. The Office of Inspector General has recommended this 

be fixed, and it should be changed in this rule. 

• Third, regulation includes language that ‘‘requires’’ the Secretary of USDA to 

approve ABAWD work requirement waivers when certain criteria are met. However, the law states only that the Secretary ‘‘may’’ approve waivers in these 

cases. The rule should return this discretion to the Secretary as Congress intended. 

Question 4. The 2018 Farm Bill allows states to exempt up to 12% of their 

ABAWDs, per month, for myriad reasons. How can states more effectively use this 

allowance to capture the appropriate exceptions, as opposed to waiving larger areas 

and more people from the work requirement? 

Answer. The use of this particular exemption is often ignored in the discussion 

about the larger geographic waivers. Although some proponents of the current waiver structure treat the new rule as if it will eliminate waivers altogether, it will not. 

The rule would simply move the standards for qualifying back towards Congressional intent of approving them only in economically-disadvantaged areas. 

Further, even taken to the extreme and assuming there are No geographic waivers, states still have the option to exempt 12 percent of their ABAWD caseload. This 

presents states with a much more targeted opportunity to exempt individuals from 

the work requirement when there is a true need to do so. A prime advantage of this 

for states is that there is no requirement to complete the administrative process or 

management of a geographic waiver. The state can simply deploy these exemptions 

as they deem necessary. 

A good example of how these 12 percent exemptions might be used is in the case 

of major and sudden job loss in the state. For example, if a large employer decides 

to suddenly leave town, the state may use these exemptions for the specific people 

impacted by layoffs. This allows for rapid response and individual targeting, instead 

of the heavy handed and administratively burdensome geographic waiver approach. 

Question 5. The House-passed farm bill included language that would have mandated the collection of integral data related to SNAP households. Data collection had 

long been a focus of the hearing series, with many bipartisan witnesses stating that 

there is a reality in SNAP: limited data. This data collection would have debunked 

claims about recipient households and would have informed future policy based on 

facts rather than (tiny) sample-based assumptions. As an example, most assumptions are based on a survey of 1⁄4 of one percent of SNAP households (52,000 households of 20.8 million). Per The Center on Budget and Policy Priorities, this provision 

was seen as one that ‘‘unnecessarily puts personal information for tens of millions 

of Americans at risk.’’ Mr. Adolphsen, did FGA support this data collection? Would 

it have mitigated the concerns that there is no data on ABAWDs? 

401 

Answer. FGA does support the collection of better data to ensure proper evaluation and management of the program. For example, several witnesses at the recent 

hearing on ABAWDs were relying heavily on extrapolations of survey data to promote their viewpoint. Our research has tracked the actual experiences of more than 

500,000 individuals, following their progress from welfare to work, and looking at 

each person’s actual increase in income. 

While there could be better data collection, the assertion put forth that we ‘‘do 

not know who these ABAWDs are’’ is also not entirely accurate. We have enough 

data available to know that ABAWDs are mostly male, mostly young, and most are 

not working at all. We know for sure that they are not part-time or full-time students, and we know that they are not working in the seven million available jobs. 

We know this in particular because if an ABAWD works even in a minimum wage 

job full-time, they will be out of poverty and off of welfare. Improved data will help 

all interested parties better analyze this important program. 

Response from Lisa Hamler-Fugitt, Executive Director, Ohio Association of 

Foodbanks 

Dear Honorable Dusty Johnson, Ranking Minority Member: 

Thank you for your time and interest in the Ohio Association of Foodbanks SNAP 

Work Experience Program that serves only work-mandated recipients who are considered unemployed and underemployed Able-Bodied Adults without Dependents in 

Franklin County, Ohio. It is my pleasure to provide you with our responses to the 

questions I received from Jennifer Yezak, via email on April 17, 2019. 

Question 1. Ms. Hamler-Fugitt, your written testimony mentions the myriad ‘‘selfreported’’ issues individuals categorized as ‘‘able-bodied’’ disclose. At what point in 

this assessment do you engage with medical service providers to either support or 

dispute such claims? What is the process once you engage with those medical service providers? 

Answer. When a SNAP work-mandated recipient states during their assessment 

that they have a disability and/or limitation, and the County SNAP Caseworker did 

not document the disability, the Association’s Work Assessment Specialist directs 

the SNAP recipient to go back to their County SNAP Caseworker to secure the 

‘‘Franklin County ABAWD Employability Form’’ (attached). The SNAP recipient is 

then required to locate a doctor or medical professional to complete the form on 

their behalf. 

