Use of Unemployment Insurance and Employment Services

by Newly Unemployed Leavers from

Temporary Assistance for Needy Families

Final Report

USDOL Grant Agreement #: MI-17622-09-60-A-26

Submitted by:

Christopher J. O’Leary and Kenneth J. Kline

W.E. Upjohn Institute for Employment Research

300 South Westnedge Avenue

Kalamazoo, MI 49007

Tel: 269-343-5541

Fax: 269-343-3308

oleary@upjohn.org

Submitted to:

U.S. Department of Labor 

Employment and Training Administration

Wayne Gordon, Project Officer

Gordon.Wayne@dol.gov

December 2009

iii

PREFACE

This study examines participation in Unemployment Insurance (UI) and Employment 

Services (ES) by adults who received cash welfare benefits through Temporary Assistance for 

Needy Families (TANF). Among those who leave TANF for employment, we measure the rates 

of subsequent unemployment, application for UI, eligibility for and receipt of UI benefits, and 

the use of Wagner-Peyser funded ES. We also investigate the correlations between UI and ES 

services receipt with reemployment and future independence from TANF. The analysis is based 

on person-level administrative program records from four of the nine most populated states 

between 1997 and 2003. Evidence suggests that three-quarters of new TANF leavers experience 

unemployment within three years, and one-quarter of the newly unemployed apply for UI 

benefits. About 87 percent of UI applicants have sufficient prior earnings to qualify for benefits. 

However, only about 44 percent qualify based on their job separation reasons. Among UI 

applicants, TANF leavers had much higher rates of voluntary quits and employer dismissals than 

did non-TANF leavers. Nonetheless, 50 percent of TANF leavers who apply for UI ultimately 

receive benefits. Public employment services (ES) are used by one-quarter of newly 

unemployed TANF leavers. Among UI applicants more than three-quarters use the ES whether 

they receive UI benefits or not, while 14 percent of newly unemployed TANF leavers who do 

not apply for UI choose to use ES services. Among TANF leavers who become unemployed and 

apply for UI, the rate of return to TANF is lower for those who receive UI benefits. Rates of 

return to TANF are highest among non-beneficiary UI applicants, and non-UI applicants with 

low recent earnings. A characteristics analysis of these groups provides a guide for targeting job 

retention and advancement services to TANF leavers.
iv
v

ACKNOWLEDGMENTS

This report presents results of research based on administrative data from multiple 

programs in the states of Florida, Georgia, Michigan, and Ohio. We thank all the people and 

organizations who contributed to this project. Some deserve particular recognition, because 

without them this research would not have been possible.

At the U.S. Department of Labor (USDOL), the Honorable Brent R. Orrell, Acting 

Assistant Secretary for Employment and Training, raised the essential research questions and 

supported this project. Also at USDOL, in the Employment and Training Administration’s 

Office of Policy Development and Research, we thank Heidi Casta, Director of the Office of 

Research and Evaluations, Wayne Gordon, grant manager, and Jonathan Simonetta, project 

manager of the Administrative Data Analysis and Research (ADARE) consortium. Wayne 

provided insightful and timely guidance throughout the course of the project. Jonathan 

facilitated acquisition of the necessary administrative data for this project along with David 

Stevens of the University of Baltimore, Jacob France Institute who organized the ADARE 

consortium of state agencies and researchers. Also at USDOL we thank Robert Pavosevich, 

Mike Miller, David Balducchi, and Stephen Wandner for their support and useful suggestions.

Florida UI and TANF data were provided under an ADARE data-sharing agreement by 

Jay Pfeiffer and Andre Smith of the Florida Department of Education, Florida Education and 

Training Placement Information Program (FETPIP). 

Mary Dean Harvey, director of the Georgia Department of Human Resources (DHR), 

Division of Family and Children, took an interest in this project and authorized O’Dell 

Covington of the DHR to arrange for sharing of TANF administrative records. At Georgia State 

University, Lakshmi Pandey prepared TANF files for transfer to the Upjohn Institute. Use of 

Georgia UI data was authorized by Robert Thomas, Assistant Commissioner for Unemployment 

Insurance in the Georgia Department of Labor. 

Michigan participation in the project was endorsed by Liza Estlund Olson of the UI 

Agency in the Michigan Department of Labor and Economic Growth (DLEG) and Marianne 

Udow of the Michigan Department of Human Services (DHS). At DLEG, Joe Billig and Dell 

Alston organized participation in the project. TANF data were provided by Bruce Grant under 

contract with the Michigan DHS, and UI data were provided by Sandy Damesworth and Shirley 

Heaslip of the Michigan UI Agency. Before delivery to the Upjohn Institute, files were merged 

by Howard Boyer and Cheryl Thoms of DLEG. 

Ohio UI data availability was arranged by Dixie Sommers, who is now associate 

commissioner for Occupational Statistics and Employment Projections at the Bureau of Labor 

Statistics, USDOL. While Dixie was a member of the ADARE steering committee and on the 

staff at the Center for Human Resource Research, Ohio State University, she along with center 

director Randy Olson established a data-sharing agreement for access to Ohio UI administrative 

records. Dixie supported efforts to acquire additional UI data from the Ohio Department of Job 

and Family Services (ODJFS). At ODJFS, agreements for UI data-sharing and delivery were 
vi

facilitated by Michael McCreight, Fran Hersh, Vickie Maddux, and Jason Turner; agreements for 

TANF data sharing and delivery were arranged by Mary Lou Owens. 

At the Upjohn Institute we thank Randy Eberts for his support in all phases of the project 

including design, analysis, and delivery of the final products. Randy also helped negotiate 

acquisition of data essential for doing the work. Institute editor, Ben Jones, professional edited 

this manuscript. Special thanks go to Claire Black for administrative and clerical support. Claire 

expertly assembled and reviewed all deliverables. 

This project extends our earlier research done for the U.S. Department of Health and 

Human Services (HHS). Several policy scholars at HHS helped build the foundation for this 

work. In particular we thank Reuben Snipper, Susan Hauan, Laura Chadwick, and Don 

Oellerich for their interest and useful suggestions. Former HHS researchers Kelleen Kaye and 

Julia Isaacs helped launch us on this line of inquiry. We also thank Daniel Schroeder of the Ray 

Marshall Center, University of Texas, who contributed to our recent HHS report. 

In addition to support from USDOL, the W.E. Upjohn Institute for Employment Research 

also financially supported a share of the research on this project. 

Opinions expressed are our own and do not represent the views of the W.E. Upjohn 

Institute for Employment Research or other supporters and contributors to this project. Any 

errors and omissions are our responsibility. 

Christopher J. O’Leary

Kenneth J. Kline

Kalamazoo, Michigan

December 2009
vii

TABLE OF CONTENTS

SECTION Page

Preface............................................................................................................................................iii

Acknowledgments........................................................................................................................... v

List of Tables ............................................................................................................................... viii

List of Figures................................................................................................................................. x

Executive Summary....................................................................................................................... xi

1. INTRODUCTION ..................................................................................................................... 1

2. BACKGROUND ....................................................................................................................... 3

2.1 UI Eligibility and Benefits................................................................................................... 3

2.2 TANF Eligibility and Benefits............................................................................................. 5

2.3 ES Eligibility and Services .................................................................................................. 7

2.4 Previous Research on Use of UI by TANF Leavers............................................................ 7

2.5 Previous Research on Use of ES by TANF Leavers.......................................................... 11

2.6 TANF Leaver Samples for Analysis.................................................................................. 11

3. USE OF UI BY TANF LEAVERS.......................................................................................... 13

3.1 Unemployment Among TANF Leavers............................................................................. 13

3.2 Applications for UI by Unemployed TANF Leavers ........................................................ 14

3.3 Monetary Eligibility for UI................................................................................................ 20

3.4 Nonmonetary Eligibility for UI ......................................................................................... 25

3.5 Receipt of UI...................................................................................................................... 31

3.6 TANF-Leaver UI Eligibility and Receipt Compared to Others......................................... 36

4. PATTERNS OF SELF-SUFFICIENCY AND TANF DEPENDENCY................................. 43

4.1 Rates of Return to Employment and TANF ...................................................................... 43

4.2 Models of Return to Employment and TANF ................................................................... 47

4.3 Rates of Self-Sufficiency after New Unemployment ........................................................ 52

4.4 Models of Self-Sufficiency after New Unemployment among UI Applicants.................. 55

4.5 Self-Sufficiency of UI Nonapplicants Compared to UI Applicants .................................. 58

5. USE AND EFFECTS OF WAGNER-PEYSER FUNDED EMPLOYMENT SERVICES.... 67

5.1 Use of Employment Services by TANF Leavers in Georgia and Ohio............................. 67

5.2 Employment Services and Self-Sufficiency ...................................................................... 73

5.3 Employment Services, Earnings, and Income ................................................................... 79

6. SUMMARY, CONCLUSIONS, AND EXTENSIONS........................................................... 85

6.1 Summary............................................................................................................................ 85

6.2 Conclusions........................................................................................................................ 92

6.3 Extensions.......................................................................................................................... 93

Appendix A Supplementary Tables............................................................................................. 95

References................................................................................................................................... 177
viii

LIST OF TABLES

Page

E.1 Summary of New Unemployment and UI Application among TANF Leavers.................... xii

E.2 Characteristics Comparisons of Newly Unemployed TANF-Leaver UI Applicants 

and UI Eligibility Groups with Others............................................................................. xiv

E.3 Summary of UI Entitlement, Benefit Receipt, and Exhaustion............................................ xvi

E.4 Return to Employment and TANF by UI Status in the Pooled Four-State Sample ............. xix

E.5 Marginal Effects of Job Referrals (Core) and Job Search Planning (Intensive) 

Services on Return to Employment and TANF among Newly Unemployed 

TANF Leavers in Georgia (GA) and Ohio (OH)........................................................... xxvi

E.6 Effects of Job Interview Referrals on Components of Income for Newly 

Unemployed TANF Leavers by UI Status in Georgia and Ohio.................................. xxvii

2.1 Comparison of State Laws for UI and TANF for Program Year 2000.................................... 4

2.2 Previous Estimates for Welfare Leavers of Percentage Rates for UI Monetary and 

Nonmonetary Eligibility and UI Benefit Receipt ............................................................... 8

2.3 TANF Exit for Employment, Subsequent Unemployment, and UI Application across 

States Based on the First Observed Spell of TANF Receipt, Exit, and New 

Unemployment.................................................................................................................. 12

3.1 Characteristics of Newly Unemployed TANF Leavers by UI Application Status and 

State................................................................................................................................... 16

3.2 State-Specific Linear Probability Models of UI Application among Newly 

Unemployed TANF Leavers............................................................................................. 19

3.3 Pooled Linear Probability Models of UI Application among Newly Unemployed 

TANF Leavers .................................................................................................................. 21

3.4 Summary of UI Application, Eligibility and Benefit Receipt Across States......................... 22

3.5 Characteristic Comparison of Newly Unemployed TANF-Leaver UI Applicants 

Having Monetarily Eligible UI Claims with All Other TANF-Leaver UI Applicants..... 24

3.6 Actual and Simulated Monetary Eligibility by UI Application Status among Newly 

Unemployed TANF Leavers............................................................................................. 25

3.7 Characteristic Comparison of Newly Unemployed TANF-Leaver UI Applicants 

Having Nonmonetarily Eligible UI Claims (acceptable job separations under UI law) 

with All Other TANF-Leaver UI Applicants.................................................................... 27

3.8 Characteristic Comparison of Newly Unemployed TANF-Leaver UI Applicants 

Who Quit Prior Employment with All Other TANF-Leaver UI Applicants.................... 29

3.9 Characteristic Comparison of Newly Unemployed TANF-Leaver UI Applicants 

Discharged from Prior Employment with All Other TANF-Leaver UI Applicants......... 30

3.10 Characteristic Comparison of Newly Unemployed TANF-Leaver UI Applicants 

Who Are UI Beneficiaries with All Other TANF-Leaver UI Applicants......................... 33

3.11 Characteristic Comparison of Newly Unemployed TANF-Leaver UI Beneficiaries 

with Newly Unemployed TANF-Leavers Who Do Not Apply for UI Benefits............... 34

3.12 UI Benefit Entitlement Receipt............................................................................................ 35
List of Tables—Continued

Page

ix

3.13 UI Monetary Eligibility, Nonmonetary Eligibility, and Benefit Receipt Summary 

Comparing Newly Unemployed TANF-Leaver UI Applicants with Other UI 

Applicants Not Recently Involved with TANF ................................................................ 37

3.14 Quit or Discharge Job Separations Resulting in Nonmonetary Ineligibility 

Comparing Newly Unemployed TANF-Leaver UI Applicants with Other UI 

Applicants Not Recently Involved with TANF ................................................................ 39

3.15 Comparison of UI Duration and Exhaustion among Newly Unemployed 

TANF-Leaver UI Beneficiaries with All Other UI Beneficiaries Not Recently 

Involved with TANF......................................................................................................... 41

4.1 Rates of Return to Employment and TANF among Newly Unemployed TANF Leavers 

Using Pooled Data from Florida, Georgia, Michigan, and Ohio...................................... 44

4.2 Linear Probability Models of Return to Employment and TANF with Beneficiary 

Indicators among Newly Unemployed TANF-Leaver UI Applicants Using 

Pooled Data from Florida, Georgia, Michigan, and Ohio................................................. 49

4.3 Effects of UI Benefit Receipt and Exhaustion on Return to Employment and TANF 

among Newly Unemployed TANF-Leaver UI Applicants and UI-Eligible 

Applicants, Using Pooled Data from Florida, Georgia, Michigan, and Ohio................... 51

4.4 TANF-Employment Outcomes Matrix.................................................................................. 52

4.5 Rates of Self-Sufficiency and TANF Dependency among Newly Unemployed TANF 

Leavers Using Pooled Data from Florida, Georgia, Michigan, and Ohio ........................ 54

4.6 Rates of Self-Sufficiency after New Unemployment among UI Applicants......................... 56

4.7 Rates of Self-Sufficiency after New Unemployment among All TANF Leavers................. 59

4.8 Characteristics Comparison of Newly Unemployed TANF Leaver UI Nonapplicants 

and Nonbeneficiary Applicants......................................................................................... 64

5.1 Service Participation among TANF Leavers in Georgia ....................................................... 69

5.2 Service Participation among TANF Leavers in Ohio Using Service Categories 

Introduced into Regression Models.................................................................................. 70

5.3 Marginal Impacts of Employment Services Participation on Return to Employment 

and TANF among Newly Unemployed TANF Leavers in Georgia ................................. 75

5.4 Marginal Impacts of Employment Services Participation on Return to Employment 

and TANF among Newly Unemployed TANF Leavers in Ohio...................................... 76

5.5 Marginal Impacts of Employment Services Participation on Income from Employment, 

TANF, and UI among All Newly Unemployed TANF Leavers in Georgia..................... 80

5.6 Marginal Impacts of Employment Services Participation on Total Income from Wages, 

TANF, and UI among Newly Unemployed TANF Leavers in Georgia........................... 81

5.7 Marginal Impacts of Employment Services Participation on Income from Employment, 

TANF, and UI among All Newly Unemployed TANF Leavers in Ohio.......................... 82

5.8 Marginal Impacts of Employment Services Participation on Total Income from Wages, 

TANF, and UI among Newly Unemployed TANF Leavers in Ohio................................ 83
x

LIST OF FIGURES

Page

E.1 Rates of New Unemployment and UI Application among TANF Leavers..................... xiii

E.2 Rates of UI Monetary Eligibility, Nonmonetary Eligibility, and UI Benefit Receipt ..... xiv

E.3 Shares of UI Entitlement Drawn and UI Exhaustion Rates............................................ xvii

E.4 Rates of Return to Employment and TANF for all Newly Unemployed

TANF Leavers ................................................................................................................ xix

E.5 TANF-Employment Outcomes Matrix ........................................................................... xxi

E.6 Use of Core and Intensive ES Services by UI Status in Georgia and Ohio .................. xxiv

3.1 Rates of New Unemployment among TANF Leavers by State over Time .......................13

3.2 UI Application Rates among Newly Unemployed TANF Leavers 

by State over Time .............................................................................................................14

3.3 Rates of Monetary Eligibility among TANF Leaver UI Applicants 

by State over Time .............................................................................................................23

3.4 Rates of Nonmonetary Eligibility among TANF Leaver UI Applicants,

by State over Time .............................................................................................................26

3.5 UI Beneficiary Rates among TANF Leaver UI Applicants by State over Time ...............32

3.6 UI Monetary Eligibility Rates for TANF Leavers and Non-TANF UI Applicants...........38

3.7 UI Nonmonetary Eligibility Rates for TANF Leavers and Non-TANF UI 

Applicants..........................................................................................................................38

3.8 UI Benefit Receipt Rates for TANF Leavers and Non-TANF UI Applicants...................38

3.9 Quit Rates Comparing TANF Leavers and Other UI Applicants......................................39

3.10 Rates of Discharge Comparing TANF Leavers and Other UI Applicants.........................40

3.11 Average Weeks of UI Comparing TANF Leavers and Non-TANF UI

Beneficiaries ......................................................................................................................41

3.12 UI Benefit Exhaustion Rates Comparing TANF Leavers and Non-TANF 

UI Beneficiaries.................................................................................................................42

4.1 Rates of Return to Employment and TANF for All Newly Unemployed

TANF Leavers ..................................................................................................................44

4.2 Rates of Return to Employment and TANF for UI Beneficiaries and

Nonbeneficiary UI Applicants ..........................................................................................46

4.3. Rates of Self Sufficiency among All Newly Unemployed TANF Leavers ......................53

4.4 Rates of Self-Sufficiency and Working Poor for UI Beneficiaries and

other UI Applicants ...........................................................................................................54

4.5 Rates of TANF Dependency and Inactivity for UI Beneficiaries and

other UI Applicants ...........................................................................................................55

5.1 Employment Services Usage by Degree of UI Involvement in Georgia ..........................72

5.2 Employment Services Usage by Degree of UI Involvement in Ohio ...............................73
xi

EXECUTIVE SUMMARY

Unemployment insurance (UI) provides temporary partial wage replacement to the 

involuntarily unemployed. The Employment Service (ES) provides job matching services for 

job seekers and employers. The ES also administers the UI work test to ensure that UI 

beneficiaries are able, available, and actively seeking work. The Personal Responsibility and 

Work Opportunity Reconciliation Act (PRWORA) of 1996 changed welfare by establishing 

Temporary Assistance for Needy Families (TANF). This new law introduced lifetime limits and 

work requirements for continued TANF benefit eligibility. 

Using state administrative data from four of the nine largest states, this study expands on 

prior knowledge about the use of UI and ES by recent TANF leavers. We examine the incidence 

of unemployment, the rates of UI application, eligibility, and benefit receipt. We also report on 

the correlation between UI receipt and patterns of self-sufficiency. In addition to studying 

outcomes for UI applicants, we examine self-sufficiency and use of ES for non-UI applicants. 

Finally, for two of the states we employ data on the use of Wagner-Peyser funded employment 

services (ES) to examine their value for newly unemployed TANF leavers. 

Data for Analysis 

TANF exit and use of UI were studied with administrative data from Florida, Georgia, 

Michigan, and Ohio. Access to administrative data on UI and TANF for Florida and Ohio was 

provided through the Administrative Data Analysis and Research (ADARE) consortium 

supported by the U.S. Department of Labor (USDOL). Additional data were provided by 

Georgia, Michigan, and Ohio directly to the Upjohn Institute under separate bilateral data 

sharing agreements. 

Analysis samples were set up within time ranges of available data to ensure state panels 

with at least 12 calendar quarters for observing UI and ES program use and labor market 

transitions after TANF exit. The combined state samples totaled 322,036 (Table E.1). They 

represent a census of TANF leavers in the four states during these years. These data include 

adult grantees in TANF recipient households who left TANF for employment.
xii

Incidence of Unemployment

Among TANF leavers, 253,189 experienced a new spell of unemployment within three

years after leaving TANF. The cumulative rates of unemployment ranged from 75.1 to 81.2 

percent in the states with a weighted mean cumulative unemployment rate of 78.6 percent in the 

four-state pooled data (Table E.1; Figure E.1).

Among UI applicants, the pooled data on newly unemployed TANF leavers includes 34.0 

percent youths (18–24) and 58 percent prime-age persons (25–44), 82 percent females, 37 

percent whites, 60 percent African Americans, and 2 percent Hispanics. In nominal dollars, the 

average quarterly earnings in the three years before TANF exit were $1,414, and average 

quarterly earnings from TANF exit to new unemployment were $1,772. 

Table E.1 Summary of New Unemployment and UI Application among TANF Leaversa

Florida Georgia Michigan Ohio Pooled

TANF leavers 59,726 152,278 27,172 82,860 322,036

Newly unemployed 46,245 123,701 21,043 62,200 253,189

UI applicants 18,309 27,257 4,776 11,116 61,458

Monetarily-eligible for UI benefits 17,331 24,294 4,687 7,256 53,568

Nonmonetarily-eligible for UIb, c 8,406 13,100 1,874 3,498 26,878

UI beneficiaries 11,095 13,389 3,097 3,339 30,920

Newly unemployed rate 0.774 0.812 0.774 0.751 0.786

UI application rate 0.396 0.220 0.227 0.179 0.243

Monetary-eligibility rate 0.947 0.891 0.981 0.653 0.872

Nonmonetary eligibility rate 0.459 0.481 0.392 0.315 0.437

UI beneficiary rate 0.606 0.491 0.648 0.300 0.503 a For all observations summarized in this table, we have twelve quarters of data after TANF exit to observe any new 

unemployment. Relative to the quarter of new unemployment, we see UI application, eligibility, and benefit receipt for UI 

applications that occur from one quarter before new unemployment through three quarters after. In subsequent analysis 

attempting to determine the impact of UI application, eligibility, and benefit receipt on the likelihood of return to TANF or 

employment, sample sizes will be smaller for two primary reasons: 1) persons who applied for UI may have done so after the 

period for which we are able to observe re-employment or TANF outcomes, and 2) persons may have returned to TANF or had 

interim employment prior to UI application. In both cases, those persons will be excluded from the outcome analysis. b In Georgia, the number of persons ineligible because they quit or were discharged, and therefore the total number of persons 

nonmonetarily eligible for UI, was imputed using the rates of quit or discharge based on a sample of 26,610 UI applicants for 

whom job separation reason data were available. Because of this, the pooled rate of non-monetary eligibility observed in this 

table for TANF-leaver UI applicants will differ from the rate reported in Table 3.13, since the weights are determined by the 

individual state’s share of UI applications (for Georgia, 27,757 in this table, compared with 26,610 in Table 3.13). c Ohio nonmonetary eligibility is based on claims filed on or before December 31, 2002. Claims beginning in 2003 did not 

include the characteristic data needed to define nonmonetary eligibility. Persons who were nonmonetarily eligible to receive 

benefits must not have had a quit or discharge job separation reason and must not have been in the UI agency, nonmonetary 

determination file. Therefore, based on 8,513 UI claims filed before year end 2002, 2,679 were nonmonetarily eligible for 

benefits. That rate (0.315) was then applied to the 11,116 UI applicants observed in the full range of Ohio data to estimate the 

total number of nonmonetarily eligible UI applicants. Because of this, the pooled rate of nonmonetary eligibility observed in 

this table will differ from the rate reported in Table 3.13, since the weights are determined by the individual state’s share of UI 

applications (for Ohio, 11,116 in this table compared with 8,513 in Table 3.13).
xiii

Figure E.1 Rates of New Unemployment and UI Application among TANF

 Leavers

0.0

0.2

0.4

0.6

0.8

Florida Georgia Michigan Ohio Pooled

Newly unemployed rate UI application rate

UI Application

The UI application rates ranged from 17.9 to 39.6 percent of newly unemployed in the 

four states within three years after leaving TANF (Table E.1; Figure E.1). The mean rate in the 

pooled data from all four states is 24.3 percent. 

Among newly unemployed TANF leavers, compared to nonapplicants, those who apply 

for UI include higher proportions who are of prime age, who are African American, who have 

dependent children, higher earnings before UI application, more prior work experience, and who 

have prior employment in construction, manufacturing, wholesale trade, or administration. 

Higher UI application rates were also observed in areas with higher or faster-rising 

unemployment (Table E.2). The more-than-75 percent of newly unemployed TANF leavers who 

fail to apply for UI are more likely to be young, white, have lower earnings before a new spell of 

unemployment, fewer calendar quarters with employment before TANF exit, and recent prior 

employment in the industries of retail trade, educational service, health care, or hospitality. 

UI Monetary Eligibility

Among TANF leavers who become newly unemployed and apply for UI benefits, 87.2 

percent were initially eligible for UI based on monetary requirements in the four-state pooled 

data (Table E.1; Figure E.2). The rates of monetary eligibility range from 65.3 percent of the 

Ohio sample to 98.1 of the Michigan sample. The lower monetary eligibility rates in Ohio result 

from the strict requirement for 20 or more weeks of work with average earnings being at least 
xiv

27.5 percent of the state average weekly wage in UI-covered employment. For Ohio in the year 

2000 a week of insured employment required earnings of at least $172, or more than 33 hours of 

work at the federal minimum wage of $5.15 per hour. 

Among newly unemployed TANF leavers who apply for UI benefits, those meeting 

monetary eligibility conditions have larger sample proportions of males, prime-age persons, and 

highly educated persons. Monetarily-eligible UI applicants also had more calendar quarters with 

earnings before UI application and higher levels of UI base period earnings. Monetarily-eligible 

Table E.2 Characteristics Comparisons of Newly Unemployed TANF-Leaver UI Applicants and UI 

Eligibility Groups with Others

Focus group UI applicant

Monetarily 

eligible

Nonmonetarily

eligible

Quit 

prior job

Discharged 

from prior 

job

UI 

beneficiary

UI 

beneficiary

Comparison

group

UI nonapplicantOther UI 

applicants

Other UI 

applicants

Other UI 

applicants

Other UI 

applicants

Other UI 

applicants

UI nonapplicants

Age Older Older Older — Younger Older Older

Gender — Male Male Female Female Male Male

African 

American

More — Less Less More Less More

Educational 

attainment

— Higher — — Lower Higher —

Base period 

earnings

Higher Higher — Lower — Higher Higher

Quarters from 

TANF exit to 

unemployment

More More — — — More More

NOTE: Contrasts in this table are computed as the focus group minus the comparison group. — = not available.

SOURCE: Summary of contrasts in tables 3.1, 3.5, 3.7, 3.8, 3.9, 3.10, and 3.11. See these tables for additional detail.

Figure E.2 Rates of UI Monetary Eligibility, Nonmonetary Eligibility, and

 UI Benefit Receipt

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1.0

Florida Georgia Michigan Ohio Pooled

Monetary eligibility rate Nonmonetary eligibility rate UI beneficiary rate
xv

UI applicants were more likely to have had prior employment in the industries of wholesale trade 

and real estate, and were less likely to have been employed in retail trade (Table E.2). 

Among the three-quarters of newly unemployed TANF leavers who do not apply for UI, 

we estimate that an average of 69.9 percent would have satisfied UI monetary eligibility 

requirements in the four states had they applied for benefits. That rate is 17.3 percentage points 

or 20 percent lower than the monetary eligibility rate among TANF-leaver UI applicants. 

However, the simulated monetary eligibility rate suggests that a large number of unemployed 

TANF leavers could potentially have qualified for UI had they filed applications for benefits.

UI Nonmonetary Eligibility

In addition to having sufficient levels of prior employment and earnings, applicants for 

UI must also have separated involuntarily from their previous jobs and must currently be able, 

available, and actively seeking work. In the sample of UI applicants pooled across four states the 

rate of nonmonetary eligibility is 43.7 percent. Rates for individual states range from 31.5 

percent in Ohio to 48.1 percent in Georgia (Table E.1; Figure E.2). 

Among newly unemployed TANF leavers who apply for UI benefits, those meeting 

nonmonetary eligibility requirements have larger sample proportions of males, Hispanics, and 

those with higher educational attainment.

For TANF leavers, higher rates of voluntary job quits and justifiable dismissals result in 

lower rates of nonmonetary eligibility. Among newly unemployed TANF leavers who apply for 

UI, 17.3 percent quit their prior job while 33.1 percent were fired. Within these groups, those 

who quit tend to have larger sample proportions of females; whites; members of the industry 

groups retail trade, hotels and restaurants, and health care; and members of services occupations. 

Compared to other TANF-leaver UI applicants, those who got fired had larger sample 

proportions with prior employment in the industries of retail trade; finance, insurance and real 

estate; health care; and hotels and restaurants. While there are no other statistically significant 

patterns across all states, those experiencing discharge had larger proportions of youths, females, 

and African Americans. Discharge was suffered by smaller proportions of Hispanics and those 

with lower levels of educational attainment. 

For UI nonapplicants among newly unemployed TANF leavers, nonmonetary eligibility 

rates can be inferred from the 0.80 ratio of simulated monetary eligibility rates for nonapplicants 
xvi

relative to actual monetary eligibility rates for UI applicants. The imputed nonmonetary 

eligibility rate is 35 percent for UI nonapplicants. However, the actual rate would probably 

somewhat lower, since a voluntary job quit or employer dismissal is likely to be a major factor 

influencing the decision not to apply for UI benefits.

Receipt of UI Benefits

Among TANF leavers who are UI applicants, the proportions receiving UI benefits in the 

states examined range from 30.0 percent in Ohio to 64.8 percent in Michigan (Table E.1; Figure 

E.2). The overall mean rate of benefit receipt was 50.3 percent in the sample pooled across four 

states. 

Among TANF leavers who qualify for UI, mean weekly benefit amounts are $159, mean 

entitled durations of UI benefits are 19.6 weeks, and on average 74.6 percent of entitled UI 

benefits are drawn (Table E.3). Mean UI payments are $2,442 over the full benefit year, or a 

mean of 14.5 weeks of UI at the average weekly benefit amount for this sample. Benefit 

entitlements are fully exhausted by 53.2 percent of TANF-leaver UI beneficiaries, which is a 

higher rate of UI benefit exhaustion than among UI beneficiaries not recently involved with 

TANF in these states (Figure E.3). 

Table E.3 Summary of UI Entitlement, Benefit Receipt, and Exhaustion

Florida Georgia Michigan Ohio Pooled

Weeks of UI entitlement 18.4 18.4 22.1 25.4 19.6

Weeks of UI drawna 14.7 12.6 18.7 18.0 14.5

Share of UI entitlement drawn 0.798 0.689 0.843 0.709 0.746

UI exhaustion rate 0.610 0.497 0.556 0.383 0.532

UI weekly benefit amount ($) 165 145 201 157 159

UI compensation received in benefit year ($) 2,528 1,959 3,806 2,824 2,442

UI monthly amount receivedb ($) 535 411 683 453 487

TANF monthly amount receivedc ($) 134 165 199 225 164

Ratio of mean UI to mean TANF 4.0 2.5 3.4 2.0 3.1

a This is full-time equivalent weeks of UI computed as total dollars of UI benefits received divided by the beneficiary's UI 

weekly benefit amount (WBA) for joblessness throughout a full week. b Computed as total dollars of UI received in the benefit year divided by maximum entitled weeks of UI benefits times four.

c TANF payments received in the two calendar quarters completed prior to TANF exit divided by six.
xvii

Among TANF-leaver UI applicants, the UI beneficiaries include higher proportions that 

are older, male, white, Hispanic, and have UI base period earnings on average more than $3,000 

higher (Table E.3). UI beneficiaries also have higher proportions from the construction and 

manufacturing industries and smaller proportions from the retail trade, health care, and 

hospitality industries. By occupation, UI recipients include higher proportions from 

management, professional, and production occupations and smaller proportions from service 

occupations. 

Among TANF leavers, comparing UI beneficiaries and UI nonapplicants, those who 

receive UI include higher proportions that are older, male, African American, and have UI base 

period earnings on average more than $4,000 higher (Table E.3). UI beneficiaries also have 

higher proportions from the construction and manufacturing industries, and smaller proportions 

from retail trade, health care, and hospitality industries. 

Applying the 80 percent nonapplicant/applicant ratio from monetary eligibility 

computations to the 50.3 percent beneficiary rate for UI applicants, we estimate that 40 percent 

of newly unemployed nonapplicants for UI could have received benefits had they applied. The 

actual beneficiary rate for this group would probably be somewhat lower due to unobserved 

actual rates of job quits and dismissals influencing the decision to apply for benefits. 

Nonetheless, within these four states there could have been nearly 90,000 additional UI 

beneficiaries among TANF leavers in the time period during which 30,000 actually received UI 

compensation. 

Figure E.3 Shares of UI Entitlement Drawn and UI Exhaustion Rates

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

Florida Georgia Michigan Ohio Pooled

Share of UI entitlement drawn UI exhaustion rate
xviii

TANF Leavers’ UI Use Compared to Others

While TANF leavers compare favorably to those not recently involved with TANF in 

terms of monetary eligibility for UI, they have much lower rates of UI eligibility based on initial 

nonmonetary eligibility factors.

In the combined sample pooled across all four states, simple differences between the two 

groups reveal lower rates of monetary eligibility, nonmonetary eligibility, and benefit receipt for 

TANF leavers compared to all other UI applicants in the same time periods. However, the 

pattern changes somewhat when comparisons are made while controlling for differences in 

observable characteristics. Variables available as controls for comparisons are as follows: age, 

gender, race, ethnicity, family size, prior earnings, and prior employment patterns. For some 

contrasts indicators of prior industry and occupation are also available. 

In data pooled across four states controlling for characteristics, TANF leavers are 

estimated to have higher rates of UI monetary eligibility than other UI applicants. In terms of 

monetary eligibility, Ohio is alone among the four states in having a lower adjusted monetary 

eligibility rate for TANF leavers than for other UI applicants. The Ohio result suggests that 

TANF leavers have more difficulty satisfying the 20-weeks-of-work monetary eligibility 

requirement than do UI applicants not recently involved with TANF. 

Even in regression models with characteristics controls, nonmonetary eligibility rates are 

estimated to be lower for TANF leavers in all states, with the greatest difference being in 

Michigan. Similarly, rates of UI benefit receipt are lower in every state for recent TANF leavers 

compared to other UI applicants; differences in the rate of receipt range from 10.5 percentage 

points in Florida to 36.5 percentage points in Ohio. 

Failure of nonmonetary eligibility requirements is the main reason for lower rates of UI 

benefit receipt by TANF leavers in all four states. Voluntary quit rates are higher for TANF 

leavers than for other UI applicants in all states examined. In the pooled four-state sample of 

TANF-leaver UI applicants, 17.2 percent voluntarily quit their prior job, which is almost double 

the 9.4 percent rate for other UI applicants. Employer dismissals are also higher for TANF 

leavers. For non-TANF-leaver UI applicants, 19.2 percent got fired from their prior jobs, while 

33.1 percent of TANF leavers were fired. Controlling for observable characteristics, TANF 

leavers were 3.8 percentage points more likely to quit and 7.0 percentage points more likely to 

get fired than other similar UI applicants. 
xix

UI and Self-Sufficiency

A goal of UI as social insurance is to prevent descent into poverty by those who are 

temporarily jobless through no fault of their own. Of the 241,719 newly unemployed TANF 

leavers in the four-state pooled sample, 77.5 percent returned to employment and 36.5 percent 

returned to TANF within three years of first leaving TANF (Table E.4). Compared to Florida 

and Georgia, rates of return to employment are lower, and return to TANF higher, in Michigan 

and Ohio (Figure E.4).

Table E.4 Return to Employment and TANF by UI Status in the Pooled Four-State Sample (%)

Reemployed Return to TANF

Newly unemployed TANF leavers 77.5 36.5

UI applicants 73.4 37.5

Monetarily eligible 73.2 36.7

Monetarily ineligible 74.7 43.9

Nonmonetarily eligible 75.3 32.1

Quit prior employment 72.9 43.1

Discharged/fired 74.5 42.2

UI beneficiary 74.2 30.1

UI applicant but not a UI beneficiary 72.6 45.2

UI nonapplicants 78.6 36.2

Among UI beneficiaries in this sample, 74.2 percent return to employment, compared 

with 72.6 percent of nonbeneficiary UI applicants and 78.6 percent of UI nonapplicants. Return 

to TANF rates are 30.1 percent for UI beneficiaries, 45.2 percent for nonbeneficiary UI 

applicants, and 36.2 percent for UI nonapplicants. These simple unadjusted comparisons suggest 

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

Florida Georgia Michigan Ohio Pooled

Employed TANF

Figure E.4 Rates of Return to Employment and TANF for all Newly 

Unemployed TANF Leavers
xx

that UI nonapplicants have stronger workforce attachments and better return to work prospects 

than UI applicants. Some of the factors driving these differences are part of UI eligibility rules: 

prior earnings and reasons for job separation.

Applicants for UI who have sufficient prior earnings to be monetarily eligible have a 

slightly lower rate of reemployment (73.2 percent), but a significantly lower rate of return to 

TANF (36.7 percent) than UI applicants who are not monetary eligible (74.4 percent and 43.9 

percent). UI applicants who are nonmonetarily eligible have a slightly higher rate of 

reemployment (75.3 percent) than those who quit (72.9 percent) or were discharged for cause 

(74.5 percent) from their prior jobs. However, rate of return to TANF for nonmonetarily eligible 

UI applicants is only 32.1 percent, while for job quitters it is 43.1 percent, and for those 

discharged for justifiable cause such as absence, misconduct, or poor job performance it is 42.2 

percent. 

UI Beneficiaries Compared to Nonbeneficiary UI Applicants 

Controlling for observable differences across UI eligibility groups in regression models, 

receipt of UI is estimated to increase return to employment by 4.8 percentage points and reduce 

return to TANF by 10.5 percentage points compared to nonbeneficiary UI applicants. In these 

models, return to employment is more likely among those who are younger, female, African 

American, have worked in more calendar quarters before applying for UI, have had multiple 

employers in calendar quarters before UI application, and have had prior employment in 

agriculture, manufacturing, administrative support, or hospitality industries. The models suggest 

that return to TANF is less likely among UI applicants who are older, male, not African 

American, have had employment in more calendar quarters before UI application, and have lived

in areas with lower unemployment, and have worked outside the hospitality industry. 

Variation in rates of return to employment is small for groups defined by their degree of 

involvement with UI, ranging between 72.6 and 78.6 percent. By interacting return to 

employment with return to TANF we get a much more informative view of how UI receipt is 

correlated with self-sufficiency–return to employment without return to TANF. Proportions in 

each of the resulting groups are given in Figure E.5.
xxi

Figure E.5 TANF-Employment Outcomes Matrix

 (% newly unemployed in four-state pooled sample) 

No TANF TANF

Employment Self-sufficient

(47.6)

Working poor

(29.9)

No employment Inactive

(16.0)

TANF-dependent

(6.5)

Controlling for observable characteristics, compared to nonrecipient UI applicants, UI 

beneficiaries are estimated as 12.0 percentage points more likely to be self-sufficient, 7.2 

percentage points less likely to be working poor, 3.2 percentage points less likely to be TANFdependent, and 1.5 percentage points less likely to be inactive.

Self-sufficiency (employment without TANF) is most likely among those who are of 

prime age for the labor market (between 25 and 49), male, white, those with employment in 

more quarters before UI application, those with multiple employers in at least one of their UI 

base-period quarters, and those with recent prior employment in the industries of agriculture, 

manufacturing, and administrative support, and in areas where unemployment is lower.

Working poor (employment with TANF) is most likely among younger (less than 25) 

workers, females, African Americans, those with more quarters of employment before UI 

application, those with multiple employers in at least one UI base-period quarter, and those 

recently employed in the hospitality industry, and in areas with higher unemployment rates.

TANF dependency (TANF but no employment) is most likely among those aged 50 and 

over, female, those with few quarters of employment before UI application, and those in high 

unemployment areas.

Inactivity (neither employment nor TANF) is most likely for those aged 50 and over, 

males, those not African American, those having fewer calendar quarters with earnings before UI 

application, those having new unemployment longer after TANF exit, and those in low 

unemployment areas. 
xxii

UI Nonapplicants Compared to UI Beneficiaries

Unemployment insurance beneficiaries return to work at lower rates (74.2 percent) than 

UI nonapplicants (78.6 percent) in simple unadjusted comparisons. However, controlling for 

observable characteristics, there is no measurable difference in the rate of return to employment 

between the two groups. In the full sample of all newly unemployed TANF leavers, 

reemployment is positively correlated with higher base-period earnings, more quarters with 

employment prior to TANF exit, and having multiple employers in any calendar quarter between 

TANF exit and new unemployment

Unadjusted comparison of means suggests that UI beneficiaries return to TANF at a 

lower rate (30.1 percent) than UI nonapplicants (36.2 percent). However, compared to UI nonapplicants with similar characteristics, UI beneficiaries return to TANF at a rate 2.5 percentage 

points higher. This suggests that increased self-sufficiency may be attributable to receipt of UI 

cash benefit payments. Compared to nonapplicants, UI beneficiaries are more likely to be older, 

male, African American, have higher base-period earnings, and have more quarters with 

employment between TANF exit and new unemployment. 

UI Nonapplicants Compared to Nonbeneficiary UI Applicants

Applicants for UI who fail to receive benefit payments return to work at lower rates (72.6 

percent) than UI nonapplicants (78.6 percent) in simple comparisons. Controlling for observable 

characteristics reduces the difference to 3.6 percentage points, but regression controls do not 

entirely eliminate the difference. In terms of observable characteristics, nonbeneficiary 

applicants tend to have low preunemployment earnings and employment, they also have high 

rates of job quits and employer discharge. 

UI applicants who do not receive benefits return to TANF at much higher rates (45.2 

percent) than UI nonapplicants (36.2 percent). Controlling for observable characteristics, the 

return-to-TANF rate is still greater for nonbeneficiary UI applicants, and the difference from UI 

nonapplicants is greater (12.4 percentage points). Independent variables in the models suggest 

that return to TANF is less likely among those with high earnings in what would be the UI base 

period and those having more calendar quarters with earnings between TANF exit and new 

unemployment. 
xxiii

Among newly unemployed TANF leavers, those who do not apply for UI benefits are 

much more successful than nonbeneficiary UI applicants. Nonapplicants have more favorable 

outcomes on reemployment, return to TANF, and all four interactions of these two outcomes. 

Relative to UI applicants who do not become beneficiaries, UI nonapplicants tend to be younger, 

female, have lower base-period earnings, and have fewer quarters with employment between 

TANF exit and new unemployment. Even when controlling for observable characteristics in 

computing differences, nonbeneficiary UI applicants are less successful on three of the selfsufficiency outcomes. 

Summary of Contrasts

Whenever three groups are compared, one will have the least favorable outcomes. Nonbeneficiary UI applicants are least successful at maintaining self-sufficiency in comparison to 

either UI beneficiaries or UI nonapplicants. These results persist even when we control for 

observable characteristics of the individuals and their labor markets. Additional information is 

required to understand results for nonbeneficiary UI applicants. UI application for this group 

may be correlated with return to TANF, because of federal and state TANF eligibility requires 

UI application despite a low likelihood of qualification and UI benefit receipt. We next proceed 

to investigate the importance of publicly provided employment services (ES) for all three groups 

of newly unemployed TANF leavers. Results of the ES investigation are very important for 

shaping policy for assistance to UI applicants who do not receive UI benefits.

Use of the Public Employment Service by Unemployed TANF Leavers

The public Employment Service (ES) in the United States is funded through the WagnerPeyser Act. One-stop career centers operating under the Workforce Investment Act deliver 

reemployment services divided into three increasing levels of service: core, intensive, and 

training. The core and intensive services at one-stops are commonly delivered by the ES with 

Wagner-Peyser funding. Participants typically use core services before progressing to intensive 

or training services. The ES and UI systems are closely linked by the work test for continued UI 

benefit eligibility, which is administered by the ES. Using data from Georgia and Ohio we 

examined the use of Wagner-Peyser funded ES services by newly unemployed TANF leavers 
xxiv

and measure the correlations between ES usage and labor market outcomes, controlling for the 

degree of UI involvement.

Evidence from these two states suggests that large proportions of newly unemployed 

TANF leavers use the ES. Among these, sizable numbers of UI nonapplicants use ES services, 

but usage rates are significantly higher among UI applicants. Importantly, ES usage rates are 

similar between UI beneficiaries and nonbeneficiary UI applicants. This suggests that 

application for UI is a pathway to reemployment services provided by the ES even if cash UI 

benefits are not forthcoming. 

Usage rates for any core or intensive service in Georgia are shown in Figure E.6, together 

with usage rates for the most popular core and intensive type services in Ohio (service type is 

categorized for our Georgia data, but not for Ohio data). The figure shows that in Georgia 14 

percent of UI nonapplicants receive at least one core ES service after new unemployment, while 

a core service was used by 78 percent of UI beneficiaries and 77 percent of UI-ineligible 

applicants. The core service called “job seeker match” in Ohio was used by 8 percent of UI 

nonapplicants, 45 percent of UI beneficiaries, and 48 percent of ineligible UI applicants. While 

usage rates are lower across the board for intensive services, a similar pattern of usage can be 

seen in both states across the UI usage groups (Figure E.6). A key contrast is the substantially 

higher rate of usage for both core and intensive services by ineligible UI applicants compared to 

UI nonapplicants.

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

Core (GA) Core (OH) Intensive (GA) Intensive (OH)

UI nonapplicants UI beneficiaries UI ineligibles

Figure E.6 Use of Core and Intensive ES Services by UI Status 

in Georgia and Ohio
xxv

Employment Services and Return to Employment and TANF

For our samples of newly unemployed TANF leavers in Georgia and Ohio, statistical 

analysis suggests that public employment services help to maintain connections with 

employment opportunities, particularly for the working poor. This appears to be true regardless 

of the degree of involvement with UI and, despite the fact that UI applicants use the ES more 

often, this result still holds for UI nonapplicants. Additionally there is evidence that use of 

services through the ES reduces rates of complete TANF dependency and inactivity. However, 

our measurement of correlations between service receipt and outcomes is affected by the time 

frames available for observation. Since core services are likely to be received earlier in a jobless 

spell than intensive services, there is a better chance to observe a positive outcome within 12 

calendar quarters after initial TANF exit. Participants enter intensive services only after 

exhausting more immediate reemployment opportunities offered by core services. Consequently 

there is less time to observe reemployment and earnings activity for intensive service recipients.

In regression models of ES effects, the largest estimates are for the most popular core 

service: job referrals (Table E.5). In Georgia, job referrals boost reemployment rates by 6.5, 4.9, 

and 10.7 percentage points respectively for UI nonapplicants, UI beneficiaries, and nonbeneficiary UI applicants. Job referrals impact estimates are also positive and significant on 

employment in Ohio for all three UI involvement groups. The point estimates are 5.7, 8.3, and 

4.6 percentage points in increased employment rates respectively for UI nonapplicants, UI 

beneficiaries, and nonbeneficiary UI applicants. 