The Association’s Work Assessment Specialist encourages the SNAP recipient to 

apply for Medicaid, if they are without health care coverage, and provides them with 

a list of free medical clinics if they don’t currently have a doctor. It is the responsibility of the SNAP recipient to locate and secure the medical service provider that 

will assess and document their medical condition and who is willing to complete the 

form, documenting the recipient’s inability to work. It is becoming more difficult to 

locate medical professionals who are willing to complete these assessments and complete the paper work for free. We have had a number of SNAP recipients report that 

the local medical providers are charging $20 to complete the form in addition to the 

cost of an office visit. 

These costs are prohibitive for an unemployed SNAP recipient that has no income 

and is not covered by health insurance. 

Question 2. Ms. Hamler-Fugitt, your testimony presents a variety of circumstances that should void ABAWDs from work, and four reasons to withdraw the 

proposed rule. USDA made it a point—multiple times—to ask for additional feedback in both the ANPRM and the NPRM. Do you have suggestions that can be handled via rulemaking as to how to hold states accountable, engage ABAWDs in the 

labor force, and work to move individuals to personal autonomy? 

Answer. USDA does not mandate that states provide SNAP work-mandated recipients with education, training, Work Force Investment Act, SNAP Employment 

and Training or any workforce supports. The Franklin County Department of Job 

and Family Services (FC[D]JFS) contracts with the Association to provide these 

services to SNAP work-mandated recipients who reside in Franklin County, Ohio. 

The Ohio Association of Foodbanks supports work by providing assignments and 

placements at over 50 nonprofit and faith-based organizations to help recipients 

meet their work requirements when they are unable to secure paid employment or 

a slot to participate in a qualifying education and training program. 

In our experience there is significant evidence that restricting time limit waivers 

increases the direct cost to the state and county agencies, places an additional administrative burden on the SNAP recipients, and likely decreases the number of 

families who are able to get the food assistance they need. In fact, without additional funding from Congress, this rule is a significant unfunded mandate on state 

402 

* The document entitled, Ohio Association of Foodbanks: Annual Report 2018, is retained in 

Committee file. 

and local governments. Programs with lower administrative burdens reach more eligible people than programs that make participants jump through hoops to get help 

meeting their basic needs. 

The proposed rule change would make it harder for states to obtain and implement area waivers by dropping statewide waivers except when a state triggers extended benefits under unemployment insurance. It would unduly limit the economic 

factors considered in assessing an area’s eligibility for a waiver (e.g., by no longer 

allowing employment to population ratios that demonstrate economic weakness to 

qualify areas for waivers). It would undermine efficient state implementation of area 

waivers by limiting their duration to 12 months and delaying their start dates until 

after USDA processes the request. In addition, the proposed rule would remove 

states’ ability to use exemptions accumulated prior to the rule’s implementation as 

well as limit the time states have to use exemptions they receive in the future. 

USDA provides little analysis to explain its conclusions about the impacts the 

changes would have on individuals and population groups nor of realistic plans to 

avert harm from those changes. Instead it merely asserts its expectation that 2⁄3 of 

those individuals made newly subject to the time limit ‘‘would not meet the requirements for failure to engage meaningfully in work or work training.’’ Moreover, while 

USDA concedes that the proposed changes ‘‘have the potential for disparately impacting certain protected groups due to factors affecting rates of employment of 

these groups, it finds that implementation of mitigation strategies and monitoring 

by the Civil Rights Division of FNS will lessen these impacts.’’ But no explanation 

of the mitigation strategies and monitoring is provided, so there is no opportunity 

for us to comment on whether the acknowledged disparate impact will in fact be 

mitigated. 

The time limit proposal goes around Ohio’s Governor and lawmakers and the rest 

of Congress, which just concluded a review and reauthorization of SNAP in the 2018 

Farm Bill and did not make the changes proposed. The rules governing areas’ eligibility for waivers and individual exemptions have been in place for nearly 20 years. 

In that time, the waiver rules have proven to be reasonable, transparent, and manageable for states to operationalize. 

We strongly oppose the proposed rule that would expose even more Ohioans to 

the SNAP food cutoff policy, increase hunger and food insecurity and harm our state 

and community. 

Question 3. Per your website, Feeding America’s mission is to feed America’s hungry through a nationwide network of food banks and to engage the United States 

in the fight to end hunger. Feeding America also ‘‘works hard to protect and promote government programs that help families facing hunger.’’ SNAP is one of those 

programs, which also includes an emphasis on work and self-sufficiency. Feeding 

America has over $2.8 billion in revenues, distributes over $2.7B of that in grants 

and other ‘‘assistance;’’ what is Feeding America doing to promote work, personal 

goals, self-sufficiency, and a lifetime of independence? 

Answer. The Ohio Association of Foodbanks a separate 501(c)(3) and is a partner 

state Association of Feeding America. The Association is unable to respond to this 

question and we have referred it on to Feeding America. 

For additional information about the Ohio Association of Foodbanks, the following 

link is to our 2018 Annual Report, which provides an in-depth account of Ohio’s 

hunger relief network and the programs and partners that drive our mission to provide food and other resources to people in need: http://ohiofoodbanks.org/docs/publications/SFY2018_annual_report.pdf.* 

Question 4. Feeding America’s website states that over 46 million people benefit 

from their services. That’s over 14% of our nation. We have spent decades and trillions of dollars fighting poverty. It is obvious that some, if not all, of the over 80 

social welfare programs are not working. What, in your opinion, has worked? What 

is not working? What are the efficiencies that can be most easily achieved to improve the program in the near term? 

Answer. The Ohio Association of Foodbanks a separate 501(c)(3) and is a partner 

state Association of Feeding America. Our efforts in Ohio fed one in six hunger 

Ohioans last year. 

I appreciate the question of whether there are ways to improve efficiencies in government programs. It is, and has always been, crucial that each tax dollar is spent 

wisely and prudently. While I have thoughts to share, my responses only focus on 

Federal nutrition programs. 

403 

Programs with overlapping purposes or services do not necessarily mean that families are receiving more help than they need. Too often, the programs and supports 

available to families and seniors do not reach them or fail to address the enormous 

problems so many families and individuals face in this economy. This is typically 

because the programs are difficult to access due to confusing rules and requirements 

and because many key services, such as housing, child care, and job training, have 

fixed funding and cannot respond to increased need, particularly during a weak 

economy. When key programs do reach Ohioans, they are a powerful weapon 

against poverty and hardship. We must do more to improve how programs and 

agencies work together to ensure that these programs are accessible to the families 

and individuals they are intended to serve. 

However, there are some real-world realities that I want to highlight. For one, it 

is crucial to recognize that program overlap does not always mean duplication. People who struggle to afford an adequate diet may be better served by different types 

of programs and rarely are the value of benefits provided by any one given program 

sufficient to support the food needs of an individual or family. 

For example, SNAP works, yet the benefits fall far short of what a family requires 

and do not last the whole month. Thus, families that receive SNAP may also turn 

to food banks to fill in the gaps. A recent study found that in Ohio, low-income families continued to be food-insecure despite accessing several food assistance programs. For example, 42% of the households standing in our food lines receiving 

SNAP benefits in the study were at risk of hunger and another 42% had cut back 

on the number or size of their meals. Additionally, among households with children 

ages 0–3 years, 58% participate in the Special Supplemental Nutrition Program for 

Women, Infants, and Children (WIC). Among households with school-age children, 

63% and 55%, respectively, participate in the Federal school lunch and school breakfast programs and 14% participate in the summer food program. 

These benefits are provided to families that ask for help and these families have 

to exert a significant amount of effort in order to access and maintain these benefits. 

So, it is crucial that we recognize that the food assistance programs that we already 

have do not provide enough to meet all the nutritional needs of families. 

A simple recommendation is that Congress increase the SNAP benefit to the lowcost and moderate food program. In addition, automatically enroll low-income seniors, persons with disabilities, and families with children into the SNAP program. 

The fact that food insecurity (or risk of hunger) remains at a high level confirms 

that too few, not too many, resources are being made available for the families that 

need them. 

That said, I recommend that Congress enact policies that simplify and streamline 

eligibility rules so that families who participate in one program can be easily enrolled into all the other low-income programs for which they are eligible. For example, states and school districts have been working to cut red tape and streamline 

enrollment into the school lunch program by automatically enrolling children from 

families receiving SNAP and TANF through a process known as direct certification. 