Statistical analysis suggests a positive correlation between ES services and return to 

TANF in both Georgia and Ohio. These results are probably an artifact of underlying tendencies 

for these groups of TANF leavers. These people are struggling to maintain adequate income 

from multiple sources, which may often mean combining income from earnings and TANF. The 

results’ parameter estimates suggest that ES services may be particularly useful for the working 

poor. We find significant positive correlations between use of ES services and return to work 

among those who continue to rely on TANF. 

A uniformly favorable result following job referrals is a reduction in inactivity for all 

newly unemployed TANF leavers. Inactivity means a lack of involvement with either 

employment or TANF. For Georgia, job referrals are measured as reducing inactivity by 4.8,
xxvi

Table E.5 Marginal Effects of Job Referrals (Core) and Job Search Planning (Intensive) Services on Return 

to Employment and TANF among Newly Unemployed TANF Leavers in Georgia (GA) and Ohio 

(OH)a

Employment Service

Returned to employment Returned to TANF

Nonapplicant

UI

beneficiary

Nonbeneficiary

UI applicant Nonapplicant

UI

beneficiary

Nonbeneficiary

UI applicant

Job interview referrals (GA) 0.065** 0.049** 0.107** 0.061** 0.035** 0.032**

Job interview referrals (OH) 0.057** 0.083** 0.046** 0.026** 0.078** 0.032

Customer service plan (GA) −0.020 −0.033 −0.036* −0.010 0.041 0.014

Job search planning (OH) −0.005 −0.016 0.007 −0.032* 0.022 −0.028

Employment Service

Employment and no TANF

(Self-sufficient)

Employment with TANF

(Working poor)

Nonapplicant

UI

beneficiary

Nonbeneficiary

UI applicant Nonapplicant

UI

beneficiary

Nonbeneficiary

UI applicant

Job interview referrals (GA) −0.013** 0.009 0.047** 0.077** 0.040** 0.061**

Job interview referrals (OH) 0.021* −0.001 0.018 0.036** 0.084** 0.028

Customer service plan (GA) −0.017 −0.047 −0.036 −0.003 0.014 0.000

Job search planning (OH) 0.014 −0.025 0.020 −0.019 0.008 −0.014

Employment Service

No employment, no TANF

(Inactive)

No employment with TANF

(TANF dependent)

Nonapplicant

UI

beneficiary

Nonbeneficiary

UI applicant Nonapplicant

UI

beneficiary

Nonbeneficiary

UI applicant

Job interview referrals (GA) −0.048** −0.044** −0.078** −0.017** −0.005 −0.029**

Job interview referrals (OH) −0.047** −0.077** −0.050** −0.010 −0.006 0.004

Customer service plan (GA) 0.027** 0.005 0.023 −0.007 0.027** 0.013

Job search planning (OH) 0.019 0.003 0.008 −0.014 0.014 −0.015

* (**) Significantly different from zero at the 90 (95) percent confidence level in a two-tailed test.

4.4, and 7.8 percentage points respectively for UI nonapplicants, UI beneficiaries, and nonbeneficiary UI applicants. For Ohio, estimates of the same effects were 4.7, 7.7, and 5.0 

percentage points.

Among all effect estimates for job referrals, results are particularly encouraging for nonbeneficiary UI applicants. The largest positive effects on employment and self-sufficiency 

(employment without TANF) are measured for these newly unemployed TANF leavers who 

connect with the ES at dramatically higher rates than UI nonapplicants.

Few of the intensive services in Georgia and Ohio are measured to have statistically 

significant effects on employment and return to TANF. The Georgia intensive service called 

“customer service plan” is similar to the Ohio service called “job search planning.” Neither has 

a significant effect on employment or TANF for UI beneficiaries, but the respective programs 

measurably reduce return to TANF for UI nonapplicants in Ohio while modestly reducing the 

rate of return to employment for nonbeneficiary UI applicants in Georgia. The latter result may
xxvii

be due to the fact that customer service plans occur later in job search spells, permitting less time 

to observe return to employment in our restricted measurement period. 

Employment Services and Income

Mixed evidence for effects of ES on employment and return to TANF suggest that job 

seekers may be aiming for something else (Table E.6). A natural possibility is that newly 

unemployed TANF leavers might be using ES services as part of a strategy to maximize total 

combined income from sources including employment earnings, UI benefits, and TANF. 

Job interview referrals had positive impacts on employment earnings for all newly 

unemployed TANF leavers in Georgia. Positive and statistically significant impacts of $352 and 

$1,171 were estimated for UI beneficiaries and nonbeneficiary UI applicants respectively. These 

impact estimates are the differences in observed earnings over the four quarters immediately 

after new unemployment begins. For the Ohio sample, impact estimates for job interview 

Table E.6 Effects of Job Interview Referrals on Components of Income for Newly Unemployed TANF 

Leavers by UI Status in Georgia and Ohio ($)

Nonapplicants UI beneficiaries

Nonbeneficiary UI 

applicants

Job interview referrals (GA)

Earned income

TANF

UI

Total income

120

81**

—

231**

352**

21

115**

285

1,171**

4

—

1,197**

Job interview referrals (OH)

Earned income

TANF

UI

Total income

409**

67

—

478**

−377

185*

230**

−120

464**

70

—

533**

Customer service plan (GA)

Earned income

TANF

UI

Total income

−569

28

—

−523*

−569

113

26

−682

356

53

—

454

Job search planning (OH)

Earned income

TANF

UI

Total income

−439**

−59

—

−521**

−1,055**

180*

−108

−959**

−404**

−48

—

−454**

NOTE: Effects were not constrained in estimation to sum to the effect on total income. Separate models were estimated for 

each component of income. See tables 5.5, 5.6, 5.7, 5.8, A.34, and A.35. — = not available.

*(**) Statistically significant at the 90 (95) percent level of confidence in a two-tailed test.
xxviii

referrals are positive and large for UI nonapplicants ($409) and for nonbeneficiary UI applicants 

($464). While the job referral impact for Ohio UI beneficiaries is not different from zero, the 

impact for job placements on this group is $1,665 in the four calendar quarters after the UI 

benefit year begin date. In both states for all three groups defined by degree of involvement with 

UI employment, earnings make up the biggest part of total income. Job referrals are associated 

with a sizable increase in TANF receipts for UI nonapplicants and with a significant increase in 

UI benefits among UI beneficiaries.

Receipt of a customer service plan in Georgia or a job search plan in Ohio led to 

unchanged or significantly lower levels of earned income in both states. Among nonbeneficiary 

UI applicants in Georgia, receiving a customer service plan had no significant impact on income. 

Impacts were negative for other groups. These intensive services had largely insignificant 

impacts on receipt of UI benefits and cash TANF assistance. The sole exception was a positive 

effect on UI benefits in Ohio. These impacts were estimated on the full samples of all newly 

unemployed TANF leavers. The estimates suggest that the reference groups—those not 

receiving intensive employment services—returned to work sooner, resulting in higher 

employment earnings. These results do not measure the effect of intensive ES services 

conditional on being unemployed an extended period of time. 

Analysis of newly unemployed TANF leavers using public employment services in 

Georgia and Ohio show the ES to be an important partner with UI in providing income security. 

The central message that emerges is that connections with employment opportunities improve 

labor market success for newly unemployed TANF leavers, particularly for those who remain the 

working poor. This appears to be true regardless of the degree of involvement with UI, and, 

despite the fact that UI applicants use the ES more often, this result still holds for UI nonapplicants. Additionally there is evidence that use of services through the ES reduces rates of 

complete TANF dependency and inactivity.

Next Steps

Welfare caseloads have declined dramatically since TANF was introduced in 1996. It is 

undeniable that TANF changed welfare as we knew it. While caseloads have vanished, need 

remains. Former TANF recipients and others vulnerable to welfare dependency are turning to 

multiple sources to replace cash public assistance. The roles of UI and ES for low-income 
xxix

Americans in a post-TANF economy should be better understood. The degree to which this 

population is served under current arrangements should be documented. We must also learn 

about the extent to which initiatives of UI modernization and ES revitalization under the 

American Recovery and Reinvestment Act broaden the effectiveness of these programs for our 

most vulnerable households. Additionally we should identify federal and state program changes 

to make these institutions accessible, sustainable, and more compatible for employers and job 

seekers in competitive labor markets. 
xxx
1

1. INTRODUCTION

Unemployment insurance (UI) provides temporary partial-wage replacement to labor 

force members who become involuntarily unemployed through no fault of their own. It is a 

federal-state program operated in cooperation with a nationwide network of more than 1,800 

Wagner-Peyser funded Employment Service (ES) offices. The ES administers the UI work test 

to ensure that continuing UI beneficiaries are able, available, actively seeking work, and do not 

refuse an offer of suitable work. These two public labor-market support programs are essential 

parts of the social safety net promoting self-sufficiency through employment for all Americans. 

Both programs are operated by the states following administrative guidelines issued and 

monitored by the U.S. Department of Labor, Employment and Training Administration.

The Personal Responsibility and Work Opportunity Reconciliation Act (PRWORA) of 

1996 replaced the federal program Aid to Families with Dependent Children (AFDC) with 

Temporary Assistance for Needy Families (TANF). The new law changed the character of 

public cash support by introducing lifetime limits and adding work requirements for continued 

benefit eligibility. Incentives and rewards were established for achievement of self-sufficiency 

through employment. These changes combined with a strong economic expansion to induce a 

mass exodus from TANF rolls (King and Mueser 2005). This trend was slowed but not arrested 

by the 2001 economic recession (NBER 2001). Recent years have seen TANF rolls continue to 

decline during a modest recovery from the 2001 recession. 

Public employment and training programs support self-sufficiency for new TANF leavers 

who become separated from their jobs. Unemployment insurance (UI) has been identified as a 

prime factor supporting self-sufficiency for TANF leavers during and after the 2001 recession 

(Isaacs 2005). Using state administrative data from four of the nine largest states, this study 

expands on prior knowledge about the use of UI by recent TANF leavers (Kaye 2001; 

Rangarajan and Razafindratoko 2004). Direct measures of UI application, eligibility, and benefit 

receipt from administrative data matched with TANF payment data illuminate clear patterns of 

client use and flows between the two programs. 

For TANF leavers in Florida, Georgia, Michigan, and Ohio, this study examines the 

incidence of unemployment, and the rates of UI application, eligibility, and benefit receipt. We 

also report on the correlation between UI receipt and patterns of self-sufficiency. In addition to 

studying outcomes for UI applicants, we examine self-sufficiency by non-UI applicants. Finally, 
2

for TANF leavers in Georgia and Ohio, we employ data on the use of Wagner-Peyser funded 

employment services (ES) to examine their value for newly unemployed TANF leavers. We 

conclude this report with a concise summary of results, conclusions regarding possible uses of 

these findings for policy development, and suggestions about extending this analysis to the 

broader population of working poor. 
3

2. BACKGROUND

The introduction of TANF, with its lifetime limits and work requirements for continued 

receipt of cash assistance, meant that traditional employment and training programs would be 

key to self-sufficiency for TANF leavers. Research before TANF suggested that few leavers 

from cash social assistance would qualify for UI, but analysis after TANF was in place estimated 

higher UI recipiency rates (Gustafson and Levine 1997; Rangarajan, Razafindrakoto, and Corson 

2002). As background for the present research, we examine UI and TANF eligibility rules in 

each of the four states analyzed and review prior research on use of UI by TANF leavers.1

2.1 UI Eligibility and Benefits

Unemployment insurance eligibility rules ensure that beneficiaries are strongly attached 

to the labor force and are temporarily jobless through no fault of their own. To initially qualify 

for UI, a claimant must have sufficient prior earnings and employment; these are called monetary 

eligibility conditions. Furthermore, the job separation must be involuntary. Nonmonetary 

eligibility rules prohibit quits and discharge for misconduct or other causes justifiable by an 

employer. Employer discharge for cause is usually related to frequent tardiness, unexplained 

absences, misconduct, or poor job performance.2

Monetary eligibility for UI is determined by base period earnings. The UI base period is 

normally the first four of the previous five completed calendar quarters before the date of claim 

for benefits.

 UI applicants must also be able, available, and 

actively seeking full time work. For initial and continuing eligibility, beneficiaries may not 

refuse an offer of suitable work. 

3

 1

This discussion updates and expands on the exposition in O’Leary and Kline (2008).

 Table 2.1 lists the minimum base-period earnings required to qualify for the 

2

In the case of benefit denial due to voluntary quit or discharge for cause, the UI applicant may requalify 

for UI benefits in the following manner: in Florida, by earning 17 times the client’s weekly benefit amount (WBA); 

in Georgia, by earning 10 times the client’s WBA; in Michigan, by earning the lesser of 7 times the client’s WBA or 

280 times Michigan’s minimum wage (7 x 40 x MI minimum wage); and, in Ohio, by having six weeks of work in 

covered employment with the amount of wages in each week at least 27.5 percent of the state’s average weekly 

wage (USDOL 2001). 3

For claimants not eligible based on earnings in the standard base period, earnings in an alternate base year 

(ABY)—the most recent four completed calendar quarters—is checked in Michigan and Ohio. Georgia does not 

have an ABY rule. An ABY amendment was considered by the 2002 Florida legislature but did not pass both 

houses. 
4

minimum UI weekly benefit amount. For 2000, base-period earnings requirements in the four 

states studied ranged from $1,872 in Georgia to $3,400 in Florida.4

Monetary qualification for UI in many states requires earnings in the high calendar 

quarter of the base period to be above a specified level.5

 4

The Base Period Earnings (BPE) requirement is indexed to a multiple of the state average weekly wage 

(AWW) in UI-covered employment or the state minimum wage in Michigan. The required level of earnings to 

qualify for UI is determined by legislative discretion in Florida, Georgia, and Ohio. In Georgia minimum required 

base-period earnings are a multiple of the minimum weekly benefit amount. 

 Most states with a high quarter earnings 

requirement also have an earnings dispersion requirement—all of the four states studied require 

5

The minimum base-period earnings level to qualify for UI is 1.5 times the minimum high-quarter earnings 

in Florida and Michigan.

Table 2.1 Comparison of State Laws for UI and TANF for Program Year 2000

Florida Georgia Michigan Ohio

UI minimum BPEa ($) 3,400 1,872 2,020 2,640

UI-covered weeks of work 20 weeks at 30 x 

state minimum 

wage ($101)

20 weeks at 

27.5% of Ohio 

AWW ($172)

State AWWb ($) 578 668 726 624

Avg. weekly benefit amount (WBA) ($) 220 212 244 236

Minimum/maximum WBA ($) 32/275 39/264 87/300 77/279

BPE required for max. WBA ($) 10,725 10,752 11,840 10,680

Entitled duration (weeks) 26 12–26 15–26 20–26

Average entitled duration (weeks) for 

TANF-leaver UI beneficiaries

18.4 18.5 22.1 25.4

Quit/discharge qualification 17 × WBA 10 × WBA Lesser of 7 × WBA 

or (7 × 40 × state 

minimum wage)

6 weeks of wages 

at 27.5% of 

state AWW

TANF earnings disregard ($) 200 plus 

50% of 

remainder

120 plus one-third 

of remainder for 4 

months, $120 for 

next 8 months, 

$90 thereafter

200 plus 20% of 

remainder

250 plus 25% of 

remainder

TANF monthly benefit c ($) 303 280 459 373

TANF breakeven earningsd ($) 806 540/400/370 774 996

a Base Period Earnings (BPE) is the sum of earnings in first four of the previous five completed calendar quarters. For 

Michigan, there is an alternative, flat requirement of 14 weeks of work and base period earnings that total 20 times the state’s 

average weekly wage. b State average weekly wage (AWW) earned by those working in UI-covered employment. c Family of three (one adult and two children with no income).

d This is the point at which the TANF benefit is zero due to earnings. Breakeven earnings is computed as (TANF benefit 

amount) divided by (1−disregard rate) plus the lump sum disregard 

SOURCE: TANF (2000), tables 12:2, 12:5; ET Financial Data Handbook 394; Comparison of State Unemployment Insurance 

Laws, 2000. 
5

earnings in at least two calendar quarters of the base period. Ohio is one of the few states in the 

nation with a base period employment requirement, and it is a very restrictive rule.6

Prior research has suggested that TANF leavers would have a high probability of passing 

monetary eligibility requirements but speculates that nonmonetary eligibility requirements would 

eliminate a greater share of TANF leavers from UI eligibility. Regarding monetary eligibility, 

prior research has failed to recognize the importance of employment requirements separate from 

earnings rules, and there has been little prior direct evidence on the job separation patterns for 

recent TANF leavers. The present study does not examine the sensitivity of UI eligibility to a 

more recent base period for earnings computation or relaxing the requirement that job-seeking be 

for full-time work. Prior research suggests modest impacts on UI eligibility for TANF leavers 

from such changes (Vroman 1998).

 The Ohio 

weeks of employment rule limits eligibility to those with at least 20 weeks of work in which 

earnings average at least 27.5 percent of the state average weekly wage in covered employment 

(Table 2.1). For Ohio in 2000, a week of insured employment required earnings of at least $172, 

which is more than 33 hours of work at the federal minimum wage of $5.15 per hour. 

For those who qualify, UI pays benefits weekly; the cash amount increases with the level 

of prior earnings up to a state maximum. Table 2.1 lists the statewide average UI weekly benefit 

amounts. Also listed in Table 2.1 are average weekly wages of all workers covered by UI in 

calendar year 2000 in the states examined. This provides a sense of the average wage 

replacement rate provided by UI to regular full-time workers. 

2.2 TANF Eligibility and Benefits

Needy families with dependent children and earnings below the breakeven thresholds 

listed in Table 2.1 may have qualified for cash TANF assistance. States set maximum monthly 

TANF grant amounts and resource levels. Resource limits apply to liquid financial and vehicle 

assets. There are also employment requirements for continued TANF eligibility. Work is 

required immediately upon receipt of benefits in 28 states, within six months in 9 states, and 

within 24 months in 13 states. States also impose lifetime limits between 24 and 60 months on 

receipt of benefits (HHS 2000). 

 6

Three other states have employment requirements. New Jersey requires 20 weeks or a different earnings 

formula. Pennsylvania requires 16 weeks. The Washington rule requires 680 hours and one dollar of earnings. 
6

Regarding earnings, federal eligibility guidelines disregard a lump sum equal to the first 

$90 in earnings and one-third of other earnings up to the breakeven level of income, at which 

point the household has worked off TANF.7

For the present analysis, a key aspect of TANF eligibility is an administrative 

requirement that to qualify for additional cash public assistance, applicants must claim all other 

available sources of income, such as UI benefits. Rangarajan, Razafindrakoto, and Corson 

(2002) note that New Jersey had such a rule in place under AFDC and continued to apply it 

under TANF. Similar administrative rules are in place in Georgia, Ohio, and Michigan. These 

rules could lower measured UI eligibility rates among TANF-leaver UI applicants. Some 

persons with little expectation of qualifying for UI may be forced to jump this hurdle on their 

way back to TANF.

Each state sets its own earnings disregard rate and 

lump sum. Some states have adjusted parameters to permit continued support with household 

income at thresholds as high as four times the poverty level. TANF benefit levels across our 

cohorts are quite similar for Florida and Georgia, while being somewhat higher in Michigan and 

Ohio (Table 2.1). Breakeven levels of earnings are similar in Florida, Michigan, and Ohio but 

are lower in Georgia; the level in Georgia declines after four and eight months of continuous 

receipt of benefits. 

8

The TANF eligibility manual for the State of Michigan, Department of Human Services, 

states that “clients must apply for benefits for which they may be eligible ... refusal by a 

program group member to pursue a potential benefit results in group ineligibility” (State of 

Michigan 2007, PEM 270, pp. 1–6).9

Ohio administrative rules state that “the assistance group must apply for any monthly 

benefits to which it is entitled. Ineligibility to participate in OWF results if the assistance group 

 The Michigan manual specifically identifies UI as a 

potential source of cash payments to an unemployed person and lists instructions on how to file 

an application for UI. 

 7

Breakeven earnings are computed as the TANF benefit amount divided by (1−disregard rate) plus the 

lump sum disregard. 8

Program administrators suspect that TANF applicants with very low prior earnings might not be directed 

to UI if failure to qualify under UI monetary eligibility rules is highly likely. 9

Legal basis for this policy by the Michigan Department of Human Services is set forth in Michigan Public 

Act 280 of 1939, as amended. Also known as the Social Welfare Act. 
7

refuses to accept unconditionally available income (ODJFS 2007, p. 350).10

2.3 ES Eligibility and Services

 Ohio Works First 

(OWF) is the financial assistance portion of Ohio’s TANF program. Ohio Works First provides 

cash benefits to eligible needy families for up to 36 months. After 36 months, a family cannot 

receive additional cash assistance unless a time extension for benefit receipt is approved by the 

relevant County Department of Job and Family Services official. 

Public employment services in the United States are funded under the Wagner-Peyser 

Act, which established the U.S. Employment Service (ES) in 1933. Services provided by the ES 

are delivered in one-stop centers under the Workforce Investment Act (WIA), and are available 

free of charge to all job seekers. There are four main categories of ES services: 

1) Job referrals. Job interview referrals for job seekers, job vacancy listings for 

employers, and job developers to link job seekers with employers; 

2) Job search assistance. Resume preparation help, job search workshops, job clubs, 

labor market information, and job search plans; 

3) Assessment services. Job interview practice, employment counseling, and testing for 

job aptitudes and of job skills; and 

4) Training referrals. Referrals to federally or state-funded training for job skills or job 

search skills. Depending on available funding, some ES offices also offer supportive services for 

job search or training including temporary assistance with transportation or child care costs. 

Data available for analysis of ES use in this study are limited to Wagner-Peyser funded services 

during limited time periods in Georgia and Ohio.

2.4 Previous Research on Use of UI by TANF Leavers

Some research was done on the interaction between cash social assistance and UI before 

enactment of TANF. Based on employment patterns of women who received Aid to Families 

with Dependent Children (AFDC) and then left the program, Spalter-Roth, Hartmann, and Burr 

(1994) estimate that only about 10 percent of those who left AFDC for employment would 

actually collect UI benefits if they subsequently became jobless. Kaye (1997) estimates that 

 10Administrative policy requiring claiming of UI is stated in the Ohio Department of Job and Family 

Services (ODJFS) Cash Assistance Manual. 
8

about 13 percent of women leaving AFDC would actually draw a UI benefit, while about 35 

percent would accumulate sufficient earnings and work experience to qualify for UI (Table 2.2). 

Table 2.2 Previous Estimates for Welfare Leavers of Percentage Rates for UI Monetary and Nonmonetary 

Eligibility and UI Benefit Receipt (%)

Authors Samples

Monetary

UI eligible

Nonmonetary 

UI eligible

Beneficiary

of UI

Gustafson and 

Levine (1997)

National Longitudinal Survey of Youth aged 

14 to 22 in 1979. Data from 1979 to 1994 on 

43,913 job separations, including 4,213 by 

AFDC leavers. 

Up to 85 About 25 About 10

Vroman (1998) Estimates based on 1996 UI state wage and 

earnings, state UI recipiency and eligibility 

rates, assuming part-time minimum wage 

employment. 

— — Up to 20

Holzer (2000) Estimates based on 1997–1999 employment 

and earnings of hired welfare recipients in a 

survey of 3,000 employers in four large 

American cities.

— — Under 30

Kaye (2001) Survey of Program Dynamics data for the 

year 2000 on 56,000 persons. Simulated UI 

eligibility for those at risk of welfare receipt.

81 36 25

Rangarajan, 

Razafindrakoto, and 

Corson (2002) 

New Jersey data from the Work First NJ 

evaluation tracking 2,000 TANF beneficiaries 

in the 18 months starting July 1997.

75 40 56

Rangarajan, and 

Razafindrakoto 

(2004)

National Evaluation of Welfare-to-Work 

grants in metropolitan counties in five states. 

TANF leavers, September 1999 to August 

2000. Each state sample ranged in size from 

1,000 to 15,000.

90 — —

NOTE: — = not available.

Gustafson and Levine (1997) examined leavers from AFDC using data from the National 

Longitudinal Survey of Youth and estimated the proportion that would satisfy simulated UI 

monetary eligibility in data spanning from 1979 to 1994. Among those leaving welfare, they 

estimate that 70 to 85 percent would satisfy the monetary eligibility requirements for UI, and 

about 25 percent of women with job separations would satisfy nonmonetary eligibility 

requirements for UI. Since only a fraction of UI-eligible unemployed actually draw UI 

compensation, they estimate about 10 percent of AFDC leavers would get UI pay. They assert 

that the provision mandating that separations be “involuntary” would prevent most workers from 

gaining UI eligibility, and conjectured that the UI system will provide little additional support to 

the safety net following welfare reform. 
9

Vroman (1998) examined average earnings rates and UI eligibility requirements across 

states at the time TANF was introduced. He reported that about 35 percent of all unemployed 

persons receive UI benefits, and that that rate is higher at the beginning of recessions and in 

states with weaker eligibility criteria. He speculated that compared to others in the workforce, 

TANF leavers are likely to have higher jobless rates, lower wage rates, higher rates of voluntary 

quits and discharges, and lower availability for full-time work. Vroman inferred that among 

jobless TANF leavers only about 20 percent will qualify for UI benefits. He warns that UI is not 

likely to evolve in ways that broaden eligibility for TANF leavers, and that UI is “likely to play a 

very limited support role for TANF leavers.” (p. 5)

Holzer (2000) examined earnings and employment of TANF leavers in the years 

immediately following introduction of TANF. Based on his survey of 3,000 employers in four 

large American cities between 1997 and 1999, he asserts that more claimants would qualify 

monetarily for UI than in earlier years. Nonetheless, Holzer warns that several remaining 

barriers to UI eligibility could be significant. These include: job separations due to voluntary 

quits and dismissals for cause, lack of availability for full-time work, and employment in 

informal jobs or others not covered by UI.

Kaye (2001) estimates the likelihood that workers at risk of public assistance receipt 

would meet UI monetary and nonmonetary eligibility requirements in 2000. Her analysis uses 

the nationally representative Survey of Program Dynamics (SPD). Annual waves of SPD 

include responses from about 16,000 households and 56,000 persons. She is able to simulate UI 

eligibility for all but the nine least populated states. She does not analyze welfare leavers, but 

rather those at risk of welfare receipt. She estimates that 81 percent of at-risk workers would 

meet the UI monetary eligibility requirements in 1998. Among these, Kaye estimates that less 

than three-quarters had a qualifying job separation, 40 percent were not available for full-time 

work, and 64 percent were unlikely to be both available and actively seeking work. The net 

result is a beneficiary rate of about 25 percent among likely UI applicants. 

Rangarajan, Razafindrakoto, and Corson (2002) studied the extent to which former 

welfare recipients are likely to be eligible for UI, and the rate at which those who leave TANF 

for work file UI claims. Their analysis is based on data from the Work First New Jersey (WFNJ) 

evaluation, which tracks a representative statewide sample of 2,000 TANF recipients who were 

paid benefits during the first 18 months after TANF started in July 1997. They found that nearly 
10

75 percent of those who left TANF for employment would be monetarily eligible for UI at some 

point during the first two years after TANF exit. Among these, about 40 percent would satisfy 

nonmonetary eligibility requirements. UI ineligibility for nonmonetary reasons would be twice 

as high among TANF leavers as for all other UI claimants in New Jersey. This could be driven 

in part by the TANF requirement to claim UI before returning to TANF. Overall about one-third 

of TANF leavers would potentially satisfy both monetary and nonmonetary eligibility criteria. 

Among TANF leaver UI applicants about 56 percent received some cash UI benefits. Potential 

monthly UI benefits for this group would average about $866 per month, compared with 

maximum monthly TANF benefits of $424 for a family of three. Relaxing monetary eligibility 

requirements would modestly raise the share of TANF leavers who would qualify. Relaxing the 

weeks of work requirement has a greater effect than relaxing the earnings requirement. 

Alternative base-period rules that consider more recent earnings would allow TANF leavers to 

qualify for UI faster, but the proportion qualifying would not increase much.

Sanford et al. (2003) did a correlation analysis of factors related to UI monetary 

eligibility for a sample of 3,085 of the 3,097 welfare recipients in Wisconsin who left TANF for 

work in the second quarter of 1998. They found that monetary eligibility for UI had a strong 

positive correlation with being a high school graduate and having access to child care and 

medical insurance coverage. They estimated a negative correlation between UI monetary 

eligibility and the presence of a child less than 6 years of age. 

Rangarajan and Razafindrakoto (2004) study the extent to which former welfare 

recipients would have monetary eligibility for UI if they were to experience a qualifying job 

separation. They used data from the national evaluation of the Welfare-to-Work (WtW) Grants 

Program. The sample included those who left TANF for employment between September 1999 

and August 2000. Employment and earnings were tracked for eight calendar quarters after 

TANF exit. Sample sizes ranged between 1,000 and 15,000 welfare recipients who exited 

welfare for work in five sites in Maricopa County, Arizona; Cook County, Illinois; Baltimore 

County, Maryland; Philadelphia County, Pennsylvania; and Tarrant County, Texas. They 

estimated that 90 percent would potentially attain UI monetary eligibility in the two-year period 

after TANF exit, while between 50 and 80 percent would qualify in any quarter during the twoyear period. The rate of potential monetary eligibility was estimated to rise with the time from 

TANF exit to first jobless experience. Rates of expected monetary eligibility were not sensitive 
11

to changes in program eligibility rules. Changes examined included adjustments to consider 

more recent earnings when determining benefit eligibility, and relaxing rules requiring 

availability for full-time work. 

2.5 Previous Research on Use of ES by TANF Leavers

Before this study, there has not been research on the use of ES by TANF leavers in the 

United States. However, there has been recent research in Canada on use of public employment 

services by leavers from social assistance. A Canadian field experiment found that financial 

incentives for leaving welfare alone did not result in significant reductions in dependency, but 

when combined with reemployment services the financial incentives yielded large and 

statistically significant reductions in rates of welfare receipt (Robins, Michalopolous, and Foley 

2008).

2.6 TANF Leaver Samples for Analysis

Samples of TANF leavers were created from administrative data on recipients of public 

cash assistance in each of the states. The samples include those voluntarily leaving TANF for 

employment. Samples exclude those who fail to receive a TANF cash payment because of a 

sanction or other involuntary reason. Because of the periodicity of some administrative data 

needed for the study, the time unit for analysis is the calendar quarter. Because of the uneven 

time periods for data available across the states, the sample time frames differ across the states. 

However, data for all four states include TANF exits in all four calendar quarters of 2000. 

Leaving TANF for employment is defined as: making zero cash TANF payment to the 

assistance unit in a calendar quarter (with no sanction) and having earnings of at least $100 in 

that calendar quarter or the next quarter.

Key concepts in the analysis are as follows:

TANF exit for employment is defined as making zero cash TANF payment to the 

assistance unit in a calendar quarter and having earnings of at least $100 in that calendar quarter 

or the next quarter. The zero payment must not be due to a sanction.

Employment is defined as earnings of at least $100 in a calendar quarter. This definition 

is the same as that applied by the Social Security Administration when measuring the duration of 

insured employment to determine eligibility for retirement benefits.
12

Unemployment is defined as a calendar quarter with earnings of less than $100.

All three of these concepts are measured using UI administrative records on earnings as 

reported quarterly by employers. The definition of unemployment is a very strict one and 

certainly understates the true extent of experience with joblessness in the samples. 

The state-specific TANF exit time frames (quarters) are as follows: 

Florida: 1998Q4 through 2001Q1 (10 quarters), 

Georgia: 1996Q2 through 2001Q4 (23 quarters), 

Michigan: 2001Q1 through 2002Q1 (5 quarters), and 

Ohio: 2000Q2 through 2001Q3 (6 quarters). 

Each of these time frames permits observation of UI claims and possible return to TANF 

for at least 12 calendar quarters after TANF exit. The sample sizes for TANF leavers analyzed 

are listed in Table 2.3. The four-state total sample size is 322,038.

Table 2.3 TANF Exit for Employment, Subsequent Unemployment, and UI Application across States Based 

on the First Observed Spell of TANF Receipt, Exit, and New Unemploymenta

State (quarters)

TANF

leavers

Newly unemployed UI applicants

Number Share Number Share

Florida (10) 59,726 46,245 0.774 18,309 0.396

Georgia (23) 152,278 123,701 0.812 27,257 0.220

Michigan (5) 27,172 21,043 0.774 4,776 0.227

Ohio (6) 82,860 62,200 0.751 11,116 0.179

Total 322,038 253,189 0.786 61,458 0.243 a For all persons included in this table, we are able to observe twelve quarters subsequent to TANF exit for the occurrence of 

new unemployment. Relative to the quarter of new unemployment, we are further able to observe UI application, eligibility, and 

benefit receipt for UI applications that occur from one quarter before new unemployment through three quarters after. In 

subsequent analysis attempting to determine the impact of UI application, eligibility, and benefit receipt on the likelihood of 

return to TANF or employment, sample sizes will be smaller for two primary reasons: 1) persons who applied for UI may have 

done so after the period for which we are able to observe reemployment or TANF outcomes, and 2) persons may have returned to 

TANF or had interim employment prior to UI application. In both cases, those persons will be excluded from the outcome 

analysis.

Samples are based on TANF exit for employment during the following intervals: 

Florida: 1998Q4 through 2001Q1 (10 quarters), 

Georgia: 1996Q2 through 2001Q4 (23 quarters), 

Michigan: 2001Q1 through 2002Q1 (5 quarters), and 

Ohio: 2000Q2 through 2001Q3 (6 quarters). 

These time frames permit observation of UI claims and possible return to TANF for at least 12 calendar quarters after TANF exit. 
13

0.60

0.65

0.70

0.75

0.80

0.85

0.90

0.95

1.00

Unemployment Rate within 12 Qtrs

Year and quarter of TANF exit

Florida Georgia Michigan Ohio

Figure 3.1 Rates of New Unemployment among TANF Leavers by State over Time

3. USE OF UI BY TANF LEAVERS

Use of UI is examined among newly unemployed TANF leavers. The definition of 

unemployment as given above is a calendar quarter with less than $100 in earnings. We examine 

the rates of new unemployment and of UI application, eligibility, and benefit receipt. As a guide 

to understanding these rates we also compare the observable characteristics of UI applicants, 

eligible applicants, and beneficiaries with others. 

3.1 Unemployment Among TANF Leavers

Rates of new unemployment among TANF leavers in our four-state samples are reported 

in Table 2.3. Within twelve quarters of leaving TANF the sample proportions experiencing new 

unemployment range from 75.1 percent in Ohio to 81.2 percent in Georgia. The average across 

all four states is 78.6 percent. 

The higher average rate of new unemployment for Georgia is partly due to the longer 

time frame of data availability for Georgia. Figure 3.1 shows unemployment rates among 

Georgia TANF leavers exceeding 85 percent in quarters before 1999 dating back to 1996. In 

quarters including and after 1999 unemployment rates among TANF leavers in Georgia are 

lower than in the other states. Unemployment rates for TANF leavers in 2000 and 2001 average 

around 75 percent across the four states of Florida, Georgia, Michigan, and Ohio. 
14

0.10

0.15

0.20

0.25

0.30

0.35

0.40

0.45

0.50

UI Application Rate

Year and quarter of TANF exit

Florida Georgia Michigan Ohio

Figure 3.2 UI Application Rates among Newly Unemployed TANF Leavers,

by State over Time

Among all newly unemployed TANF leavers the sample percentages for important 

observable characteristics are as follows: 37.0 percent young (ages 18–24), 57.8 percent prime 

age (25–44), 81.9 percent female, 35.7 percent white, 59.2 percent African American , 4.2 

percent Hispanic, average quarterly earnings in the three years before TANF exit of $1,788, 

average quarterly earnings from TANF exit to new unemployment of $2,222, and the average 

number of calendar quarters from TANF exit to new unemployment of 4.1 quarters.11

3.2 Applications for UI by Unemployed TANF Leavers

Among those identified as newly unemployed we examine patterns of application for UI 

benefits. Table 2.3 lists UI application rates for each of the TANF leaver cohorts in the first 

three years after TANF exit. Analysis of involvement with UI is restricted to those leaving 

TANF for employment that subsequently experience unemployment. UI application rates range 

from 17.9 percent in Ohio to 39.6 percent in Florida, with a mean of 24.3 percent in the sample 

pooled across all four states. 

The rates of UI applications for newly unemployed TANF leavers by the quarter of 

TANF exit are presented graphically in Figure 3.2. This graph provides some evidence that UI 

application rates were higher for those leaving TANF around the time of the 2001 economic 

 11Sample proportions and means of all newly unemployed TANF leavers imputed from figures for UI 

applicants and nonapplicants summarized in Table 3.1. 
15

recession in the United States. Rates of UI application for Florida tend to be much higher than in 

other states, while UI application rates in Ohio are lower. The lower Ohio application rates may 

be due to the stricter monetary eligibility requirements in that state.

3.2.1 Observable characteristics of UI applicants

To understand the demographics for our analysis cohorts we summarize characteristics of 

UI claimants among TANF leavers. Consistent data on demographic characteristics are only 

available on a limited number of variables. These data are gathered in applications for benefits 

compiled in UI administrative records. Table 3.1 presents sample percentages on subgroups by 

age, sex, race, and educational attainment, as well as the mean value for UI base-period 

earnings.12

Among TANF leavers who are newly unemployed, the average age for UI applicants is 

higher than for nonapplicants. Age data for this contrast is available for Georgia, Michigan, and 

Ohio. For Florida, age data is only available for UI applicants who have an average age of 31.9 

years, which is higher than UI applicant TANF leavers in any of the other three states. Based on 

three broad age categories, the distributions for the TANF leaver cohorts are similar across the 

states, with the bulk of the samples coming from the middle range, aged 25 to 44. 

Since our analysis cohorts are samples of TANF leavers, it is not surprising to see female 

percentages among UI applicants ranging from 76.9 in Michigan to 83.5 in Ohio. Regarding UI 

application, women are more likely to apply in Ohio, but less likely in Michigan. 

Among newly unemployed TANF leavers, African Americans are more likely to apply 

for UI in Georgia, Michigan, and Ohio. While data is not available for this contrast in the 

Florida sample, a sizeable percentage of UI applicants are African American. 

Data available on dependents of household heads indicates that the great majority of 

TANF leaver households include three persons, two of whom are children, including one under 

the age of six. TANF recipients with children are more likely to apply for UI after becoming

newly unemployed. The effect is most pronounced in the Ohio sample but is still statistically 

significant in the samples for Georgia and Michigan.

 12The UI base period is typically the first four of the five calendar quarters immediately preceding the 

quarter of UI application for benefits. For those who fail this first test, UI eligibility can be evaluated alternatively 

based on the four most recent calendar quarters. See Appendix Table A.1 for comparisons to Table 3.1 based on the 

full list of available variables from UI administrative records. These variables include the sample proportions newly 

unemployed in each calendar year and quarter. 
16

Table 3.1 Characteristics of Newly Unemployed TANF Leavers by UI Application Status and State (All Differences Significant

90 Percent Confidence Level Unless Otherwise Noted by “#”)

Florida Georgia Michigan 

UI applicant status Yes No Yes No Yes No 

description 18,309 27,936 Diff. 27,257 96,444 Diff. 4,776 16,267 Diff. 

Age at TANF exita 31.9 30.0 29.1 0.86 29.7 27.6 2.12 

 18–24 0.219 0.308 0.369 −0.061 0.326 0.459 −0.133 

 25–44 0.720 0.633 0.572 0.061 0.623 0.498 0.125 

 45+ 0.062 0.059 0.059 −0.000# 0.050 0.042 0.008 

Gender, male 0.187 — — — 0.231 0.187 0.043 

Gender, female 0.813 — — — 0.769 0.813 −0.043 

Race, whiteb 0.255 0.206 0.300 −0.094 0.475 0.529 −0.054 

Race, black 0.432 0.781 0.683 0.098 0.466 0.417 0.049 

Race, hispanic 0.287 0.009 0.011 −0.003 0.044 0.039 0.005 

Adults on case at exit 1.20 1.25 −0.05 1.08 1.10 −0.02 

Children < age 18 on case at exit 1.95 1.90 0.05 1.64 1.57 0.07 

Children < age 6 on case at exit 0.88 0.90 −0.02 0.74 0.79 −0.05 

“Base” period earningsc ($) 11,880 8,239 3,641 9,946 7,640 2,307 12,531 7,260 5,271 

High quarter earnings in “base”c ($) 4,233 3,266 967 3,851 3,096 755 4,620 2,988 1,632 

“Base” earnings < $10,000c ($) 0.485 0.688 −0.204 0.615 0.753 −0.138 0.438 0.754 −0.316 

Qtrs., exit to new unemployment 5.4 4.1 1.30 4.6 3.8 0.78 5.0 3.7 1.24 

Qtrs. employed before exit (of 12) 5.7 5.6 0.16 6.0 5.4 0.59 7.2 6.1 1.10 

Avg. qtrly earnings before exit ($) 2,197 1,994 203 1,916 1,721 195 2,501 1,818 683 

Avg. qtrly earnings after exit ($) 3,037 2,244 793 2,683 2,154 529 3,272 1,960 1,312 

Multiple employers exit-to-unempl. 0.520 0.480 0.040 0.465 0.422 0.043 0.445 0.384 0.060 

Qtrs. employed before unempl. (of 12) 8.7 7.7 1.04 8.4 7.4 0.99 9.3 7.8 1.45 

NOTE: — = not available. a In Florida, because there are no characteristic data available to define age at TANF exit, we initially start with age as of BYB, which is 33.3 years. 

from TANF exit to new unemployment is 5.4 quarters for UI applicants (or 1.4 years), the average age at TANF exit is set at 31.9 years. b Because Florida uses Hispanic and non-Hispanic distinctions in its race categories (White, non-Hispanic, White and Hispanic, Black non-Hispanic

not strictly comparable to the other states. c Defined for both applicants and nonapplicants as the first four of the five quarters preceding the quarter of new unemployment.
17

For all of the four states analyzed, newly unemployed TANF leavers with higher UI base 

period earnings are observed to have higher rates of UI application. Furthermore, TANF leavers 

with base period earnings of less than $10,000 are significantly less likely to apply for UI. 

Higher average quarterly earnings are also associated with higher rates of UI application. This is 

true for average quarterly earnings either before or after TANF exit. 

Prior employment stability is associated with higher rates of UI application. Those who 

had more calendar quarters with some employment between the time they left TANF and became 

newly unemployed were more likely to apply for UI. Similarly, those having more calendar 

quarters with some employment before leaving TANF were more likely to apply for UI when 

they did become newly unemployed. 

3.2.2 Observable characteristics of UI nonapplicants

Characteristics of the three-quarters of newly unemployed TANF leavers who do not 

apply for UI mirror those of UI applicants. The average age for UI nonapplicants is lower, and 

UI nonapplicants include a higher proportion of females, include a lower proportion of African 

Americans, are somewhat less likely to have children, include a higher proportion with UI baseperiod earnings of less than $10,000, and had prior employment in fewer calendar quarters. 

3.2.3 Models of UI application

Linear probability models were estimated to measure the influence of observable factors 

on UI application. Computations were done on each of the separate state samples as well as on 

combined samples pooled across the states. The models have the general form

(1) y = Xβ + RΓ + Tθ + ε 

where 

y is a vector of data on newly unemployed TANF leavers which takes the value 1 for 

persons who applied for UI benefits within 12 calendar quarters of TANF exit and 

0 otherwise. 

X is a matrix of data on variables for observable individual characteristics of newly 

unemployed TANF leavers. These variables include age, gender, race, number of 

children, educational attainment, marital status, measures of prior earnings and 

employment, and prior industry of employment.

β is a conformable vector of parameters estimated on observable individual characteristic 

variables.
18

R is a matrix of data on variables representing characteristics of the regional labor 

market. For models estimated on data pooled across the states, state dummy 

variables were included.13

Γ is a conformable vector of parameters estimated on variables for characteristics of the 

regional labor market at the time of TANF exit for employment. 

T is a matrix of data on indicator variables representing the year and calendar quarter of 

TANF exit for employment.

θ is a vector of parameters estimated on variables representing the year and calendar 

quarter of TANF exit for employment. 

ε is a vector representing an unobserved random variable summarizing unmeasured 

differences across individuals in the samples. It is assumed to be normally 

distributed with mean zero, constant variance, and zero covariance across 

observations. 

State-specific regression models of UI application reported in Table 3.2 concisely 

summarize the influence of observable individual and regional characteristics on rates of UI 

application among newly unemployed TANF leavers. These linear probability models of UI 

application were estimated on all newly unemployed TANF leavers in each state. Results for 

two pooled models estimated on data combined across all four states are reported in Table 3.3. 

Since there were a limited number of explanatory variables available for Florida, a second 

pooled model with more independent variables was estimated on data from the other three states.

Parameter estimates from state-specific models of UI application suggest that within 

these groups of newly unemployed TANF leavers, applications are more likely for those who are 

older, who are African American, who had relatively higher earnings in the time between leaving 

TANF and becoming newly unemployed, and who had more calendar quarters with some 

employment in that same time frame or in other earlier periods.14

 13 For the state dummy variable and other categorical variables in the UI application models, variables for 

the full set of categories for each independent variable are included. The full set of dummy variables (zero, one) 

defining an exhaustive partition of categories for an independent variable (e.g., the categories male and female 

exhaustively partition the independent variable sex) can be included in a regression model if linear restrictions are 

imposed to force the weighted mean of each category within the independent variable to be equal to zero. The 

weights are the share of each category within the sample. Parameter estimates on such categorical variables are 

interpreted relative to the mean effect of the independent variable on the dependent variable. 14 A full set of dummy variables (zero, one) defining an exhaustive partition of categories for an 

independent variable (e.g., the categories male and female exhaustively partition the independent variable sex) can 

be included in a regression model if a linear restriction is imposed to force the weighted mean of each category 

within the independent variable to be equal to zero. The weights are the share of each category within the sample. 

Parameter estimates on such categorical variables are interpreted relative to the mean effect of the independent 

variable on the dependent variable.
19

Table 3.2 State-Specific Linear Probability Models of UI Application among Newly Unemployed TANF 

Leavers

Independent variablea Florida Georgia Michigan Ohio

Intercept 0.374** 0.172** 0.122** −0.058**

Age 24 or Less

Age 25–44

Age 45 or Older

−0.024**

0.016**

−0.017**

−0.027**

0.021**

0.008

−0.032**

0.020**

0.036**

Race, white

Race, black

Race, Hispanic

Race, other

−0.055**

0.022**

−0.052**

−0.051**

−0.033**

0.038**

0.017

−0.017

−0.034**

0.036**

0.009

−0.007

Base-period earnings ($1,000)

High quarter earnings ($1,000)

Base-period earnings < $10,000

Amount of last TANF payment ($100)

0.013**

−0.005**

−0.063**

−0.000

0.007**

−0.006**

−0.023**

−0.001*

0.007**

0.011**

−0.116**

−0.001

0.007**

0.005**

−0.005

−0.002**

Qtrs., TANF exit to new unemployment

Qtrs. of employment before TANF exit (of 12)

Avg. qtrly. earnings ($1,000), 3 yrs. before exit

Multiple employers, any qtr. exit to unempl.