Children in households receiving SNAP benefits are eligible for free school meals 

and school districts are required to work with the SNAP administrators to enroll 

them automatically, using the direct certification process noted above. Parents who 

have already completed a lengthy and detailed SNAP application should not have 

to complete another application; schools should not have to process unnecessary paperwork. 

This same method of simplifying and streamlining eligibility should apply to lowincome seniors on Social Security who are receiving assistance and extra help with 

Medicaid part D. A hungry senior is not a healthy senior and I recommend that 

Congress enact policies that would allow states to auto-enroll seniors on low, fixed 

incomes into the SNAP and Commodity Supplemental food Programs, without requiring these seniors to complete multiple applications for critical food assistance. 

Recommendations: 

• Congress should facilitate the ability for states to integrate streamlined enrollment of eligible people across several key programs: SSI/SSDI, Medicaid, Medicare and Domestic Food Programs. This could be supported by allowing for data 

sharing and interconnected data systems and providing the Social Security Administration with the ability and mandate to directly enroll low-income seniors 

and person with disabilities in all Federal nutrition programs for which they 

are eligible. 

• Recipients of Unemployment Compensation should be notified about Federal 

employment and training programs that are available to them for additional 

education to enhance their skills. 

404 

• The United States Department of Agriculture should require states to provide 

a comprehensive plan for how they will ensure that eligible individuals will be 

enrolled in all domestic food programs rather than individual, program-specific 

efforts. In support of that effort, USDA could provide information to states and 

localities about how best to cross-leverage their outreach efforts. 

• The Federal Government should measure states’ success with enrolling eligible 

individuals in a core package of programs, such as SNAP, Medicaid, and school 

meals, rather than assess participation by individual programs. Agencies could 

establish a national standard for multi-benefit application assistance programs 

and create incentives and funding to maximize participation by eligible low-income families and individuals in income-enhancing programs. States and local 

governments that create seamless enrollment systems to connect those most in 

need to available supports should be recognized and rewarded. Their best practices could be promoted in other locations. 

• Expand efforts and resolve to strengthen and create interdepartmental coordination, universal application, single agency consolidation and facilitate streamlining of public benefits, eligibility and applications processes. These efforts will 

free up administrative funding that can be directed to increasing benefits levels 

and support expansion of eligibility standards. 

Question 5. USDA provided Regional Directors with a memorandum on November 

19, 2015 that explicitly speaks to how states can better assess an individual’s fitness 

for work ‘‘methodically and comprehensively.’’ The memorandum goes on to say that 

Federal rules (CFR 273.24) allow states this flexibility to prevent placing unnecessary burden on individuals who are clearly unfit for employment. Ms. HamlerFugitt, where do you see the breakdown in this process? 

Answer. CFR 273.24 pertains to General eligibility guidelines to states, and in my 

experience, states err on the side of more rules, not less when defining their policies. 

In addition, there is no Congressional oversight, no Federal funding, no administrative oversight, no national standards and no penalties on states that refuse and fail 

to comply with this Federal rule. Might I recommend that Congress request a GAO 

report be completed on how states have or have not implemented CFR 273.24. Another Congressional action that may be warranted is a review and report by state 

on the number of work, training, and work fair slots and programs are operating 

in each county in every state. This would provide Congress with baseline information about the capacity or lack thereof to provide these program services to SNAP 

recipients that are subject to the time limits. 

In closing, food insecurity remains at very high levels, which confirms that too 

few, not too many resources are being made available to struggling families who 

desperately need them. SNAP is one of the MOST efficient ‘‘welfare’’ programs out 

there. Tens of millions of the people served in emergency hunger relief are not eligible for ‘‘social welfare programs’’ and not considered to be ‘‘living in poverty’’ under 

Federal guidelines, yet nonetheless they can’t afford to put food on the table. These 

are merely nutrition programs. SNAP should continue to exist because proper nutrition is critical to the healthy livelihoods of every person. Other programs should address employability separately. SNAP is not a jobs program. It is not funded as a 

jobs program. 

Thank you again for the opportunity to testify and I would be pleased to respond 

to any additional questions that you might have. I can be reached either my email 

at Redacted or my telephone at Redacted. 

Best regards, 

LISA HAMLER-FUGITT, 

Executive Director. 


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ATTACHMENT

Response from Jay C. Shambaugh, Ph.D., Director, The Hamilton Project, and Senior Fellow, Economic Studies, Brookings Institution; Professor of Economics, 

George Washington University 

Dear Representative Johnson, 

Thank you for the questions regarding my testimony. I appreciate your interest 

in this important topic and welcome the opportunity to share thoughts on these 

issues. I answer the questions below. 

Best regards, 

JAY SHAMBAUGH. 

Question 1. Mr. Shambaugh, if the Administration were loosening the ability of 

states to receive waivers, or relaxing the data criteria that should be used, would 

you have concerns about whether it is within the purview of the Administration to 

make changes to ABAWD waiver regulations? Is there any evidence that this Administration’s interpretation of the phrasing of the Food and Nutrition Act of 2008 

of ‘‘does not have a sufficient number of jobs to provide employment for the individVerDate Aug 31 2005 11:16 Jun 14, 2019 Jkt 041481 PO 00000 Frm 00411 Fmt 6621 Sfmt 6621 P:\DOCS\116-02\36188.TXT BRIAN

11602113.eps
406 

uals’’ is inappropriate and not within an allowable range of possible regulatory interpretations? 

Answer. Given that SNAP is a highly effective automatic stabilizer, proposals that 

change the conditions by which economically distressed places become eligible for 

work requirement waivers should be held to the highest evidentiary standards. The 

concerns expressed in my testimony did not relate to USDA’s jurisdiction or purview 

to implement regulatory changes, as such matters span beyond my research and 

academic expertise. What my testimony did, however, discuss in detail was the lack 

of evidence supporting the change. The U.S. Department of Agriculture’s (USDA) 

Proposed Rule does not meet an evidentiary standard and would weaken SNAP’s 

responsiveness to an economic downturn without increasing labor force participation 

rates. The USDA and its Regulatory Impact Analysis (RIA) fail to fully consider the 

costs and benefits of the proposed rule, including the costs and benefits under alternative economic conditions. 

The USDA and the RIA do not consider the benefits to program participation for 

individuals nor SNAP’s role as an automatic stabilizer when weighing proposed 

changes. The rule is likely to push a considerable number of current beneficiaries 

who are either in the labor market or unable to work off the SNAP rolls while failing to expand for newly eligible participants at the onset of a recession. It does so 

absent evidence that labor force attachment among ABAWDs would increase as a 

result of this proposal even in a strong economy and without consideration to the 

costs both for individuals and the economy in any circumstance. Given the importance of SNAP in a recession, it seems impossible to change how waivers work without considering the effects of the policy change under a range of economic circumstances. The proposed rule and the RIA do not factor in such considerations. 

Question 2. Mr. Shambaugh, your written testimony states that the vast majority 

of ABAWDs are in the labor force. The recently released Characteristics of SNAP 

Households shows that just over 31% of ABAWDs have any countable earned income, meaning less than 32% work. Why the discrepancy? Even if the majority of 

ABAWDs work at some point, if the majority are not working while on SNAP than 

at any given point in time, it seems that the majority are not working, correct? 

Answer. Because states are not required to provide precise numbers on ABAWDs, 

the administrative data reports are also not precise. The Characteristics of SNAP 

Households Table 3.3 from which the 31 percent number is taken is for ‘‘Adults age 

18 to 49 without disabilities in childless households.’’ ABAWDs are a subset of this 

larger group, as some in this group have been identified as not being an ABAWD 

by the eligibility caseworker or Quality Control reviewer. When President Trump’s 

White House Council of Economic Advisors used the Quality Control data to look 

at the average monthly employment rate, which is lower than the rate of those in 

the labor force because it does not consider those seeking work, they found that 38 

percent were working in a given month in 2017 (Economic Report of the President, 

March 2019, p. 464). 

More importantly, these monthly snapshots do not capture the full picture of labor 

force engagement of those on SNAP. As our work has shown, the monthly snapshot 

provides an incomplete picture due to the volatility of the low wage labor market. 

In fact, when looking at an extended period, we have found that 75 percent of 

18–49 year old adults without dependents and without disability income who are 

SNAP beneficiaries are in the labor force at some point over a 2 year period. Using 

the same method with a slightly different sample (18 to 64 year olds as opposed 

to 18 to 49 year olds), The 2019 Economic Report of the President found that about 

70 percent of those who were non-disabled working-age SNAP recipients in December 2013 worked at some point from January 2013 to December 2014 (p. 463). 