0.013**

−0.006**

−0.022**

−0.038**

0.005**

0.001**

−0.003**

−0.002

0.001

0.004**

−0.002

−0.004

0.006**

0.002**

0.001

−0.014**

Gender, male

Gender, female

−0.011

0.003

0.006

−0.001

Education, less than high school

Education, high school graduate/GED

Education, some college

Education, bachelor degree or higher

−0.001

0.003

−0.015*

0.022

Marital status, single

Marital status, married

Marital status, divorced/abandoned

Marital status, separated

Marital status, widow/widower

−0.000

0.006

0.005

−0.012**

0.042

Number of adults on case at exit

Number of children under age 18 at exit

−0.035**

0.001

−0.008

−0.003

−0.011**

0.001

Classified as disabled before exit

Classified as ineligible grantee before exit

Classified as incapacitated before exit

Received local office deferral before exit

Had sanction before end of TANF

On multiple cases at TANF exit −0.052

−0.004

−0.064**

−0.006

−0.007

−0.001

Agriculture, forestry, fishing

Mining

Utilities

Construction

Manufacturing

Wholesale trade

Retail trade

Transportation, warehousing

Information

Finance and insurance 

Real estate, rental, leasing

Professional, scientific, technical

Company/enterprise management

0.032**

0.048

−0.032

0.049**

0.101**

0.035**

−0.008**

−0.008

0.009

0.004

0.026**

0.027**

−0.082

0.063

−0.080

−0.093

0.117**

0.048**

0.044*

−0.006

0.025

−0.016

0.057**

0.017

0.010

0.107

Admin., support and waste mgmt. 0.017** 0.027**
Table 3.2 (continued)

20

Independent variablea Florida Georgia Michigan Ohio

Educational services

Health care/social assistance

Art, entertainment, recreation

Accommodation and food services

Other services (except public admin.)

Public administration

Unclassifiable

Missing

−0.101**

−0.036**

0.003

−0.037**

−0.012*

−0.038**

0.005

—

−0.109**

−0.024**

−0.021

−0.026**

0.018

−0.044

0.056

−0.015

Unemployment rate at TANF exit

Chg. in unempl. rate, exit-to-new unempl.

0.013**

0.018**

0.013

0.016

0.035**

0.019**

Sample size 42,094 113,272 19,745 57,630

R-square 0.0674 0.0561 0.1229 0.0660

Adjusted R-square 0.0670 0.0543 0.1171 0.0654

NOTE: * Parameter estimate statistically significant at the 90 percent confidence level in a two-tailed test; ** parameter 

estimate statistically significant at the 95 percent confidence level in a two-tailed test. — = not available. a All models include variables for year and quarter of TANF exit. Models for Georgia, Michigan, and Ohio further include 

variables for geographic location of residence.

Pooled linear probability regression models were estimated on a somewhat reduced set of 

independent variables. A pooled model, presented in Table 3.3, was estimated on data from all 

four states excluding variables for age, race, family size, and local unemployment measures. 

These variables were not available for UI nonapplicants in Florida. A model including variables 

for age, race, family size, and local unemployment measures was estimated on data pooled from 

Florida, Michigan, and Ohio. Both models also included indicator variables for state and time 

fixed-effect estimates. These models suggest that even after controlling for observable 

differences in characteristics, UI application rates are highest in Florida and lowest in Ohio. This

result may be due to disaster UI claims caused by hurricanes in Florida and by the strict 

monetary eligibility requirements in Ohio.15

3.3 Monetary Eligibility for UI

 Relative to TANF leavers in earlier calendar 

quarters, UI application rates were higher for those leaving TANF in 2000 and 2001. 

Unemployment for these TANF leavers was more likely to occur during or soon after the 

recession of 2001.

Among TANF leavers who become newly unemployed and apply for UI, Table 3.4 

reports that 87.2 percent were initially UI-eligible based on monetary requirements in the sample 

 15 Disaster UI claims in Florida resulting from active hurricane seasons may have resulted in increased 

claims for regular UI benefits.
21

21

Table 3.3 Pooled Linear Probability Models of UI Application among Newly Unemployed TANF Leavers

Description

States pooled,

all four

states pooled,

omit Florida

Intercept 0.230** 0.125**

Age 24 or Less

Age 25–44

Age 45 or Older

−0.027**

0.018**

−0.003

Race, white

Race, black

Race, Hispanic

Race, other

−0.042**

0.026**

−0.001

−0.021*

Base-period earnings ($1,000)

High quarter earnings ($1,000)

Base-period earnings < $10,000

Amount of last TANF payment ($100)

0.008**

0.002*

−0.071**

−0.001*

0.004**

0.011**

−0.074**

−0.001**

Qtrs., TANF exit to new unemployment

Qtrs. of employment before TANF exit (of 12)

Avg. qtrly. earnings ($1,000), 3 yrs. before exit

Multiple employers, any qtr. exit to unempl.

0.010**

0.000

−0.001*

−0.015**

0.006**

0.002**

0.001*

−0.006**

Number of adults on case at exit

Number of children under age 18 at exit

−0.020**

0.000

Unemployment rate at TANF exit

Chg. in unempl. rate, exit-to-new unempl.

0.021**

0.019**

Florida

Georgia

Michigan

Ohio

0.102**

0.026**

−0.073**

−0.100**

0.048**

−0.069**

−0.070**

TANF exit in 1st quarter

TANF exit in 2nd quarter

TANF exit in 3rd quarter

TANF exit in 4th quarter

−0.001

−0.003*

−0.002

0.006

−0.002

−0.001

−0.001

0.004**

Year of TANF exit = 1996

Year of TANF exit = 1997

Year of TANF exit = 1998

Year of TANF exit = 1999

Year of TANF exit = 2000

Year of TANF exit = 2001

Year of TANF exit = 2002

−0.014**

−0.023**

−0.021**

−0.010**

0.007**

0.024**

0.016*

−0.022**

−0.032**

−0.026**

0.001

0.016**

0.021**

0.006

Sample size 232,791 190,665

R-square 0.0673 0.0518

Adjusted R-square 0.0671 0.0516

NOTE: * Parameter estimate statistically significant at 90 percent confidence level in a two-tailed test; ** parameter estimate 

statistically significant at the 95 percent confidence level in a two-tailed test.
22

Table 3.4 Summary of UI Application, Eligibility and Benefit Receipt Across Statesa

State (quarters)

UI 

applicants

Monetarily eligible Nonmonetarily eligible UI beneficiary

Number Share Number Share Number Share

Florida (10) 18,309 17,331 0.947 8,406 0.459 11,095 0.606

Georgia (23)b 27,257 24,294 0.891 13,100 0.481 13,389 0.491

Michigan (5) 4,776 4,687 0.981 1,874 0.392 3,097 0.648

Ohio (6)c 11,116 7,256 0.653 3,498 0.315 3,339 0.300

Total 61,458 53,568 0.872 26,914 0.438 30,920 0.503 a For all persons included in this table, we are able to observe twelve quarters subsequent to TANF exit for the occurrence of 

new unemployment. Relative to the quarter of new unemployment, we are further able to observe UI application, eligibility, and 

benefit receipt for UI applications that occur from one quarter before new unemployment through three quarters after. In 

subsequent analysis attempting to determine the impact of UI application, eligibility, and benefit receipt on the likelihood of 

return to TANF or employment, sample sizes will be smaller for two primary reasons: 1) persons who applied for UI may have 

done so after the period for which we are able to observe reemployment or TANF outcomes, and 2) persons may have returned to 

TANF or had interim employment prior to UI application. In both cases, those persons will be excluded from the outcome 

analysis. b In Georgia, the number of persons ineligible because they quit or were discharged, and therefore the total number of persons 

nonmonetarily eligible to receive UI benefits, was imputed using the rates of quit or discharge based on a sample of 26,610 UI 

applicants for whom job separation reason data were available. Because of this, the pooled rate of non-monetary eligibility 

observed in this table for TANF-leaver UI applicants will differ from the rate reported in Table 3.13, since the weights are 

determined by the individual state’s share of UI applications (for Georgia, 27,757 in this table, compared with 26,610 in Table 

3.13). c Ohio nonmonetary eligibility is based on claims filed on or before December 31, 2002. Claims beginning in 2003 did not 

include the characteristic data needed to define nonmonetary eligibility. Persons who were nonmonetarily eligible to receive 

benefits must not have had a quit or discharge job separation reason and must not have been in the UI agency, nonmonetary 

determination file. Therefore, based on 8,513 UI claims filed before year end 2002, 2,679 were nonmonetarily eligible for 

benefits. That rate (0.315) was then applied to the 11,116 UI applicants observed in the full range of Ohio data to estimate the 

total number of nonmonetarily eligible UI applicants. Because of this, the pooled rate of nonmonetary eligibility observed in this 

table will differ from the rate reported in Table 3.13, since the weights are determined by the individual state’s share of UI 

applications (for Ohio, 11,116 in this table, compared with 8,513 in Table 3.13).

pooled across the four states of Florida, Georgia, Michigan, and Ohio. The state rates ranged 

from 65.3 percent for Ohio to 98.1 percent for Michigan. The lower monetary eligibility rate for 

Ohio results from the requirement for 20 or more weeks of work with average earnings of at least 

27.5 percent of the state average weekly wage in UI-covered employment. 

In the period examined, the rates of UI monetary eligibility among TANF leavers who 

become newly unemployed and apply for UI benefits is relatively stable within the separate 

states except for Ohio (Figure 3.3). For that state the monetary eligibility rate was about 70 

percent for TANF leavers in mid-2000 and dropped below 55 percent for TANF leavers in the 

fourth quarter of 2001. That pattern was not observed in any of the other three states despite the 

early 2001 economic recession. 

3.3.1 Observable characteristics of monetarily eligible UI applicants

Among TANF leavers who are newly unemployed and apply for UI benefits, Table 3.5 

contrasts observable characteristics of monetarily eligible UI applicants to others. Compared to 
23

23

0.50

0.55

0.60

0.65

0.70

0.75

0.80

0.85

0.90

0.95

1.00

Monetary Validity Rate

Year and quarter of TANF exit

Florida Georgia Michigan Ohio

Figure 3.3 Rates of Monetary Eligibility among TANF Leaver UI Applicants by State over Time

other newly unemployed TANF leaver UI applicants, those with monetarily eligible applications 

for benefits tend to have larger sample proportions in the male and prime-age group. They also 

have higher levels of educational attainment, more calendar quarters with earnings before UI 

application, and higher levels of UI base period earnings. 

3.3.2 Simulated UI monetary eligibility for unemployed TANF-leaver UI nonapplicants

For the three-quarters of newly unemployed TANF leavers who do not apply for UI, if 

we use UI wage records on earnings it is possible to estimate what the monetary eligibility rate 

would have been if they had applied for UI. Based on earnings in the first four of the five 

calendar quarters completed before the quarter of new unemployment, monetary eligibility was 

checked for UI nonapplicants in the four state samples. To be monetarily eligible, earnings in 

that simulated UI base period must have exceeded the minimum required earnings for the states 

in the relevant years. The requirement that earnings be in at least two of the four base period 

calendar quarters was also applied. Table 3.6 provides a state-by-state comparison of simulated 

monetary eligibility rates for actual UI applicants with their actual monetary eligibility rates. 

There is close concordance for three of the four states, but there is a large discrepancy between 

simulated and actual rates observed for Ohio. This is because it is impossible to simulate the 20 

weeks of work rule required for monetary eligibility in Ohio. Simulating monetary eligibility for 
24

Table 3.5 Characteristic Comparison of Newly Unemployed TANF-Leaver UI Applicants Having Monetarily Eligible UI Claim

Leaver UI Applicants

Description

Florida Georgia Michigan 

Monetarily

eligible

(n = 17,331)

All other

claimants

(n = 978)

Monetarily

eligible

(n = 24,294)

All other 

claimants

(n = 2,963)

Monetarily 

eligible

(n = 4,687)

All other 

claimants

(n = 89)

M

(n 

Age at BYB 33.4** 30.9 31.6** 30.2 31.4 32.5 

 18–24 0.213** 0.319 0.225** 0.275 0.256* 0.148 

 25–44 0.724** 0.640 0.738** 0.710 0.670** 0.815 

 45+ 0.063** 0.041 0.036** 0.015 0.074 0.037 

Gender, male 0.188** 0.160 0.084** 0.070 0.235 0.154 

Gender, female 0.812** 0.840 0.916** 0.930 0.765 0.846 

Race, white 0.255 0.252 0.192** 0.229 0.473 0.547 

Race, black 0.429** 0.482 0.783** 0.743 0.467 0.395 

Race, Hispanic 0.289** 0.245 0.009 0.010 0.053 0.047 

Race, other 0.026 0.021 0.016 0.018 0.015 0.035 

Education, less than high school 0.359** 0.418 0.275** 0.349 0.258** 0.539 

Education, HS grad/GED 0.494** 0.456 0.533** 0.504 0.467** 0.315 

Education, some college 0.114 0.107 0.171** 0.133 0.240** 0.101 

Education, bachelor’s or higher 0.034** 0.019 0.021** 0.014 0.035 0.045 

Base-period earnings ($) 11,892** 2,497 9,926** 2,779 11,311** 5,836 

High quarter earnings in base ($) 4,118** 1,636 4,981** 2,040 4,425** 3,026 

Base earnings < $10,000 0.485** 0.979 0.626** 0.977 0.524** 0.865 

Multiple employers, any base qtr. 0.510** 0.450 0.505** 0.374 0.507 0.427 

Qtrs., TANF exit to unemployment 5.5** 3.8 4.8** 2.4 5.0** 3.7 

Consec. qtrs. employed before exit 3.1** 1.7 3.1** 1.4 7.3** 4.8 

Qtrs. employed before BYB 8.5** 6.2 8.6** 5.4 8.9** 6.2 

NOTE: * Mean for monetarily valid claimants significantly different from the mean for all other claimants at the 90 percent confidence level in a two

monetarily valid claimants significantly different from the mean for all other claimants at the 95 percent confidence level in a two-tailed test. See App

detail.
25

25

UI nonapplicants suggests that an average rate of 69.9 percent would have satisfied monetary 

eligibility requirements in the four states. That rate is 17.3 percentage points or 20 percent lower 

than the monetary eligibility rate among TANF-leaver UI applicants. However, these 

computations suggest that a large number of unemployed TANF leavers could have qualified for 

UI had they filed applications for benefits.

3.4 Nonmonetary Eligibility for UI

Among TANF leavers who become newly unemployed and apply for UI, 43.8 percent are 

initially eligible for UI based on nonmonetary conditions of their job separation in the sample 

pooled across all four states (Table 3.4). The state nonmonetary eligibility rates range from 31.5 

percent for Ohio to 48.1 percent for Georgia. 

The rates of UI nonmonetary eligibility among TANF leavers who become newly 

unemployed and apply for UI benefits tended to be stable within states during recent years 

(Figure 3.4). There was a gradual drop over time in the nonmonetary eligibility rate in Georgia, 

followed by a recent rise in the rate. Time series for the other states are relatively short, but the 

nonmonetary eligibility rates do not vary much within states by the calendar quarter of TANF 

exit. It is notable from Figure 3.4 that Michigan tends to have only an average rate of nonmonetary eligibility among TANF leavers across all the states, while Michigan has the highest 

rates of monetary eligibility (Figure 3.3).

Table 3.6 Actual and Simulated Monetary Eligibility by UI Application Status among Newly Unemployed 

TANF Leavers

State

UI applicants UI nonapplicants

Actual UI

applicants

Actual monetarily 

eligibility from UI 

administrative data

Simulated

monetarily

eligible from

wage dataa

Did not apply

for UI

Simulated

monetarily

eligible from

wage dataa

Florida 18,309 0.947 0.925 27,936 0.666

Georgiab 27,244 0.891 0.922 96,457 0.768

Michigan 4,776 0.981 0.947 16,267 0.654

Ohio 11,116 0.653 0.860 51,084 0.599

Total 61,445 0.872 0.913 191,744 0.699 a Based on earnings in the first four of the five quarters prior to new unemployment, which may not correspond to the quarter 

of BYB in the case of UI applicants. Wages must be present in at least two quarters, and the statutory minimum base period 

earnings required is then evaluated to determine monetary eligibility. b The sample size of UI applicants for Georgia has 14 fewer observations than the number shown in Table 2.3. We have 12 

quarters of wage records for every TANF leaver in the sample, and for this handful of observations we have administrative data 

on UI claims for one or two quarters more than three years after TANF exit. 
26

26

3.4.1 Observable characteristics of nonmonetarily eligible UI applicants

Among TANF leavers who are newly unemployed and apply for UI benefits, Table 3.7

contrasts observable characteristics of nonmonetarily eligible UI applicants with others. 

Compared to other newly unemployed TANF-leaver UI applicants, those with nonmonetarily 

eligible claims for benefits tend to have larger sample proportions in the male group. However, 

there is no clear pattern across states on other observable characteristics associated with UI 

nonmonetary eligibility. In all states, those with a bachelor’s degree or higher educational 

attainment are more likely to be nonmonetarily eligible for UI, but the difference is not 

statistically significant in all states. Additionally, Hispanics have statistically significantly 

higher rates of nonmonetary eligibility in three of the four states. 

Overall, there is some consistency in the pattern of characteristics associated with nonmonetary eligibility in three of the four states. However, for Ohio the pattern is distinctly 

different from the other three states. In Ohio, nonmonetary eligibility is more likely for younger 

and older UI applicants compared to those of prime working age (25–44). Furthermore, in Ohio

nonmonetary UI eligibility is more likely for those with the lowest educational attainment, lower

0.30

0.35

0.40

0.45

0.50

0.55

Nonmonetary eligibility rate

Year and quarter of TANF exit

Florida Georgia Michigan Ohio

Figure 3.4 Rates of Nonmonetary Eligibility among TANF Leaver UI 
27

Table 3.7 Characteristic Comparison of Newly Unemployed TANF-Leaver UI Applicants Having Nonmonetarily Eligible UI C

separations under UI law) with All Other TANF-Leaver UI Applicants

Description

Florida Georgia Michigan 

Nonmonetarily

eligible

(n = 17,331)

All other

applicants

(n = 978)

Nonmonetarily

eligible

(n = 12,789)

All other

applicants

(n = 13,821)

Nonmonetarily

eligible

(n = 1,874)

All other

applicants

(n = 2,902)

N

Age at BYB

 18–24 

 25–44 

 45+ 

35.0**

0.173**

0.742**

0.085**

31.8

0.258

0.700

0.042

32.1**

0.211**

0.749**

0.041**

30.8

0.248

0.727

0.026

32.5**

0.207**

0.705**

0.087**

30.7

0.284

0.651

0.065

Gender, male 

Gender, female 

0.230**

0.770**

0.150

0.850

0.089**

0.911**

0.075

0.925

0.318**

0.682**

0.181

0.819

Race, white 

Race, black

Race, Hispanic 

Race, other 

0.211**

0.402**

0.360**

0.027

0.292

0.458

0.224

0.025

0.178**

0.793**

0.010**

0.019**

0.209

0.770

0.008

0.013

0.515**

0.415**

0.062**

0.019*

0.449

0.499

0.047

0.012

Education, less than high school 

Education, HS grad/GED 

Education, some college 

Education, bachelor’s or higher 

0.387**

0.460**

0.111

0.043**

0.341

0.519

0.115

0.025

0.263**

0.539**

0.173**

0.024**

0.299

0.521

0.163

0.017

0.261

0.470

0.231

0.039

0.266

0.461

0.241

0.032

Base-period earnings ($)

High quarter earnings in base ($)

Base-period earnings < $10,000

Multiple employers, any base qtr.

11,817**

4,160**

0.488**

0.477**

11,029

3,837

0.531

0.532

9,465**

3,939**

0.651**

0.486*

8,889

3,633

0.677

0.500

11,103

4,552**

0.540

0.487**

11,269

4,299

0.525

0.518

Qtrs., TANF exit to unemployment

Consec. qtrs. employed before exit

Qtrs. employed before BYB

5.5**

3.0*

8.4

5.4

3.1

8.4

4.6

3.0**

8.3

4.6

2.8

8.2

4.7**

7.3**

8.7**

5.1

7.1

9.0

NOTE: * Nonmonetarily eligible mean significantly different from the mean for all other UI applicants at the 90 percent confidence level in a two-tai

eligible mean significantly different from the mean for all other UI applicants at the 95 percent confidence level in a two-tailed test. See Appendix Ta

a Ohio nonmonetarily eligible data limited to claims on or before December 31, 2002
28

28

rates of employment and earnings before TANF exit, and lower rates of employment and 

earnings between TANF exit and new unemployment. 

3.4.2 Reasons for failure of UI nonmonetary eligibility requirements

The two main reasons for failure to meet nonmonetary eligibility requirements are 

voluntarily quitting a job and employer discharge for cause. In addition to reasons like poor job 

performance, habitual tardiness, and unexplained absences, employer discharge is justifiable for 

improper on-the-job behavior such as theft, vandalism, substance abuse, or improper interactions 

with coworkers. To learn if there are differing factors associated with the separate causes of 

failing nonmonetary eligibility, we examine the observable characteristics associated with each 

of the two main reasons for nonmonetary UI denial.

3.4.3 Failure of UI nonmonetary eligibility requirements because of job quits

Among newly unemployed TANF leavers who apply for UI in our total sample pooled 

across four states, 17.3 percent quit their prior job. For this sample, Table 3.8 contrasts 

observable characteristics of those initially denied UI because of quitting their prior job with 

other UI applicants. Compared to other newly unemployed TANF-leaver UI applicants, those 

who quit tend to be made up of larger sample proportions of females and whites. Contrasts on 

supplementary characteristics to Table 3.8 are presented in Appendix Table A.4 suggest that 

newly unemployed TANF leavers have higher quit rates from the industry groups of retail trade, 

hotels and restaurants, and health care, as well as from jobs in service occupations. 

3.4.4 Failure of UI nonmonetary eligibility requirements due to employer 

discharge

Among newly unemployed TANF leavers who apply for UI in our total sample pooled 

across four states, 33.1 percent were fired from their previous job. For this sample, Table 3.9

contrasts observable characteristics of those initially denied UI because of being fired from their 

previous job with other UI applicants. Compared to other newly unemployed TANF-leaver UI 

applicants, those who were fired tend to have larger sample proportions of employment in the 

industries of retail trade; finance, insurance and real estate; health care; and hotels and 

restaurants (Table A.5). There is no consistent pattern of correlation with dismissal for other

factors among this group. In Florida, Georgia, and Michigan, newly unemployed TANF leavers 

in the youngest age group (18–24) are more likely to be fired. In Ohio there is a statistically
29

Table 3.8 Characteristic Comparison of Newly Unemployed TANF-Leaver UI Applicants Who Quit Prior Employment with A

UI Applicants

Description

Florida Georgia Michigan 

Quit prior

employment

(N = 3,675)

All other

applicants

(N = 14,364)

Quit prior

employment

(N = 4,628)

All other

applicants

(N = 21,982)

Quit prior

employment

(N = 831)

All other

applicants

(N = 3,945)

e

Age at BYB 31.4** 33.8 30.4** 31.7 31.6 31.4 

 18–24 0.281** 0.203 0.265** 0.222 0.250 0.255 

 25–44 0.677** 0.730 0.709** 0.743 0.670 0.672 

 45+ 0.041** 0.067 0.026** 0.034 0.080 0.072 

Gender, male 0.131** 0.200 0.065** 0.085 0.193** 0.243 

Gender, female 0.869** 0.800 0.935** 0.915 0.807** 0.757 

Race, white 0.312** 0.241 0.226** 0.188 0.488 0.472 

Race, black 0.418** 0.436 0.752** 0.787 0.449 0.469 

Race, Hispanic 0.241** 0.298 0.007 0.009 0.051 0.053 

Race, other 0.029 0.025 0.014 0.016 0.025** 0.013 

Education, less than high school 0.331** 0.370 0.306** 0.277 0.271 0.262 

Education, HS grad/GED 0.534** 0.481 0.530 0.530 0.457 0.466 

Education, some college 0.105* 0.115 0.149** 0.172 0.235 0.237 

Education, bachelor’s or higher 0.029 0.034 0.015** 0.022 0.036 0.035 

Base-period earnings ($) 10,486** 11,618 8,367** 9,334 10,954 11,258 

High quarter earnings in base ($) 3,662** 4,066 3,427** 3,855 4,214** 4,437 

Base-period earnings < $10,000 0.562** 0.499 0.707** 0.655 0.557 0.526 

Multiple employers, any base qtr. 0.567** 0.492 0.512** 0.489 0.572** 0.492 

Qtrs., TANF exit to unemployment 5.2** 5.5 4.5* 4.6 5.1 5.0 

Consec. qtrs. employed before exit 3.1 3.0 2.8 2.9 7.0** 7.3 

Qtrs. employed before BYB 8.3** 8.4 8.2 8.2 8.8 8.9 

NOTE: * Mean for persons who quit prior employment significantly different from all other applicants at the 90 percent confidence level in a two-tail

who quit prior employment significantly different from all other applicants at the 95 percent confidence level in a two-tailed test. a

Data for Ohio limited to UI claims filed on or before December 31, 2002.
30

Table 3.9 Characteristic Comparison of Newly Unemployed TANF-Leaver UI Applicants Discharged from Prior Employment 

Leaver UI Applicants

Description

Florida Georgia Michigan 

Discharged

from prior

employment

(N = 6,228)

All other

applicants

(N = 12,081)

Discharged

from prior

employment

(N = 9,193)

All other

applicants

(N = 17,417)

Discharged

from prior

employment

(N = 2,071

All other

applicants

(N = 2,705)

D

f

em

(N 

Age at BYB 32.1** 33.9 31.0** 31.7 30.4** 32.2 

 18–24 0.244** 0.206 0.239** 0.225 0.298** 0.221 

 25–44 0.714 0.722 0.736 0.738 0.643** 0.694 

 45+ 0.042** 0.072 0.025** 0.037 0.059** 0.085 

Gender, male 0.161** 0.200 0.079 0.083 0.177** 0.279 

Gender, female 0.839 0.800 0.921 0.917 0.823** 0.721 

Race, white 0.281** 0.242 0.200* 0.191 0.433** 0.506 

Race, black 0.482** 0.407 0.779 0.782 0.518** 0.426 

Race, Hispanic 0.215** 0.324 0.008 0.009 0.045** 0.058 

Race, other 0.023* 0.027 0.013** 0.018 0.007** 0.021 

Education, less than high school 0.347** 0.370 0.295** 0.275 0.264 0.264 

Education, HS grad/GED 0.510** 0.483 0.517** 0.537 0.462 0.466 

Education, some college 0.121** 0.109 0.169 0.167 0.244 0.232 

Education, bachelor’s or higher 0.023** 0.038 0.019 0.021 0.031 0.038 

Base-period earnings ($) 11,349 11,412 9,152 9,173 11,397 11,057 1

High quarter earnings in base ($) 3,940* 4,008 3,737 3,803 4,333 4,447 

Base-period earnings < $10,000 0.513 0.511 0.661 0.666 0.513** 0.545 

Multiple employers, any base qtr. 0.511 0.504 0.494 0.493 0.496 0.513 

Qtrs., TANF exit to unemployment 5.5 5.4 4.6 4.6 5.2** 4.8 

Consec. qtrs. employed before exit 3.1 3.0 2.8** 2.9 7.2 7.2 

Qtrs. employed before BYB 8.5** 8.3 8.2 8.2 9.0** 8.8 

NOTE: *Mean for persons discharged from prior employment significantly different from the mean for all other applicants at the 90 percent confiden

** Mean for persons discharged from prior employment significantly different from the mean for all other applicants at the 95 percent confidence leve

a

Data for Ohio are based on UI claims filed on or before December 31, 2002.
31

31

significantly higher rate of dismissal for those with higher levels of base period employment and 

earnings.

3.4.5 Simulated UI nonmonetary eligibility for unemployed TANF-leaver UI nonapplicants

Nonmonetary eligibility rates cannot be directly estimated for UI nonapplicants among 

newly unemployed TANF leavers. However, these rates can be inferred from the 0.80 ratio of 

simulated monetary eligibility rates for nonapplicants relative to actual monetary eligibility rates 

observed among UI applicants. Assuming UI nonapplicants would satisfy nonmonetary 

eligibility requirements at a rate that is 80 percent of the 43.7 percent rate for UI applicants, then 

35 percent of UI nonapplicants would pass the nonmonetary eligibility requirement based on 

circumstances of their job separation. The true unobserved rate is probably somewhat lower, 

since a voluntary job quit or employer dismissal would be a major factor influencing the decision 

not to apply for UI benefits.

3.5 Receipt of UI

Among newly unemployed TANF leavers who are UI applicants, the overall proportion 

receiving UI benefits is 50.3 percent in our sample pooled across all four states (Table 3.4). The 

individual state rates of UI recipiency range from 30.0 percent for Ohio to 64.8 percent for 

Michigan. 

In Florida and Michigan, recipiency rates are much higher than initial nonmonetary 

eligibility rates, while in Georgia and Ohio recipiency rates are about the same level as 

nonmonetary eligibility rates. As described in footnote 3 above, even if the nonmonetary 

eligibility conditions are not satisfied at the time of UI application, it is possible for a claimant to 

draw UI later in that same benefit year if there is both sufficient additional earnings and a second 

job separation which satisfies the nonmonetary eligibility conditions. 

Over time, rates of UI benefit receipt among newly unemployed TANF leaver applicants 

are stable within states, but there are some noteworthy differences across states (Figure 3.5). 

Beneficiary rates in Florida and Michigan are typically over 60 percent for TANF leavers 

between 1999 and 2001, whereas the rate hovers around 50 percent for Georgia TANF leavers 

from 1996 through 2001, and the recipiency rate in Ohio is significantly lower averaging 30 

percent for TANF leavers from mid-2000 through late 2001. Ohio imposes a high monetary 
32

32

0.20

0.25

0.30

0.35

0.40

0.45

0.50

0.55

0.60

0.65

0.70

UI beneficiary rate

Year and quarter of TANF exit

Florida Georgia Michigan Ohio

Figure 3.5 UI Beneficiary Rates among TANF Leaver UI Applicants by State over Time

eligibility standard on applicants to qualify for UI after an initial nonmonetary denial of benefit 

entitlement.

3.5.1 Observable characteristics of UI beneficiaries

Among TANF-leaver UI applicants, the UI beneficiaries include higher proportions that 

are older, male, white, Hispanic, and have UI base period earnings that are, on average, more 

than $3,000 higher (Table 3.10). Contrasts for these groups by prior industry and occupation of 

employment in Appendix Table A.6 indicate that UI beneficiaries have statistically significantly 

higher proportions from the construction and manufacturing industries, and smaller proportions 

from retail trade, health care, and hospitality industries. Recipients of UI include statistically 

significantly higher proportions from management, professional, and production occupations, 

and smaller proportions from service occupations. 

Among TANF leavers, comparing UI beneficiaries and UI nonapplicants, beneficiaries 

include higher proportions that are older, male, African American, and have UI base period 

earnings that are on average more than $4,000 higher (Table 3.11). Contrasts for these groups by 

prior industry and occupation of employment in Appendix Table A.7 indicate that UI 

beneficiaries have statistically significantly higher proportions from the construction and 
33

Table 3.10 Characteristic Comparison of Newly Unemployed TANF-Leaver UI Applicants Who Are UI Beneficiaries with All O

Applicants

Description

Florida Georgia Michigan 

UI

beneficiary

(N = 11,095)

All other

applicants

(N = 7,214)

UI

beneficiary

(N = 13,389)

All other

applicants

(N = 13,868)

UI

beneficiary

(N = 3,097)

All other

applicants

(N = 1,679)

be

(N 

Age at BYB 34.6** 31.2 32.6** 30.4 32.0** 30.4 

 18–24 0.173** 0.289 0.190** 0.270 0.225** 0.309 

 25–44 0.749** 0.674 0.764** 0.707 0.696** 0.627 

 45+ 0.078** 0.037 0.046** 0.022 0.079* 0.064 

Gender, male 0.209** 0.153 0.092** 0.073 0.265** 0.176 

Gender, female 0.791** 0.847 0.908** 0.927 0.735** 0.824 

Race, white 0.246** 0.269 0.202** 0.191 0.502** 0.424 

Race, black 0.405** 0.475 0.772** 0.784 0.437** 0.519 

Race, Hispanic 0.322** 0.232 0.008* 0.011 0.055 0.048 

Race, other 0.027 0.024 0.018* 0.015 0.015 0.016 

Education, less than high school 0.351** 0.379 0.254** 0.310 0.240** 0.307 

Education, HS grad/GED 0.487* 0.500 0.535* 0.524 0.466 0.461 

Education, some college 0.120** 0.102 0.184** 0.152 0.256** 0.203 

Education, bachelor’s or higher 0.042** 0.019 0.027** 0.014 0.038* 0.029 

Base-period earnings ($) 12,606** 9,521 10,787** 7,659 11,829** 10,071 

High quarter earnings in base ($) 4,383** 3,373 4,284** 3,298 4,642** 3,953 

Base-period earnings < $10,000 0.443** 0.616 0.570** 0.752 0.491** 0.603 

Multiple employers, any base qtr. 0.488** 0.535 0.498** 0.484 0.507 0.503 

Qtrs., TANF exit to new unemployment 5.7** 5.0 5.0** 4.1 5.1** 4.8

Consec. qtrs. employed before exit 3.1** 2.9 3.2** 2.6 7.5** 6.8 

Qtrs. employed before BYB 8.6** 8.0 8.8** 7.7 9.1** 8.6 

NOTE: *Mean for UI beneficiaries significantly different from the mean for all other applicants at the 90 percent confidence level in a two-tailed test. 

beneficiaries significantly different from the mean for all other applicants at the 95 percent confidence level in a two-tailed test.
34

Table 3.11 Characteristic Comparison of Newly Unemployed TANF-Leaver UI Beneficiaries with Newly Unemployed TANF-L

Apply for UI Benefits (all differences in means significantly different from zero at the 90 percent confidence level un

Description

Florida Georgia Michigan 

UI

beneficiaries

(N = 11,095)

Did not apply

for UI

(N = 27,936)

UI

beneficiaries

(N = 13,389)

Did not apply

for UI

(N = 96,444)

UI

beneficiaries

(N = 3,097)

Did not apply

for UI

(N = 16,267)

b

(

Age at TANF Exit 31.0 29.6 30.3 27.6 

 18–24 0.266 0.369 0.294 0.459 

 25–44 0.658 0.572 0.651 0.498 

 45+ 0.076 0.059 0.055 0.042 

Gender, male — — 0.263 0.187 

Gender, female — — 0.737 0.813 

Race, white 0.212 0.300 0.502 0.529 

Race, black 0.775 0.683 0.437 0.417 

Race, Hispanic 0.008 0.011 0.055 0.047 

Race, other 0.005# 0.005 0.015# 0.015 

Base-period earningsa 13,153 8,239 11,493 7,640 13,252 7,260 

High qtr. earnings in base perioda 4,604 3,266 4,295 3,096 4,883 2,988 

Base earnings < $10,000a 0.415 0.688 0.519 0.753 0.396 0.754 

Multiple employers, any qtr. after exit 0.510 0.480 0.487 0.422 0.369 0.285 

Qtrs., exit to new unemployment 5.7 4.1 5.0 3.8 5.1 3.7 

Consecutive qtrs. employed before exit 3.1 2.7 3.2 2.5 3.8 2.6 

Qtrs. employed before unempl. (of 12) 9.0 7.7 8.9 7.4 9.4 7.8 

Qtrs. of employment before exit (of 12) 5.9 5.6 6.4 5.4 7.5 6.1 

Avg. qtrly. earnings before exit 2,392 1,994 2,128 1,721 2,689 1,818 

Avg. qtrly. earnings after exit 3,353 2,244 3,052 2,154 3,672 2,322 

NOTE: — = not available. a

The “base” period is defined for both applicants and nonapplicants as the first four of the five quarters preceding the quarter of new unemployment
35

35

manufacturing industries, and smaller proportions from retail trade, health care, and hospitality 

industries.

3.5.2 Amount and duration of UI benefit receipt among TANF leavers

Among TANF leavers who qualify for UI, the mean weekly benefit amount in the four-state 

pooled sample is $159, the mean entitled duration of UI benefits is 19.6 weeks, and on average 

74.6 percent of entitled UI benefits are drawn. Mean UI payments per TANF-leaver UI 

beneficiary over the full benefit year are $2,442, or a mean of 14.5 weeks of UI at the average 

weekly benefit amount for this sample. Benefit entitlements are fully exhausted by 53 percent of 

TANF-leaver UI beneficiaries. Among the four states examined, Michigan had the highest 

average weekly benefit amount, $201, the highest average number of weeks compensated in 

benefit years, 18.7, and the largest share of UI entitlements drawn, 84.3 percent. Among the four 

states, the highest exhaustion rate, 61.0 percent, was observed in Florida. The longest entitled 

duration, 25.4 weeks, and the lowest exhaustion rate, 38.3 percent, were in Ohio. The fewest 

average weeks, 12.6, and the smallest share of entitled compensation, 68.9 percent, were drawn 

by TANF-leavers in Georgia (Table 3.12). 

Table 3.12 UI Benefit Entitlement Receipta

Florida Georgia Michiganb Ohiob Pooled

Number of UI beneficiaries 11,079 13,387 3,092 3,339 30,897

Weeks of UI entitlement 18.4 18.4 22.1 25.4 19.6

Weeks of UI drawnc 14.7 12.6 18.7 18.0 14.5

Share of UI entitlement drawn 0.798 0.689 0.843 0.709 0.746

UI exhaustion rate 0.610 0.497 0.556 0.383 0.532

UI weekly benefit amount 165 145 201 157 159

UI compensation received in benefit year 2,528 1,959 3,806 2824 2,442

UI monthly amount receivedd 535 411 683 453 487

TANF monthly amount receivede 134 165 199 225 164

Ratio of mean UI-to-mean TANF 4.0 2.5 3.4 2.0 3.1 a To allow for complete benefit year information, claims must have occurred before the end of the second quarter of 2004 in 

Florida and the second quarter of 2005 for Georgia and Michigan. Benefit year data are complete for Ohio for all claims 

observed. b In Michigan and Ohio, the number of persons with nonzero UI compensation received in the benefit year is greater than the 

number of persons for whom we observe nonzero weekly benefit amount (WBA) or maximum benefits payable (MBP). 

Because of this, the sample size for which full-time equivalent weeks and exhaustion are observed is 3,091 for Michigan and 

3,218 for Ohio. c Full-time equivalent weeks of UI computed as total dollars of UI benefits received in the benefit year divided by the 

beneficiary's UI weekly benefit amount (WBA) for joblessness throughout a full week. d Computed as total dollars of UI received in the benefit year divided by maximum entitlement weeks of UI benefits times 

four.

e Computed as TANF payments received in the two calendar quarters completed prior to TANF exit, divided by six.
36

36

3.5.3 Simulated UI beneficiary rates for unemployed TANF-leaver UI nonapplicants

Applying the 80 percent nonapplicant/applicant ratio from monetary eligibility 

computations to the 50.3 percent beneficiary rate for UI applicants, we estimate that 40 percent 

of newly unemployed nonapplicants for UI could have received benefits had they applied. The 

actual beneficiary rate for this group would probably be somewhat lower due to unobserved 

actual rates of job quits and dismissals influencing the decision to apply for benefits. 

Nonetheless, within these four states there could have been nearly 90,000 additional UI 

beneficiaries among TANF leavers in the time period, of which 30,000 actually received UI 

compensation. 

3.6 TANF-Leaver UI Eligibility and Receipt Compared to Others

To put into perspective the rates of UI eligibility and benefit receipt by newly 

unemployed TANF-leaver UI applicants, we compare their outcomes to other UI applicants in 

the same time frames who were not recently involved with TANF. 

In the combined sample pooled across all four states, simple differences between the two 

groups reveal lower rates of monetary eligibility, nonmonetary eligibility, and benefit receipt for 

TANF leavers compared to all other UI applicants in the same time periods (Table 3.13). 

Controlling for observable characteristics of UI applicants by regression models in computing 

differences, we see that TANF leavers have higher rates of UI monetary eligibility, given their 

circumstances, than other UI applicants. However, rates of nonmonetary eligibility and benefit 

receipt remain lower for TANF leavers even after controlling for observable differences in 

characteristics between the two groups. 

Simple unadjusted comparisons of these outcomes across TANF leavers and other UI 

applicants are presented graphically in Figures 3.6, 3.7, and 3.8. The bar charts clearly reveal the 

similar rates of monetary eligibility in three of the four states, the exception being Ohio, where 

TANF leavers have a lower rate of monetary eligibility because of Ohio’s strict requirement for

prior earnings. Nonmonetary eligibility is lower for TANF leavers in all states, with the greatest 

difference being in Michigan. Rates of UI benefit receipt are lower in every state for recent 

TANF leavers compared to other UI applicants, with differences in the rate of receipt ranging 

from 10.5 percentage points in Florida to 36.5 percentage points in Ohio.
37

37

Table 3.13 UI Monetary Eligibility, Nonmonetary Eligibility, and Benefit Receipt Summary Comparing 

Newly Unemployed TANF-Leaver UI Applicants with Other UI Applicants Not Recently Involved 

with TANF

State

Eligibility Mean Simple Difference Regression Adjusted

Difference

Standard

Error t-statistic Difference

Standard

TANF Non-TANF Error t-statistic a

Monetary eligibility rate:

 Florida

 Georgia

 Michigan

 Ohio

0.947

0.891

0.981

0.653

0.906

0.903

0.985

0.844

0.041

−0.011

−0.004

−0.191

0.002

0.002

0.002

0.003

18.88

−6.32

−2.06

−55.22

0.052

0.028

0.000

−0.216

0.002

0.002

0.001

0.005

26.53

18.12

0.87

−41.60

 Pooled 0.872 0.913 −0.041 0.001 −36.07 0.036 0.001 38.27

Nonmonetary eligibility rate:

 Florida

 Georgia

 Michigan

 Ohiob

0.459

0.481

0.392

0.315

0.629

0.625

0.789

0.465

−0.170

−0.145

−0.396

−0.150

0.004

0.003

0.006

0.005

−47.42

−48.44

−66.96

−27.67

−0.105

−0.056

−0.187

−0.070

0.004

0.003

0.006

0.005

−28.95

−16.70

−33.72

−13.24

 Pooledc 0.442 0.654 −0.211 0.002 −106.73 −0.111 0.003 −43.03

UI beneficiary rate:

 Florida

 Georgia

 Michigan

 Ohio

0.606

0.491

0.648

0.300

0.711

0.690

0.866

0.665

−0.105

−0.199

−0.217

−0.365

0.003

0.003

0.005

0.004

−31.16

−70.67

−43.93

−81.29

−0.027

−0.028

−0.044

−0.233

0.003

0.003

0.004

0.010

−8.10

−9.02

−10.13

−23.04

 Pooled 0.503 0.732 −0.229 0.002 −127.42 −0.131 0.002 −77.81 a Non-TANF UI applicants do not appear at any point in the individual state TANF payments file, and the time period of UI 

claims selected for non-TANF persons is consistent with the periods in which TANF recipients leave TANF for employment and 

become newly unemployed. b For Ohio, nonmonetary eligibility rates are based on UI claims filed on or before December 31, 2002. New UI data received 

in December 2007 for claims filed in 2003 through 2005 did not include the characteristic data needed to define nonmonetary 

eligibility.

Failure of nonmonetary eligibility requirements is the main reason for lower rates of UI 

benefit receipt by TANF leavers in all four states. Rates of voluntary job leaving are higher for 

TANF leavers than for other UI applicants in all states examined (Table 3.13). In the pooled 

four-state sample of TANF-leaver UI applicants, 17.2 percent voluntarily quit their prior jobs, 

compared to only 9.4 percent of other UI applicants. The difference of 7.9 percentage points 

means TANF leavers quit at almost double the rate of other UI applicants not recently involved

with TANF (Table 3.14, Figure 3.9). A similar pattern is seen in rates of justifiable employer 

dismissals in the four-state pooled sample (Table 3.14, Figure 3.10). Among non-TANF leaver

UI applicants 19.2 percent were fired from their prior job, while 33.1 percent of TANF leavers 

had been fired. Controlling for observable characteristics, TANF leavers were 3.8 percentage 

points more likely to quit and 7.0 percentage points more likely to get fired than other similar UI 

applicants. That is, even when TANF leavers are compared to others having similar average age,
38

Figure 3.8 UI Benefit Receipt Rates for

TANF Leavers and Non-TANF UI Applicants

0.0

0.2

0.4

0.6

0.8

Florida Georgia Michigan Ohio Pooled

TANF Non-TANF

Figure 3.7 UI Nonmonetary Eligibility Rates for

TANF Leavers and Non-TANF UI Applicants 

0.0

0.2

0.4

0.6

0.8

Florida Georgia Michigan Ohio Pooled

TANF Non-TANF

Figure 3.6 UI Monetary Eligibility Rates for

TANF Leavers and Non-TANF UI Applicants

0.0

0.2

0.4

0.6

0.8

1.0

Florida Georgia Michigan Ohio Pooled

TANF Non-TANF
39

39

Table 3.14 Quit or Discharge Job Separations Resulting in Nonmonetary Ineligibility Comparing Newly 

Unemployed TANF-Leaver UI Applicants with Other UI Applicants Not Recently Involved with 

TANF

State

Separation mean Simple difference Regression adjusted difference

TANF Non-TANFa Difference

Standard

error t-statistic Difference

Standard

error t-statistic

Quit

 Florida 0.201 0.112 0.089 0.002 37.75 0.054 0.002 22.94

 Georgia 0.174 0.132 0.042 0.002 20.00 0.015 0.002 6.44

 Michigan 0.174 0.069 0.105 0.004 28.56 0.036 0.004 9.90

 Ohiob 0.105 0.041 0.063 0.002 29.18 0.033 0.002 14.53

 Pooledc 0.172 0.094 0.079 0.001 64.83 0.038 0.001 31.45

Fired/Discharged

 Florida 0.340 0.259 0.081 0.003 25.04 0.051 0.003 15.13

 Georgia 0.345 0.243 0.103 0.003 38.85 0.041 0.003 13.55

 Michigan 0.434 0.142 0.291 0.005 57.47 0.151 0.005 30.33

 Ohiob 0.209 0.081 0.127 0.003 42.65 0.070 0.003 23.30

 Pooledc 0.331 0.192 0.139 0.002 84.47 0.070 0.002 42.48 a Non-TANF UI applicants do not appear at any point in the individual state TANF payments file, and the time period of UI 

claims selected for non-TANF persons is consistent with the periods in which TANF recipients leave TANF for employment and 

become newly unemployed. b Estimates for Ohio are based on UI claims filed on or before December 31, 2002. New UI data received in December 2007 

for claims filed from 2003 through 2005 did not include the characteristic data needed to define quit and discharge or to derive 

regression-adjusted estimates. c Pooled, regression-adjusted estimates across states control for age, gender, education, race, employment history in the three 

years prior to filing, wages in the base period, weekly benefit amount, unemployment rate at filing, industry of prior employment, 

and year and quarter of filing.