As noted in our research, the majority of those not working in a given month who 

do work at other times are not working because of ‘‘work-related reasons’’ such as 

problems finding hours, the loss of a job, closure of an employer, etc. These people 

are trying to work. They may not have income every month, but they are actively 

engaged in the labor force. 

Question 3. According to the American Enterprise Institute, many scholars and 

public policy professionals are moving away from using survey data to inform policy. 

AEI continues to say that these individuals cite a lack of reliability and the importance of comparing self-reported data to administrative data. Mr. Shambaugh, what 

do you envision as the best data to capture the information discussed at the hearing? 

Answer. There is value in both administrative data and surveys. Surveys are a 

critical tool to complement administrative data sources and are vital to providing 

valid evidence for the policy debate. In particular, surveys can provide evidence 

about why people are behaving as they are, what keeps them from working, what 

407 

* The document entitled, ‘‘In Order That They Might Rest Their Arguments on Facts’’: The 

Vital Role of Government-Collected Data, is retained in Committee file. 

their health status is, among many other crucial pieces of information. As we have 

said, the data that we have used to analyze policy issues regarding work requirements have also been employed by the White House Council of Economic Advisors 

in its most recent Economic Report to the President. 

While data is a critical input, research design is more so. Research conducted this 

year by Jeehoon Han (University of Chicago) and Timothy Harris (Illinois State 

University for the W.E. Upjohn Institute for Employment Research) used administrative data, survey data, and a quasi-experimental research design to identify the 

effect of SNAP work requirement waivers on caseload levels and employment outcomes. Han finds no negative effect of place-based work requirement waivers on employment and no positive effect of the reimposition of work requirements on employment. These findings are consistent with work requirements having no effects on 

employment. Harris typically finds an extremely small (less than one percent) but 

statistically significant impact of work requirements on employment, but even the 

most generous specifications find the number incentivized to work is far smaller 

than those removed from the program. Crucially, they compare those facing work 

requirements to those who do not, giving a valid comparison of treatment and control groups. 

By contrast, we urge policymakers to be cautious in their review of published research using administrative data that does not employ a research design for causal 

inference. These studies, including one referenced repeatedly during the Subcommittee’s April 3 hearing, do not identify treatment and control groups, incorrectly sample the study population, and do not account for factors that would otherwise explain their findings like work history before and while on the program. Because they 

fail to design their studies correctly, the administrative data employed cannot answer the research question asked. 

In [addition] to using administrative data and survey data in our research, The 

Hamilton Project has produced evidence in support of the Federal statistical agencies role in collecting data that supports economic growth and evidence-based policy. 

In a March 2017 report published jointly by the American Enterprise Institute and 

The Hamilton Project, the organizations supported government-collected data, including surveys. In particular, this report notes that research based on surveys is 

used not only by researchers, but by private businesses (see Chapter 1: Businesses). 

The report can be found at: http://www.aei.org/publication/in-order-that-theymight-rest-their-arguments-on-facts-the-vital-role-of-government-collected-data/.* 

Question 4. Mr. Shambaugh, as an economist you understand the difficulties in 

compiling longitudinal data on ABAWDs that would provide improved information 

on the status and situation that contribute to ABAWDs enrolling in and staying enrolled in SNAP? What can USDA do right now that would provide policymakers, 

states, and nonprofits serving the ABAWD population with even better information 

on what this group needs to receive the services they need and obtain employment 

if possible? 

Answer. I agree that in order to better understand the needs of the ABAWD population and to improve their labor market outcomes, longitudinal data that includes 

demographic, casework, and employment information on ABAWDs would provide 

improved descriptive information for oversight and policymaking. For example, identifying volatility as a key feature of the low-wage labor market and the longer-term 

outcomes for those who failed to meet a work requirement can only be done with 

longitudinal data. 

At present, using available information to better describe who ABAWDs are and 

addressing screening procedures to limit exposure to work requirements only to 

those who the law feels should face a work requirement are the best first steps. 

There should be improved screening mechanisms for disability and individual barriers to work. States have used individual exemptions to shield a variety of vulnerable populations from work requirements, such as victims of domestic abuse, veterans, and those who have aged out of the foster care system. This could be done 

more systematically with point-in-time information. 

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