Figure 3.9 Quit Rates Comparing TANF Leavers and Other UI 

 Applicants

0.00

0.05

0.10

0.15

0.20

Florida Georgia Michigan Ohio Pooled

TANF Non-TANF 
40

40

Figure 3.10 Rates of Discharge Comparing TANF Leavers and 

 Other UI Applicants

0.0

0.1

0.2

0.3

0.4

Florida Georgia Michigan Ohio Pooled

TANF Non-TANF 

gender, race, ethnicity, family size, prior earnings, and prior employment patterns; recent TANF 

leavers are still more likely to quit or get fired from their prior job. 

In the pooled sample of 30,775 TANF leavers who become UI beneficiaries, the average 

duration of receipt was 14.5 weeks over the benefit year, with an average exhaustion rate of 53.2 

percent. Compared to all other 6.5 million UI beneficiaries in the four states in the same time 

frame, TANF leavers on average drew 2.0 more weeks of UI and had an exhaustion rate 25.4 

percentage points higher (Table 3.15, Figures 3.11, 3.12). This same pattern was observed for 

each state separately, with the largest differences occurring in Michigan (5.8 weeks, 33.6 

percentage points) and smallest in Florida (0.5 weeks, 17.8 percentage points). Controlling for 

observable factors, TANF leavers were estimated to draw 3.0 weeks more, and to have exhausted 

their full benefit entitlements at a rate 17.2 percentage points higher than in an observationally 

comparable group of those not recently involved with TANF (Table 3.15).
41

41

Table 3.15 Comparison of UI Duration and Exhaustion among Newly Unemployed TANF-Leaver UI 

Beneficiaries with All Other UI Beneficiaries Not Recently Involved with TANFa

TANF leaver Non-TANF

Simple

difference

Adjusted

difference

Sample

size Mean

Sample

size Mean

Full-time equivalent weeks

 Florida

 Georgia

 Michiganb

 Ohiob

 Pooledc

11,079

13,387

3,091

3,218

30,775

14.7

12.6

18.7

18.0

14.5

1,439,720

1,727,387

1,962,584

1,335,721

6,465,412

14.2

10.4

12.9

13.0

12.5

0.5**

2.2**

5.8**

5.1**

2.0**

2.2**

1.9**

2.7**

4.7**

3.0**

Exhausted benefits

 Florida

 Georgia

 Michiganb

 Ohiob

 Pooledc

11,079

13,387

3,091

3,218

30,775

0.610

0.497

0.556

0.383

0.532

1,439,720

1,727,387

1,962,584

1,335,721

6,465,412

0.432

0.277

0.220

0.190

0.277

0.178**

0.220**

0.336**

0.193**

0.254**

0.151**

0.130**

0.173**

0.198**

0.172**

NOTE: **Difference significantly different from zero at the 95 percent confidence level in a two-tailed test. a To allow for complete benefit-year information, claims must have occurred before the end of the second quarter of 2004 in 

Florida and the second quarter of 2005 for Georgia and Michigan. Benefit year data are complete for Ohio for all claims 

observed. b In Michigan and Ohio, the number of persons with nonzero UI compensation received in the benefit year is greater than the 

number of persons for whom we observe nonzero weekly benefit amount (WBA) or maximum benefits payable (MBP). 

Because of this, the sample size for which full-time equivalent weeks and exhaustion are observed is 3,091 for Michigan and 

3,218 for Ohio. c Right-side variables in pooled models limited by characteristic data available for Ohio. The pooled model includes variables 

for the states, weekly benefit amount (WBA), WBA at maximum, base period earnings, employment history in the three years 

prior to UI filing and dummies for the year and quarter of UI filing. State-specific models for Florida, Georgia, and Michigan 

utilize a broader set of explanatory variables that vary state-to-state.

Figure 3.11 Average Weeks of UI Comparing TANF Leavers and 

 Non-TANF UI Beneficiaries

0.0

5.0

10.0

15.0

20.0

Florida Georgia Michigan Ohio Pooled

TANF Non-TANF
42

42

Figure 3.12 UI Benefit Exhaustion Rates Comparing TANF Leavers and

 Non-TANF UI Beneficiaries

0.0

0.1

0.2

0.3

0.4

0.5

0.6

Florida Georgia Michigan Ohio Pooled

TANF Non-TANF
43

43

4. PATTERNS OF SELF-SUFFICIENCY AND TANF DEPENDENCY

A goal of UI as social insurance is to prevent descent into poverty by those who are 

temporarily jobless through no fault of their own (Blaustein 1990, pp. 44–46). To investigate the 

importance of UI benefits in maintaining self-sufficiency after leaving TANF and becoming 

newly unemployed, we examine rates of future employment and return to TANF. The analysis is 

done for several different groups defined by their degree of involvement with the UI system. 

The core contrasts compare rates of return to employment and TANF for UI beneficiaries and 

nonbeneficiary UI applicants. Additionally, to better understand the 75 percent of newly 

unemployed TANF leavers who do not apply for UI benefits, contrasts between UI applicants 

and nonapplicants are also made. Further insight is gained about the importance of UI for selfsufficiency among TANF leavers by examining rates of being reemployed while remaining off 

TANF. Other outcomes in the matrix of reemployment and future TANF receipt are also 

examined.

4.1 Rates of Return to Employment and TANF

Among TANF leavers who become newly unemployed, the rates of return to 

employment and TANF are summarized in Table 4.1 for the sample pooled across all four states. 

The rows of this table show various subgroups defined in relation to their use of UI. Within 12 

quarters of their original exit from TANF, of the 241,719 newly unemployed TANF leavers in 

the four-state pooled sample, 77.5 percent return to employment and 36.5 percent return to 

TANF. Similar tables for each of the four states are given in Appendix A as Tables A.8 to A.11. 

Data summarized in these state tables are consistent with the pooled data and are presented in 

Figure 4.1. Compared to Florida and Georgia, rates of return to employment are lower and 

return to TANF higher in Michigan and Ohio. The data for analysis includes the fourth quarter 

2001 for all four states; in that quarter both unemployment rates and average TANF payments 

were somewhat higher in Michigan and Ohio than in the other two states.16

 16For Florida, Georgia, Michigan, and Ohio, first quarter 2000 total unemployment rates were 3.7, 3.5, 5.2, 

and 4.4, respectively, while insured unemployment rates were 1.2, 1.3, 3.7, and 2.4, respectively (USDOL, 2001). 

Average TANF payments for our samples by state are reported in Table 2.1 as $303, $280, $459, and $373, 

respectively. 

 
44

Table 4.1 Rates of Return to Employment and TANF among Newly Unemployed TANF Leavers Using 

Pooled Data from Florida, Georgia, Michigan, and Ohioa

Group

Sample

size

Returned to

employment

Returned to

TANF

Newly unemployed TANF leavers 241,719 0.775 0.365

UI applicants

 Monetarily eligible

 Monetarily ineligible

49,988

44,050

5,938

0.734

0.732

0.747

0.375

0.367

0.439

 Nonmonetarily eligibleb

 Quit prior employment

 Discharged/fired

20,882

8,204

15,904

0.753

0.729

0.745

0.321

0.431

0.422

 UI beneficiary

 Not UI beneficiary

25,411

24,577

0.742

0.726

0.301

0.452

 UI eligible and UI beneficiary

 UI eligible and not UI beneficiary

13,877

4,015

0.747

0.758

0.268

0.410

UI nonapplicants

 Pseudo monetarily eligiblec

 Pseudo monetarily ineligiblec

191,731

134,078

56,194

0.786

0.780

0.795

0.362

0.323

0.454

a The sample sizes for newly unemployed TANF leavers and UI applicants is smaller than reported in Table 2.3 because this 

table excludes people who applied for UI more than 12 quarters after TANF exit. Also excluded from these tabulations are 

persons who returned to TANF prior to UI application or had interim employment prior to filing for UI. b An exact count of the number of non-monetary ineligible UI applicants is not possible due to missing data for Georgia and 

Ohio. c Based on wage records for the first four of the five quarters prior to the quarter of new unemployment and the applicable UI 

law.

Among all TANF leavers in the sample pooled across the four states, UI applicants have 

a lower return to employment rate (73.4 percent) and a higher return to TANF rate (37.5) than 

for the full sample of all newly unemployed TANF leavers. For those who do not apply for UI 

the return to employment rate is somewhat higher (78.6) and the return to TANF rate is slightly 

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

Florida Georgia Michigan Ohio Pooled

Employed TANF

Figure 4.1 Rates of Return to Employment and TANF for All Newly 

Unemployed TANF Leavers
45

lower (36.2 percent). These unadjusted contrasts suggest that UI nonapplicants have stronger 

workforce attachments and better return-to-work prospects. We investigate this further below.

The rate of return to employment differs for each of the groups summarized as rows in 

Table 4.1, however there is very little variation across the groups. The lowest rate is 72.6 

percent among UI applicants who do not receive UI benefits. The highest rate of return to 

employment is 79.5 percent among UI nonapplicants who did not have sufficient base period 

earnings to be monetarily eligible for UI if they would have applied. 

4.1.1 Rates by UI monetary eligibility

Rates of return to employment and TANF differ between UI applicants with high and low 

prior earnings. The 12 percent of UI applicants who are monetarily ineligible for UI benefits 

return to employment at a rate 1.5 percentage points higher than monetarily eligible UI 

applicants, and they return to TANF at much higher rates too. Among monetarily ineligible UI 

applicants, 43.9 percent return to TANF, while 36.7 percent of monetarily eligible UI applicants 

do. 

We simulated UI monetary eligibility among nonapplicants to check whether the level of 

base period earnings may have influenced their decisions to return to employment or TANF. We 

call this simulated rate “pseudo monetary eligibility.” Among UI nonapplicants, those who are 

pseudo monetarily ineligible constitute 29.3 percent. Their return to employment rate is 1.5 

percentage points higher than for UI nonapplicants with higher preunemployment earnings, but 

their rate of return to TANF is 45.4 percent, compared to only 32.3 percent for pseudo 

monetarily eligible UI nonapplicants. This means that a sizeable share of newly unemployed 

TANF leavers with low preseparation earnings end up as working poor persons. They have 

earnings, but they also return to receiving TANF. 

4.1.2 Rates by UI nonmonetary eligibility

Applicants for UI who satisfy job separation conditions for nonmonetary eligibility return 

to employment at slightly higher rates than those failing to meet nonmonetary eligibility 

conditions, and they return to TANF at much lower rates. Compared to the rate for nonmonetary eligibles (32.1 percent), the rates of return to TANF among UI applicants disqualified 
46

for voluntary job quits (43.1 percent) and employer discharge for cause (42.2 percent) are much 

higher.17

4.1.3 Rates by UI benefit receipt

 

A central question of this research is the importance of UI in maintaining self-sufficiency 

from TANF through employment. Table 4.1 reports that among UI applicants, those who 

receive benefits return to employment at a higher rate (74.2 percent) than those who do not 

receive benefits (72.6 percent). Furthermore, UI beneficiaries return to TANF at a significantly 

lower rate (30.1 percent) than do nonbeneficiaries (45.2 percent). Graphical presentation of 

these contrasts is given for each of our four states in Figure 4.2 and for the pooled sample. 

Patterns in each state reflect those in the pooled sample on both outcomes, except that return to 

employment in Florida is slightly lower among UI beneficiaries than among nonbeneficiary UI 

applicants. 

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

Florida Georgia Michigan Ohio Pooled

UI Employed No UI employed UI TANF No UI TANF

Figure 4.2 Rates of Return to Employment and TANF for UI Beneficiaries and 

Nonbeneficiary UI Applicants

Comparing return to employment and TANF among UI applicants who either become 

beneficiaries or not may suffer from a problem of selection bias. Some factors associated with 

return to employment and TANF may be associated with UI benefit receipt. Econometric 

methods for selection bias correction can be applied. However, a simple reexamination of the 

data after regrouping observations may be equally enlightening. It is the case that not all fully 

eligible UI applicants end up drawing UI payments during their benefit year. For some this may 

 17Data on job separation reasons are not available for sizeable numbers of observations from Ohio and 

Georgia. 
47

result from returning to work too quickly to draw benefits. Alternatively, others who are fully 

eligible at application may subsequently fail to satisfy continuing eligibility rules when a week of 

compensation is claimed. 

In our sample pooled across the four states, we had sufficient data to identify 17,892 UI 

claimants who satisfied both monetary and nonmonetary eligibility criteria at the time of UI 

application (Table 4.1). Of these, 13,877, or 77.6 percent, received UI benefits. The following 

exercise exploits these facts in the data. Among UI applicants who are initially fully eligible for 

benefits, those who receive benefits return to employment at a slightly lower rate (74.7 percent) 

than those who do not receive benefits (75.8 percent). This result is driven mainly by patterns of 

reemployment in Florida (Table A.8). Within this group of fully eligible UI applicants, 

beneficiaries return to TANF at a significantly lower rate (26.8 percent) than do nonbeneficiaries 

(41.0 percent). This latter result is consistent across all four states (Tables A.8 to A.11). 

4.2 Models of Return to Employment and TANF

To measure the correlation between UI benefit receipt and return to employment or 

TANF, controlling for observable differences among UI applicants, linear probability models 

were estimated. Models for both binary outcomes take the same general form. For example, the 

models for return to employment have the form

(2) Y = Xβ + RΓ + Tθ + PΦ + ε 

where 

Y is a vector of data on newly unemployed TANF leavers who apply for UI, which takes 

the value 1 for persons who return to employment within 12 calendar quarters of 

prior TANF exit and 0 otherwise. Other variables and parameters are as defined 

in Equation (1). 

Two additional elements are included in Equation (2). These are defined as:

P is a matrix of variables specifying UI entitlements established by applicants for 

benefits. These variables include indicator variables for monetary eligibility, nonmonetary eligibility, benefit receipt, and whether the entitlement is at the state 

maximum weekly benefit amount. Also included are continuous variables for the 

UI weekly benefit amount (WBA), the maximum entitled length of benefit 

receipt, and the duration of benefit receipt in full-time equivalent weeks (total 

dollars of compensation divided by the WBA).

Φ is a conforming vector of regression parameters.
48

4.2.1 Outcomes associated with UI benefit receipt

Results from estimation of models on the samples pooled across all four states with 

binary-indicator dependent variables for return to employment and TANF are presented in Table 

4.2. Controlling for observable characteristics, receipt of UI is estimated to increase return to 

employment by 4.8 percentage points and reduce return to TANF by 10.5 percentage points 

compared to nonbeneficiary UI applicants. 

Regarding return to employment, other parameter estimates in the model suggest that UI 

applicants who are initially monetarily eligible are 2.4 percentage points more likely to return to 

employment. Furthermore, return to employment is more likely among TANF-leaver UI 

applicants who are younger, female, African American, had worked in more calendar quarters 

before applying for UI, had multiple employers in calendar quarters before UI application, and 

lived in areas with higher unemployment. The likelihood of return to employment was higher 

for those whose prior employment was in agriculture, manufacturing, administrative support, and 

hospitality industries. 

Control variables in the return to TANF model estimated on the pooled sample of UI 

applicants suggest that UI applicants who are initially monetarily eligible are 5.1 percentage 

points more likely to return to TANF, while UI applicants who are initially nonmonetarily 

eligible are 6.2 percentage points less likely to return to TANF. The net effect is that UI 

applicants fully eligible for UI at application are 1.1 percentage points less likely to return to 

TANF. Additionally, return to TANF is less likely among TANF leaver UI applicants who are 

older, male, not African American, had employment in more calendar quarters before UI 

application, and lived in areas with lower unemployment. The probability of return to TANF 

was higher for those whose prior employment was in the hospitality industry.

Indicator variables controlling for each of the four states were included in the models for 

employment and TANF reported in Table 4.2. These parameter estimates suggest that among 

newly unemployed TANF leaver UI applicants, being in Michigan and Ohio tended to increase 

the rate of return to employment, while being in Florida and Georgia tended to reduce the rate of 

return to TANF. State specific models give insight into how UI benefit receipt affected return to 

employment and TANF among UI applicants (Tables A.12 and A.13). Key results from the state
49

Table 4.2 Linear Probability Models of Return to Employment and TANF with Beneficiary Indicators 

among Newly Unemployed TANF-Leaver UI Applicants Using Pooled Data from Florida, Georgia, 

Michigan, and Ohio

Independent variables

Return to employment Return to TANF

Parameter

estimate

Standard

error t-Statistic

Parameter

estimate

Standard

error t-Statistic

Intercept 0.847 0.021 40.22 0.541 0.025 21.83

Monetarily eligible UI claim

Nonmonetarily eligible UI claim

0.024

0.004

0.008

0.004

3.20

0.95

0.051

−0.062

0.009

0.005

5.69

−13.05

Weekly benefit amount

WBA at maximum

Entitlement length

0.000

−0.024

0.001

0.000

0.010

0.001

3.45

−2.42

1.59

−0.000

−0.025

−0.002

0.000

0.011

0.001

−4.71

−2.17

−2.81

UI beneficiary 0.048 0.004 11.11 −0.105 0.005 −20.69

Age 24 or less

Age 25–49

Age 50 or older

0.067

−0.013

−0.137

0.003

0.001

0.008

19.67

−10.71

−16.72

0.051

−0.010

−0.097

0.004

0.001

0.010

12.69

−7.25

−10.07

Gender, male

Gender, female

−0.009

0.002

0.005

0.001

−1.86

1.86

−0.101

0.017

0.006

0.001

−16.99

16.99

Race, white

Race, black

Race, Hispanic

Race, other

−0.011

0.011

−0.032

−0.027

0.003

0.002

0.006

0.014

−3.51

6.87

−5.21

−1.98

−0.060

0.031

−0.023

−0.018

0.004

0.002

0.007

0.016

−16.05

16.33

−3.25

−1.10

Base-period earnings ($1,000)

Base-period earnings < $10,000

0.000

0.001

0.000

0.006

0.23

0.11

0.000

−0.002

0.000

0.007

1.56

−0.26

4 or fewer qtrs. of employment before BYB

5–8 qtrs. of employment before BYB

9–12 qtrs. of employment before BYB

−0.090

−0.009

0.025

0.006

0.003

0.002

−16.11

−3.19

12.85

−0.025

−0.004

0.008

0.007

0.003

0.002

−3.88

−1.14

3.41

Quarters from TANF exit to new unemployment

Had multiple employers in any base qtrs.

−0.046

0.053

0.001

0.004

−51.15

13.95

−0.030

0.013

0.001

0.004

−28.52

2.91

Unemployment rate, month of BYB

Unemployment rate ∆ BYB to BYE

Florida

Georgia

Michigan

Ohio

0.003

−0.003

0.003

−0.018

0.040

0.025

0.001

0.002

0.004

0.003

0.008

0.007

2.37

−1.14

0.80

−5.92

4.85

3.76

0.020

0.016

−0.022

−0.015

0.079

0.047

0.002

0.003

0.004

0.004

0.010

0.008

12.01

6.22

−5.19

−4.31

8.09

6.10

Agriculture, forestry, fishing

Mining

Utilities

Construction

Manufacturing

Wholesale trade

Retail trade

Transportation, warehousing

Information

Finance and insurance

Real estate, rental, leasing

Professional, scientific, technical

Company/enterprise management

Admin., support, and waste mgmt.

Educational services

0.078

0.001

0.116

0.008

0.012

−0.018

0.004

0.020

−0.005

−0.020

−0.030

−0.019

0.020

0.013

−0.001

0.019

0.090

0.074

0.011

0.005

0.010

0.005

0.012

0.014

0.013

0.015

0.013

0.032

0.004

0.013

4.07

0.01

1.56

0.74

2.47

−1.77

0.85

1.77

−0.36

−1.54

−2.00

−1.49

0.64

3.23

−0.05

−0.062

−0.037

−0.039

−0.008

0.002

−0.025

0.006

−0.008

−0.026

−0.026

−0.001

−0.037

0.001

−0.005

−0.048

0.023

0.106

0.087

0.013

0.006

0.012

0.005

0.014

0.017

0.015

0.018

0.015

0.037

0.005

0.015

−2.74

−0.35

−0.45

−0.62

0.39

−2.04

1.02

−0.60

−1.56

−1.74

−0.06

−2.49

0.04

−1.06

−3.24
Table 4.2 (Continued)

50

Independent variables

Return to employment Return to TANF

Parameter

estimate

Standard

error t-Statistic

Parameter

estimate

Standard

error t-Statistic

Health care/social assistance

Art, entertainment, recreation

Hotels and restaurants

Other services (except pub. admin.)

Public administration

Unclassifiable

Missing

0.001

0.012

0.023

−0.035

−0.043

−0.022

−0.102

0.005

0.021

0.005

0.011

0.013

0.024

0.009

0.11

0.54

4.71

−3.24

−3.35

−0.93

−12.04

0.005

−0.031

0.020

−0.011

0.002

0.008

0.030

0.006

0.025

0.006

0.013

0.015

0.028

0.010

0.87

−1.23

3.49

−0.86

0.13

0.28

3.01

Observations 45,165 45,165

R-Squared 0.1625 0.1088

Adjusted R-Squared 0.1610 0.1072

NOTE: This model was estimated including year:quarter indicator variables for time of new unemployment after 

TANF exit from 1996:2 to 2005:1. Four-state-specific models of this specification are reported in Appendix A as 

Tables A.12 to A.15.

specific models are summarized in Table 4.3. Among the four states, UI benefit receipt tends to 

increase return to employment more in Florida and Ohio, and has the greatest affect on reducing 

return to TANF in Ohio. 

4.2.2 Outcomes associated with UI benefit exhaustion

To investigate whether UI receipt affects return to employment or TANF differently for 

those who exhaust their UI entitlement compared to beneficiaries who do not exhaust their 

entitlement, models similar to Equation (2) were estimated. In these models, the single UI 

beneficiary variable was replaced by a pair of indicator variables, one for nonexhauster 

beneficiaries and the other for exhausters of their UI benefit entitlement. The pair of parameter 

estimates suggests that the effect of UI benefit receipt on return to employment declines with the 

duration of benefit receipt: among nonexhausters UI receipt increases return to employment by 

8.2 percentage points, whereas the effect for UI exhausters is only 1.7 percentage points (Tables 

4.3 and A.16).

The correlation between UI receipt and a reduced rate of return to TANF is greatly 

diminished for UI exhausters. In the sample pooled across the four states, UI receipt reduces 

return to TANF by 14 percentage points for nonexhausters but by only 7.2 percentage points for 

exhausters of their UI entitlement (Tables 4.3 and A.16).

4.2.3 Controlling for selection bias in the estimation sample

As mentioned above, estimating the probability of return to TANF on samples of UI 

applicants who either become beneficiaries or not may suffer from a problem of selection bias 
51

Table 4.3 Effects of UI Benefit Receipt and Exhaustion on Return to Employment and TANF among Newly 

Unemployed TANF-Leaver UI Applicants and UI-Eligible Applicants, Using Pooled Data from 

Florida, Georgia, Michigan, and Ohio

Independent variables

Return to employment Return to TANF

Parameter

estimate

Standard

error t-Statistic

Parameter

estimate

Standard

error t-Statistic

UI applicants

 UI beneficiaries, pooleda

 UI beneficiaries, Floridab

 UI beneficiaries, Georgiac

 UI beneficiaries, Michigand

 UI beneficiaries, Ohioe

0.048

0.060

0.048

0.023

0.091

0.004

0.009

0.006

0.015

0.011

11.11

6.93

7.71

1.52

8.67

−0.105

−0.079

−0.097

−0.094

−0.151

0.005

0.010

0.008

0.018

0.012

−20.69

−8.23

−12.98

−5.25

−12.63

 UI beneficiaries, not exhaustersf

 UI exhausters*f 

0.082

0.017

0.005

0.005

15.93

3.38

−0.140

−0.072

0.006

0.006

−23.22

−12.33

UI-eligible applicants

 UI beneficiariesg 0.047 0.008 6.18 −0.105 0.009 −12.21

 UI beneficiaries, not exhaustersh

 UI exhausters*h

0.085

0.015

0.008

0.008

9.95

1.89

−0.145

−0.071

0.010

0.009

−15.10

−7.62

NOTE: *Parameter estimates for UI exhausters significantly different from estimates for other UI beneficiaries who do not 

exhaust UI entitlement in both models at the 95 percent confidence level in a two-tailed test. a See Table 20 for all parameter estimates in the full model.

b See Appendix A, Table A.12 for all parameter estimates in the full model.

c See Appendix A, Table A.13 for all parameter estimates in the full model. d See Appendix A, Table A.14 for all parameter estimates in the full model.

e See Appendix A, Table A.15 for all parameter estimates in the full model.

f See Appendix A, Table A.16 for all parameter estimates in the full model. g See Appendix A, Table A.17 for all parameter estimates in the full model.

h See Appendix A, Table A.18 for all parameter estimates in the full model.

because the UI eligibility may be correlated with application for TANF. Restricting analysis to 

the sample of those fully eligible for UI at the time of application may be informative. As noted 

above, more than 20 percent of UI-eligible applicants in this sample did not receive UI benefits. 

The models for return to employment or TANF in the form of Equation (2) were reestimated on 

a sample pooled across the four states of persons who applied for UI and were initially fully 

eligible for benefits. That is, each newly unemployed TANF-leaver UI applicant in this new 

sample initially satisfied both monetary and nonmonetary eligibility conditions. The high rate of 

nonbenefit receipt in this sample provides sufficient statistical leverage for the exercise. 

Estimation of Equation (2) on these data yields additional support for the role of UI 

benefits supporting independence from TANF. Controlling for observable differences, UI 

beneficiaries were 4.7 percentage points more likely to return to employment and 10.5 

percentage points less likely to return to TANF than other UI-eligible applicants (Tables 4.3 and 

A.17). Furthermore, nonexhaustee beneficiaries were 8.5 percentage points more likely to return 

to employment and 14.5 percentage points less likely to return to TANF than nonbeneficiary UI-
52

eligible applicants (Tables 4.3 and A.18). Even UI exhausters were 1.5 percentage points more 

likely to return to employment and 7.1 percentage points less likely to return to TANF than nonUI beneficiary applicants (Tables 4.3 and A.18). 

4.3 Rates of Self-Sufficiency after New Unemployment

The above analysis of correlations between UI receipt and return to employment or 

TANF are enlightening. However, the variation in outcomes across many of these contrasts is 

neither large nor statistically significant. Particularly for employment. The rates of return to 

employment for all the UI applicant and eligibility groups examined in Table 4.1 range between 

72.6 and 78.0 percent. By interacting return to employment with return to TANF we get a much 

more informative view of how UI receipt is correlated with self-sufficiency—return to 

employment without return to TANF. In our sample of newly unemployed TANF leavers pooled 

across four states, 47.6 percent remain self-sufficient in the 12 calendar quarters after TANF exit.

In this section we examine the correlation of UI receipt with all of the four possible 

combinations of employment and TANF receipt outcomes as summarized in the two-by-two 

matrix given as Table 4.4. In addition to the concept of self-sufficiency (47.6 percent in our 

pooled sample), we label employed with return to TANF as working poor (29.9 percent), no 

employment with return to TANF as TANF-dependent (6.5), and no employment with no return 

to TANF as inactive (16.0). These pooled results are presented graphically in Figure 4.3, along 

with the separate state-specific rates. Among the four outcomes, the rate of self-sufficiency is 

the highest outcome in the pooled sample and in 3 out of 4 state samples. In Ohio, the rate of 

working poor is slightly higher than the rate of self-sufficiency.

Table 4.4 TANF-Employment Outcomes Matrix (% newly unemployed in the four-state pooled sample) 

No TANF TANF

Employment Self-sufficient

(47.6)

Working poor

(29.9)

No employment Inactive

(16.0)

TANF-dependent

(6.5)
53

0.0

0.1

0.2

0.3

0.4

0.5

0.6

Florida Georgia Michigan Ohio Pooled

Self-sufficient Working poor TANF-dependent Inactive

Figure 4.3 Rates of Self Sufficiency among All Newly Unemployed TANF Leavers

4.3.1 Self-sufficiency following UI benefit receipt

Among UI applicants who become reemployed, some remain off TANF and therefore 

self-sufficient while others work but also receive TANF benefits. Among those who become UI 

beneficiaries, 50.1 percent remain self-sufficient, compared to 36.4 percent of nonbeneficiary UI 

applicants (Table 4.5 and Figure 4.4). The rate of self-sufficiency among UI beneficiaries is 

higher than among all non-UI applicants (48.7 percent), but lower than pseudo monetarily 

eligible non-UI applicants (51.5 percent). Rates of self-sufficiency are particularly low for 

monetarily ineligible UI applicants (38.4 percent) and those who quit their prior job (37.8 

percent) (Table 4.5 for the pooled sample and Tables A.19 to A.22 for the state-specific results). 

Rates of working poor are lower for UI beneficiaries (24.1 percent) than for nonbeneficiary UI applicants (36.2 percent) (Figure 4.4). Compared to UI beneficiaries, rates of 

working poor are higher among UI nonapplicants (29.9 percent), UI applicants who quit their 

prior jobs (35.1 percent), and UI applicants who were fired from their prior jobs (33.8 percent) 

(Table 4.5). 

Among newly unemployed TANF leavers, UI beneficiaries have very low rates of 

returning to TANF dependency—6.0 percent (Figure 4.5). The rate of future TANF dependency 

is much higher among UI applicants who do not receive UI (9.0 percent), somewhat higher 

among UI nonapplicants (6.3 percent), much higher among those who quit their prior jobs (8.0 

percent) or got fired from their prior jobs (8.3 percent) (Table 4.5). 
54

Table 4.5 Rates of Self-Sufficiency and TANF Dependency among Newly Unemployed TANF Leavers Using 

Pooled Data from Florida, Georgia, Michigan, and Ohioa

Group

Sample

size

Employed and

no TANF

(self-sufficient)

Employed 

with TANF

(working 

poor)

TANF and no

employment

(TANFdependent)

No TANF 

and no 

employment

(inactive)

Newly unemployed TANF leavers 241,719 0.476 0.299 0.065 0.160

UI applicants

 Monetarily eligible

 Monetarily ineligible

49,988

44,050

5,938

0.433

0.440

0.384

0.301

0.292

0.363

0.075

0.074

0.076

0.191

0.193

0.177

 Nonmonetarily eligibleb

 Quit prior employment

 Discharged/fired

20,882

8,204

15,904

0.492

0.378

0.406

0.261

0.351

0.338

0.059

0.080

0.083

0.187

0.191

0.172

 UI beneficiary

 Not UI beneficiary

25,411

24,577

0.501

0.364

0.241

0.362

0.060

0.090

0.199

0.184

 UI-eligible and UI beneficiary

 UI-eligible and not UI beneficiary

13,877

4,015

0.534

0.416

0.213

0.341

0.054

0.069

0.199

0.173

UI nonapplicants

 Pseudo monetarily eligiblec

 Pseudo monetarily ineligiblec

191,731

134,078

56,194

0.487

0.515

0.417

0.299

0.265

0.379

0.063

0.058

0.075

0.151

0.162

0.129 a The sample sizes for newly unemployed TANF leavers and UI applicants is smaller than reported in Table 2.3 because this 

table excludes people who applied for UI more than 12 quarters after TANF exit. Also excluded from these tabulations are 

persons who returned to TANF prior to UI application or had interim employment prior to filing for UI. b An exact count of the number of nonmonetarily ineligible UI applicants is not possible because of missing data for Georgia 

and Ohio. c Based on wage records for the first four of the five quarters prior to the quarter of new unemployment and applicable UI law.

0.0

0.1

0.2

0.3

0.4

0.5

0.6

Florida Georgia Michigan Ohio Pooled

UI self-sufficient No UI self-sufficient UI working poor No UI working poor

Figure 4.4 Rates of Self Sufficiency and Working Poor for UI Beneficiaries and other 

UI Applicants
55

0.00

0.05

0.10

0.15

0.20

0.25

Florida Georgia Michigan Ohio Pooled

UI TANF-dependent No UI TANF-dependent UI inactive No UI inactive

Figure 4.5 Rates of TANF Dependency and Inactivity for UI Beneficiaries and other UI 

Applicants

During the 12 quarters after leaving TANF for employment, neither future TANF receipt 

nor new employment are observed for 19.9 percent of UI beneficiaries (Figure 4.5). This rate of 

inactivity is higher than among nonbeneficiary UI applicants (18.4 percent), UI nonapplicants 

(15.1 percent), and both those who quit their prior jobs (19.1 percent) and those who got fired 

from their prior jobs (18.4 percent) (Table 4.5). 

In these simple, unadjusted contrasts on the pooled sample, UI benefit receipt is 

associated with more favorable results on three of the four outcomes. UI beneficiaries have 

higher rates of self-sufficiency and lower rates of being working poor or TANF-dependent, but 

become inactive at somewhat higher rates than nonbeneficiary UI applicants and UI nonapplicants. To gain insight into the factors correlated with these patterns we examine results 

from estimation of regression models on these four outcomes. 

4.4 Models of Self-Sufficiency after New Unemployment among UI 

Applicants

To measure the correlation between UI benefit receipt and the four measures of selfsufficiency controlling for observable differences, we estimated linear probability models in the 

general form of Equation (2), including models for all four separate outcomes. 

Controlling for observable characteristics, compared to nonrecipient UI applicants, UI 

beneficiaries are estimated as 12.0 percentage points more likely to be self-sufficient, 7.2 

percentage points less likely to be working poor, 3.2 percentage points less likely to be TANFdependent, and 1.5 percentage points less likely to be inactive (Table 4.6). Each of these four 
56

Table 4.6 Rates of Self-Sufficiency after New Unemployment among UI Applicants

Return-to-employment status Employed, Employed, Not employed, Not employed,

Return-to-TANF status no TANF TANF TANF no TANF

Self-sufficient Working poor TANF-dependent Inactive

UI applicants

 UI beneficiaries

 UI nonbeneficiaries

 Simple differences

 Adjusted differences

0.501

0.364

0.137

0.120**

0.241

0.362

−0.121

−0.072**

0.060

0.090

−0.030

−0.032**

0.199

0.184

0.015

−0.015**

Effects of independent variables on outcomes

Age 24 or less

Age 25–49

Age 50 or older

−0.003

0.003*

−0.023**

0.070**

−0.015**

−0.114**

−0.019**

0.005**

0.017**

−0.048**

0.007**

0.121**

Gender, male

Gender, female

0.079**

−0.013**

−0.088**

0.015**

−0.012**

0.002**

0.022**

−0.004**

Race, white

Race, black

Race, Hispanic

Race, other

0.043**

−0.019**

−0.002

−0.011

−0.054**

0.030**

−0.030**

−0.017

−0.006**

0.001

0.006

−0.001

0.017**

−0.013**

0.025**

0.029**

4 or fewer qtrs. employment pre-BYB

5–8 qtrs. employment pre-BYB

9–12 qtrs. employment pre-BYB

−0.039**

−0.001

0.009**

−0.051**

−0.007**

0.016**

0.026**

0.004**

−0.008**

0.064**

0.005**

−0.017**

Qtrs. from TANF exit to unemployment

Multiple employers in any base-pd. qtr.

−0.010**

0.020**

−0.036**

0.033**

0.006**

−0.020**

0.040**

−0.033**

Agriculture, forestry, fishing

Manufacturing

Wholesale trade

Retail trade

Administrative support waste mgmt.

Health care/social assistance

Art, entertainment, recreation

Hotels and restaurants

0.131**

0.011*

0.008

−0.001

0.014**

−0.000

0.051

−0.000

−0.052**

0.001

−0.026**

0.005

−0.001

0.001

−0.039

0.023**

−0.010

0.001

0.001

0.001

−0.004

0.004

0.008

−0.003

−0.069**

−0.014**

0.017*

−0.005

−0.009**

−0.005

−0.020

−0.020**

Unemployment rate, month of BYB

Unemployment rate change BYB to BYE

−0.012**

−0.014**

0.015**

0.011**

0.005**

0.005**

−0.008**

−0.003

Florida

Georgia

Michigan

Ohio

0.019**

0.001

−0.028**

−0.024**

−0.016**

−0.018**

0.069**

0.048**

−0.007**

0.003

0.010*

−0.001

0.004

0.015**

−0.051**

−0.023**

NOTE: This table summarizes results presented in Tables 4.5 and A.23.

* (**) Statistically significant in a two-tailed test at the 90 (95) percent confidence level.

regression-adjusted estimates of the difference between beneficiaries and nonbeneficiary 

applicants is in the same direction as the unadjusted difference. Controlling for observable 

variables changes the parameter estimate of the difference significantly only for the outcome for 

working poor who get reemployed and also return to TANF. 
57

The regression-adjusted difference in the rate of becoming working poor is smaller in 

magnitude than the unadjusted difference, suggesting that among UI applicants, having 

characteristics correlated with UI benefit eligibility and receipt tends to lower the probability of 

becoming working poor. In other words, if all UI applicants had the same characteristics as 

those who become UI beneficiaries, a larger share of the sample would remain self-sufficient and 

a smaller share would become working poor. 

4.4.1 Correlations between independent variables and outcomes

Models for each of the four outcomes measuring the degree of self-sufficiency or TANF 

dependency included covariates to control for observable differences in characteristics of persons 

in the UI applicant samples. Parameter estimates on these variables provide some evidence on 

the direction of associations between characteristics and outcomes (Table 4.6). 

Self-sufficiency measured as reemployment without any return to TANF is most likely 

among those who are of prime age for the labor market (between 25 and 49), males, whites, 

those with employment in more quarters before UI application, those with multiple employers in 

at least one of their UI base-period quarters, and those with recent prior employment in the

industries of agriculture, manufacturing, and administrative support. Self-sufficiency is also 

more likely in areas where unemployment is lower; among the four states it is higher in Florida. 

Working poor, defined as returning back to both employment and TANF, is most likely 

among younger workers (less than 25), females, African Americans, those with more quarters of 

employment before UI application, multiple employers in at least one UI base-period quarter, 

and those recently employed in the hospitality industry. Rates of working poor are slightly 

higher in areas with higher unemployment rates and somewhat higher in Michigan and Ohio. 

Returning to TANF dependency—that is, TANF cash payments with no earned income—is most 

likely among older (age 50 and over) females who have few quarters of employment before UI 

application. Future TANF dependency is higher in high unemployment areas, and among the 

four states it is slightly higher in Michigan.

A spell of new unemployment is most likely to be followed by inactivity with neither 

employment nor TANF receipt by those who are older (age 50 or more), male, not African 

American, having fewer calendar quarters with earnings before UI application, and having new 

unemployment longer after TANF exit. Inactivity is also more likely in low unemployment 

areas, and among the four states it is slightly more likely in Georgia. 
58

4.5 Self-Sufficiency of UI Nonapplicants Compared to UI Applicants

To learn something about newly unemployed TANF leavers who do not claim UI 

benefits, we estimated linear probability models in the general form of Equation (2) on the six 

dependent variables: return to employment, TANF, and the four self-sufficiency outcomes. The 

equations were estimated on the full sample of all newly unemployed TANF leavers pooled 

across all four states. For each model the specification of Equation (2) is augmented by 

including an additional dummy variable vector in the matrix P representing UI nonbeneficiary 

applicants; a parameter for this variable is added to the vector Φ. This yields models with 

indicators for UI receipt and UI nonreceipt among applicants, with the omitted indicator variable 

for the group of UI nonapplicants. A summary of empirical results from estimating these models 

on our four-state pooled sample is presented in Table 4.7.

18

4.5.1 Return to work

Unemployment insurance beneficiaries return to work at lower rates (74.2 percent) than 

do UI non-applicants (78.6 percent) in simple unadjusted comparisons. However, controlling for 

observable characteristics, there is no measurable difference in the rate of return to employment 

between the two groups. Regression adjustment in the comparison essentially contrasts UI 

beneficiaries to UI non-applicants with similar observable characteristics. The results suggest 

the rates of return to employment are similar with or without UI. 

Applicants for UI who fail to receive benefit payments return to work at lower rates (72.6 

percent) than UI non-applicants (78.6 percent) in simple comparisons. Controlling for observable 

characteristics reduces the difference to 3.6 percentage points, but regression controls do not 

entirely eliminate the difference. When UI applicant non-beneficiaries are compared to UI nonapplicants with similar observable characteristics, a statistically significant reemployment 

disadvantage remains. In terms of observable characteristics non-beneficiary applicants tend to 

 18In compiling data sets for this project, only a limited number of exogenous variables were available for 

Florida observations. Reported in Appendix A, tables A.24 to A.29, models (1) include all exogenous variables 

except age, race, and household composition. Local unemployment rates were estimated on the full four-state 

sample. In these tables, models (2) were estimated on the restricted set of variables, and models (3) were estimated 

on the full set of variables excluding Florida data. Results from models (2) and (3) provide no evidence of omitted 

variables bias, but parameter estimates are significantly different when Florida data is excluded in going from 

models (1) to (2). Our discussion of results is focused on the four-state pooled results of models (1), summarized in 

Table 4.7. 
59

Table 4.7 Rates of Self-Sufficiency after New Unemployment among All TANF Leaversa

Return-to-employment status Employed Employed, Employed Not employed, Not employed,

Return-to-TANF status TANF no TANF TANF TANF no TANF

Newly unemployed

 UI beneficiaries

 UI nonapplicants

 Simple differences

 Adjusted differences

0.742

0.786

−0.044

0.002

0.301

0.362

−0.061

0.025**

0.501

0.487

0.014

−0.020**

0.241

0.299

−0.058

0.023**

0.060

0.063

−0.003

0.002

0.199

0.151

0.048

−0.005*

Newly unemployed

 UI nonbeneficiary applicants

 UI nonapplicants

 Simple differences

 Adjusted differences

0.726

0.786

−0.060

−0.036**

0.452

0.362

0.090

0.124**

0.364

0.487

−0.123

−0.132**

0.362

0.299

0.063

0.095**

0.090

0.063

0.027

0.028**

0.184

0.151

0.033

0.008**

Effects of independent variables on outcomes

Base-period earnings ($1,000)

High qtr. wages in base ($1,000)

Base-period earnings < $10,000

0.002**

−0.001*

0.006*

−0.006**

0.007**

0.042**

0.006**

−0.006**

−0.035**

−0.004**

0.005**

0.040**

−0.002**

0.001**

0.002

0.000

−0.001**

−0.007**

TANF payment before exit ($100)

Qtrs. TANF exit to new unempl.

Qtrs. employed pre-exit (of 12)

Avg. qtr. earn pre-exit ($1,000)

Multiple employers exit to unempl.

0.001**

−0.043**

0.011**

−0.008**

0.071**

0.005**

−0.021**

0.004**

−0.009**

0.036**

−0.003**

−0.014**

0.004**

0.002**

0.017**

0.004**

−0.029**

0.007**

−0.011**

0.054**

0.001**

0.008**

−0.003**

0.001**

−0.018**

−0.001**

0.035**

−0.008**

0.007**

−0.054**

Florida

Georgia

Michigan

Ohio

0.032**

−0.012**

0.014**

−0.004**

−0.059**

−0.007**

0.040**

0.042**

0.066**

−0.003**

−0.019**

−0.034**

−0.034**

−0.009**

0.033**

0.030**

−0.025**

0.002**

0.008**

0.012**

−0.007**

0.010**

−0.021**

−0.008**

NOTE: This table summarizes results presented in tables 4.1, 4.5 and A.24 to A.29. Results from model 1 in tables A.24 to A.29

since evidence in those tables suggests no omitted variables bias in going from model 2 to model 3, and also suggests that 

parameter estimates are significantly different when Florida data is excluded from the models. * (**) Statistically significant in a 

two-tailed test at the 90 (95) percent confidence level. a Excludes persons who returned to TANF prior to UI application or had interim employment prior to filing for UI.

have low pre-unemployment earnings and employment, they also have high rates of job quits and 

employer discharge. We do not have data on the latter characteristics for UI non-applicants.

In the full sample of all newly unemployed TANF leavers, independent control variables 

in the regression models suggest that reemployment is positively correlated with higher base 

period earnings, more quarters with employment prior to TANF exit, and having multiple 

employers in any calendar quarter between TANF exit and new unemployment. Indicator 

variables for the four states suggest higher reemployment rates in Florida and Michigan. 

4.5.2 Return to TANF

Unadjusted comparison of means suggests that UI beneficiaries return to TANF at a 

lower rate (30.1 percent) than UI nonapplicants (36.2 percent). However, compared to UI nonapplicants with similar characteristics, UI beneficiaries return to TANF at a rate 2.5 percentage 
60

points higher. That is to say, UI nonapplicants with observable characteristics similar to UI 

beneficiaries return to TANF at lower rates than UI beneficiaries. This result is consistent with 

the interpretation that UI benefit receipt is a proxy for other characteristics that make some 

newly unemployed TANF leavers more successful in the job market.

UI applicants who do not receive benefits return to TANF at much higher rates (45.2 

percent) than UI nonapplicants (36.2 percent). Controlling for observable characteristics, the 

return-to-TANF rate is still greater for nonbeneficiary UI applicants, and the difference from UI 

nonapplicants is greater (12.4 percentage points). This suggests that UI nonapplicants with 

characteristics similar to nonbeneficiary applicants are more successful at remaining off TANF 

than the nonbeneficiary UI applicants. Part of this result may be due to federal and state 

requirements to pursue all other available means of income support before returning to TANF.

Independent variables in the models suggest that return to TANF is less likely among 

those with high earnings in what would be the UI base period and more calendar quarters with 

earnings between TANF exit and new unemployment. Among all newly unemployed TANF 

leavers, return to TANF is less likely in Florida and Georgia. 

4.5.3 Maintaining self-sufficiency

Unemployment insurance beneficiaries maintain self-sufficiency at a slightly higher rate 

(50.1 percent) than do UI nonapplicants (48.7 percent) in simple unadjusted comparisons. 

However, controlling for observable characteristics, the difference in rates of self-sufficiency 

changes from 1.4 to −2.0 percent. This change in sign of the difference suggests UI nonapplicants with characteristics similar to UI beneficiaries are actually more successful at 

maintaining self-sufficiency. 

Applicants for UI who fail to receive benefit payments maintain self-sufficiency at lower 

rates (36.4 percent) than UI nonapplicants (48.7 percent). Controlling for observable 

characteristics slightly increases the difference from −12.3 to −13.2 percentage points. That is, 

when UI applicant nonbeneficiaries are compared to UI nonapplicants with similar observable 

characteristics, UI application is associated with an additional disadvantage for self-sufficiency. 

In the full sample of all newly unemployed TANF leavers, independent control variables 

in the models suggest that self-sufficiency is positively correlated with higher base-period 

earnings, more quarters with employment prior to TANF exit, and having multiple employers in 
61

any calendar quarter between TANF exit and new unemployment. Indicator variables for the 

four states suggest higher self-sufficiency rates in Florida. 

4.5.4 Transition to working poor

Unemployment insurance beneficiaries become part of the working poor at a lower rate 

(24.1 percent) than do UI nonapplicants (29.9 percent) in simple unadjusted comparisons. 

However, controlling for observable characteristics, the difference in rates of working poor 

changes sign and magnitude, from −5.8 to 2.3 percentage points. This suggests that UI 

nonapplicants with characteristics similar to UI beneficiaries have a lower chance of becoming 

working poor.

Applicants for UI who fail to receive benefit payments become working poor at a higher 

rate (36.2 percent) than UI nonapplicants (29.9 percent). Controlling for observable 

characteristics significantly increases the difference to 9.5 percentage points. That is, when UI 

applicant nonbeneficiaries are compared to UI nonapplicants with similar observable 

characteristics, UI application is associated with a significant increase in the probability of 

becoming working poor. This result may be driven by requirements to apply for UI before 

returning to TANF. Jobless persons with prior earnings insufficient to qualify for UI have a 

higher chance of future reliance on TANF to supplement meager earnings. 

In the full sample of all newly unemployed TANF leavers, independent control variables 

in the models suggest that becoming a member of the working poor is positively correlated with 

having base period earnings of less than $10,000, having higher prior TANF cash payments, 

having more quarters with employment prior to TANF exit, and having multiple employers in 

any calendar quarter between TANF exit and new unemployment. Indicator variables for the 

four states suggest higher rates of working poor in Michigan and Ohio.

4.5.5 Returning to TANF dependency

After starting a new spell of unemployment, those who return to TANF but not 

employment are called TANF-dependent in our taxonomy. Unemployment insurance 

beneficiaries become TANF-dependent at a slightly lower rate (6.0 percent) than do UI nonapplicants (6.3 percent) in simple unadjusted comparisons. However, controlling for observable 

characteristics, the rate of TANF dependency is not different between the two groups. The 

simple difference is −0.3 percentage points and the adjusted difference 0.2 percentage points, the 
62

latter being statistically indistinguishable from zero. This suggests that UI nonapplicants with 

characteristics similar to UI beneficiaries have a similar chance of becoming TANF-dependent.

Applicants for UI who fail to receive benefit payments become TANF-dependent at a 

higher rate (9.0 percent) than UI nonapplicants (6.3 percent). Controlling for observable 

characteristics, there is very little change, as the adjusted difference is 2.8 percentage points. 

That is, when UI applicant nonbeneficiaries are compared to UI nonapplicants with similar 

observable characteristics, UI application is associated with a significant increase in the 

probability of becoming TANF-dependent. Again, this result may be driven by requirements to 

apply for UI before returning to TANF. 

In the full sample of all newly unemployed TANF leavers, independent control variables 

in the models suggest that returning to TANF is less likely among those with higher base period 

earnings, those having more quarters with employment prior to TANF exit, and those having 

multiple employers in any calendar quarter between TANF exit and new unemployment. 

Indicator variables for the four states suggest lower rates of future TANF dependency in Florida.

4.5.6 Transition to inactivity

After starting a new spell of unemployment, those who return to neither employment nor 

TANF are called inactive in our taxonomy. Unemployment insurance beneficiaries become 

inactive at a significantly higher rate (19.9 percent) than do UI nonapplicants (15.1 percent) in 

simple unadjusted comparisons. However, controlling for observable characteristics, the 

difference in rates of inactivity changes from 4.8 to −0.5 percentage points. This suggests UI 

nonapplicants with characteristics similar to UI beneficiaries have a higher chance of becoming 

inactive—that is, dropping out of the labor force and ending involvement with public income 

maintenance programs. 

Applicants for UI who do not receive benefit payments become inactive at a higher rate 

(18.4 percent) than UI nonapplicants (15.1 percent). Controlling for observable characteristics, 

the adjusted difference remains positive, being 0.8 percentage points higher for nonbeneficiary 

UI applicants. That is, when UI applicant nonbeneficiaries are compared to UI nonapplicants 

with similar observable characteristics, UI application is associated with a significant increase in 

the probability of becoming inactive. For this group, failure to gain income support from UI 

leads to a reluctance to return to public support from TANF. 
63

In the full sample of all newly unemployed TANF leavers, independent control variables 

in the models suggest that becoming inactive is less likely among those with base period 

earnings below $10,000, more quarters with employment prior to TANF exit, and multiple 

employers in any calendar quarter between TANF exit and new unemployment. Indicator 

variables for the four states suggest slightly higher rates of future inactivity in Georgia. 

4.5.7 Summary of UI nonapplicants compared to UI beneficiaries

Unadjusted contrasts to UI nonapplicants suggest that UI beneficiaries have more 

favorable outcomes regarding return to TANF, self-sufficiency, working poor, and TANF 

dependency (Table 4.7). Compared to nonapplicants, UI beneficiaries are more likely to be 

older, male, African American, have higher base period earnings, and have more quarters with 

employment between TANF exit and new unemployment (Table 3.11). Controlling for 

observable characteristics, the advantage for UI beneficiaries remains only in terms of reduced 

inactivity. That is, in a group of newly unemployed TANF leavers with similar observable 

characteristics, UI beneficiaries are somewhat less successful at maintaining self-sufficiency than 

UI non-applicants. There are unobservable factors contributing to the success of UI beneficiaries 

at maintaining self-sufficiency.

4.5.8 Summary of UI nonapplicants compared to UI applicant nonbeneficiaries

Among newly unemployed TANF leavers, those who do not apply for UI benefits are 

much more successful than nonbeneficiary UI applicants. Nonapplicants have more favorable 

outcomes on reemployment, return to TANF, and all four interactions of these two outcomes 

(Table 4.7). Relative to UI applicants who do not become beneficiaries, UI nonapplicants tend to 

be younger, female, to have lower base period earnings, to be more likely to have base period 

earnings under $10,000, and to have fewer quarters with employment between TANF exit and 

new unemployment (Table 4.8). Even when controlling for observable characteristics in 

computing differences, nonbeneficiary UI applicants remain less successful on three selfsufficiency outcomes.

Whenever three groups are compared, one will have the least favorable outcomes. 

Nonbeneficiary UI applicants are least successful in comparison to either UI beneficiaries or UI 

nonapplicants. These results persist even controlling for observable characteristics of the 

individuals and their labor markets. Additional information is required to understand results for 
64

Table 4.8 Characteristics Comparison of Newly Unemployed TANF Leaver UI Nonapplicants and Nonbeneficiary Applicants

Description

Florida Georgia Michigan 

Applied for 

UI but no 

benefits

(N = 7,214)

Did not 

apply

for UI

(N = 27,936)

Applied for 

UI but no 

benefits

(N = 13,868)

Did not 

apply

for UI

(N = 96,444)

Applied for 

UI but no 

benefits

(N = 1,679)

Did not 

apply

for UI

(N = 16,267)

App

UI 

b

(N 

Age at TANF exit 31.2 30.4 29.6 30.4 27.6 

 18–24 0.289 0.27 0.369 0.309 0.459 

 25–44 0.674 0.707 0.572 0.627 0.498 0

 45+ 0.037 0.022 0.059 0.064 0.042 0

Gender, male 0.153 0.073 na 0.176 0.187 0

Gender, female 0.847 0.927 na 0.824 0.813 0

Race, white 0.269 0.191 0.3 0.424 0.529 0

Race, black 0.475 0.784 0.683 0.519 0.417 0

Race, Hispanic 0.232 0.011 0.011 0.048 0.047 0

Race, other 0.024 0.015 0.005 0.016 0.015 0

Base period earningsa 9,521 8,239 7,659 7,640 10,071 7,260 7

High qtr. base pd. earningsa 3,373 3,266 3,298 3,096 3,953 2,988 3

Base earnings < $10,000a 0.616 0.688 0.752 0.753 0.603 0.754 0

Multiemployer qtr. post-TANF 0.535 0.48 0.484 0.422 0.503 0.285 0

Qtrs. exit to new unemployment 5.0 4.1 4.1 3.8 4.8 3.7 

Qtrs. steady employed pre-exit 2.9 2.7 2.6 2.5 3.8 2.6 

Qtrs. employ pre-unempl.b 8.0 7.7 7.7 7.4 8.6 7.8 
65

nonbeneficiary UI applicants. UI application for this group may be correlated with return to 

TANF, because federal and state TANF eligibility rules require a UI application despite a low 

likelihood of UI eligibility. In the next chapter we investigate the importance of publicly provided 

employment services (ES) for all three groups of newly unemployed TANF leavers. Results of the 

ES investigation are very important for shaping policy for assistance to UI applicants who do not 

receive UI benefits.
66
67

5. USE AND EFFECTS OF WAGNER-PEYSER FUNDED EMPLOYMENT 

SERVICES

Unemployment insurance benefits are regarded as passive labor market support programs. 

Active labor market programs (ALMPs) include publicly funded employment services, job 

training, wage subsidies, and direct job creation. Activation from income support to employment is 

a core principle of UI in the United States, and is increasingly important in programs for cash

public assistance to the needy (Quade, O’Leary, and Dupper 2008). Indeed, the activation 

principle is being adopted by social programs worldwide (Eichorst, Hoffmann, and Konle-Seidl 

2008). 

Evaluations of active labor market programs across countries suggest three things: 1) job 

search assistance is the most cost-effective type of program; 2) direct job creation programs are the 

least effective and most costly; and 3) job training programs and employment subsidies fall in 

between, their cost-effectiveness dependent on targeting (Fay 1996). A recent field experiment in 

Canada found that financial incentives induce exit from cash public assistance, but adding public 

employment services to those same financial incentives more than doubles the rate of exit to 

employment (Robins, Michalopoulos, and Foley 2008). 

In this chapter we examine the usage of public employment services (ES) and their 

association with labor market success and self-sufficiency from TANF. Analysis is done on our 

samples of newly unemployed TANF leavers from the states of Georgia and Ohio. We look at ES 

usage and self-sufficiency among UI beneficiaries, nonapplicants, and nonbeneficiary applicants. 

5.1 Use of Employment Services by TANF Leavers in Georgia and Ohio

The Wagner-Peyser Act of 1933 established a nationwide network of public Employment 

Service (ES) offices (Balducchi, Eberts, and O’Leary 2004). The Workforce Investment Act of 

1998 required each workforce investment area around the country to have at least one 

comprehensive one-stop center, with ES being a required partner in every comprehensive one-stop. 

The ES network now includes more than 1,750 offices which serve as the foundation for a national 

system of one-stop career centers. Nearly 20 million job seekers and employers receive services 

from the ES every year—more than from all other publicly funded employment and training 

programs combined (O’Leary and Eberts 2009). Employment services provided through WagnerPeyser funding are available to all workers—those who have jobs but are looking for better career 
68

opportunities, those who have lost their jobs and are seeking reemployment, those seeking 

employment for the first time, and of course newly unemployed TANF leavers looking to get back 

to work. 

Services offered at one-stop centers are divided into three levels: core, intensive, and 

training. Services within each level are characterized by the amount of staff involvement and the 

extent to which customers can access the service independently. Core services typically have the 

broadest access and the least staff involvement of the three categories. Intensive services require a 

greater level of staff involvement, and consequently access is generally more limited than for core 

services. Training services involve the highest level of service intensity and are open to customers 

only through referrals.

Core services are freely available to all job seekers and can often be accessed on a selfserve basis. Core services include the following: assessment interviews, job interview referrals, 

job placements, help in resume writing, job search workshops, labor market information, and 

testing of job skills and aptitudes. Intensive services require a greater level of staff involvement, 

and consequently access is more limited than for core services. Intensive services include 

individual and group counseling, case management, aptitude and skill-proficiency testing, jobfinding clubs, creation of a job search plan, and career planning. Training services, which form the 

third and highest level of service intensity, are open to customers only through referrals. Typically 

a list is set of approved organizations outside of one-stop centers to provide these services. 

Training services typically include adult basic skills education, on-the-job-training (OJT), work 

experience, and occupational skills training. The Wagner-Peyser data available for Georgia and 

Ohio include only data on core and intensive services. 

For TANF leavers in our samples, participation in employment services is summarized for 

Georgia and Ohio in Tables 5.1 and 5.2, respectively. The table columns report counts and rates of 

ES participation by the degree of involvement with UI. Six columns are in each table reporting on 

the following categories: all TANF leavers, newly unemployed TANF leavers, UI nonapplicants, 

UI applicants, UI beneficiaries, and those initially ineligible for UI benefits. 

Participation in employment services is counted relative to a reference date. Reference 

date definitions differ depending on the participant group. For TANF leavers, the reference date is 

the quarter of TANF exit. For TANF leavers who become newly unemployed and who do not 

apply for UI benefits, the reference date is the quarter of the first occurrence of unemployment
69

Table 5.1 Service Participation among TANF Leavers in Georgiaa

Service description

TANF leaver

(n = 152,278)

Newly unemployed

(n = 123,424)

Nonapplicants

(n = 96,254)

UI applicants

(n = 27,166)

UI beneficiarie

(n = 13,335)

Participants Rate Participants Rate Participants Rate Participants Rate Participants Ra

Core services

 Orientation 1,622 0.011 4,403 0.036 407 0.004 4,965 0.183 4,407 0.

 Service needs evaluation 7,724 0.051 10,409 0.084 3,610 0.038 7,989 0.294 5,358 0.

 Testing 252 0.002 220 0.002 89 0.001 151 0.006 97 0.

 Resume preparation 1,222 0.008 1,819 0.015 633 0.007 1,330 0.049 818 0.

 LMI 12,917 0.085 17,080 0.138 5,869 0.061 13,151 0.484 6,756 0.

 Job search planning 6,032 0.040 8,730 0.071 2,630 0.027 6,960 0.256 4,199 0.

 Job development 3,292 0.022 3,293 0.027 1,431 0.015 2,058 0.076 1,138 0.

 Job search assistance 5,459 0.036 6,050 0.049 1,938 0.020 4,434 0.163 2,578 0.

 Supportive service referral 859 0.006 986 0.008 363 0.004 718 0.026 448 0.

 Job search workshopb 3,271 0.024 4,152 0.043 1,278 0.016 3,635 0.183 2,715 0.

 Other workshop 822 0.005 2,689 0.022 566 0.006 2,250 0.083 1,805 0.

 Job order search 17,851 0.117 19,310 0.156 7,206 0.075 13,963 0.514 7,206 0.

 Call-in job order 3,754 0.025 3,477 0.028 1,450 0.015 2,317 0.085 1,341 0.

 Job referral 23,960 0.157 20,876 0.169 10,443 0.108 11,317 0.417 5,748 0.

Any core service 32,135 0.211 31,549 0.256 13,349 0.139 20,683 0.761 10,374 0.

Intensive services

 Individual counseling 6,313 0.041 6,779 0.055 2,451 0.025 5,368 0.198 3,677 0.

 Customer service plan 5,777 0.038 6,483 0.053 2,273 0.024 5,217 0.192 3,615 0.

 Expanded Workshopb 2,100 0.022 2,542 0.024 1,279 0.016 1,264 0.054 455 0.

 Other intensive service 821 0.005 1,650 0.013 329 0.003 1,737 0.064 1,526 0.

Any intensive service 8,188 0.054 8,971 0.073 3,627 0.038 6,355 0.234 4,010 0.

Other

 WIA registrationb 358 0.003 415 0.003 195 0.002 225 0.009 143 0.

 Referred to training 601 0.004 1,086 0.009 314 0.003 868 0.032 617 0.

 REU/profiled 1,534 0.010 3,661 0.030 51 0.001 4,709 0.173 4,085 0.

 ERP 1,698 0.011 4,140 0.034 305 0.003 4,810 0.177 4,477 0.

a Participation in employment services is counted relative to a reference date defined in Appendix A, Table A.30. b The participation sample size is smaller because data is not available for the entire period of TANF exit, new unemployment, and UI application.
70

Table 5.2 Service Participation among TANF Leavers in Ohio Using Service Categories Introduced into Regression Modelsa

Service description

TANF leaver

(n = 82,860)

Newly unemployed

(n = 62,200)

Nonapplicants

(n = 51,084)

UI applicants

(n = 11,101)

UI beneficiari

(n = 3,336)

Participants Rate Participants Rate Participants Rate Participants Rate Participants R

Job search planning 1,835 0.022 2,424 0.039 867 0.017 1,673 0.151 512 0.

Job seeker match 7,513 0.091 8,469 0.136 3,916 0.077 5,047 0.455 1,485 0.

DVOP/LVER (Veterans’ 

services)c 1,763 0.021 1,656 0.027 877 0.017 807 0.073 287 0.

Placement 1,913 0.023 1,366 0.022 1,001 0.020 370 0.033 112 0.

Job referral 5,731 0.069 3,770 0.061 2,531 0.050 1,221 0.110 463 0.

a Participation in Employment Services is counted relative to a reference date. Reference date definitions differ depending on the participant group. 

reference date is the quarter of TANF exit. For TANF leavers who become newly unemployed and those who do not apply for UI benefits, the referen

first occurrence of unemployment subsequent to TANF exit. For UI applicants, the reference date is the quarter in which the Benefit Year Begin (BY

participation is counted if there is a record of participation between the full calendar quarter prior to a reference date and one full calendar quarter afte

time frame three calendar quarters long. b Based on UI claims filed on or before December 31, 2002. UI data received in December 2007 for claims beginning in 2003 did not include the ch

define nonmonetary eligibility. c DVOP: Disabled Veterans Outreach Program, LVER: Local Veterans Employment Representative.
71

subsequent to TANF exit. For UI applicants, the reference date is the quarter in which the 

Benefit Year Begin (BYB) date occurs. Service participation is counted if there is a record of 

participation between the full calendar quarter prior to a reference date and one full calendar 

quarter after that date. The time frame is three calendar quarters, or 39 weeks long.

More than 48 Wagner-Peyser funded ES transaction codes for Georgia were categorized 

by the Georgia Department of Labor into either core or intensive services after WIA came into 

effect (Appendix A, Table A.30, contains additional detail). A condensed list of the codes used 

by TANF leavers is the basis for Table 5.1. Counts of service participation have been combined 

into service categories. For example, there are 10 different types of job search workshops and six 

different types of testing available through the ES. Key counts are in the second column of Table 

5.1, reporting that among newly unemployed TANF leavers 25.6 percent used at least one core 

service and 7.3 percent used at least one intensive service. For this group, the most commonly 

used core services were service needs evaluation, job search assistance, and job interview 

referrals. The most popular intensive services for newly unemployed TANF leavers were: 

individual counseling, customer service plan, and expanded workshops.

Since a prime focus of this study is UI recipients, note that in nearly all states, UI 

claimants must register for job search with the ES to establish or maintain eligibility for weekly 

benefits. This linkage between UI and ES programs is part of what is called the “work test” in 

UI, and it has been a key area of program cooperation. Consequently it is not surprising that ES 

usage among UI applicants is much higher than the rate for all unemployed. Among UI 

applicants, 76.1 percent used at least one core service, while 23.4 percent used at least one 

intensive service. However, UI non-applicants used core and intensive services at sizable rates of 

13.9 and 3.8 percent respectively. Compared to UI beneficiaries, those who applied for UI but 

were initially ineligible for benefits used core services at similar rates—77.8 percent of UI 

beneficiaries and 77.1 percent of ineligible UI applicants. Rates of intensive services usage 

differed by a larger margin—30.1 of UI beneficiaries and 22.4 percent of ineligible UI 

applicants. Nonetheless, there is an important difference in rates of usage for both core and 

intensive services between ineligible UI applicants and UI nonapplicants. 

Contrasts in core and intensive services usage in Georgia are summarized graphically in 

Figure 5.1. Despite not receiving UI benefits, among newly unemployed TANF leavers, 

ineligible UI applicants are connected with reemployment services at dramatically higher rates
72

than UI nonapplicants. The process of UI application appears to link unemployed TANF leavers 

to reemployment services. In the next subsection we examine correlations between service 

receipt and maintenance of self-sufficiency. 

Usage of the most popular Wagner-Peyser employment services in Ohio is summarized 

in Table 5.2. This list of five services is drawn from a detailed list of nearly 100 ES services 

available in Ohio (Appendix A, Table A.31). Representative of core services are: job referrals, 

job placements, and job seeker matches; representative of intensive services are: job search 

planning and veterans’ services. Naturally, the latter are only available to job seekers with a 

history of military service, but the usage rate for veterans’ services in this population is 

comparable to that for other popular services. Patterns of services usage across Ohio TANF 

leaver groups, as defined by their involvement with UI, are summarized in Figure 5.2. 

As for Georgia, counts of services usage for Ohio were made within a three-calendarquarter window extending one quarter before and one quarter after the reference quarter. 

Reference quarters are defined for each UI involvement group, as above for Georgia. In our 

Ohio sample, UI nonapplicants used the core-service job seeker match at a rate of 13.6 percent, 

while UI beneficiaries used it at a rate of 44.5 percent and ineligible UI applicants at a rate of 

48.4 percent. The Ohio intensive job search planning was used by 1.7 percent of UI 

nonapplicants but by 15.3 percent of UI beneficiaries and 16.4 percent of ineligible UI 

applicants. As in Georgia, application for UI brings newly unemployed TANF leavers into 

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

Core service

Intensive service

Figure 5.1 Employment Services Usage by Degree of UI Involvement in Georgia
73

contact with the ES even if they are ineligible for UI. If use of services provided by ES is 

associated with higher rates of self-sufficiency for ineligible UI applicants, it is an additional

reason to encourage UI application among newly unemployed TANF leavers. 

5.2 Employment Services and Self-Sufficiency

For our samples of newly unemployed TANF leavers in Georgia and Ohio, statistical 

analysis suggests that public employment services help to maintain connections with 

employment opportunities, particularly for the working poor. This appears to be true regardless 

of the degree of involvement with UI, and, despite the fact that UI applicants use the ES more 

often, this result still holds for UI nonapplicants. Additionally there is evidence that use of 

services through the ES reduces rates of complete TANF dependency and inactivity. 

To examine the associations between ES and self-sufficiency we estimated regression 

models on separate Georgia and Ohio state samples of all newly unemployed TANF leavers. 

Since the correlations between ES usage and self-sufficiency may be influenced by application 

for and receipt of UI benefits, we account for involvement with UI in this analysis. Models of 

self-sufficiency are estimated for six binary outcomes: 1) employment, 2) return to TANF, 3) 

self-sufficiency, 4) working poor, 5) TANF dependency, and 6) inactivity. 

To measure the correlation between receipt of ES services and the above six outcomes, 

controlling for observable differences among newly unemployed TANF leavers, linear 

probability models were estimated. Models for all binary outcomes take the same general form. 

0.0

0.1

0.2

0.3

0.4

0.5

Job seeker match Job search planning

Figure 5.2 Employment Services Usage by Degree of UI Involvement in Ohio
74

For example, the models for return to employment have the form

(3) Y = X + R + T + P’E + 

where

Y is a vector of data on newly unemployed TANF leavers, which takes the value 1 for 

persons who return to employment within 12 calendar quarters of prior TANF exit 

and 0 otherwise. 

With a few exceptions, the other variables and parameters are similar to those defined in 

Equations (1) and (2). These are defined as follows:

X is a matrix of data on variables for observable individual characteristics of newly 

unemployed TANF leavers. These variables include age, race, presence of other 

adults on the TANF case, presence of children on the TANF case, measures of 

prior earnings and employment, prior industry of employment, dollar amount of 

last TANF payment, and whether on multiple TANF cases at TANF exit.

 is a conformable vector of parameters estimated on observable individual characteristic 

variables.

R is a matrix of data on variables representing characteristics of the regional labor 

market. These include dummy variables for county of residence, county 

unemployment rate at the time of TANF exit, and the change in county 

unemployment rate from TANF exit to new unemployment. 

 is a conformable vector of parameters estimated on variables for characteristics of the 

regional labor market at the time of TANF exit for employment. 

T is a matrix of data on indicator variables representing the year and calendar quarter of 

TANF exit for employment.

 is a vector of parameters estimated on variables representing the year and calendar 

quarter of TANF exit for employment. 

P is a matrix including one unit vector and two dummy variables. One dummy indicates 

UI benefit receipt or not; the other dummy variable indicates no benefit receipt 

after UI application or not. 

E is a matrix representing core and intensive Wagner-Peyser funded employment 

services. 

 is a conforming vector of regression parameters.19

 is a vector representing an unobserved random variable summarizing unmeasured 

differences across individuals in the samples. It is assumed to be normally 

distributed with mean zero, constant variance, and zero covariance across 

observations. 

 19Parameter estimates of the linear probability models for return to employment and TANF are presented in 

Appendix Tables A.32 and A.33 for Georgia and Ohio, respectively. For UI nonapplicants the marginal effects 

reported in Tables 5.3 and 5.4 are the parameter estimates on the service variables in Appendix Tables A.32 and 

A.33. For UI beneficiaries the marginal effects are sums of parameters on the ES variables plus the UI beneficiary 

variable interacted with the ES variables. Similarly, for nonbeneficiary UI applicants the marginal effects are sums 

of parameters on the ES variables plus the nonbeneficiary UI applicants variable interacted with the ES variables. 

Tests of statistical significance in Tables 5.3 and 5.4 are based on the sums of the variances of the parameters in 

Tables A.32 and A.33 plus two times the covariances.
75

Table 5.3 Marginal Impacts of Employment Services Participation on Return to Employment and TANF 

among Newly Unemployed TANF Leavers in Georgiaa

Employment service

Returned to employment Returned to TANF

Nonapplicant

UI 

beneficiary

Nonbeneficiary

UI applicant Nonapplicant

UI 

beneficiary

Nonbeneficiary

UI applicant

Assessment, service needs 0.026** −0.011 0.028** 0.138** 0.018 0.082**

Job search assistance 0.023** −0.001 0.031** 0.049** 0.009 0.059**

Job referral 0.065** 0.049** 0.107** 0.061** 0.035** 0.032**

Individual counseling 0.017 0.030 0.023 0.062** −0.002 0.020

Customer service plan −0.020 −0.033 −0.036* −0.010 0.041 0.014

Expanded workshop 0.038** 0.017 0.035** 0.311** 0.321** 0.289**

Employment service

Employment and no TANF

(self-sufficient)

Employment with TANF

(working poor)

Nonapplicant

UI 

beneficiary

Nonbeneficiary

UI applicant Nonapplicant

UI 

beneficiary

Nonbeneficiary

UI applicant

Assessment, service needs −0.096** −0.014 −0.026 0.122** 0.003 0.054**

Job search assistance −0.020** −0.017* −0.008 0.043** 0.016* 0.039**

Job referral −0.013** 0.009 0.047** 0.077** 0.040** 0.061**

Individual counseling −0.044** 0.006 −0.027 0.061 0.024 0.050**

Customer service plan −0.017 −0.047 −0.036 −0.003 0.014 0.000

Expanded workshop −0.246** −0.236** −0.199** 0.284** 0.253** 0.234**

Employment service

No employment, No TANF

(inactive)

No employment with TANF

(TANF-dependent)

Nonapplicant

UI 

beneficiary

Nonbeneficiary

UI applicant Nonapplicant

UI 

beneficiary

Nonbeneficiary

UI applicant

Assessment, service needs −0.042** −0.004 −0.056** 0.016** 0.015** 0.028**

Job search assistance −0.030** 0.008 −0.051** 0.007 −0.007 0.020**

Job referral −0.048** −0.044** −0.078** −0.017** −0.005 −0.029**

Individual counseling −0.017 −0.004 0.006 0.000 −0.026** −0.029**

Customer service plan 0.027** 0.005 0.023 −0.007 0.027** 0.013

Expanded workshop −0.065** −0.085** −0.090** 0.027** 0.068** 0.055**

NOTE: * Parameter estimate significantly different from zero at the 95 percent confidence level in a two-tailed test. 

** Parameter estimate significantly different from zero at the 95 percent confidence level in a two-tailed test. a Persons are classified as having participated in a given service if the data indicate a service participation date within a three 

quarter interval that starts with the full calendar quarter prior to the quarter of a given reference date and extends through the full

calendar quarter that follows the quarter in which the reference date occurs. For newly unemployed TANF leavers who do not 

apply for UI benefits, the reference date is the quarter of new unemployment. For UI applicants, the reference date is the quarter

in which the BYB occurs.
76

Table 5.4 Marginal Impacts of Employment Services Participation on Return to Employment and TANF 

among Newly Unemployed TANF Leavers in Ohioa

Employment service

Returned to employment Returned to TANF

NonapplicantsUI

beneficiaries

Nonbeneficiary

UI applicants

NonapplicantsUI

beneficiaries

Nonbeneficiary

UI applicants

Job search planning −0.005 −0.016 0.007 −0.032* 0.022 −0.028

Job seeker match 0.051** 0.031 0.039** 0.068** 0.032 0.055**

Veterans (DVOP/LVER) −0.005 0.010 0.026 0.003 −0.032 −0.004

Placement 0.009 0.031 0.008 0.007 −0.092 0.048

Referral 0.057** 0.083** 0.046** 0.026** 0.078** 0.032

Employment service

Employment and no TANF

(self-sufficient)

Employment with TANF

(working poor)

NonapplicantsUI

beneficiaries

Nonbeneficiary

UI applicants

NonapplicantsUI

beneficiaries

Nonbeneficiary

UI applicants

Job search planning 0.014 −0.025 0.020 −0.019 0.008 −0.014

Job seeker match −0.008 0.009 0.005 0.059** 0.022 0.034**

Veterans (DVOP/LVER) 0.001 0.026 0.020 −0.005 −0.017 0.006

Placement −0.009 0.091 −0.081** 0.018 −0.059 0.089**

Referral 0.021* −0.001 0.018 0.036** 0.084** 0.028

Employment service

No employment and no TANF

(inactive)

No employment with TANF

(TANF-dependent)

NonapplicantsUI

beneficiaries

Nonbeneficiary

UI applicants

NonapplicantsUI

beneficiaries

Nonbeneficiary

UI applicants

Job search planning 0.019 0.003 0.008 −0.014 0.014 −0.015

Job seeker match −0.060** −0.041** −0.060** 0.009 0.010 0.021**

Veterans (DVOP/LVER) −0.004 0.005 −0.016 0.009 −0.015 −0.010

Placement 0.002 0.001 0.033 −0.011 −0.032 −0.041

Referral −0.047** −0.077** −0.050** −0.010 −0.006 0.004

NOTE: *Parameter estimate significantly different from zero at the 90 percent confidence level in a two-tailed test. ** Parameter 

estimate significantly different from zero at the 95 percent confidence level in a two-tailed test. a Persons are classified as having participated in a given service if the data indicate a service participation date within a three 

quarter interval that starts with the full calendar quarter prior to the quarter of a given reference date and extends through the full 

calendar quarter that follows the quarter in which the reference date occurs. For newly unemployed TANF leavers who do not 

apply for UI benefits, the reference date is the quarter of new unemployment. For UI applicants, the reference date is the quarter in 

which the BYB occurs.

Estimated marginal impacts of employment services for UI nonapplicants, UI 

beneficiaries, and nonbeneficiary UI applicants are given in Tables 5.3 and 5.4 for Georgia and 

Ohio, respectively. Impact estimates are reported for the Georgia core services (service needs 

evaluation, job search assistance, and job interview referrals) and the Georgia intensive services 

(individual counseling, customer service plan, and expanded workshops). For each Georgia 

outcome we examine 18 parameter estimates. For Ohio we examine impacts for five services on 

three UI involvement groups, or a total of 15 parameter estimates.

5.2.1 ES and employment

For Georgia we examine use of six employment services among three groups defined by 

involvement with UI. For these Georgia Wagner-Peyser services, all but one of ten statistically 
77

significant marginal effect estimates are positive on rates of employment. The largest effect 

estimates are for the most popular core service: job referrals. Employment rates are boosted by 

job referrals by 6.5, 4.9, and 10.7 percentage points respectively for UI nonapplicants, UI 

beneficiaries, and nonbeneficiary UI applicants (Table 5.3). Connection to the ES for nonbeneficiary UI applicants is seen to be particularly important in Georgia. Job-referral impact 

estimates are also positive and significant on employment in the Ohio data for all three UI 

involvement groups. The estimates are that employment rates increased 5.7, 8.3, and 4.6 

percentage points respectively for UI nonapplicants, UI beneficiaries, and nonbeneficiary UI 

applicants (Table 5.4). The statistically significant impact estimates on the Ohio core service job 

seeker match are also positive on employment.

5.2.2 ES and return to TANF

For Georgia the 11 statistically significant parameter estimates, indicate positive 

correlations between receipt of ES services and return to TANF; the remaining seven estimates 

are not different from zero. For Ohio, 10 of 15 parameter estimates indicated no correlation 

between receipt of ES services and return to TANF, while four of the five statistically significant 

estimates are positive. This evidence of a positive correlation between ES services and return to 

TANF is most likely an artifact of underlying tendencies for these groups of TANF leavers. 

Below we see evidence of the value of ES services for the working poor.

5.2.3 ES and self-sufficiency

The Georgia computations yield 9 of 18 statistically significant estimates, with only one 

being positive. For Ohio, 13 of 15 parameter estimates are not significantly different from zero. 

These results suggest ES services are not strongly correlated with self-sufficiency and 

independence from future TANF receipt. However, there is evidence that for these samples of 

newly unemployed TANF leavers the ES provides important services for reconnecting with 

employment and avoiding inactivity. 

5.2.4 ES and the working poor

Parameter estimates suggest that ES services help achieve employment for those who are 

likely to return to TANF. That is, public employment services support employment and earnings 

for the working poor who remain TANF-dependent. The results for Georgia yield 12 of 18 
78

parameter estimates as statistically significant, with all 12 being positive. The Ohio results yield 

6 of 15 statistically significant parameter estimates, with all 6 being positive. 

5.2.5 ES and TANF dependency

Estimates on Georgia data yield 12 statistically significant among 18 parameter estimates. 

Two of three estimates suggest ES services are associated with increased TANF dependency. 

Results from Ohio indicate no association between use of ES and TANF dependency. The Ohio 

data yielded zero correlations for 11 of 12 parameters. 

5.2.6 ES and inactivity

Participation in ES services is strongly associated with a reduction in inactivity. Results 

from Georgia yield 11 statistically significant impacts out of 18. Among these, 10 of 11 impacts 

are negative, indicating a reduction in inactivity. In Ohio, the key core services of job interview 

referrals and job seeker matches are both strongly negatively correlated with inactivity. For 

Ohio these services yield the only statistically significant impacts on being inactive, and the 

impact estimates are all negative for all three UI involvement groups. In particular, for Ohio a 

job interview referral reduced inactivity by 4.7, 7.7, and 5.0 percent for UI nonapplicants, UI 

beneficiaries, and nonbeneficiary UI applicants, respectively. 

5.2.7 Summary

Use of employment services by newly unemployed TANF leavers, regardless of their 

degree of involvement with UI, is associated with significantly higher employment rates and 

significantly lower rates of inactivity. The core and intensive Wagner-Peyser services are 

popular among UI applicants regardless of whether UI compensation is actually received. As 

many as 77 percent of UI applicants in Georgia used at least one employment service, and more 

than 45 percent of Ohio UI applicants in our sample received a job seeker match. Evidence from 

both states indicates that UI application results in high rates of ES usage, and ES services have 

similar effects for all UI applicants regardless of whether or not they receive cash UI 

compensation. The ES services are particularly valuable in promoting employment and earnings 

among low income job seekers who are also reliant on TANF. 
79

5.3 Employment Services, Earnings, and Income

To sharpen understanding of ES impacts on self-sufficiency of newly unemployed TANF 

leavers, we look at the effects of services on all observable components of income. This 

approach considers the possibility that newly unemployed TANF leavers might be using ES 

services as part of a strategy to maximize total income combining sources from earnings, UI 

benefits, and TANF. Using data for Georgia and Ohio, we estimate the impacts of ES on each of 

these three components of income and the total of the three for UI nonapplicants, UI 

beneficiaries, and nonbeneficiary UI applicants. 

Estimates of ES services on components of income are computed in regression models of 

the form described by Equation (3). Parameters of the full models are presented in Appendix 

Tables A.34 and A.35 for Georgia and Ohio, respectively. Estimates of effects on the 

components of income are presented in Tables 5.5 and 5.7, respectively, for Georgia and Ohio; 

the effect estimates on total income are given in Tables 5.6 and 5.8 for Georgia and Ohio, 

respectively.20

5.3.1 ES and employment earnings

 

Job interview referrals had positive impacts on employment earnings for all newly 

unemployed TANF leavers in Georgia. Positive and statistically significant impacts of $352 and 

$1,171 were estimated for UI beneficiaries and nonbeneficiary UI applicants, respectively. 

These impact estimates are the differences in observed earnings over the four quarters 

immediately after new unemployment begins.21

 20The effect estimates presented in Tables 5.5 and 5.6 for Georgia and in Tables 5.7 and 5.8 for Ohio are 

computed by the same procedure outlined in the previous footnote, using parameter estimates presented in Appendix 

Table A.34 for Georgia and A.35 for Ohio. 

The sizable impact for nonbeneficiary UI 

applicants is the only one of six Georgia ES services with an impact estimate that is statistically 

significantly different from zero for this group. For UI beneficiaries in Georgia the intensive 

service called expanded workshop has a statistically significant impact of $903; the other 

services estimated to have statistically significant effects for UI beneficiaries are two negative 

21The reference dates for measuring employment earnings are the same as for counting use of employment 

services. Earnings are cumulated for four quarters starting with the calendar quarter after the reference date. 
80

impacts. Service needs assessment and job search assistance have negative impacts on earnings 

for UI beneficiaries, these services are activities commonly accessed later in a UI benefit year 

after more timely services are determined to be insufficient. The statistically significant impacts 

of ES services for UI nonapplicants are intensive services: customer service plan and expanded 

workshop. Again, these services are typically received later in a job search spell after other 

avenues for reemployment have been tried; both estimates indicate earnings are lower.

Table 5.5 Marginal Impacts of Employment Services Participation on Income from Employment, TANF, 

and UI among All Newly Unemployed TANF Leavers in Georgiaa

Employment services

Total earnings from employment

Nonapplicants UI beneficiaries

Nonbeneficiary UI 

applicants

Parameter

estimate ($) t-statistic

Parameter

estimate ($) t-statistic

Parameter

estimate ($) t-statistic

Assessment, service needs −60 −0.26 −863** −3.21 −56 −0.18

Job search assistance −64 −0.40 −844** −4.64 −47 −0.26

Job referral 120 1.24 352** 1.99 1,171** 7.07

Individual counseling −268 −1.06 301 0.57 −545 −1.45

Customer service plan −569** −2.05 −569 −1.07 356 0.87

Expanded workshop −633** −2.51 903* 1.91 −75 −0.21

Employment services

Total TANF income

Nonapplicants UI beneficiaries

Nonbeneficiary UI 

applicants

Parameter

estimate ($) t-statistic

Parameter

estimate ($) t-statistic

Parameter

estimate ($) t-statistic

Assessment, service needs 303** 9.40 −8 −0.20 205** 4.68

Job search assistance 132** 5.87 4 0.15 163** 6.36

Job referral 81** 5.93 21 0.85 4 0.19

Individual counseling 131** 3.70 14 0.19 −11 −0.20

Customer service plan 28 0.71 113 1.52 53 0.92

Expanded workshop 967** 27.45 594** 9.01 599** 11.87

Employment services

Total UI compensation in benefit year

Nonapplicants UI beneficiaries

Nonbeneficiary UI 

applicants

Parameter

estimate ($) t-statistic

Parameter

estimate ($) t-statistic

Parameter

estimate ($) t-statistic

Assessment, service needs — — 121** 3.08 — —

Job search assistance — — 355** 14.09 — —

Job referral — — 115** 4.79 — —

Individual counseling — — 26 0.37 — —

Customer service plan — — 118 1.64 — —

Expanded workshop — — −101 −1.60 — —

NOTE: * Parameter estimate significantly different from zero at the 90 percent confidence level in a two-tailed test. 

** Parameter estimate significantly different from zero at the 95 percent confidence level in a two-tailed test. — = not available. a Income from employment includes earnings from one quarter after the reference quarter (quarter of UI filing or new 

unemployment) through four quarters after. Income from TANF includes TANF receipt from one quarter prior to the reference 

quarter (quarter of UI filing or new unemployment) through four quarters after. Income from UI includes all regular UI 

compensation received in the benefit year. UI applicants with earnings or TANF prior to UI filing are excluded.
81

For the Ohio sample, statistically significant impact estimates for job interview referrals 

and job placements are positive and large. Impacts on earnings of job interview referrals are 

$409 for UI nonapplicants and $464 for nonbeneficiary UI applicants, and the impact for an Ohio 

job placement for UI beneficiaries is $1,665 in the four calendar quarters after the UI benefit 

year begin date. Veterans’ placement services are estimated to have a large and positive impact 

for UI nonapplicants of $409. Job search planning is an intensive employment service that is 

normally accessed only after speedier avenues of reemployment have been tried. Job search 

planning is estimated to have large and negative impacts for all three categories of job seekers 

examined. The negative impact estimates most likely reflect the relatively longer jobless period 

for participants in job search planning before return to work.

5.3.2 ES and TANF income

Among UI beneficiaries in Georgia, only the expanded workshop has a statistically significant 

effect on TANF receipt, and the estimated increase of $594 is most likely a result of the longer 

jobless period for participants in this intensive employment service. Among non-beneficiary UI 

applicants in Georgia, five of six ES impacts on TANF receipt are positive and three are 

statistically significant, with the largest associated with the intensive service called expanded 

workshop. For UI nonapplicants, all six ES impacts on TANF receipt are positive; as for 

nonbeneficiary UI applicants, the largest increase in TANF receipt is associated with 

Table 5.6 Marginal Impacts of Employment Services Participation on Total Income from Wages, TANF, 

and UI among Newly Unemployed TANF Leavers in Georgiaa

Employment services

Total income from wages, TANF, and UI

Nonapplicants UI beneficiaries

Nonbeneficiary UI 

applicants

Parameter

estimate ($) t-statistic

Parameter

estimate ($) t-statistic

Parameter

estimate ($) t-statistic

Assessment, service needs 231 1.01 −137 −0.51 125 0.40

Job search assistance 63 0.40 −423** −2.35 119 0.66

Job referral 231** 2.40 285 1.62 1,197** 7.28

Individual counseling −131 −0.52 125 0.24 −549 −1.47

Customer service plan −523* −1.90 −682 −1.29 454 1.12

Expanded workshop 334 1.34 1,021** 2.18 511 1.43

NOTE: * Parameter estimate significantly different from zero at the 90 percent confidence level in a two-tailed test.

** Parameter estimate significantly different from zero at the 95 percent confidence level in a two-tailed test. a Based on income from wages, TANF, and UI covering a six-quarter period, which for UI applicants ranges from one quarter 

prior to the quarter of UI filing through four quarters after, and for nonapplicants ranges from one quarter prior to the quarter of 

new unemployment through four quarters after. Income from employment includes earnings from one quarter after the reference 

quarter (quarter of UI filing or new unemployment) through four quarters after. Income from TANF includes TANF receipt 

from one quarter prior to the reference quarter (quarter of UI filing or new unemployment) through four quarters after. Income 

from UI includes all regular UI compensation received in the benefit year. UI applicants with earnings or TANF prior to UI 

filing are excluded.
82

participation in the intensive service called expanded workshop. Therefore, the largest increase 

in TANF receipt after new unemployment across all three groups defined by their involvement 

with UI is associated with their involvement in expanded workshop. This intensive service is 

used by those with longer spells of joblessness and probably more barriers to reemployment.

Table 5.7 Marginal Impacts of Employment Services Participation on Income from Employment, TANF, 

and UI among All Newly Unemployed TANF Leavers in Ohioa

Employment services

Total income from employment

Nonapplicants UI beneficiaries

Nonbeneficiary UI 

applicants

Parameter

estimate ($) t-statistic

Parameter

estimate ($) t-statistic

Parameter

estimate ($) t-statistic

Job search planning −439** 2.33 −1,055** −3.50 −404** −2.08

Job seeker match −272** −2.65 −349 −1.42 176 1.15

Veterans (DVOP/LVER) 490** 2.68 77 0.22 78 0.30

Placement −105 −0.55 1,665** 2.73 415 0.99

Referral 409** 3.08 −377 −1.17 464* 1.78

Employment services

Total income from TANF

Nonapplicants UI beneficiaries

Nonbeneficiary UI 

applicants

Parameter

estimate ($) t-statistic

Parameter

estimate ($) t-statistic

Parameter

estimate ($) t-statistic

Job search planning −59 −0.92 180* 1.74 −48 −0.72

Job seeker match 57 1.61 −57 −0.68 68 1.30

Veterans (DVOP/LVER) 81 1.29 51 0.42 −20 −0.22

Placement −53 −0.81 −90 −0.43 127 0.89

Referral 67 1.47 185* 1.67 70 0.77

Employment services

Total UI compensation

Nonapplicants UI beneficiaries

Nonbeneficiary UI 

applicants

Parameter

estimate ($) t-statistic

Parameter

estimate ($) t-statistic

Parameter

estimate ($) t-statistic

Job search planning — — −108 −1.24 — —

Job seeker match — — −3 −0.04 — —

Veterans (DVOP/LVER) — — 128 1.24 — —

Placement — — −530** −2.97 — —

Referral — — 230** 2.40 — —

NOTE: *Parameter estimate significantly different from zero at the 90 percent confidence level in a two-tailed test.

**Parameter estimate significantly different from zero at the 95 percent confidence level in a two-tailed test. — = not available. a Income from employment includes earnings from one quarter after the reference quarter (quarter of UI filing or new 

unemployment) through four quarters after. Income from TANF includes TANF receipt from one quarter prior to the reference 

quarter (quarter of UI filing or new unemployment) through four quarters after. Income from UI includes all regular UI 

compensation received in the benefit year. UI applicants with earnings or TANF prior to UI filing are excluded.
83

Participation in ES is estimated to have statistically significant impacts on TANF receipt 

in the Ohio sample only for UI beneficiaries. Receipt of job interview referrals and job search 

planning are associated with increases in TANF of $185 and $180 respectively.22

5.3.3 ES and UI receipt

In the Georgia sample, receipt of intensive ES services has no statistically significant 

impact on the amount of UI benefits received. Alternatively, the three core services each have 

positive and statistically significant effects on receipt of UI benefits. The estimated increases in 

UI benefit receipt are $121 for service needs assessment, $355 for job search assistance, and 

$115 for job interview referrals. 

In the Ohio sample, only two ES services have statistically significant effects on UI 

benefit receipt. Job interview referrals are estimated to increase UI benefit receipt by $230, but 

actual job placements were estimated to reduce UI benefit receipt by $530 for newly unemployed 

TANF-leaver UI beneficiaries. 

5.3.4 ES and total income

The strategy of examining impacts on components of income resulting from receipt of ES 

services recognizes the fact that program participants know how income maintenance programs 

 22Receipt of TANF cash payments are totaled over the six calendar quarters, starting with the quarter before 

the reference date as defined for each of the three analysis groups: UI nonapplicants, UI beneficiaries, and nonbeneficiary UI applicants. 

Table 5.8 Marginal Impacts of Employment Services Participation on Total Income from Wages, TANF, 

and UI among Newly Unemployed TANF Leavers in Ohioa

Service description

Total income from wages, TANF, and UI

Nonapplicants UI beneficiaries

Nonbeneficiary UI 

applicants

Parameter

estimate ($) t-statistic

Parameter

estimate ($) t-statistic

Parameter

estimate ($) t-statistic

Job search planning −521** −2.68 −959** −3.09 −454** −2.28

Job seeker match −229** −2.17 −599** −2.37 241 1.53

Veterans (DVOP/LVER) 563** 2.99 401 1.10 54 0.18

Placement −147 −0.76 1,054* 1.68 562 1.31

Referral 478** 3.49 −120 −0.36 533** 1.98

NOTE: *Parameter estimate significantly different from zero at the 90 percent confidence level in a two-tailed test. **Parameter 

estimate significantly different from zero at the 95 percent confidence level in a two-tailed test. a Based on income from wages, TANF, and UI covering a six-quarter period which for UI applicants ranges from one quarter 

prior to the quarter of UI filing through four quarters after and for nonapplicants ranges from one quarter prior to the quarter of 

new unemployment through four quarters after. Income from employment includes earnings from one quarter after the reference 

quarter (quarter of UI filing or new unemployment) through four quarters after. Income from TANF includes TANF receipt 

from one quarter prior to the reference quarter (quarter of UI filing or new unemployment) through four quarters after. Income 

from UI includes all regular UI compensation received in the benefit year. UI applicants with earnings or TANF prior to UI 

filing are excluded.
84

operate and interact with other social programs. The presumption is that program participants 

will navigate the array of programs to maximize their total income from all sources.23

For UI beneficiaries in Georgia the expanded workshop has the biggest statistically 

significant positive estimated impact on total income, $1,021. This effect is mainly due to the 

positive impact of the expanded workshop on employment earnings, although the impact on 

TANF income is also sizable. For UI beneficiaries in Ohio the biggest increase in total income 

resulted from job placements by the ES which increased total income by $1,054, with the bulk of 

this increase coming from employment earnings (Table 5.8).

 In 

examining the impacts of ES services on total income, the predominant component is wage and 

salary income from employment. 

24

Among nonbeneficiary UI applicants in Georgia only job referrals had a statistically 

significant effect on total income, estimated at an increase of $1,197—again the bulk of this 

increase is due to increased employment earnings. For nonbeneficiary UI applicants in Ohio the 

largest impact estimate on total income is a $533 increase for recipients of job interview 

referrals. Participants in the intensive service called job search planning among Ohio nonbeneficiary UI applicants had an estimated $454 reduction in total income, with the bulk of the 

reduction due to lower employment earnings. Participants in intensive services typically have 

longer than average unemployment durations, and therefore lower observed earnings.

Total income for UI nonapplicants increased most for those in Georgia who received a 

job interview referral. For UI nonapplicants in Georgia who found their way to the ES intensive 

service called customer service plan, total income declined by $523. Among newly unemployed 

TANF leavers in Ohio who did not apply for UI, job interview referrals increased total income 

by $478 and veterans’ reemployment services increased total income by $563. Ohio UI nonapplicants receiving job search planning or job seeker matches had lower total income. 

 23We thank U.S. Department of Labor policy analyst Wayne Gordon for suggesting this research strategy. 

24Impacts of services on total income for different categories of participants are not the simple sums of 

impacts on components of income. Separate models in the general form of Equation (3) were estimated for the 

components of income and total income. 
85

6. SUMMARY, CONCLUSIONS, AND EXTENSIONS

Unemployment insurance (UI) provides temporary partial wage replacement to the 

involuntarily unemployed. The employment service (ES) provides job matching services for job 

seekers and employers. The ES also administers the UI work test to ensure that UI beneficiaries 

continue to be able, available, and actively seeking work. The Personal Responsibility and Work 

Opportunity Reconciliation Act (PRWORA) of 1996 changed welfare by establishing Temporary 

Assistance for Needy Families (TANF). This law introduced lifetime limits and work 

requirements for continued TANF benefit eligibility. Using state administrative data from four of 

the nine largest states, this study expands on prior knowledge about the use of UI and ES by 

recent TANF leavers. 

6.1 Summary

For TANF leavers in Florida, Georgia, Michigan, and Ohio, this study examines the 

incidence of unemployment, and the rates of UI application, eligibility, and benefit receipt. We 

also report on the correlation between UI receipt and patterns of self-sufficiency. In addition to 

studying outcomes for UI applicants, we examine self-sufficiency by non-UI applicants. Finally, 

for TANF leavers in Georgia and Ohio, we use data on Wagner-Peyser funded employment 

services (ES) to examine their value for newly unemployed TANF leavers.

Since 1996 the number of TANF recipients has declined dramatically. The four-state 

sample of TANF leavers totaled 322,038. This data is a census of adult grantees in TANF 

recipient households who left TANF for employment. The four-state pooled data on newly 

unemployed TANF leavers includes 34 percent youth and 58 percent prime-age persons, 82 

percent females, 37 percent whites, 60 percent African Americans, and 2 percent Hispanics. 

Average quarterly earnings in the three years before TANF exit were $1,414, and average 

quarterly earnings from TANF exit to new unemployment were $1,772. 

6.1.1 Unemployment, UI application, UI eligibility and benefit receipt

Based on administrative data from Florida, Georgia, Michigan, and Ohio examined in 

this study, approximately 79 percent of TANF leavers experience unemployment within three 

years of their exit. Between 18 and 40 percent of newly unemployed TANF leavers apply for UI 

benefits, with the average across states being 24 percent.
86

To initially qualify for UI, a claimant must have sufficient prior earnings and 

employment. These “monetary eligibility” conditions require demonstration of labor force 

attachment and assure that a prior employer has paid tax contributions as premiums for the UIcovered worker. Furthermore, the job separation must be involuntary. These “nonmonetary 

eligibility” rules prohibit quits and discharge for misconduct or other causes justifiable by an 

employer. 

Among TANF leavers applying for UI, between 89 and 98 percent had sufficient prior 

earnings to qualify for UI benefits in Florida, Georgia, and Michigan. In Ohio a strict 

employment requirement results in a monetary eligibility rate of about 65 percent. The monetary 

eligibility rate in the full four-state sample was 87 percent, a rate consistent with estimates in 

previous studies. 

For TANF leavers who apply for UI, between 32 and 48 percent qualify for UI based on 

the circumstances of their job separation. Among UI applicants, TANF leavers had much higher 

rates of voluntary quits and discharges for cause than did other UI applicants. The overall rate of 

initial nonmonetary eligibility in the four-state sample was 44 percent, being somewhat higher 

than estimated in earlier studies.

Among TANF leavers who apply for UI, the UI beneficiary rate among applicants ranged 

from 30 percent in Ohio to 65 percent in Michigan. The overall mean rate of benefit receipt was 

50 percent in the pooled sample.25

6.1.2 Comparing UI eligibility between TANF leavers and other UI applicants

 Among UI beneficiaries the mean weekly benefit amount was 

$159, entitled duration averaged nearly 20 weeks, and on average 75 percent of entitled UI 

benefits were drawn. Benefit year UI payments averaged $2,442 with a mean of 14.5 weeks 

duration. Benefit entitlements were fully exhausted by 53 percent of TANF-leaver UI 

beneficiaries, which is a higher rate of UI benefit exhaustion than among UI beneficiaries not 

recently involved with TANF in these states. 

Compared to the general population of UI applicants, newly unemployed TANF leavers 

applying for UI had similar chances of monetary eligibility, but much lower chances of nonmonetary eligibility and benefit receipt. The main reasons driving these results were higher rates 

 25 The 50 percent rate of UI benefit receipt for TANF leavers in our combined sample from Florida, 

Georgia, Michigan, and Ohio is in the neighborhood of the 55 percent rate observed by O’Leary and Kline (2008) in 

Florida, Michigan, Ohio, and Texas, and 56 percent rate observed in New Jersey by Rangarajan, Razafindratkoto, 

and Corson (2002).
87

of voluntary job quits and employer dismissals for cause among recent TANF leavers. 

Controlling for observable characteristics, TANF leavers are estimated to have higher rates of UI 

monetary eligibility than other UI applicants, except in Ohio, where there is a 20-weeks-of-work 

requirement. However, controlling for characteristics, nonmonetary eligibility rates are 

estimated to be lower for TANF leavers in all states, with the greatest difference being in 

Michigan. Rates of UI benefit receipt are lower in every state for recent TANF leavers 

compared to other UI applicants, with differences in the rate of receipt ranging from 11 

percentage points in Florida to 37 percentage points in Ohio. 

Failure of nonmonetary eligibility requirements is the main reason for lower rates of UI 

benefit receipt by TANF leavers compared to other UI applicants. Voluntary quit rates are 

higher for TANF leavers than for other UI applicants in all states examined. In the pooled fourstate sample of TANF-leaver UI applicants, 17 percent voluntarily quit their prior jobs which is 

almost double the 9 percent rate for other UI applicants. Employer dismissals are also higher for 

TANF leavers. For non-TANF-leaver UI applicants, 19 percent got fired from their prior jobs, 

while 33 percent of TANF leavers were fired. Controlling for observable characteristics, TANF 

leavers were 4 percentage points more likely to quit and 7 percentage points more likely to get 

fired than similar UI applicants. 

6.1.3 UI take-up rate among newly unemployed TANF leavers

Among newly unemployed TANF leavers, we estimate that 80 percent of UI nonapplicants had sufficient prior earnings to be monetarily eligible, and 35 percent would be 

nonmonetarily eligible. Since the beneficiary rate is typically higher than the nonmonetary 

eligibility rate, an upper bound estimate for UI nonapplicants would be a 40 percent beneficiary 

rate if they were to apply.26 The 50 percent beneficiary rate among the 24 percent of newly 

unemployed TANF leavers who do apply, combined with the imputed rate for UI nonapplicants, 

suggests a UI take-up rate of 28 percent among newly unemployed TANF leavers who are likely 

to be fully eligible for UI benefits.27

 26Based on actual nonmonetary eligibility percentages among UI applicants. 

 Within these four states there could have been nearly 

27Among all newly unemployed TANF leavers, 12 percent receive UI benefits while 42 percent are 

potentially eligible. The 42 percent is a sum of 0.4 times the 76 percent who are nonapplicants plus 0.5 times the 24 

percent who do apply for UI benefits. 
88

77,000 additional UI beneficiaries among TANF leavers in the time period during which 30,900 

actually applied for and received UI compensation.28

6.1.4 UI and self-sufficiency

 

Among all newly unemployed TANF leavers in the pooled sample, 78 percent returned to 

employment and 37 percent returned to TANF within three years of first leaving TANF. Those 

who received UI returned to employment at a rate of 74 percent, compared with 73 percent of 

nonbeneficiary UI applicants and 79 percent of UI nonapplicants. Return to TANF rates are 30 

percent for UI beneficiaries, 45 percent for nonbeneficiary UI applicants, and 36 percent for UI 

nonapplicants. These simple unadjusted comparisons suggest that UI nonapplicants have 

stronger workforce attachments and better return-to-work prospects than UI applicants. 

6.1.5 UI beneficiaries compared to nonbeneficiary UI applicants 

Controlling for observable differences across UI eligibility groups in regression models, 

receipt of UI is estimated to increase return to employment by 4.8 percentage points and reduce 

return to TANF by 10.5 percentage points compared to nonbeneficiary UI applicants. In these 

models, return to employment is more likely among those who are younger, female, African 

American, worked in more calendar quarters before applying for UI, had multiple employers in 

calendar quarters before UI application, and had prior employment in agriculture, manufacturing, 

administrative support, or hospitality industries. The models suggest that return to TANF is less 

likely among UI applicants who are older, male, not African American, had employment in more 

calendar quarters before UI application, lived in areas with lower unemployment, and worked 

outside the hospitality industry. 

6.1.6 UI beneficiaries compared to UI nonapplicants

Controlling for observable characteristics, there is no measurable difference in the rate of 

return to employment between the UI beneficiaries and nonapplicants. Reemployment is 

positively correlated with higher base period earnings, more quarters with employment prior to 

TANF exit, and having multiple employers in any calendar quarter between TANF exit and new 

unemployment.

 28Since our unemployment methodology relying on quarterly earnings probably underestimates the 

incidence of unemployment, the numbers of UI beneficiaries would probably have been higher.
89

Compared to UI nonapplicants with similar characteristics, UI beneficiaries return to 

TANF at a rate 2.5 percentage points higher. However, only 30 percent of UI beneficiaries 

return to TANF, compared with 36 percent of UI nonapplicants who do. This suggests that 

increased self-sufficiency may be attributable to receipt of UI benefit payments. Compared to 

nonapplicants, UI beneficiaries are more likely to be older, male, African American, have higher 

base period earnings, and have more quarters with employment between TANF exit and new 

unemployment. 

6.1.7 UI nonapplicants compared to nonbeneficiary UI applicants

Applicants for UI who fail to receive benefit payments return to work at significantly 

lower rates than UI nonapplicants in simple comparisons. Controlling for observable 

characteristics reduces the difference to 4 percentage points, but regression controls do not 

entirely eliminate the difference. In terms of observable characteristics, nonbeneficiary 

applicants tend to have low preunemployment earnings and employment; they also have high 

rates of job quits and employer discharge. 

UI applicants who do not receive benefits return to TANF at much higher rates (45 

percent) than UI nonapplicants (36 percent). Controlling for observable characteristics, the 

return to TANF rate is still greater for nonbeneficiary UI applicants, and the difference from UI 

nonapplicants is greater (12 percentage points). Independent variables in the models suggest that 

return to TANF is less likely among those with high earnings in what would be the UI base 

period and more calendar quarters with earnings between TANF exit and new unemployment. 

Among newly unemployed TANF leavers, those who do not apply for UI benefits are 

much more successful than nonbeneficiary UI applicants. Relative to UI applicants who do not 

become beneficiaries, UI nonapplicants tend to be younger, female, have lower base period 

earnings, and have fewer quarters with employment between TANF exit and new 

unemployment. 

6.1.8 Summary of contrasts

Nonbeneficiary UI applicants are least successful at maintaining self-sufficiency in 

comparison to either UI beneficiaries or UI nonapplicants. These results persist even when 

controlling for observable characteristics of the individuals and their labor markets. UI 

application for this group may be correlated with return to TANF, because federal and state 
90

TANF eligibility requires UI application despite a low likelihood of qualification and UI benefit 

receipt. We next proceed to investigate the importance of publicly provided employment 

services (ES) for all three groups of newly unemployed TANF leavers. Results of the ES 

investigation are very important for shaping policy for assistance to UI applicants who do not 

receive UI benefits.

6.1.9 Use of the public employment service by unemployed TANF leavers

Evidence from Georgia and Ohio suggests that large proportions of newly unemployed 

TANF leavers use the ES. Among these, sizeable numbers of UI nonapplicants use ES services, 

but usage rates are significantly higher among UI applicants. Importantly, ES usage rates are 

similar between UI beneficiaries and nonbeneficiary UI applicants. This suggests that 

application for UI is a pathway to reemployment services provided by the ES even if cash UI 

benefits are not forthcoming. 

Among newly unemployed TANF leavers in Georgia, 14 percent of UI nonapplicants 

receive at least one core ES service after new unemployment, while a core service was used by 

78 percent of UI beneficiaries and 77 percent of UI-ineligible applicants. In Ohio, the core 

service, called “job seeker match,” was used by 8 percent of UI nonapplicants, 45 percent of UI

beneficiaries, and 48 percent of ineligible UI applicants. Usage rates are lower for intensive 

services, but similar patterns of ES usage across UI involvement groups are seen in both states. A 

key contrast is the dramatically higher rates of usage of either core or intensive services by 

ineligible UI applicants (77 percent), compared to UI nonapplicants (14 percent) who were 

recently unemployed.

6.1.10 Employment services and return to employment and TANF

For our samples of newly unemployed TANF leavers in Georgia and Ohio, public 

employment services help to maintain connections with employment opportunities, particularly 

for the working poor. This is true regardless of the degree of involvement with UI, and despite 

the fact that UI applicants use the ES more often than UI nonapplicants. Additionally there is 

evidence that use of services through the ES reduces rates of complete TANF dependency and 

inactivity. Our analysis suggests that core services are likely to be more effective than intensive 

services. However, this result may be an artifact of the limited time frame we have for observing 
91

a positive outcome, combined with the fact that core services are received sooner in a jobless 

spell. 

The largest estimates of ES are for the most popular core service: job referrals. In 

Georgia, job referrals boost reemployment rates by 7, 5, and 11 percentage points respectively 

for UI nonapplicants, UI beneficiaries, and nonbeneficiary UI applicants. Job-referral impact 

estimates are also positive and significant on employment in Ohio for all three UI involvement 

groups: the point estimates are 6, 8, and 5 percentage points of increased employment rates 

respectively for UI nonapplicants, UI beneficiaries, and nonbeneficiary UI applicants. 

A uniformly favorable result following job referrals is a reduction in inactivity for all 

newly unemployed TANF leavers. Inactivity means a lack of involvement with either 

employment or TANF. For Georgia, job referrals are measured as reducing inactivity 5, 4, and 8 

percentage points respectively for UI nonapplicants, UI beneficiaries, and nonbeneficiary UI 

applicants. For Ohio, estimates of these effects for the same groups are 5, 8, and 5 percentage 

points.

Among all effect estimates for job referrals, results are particularly encouraging for nonbeneficiary UI applicants. The largest positive effects on employment and self-sufficiency 

(employment without TANF) are measured for these newly unemployed TANF leavers who 

connect with the ES at dramatically higher rates than UI nonapplicants.

6.1.11 Employment services and income

Instead of simply trying to find a job, newly unemployed TANF leavers might be using 

ES services as part of a strategy to maximize total combined income from all sources, including 

employment earnings, UI benefits, and TANF. Job interview referrals had positive impacts on 

employment earnings for all newly unemployed TANF leavers in Georgia. Positive and 

statistically significant impacts of $352 and $1,171 were estimated for UI beneficiaries and nonbeneficiary UI applicants, respectively, over a year. For the Ohio sample, impact estimates for 

job interview referrals are positive and large for UI nonapplicants ($409) and for nonbeneficiary 

UI applicants ($464). While the job referral impact for Ohio UI beneficiaries is not different 

from zero, the impact for job placements on this group is $1,665 in the year after the UI benefit 

year begin date. In both states, for all three groups defined by degree of involvement with UI, 

employment earnings makes up the biggest part of total income.
92

Analysis of newly unemployed TANF leavers using public employment services in 

Georgia and Ohio show the ES to be an important partner with UI in providing income security. 

The central message that emerges is that connections with employment opportunities improve 

labor market success for newly unemployed TANF leavers, particularly for those who remain the 

working poor. This appears to be true regardless of the degree of involvement with UI, and, 

despite the fact that UI applicants use the ES more often, this result still holds for UI nonapplicants. Additionally, there is evidence that use of services through the ES reduces rates of 

complete TANF dependency and inactivity. 

6.2 Conclusions

The central result that half of newly unemployed TANF leavers who apply for UI receive 

benefits is encouraging news compared to earlier estimates of no higher than one-third. The 

main reasons for ineligibility are job separations due to voluntary quits and employer dismissals 

for cause. Our analysis identifies characteristics of UI applicants most likely to have quit or been 

fired. This information can guide preemptive job retention interventions. 

Nonapplicants for UI constitute three-quarters of all newly unemployed TANF leavers. 

A large proportion of these UI nonapplicants return to employment and stay off TANF in the 

near term. However, many slip back to TANF dependency or inactivity—that is, being off 

TANF and not working. Among UI applicants, UI beneficiaries are much more successful at 

returning to employment and staying off TANF in the near future. It is disappointing that only 

28 percent of newly unemployed TANF leavers likely to be UI-eligible actually take up UI. 

Connecting the jobless with UI can promote self-sufficiency. 

Application for UI not only might lead to cash benefits, it can also connect unemployed 

TANF leavers with public employment services (ES). Reemployment services through the ES, 

particularly core Wagner-Peyser services, get newly unemployed TANF leavers back to work 

and earning. These ES services are used by ineligible UI applicants as much as by UI 

beneficiaries and are equally effective for both groups. Nonapplicants for UI appear to wait a 

long time before using ES services. Our analysis yields clear instructions for targeting services 

to those less likely to connect with UI and ES during unemployment after TANF exit.
93

6.3 Extensions

The lessons learned in this study can be used to inform policies promoting activation 

from dependency for recent recipients of public assistance. Some of our most informative data 

came from the state of Georgia, where we observed trends in activity from the start of TANF in 

1996 up to the beginning of 2005. In that time, more than 152,000 adults left TANF caseloads in 

Georgia. Currently there are fewer than 3,000 adults on TANF cases in Georgia. It is 

undeniable that TANF changed welfare as we knew it. But while caseloads have vanished, need 

remains. 

Former TANF recipients and others vulnerable to welfare dependency are turning to 

multiple sources to replace cash public assistance. In addition to providing income, employment 

is now an essential for accessing publicly provided health insurance for the needy, food-buying 

assistance, and other supportive services. The latter might include child care, transportation 

assistance, and housing subsidies. Policy can no longer focus only on reducing TANF caseloads. 

Since employment has become the foundation for alleviating persistent hardship, more attention 

must be given to coordination with employment programs. 

The roles of UI and ES for low income Americans in a post-TANF economy must be 

better understood. The degree to which this population is served under current arrangements 

should be documented. We must also learn about the extent to which initiatives of UI 

modernization and ES revitalization under the American Recovery and Reinvestment Act 

broaden the effectiveness of these programs for our most vulnerable households. Additionally, 

we should identify federal and state program changes to make these institutions accessible, 

sustainable, and more compatible for employers and job seekers in competitive labor markets. 
94
95

APPENDIX A

SUPPLEMENTARY TABLES
96
97

Table A.1 Characteristics of Newly Unemployed TANF Leavers by UI Application Status and State

 (all differences significantly different from zero at the 90 percent confidence level unless otherwise noted by “#”)

Florida Georgia Michigan 

UI Applicant Status Yes No Yes No Yes No 

Description 18,309 27,936 Diff. 27,257 96,444 Diff. 4,776 16,267 Diff. 

Age at TANF Exita 31.9 30.0 29.1 0.86 29.7 27.6 2.12 

 Age 18–24 0.219 0.308 0.369 −0.061 0.326 0.459 −0.133 

 Age 25–44 0.720 0.633 0.572 0.061 0.623 0.498 0.125 

 Age 45+ 0.062 0.059 0.059 −0.000# 0.050 0.042 0.008 

Gender, male 0.187 — — — 0.231 0.187 0.043 

Gender, female 0.813 — — — 0.769 0.813 −0.043 

Race, whiteb 0.255 0.206 0.300 −0.094 0.475 0.529 −0.054 

Race, black 0.432 0.781 0.683 0.098 0.466 0.417 0.049 

Race, Hispanic 0.287 0.009 0.011 −0.003 0.044 0.039 0.005 

Race, Native American 0.003 0.000 0.000 −0.000# 0.008 0.008 0.000# 

Race, Asian/Pacific Islander 0.012 0.004 0.004 −0.001# 0.007 0.007 −0.000# 

Race, other 0.011 0.001 0.001 −0.000# 0.000 0.000 −0.000# 

Adults on case at exit 1.20 1.25 −0.05 1.08 1.10 −0.02 

Children < age 18 on case at exit 1.95 1.90 0.05 1.64 1.57 0.07 

Children < age 6 on case at exit 0.88 0.90 −0.02 0.74 0.79 −0.05 

Qtrs., exit to new unemployment 5.4 4.1 1.30 4.6 3.8 0.78 5.0 3.7 1.24 

Qtrs. employed before exit (of 12) 5.7 5.6 0.16 6.0 5.4 0.59 7.2 6.1 1.10 

Avg. qtrly. earnings before exit ($) 2,197 1,994 203 1,916 1,721 195 2,501 1,818 683 

Avg. qtrly. earnings after exit ($) 3,037 2,244 793 2,683 2,154 529 3,272 1,960 1,312 

Multiple employers exit-to-unempl. 0.520 0.480 0.040 0.465 0.422 0.043 0.445 0.384 0.060 

Qtrs. employed before unempl. (of 12) 8.7 7.7 1.04 8.4 7.4 0.99 9.3 7.8 1.45 

Employed 1–4 qtrs. before unempl. 0.102 0.227 −0.125 0.128 0.242 −0.113 0.068 0.197 −0.129 

Employed 5–8 qtrs. before unempl. 0.320 0.304 0.016 0.347 0.345 0.002# 0.265 0.329 −0.064 

Employed 9–12 qtrs. before unempl. 0.578 0.470 0.109 0.525 0.414 0.111 0.668 0.475 0.193 

Base period earningsc ($) 11,880 8,239 3,641 9,946 7,640 2,307 12,531 7,260 5,271 

High quarter earnings in basec ($) 4,233 3,266 967 3,851 3,096 755 4,620 2,988 1,632 

Base earnings < $10,000c 0.485 0.688 −0.204 0.615 0.753 −0.138 0.438 0.754 −0.316 

Amount of last TANF payment ($) 409 409 −0 450 453 −4 622 634 −12 

Unemployment rate at exitd 4.6 5.0 4.8 0.27 6.0 5.9 0.09 

UNRATE at new unemployment 5.0 5.1 4.7 0.39 7.3 6.8 0.50 
Table A.1 (Continued)

98

Florida Georgia Michigan 

UI Applicant Status Yes No Yes No Yes No 

Description 18,309 27,936 Diff. 27,257 96,444 Diff. 4,776 16,267 Diff. 

UNRATE ∆ year prior to exit −0.5 −0.2 −0.2 0.01# 1.5 1.5 0.02 

UNRATE ∆ TANF to new unempl. 0.5 0.0 −0.1 0.12 1.2 0.8 0.40 

Empl. (000s) at TANF exitd 564.609 121.402 125.716 −4.314 379.607 376.475 3.132# 

Empl. (000s) at new unemployment 565.052 124.473 129.047 −4.574 366.341 366.387 −0.046# 

Employment % ∆ year prior to exit 2.4 2.0 2.3 −0.29 −1.8 −1.8 −0.04# 

Employment % ∆ exit to new unempl. 1.2 1.9 2.2 −0.27 −3.0 −2.2 −0.82 

Agriculture, forestry, fishing 0.019 0.007 0.006 0.001# 0.006 0.004 0.002#

Mining 0.000 0.000 0.000 0.000# 0.000 0.000 0.000#

Utilities 0.001 0.001 0.001 0.000# 0.000 0.000 0.000#

Construction 0.035 0.022 0.019 0.002 0.043 0.019 0.024

Manufacturing 0.061 0.198 0.107 0.091 0.109 0.065 0.043

Wholesale trade 0.030 0.033 0.027 0.006 0.020 0.014 0.006

Retail trade 0.128 0.144 0.166 −0.022 0.162 0.195 −0.033

Transportation, warehousing 0.033 0.019 0.019 0.000# 0.020 0.012 0.008

Information 0.018 0.019 0.015 0.004 0.013 0.009 0.004

Finance and insurance 0.019 0.018 0.014 0.004 0.026 0.013 0.014

Real estate, rental, leasing 0.017 0.013 0.011 0.002 0.016 0.013 0.003#

Professional, scientific, technical 0.034 0.012 0.010 0.002 0.024 0.019 0.005

Company/enterprise management 0.010 0.000 0.000 0.000# 0.003 0.002 0.001#

Admin., support and waste mgmt. 0.186 0.156 0.152 0.004# 0.165 0.157 0.008#

Educational services 0.020 0.023 0.038 −0.015 0.022 0.034 −0.012

Health care/social assistance 0.099 0.124 0.135 −0.011 0.140 0.128 0.012

Art, entertainment, recreation 0.009 0.004 0.005 −0.001# 0.017 0.016 0.002#

Accommodation and food services 0.117 0.149 0.215 −0.066 0.126 0.214 −0.088

Other services (except publ. admin.) 0.028 0.027 0.029 −0.002 0.028 0.027 0.002#

Public administration 0.016 0.027 0.026 0.000# 0.011 0.010 0.001#

Unclassifiable 0.013 0.002 0.003 −0.000# 0.006 0.006 0.001#

Missing 0.107 0.000 0.000 0.039 0.043 −0.004#

NOTE: — = not available. a In Florida, because there are no characteristic data available to define age at TANF exit, we initially start with age as of BYB (benefit year beginni

average length of time from TANF exit to new unemployment is 5.4 quarters for UI applicants (or 1.4 years), the average age at TANF exit is set at 31

b Because Florida uses Hispanic and non-Hispanic distinctions in its race categories (White, non-Hispanic, White and Hispanic, Black non-Hispanic

are not strictly comparable to the other states. c Defined for both applicants and nonapplicants as the first four of the five quarters preceding the quarter of new unemployment. d The LMI data are monthly by county, and the means presented here are weighted by sample inflow and are not statewide aggregates.
99

Table A.2 Newly Unemployed TANF-Leaver UI Applicants Who Have Monetarily Eligible UI Claims, Compared by Characte

TANF-Leaver UI Applicants

Description

Florida Georgia Michigan 

Monetarily

eligible

(n = 17,331)

All other

claimants

(n = 978)

Monetarily 

eligible

(n = 24,294)

All other 

claimants

(n = 2,963)

Monetarily 

eligible

(n = 4,687)

All other 

claimants

(n = 89)

M

(n 

Age at BYB 33.4** 30.9 31.6** 30.2 31.4 32.5 

 18–24 0.213** 0.319 0.225** 0.275 0.256* 0.148 

 25–44 0.724** 0.640 0.738** 0.710 0.670** 0.815 

 45+ 0.063** 0.041 0.036** 0.015 0.074 0.037 

Gender, male 0.188** 0.160 0.084** 0.070 0.235 0.154 

Gender, female 0.812** 0.840 0.916** 0.930 0.765 0.846 

Race, white 0.255 0.252 0.192** 0.229 0.473 0.547 

Race, black 0.429** 0.482 0.783** 0.743 0.467 0.395 

Race, Hispanic 0.289** 0.245 0.009 0.010 0.053 0.047 

Race, other 0.026 0.021 0.016 0.018 0.015 0.035 

Education, less than high school 0.359** 0.418 0.275** 0.349 0.258** 0.539 

Education, HS grad/GED 0.494** 0.456 0.533** 0.504 0.467** 0.315 

Education, some college 0.114 0.107 0.171** 0.133 0.240** 0.101 

Education, bachelor’s degree or higher 0.034** 0.019 0.021** 0.014 0.035 0.045 

Base period earnings ($) 11,892** 2,497 9,926** 2,779 11,311** 5,836 

High quarter earnings in base ($) 4,118** 1,636 4,981** 2,040 4,425** 3,026 

Base earnings < $10,000 0.485** 0.979 0.626** 0.977 0.524** 0.865 

Multiple employers, any base qtr. 0.510** 0.450 0.505** 0.374 0.507 0.427 

Qtrs., TANF exit to unemployment 5.5** 3.8 4.8** 2.4 5.0** 3.7 

Consec. qtrs. employed before exit 3.1** 1.7 3.1** 1.4 7.3** 4.8 

 0 or 1 0.499** 0.735 0.454** 0.722 0.077** 0.236 

 2–4 0.280** 0.184 0.329** 0.237 0.185** 0.292 

 5–8 0.098** 0.042 0.115** 0.024 0.298 0.270 

 9–12 0.124** 0.039 0.102** 0.017 0.440** 0.202 

Qtrs. employed before BYB 8.5** 6.2 8.6** 5.4 8.9** 6.2 

 4 quarters or less 0.104** 0.356 0.092** 0.426 0.083** 0.315 

 5–8 0.339 0.349 0.344** 0.400 0.286** 0.472 

 9–12 0.556** 0.296 0.563** 0.174 0.631** 0.213 

Adults on case at exit 1.20 1.19 1.08 1.06

Children under age 18 on case 1.95 1.95 1.91 1.78
Table A.2 (Continued)

100

Description

Florida Georgia Michigan 

Monetarily

eligible

(n = 17,331)

All other

claimants

(n = 978)

Monetarily 

eligible

(n = 24,294)

All other 

claimants

(n = 2,963)

Monetarily 

eligible

(n = 4,687)

All other 

claimants

(n = 89)

M

(n 

Children under age 6 on case 0.88** 0.93 0.87 0.80

Agriculture, forestry, fishing a 0.018** 0.036 0.006** 0.013 0.006** 0.045 

Mining 0.000 0.000 0.000 0.000 0.001 0.000 

Utilities 0.001 0.000 0.001 0.000 0.000 0.000 

Construction 0.035** 0.024 0.021 0.026 0.039 0.011 

Manufacturing 0.062** 0.034 0.193 0.198 0.101 0.079 

Wholesale trade 0.030** 0.018 0.034* 0.027 0.020 0.000 

Retail trade 0.127** 0.149 0.147** 0.128 0.164 0.146 

Transportation, warehousing 0.033 0.033 0.020 0.018 0.021 0.011 

Information 0.018 0.016 0.020** 0.012 0.014 0.011 

Finance and insurance 0.019 0.015 0.019** 0.013 0.026 0.034 

Real estate, rental, leasing 0.018** 0.008 0.012 0.010 0.017 0.000 

Professional, scientific, technical 0.034 0.038 0.013 0.011 0.026 0.011 

Company management 0.009 0.014 0.000 0.000 0.002 0.000 

Admin., support, waste mgmt. 0.182** 0.253 0.154** 0.197 0.174 0.157 

Educational services 0.020** 0.030 0.024 0.023 0.022 0.022 

Health care/social assistance 0.100** 0.076 0.128** 0.106 0.143 0.124 

Art, entertainment, recreation 0.008** 0.016 0.004 0.003 0.017 0.011 

Accommodation, food 0.115** 0.155 0.148** 0.169 0.128** 0.202 

Other services (except publ. admin.) 0.028 0.030 0.026 0.021 0.028 0.011 

Public administration 0.016 0.014 0.027 0.024 0.011 0.000 

Unclassifiable 0.012** 0.037 0.003 0.002 0.006 0.011 

Industry missing 0.112** 0.004 0.000 0.000 0.037** 0.112 

Mgmt., business, financial 0.048* 0.035 0.031** 0.015

Professional, related occupations 0.076 0.075 0.059** 0.038

Services 0.222 0.225 0.258 0.251

Sales and related occupations 0.119** 0.149 0.066** 0.052

Office, administrative support 0.193** 0.162 0.229** 0.198

Farming, fishing and forestry 0.009 0.007 0.007 0.007

Construction and extraction 0.030 0.028 0.016 0.016

Install, maintain, repair 0.027** 0.016 0.009 0.008

Production 0.102 0.105 0.165** 0.201

Transportation, material moving 0.055** 0.074 0.109* 0.119

Occupation missing 0.105 0.122 0.050** 0.095
Table A.2 (Continued)

101

Description

Florida Georgia Michigan 

Monetarily

eligible

(n = 17,331)

All other

claimants

(n = 978)

Monetarily 

eligible

(n = 24,294)

All other 

claimants

(n = 2,963)

Monetarily 

eligible

(n = 4,687)

All other 

claimants

(n = 89)

M

(n 

Unemployment rate, month of BYB 5.0** 4.9 5.0** 5.3 7.1 7.3 

Unemployment rate, TANF exit 4.4** 4.2 5.1** 5.3 6.0 5.9 

Change, unempl. rate, year-ago BYB 0.3 0.4 −0.1** −0.2 1.1* 1.5 

Change, unempl. rate over benefit year 0.4** 0.5 −0.2 −0.2 0.6** 1.0 

Change, unempl. rate, TANF to BYB 0.7** 0.8 −0.1 −0.1 1.1 1.4 

Change unempl. rate, exit to BYE 1.0** 1.3 −0.3 −0.3 1.6* 2.3 

Pct. chg., labor force, year-ago BYB 1.3** 1.7 1.3 1.3 −1.0 −1.0 

Employed (000s), month of BYB 568.2** 510.7 126.3** 98.2 365.9 454.9 

Employed (000s), at TANF exit 568.9** 512.2 123.8** 97.3 377.7 468.9 

Pct. chg., employment, year-ago BYB 1.0** 1.4 1.4 1.5 −2.2 −2.6 

Pct. chg., employment, over ben. year 0.6** 0.2 1.5** 1.2 −0.9 −1.5 

Pct. chg., employ., TANF exit to BYB 0.9 0.7 1.5** 0.6 −2.6 −2.4 

Pct. chg., employ., TANF exit to BYE 1.6** 1.0 3.1** 1.8 −3.5 −3.9 

BYB in 1st qtr. 0.236** 0.299 0.240 0.237 0.254 0.247 

BYB in 2nd qtr. 0.264 0.264 0.250 0.256 0.235 0.247 

BYB in 3rd qtr. 0.270** 0.234 0.263* 0.248 0.229 0.281 

BYB in 4th qtr. 0.230* 0.203 0.247* 0.259 0.282 0.225 

TANF exit = 1996:2 — — 0.076** 0.062 — — 

TANF exit = 1996:3 — — 0.074** 0.063 — — 

TANF exit = 1996:4 — — 0.072 0.068 — — 

TANF exit = 1997:1 — — 0.065 0.064 — — 

TANF exit = 1997:2 — — 0.052** 0.063 — — 

TANF exit = 1997:3 — — 0.068 0.068 — — 

TANF exit = 1997:4 — — 0.046 0.047 — — 

TANF exit = 1998:1 — — 0.041 0.044 — — 

TANF exit = 1998:2 — — 0.038 0.042 — — 

TANF exit = 1998:3 — — 0.036 0.038 — — 

TANF exit = 1998:4 0.121** 0.037 0.041** 0.054 — — 

TANF exit = 1999:1 0.121** 0.057 0.026** 0.034 — — 

TANF exit = 1999:2 0.122** 0.080 0.037 0.043 — — 

TANF exit = 1999:3 0.102** 0.071 0.034* 0.040 — — 

TANF exit = 1999:4 0.089** 0.122 0.033 0.031 — — 

TANF exit = 2000:1 0.148 0.149 0.033 0.034 — — 

TANF exit = 2000:2 0.087** 0.108 0.036 0.033 — — 
Table A.2 (Continued)

102

Description

Florida Georgia Michigan 

Monetarily

eligible

(n = 17,331)

All other

claimants

(n = 978)

Monetarily 

eligible

(n = 24,294)

All other 

claimants

(n = 2,963)

Monetarily 

eligible

(n = 4,687)

All other 

claimants

(n = 89)

M

(n 

TANF exit = 2000:3 0.077** 0.116 0.034 0.030 — — 

TANF exit = 2000:4 0.066** 0.115 0.029* 0.035 — — 

TANF exit = 2001:1 0.067** 0.146 0.033** 0.023 0.201 0.247 

TANF exit = 2001:2 — — 0.034* 0.028 0.206 0.213 

TANF exit = 2001:3 — — 0.031 0.029 0.227 0.213 

TANF exit = 2001:4 — — 0.032* 0.025 0.192 0.225 

TANF exit = 2002:1 — — — — 0.174* 0.101 

BYB = 1996:2 — — 0.002** 0.013 — — 

BYB = 1996:3 — — 0.008** 0.029 — — 

BYB = 1996:4 — — 0.015** 0.041 — — 

BYB = 1997:1 — — 0.022** 0.042 — — 

BYB = 1997:2 — — 0.031** 0.061 — — 

BYB = 1997:3 — — 0.042** 0.053 — — 

BYB = 1997:4 — — 0.044** 0.063 — — 

BYB = 1998:1 — — 0.048** 0.056 — — 

BYB = 1998:2 — — 0.055 0.054 — — 

BYB = 1998:3 — — 0.059** 0.046 — — 

BYB = 1998:4 0.002 0.000 0.056** 0.044 — — 

BYB = 1999:1 0.009 0.001 0.056 0.050 — — 

BYB = 1999:2 0.028 0.001 0.053 0.047 — — 

BYB = 1999:3 0.038 0.001 0.050 0.043 — — 

BYB = 1999:4 0.040 0.007 0.039 0.042 — — 

BYB = 2000:1 0.054 0.086 0.037 0.035 — — 

BYB = 2000:2 0.078 0.087 0.027 0.029 — — 

BYB = 2000:3 0.090 0.092 0.024** 0.030 — — 

BYB = 2000:4 0.076 0.095 0.024 0.027 — — 

BYB = 2001:1 0.083 0.092 0.024 0.027 0.009 0.000 

BYB = 2001:2 0.086 0.092 0.032** 0.023 0.025 0.034 

BYB = 2001:3 0.088 0.092 0.035** 0.020 0.048 0.056 

BYB = 2001:4 0.081 0.065 0.039** 0.031 0.108 0.067 

BYB = 2002:1 0.065 0.093 0.032** 0.020 0.112 0.135 

BYB = 2002:2 0.057 0.059 0.031* 0.025 0.110 0.112 

BYB = 2002:3 0.043 0.034 0.031** 0.017 0.104** 0.169 

BYB = 2002:4 0.026 0.031 0.023** 0.010 0.103 0.101 

BYB = 2003:1 0.024 0.025 0.017** 0.004 0.083 0.056 
Table A.2 (Continued)

103

Description

Florida Georgia Michigan 

Monetarily

eligible

(n = 17,331)

All other

claimants

(n = 978)

Monetarily 

eligible

(n = 24,294)

All other 

claimants

(n = 2,963)

Monetarily 

eligible

(n = 4,687)

All other 

claimants

(n = 89)

M

(n 

BYB = 2003:2 0.014 0.018 0.014** 0.004 0.067 0.056 

BYB = 2003:3 0.009 0.013 0.011** 0.005 0.056 0.056 

BYB = 2003:4 0.005 0.003 0.007** 0.003 0.056 0.022 

BYB = 2004:1 0.002 0.002 0.004** 0.000 0.045 0.045 

BYB = 2004:2 0.001 0.006 0.003* 0.001 0.032 0.034 

BYB = 2004:3 0.001 0.002 0.002 0.002 0.021 0.000 

BYB = 2004:4 0.000 0.002 0.001 0.000 0.015 0.034 

BYB = 2005:1 — — — — 0.004 0.011 

BYB = 2005:2 0.002* 0.0011

BYB = 2005:3 0.001 0.000

BYB = 2005:4 0.001 0.000

NOTE: — = data not available. BYB = benefit year beginning. BYE = benefit year ending. GED = general equivalency diploma. * Mean for monet

significantly different from the mean for all other claimants at the 90 percent confidence level in a two-tailed test; **mean for monetarily valid claima

from the mean all other claimants at the 95 percent confidence level in a two-tailed test. a New UI data for Ohio received in December 2007 for benefit years beginning in 2003 did not include characteristic information. Therefore, data p

this variable are limited to claims prior to December 31, 2002.
104

Table A.3 Newly Unemployed TANF-Leaver UI Applicants Having Nonmonetarily Eligible UI Claims (acceptable job separati

Compared by Characteristics with All Other UI Applicants

Description

Florida Georgia Michigan 

Nonmonetarily

eligible

(n = 17,331)

All other

applicants

(n = 978)

Nonmonetarily

eligible

(n = 12,789)

All other

applicants

(n = 13,821)

Nonmonetarily

eligible

(n = 1,874)

All other

applicants

(n = 2,902)

Non

(n 

Age at BYB 35.0** 31.8 32.1** 30.8 32.5** 30.7 

 18–24 0.173** 0.258 0.211** 0.248 0.207** 0.284 

 25–44 0.742** 0.700 0.749** 0.727 0.705** 0.651 

 45+ 0.085** 0.042 0.041** 0.026 0.087** 0.065 

Gender, male 0.230** 0.150 0.089** 0.075 0.318** 0.181 

Gender, female 0.770** 0.850 0.911** 0.925 0.682** 0.819 

Race, white 0.211** 0.292 0.178** 0.209 0.515** 0.449 

Race, black 0.402** 0.458 0.793** 0.770 0.415** 0.499 

Race, Hispanic 0.360** 0.224 0.010** 0.008 0.062** 0.047 

Race, other 0.027 0.025 0.019** 0.013 0.019* 0.012 

Education, less than high school 0.387** 0.341 0.263** 0.299 0.261 0.266 

Education, high school grad/GED 0.460** 0.519 0.539** 0.521 0.470 0.461 

Education, some college 0.111 0.115 0.173** 0.163 0.231 0.241 

Education, bachelor’s degree or higher 0.043** 0.025 0.024** 0.017 0.039 0.032 

Base period earnings ($) 11,817** 11,029 9,465** 8,889 11,103 11,269 

High quarter earnings in base ($) 4,160** 3,837 3,939** 3,633 4,552** 4,299 

Base period earnings < $10,000 0.488** 0.531 0.651** 0.677 0.540 0.525 

Multiple employers, any base qtr. 0.477** 0.532 0.486* 0.500 0.487** 0.518 

Qtrs., TANF Exit to Unemployment 5.5** 5.4 4.6 4.6 4.7** 5.1 

Consec. qtrs. employed before exit 3.0* 3.1 3.0** 2.8 7.3** 7.1 

 0 or 1 0.526** 0.499 0.476** 0.490 0.085 0.076 

 2–4 0.267** 0.281 0.319 0.321 0.175* 0.194 

 5–8 0.087** 0.102 0.106 0.105 0.272** 0.315 

 9–12 0.120 0.118 0.099** 0.085 0.467** 0.415 

Qtrs. employed before BYB 8.4 8.4 8.3 8.2 8.7** 9.0 

 4 qtrs. or less 0.128** 0.110 0.129* 0.122 0.105** 0.077 

 5–8 0.328** 0.350 0.341** 0.362 0.281 0.295 

 9–12 0.544 0.541 0.529* 0.516 0.613 0.628 

Adults on case at exit 1.20 1.19 1.11** 1.06

Children under age 18 on case 1.94** 1.97 1.99** 1.86
Table A.3 (Continued)

105

Description

Florida Georgia Michigan 

Nonmonetarily

eligible

(n = 17,331)

All other

applicants

(n = 978)

Nonmonetarily

eligible

(n = 12,789)

All other

applicants

(n = 13,821)

Nonmonetarily

eligible

(n = 1,874)

All other

applicants

(n = 2,902)

Non

(n 

Children under age 6 on case 0.85** 0.92 0.84 0.88

Agriculture, forestry, fishing 0.035** 0.006 0.010** 0.004 0.013** 0.002 

Mining 0.000 0.000 0.000 0.000 0.001 0.000 

Utilities 0.001 0.001 0.000 0.001 0.000 0.001 

Construction 0.047** 0.025 0.027** 0.016 0.068** 0.020 

Manufacturing 0.075** 0.048 0.216** 0.169 0.132** 0.080 

Wholesale trade 0.035** 0.025 0.035* 0.031 0.019 0.019 

Retail trade 0.095** 0.157 0.127** 0.161 0.121** 0.190 

Transportation, warehousing 0.030** 0.036 0.021 0.019 0.024 0.019 

Information 0.018 0.017 0.019 0.020 0.010* 0.016 

Finance and insurance 0.016** 0.022 0.017* 0.020 0.017** 0.031 

Real estate, rental, leasing 0.016 0.019 0.010** 0.014 0.014 0.018 

Professional, scientific, technical 0.036 0.032 0.014** 0.011 0.034** 0.021 

Company management 0.007** 0.012 0.000 0.000 0.002 0.002 

Admin., support, waste mgmt. 0.201** 0.173 0.175** 0.144 0.193** 0.161 

Educational services 0.025** 0.017 0.028** 0.020 0.035** 0.014 

Health care/social assistance 0.074** 0.120 0.111** 0.142 0.107** 0.165 

Art, entertainment, recreation 0.008 0.009 0.004 0.004 0.015 0.018 

Accommodation, food services 0.091** 0.139 0.125** 0.172 0.097** 0.150 

Other services (except publ. admin.) 0.027 0.029 0.027 0.025 0.029 0.028 

Public administration 0.017 0.015 0.029* 0.026 0.015** 0.007 

Unclassifiable 0.014 0.012 0.002 0.003 0.010** 0.003 

Industry missing 0.131** 0.086 0.000 0.000 0.046** 0.034 

Mgmt., business, financial 0.048 0.046 0.025** 0.035 — — 

Professional, related occupations 0.077 0.075 0.063** 0.053 — — 

Services 0.181** 0.257 0.230** 0.293 — — 

Sales and related occupations 0.091** 0.146 0.059** 0.071 — — 

Office, administrative support 0.180** 0.201 0.222** 0.238 — — 

Farming, fishing and forestry 0.012** 0.007 0.009** 0.006 — — 

Construction and extraction 0.041** 0.020 0.020** 0.013 — — 

Install, maintain, repair 0.029** 0.024 0.011** 0.007 — — 

Production 0.124** 0.083 0.195** 0.150 — — 

Transport, material moving 0.060* 0.053 0.128** 0.096 — — 

Occupation missing 0.141** 0.076 0.037 0.039 — — 
Table A.3 (Continued)

106

Description

Florida Georgia Michigan 

Nonmonetarily

eligible

(n = 17,331)

All other

applicants

(n = 978)

Nonmonetarily

eligible

(n = 12,789)

All other

applicants

(n = 13,821)

Nonmonetarily

eligible

(n = 1,874)

All other

applicants

(n = 2,902)

Non

(n 

Unemployment rate, month of BYB 5.2** 4.9 5.1** 4.9 7.1 7.0 

Unemployment rate, TANF exit 4.5** 4.2 5.2** 5.0 6.1* 6.0 

Chg. unempl. rate, year-ago BYB 0.3 0.3 −0.1 −0.1 1.1 1.1 

Chg. unempl. rate over ben. year 0.4 0.4 −0.2** −0.2 0.5** 0.6 

Chg. unempl. rate, end TANF to BYB 0.7** 0.7 −0.1 −0.1 1.0 1.1 

Chg. unempl. rate, end TANF to BYE 1.1** 1.0 −0.3** −0.3 1.6 1.6 

Pct. chg., labor force, year-ago BYB 1.1** 1.5 1.3 1.3 −1.0* −1.0 

Employed (000s), month of BYB 630.6** 507.9 126.2** 118.8 344.1** 380.1 

Employed (000s), at TANF exit 632.5** 507.7 123.9** 116.6 355.1** 392.6 

Pct. chg. employment, year-ago BYB 0.8** 1.2 1.4 1.4 −2.1 −2.2 

Pct. chg. employment over ben. year 0.4** 0.8 1.5 1.4 −0.9 −0.9 

Pct. chg. emplmt., TANF exit to BYB 0.6** 1.2 1.4 1.5 −2.5* −2.7 

Pct. chg. emplmt., end TANF to BYE 1.0** 2.0 2.9 2.9 −3.4 −3.6 

BYB in 1st qtr. 0.229 0.248 0.236 0.243 0.247 0.258 

BYB in 2nd qtr. 0.266 0.262 0.253 0.252 0.225 0.242 

BYB in 3rd qtr. 0.271 0.266 0.262 0.260 0.208** 0.244 

BYB in 4th qtr. 0.234 0.224 0.248 0.246 0.320** 0.255 

TANF exit = 1996:2 — — 0.079** 0.071 — — 

TANF exit = 1996:3 — — 0.074 0.072 — — 

TANF exit = 1996:4 — — 0.073 0.070 — — 

TANF exit = 1997:1 — — 0.069** 0.061 — — 

TANF exit = 1997:2 — — 0.053 0.053 — — 

TANF exit = 1997:3 — — 0.068 0.067 — — 

TANF exit = 1997:4 — — 0.047 0.045 — — 

TANF exit = 1998:1 — — 0.044** 0.038 — — 

TANF exit = 1998:2 — — 0.041** 0.036 — — 

TANF exit = 1998:3 — — 0.038 0.035 — — 

TANF exit = 1998:4 0.105** 0.126 0.042 0.043 — — 

TANF exit = 1999:1 0.109** 0.126 0.027 0.027 — — 

TANF exit = 1999:2 0.111** 0.127 0.035** 0.040 — — 

TANF exit = 1999:3 0.100 0.100 0.033* 0.037 — — 

TANF exit = 1999:4 0.097** 0.085 0.032 0.035 — — 

TANF exit = 2000:1 0.163** 0.135 0.031** 0.036 — — 
Table A.3 (Continued)

107

Description

Florida Georgia Michigan 

Nonmonetarily

eligible

(n = 17,331)

All other

applicants

(n = 978)

Nonmonetarily

eligible

(n = 12,789)

All other

applicants

(n = 13,821)

Nonmonetarily

eligible

(n = 1,874)

All other

applicants

(n = 2,902)

Non

(n 

TANF exit = 2000:2 0.092* 0.085 0.036 0.035 — — 

TANF exit = 2000:3 0.081 0.078 0.032 0.034 — — 

TANF exit = 2000:4 0.068 0.070 0.028 0.031 — — 

TANF exit = 2001:1 0.073 0.069 0.030** 0.034 0.203 0.201 

TANF exit = 2001:2 — — 0.029** 0.037 0.204 0.208 

TANF exit = 2001:3 — — 0.029 0.032 0.235 0.221 

TANF exit = 2001:4 — — 0.030 0.031 0.200 0.188 

TANF exit = 2002:1 — — — — 0.158** 0.182 

BYB = 1996:2 — — 0.004* 0.003 — — 

BYB = 1996:3 — — 0.010 0.010 — — 

BYB = 1996:4 — — 0.018 0.017 — — 

BYB = 1997:1 — — 0.025 0.024 — — 

BYB = 1997:2 — — 0.034 0.034 — — 

BYB = 1997:3 — — 0.046* 0.041 — — 

BYB = 1997:4 — — 0.047 0.045 — — 

BYB = 1998:1 — — 0.048 0.049 — — 

BYB = 1998:2 — — 0.055 0.055 — — 

BYB = 1998:3 — — 0.062** 0.054 — — 

BYB = 1998:4 0.002 0.002 0.055 0.053 — — 

BYB = 1999:1 0.007** 0.011 0.057 0.053 — — 

BYB = 1999:2 0.022** 0.030 0.057** 0.049 — — 

BYB = 1999:3 0.030** 0.042 0.052** 0.046 — — 

BYB = 1999:4 0.030** 0.044 0.038 0.040 — — 

BYB = 2000:1 0.048** 0.062 0.035 0.038 — — 

BYB = 2000:2 0.077 0.079 0.027 0.029 — — 

BYB = 2000:3 0.087 0.093 0.025 0.025 — — 

BYB = 2000:4 0.081** 0.073 0.025 0.023 — — 

BYB = 2001:1 0.085 0.082 0.024 0.025 0.012* 0.007 

BYB = 2001:2 0.094** 0.080 0.030 0.033 0.022 0.026 

BYB = 2001:3 0.104** 0.076 0.030** 0.037 0.046 0.049 

BYB = 2001:4 0.090** 0.072 0.038 0.038 0.131** 0.092 

BYB = 2002:1 0.067 0.067 0.027** 0.034 0.123* 0.106 

BYB = 2002:2 0.058 0.056 0.029 0.032 0.104 0.114 

BYB = 2002:3 0.039** 0.045 0.024** 0.034 0.089** 0.116 

BYB = 2002:4 0.025 0.027 0.020* 0.023 0.115** 0.095 
Table A.3 (Continued)

108

Description

Florida Georgia Michigan 

Nonmonetarily

eligible

(n = 17,331)

All other

applicants

(n = 978)

Nonmonetarily

eligible

(n = 12,789)

All other

applicants

(n = 13,821)

Nonmonetarily

eligible

(n = 1,874)

All other

applicants

(n = 2,902)

Non

(n 

BYB = 2003:1 0.021* 0.026 0.016 0.016 0.071** 0.089 

BYB = 2003:2 0.013 0.016 0.013 0.014 0.061 0.071 

BYB = 2003:3 0.009 0.009 0.010 0.010 0.052 0.059 

BYB = 2003:4 0.005 0.006 0.006 0.006 0.057 0.055 

BYB = 2004:1 0.002 0.002 0.004 0.004 0.038* 0.049 

BYB = 2004:2 0.001 0.001 0.004* 0.002 0.032 0.031 

BYB = 2004:3 0.002* 0.001 0.002 0.002 0.020 0.020 

BYB = 2004:4 0.000 0.000 0.001 0.000 0.018 0.013 

BYB = 2005:1 — — — — 0.005 0.004 

BYB = 2005:2 — — — — 0.002 0.003

BYB = 2005:3 — — — — 0.001 0.001

BYB = 2005:4 — — — — 0.001 0.001

NOTE: — = data not available. BYB = benefit year beginning. BYE = benefit year ending. GED = general equivalency diploma. * Nonmonetarily 

different from the mean for all other UI applicants at the 90 percent confidence level in a two-tailed test; **nonmonetarily eligible mean significantly 

all other UI applicants at the 95 percent confidence level in a two-tailed test. a New UI data for Ohio that was received in December 2007 for UI claims beginning in 2003 did not include the characteristic information needed to 

eligibility. Therefore, the means presented for Ohio are for UI claims prior to December 31, 2002. Also, nonmonetary eligibility combines two sourc

and 2) an individual’s presence in the agency’s nonmonetary determination file.
109

Table A.4 Newly Unemployed TANF-Leaver UI Applicants Who Quit Their Prior Employment, Compared by Characteristics 

Leaver UI Applicants

Description

Florida Georgia Michigan 

Quit prior 

employment

(n = 3,675)

All other

applicants

(n = 14,364)

Quit prior

employment

(n = 4,628)

All other

applicants

(n = 21,982)

Quit prior

employment

(n = 831)

All other

applicants

(n = 3,945)

e

Age at BYB 31.4** 33.8 30.4** 31.7 31.6 31.4 

 18–24 0.281** 0.203 0.265** 0.222 0.250 0.255 

 25–44 0.677** 0.730 0.709** 0.743 0.670 0.672 

 45+ 0.041** 0.067 0.026** 0.034 0.080 0.072 

Gender, male 0.131** 0.200 0.065** 0.085 0.193** 0.243 

Gender, female 0.869** 0.800 0.935** 0.915 0.807** 0.757 

Race, white 0.312** 0.241 0.226** 0.188 0.488 0.472 

Race, black 0.418** 0.436 0.752** 0.787 0.449 0.469 

Race, Hispanic 0.241** 0.298 0.007 0.009 0.051 0.053 

Race, other 0.029 0.025 0.014 0.016 0.025** 0.013 

Education, less than high school 0.331** 0.370 0.306** 0.277 0.271 0.262 

Education, high school grad/GED 0.534** 0.481 0.530 0.530 0.457 0.466 

Education, some college 0.105* 0.115 0.149** 0.172 0.235 0.237 

Education, bachelor’s degree or higher 0.029 0.034 0.015** 0.022 0.036 0.035 

Base period earnings ($) 10,486** 11,618 8,367** 9,334 10,954 11,258 

High quarter earnings in base ($) 3,662** 4,066 3,427** 3,855 4,214** 4,437 

Base period earnings < $10,000 0.562** 0.499 0.707** 0.655 0.557 0.526 

Multiple employers, any base qtr. 0.567** 0.492 0.512** 0.489 0.572** 0.492 

Qtrs., TANF exit to unemployment 5.2** 5.5 4.5* 4.6 5.1 5.0 

Consec. qtrs. employed before exit 3.1 3.0 2.8 2.9 7.0** 7.3 

 0 or 1 0.497* 0.515 0.503** 0.479 0.087 0.078 

 2–4 0.291** 0.270 0.306** 0.323 0.206 0.183 

 5–8 0.091 0.096 0.100 0.107 0.312 0.295 

 9–12 0.120 0.119 0.090 0.092 0.396** 0.444 

Qtrs. employed before BYB 8.3** 8.4 8.2 8.2 8.8 8.9 

 4 qtrs. or Less 0.120 0.117 0.122 0.126 0.086 0.088 

 5–8 0.364** 0.334 0.363* 0.350 0.313 0.285 

 9–12 0.516** 0.549 0.514 0.524 0.601 0.627 
Table A.4 (Continued)

110

Description

Florida Georgia Michigan 

Quit prior 

employment

(n = 3,675)

All other

applicants

(n = 14,364)

Quit prior

employment

(n = 4,628)

All other

applicants

(n = 21,982)

Quit prior

employment

(n = 831)

All other

applicants

(n = 3,945)

e

Total adults on case 1.19 1.20 1.09 1.07 

Total children (< 18) on case 1.96 1.96 1.91 1.91 

Total children (< 6) on case 0.94** 0.88 0.82 0.87 

Agriculture, forestry, fishing 0.007** 0.022 0.005 0.007 0.003 0.007 

Mining 0.000 0.000 0.000 0.000 0.001 0.001 

Utilities 0.001 0.001 0.000 0.001 0.000 0.001 

Construction 0.023** 0.038 0.016** 0.022 0.018** 0.043 

Manufacturing 0.045** 0.064 0.203** 0.190 0.066** 0.108 

Wholesale trade 0.028 0.030 0.026** 0.035 0.018 0.020 

Retail trade 0.169** 0.118 0.157** 0.142 0.198** 0.156 

Transportation, warehousing 0.040** 0.031 0.013** 0.021 0.024 0.020 

Information 0.015 0.018 0.017 0.020 0.011 0.014 

Finance and insurance 0.019 0.019 0.017 0.019 0.025 0.026 

Real estate, rental, leasing 0.018 0.017 0.010 0.013 0.009* 0.018 

Professional, scientific, technical 0.032 0.035 0.008** 0.013 0.021 0.027 

Company management 0.013** 0.009 0.000 0.000 0.003 0.002 

Admin., support, waste mgmt. 0.181 0.187 0.139** 0.163 0.178 0.173 

Educational services 0.024 0.020 0.021 0.025 0.015 0.024 

Health care/social assistance 0.127** 0.092 0.137** 0.125 0.151 0.140 

Art, entertainment, recreation 0.009 0.009 0.003 0.004 0.016 0.017 

Accommodation, food services 0.144** 0.110 0.174** 0.145 0.168** 0.121 

Other services (except publ. admin.) 0.028 0.028 0.022 0.026 0.024 0.029 

Public administration 0.016 0.016 0.026 0.028 0.010 0.010 

Unclassifiable 0.012 0.013 0.003 0.003 0.003 0.006 

Industry missing 0.049** 0.121 0.000 0.000 0.041 0.038 

Mgmt., business, financial 0.041** 0.048 0.029 0.030 — — 

Professional, related occupations 0.070 0.077 0.048** 0.060 — — 

Services 0.265** 0.212 0.292** 0.256 — — 

Sales and related occupations 0.145** 0.115 0.064 0.065 — — 

Office, administrative support 0.201* 0.189 0.237 0.229 — — 

Farming, fishing, and forestry 0.007 0.010 0.006 0.008 — — 

Construction and extraction 0.019** 0.032 0.010** 0.018 — — 

Install, maintain, repair 0.021** 0.028 0.007 0.009 — — 

Production 0.087** 0.106 0.170 0.172 — — 

Transport, material moving 0.049** 0.058 0.098** 0.114 — — 
Table A.4 (Continued)

111

Description

Florida Georgia Michigan 

Quit prior 

employment

(n = 3,675)

All other

applicants

(n = 14,364)

Quit prior

employment

(n = 4,628)

All other

applicants

(n = 21,982)

Quit prior

employment

(n = 831)

All other

applicants

(n = 3,945)

e

Occupation missing 0.089** 0.110 0.038 0.038 — — 

Unemployment rate, month of BYB 4.9** 5.1 5.0 5.0 7.1 7.0 

Unemployment rate, TANF exit 4.2** 4.4 5.1 5.1 6.0 6.0 

Chg. unempl. rate, year-ago BYB 0.3 0.3 −0.1 −0.1 1.1 1.1 

Chg. unempl. rate over benefit year 0.4 0.4 −0.2 −0.2 0.6 0.6 

Chg. unempl. rate, end TANF to BYB 0.7 0.7 −0.1 −0.1 1.1 1.0 

Chg. unempl. rate, end TANF to BYE 1.0 1.1 −0.3 −0.3 1.7 1.6 

Pct. chg., labor force, year-ago BYB 1.6** 1.3 1.4 1.3 −1.0 −1.0 

Employed (000s), month of BYB 481.1** 584.3 103.9** 126.2 374.8 364.5 

Employed (000s), at TANF exit 480.6** 585.4 102.2** 123.8 387.3 376.2 

Pct. chg. employment, year-ago BYB 1.3** 1.0 1.5 1.4 −2.2 −2.2 

Pct. chg. employment over benefit year 0.8** 0.5 1.3** 1.5 −0.9 −0.9 

Pct. chg. employment, TANF exit to BYB 1.2** 0.9 1.4 1.4 −2.6 −2.6 

Pct. chg. employment, end TANF to BYE 2.0** 1.4 2.7** 3.0 −3.5 −3.5 

BYB in 1st qtr. 0.237 0.240 0.243 0.239 0.252 0.254 

BYB in 2nd qtr. 0.266 0.263 0.251 0.252 0.240 0.234 

BYB in 3rd qtr. 0.273 0.267 0.261 0.261 0.250 0.226 

BYB in 4th qtr. 0.223 0.230 0.245 0.248 0.258 0.286 

TANF exit = 1996:2 — — 0.073 0.075 — — 

TANF exit = 1996:3 — — 0.081** 0.071 — — 

TANF exit = 1996:4 — — 0.077 0.070 — — 

TANF exit = 1997:1 — — 0.065 0.065 — — 

TANF exit = 1997:2 — — 0.052 0.053 — — 

TANF exit = 1997:3 — — 0.070 0.067 — — 

TANF exit = 1997:4 — — 0.044 0.047 — — 

TANF exit = 1998:1 — — 0.035** 0.042 — — 

TANF exit = 1998:2 — — 0.035 0.039 — — 

TANF exit = 1998:3 — — 0.034 0.037 — — 

TANF exit = 1998:4 0.135** 0.111 0.043 0.042 — — 

TANF exit = 1999:1 0.121 0.117 0.027 0.027 — — 

TANF exit = 1999:2 0.130** 0.117 0.040 0.038 — — 

TANF exit = 1999:3 0.093* 0.102 0.033 0.035 — — 

TANF exit = 1999:4 0.088 0.092 0.032 0.034 — — 
Table A.4 (Continued)

112

Description

Florida Georgia Michigan 

Quit prior 

employment

(n = 3,675)

All other

applicants

(n = 14,364)

Quit prior

employment

(n = 4,628)

All other

applicants

(n = 21,982)

Quit prior

employment

(n = 831)

All other

applicants

(n = 3,945)

e

TANF exit = 2000:1 0.133** 0.152 0.032 0.034 — — 

TANF exit = 2000:2 0.088 0.088 0.029** 0.037 — — 

TANF exit = 2000:3 0.075 0.080 0.031 0.034 — — 

TANF exit = 2000:4 0.067 0.069 0.029 0.030 — — 

TANF exit = 2001:1 0.070 0.071 0.032 0.032 0.195 0.203 

TANF exit = 2001:2 — — 0.035 0.033 0.199 0.208 

TANF exit = 2001:3 — — 0.037** 0.029 0.214 0.229 

TANF exit = 2001:4 — — 0.035** 0.029 0.218** 0.188 

TANF exit = 2002:1 — — — — 0.174 0.172 

BYB = 1996:2 — — 0.005 0.004 — — 

BYB = 1996:3 — — 0.011 0.010 — — 

BYB = 1996:4 — — 0.021* 0.017 — — 

BYB = 1997:1 — — 0.026 0.024 — — 

BYB = 1997:2 — — 0.038 0.033 — — 

BYB = 1997:3 — — 0.047 0.043 — — 

BYB = 1997:4 — — 0.047 0.046 — — 

BYB = 1998:1 — — 0.048 0.049 — — 

BYB = 1998:2 — — 0.051 0.056 — — 

BYB = 1998:3 — — 0.053* 0.059 — — 

BYB = 1998:4 0.002 0.002 0.056 0.054 — — 

BYB = 1999:1 0.012** 0.008 0.055 0.055 — — 

BYB = 1999:2 0.029 0.026 0.054 0.053 — — 

BYB = 1999:3 0.046** 0.034 0.044* 0.050 — — 

BYB = 1999:4 0.047** 0.036 0.037 0.040 — — 

BYB = 2000:1 0.059 0.054 0.038 0.037 — — 

BYB = 2000:2 0.079 0.078 0.025 0.028 — — 

BYB = 2000:3 0.092 0.090 0.023 0.026 — — 

BYB = 2000:4 0.073 0.078 0.024 0.024 — — 

BYB = 2001:1 0.078 0.084 0.023 0.025 0.006 0.009 

BYB = 2001:2 0.083 0.087 0.028 0.032 0.022 0.025 

BYB = 2001:3 0.087 0.089 0.036 0.033 0.049 0.047 

BYB = 2001:4 0.070** 0.083 0.033** 0.039 0.093 0.111 

BYB = 2002:1 0.066 0.067 0.027 0.031 0.088** 0.118 

BYB = 2002:2 0.057 0.057 0.030 0.031 0.123 0.107 

BYB = 2002:3 0.040 0.043 0.031 0.029 0.120 0.102 
Table A.4 (Continued)

113

Description

Florida Georgia Michigan 

Quit prior 

employment

(n = 3,675)

All other

applicants

(n = 14,364)

Quit prior

employment

(n = 4,628)

All other

applicants

(n = 21,982)

Quit prior

employment

(n = 831)

All other

applicants

(n = 3,945)

e

BYB = 2002:4 0.026 0.027 0.020 0.022 0.103 0.102 

BYB = 2003:1 0.021 0.024 0.021** 0.015 0.090 0.080 

BYB = 2003:2 0.017 0.014 0.018** 0.012 0.063 0.068 

BYB = 2003:3 0.008 0.010 0.013** 0.009 0.057 0.056 

BYB = 2003:4 0.006 0.005 0.008* 0.006 0.051 0.057 

BYB = 2004:1 0.002 0.002 0.005 0.004 0.061** 0.041 

BYB = 2004:2 0.001 0.001 0.003 0.003 0.034 0.031 

BYB = 2004:3 0.001 0.001 0.003** 0.002 0.020 0.020 

BYB = 2004:4 0.000 0.000 0.001 0.001 0.012 0.016 

BYB = 2005:1 — — — — 0.004 0.005 

BYB = 2005:2 0.004 0.002

BYB = 2005:3 0.001 0.001

BYB = 2005:4 0.000 0.001

NOTE: Blank = data not applicable; — = data not available. BYB = benefit year beginning. BYE = benefit year ending. GED = general equivalenc

persons who quit prior employment is significantly different from all other applicants at the 90 percent confidence level in a two-tailed test; ** mean f

employment is significantly different from all other applicants at the 95 percent confidence level in a two-tailed test. a Data for Ohio limited to UI claims filed on or before December 31, 2002. New UI data received in December 2007 for claims beginning in 2003 d

information needed to determine whether someone quit prior employment.
114

Table A.5 Newly Unemployed TANF-Leaver UI Applicants Discharged from Prior Employment, Compared by Characteristics 

Leaver UI Applicants

Description

Florida Georgia Michigan 

Discharged

from prior

employment

(n = 6,228)

All other

applicants

(n = 12,081)

Discharged

from prior

employment

(n = 9,193)

All other

applicants

(n = 17,417)

Discharged

from prior

employment

(n = 2,071

All other

applicants

(n = 2,705)

D

f

em

(

Age at BYB 32.1** 33.9 31.0** 31.7 30.4** 32.2 

 18–24 0.244** 0.206 0.239** 0.225 0.298** 0.221 

 25–44 0.714 0.722 0.736 0.738 0.643** 0.694 

 45+ 0.042** 0.072 0.025** 0.037 0.059** 0.085 

Gender, male 0.161** 0.200 0.079 0.083 0.177** 0.279 

Gender, female 0.839 0.800 0.921 0.917 0.823** 0.721 

Race, white 0.281** 0.242 0.200* 0.191 0.433** 0.506 

Race, black 0.482** 0.407 0.779 0.782 0.518** 0.426 

Race, Hispanic 0.215** 0.324 0.008 0.009 0.045** 0.058 

Race, other 0.023* 0.027 0.013** 0.018 0.007** 0.021 

Education, less than high school 0.347** 0.370 0.295** 0.275 0.264 0.264 

Education, high school grad/GED 0.510** 0.483 0.517** 0.537 0.462 0.466 

Education, some college 0.121** 0.109 0.169 0.167 0.244 0.232 

Education, bachelor’s degree or higher 0.023** 0.038 0.019 0.021 0.031 0.038 

Base period earnings ($) 11,349 11,412 9,152 9,173 11,397 11,057 

High quarter earnings in base ($) 3,940* 4,008 3,737 3,803 4,333 4,447 

Base period earnings < $10,000 0.513 0.511 0.661 0.666 0.513** 0.545 

Multiple employers, any base qtr. 0.511 0.504 0.494 0.493 0.496 0.513 

Qtrs., TANF exit to unemployment 5.5 5.4 4.6 4.6 5.2** 4.8 

Consec. qtrs. employed before exit 3.1 3.0 2.8** 2.9 7.2 7.2 

 0 or 1 0.500** 0.517 0.483 0.483 0.072* 0.086 

 2–4 0.275 0.274 0.328** 0.315 0.190 0.184 

 5–8 0.108** 0.089 0.107 0.105 0.316** 0.284 

 9–12 0.117 0.120 0.082** 0.097 0.423 0.445 

Qtrs. employed before BYB 8.5** 8.3 8.2 8.2 9.0** 8.8 

 4 qtrs. or less 0.103** 0.125 0.122 0.127 0.073** 0.099 

 5–8 0.342 0.339 0.362** 0.347 0.288 0.291 

 9–12 0.555** 0.535 0.516 0.525 0.639** 0.610 
Table A.5 (Continued)

115

Description

Florida Georgia Michigan 

Discharged

from prior

employment

(n = 6,228)

All other

applicants

(n = 12,081)

Discharged

from prior

employment

(n = 9,193)

All other

applicants

(n = 17,417)

Discharged

from prior

employment

(n = 2,071

All other

applicants

(n = 2,705)

D

f

em

(

Total adults on case 1.19 1.19 1.04** 1.10 

Total children (< 18) on case 1.98** 1.94 1.84** 1.96 

Total children (< 6) on case 0.91** 0.87 0.90** 0.83 

Agriculture, forestry, fishing 0.005** 0.026 0.004** 0.008 0.002** 0.010 

Mining 0.000 0.000 0.001 0.000 0.000 0.001 

Utilities 0.001 0.001 0.001 0.000 0.001 0.000 

Construction 0.025** 0.040 0.016** 0.024 0.021** 0.053 

Manufacturing 0.050** 0.066 0.153** 0.213 0.086** 0.111 

Wholesale trade 0.024** 0.033 0.034 0.033 0.020 0.019 

Retail trade 0.150** 0.117 0.163** 0.135 0.188** 0.145 

Transportation, warehousing 0.033 0.033 0.022 0.019 0.017* 0.024 

Information 0.018 0.017 0.021 0.018 0.018** 0.010 

Finance and insurance 0.023** 0.017 0.021** 0.017 0.034** 0.019 

Real estate, rental, leasing 0.019 0.016 0.015** 0.010 0.022** 0.012 

Professional, scientific, technical 0.033 0.035 0.012 0.012 0.020** 0.030 

Company management 0.011 0.009 0.000 0.000 0.002 0.002 

Admin., support, waste mgmt. 0.169** 0.195 0.146** 0.166 0.155** 0.188 

Educational services 0.013** 0.024 0.020** 0.026 0.014** 0.029 

Health care/social assistance 0.117** 0.090 0.144** 0.118 0.170** 0.121 

Art, entertainment, recreation 0.009 0.009 0.004 0.004 0.018 0.015 

Accommodation, food services 0.136** 0.107 0.171** 0.138 0.143** 0.119 

Other services (except publ. admin.) 0.029 0.027 0.026 0.026 0.029 0.027 

Public administration 0.015 0.017 0.026 0.028 0.006** 0.014 

Unclassifiable 0.012 0.014 0.003 0.002 0.004* 0.007 

Industry missing 0.107 0.106 0.000 0.000 0.031** 0.044 

Management, business, financial 0.050 0.045 0.038** 0.026 — — 

Professional, related occupations 0.078 0.075 0.056 0.059 — — 

Services 0.253** 0.207 0.293** 0.246 — — 

Sales and related occupations 0.147** 0.107 0.074** 0.061 — — 

Office, administrative support 0.201** 0.186 0.238** 0.226 — — 

Farming, fishing and forestry 0.006** 0.011 0.006 0.008 — — 

Construction and extraction 0.021** 0.034 0.014** 0.018 — — 

Install, maintain, repair 0.026 0.027 0.007** 0.010 — — 
Table A.5 (Continued)

116

Description

Florida Georgia Michigan 

Discharged

from prior

employment

(n = 6,228)

All other

applicants

(n = 12,081)

Discharged

from prior

employment

(n = 9,193)

All other

applicants

(n = 17,417)

Discharged

from prior

employment

(n = 2,071

All other

applicants

(n = 2,705)

D

f

em

(

Production 0.081** 0.112 0.141** 0.189 — — 

Transportation, material moving 0.056 0.057 0.095** 0.120 — — 

Occupation missing 0.069** 0.125 0.040 0.037 — — 

Unemployment rate, month of BYB 4.9** 5.1 4.9** 5.1 7.0* 7.1 

Unemployment rate, TANF exit 4.2** 4.4 5.0** 5.2 5.9** 6.0 

Chg. unempl. rate, year-ago BYB 0.3 0.3 −0.1 −0.1 1.1 1.1 

Chg. unempl. rate over benefit year 0.4 0.4 −0.2** −0.2 0.6 0.5 

Chg. unempl. rate, end TANF to BYB 0.7 0.7 −0.1 −0.1 1.1 1.0 

Chg. unempl. rate, end TANF to BYE 1.0** 1.1 −0.2** −0.3 1.6 1.6 

Pct. chg., labor force, year-ago BYB 1.5** 1.3 1.3 1.3 −1.0 −1.0 

Employed (000s), month of BYB 522.3** 588.0 126.2** 120.3 382.2** 353.5 

Employed (000s), at TANF exit 522.2** 589.1 123.8** 118.1 394.6** 364.9 

Pct. chg. employment, year-ago BYB 1.2** 1.0 1.4 1.4 −2.2 −2.1 

Pct. chg. employment over benefit year 0.8** 0.5 1.5 1.5 −0.9 −0.9 

Pct. chg. employment, TANF exit to BYB 1.1** 0.8 1.5** 1.4 −2.7* −2.5 

Pct. chg. employment, end TANF to BYE 1.9** 1.3 3.0* 2.9 −3.6 −3.4 

BYB in 1st qtr. 0.255** 0.231 0.243 0.238 0.261 0.249 

BYB in 2nd qtr. 0.259 0.266 0.252 0.252 0.243 0.230 

BYB in 3rd qtr. 0.261 0.271 0.259 0.262 0.242* 0.221 

BYB in 4th qtr. 0.225 0.231 0.246 0.248 0.255** 0.301 

TANF exit = 1996:2 — — 0.070** 0.077 — — 

TANF exit = 1996:3 — — 0.067** 0.076 — — 

TANF exit = 1996:4 — — 0.066** 0.074 — — 

TANF exit = 1997:1 — — 0.059** 0.068 — — 

TANF exit = 1997:2 — — 0.054 0.053 — — 

TANF exit = 1997:3 — — 0.066 0.069 — — 

TANF exit = 1997:4 — — 0.046 0.046 — — 

TANF exit = 1998:1 — — 0.040 0.042 — — 

TANF exit = 1998:2 — — 0.036 0.040 — — 

TANF exit = 1998:3 — — 0.036 0.037 — — 

TANF exit = 1998:4 0.120 0.114 0.042 0.043 — — 

TANF exit = 1999:1 0.128** 0.113 0.027 0.027 — — 
Table A.5 (Continued)

117

Description

Florida Georgia Michigan 

Discharged

from prior

employment

(n = 6,228)

All other

applicants

(n = 12,081)

Discharged

from prior

employment

(n = 9,193)

All other

applicants

(n = 17,417)

Discharged

from prior

employment

(n = 2,071

All other

applicants

(n = 2,705)

D

f

em

(

TANF exit = 1999:2 0.126* 0.117 0.041* 0.037 — — 

TANF exit = 1999:3 0.105 0.098 0.039** 0.033 — — 

TANF exit = 1999:4 0.084** 0.094 0.037** 0.032 — — 

TANF exit = 2000:1 0.136** 0.154 0.038** 0.031 — — 

TANF exit = 2000:2 0.083* 0.091 0.039** 0.034 — — 

TANF exit = 2000:3 0.079 0.079 0.036 0.032 — — 

TANF exit = 2000:4 0.071 0.068 0.031 0.028 — — 

TANF exit = 2001:1 0.069 0.072 0.035** 0.031 0.204 0.200 

TANF exit = 2001:2 — — 0.037** 0.031 0.211 0.203 

TANF exit = 2001:3 — — 0.029 0.031 0.224 0.228 

TANF exit = 2001:4 — — 0.029 0.031 0.177** 0.206

TANF exit = 2002:1 — — 0.184* 0.163

BYB = 1996:2 — — 0.002** 0.004 — — 

BYB = 1996:3 — — 0.011 0.011 — — 

BYB = 1996:4 — — 0.016* 0.019 — — 

BYB = 1997:1 — — 0.022* 0.025 — — 

BYB = 1997:2 — — 0.033 0.035 — — 

BYB = 1997:3 — — 0.038** 0.046 — — 

BYB = 1997:4 — — 0.044 0.047 — — 

BYB = 1998:1 — — 0.050 0.048 — — 

BYB = 1998:2 — — 0.057 0.054 — — 

BYB = 1998:3 — — 0.055 0.059 — — 

BYB = 1998:4 0.002 0.002 0.051 0.055 — — 

BYB = 1999:1 0.010 0.008 0.052 0.056 — — 

BYB = 1999:2 0.031** 0.024 0.047** 0.056 — — 

BYB = 1999:3 0.039 0.035 0.047 0.050 — — 

BYB = 1999:4 0.043** 0.035 0.042 0.038 — — 

BYB = 2000:1 0.063** 0.051 0.039 0.036 — — 

BYB = 2000:2 0.078 0.078 0.030* 0.026 — — 

BYB = 2000:3 0.094 0.088 0.026 0.025 — — 

BYB = 2000:4 0.073 0.079 0.023 0.025 — — 

BYB = 2001:1 0.084 0.083 0.026 0.024 0.007 0.010 

BYB = 2001:2 0.077** 0.091 0.035** 0.030 0.028 0.022 

BYB = 2001:3 0.069** 0.099 0.038** 0.032 0.048 0.047 
Table A.5 (Continued)

118

Description

Florida Georgia Michigan 

Discharged

from prior

employment

(n = 6,228)

All other

applicants

(n = 12,081)

Discharged

from prior

employment

(n = 9,193)

All other

applicants

(n = 17,417)

Discharged

from prior

employment

(n = 2,071

All other

applicants

(n = 2,705)

D

f

em

(

BYB = 2001:4 0.073** 0.084 0.041** 0.036 0.092** 0.119 

BYB = 2002:1 0.067 0.067 0.037** 0.027 0.114 0.112 

BYB = 2002:2 0.056 0.058 0.034** 0.029 0.110 0.110 

BYB = 2002:3 0.048** 0.039 0.035** 0.026 0.114* 0.098 

BYB = 2002:4 0.028 0.025 0.024** 0.020 0.091** 0.111 

BYB = 2003:1 0.028** 0.021 0.013** 0.017 0.089 0.077 

BYB = 2003:2 0.015 0.014 0.011* 0.014 0.074* 0.061 

BYB = 2003:3 0.010 0.009 0.008** 0.011 0.059 0.053 

BYB = 2003:4 0.005 0.005 0.005* 0.007 0.057 0.055 

BYB = 2004:1 0.002 0.002 0.003 0.004 0.044 0.045 

BYB = 2004:2 0.002 0.001 0.002* 0.004 0.030 0.033 

BYB = 2004:3 0.001 0.001 0.001 0.002 0.020 0.020 

BYB = 2004:4 0.000 0.000 0.000* 0.001 0.014 0.016 

BYB = 2005:1 — — — — 0.004 0.005 

BYB = 2005:2 — — — — 0.002 0.003 

BYB = 2005:3 — — — — 0.000 0.001 

BYB = 2005:4 — — — — 0.001 0.000 

NOTE: — = data not available. BYB = benefit year beginning. BYE = benefit year ending. GED = general equivalency diploma. * Mean for perso

from prior employment is significantly different from the mean for all other applicants at the 90 percent confidence level in a two-tailed test; **mean 

discharged from prior employment is significantly different from the mean for all other applicants at the 95 percent confidence level in a two-tailed te

a Data for Ohio are based on UI claims filed on or before December 31, 2002. New UI data received in December 2007 for claims filed beginning i

characteristic information needed to identify claimants discharged from prior employment.
119

Table A.6 Newly Unemployed TANF-Leaver UI Applicants Who Are UI Beneficiaries, Compared by Characteristics with All O

Applicants

Description

Florida Georgia Michigan 

UI

beneficiary

(n = 11,095)

All other

applicants

(n = 7,214)

UI

beneficiary

(n = 13,389)

All other

applicants

(n = 13,868)

UI

beneficiary

(n = 3,097)

All other

applicants

(n = 1,679)

be

(n 

Age at BYB 34.6** 31.2 32.6** 30.4 32.0** 30.4 

 18–24 0.173** 0.289 0.190** 0.270 0.225** 0.309 

 25–44 0.749** 0.674 0.764** 0.707 0.696** 0.627 

 45+ 0.078** 0.037 0.046** 0.022 0.079* 0.064 

Gender, male 0.209** 0.153 0.092** 0.073 0.265** 0.176 

Gender, female 0.791** 0.847 0.908** 0.927 0.735** 0.824 

Race, white 0.246** 0.269 0.202** 0.191 0.502** 0.424 

Race, black 0.405** 0.475 0.772** 0.784 0.437** 0.519 

Race, Hispanic 0.322** 0.232 0.008* 0.011 0.055 0.048 

Race, other 0.027 0.024 0.018* 0.015 0.015 0.016 

Education, less than high school 0.351** 0.379 0.254** 0.310 0.240** 0.307 

Education, high school grad/GED 0.487* 0.500 0.535* 0.524 0.466 0.461 

Education, some college 0.120** 0.102 0.184** 0.152 0.256** 0.203 

Education, bachelor’s degree or higher 0.042** 0.019 0.027** 0.014 0.038* 0.029 

Base period earnings ($) 12,606** 9,521 10,787** 7,659 11,829** 10,071 

High quarter earnings in base ($) 4,383** 3,373 4,284** 3,298 4,642** 3,953 

Base period earnings < $10,000 0.443** 0.616 0.570** 0.752 0.491** 0.603 

Multiple employers, any base qtr. 0.488** 0.535 0.498** 0.484 0.507 0.503 

Qtrs., TANF exit to new unemployment 5.7** 5.0 5.0** 4.1 5.1** 4.8

Consec. qtrs. employed before exit 3.1** 2.9 3.2** 2.6 7.5** 6.8 

 0 or 1 0.507 0.518 0.443** 0.521 0.069** 0.100 

 2–4 0.267** 0.286 0.323 0.316 0.179* 0.201 

 5–8 0.097 0.092 0.118** 0.093 0.282** 0.328 

 9–12 0.129** 0.104 0.116** 0.070 0.470** 0.371 

Qtrs. employed before BYB 8.6** 8.0 8.8** 7.7 9.1** 8.6 

 4 qtrs. or less 0.101** 0.143 0.084** 0.171 0.079** 0.105 

 5–8 0.322** 0.368 0.315** 0.384 0.269** 0.327 

 9–12 0.577** 0.489 0.600** 0.445 0.652** 0.568 
Table A.6 (Continued)

120

Description

Florida Georgia Michigan 

UI

beneficiary

(n = 11,095)

All other

applicants

(n = 7,214)

UI

beneficiary

(n = 13,389)

All other

applicants

(n = 13,868)

UI

beneficiary

(n = 3,097)

All other

applicants

(n = 1,679)

be

(n 

Total adults on case — — 1.21** 1.19 1.08 1.08 

Total children (< 18) on case — — 1.92** 1.99 1.92 1.89 

Total children (< 6) on case — — 0.82** 0.95 0.86 0.88 

Agriculture, forestry, fishing a 0.025** 0.011 0.007 0.006 0.009** 0.002 

Mining 0.000 0.000 0.000 0.000 0.001 0.001 

Utilities 0.001 0.001 0.001 0.000 0.000 0.001 

Construction 0.040** 0.027 0.027** 0.017 0.055** 0.010 

Manufacturing 0.068** 0.049 0.246** 0.143 0.116** 0.072 

Wholesale trade 0.032** 0.026 0.038** 0.029 0.018 0.021 

Retail trade 0.103** 0.167 0.127** 0.162 0.145** 0.197 

Transportation, warehousing 0.027** 0.041 0.021 0.019 0.021 0.020 

Information 0.019** 0.015 0.021** 0.017 0.016** 0.009 

Finance and insurance 0.020 0.018 0.021** 0.016 0.027 0.024 

Real estate, rental, leasing 0.018 0.016 0.013 0.011 0.017 0.015 

Professional, scientific, technical 0.036 0.031 0.015** 0.010 0.031** 0.016 

Company management 0.008** 0.012 0.000 0.000 0.001 0.002 

Admin., support, waste mgmt. 0.180** 0.195 0.162 0.155 0.180* 0.161 

Educational services 0.017** 0.025 0.021** 0.027 0.026** 0.015 

Health care/social assistance 0.087** 0.118 0.107** 0.145 0.118** 0.186 

Art, entertainment, recreation 0.007** 0.011 0.004 0.004 0.016 0.017 

Accommodation, food services 0.088** 0.162 0.110** 0.189 0.112** 0.160 

Other services (except publ. admin.) 0.027 0.030 0.030** 0.021 0.029 0.026 

Public administration 0.016 0.016 0.028 0.026 0.013** 0.005 

Unclassifiable 0.012 0.014 0.003 0.002 0.006 0.004 

Industry missing 0.167 0.013 0.000 0.000 0.040 0.036 

Management, business, financial 0.053** 0.038 0.033** 0.026 — — 

Professional, related occupations 0.082** 0.067 0.065** 0.049 — — 

Services 0.186** 0.279 0.203** 0.310 — — 

Sales and related occupations 0.103** 0.147 0.063 0.066 — — 

Office, administrative support 0.196* 0.184 0.229 0.223 — — 

Farming, fishing, and forestry 0.011** 0.007 0.008 0.007 — — 

Construction and extraction 0.033** 0.025 0.020** 0.012 — — 

Install, maintain, repair 0.029** 0.023 0.012** 0.007 — — 

Production 0.106** 0.095 0.202** 0.136 — — 

Transport, material moving 0.056 0.057 0.118** 0.102 — — 
Table A.6 (Continued)

121

Description

Florida Georgia Michigan 

UI

beneficiary

(n = 11,095)

All other

applicants

(n = 7,214)

UI

beneficiary

(n = 13,389)

All other

applicants

(n = 13,868)

UI

beneficiary

(n = 3,097)

All other

applicants

(n = 1,679)

be

(n 

Occupation missing 0.129** 0.071 0.048** 0.062 — — 

Unemployment rate, month of BYB 5.2** 4.8 5.1** 5.0 7.1 7.0 

Unemployment rate, TANF exit 4.4** 4.2 5.1** 5.1 6.0 6.0 

Chg. unempl. rate, year-ago BYB 0.3** 0.3 0.0** −0.1 1.1 1.1 

Chg. unempl. rate over benefit year 0.3** 0.4 −0.2** −0.2 0.5** 0.7 

Chg. unempl. rate, end TANF to BYB 0.7** 0.6 −0.1** −0.1 1.1 1.0 

Chg. unempl. rate, end TANF to BYE 1.1 1.1 −0.3 −0.3 1.6 1.7 

Pct. chg., labor force, year-ago BYB 1.1** 1.6 1.3 1.3 −1.0** −1.1 

Employed (000s), month of BYB 605.9** 499.5 123.1 123.4 344.9** 407.8 

Employed (000s), at TANF exit 607.4** 499.1 120.7 121.3 356.4** 420.3 

Pct. chg. employment, year-ago BYB 0.8** 1.4 1.3** 1.5 −2.1** −2.3 

Pct. chg. employment over benefit year 0.5** 0.7 1.5 1.4 −0.8** −1.1 

Pct. chg. employment, TANF exit to BYB 0.8** 1.2 1.6** 1.3 −2.6 −2.6 

Pct. chg. employment, end TANF to BYE 1.3** 1.9 3.1** 2.8 −3.4* −3.6 

BYB in 1st qtr. 0.236 0.245 0.247** 0.233 0.249 0.263 

BYB in 2nd qtr. 0.265 0.263 0.238** 0.263 0.237 0.233 

BYB in 3rd qtr. 0.267 0.270 0.262 0.260 0.213** 0.260 

BYB in 4th qtr. 0.233* 0.222 0.253* 0.244 0.301** 0.244 

TANF exit = 1996:2 — — 0.079** 0.071 — — 

TANF exit = 1996:3 — — 0.076** 0.070 — — 

TANF exit = 1996:4 — — 0.071 0.072 — — 

TANF exit = 1997:1 — — 0.063 0.066 — — 

TANF exit = 1997:2 — — 0.051 0.055 — — 

TANF exit = 1997:3 — — 0.065 0.070 — — 

TANF exit = 1997:4 — — 0.045 0.046 — — 

TANF exit = 1998:1 — — 0.041 0.042 — — 

TANF exit = 1998:2 — — 0.040 0.036 — — 

TANF exit = 1998:3 — — 0.036 0.036 — — 

TANF exit = 1998:4 0.111** 0.124 0.040* 0.044 — — 

TANF exit = 1999:1 0.113** 0.126 0.026 0.028 — — 

TANF exit = 1999:2 0.116** 0.126 0.037 0.039 — — 

TANF exit = 1999:3 0.103 0.096 0.036 0.034 — — 

TANF exit = 1999:4 0.089 0.093 0.034 0.032 — — 
Table A.6 (Continued)

122

Description

Florida Georgia Michigan 

UI

beneficiary

(n = 11,095)

All other

applicants

(n = 7,214)

UI

beneficiary

(n = 13,389)

All other

applicants

(n = 13,868)

UI

beneficiary

(n = 3,097)

All other

applicants

(n = 1,679)

be

(n 

TANF exit = 2000:1 0.156** 0.136 0.032 0.035 — — 

TANF exit = 2000:2 0.092** 0.082 0.033* 0.038 — — 

TANF exit = 2000:3 0.082* 0.075 0.033 0.033 — — 

TANF exit = 2000:4 0.069 0.069 0.029 0.030 — — 

TANF exit = 2001:1 0.069 0.074 0.034 0.031 0.193** 0.219 

TANF exit = 2001:2 — — 0.034 0.032 0.210 0.201 

TANF exit = 2001:3 — — 0.030 0.031 0.225 0.229 

TANF exit = 2001:4 — — 0.033** 0.029 0.197 0.186 

TANF exit = 2002:1 — — — — 0.176 0.165 

BYB = 1996:2 — — 0.002** 0.005 — — 

BYB = 1996:3 — — 0.007** 0.014 — — 

BYB = 1996:4 — — 0.013** 0.023 — — 

BYB = 1997:1 — — 0.020** 0.028 — — 

BYB = 1997:2 — — 0.026** 0.042 — — 

BYB = 1997:3 — — 0.040** 0.047 — — 

BYB = 1997:4 — — 0.046 0.046 — — 

BYB = 1998:1 — — 0.049 0.048 — — 

BYB = 1998:2 — — 0.051** 0.059 — — 

BYB = 1998:3 — — 0.058 0.057 — — 

BYB = 1998:4 0.002 0.002 0.059** 0.050 — — 

BYB = 1999:1 0.008 0.010 0.062** 0.049 — — 

BYB = 1999:2 0.026 0.028 0.054 0.052 — — 

BYB = 1999:3 0.034** 0.040 0.051 0.048 — — 

BYB = 1999:4 0.035** 0.042 0.042** 0.037 — — 

BYB = 2000:1 0.049** 0.064 0.037 0.037 — — 

BYB = 2000:2 0.073** 0.087 0.027 0.028 — — 

BYB = 2000:3 0.084** 0.100 0.025 0.025 — — 

BYB = 2000:4 0.074 0.080 0.023 0.025 — — 

BYB = 2001:1 0.084 0.082 0.023 0.026 0.010 0.006 

BYB = 2001:2 0.089* 0.082 0.031 0.032 0.022 0.029 

BYB = 2001:3 0.093** 0.082 0.034 0.033 0.039** 0.064 

BYB = 2001:4 0.089** 0.067 0.040 0.036 0.112 0.098 

BYB = 2002:1 0.068 0.066 0.034** 0.027 0.112 0.114 

BYB = 2002:2 0.061** 0.051 0.030 0.032 0.104* 0.120 

BYB = 2002:3 0.045** 0.039 0.032** 0.026 0.094** 0.126 
Table A.6 (Continued)

123

Description

Florida Georgia Michigan 

UI

beneficiary

(n = 11,095)

All other

applicants

(n = 7,214)

UI

beneficiary

(n = 13,389)

All other

applicants

(n = 13,868)

UI

beneficiary

(n = 3,097)

All other

applicants

(n = 1,679)

be

(n 

BYB = 2002:4 0.028 0.025 0.023* 0.020 0.108* 0.092 

BYB = 2003:1 0.025 0.021 0.017** 0.014 0.080 0.086 

BYB = 2003:2 0.015 0.014 0.015** 0.012 0.073** 0.055 

BYB = 2003:3 0.010 0.009 0.013** 0.008 0.058 0.052 

BYB = 2003:4 0.005 0.005 0.007 0.006 0.063** 0.043 

BYB = 2004:1 0.002 0.002 0.005* 0.003 0.042 0.049 

BYB = 2004:2 0.001** 0.002 0.004** 0.002 0.033 0.029 

BYB = 2004:3 0.001* 0.001 0.003* 0.002 0.023 0.016 

BYB = 2004:4 0.000* 0.000 0.001 0.001 0.018* 0.011 

BYB = 2005:1 — — — — 0.005 0.004 

BYB = 2005:2 — — — — 0.002 0.004 

BYB = 2005:3 — — — — 0.001 0.001 

BYB = 2005:4 — — — — 0.001 0.001 

NOTE: — = data not available. BYB = benefit year beginning. BYE = benefit year ending. GED = general equivalency diploma. *Mean for UI be

different from the mean for all other applicants at the 90 percent confidence level in a two-tailed test; **mean for UI beneficiaries significantly differe

other applicants at the 95 percent confidence level in a two-tailed test. a New UI data received in December 2007 for claims beginning in 2003 did not include characteristic information. Therefore, data for this variable 

limited to claims made on or before December 31, 2002.
124

Table A.7 Newly Unemployed TANF-Leaver UI Beneficiaries, Compared by Characteristics with Newly Unemployed TANF-L

Apply for UI Benefits

Description

Florida Georgia Michigan 

UI

beneficiaries

(n = 11,095)

Did not apply

for UI

(n = 27,936)

UI

beneficiaries

(n = 13,389)

Did not apply

for UI

(n = 96,444)

UI

beneficiaries

(n = 3,097)

Did not apply

for UI

(n = 16,267)

b

(

Age at TANF Exit 31.0 29.6 30.3 27.6 

 18–24 0.266 0.369 0.294 0.459 

 25–44 0.658 0.572 0.651 0.498 

 45+ 0.076 0.059 0.055 0.042 

Gender, male — — 0.263 0.187 

Gender, female — — 0.737 0.813 

Race, white 0.212 0.300 0.502 0.529 

Race, black 0.775 0.683 0.437 0.417 

Race, Hispanic 0.008 0.011 0.055 0.047 

Race, other 0.005# 0.005 0.015# 0.015 

Base period earnings a 13,153 8,239 11,493 7,640 13,252 7,260 

High qtr. earnings in base period a 4,604 3,266 4,295 3,096 4,883 2,988 

Base earnings < $10,000 a 0.415 0.688 0.519 0.753 0.396 0.754 

Multiple employers, any qtr. after exit 0.510 0.480 0.487 0.422 0.369 0.285 

Qtrs., exit to new unemployment 5.7 4.1 5.0 3.8 5.1 3.7 

Consecutive qtrs. employed before exit 3.1 2.7 3.2 2.5 3.8 2.6 

 0 or 1 0.507 0.594 0.443 0.574 0.453 0.586 

 2–4 0.267 0.220 0.323 0.262 0.248 0.212 

 5–8 0.097 0.081 0.118 0.083 0.112 0.098 

 9–12 0.129 0.105 0.116 0.081 0.186 0.104 

Qtrs. employed before unempl. (of 12) 9.0 7.7 8.9 7.4 9.4 7.8 

 1–4 0.085 0.227 0.083 0.242 0.060 0.197 

 5–8 0.299# 0.304 0.309 0.345 0.245 0.329 

 9–12 0.616 0.470 0.608 0.414 0.695 0.475 

Qtrs. of employment before exit (of 12) 5.9 5.6 6.4 5.4 7.5 6.1 

Avg. qtrly. earnings before exit 2,392 1,994 2,128 1,721 2,689 1,818 

Avg. qtrly. earnings after exit 3,353 2,244 3,052 2,154 3,672 2,322 

Adults on case at exit 1.21 1.25 1.08 1.10 
Table A.7 (Continued)

125

Description

Florida Georgia Michigan 

UI

beneficiaries

(n = 11,095)

Did not apply

for UI

(n = 27,936)

UI

beneficiaries

(n = 13,389)

Did not apply

for UI

(n = 96,444)

UI

beneficiaries

(n = 3,097)

Did not apply

for UI

(n = 16,267)

b

(

Children < age 18 on case at exit 1.92 1.90 1.62 1.57 

Children < age 6 on case at exit 0.82 0.90 0.72 0.79 

Agriculture, forestry, fishing 0.008 0.006 0.008 0.004

Mining 0.000# 0.000 0.000# 0.000

Utilities 0.001# 0.001 0.000# 0.000

Construction 0.028 0.019 0.059 0.019

Manufacturing 0.248 0.107 0.120 0.065

Wholesale trade 0.037 0.027 0.019 0.014

Retail trade 0.126 0.166 0.148 0.195

Transportation, warehousing 0.020# 0.019 0.021 0.012

Information 0.021 0.015 0.017 0.009

Finance and insurance 0.020 0.014 0.027 0.013

Real estate, rental, leasing 0.013 0.011 0.017# 0.013

Professional, scientific, technical 0.015 0.010 0.030 0.019

Company/enterprise management 0.000# 0.000 0.002# 0.002

Admin., support and waste mgmt. 0.162 0.152 0.172 0.157

Educational services 0.021 0.038 0.026 0.034

Health care/social assistance 0.105 0.135 0.116 0.128

Art, entertainment, recreation 0.004# 0.005 0.018# 0.016

Accommodation and food services 0.111 0.215 0.108 0.214

Other services (except publ. admin.) 0.031# 0.029 0.029# 0.027

Public administration 0.027# 0.026 0.015 0.010

Unclassifiable 0.002# 0.003 0.007# 0.006

Missing 0.000 0.000 0.040# 0.043

Unempl. rate at TANF exit 5.1 4.8 6.0 5.9 

Unempl. rate at new unemployment 5.1 4.7 7.3 6.8 

Chg., unempl. rate, year prior to exit −0.2 −0.2 1.5 1.5 

Chg., unempl. rate, exit to unempl. 0.1 −0.1 1.3 0.8 

Employment level (000s) at exit 121.0 125.7 359.3 376.5 

Employment level (000s) at new unempl. 124.1 129.0 346.4 366.4 

Pct. chg. employment from year-ago exit 1.9 2.3 −1.8# −1.8 

Pct. chg. employment, exit to unempl. 2.0 2.2 −3.1 −2.2 

Education, less than high school 
Table A.7 (Continued)

126

Description

Florida Georgia Michigan 

UI

beneficiaries

(n = 11,095)

Did not apply

for UI

(n = 27,936)

UI

beneficiaries

(n = 13,389)

Did not apply

for UI

(n = 96,444)

UI

beneficiaries

(n = 3,097)

Did not apply

for UI

(n = 16,267)

b

(

Education, high school grad or GED 

Education, some college 

Education, bachelor’s degree or higher 

Year and qtr. of TANF exit, 1996:2 0.079 0.066

Year and qtr. of TANF exit, 1996:3 0.076 0.070

Year and qtr. of TANF exit, 1996:4 0.071 0.066

Year and qtr. of TANF exit, 1997:1 0.063# 0.063

Year and qtr. of TANF exit, 1997:2 0.051 0.057

Year and qtr. of TANF exit, 1997:3 0.065 0.077

Year and qtr. of TANF exit, 1997:4 0.045 0.052

Year and qtr. of TANF exit, 1998:1 0.041 0.048

Year and qtr. of TANF exit, 1998:2 0.040 0.046

Year and qtr. of TANF exit, 1998:3 0.036 0.041

Year and qtr. of TANF exit, 1998:4 0.111 0.132 0.040 0.047

Year and qtr. of TANF exit, 1999:1 0.113 0.120 0.026 0.031

Year and qtr. of TANF exit, 1999:2 0.116 0.138 0.037 0.041

Year and qtr. of TANF exit, 1999:3 0.103 0.111 0.036# 0.033

Year and qtr. of TANF exit, 1999:4 0.089# 0.091 0.034 0.031

Year and qtr. of TANF exit, 2000:1 0.156 0.141 0.032# 0.031

Year and qtr. of TANF exit, 2000:2 0.092 0.078 0.033# 0.033 

Year and qtr. of TANF exit, 2000:3 0.082 0.070 0.033 0.029 

Year and qtr. of TANF exit, 2000:4 0.069 0.057 0.029# 0.028 

Year and qtr. of TANF exit, 2001:1 0.069 0.061 0.034 0.028 0.193 0.209 

Year and qtr. of TANF exit, 2001:2 0.034 0.029 0.210# 0.206 

Year and qtr. of TANF exit, 2001:3 0.030 0.027 0.225# 0.220 

Year and qtr. of TANF exit, 2001:4 0.033 0.025 0.197# 0.189

Year and qtr. of TANF exit, 2002:1 0.176# 0.176

Year and qtr. of TANF exit, 2002:2

Year and qtr. of TANF exit, 2002:3

Year and qtr. of TANF exit, 2002:4

NOTE: Blank = data not applicable; — = data not available. All differences in means significantly different from 0 at the 90 percent confidence lev

a The base period is defined for both applicants and nonapplicants as the first four of the five quarters preceding the quarter of new unemployment.
127

Table A.8 Rates of Return to Employment and TANF among Newly Unemployed TANF Leavers, Using Data 

from Floridaa

Group

Sample

size

Returned to

employment

Returned to

TANF

Newly unemployed TANF leavers 43,113 0.787 0.312

UI applicants 15,177 0.690 0.329

 Monetarily eligible 14,547 0.689 0.326

 Monetarily ineligible 630 0.729 0.387

 Nonmonetarily eligible 6,962 0.687 0.266

 Quit prior employment 3,073 0.672 0.404

 Discharged/fired 5,142 0.706 0.370

 UI beneficiaries 9,385 0.687 0.281

 Not UI beneficiaries 5,792 0.696 0.406

 UI-eligible and UI beneficiary 5,839 0.681 0.250

 UI-eligible and not UI beneficiary 810 0.707 0.338

UI nonapplicants 27,936 0.840 0.303

 Pseudomonetarily eligibleb 18,764 0.801 0.247

 Pseudomonetarily ineligibleb 7,713 0.918 0.425 a This excludes persons who applied for UI after the first quarter of 2004 (the last quarter in which TANF data was available). 

It also excludes persons who returned to TANF prior to UI application or had interim employment before applying for UI. b Based on wage records for the first four of the five quarters prior to the quarter of new unemployment and the applicable UI 

law.

Table A.9 Rates of Return to Employment and TANF among Newly Unemployed TANF Leavers, Using Data 

from Georgiaa

Group

Sample

size

Returned to

employment

Returned to

TANF

Newly unemployed TANF leavers 118,316 0.797 0.312

UI applicants 21,872 0.773 0.364

 Monetarily eligible 19,378 0.773 0.356

 Monetarily ineligible 2,494 0.779 0.429

 Nonmonetarily eligible 10,274 0.786 0.329

 Quit prior employment 3,649 0.788 0.423

 Discharged/fired 7,412 0.770 0.401

 UI beneficiaries 10,613 0.787 0.284

 Not UI beneficiaries 11,259 0.761 0.439

 UI-eligible and UI beneficiary 6,101 0.793 0.266

 UI-eligible and not UI beneficiary 3,006 0.770 0.424

UI Nonapplicants 96,444 0.802 0.300

 Pseudomonetarily eligibleb 74,057 0.809 0.277

 Pseud monetarily ineligibleb 22,387 0.780 0.376 a This excludes persons who applied for UI after the fourth quarter of 2004 (the last quarter in which wage data was available 

for Georgia). This also excludes persons who returned to TANF prior to UI application or had interim employment prior to 

filing for UI. b Based on wage records for the first four of the five quarters prior to the quarter of new unemployment and the applicable UI 

law.
128

Table A.10 Rates of Return to Employment and TANF among Newly Unemployed TANF Leavers, Using 

Data from Michigana

Group

Sample

size

Returned to

employment

Returned to

TANF

Newly unemployed TANF leavers 20,358 0.735 0.450

UI applicants 4,091 0.730 0.451

 Monetarily eligible 4,013 0.738 0.456

 Monetarily ineligible

 Nonmonetarily eligible 1,571 0.762 0.332

 Quit prior employment 731 0.691 0.505

 Discharged/fired 1,789 0.719 0.534

 UI beneficiaries 2,633 0.752 0.390

 Not UI beneficiaries 1,458 0.692 0.562

 UI-eligible and UI beneficiary 1,381 0.784 0.324

 UI-eligible and not UI beneficiary 115 0.774 0.513

UI Nonapplicants 16,267 0.736 0.449

 Pseudomonetarily eligibleb 10,637 0.719 0.407

 Pseudomonetarily ineligibleb 5,630 0.769 0.530 a This excludes persons who applied for UI after the first quarter of 2005 (the last quarter in which wage data was 

available for Michigan). It also excludes persons who returned to TANF prior to UI application or had interim 

employment prior to filing for UI. b Based on wage records in the first four of the five quarters prior to new unemployment and the applicable UI law.

Table A.11 Rates of Return to Employment and TANF among Newly Unemployed TANF Leavers, Using 

Data from Ohioa

Group

Sample

size

Returned to

employment

Returned to

TANF

Newly unemployed TANF leavers 59,932 0.737 0.478

UI applicants 8,848 0.713 0.447

 Monetarily eligible 6,112 0.705 0.439

 Monetarily ineligible

 Nonmonetarily eligible 2,075 0.806 0.454

 Quit prior employment 751 0.715 0.510

 Discharged/fired 1,561 0.782 0.564

 UI beneficiaries 2,780 0.745 0.344

 Not UI beneficiaries 6,068 0.699 0.495

 UI-eligible and UI beneficiary 556 0.856 0.324

 UI-eligible and not UI beneficiary 84 0.762 0.476

UI Nonapplicants 51,084 0.741 0.484

 Pseudomonetarily eligibleb 30,620 0.719 0.453

 Pseudomonetarily ineligibleb 20,464 0.774 0.530 a This excludes persons who applied for UI after the third quarter of 2004 (the last quarter in which wage data was available 

for Ohio). This also excludes persons who returned to TANF prior to UI application or had interim employment prior to filing

for UI. b Based on wage records in the first four of the five quarters prior to the quarter of new unemployment and the applicable UI 

law.
129

Table A.12 Linear Probability Models of Return to Employment and TANF, with Beneficiary Indicators,

among Newly Unemployed TANF-Leaver UI Applicants, Using Data from Florida

Independent variables

Return to employment Return to TANF

Parameter

estimate

Standard

error t-statistic

Parameter

estimate

Standard

error t-statistic

Intercept 0.913 0.038 23.84 0.542 0.043 12.70

Monetarily eligible UI claim 0.034 0.021 1.64 0.044 0.023 1.89

Nonmonetarily eligible UI claim 0.010 0.008 1.24 −0.069 0.009 −7.74

Weekly benefit amount 0.000 0.000 4.28 −0.000 0.000 −2.21

Entitlement length (weeks) 0.002 0.001 2.08 −0.001 0.001 −1.00

UI beneficiary 0.060 0.009 6.93 −0.079 0.010 −8.23

Age 24 or less 0.082 0.007 11.87 0.049 0.008 6.41

 25–44 −0.015 0.002 −6.57 −0.004 0.002 −1.71

 45 or older −0.116 0.013 −8.65 −0.121 0.015 −8.08

Gender, male −0.019 0.008 −2.21 −0.066 0.009 −7.04

Gender, female 0.004 0.002 2.21 0.015 0.002 7.04

Race, white −0.011 0.007 −1.66 −0.015 0.008 −2.00

Race, black 0.023 0.004 5.18 0.012 0.005 2.49

Race, Hispanic −0.021 0.006 −3.26 −0.009 0.007 −1.24

Race, other −0.040 0.023 −1.76 0.045 0.025 1.77

Registered alien 0.015 0.011 1.38 −0.050 0.012 −4.07

Education, less than high school −0.008 0.005 −1.58 0.012 0.005 2.20

Education, high school grad./GED 0.004 0.004 1.10 −0.005 0.004 −1.32

Education, associate’s degree −0.001 0.010 −0.06 −0.005 0.011 −0.47

Education, bachelor’s degree or higher 0.028 0.019 1.46 −0.035 0.021 −1.64

Base period earnings ($1,000) −0.002 0.001 −1.98 0.000 0.001 0.14

Base period earnings < $10,000 −0.015 0.010 −1.44 −0.009 0.012 −0.74

4 or less qtrs. of employment before BYB −0.073 0.011 −6.84 −0.014 0.012 −1.17

 5–8 qtrs. −0.001 0.005 −0.21 −0.004 0.006 −0.68

 9–12 qtrs. 0.016 0.004 4.44 0.005 0.004 1.31

Quarters, TANF exit to unemployment −0.056 0.002 −30.48 −0.031 0.002 −14.86

Multiple employers in any base qtrs. 0.061 0.007 8.53 0.028 0.008 3.56

Agriculture, forestry, fishing 0.055 0.029 1.93 −0.067 0.032 −2.11

Mining 0.282 0.202 1.40 −0.178 0.226 −0.79

Utilities 0.096 0.122 0.79 −0.177 0.135 −1.30

Construction −0.013 0.020 −0.66 −0.015 0.022 −0.68

Manufacturing −0.018 0.014 −1.30 −0.007 0.015 −0.44

Wholesale trade −0.020 0.019 −1.02 −0.052 0.022 −2.44

Retail trade −0.002 0.009 −0.26 0.011 0.010 1.09

Transportation, warehousing 0.019 0.018 1.04 −0.008 0.021 −0.41

Information −0.020 0.026 −0.80 0.022 0.028 0.78

Finance and insurance −0.019 0.024 −0.78 −0.002 0.027 −0.08

Real estate, rental, leasing −0.072 0.025 −2.87 0.012 0.028 0.44

Professional, scientific, technical −0.046 0.018 −2.51 −0.007 0.020 −0.35

Company/enterprise management 0.013 0.035 0.37 0.002 0.039 0.06

Admin., support and waste mgmt. −0.001 0.008 −0.08 0.008 0.008 0.97

Educational services −0.003 0.025 −0.11 0.054 0.027 1.98
Table A.12 (Continued)

130

Independent variables

Return to employment Return to TANF

Parameter

estimate

Standard

error t-statistic

Parameter

estimate

Standard

error t-statistic

Health care/social assistance 0.008 0.011 0.76 0.017 0.012 1.37

Art, entertainment, recreation 0.017 0.036 0.47 −0.034 0.040 −0.85

Accommodation and food services 0.025 0.010 2.45 0.010 0.011 0.89

Other services (except publ. admin.) −0.047 0.020 −2.34 −0.016 0.022 −0.70

Public administration −0.069 0.027 −2.60 0.015 0.030 0.50

Unclassifiable −0.038 0.030 −1.29 −0.007 0.033 −0.20

Missing 0.032 0.015 2.11 −0.023 0.017 −1.35

Management occupations −0.003 0.018 −0.17 −0.033 0.020 −1.66

Business and financial operations −0.017 0.034 −0.49 −0.064 0.038 −1.71

Computer and mathematical science −0.045 0.031 −1.46 0.017 0.034 0.50

Architecture and engineering 0.105 0.051 2.08 0.072 0.056 1.27

Life, physical, and social sciences 0.085 0.063 1.34 −0.045 0.071 −0.64

Community and social services −0.019 0.045 −0.42 0.019 0.050 0.37

Legal occupations 0.070 0.061 1.14 −0.054 0.068 −0.79

Education, training, library −0.026 0.024 −1.09 −0.007 0.027 −0.25

Arts, design, entertainment, sports 0.032 0.033 0.99 0.015 0.037 0.42

Healthcare practitioner and technical −0.017 0.027 −0.64 0.000 0.030 0.01

Healthcare support occupations −0.002 0.017 −0.09 0.026 0.019 1.35

Protective service occupation 0.012 0.027 0.46 0.039 0.030 1.30

Food preparation and serving 0.006 0.012 0.55 0.016 0.013 1.22

Building/grounds cleaning/maintenance −0.044 0.014 −3.11 −0.003 0.016 −0.19

Personal care and service −0.011 0.020 −0.54 0.020 0.022 0.89

Sales and related occupations 0.005 0.009 0.50 0.019 0.010 1.79

Office and administrative support 0.001 0.007 0.08 0.000 0.008 0.06

Farming, fishing, forestry −0.034 0.036 −0.95 −0.014 0.040 −0.36

Construction and extraction 0.010 0.021 0.48 −0.026 0.024 −1.09

Installation, maintenance, repair −0.011 0.021 −0.56 0.032 0.023 1.39

Production occupations 0.003 0.011 0.29 0.001 0.012 0.06

Transportation, material moving −0.013 0.014 −0.89 −0.016 0.016 −0.99

Military specific occupations −0.035 0.142 −0.25 0.082 0.159 0.51

SOC/occupation code missing 0.021 0.014 1.56 −0.040 0.015 −2.66

Other code entered for ONET/SOC 0.079 0.033 2.41 −0.023 0.037 −0.64

Unemployment rate at TANF Exit −0.002 0.004 −0.43 0.010 0.004 2.25

Pct. chg. empl., end TANF to BYB 0.000 0.001 0.43 −0.001 0.001 −0.59

Qtrs. of TANF in 2 years before exit −0.004 0.001 −2.92 0.002 0.002 1.45

Eligible for EC/TEU −0.184 0.013 −14.35 0.071 0.014 4.95

Job search exempt −0.017 0.016 −1.04 −0.016 0.018 −0.90

Completed profiling −0.019 0.021 −0.91 −0.039 0.024 −1.63

Does NOT have a phone number 0.022 0.039 0.56 0.027 0.043 0.62

Child support withheld from UI check −0.064 0.068 −0.93 −0.009 0.076 −0.12

Year and qtr. of BYB, 1998:4 −0.195 0.074 −2.63 0.095 0.083 1.15

Year and qtr. of BYB, 1999:1 −0.091 0.034 −2.70 0.062 0.037 1.66

Year and qtr. of BYB, 1999:2 −0.043 0.020 −2.12 0.081 0.023 3.57

Year and qtr. of BYB, 1999:3 −0.052 0.018 −2.91 0.083 0.020 4.17

Year and qtr. of BYB, 1999:4 −0.052 0.017 −3.03 0.055 0.019 2.87

Year and qtr. of BYB, 2000:1 −0.030 0.014 −2.08 0.004 0.016 0.23

Year and qtr. of BYB, 2000:2 −0.007 0.012 −0.58 −0.020 0.013 −1.49

Year and qtr. of BYB, 2000:3 0.028 0.011 2.51 −0.019 0.012 −1.50

Year and qtr. of BYB, 2000:4 0.019 0.012 1.55 −0.014 0.014 −1.03

Year and qtr. of BYB, 2001:1 0.020 0.012 1.69 −0.000 0.013 −0.03
Table A.12 (Continued)

131

Independent variables

Return to employment Return to TANF

Parameter

estimate

Standard

error t-statistic

Parameter

estimate

Standard

error t-statistic

Year and qtr. of BYB, 2001:2 0.038 0.011 3.38 0.017 0.012 1.38

Year and qtr. of BYB, 2001:3 0.040 0.011 3.57 −0.019 0.012 −1.52

Year and qtr. of BYB, 2001:4 0.050 0.013 3.92 −0.008 0.014 −0.57

Year and qtr. of BYB, 2002:1 0.021 0.014 1.49 −0.024 0.016 −1.56

Year and qtr. of BYB, 2002:2 0.005 0.016 0.31 −0.023 0.018 −1.31

Year and qtr. of BYB, 2002:3 0.013 0.019 0.68 0.014 0.021 0.65

Year and qtr. of BYB, 2002:4 −0.027 0.024 −1.14 0.028 0.027 1.05

Year and qtr. of BYB, 2003:1 −0.130 0.025 −5.21 −0.047 0.028 −1.70

Year and qtr. of BYB, 2003:2 −0.140 0.030 −4.62 −0.051 0.034 −1.51

Year and qtr. of BYB, 2003:3 −0.219 0.036 −6.09 0.006 0.040 0.16

Year and qtr. of BYB, 2003:4 −0.282 0.050 −5.69 −0.075 0.055 −1.35

Year and qtr. of BYB, 2004:1 −0.326 0.091 −3.59 −0.101 0.101 −0.99

CBSA 1, code = 11580 −0.046 0.134 −0.34 −0.061 0.150 −0.40

CBSA 2, code = 15980 −0.003 0.031 −0.09 −0.119 0.034 −3.50

CBSA 3, code = 17500 0.050 0.058 0.87 −0.138 0.065 −2.13

CBSA 4, code = 19660 0.000 0.027 0.02 0.026 0.031 0.87

CBSA 5, code = 23020 0.048 0.044 1.10 0.073 0.049 1.49

CBSA 6, code = 23540 −0.062 0.035 −1.76 0.056 0.039 1.42

CBSA 7, code = 26140 0.010 0.051 0.20 0.028 0.057 0.49

CBSA 8, code = 27260 0.033 0.016 2.14 −0.061 0.017 −3.54

CBSA 9, code = 28580 0.034 0.073 0.47 0.211 0.081 2.60

CBSA 10, code = 29380 −0.042 0.041 −1.01 0.012 0.046 0.25

CBSA 11, code = 29460 0.054 0.019 2.89 −0.074 0.021 −3.60

CBSA 12, code = 33100 −0.012 0.005 −2.30 0.019 0.006 3.44

CBSA 13, code = 34940 −0.006 0.050 −0.11 −0.185 0.055 −3.35

CBSA 14, code = 36100 −0.034 0.029 −1.19 −0.005 0.032 −0.16

CBSA 15, code = 36380 −0.049 0.059 −0.83 −0.041 0.065 −0.62

CBSA 16, code = 36740 −0.008 0.013 −0.62 0.029 0.014 2.11

CBSA 17, code = 37260 −0.049 0.038 −1.29 −0.054 0.042 −1.28

CBSA 18, code = 37340 0.044 0.025 1.76 0.011 0.028 0.39

CBSA 19, code = 37380 0.105 0.075 1.39 0.086 0.084 1.02

CBSA 20, code = 37460 0.062 0.041 1.50 −0.042 0.046 −0.90

CBSA 21, code = 37860 0.016 0.023 0.67 −0.020 0.026 −0.76

CBSA 22, code = 38940 0.008 0.025 0.33 −0.034 0.028 −1.21

CBSA 23, code = 39460 −0.085 0.062 −1.38 −0.009 0.069 −0.13

CBSA 24, code = 42260 0.030 0.029 1.02 −0.007 0.032 −0.20

CBSA 25, code = 42680 0.062 0.047 1.32 −0.089 0.052 −1.70

CBSA 26, code = 42700 0.060 0.044 1.37 −0.091 0.049 −1.86

CBSA 27, code = 45220 −0.001 0.024 −0.03 0.021 0.026 0.79

CBSA 28, code = 45300 0.006 0.012 0.50 −0.032 0.013 −2.49

CBSA 29, code = 45540 0.039 0.066 0.59 0.113 0.073 1.54

CBSA 30, code = 48100 0.102 0.079 1.30 −0.049 0.088 −0.56

CBSA 31, non-CBSA 0.012 0.023 0.50 0.028 0.026 1.07

Observations 14,053 14,053

R-squared 0.2202 0.1181

Adjusted R-squared 0.2132 0.1102
132

Table A.13 Linear Probability Models of Return to Employment and TANF, with Beneficiary Indicators,

among Newly Unemployed TANF-Leaver UI Applicants, Using Data from Georgia

Independent variables

Return to employment Return to TANF

Parameter

estimate

Standard

error t-statistic

Parameter

estimate

Standard

error t-statistic

Intercept 0.919 0.034 26.76 0.455 0.041 11.05

Monetarily eligible UI claim 0.043 0.011 3.98 0.043 0.013 3.35

Nonmonetarily eligible UI claim 0.001 0.005 0.14 −0.042 0.007 −6.40

Weekly benefit amount 0.000 0.000 0.75 −0.000 0.000 −1.62

WBA at maximum −0.024 0.014 −1.75 0.017 0.017 1.01

Entitlement length 0.002 0.001 2.35 −0.000 0.001 −0.02

UI beneficiary 0.048 0.006 7.71 −0.097 0.008 −12.98

Age 24 or Less 0.045 0.005 8.45 0.042 0.006 6.59

 25–49 −0.005 0.002 −2.82 −0.010 0.002 −5.19

 50 or older −0.137 0.014 −9.45 −0.031 0.017 −1.77

Gender, male −0.001 0.011 −0.14 −0.081 0.013 −6.30

Gender, female 0.000 0.001 0.14 0.008 0.001 6.30

Race, white −0.029 0.006 −4.41 −0.064 0.008 −8.25

Race, black 0.007 0.002 4.75 0.017 0.002 9.10

Race, Hispanic −0.095 0.028 −3.42 −0.135 0.033 −4.04

Race, other 0.009 0.020 0.46 −0.038 0.024 −1.54

Education, less than high school −0.009 0.005 −1.83 0.031 0.006 5.47

Education, high school grad./GED 0.006 0.002 2.51 0.001 0.003 0.43

Education, some college −0.008 0.006 −1.33 −0.035 0.007 −4.78

Education, bachelor’s degree or higher 0.012 0.019 0.66 −0.084 0.022 −3.77

Base period earnings ($1,000) 0.000 0.000 0.68 0.000 0.000 0.51

Base period earnings < $10,000 0.000 0.009 0.03 0.003 0.011 0.25

Employed 4 qtrs. or less, of last 12 −0.082 0.008 −10.09 −0.023 0.010 −2.39

Employed 5–8 qtrs. of last 12 −0.013 0.004 −3.31 0.001 0.005 0.12

Employed 9–12 qtrs. of last 12 0.022 0.003 7.99 0.004 0.003 1.11

Qtrs., TANF exit to unemployment −0.046 0.001 −38.50 −0.025 0.001 −17.53

Multiple employers any base period qtr. 0.039 0.005 7.13 0.001 0.007 0.10

Agriculture, forestry, fishing 0.094 0.034 2.76 0.033 0.041 0.81

Mining −0.003 0.133 −0.02 0.207 0.160 1.30

Utilities 0.190 0.113 1.68 0.001 0.136 0.01

Construction 0.013 0.019 0.70 0.026 0.023 1.12

Manufacturing 0.007 0.006 1.03 0.010 0.008 1.36

Wholesale trade −0.007 0.014 −0.48 −0.020 0.017 −1.21

Retail trade −0.007 0.007 −1.06 0.005 0.008 0.66

Transportation, warehousing 0.006 0.018 0.35 0.008 0.022 0.36

Information 0.003 0.019 0.16 −0.012 0.023 −0.53

Finance and insurance −0.028 0.019 −1.44 −0.029 0.023 −1.26

Real estate, rental, leasing 0.010 0.024 0.40 0.025 0.029 0.88

Professional, scientific, technical −0.006 0.023 −0.26 −0.034 0.028 −1.24

Company/enterprise management −0.114 0.142 −0.80 0.033 0.171 0.20

Admin., support and waste mgmt. 0.009 0.006 1.39 −0.003 0.007 −0.37

Educational services −0.018 0.017 −1.08 −0.047 0.020 −2.28
Table A.13 (Continued)

133

Independent variables

Return to employment Return to TANF

Parameter

estimate

Standard

error t-statistic

Parameter

estimate

Standard

error t-statistic

Health care/social assistance −0.007 0.008 −0.97 −0.000 0.009 −0.02

Art, entertainment, recreation −0.029 0.041 −0.69 −0.055 0.050 −1.10

Accommodation and food services 0.007 0.007 0.96 0.004 0.009 0.46

Other services (except publ. admin.) −0.026 0.016 −1.60 −0.017 0.019 −0.89

Public administration −0.044 0.016 −2.82 −0.003 0.019 −0.17

Unclassifiable 0.069 0.054 1.29 −0.099 0.065 −1.54

Management, business, financial 0.029 0.019 1.51 −0.041 0.023 −1.77

Professional and related occupations 0.003 0.013 0.20 −0.022 0.016 −1.43

Services 0.008 0.006 1.43 0.029 0.007 4.13

Sales and related occupations 0.023 0.011 2.10 0.008 0.013 0.60

Office and administrative support −0.005 0.007 −0.75 −0.006 0.008 −0.77

Farming, fishing, and forestry 0.010 0.032 0.31 −0.079 0.038 −2.06

Construction and extraction −0.000 0.022 −0.02 −0.009 0.027 −0.33

Installation, maintenance, and repair −0.000 0.029 −0.01 0.004 0.035 0.12

Production 0.008 0.008 1.11 0.004 0.009 0.46

Transportation and material moving 0.016 0.009 1.84 0.003 0.010 0.25

Occupation missing −0.203 0.061 −3.30 −0.099 0.074 −1.34

Adults on case at exit −0.008 0.006 −1.37 −0.043 0.007 −5.79

Children under age 6 on case at exit 0.010 0.003 3.18 0.032 0.004 8.52

Unemployment rate at BYB −0.010 0.003 −3.54 0.007 0.003 2.06

Unemployment rate ∆ BYB to BYE −0.011 0.003 −3.94 0.010 0.003 2.99

Food stamps (def. 1) 0.008 0.007 1.15 0.102 0.009 11.71

Dislocated worker −0.008 0.007 −1.23 −0.012 0.008 −1.43

Education status, 1 = in school 0.002 0.017 0.12 0.050 0.021 2.41

Veteran −0.042 0.017 −2.48 −0.014 0.020 −0.68

Data complexity, synthesizing −0.089 0.048 −1.86 −0.066 0.057 −1.16

Data complexity, coordinating −0.004 0.013 −0.35 0.022 0.015 1.48

Data complexity, analyzing 0.023 0.017 1.37 0.015 0.020 0.77

Data complexity, compiling −0.009 0.006 −1.46 −0.006 0.007 −0.81

Data complexity, computing 0.022 0.007 3.00 0.031 0.009 3.43

Data complexity, copying 0.008 0.010 0.79 −0.006 0.012 −0.52

Data complexity, comparing −0.005 0.005 −0.99 −0.009 0.006 −1.61

Data complexity, unknown or missing −0.001 0.060 −0.02 −0.014 0.072 −0.20

YYYYQ of BYB = 1996:2 −0.115 0.041 −2.80 0.131 0.049 2.67

YYYYQ of BYB = 1996:3 −0.017 0.025 −0.67 0.183 0.030 6.15

YYYYQ of BYB = 1996:4 0.017 0.020 0.89 0.143 0.023 6.09

YYYYQ of BYB = 1997:1 0.004 0.017 0.24 0.083 0.021 4.07

YYYYQ of BYB = 1997:2 0.008 0.015 0.57 0.062 0.017 3.56

YYYYQ of BYB = 1997:3 0.038 0.012 3.15 −0.003 0.015 −0.21

YYYYQ of BYB = 1997:4 0.076 0.012 6.56 −0.049 0.014 −3.58

YYYYQ of BYB = 1998:1 0.034 0.012 2.74 −0.067 0.015 −4.52

YYYYQ of BYB = 1998:2 0.083 0.011 7.44 −0.041 0.013 −3.10

YYYYQ of BYB = 1998:3 0.080 0.011 7.50 −0.050 0.013 −3.90

YYYYQ of BYB = 1998:4 0.072 0.011 6.55 −0.066 0.013 −5.03

YYYYQ of BYB = 1999:1 0.067 0.012 5.80 −0.077 0.014 −5.57

YYYYQ of BYB = 1999:2 0.018 0.013 1.40 −0.052 0.016 −3.33

YYYYQ of BYB = 1999:3 0.037 0.012 3.17 −0.040 0.014 −2.84

YYYYQ of BYB = 1999:4 0.033 0.015 2.24 −0.028 0.018 −1.58

YYYYQ of BYB = 2000:1 −0.015 0.016 −0.97 −0.041 0.019 −2.19
Table A.13 (Continued)

134

Independent variables

Return to employment Return to TANF

Parameter

estimate

Standard

error t-statistic

Parameter

estimate

Standard

error t-statistic

YYYYQ of BYB = 2000:2 −0.044 0.018 −2.38 0.055 0.022 2.47

YYYYQ of BYB = 2000:3 −0.045 0.017 −2.72 0.069 0.020 3.46

YYYYQ of BYB = 2000:4 −0.038 0.016 −2.36 0.074 0.020 3.77

YYYYQ of BYB = 2001:1 −0.030 0.016 −1.88 0.007 0.019 0.37

YYYYQ of BYB = 2001:2 −0.062 0.014 −4.31 0.042 0.017 2.46

YYYYQ of BYB = 2001:3 −0.068 0.014 −5.01 0.052 0.016 3.19

YYYYQ of BYB = 2001:4 −0.066 0.013 −5.15 0.039 0.015 2.51

YYYYQ of BYB = 2002:1 −0.076 0.014 −5.27 0.032 0.017 1.86

YYYYQ of BYB = 2002:2 −0.121 0.015 −8.13 0.021 0.018 1.17

YYYYQ of BYB = 2002:3 −0.105 0.016 −6.66 0.049 0.019 2.56

YYYYQ of BYB = 2002:4 −0.088 0.019 −4.65 0.030 0.023 1.32

YYYYQ of BYB = 2003:1 −0.075 0.021 −3.54 0.049 0.025 1.93

YYYYQ of BYB = 2003:2 −0.100 0.024 −4.22 0.044 0.028 1.55

YYYYQ of BYB = 2003:3 −0.102 0.026 −3.87 0.054 0.032 1.72

YYYYQ of BYB = 2003:4 −0.124 0.034 −3.64 0.062 0.041 1.52

YYYYQ of BYB = 2004:1 −0.087 0.043 −2.01 0.085 0.052 1.63

YYYYQ of BYB = 2004:2 −0.277 0.050 −5.49 0.027 0.060 0.44

YYYYQ of BYB = 2004:3 −0.343 0.109 −3.15 −0.097 0.131 −0.74

YYYYQ of BYB = 2004:4 −0.585 0.188 −3.11 −0.198 0.225 −0.88

APPLING County −0.090 0.057 −1.59 −0.092 0.068 −1.36

ATKINSON County 0.065 0.061 1.06 0.012 0.073 0.16

BACON County −0.035 0.074 −0.47 0.034 0.088 0.39

BAKER County 0.004 0.080 0.05 0.050 0.096 0.52

BALDWIN County 0.007 0.031 0.22 0.117 0.038 3.11

BANKS County 0.163 0.104 1.57 −0.121 0.125 −0.97

BARROW County 0.013 0.067 0.19 −0.174 0.081 −2.15

BARTOW County 0.024 0.037 0.65 −0.117 0.044 −2.65

BEN HILL County 0.034 0.040 0.83 −0.031 0.048 −0.64

BERRIEN County 0.060 0.049 1.22 0.006 0.059 0.10

BIBB County 0.016 0.014 1.14 −0.013 0.017 −0.77

BLECKLEY County 0.033 0.065 0.50 0.050 0.078 0.64

BRANTLEY County 0.063 0.078 0.80 −0.174 0.094 −1.85

BROOKS County 0.044 0.045 0.97 −0.033 0.054 −0.60

BRYAN County −0.057 0.070 −0.82 0.002 0.084 0.03

BULLOCH County 0.009 0.030 0.30 0.058 0.036 1.63

BURKE County 0.065 0.033 1.98 0.014 0.039 0.36

BUTTS County 0.037 0.075 0.49 −0.080 0.090 −0.90

CALHOUN County 0.004 0.058 0.07 0.072 0.070 1.03

CAMDEN County −0.042 0.052 −0.82 −0.234 0.062 −3.78

CANDLER County 0.009 0.071 0.12 0.042 0.085 0.50

CARROLL County 0.030 0.027 1.12 −0.110 0.032 −3.47

CATOOSA County −0.015 0.069 −0.21 −0.194 0.082 −2.36

CHARLTON County −0.081 0.108 −0.75 −0.243 0.130 −1.87

CHATHAM County 0.017 0.014 1.25 −0.035 0.016 −2.13

CHATTAHOOCHEE County 0.232 0.133 1.75 −0.070 0.159 −0.44

CHATTOOGA County 0.015 0.055 0.28 −0.165 0.066 −2.51

CHEROKEE County 0.007 0.062 0.11 −0.065 0.074 −0.87

CLARKE County −0.004 0.022 −0.20 0.003 0.027 0.11

CLAY County −0.221 0.141 −1.56 0.276 0.170 1.63

CLAYTON County −0.032 0.016 −2.06 −0.078 0.019 −4.17

CLINCH County 0.153 0.072 2.12 −0.047 0.086 −0.54

COBB County −0.054 0.018 −3.00 −0.042 0.021 −1.96
Table A.13 (Continued)

135

Independent variables

Return to employment Return to TANF

Parameter

estimate

Standard

error t-statistic

Parameter

estimate

Standard

error t-statistic

COFFEE County 0.015 0.035 0.43 −0.044 0.042 −1.04

COLQUITT County 0.014 0.026 0.54 0.029 0.032 0.91

COLUMBIA County −0.065 0.036 −1.78 0.040 0.044 0.92

COOK County 0.017 0.048 0.36 0.128 0.058 2.20

COWETA County 0.062 0.036 1.72 −0.178 0.044 −4.08

CRAWFORD County 0.049 0.097 0.50 0.102 0.116 0.88

CRISP County 0.054 0.028 1.94 0.079 0.033 2.39

DADE County −0.037 0.142 −0.26 −0.206 0.170 −1.21

DAWSON County 0.097 0.109 0.89 −0.113 0.131 −0.86

DECATUR County −0.044 0.030 −1.47 −0.027 0.036 −0.74

DEKALB County −0.041 0.010 −4.27 −0.071 0.011 −6.23

DODGE County 0.101 0.046 2.19 0.062 0.056 1.11

DOOLY County 0.018 0.047 0.38 0.067 0.056 1.20

DOUGHERTY County 0.038 0.015 2.65 0.119 0.017 6.87

DOUGLAS County −0.057 0.039 −1.48 −0.047 0.047 −1.00

EARLY County 0.077 0.043 1.82 0.164 0.051 3.21

ECHOLS County 0.172 0.167 1.03 0.004 0.201 0.02

EFFINGHAM County 0.025 0.056 0.45 0.072 0.067 1.07

ELBERT County 0.070 0.039 1.78 −0.119 0.047 −2.54

EMANUEL County 0.055 0.034 1.60 0.096 0.041 2.34

EVANS County 0.007 0.060 0.12 −0.025 0.072 −0.35

FANNIN County 0.104 0.063 1.66 −0.184 0.075 −2.45

FAYETTE County −0.035 0.054 −0.64 −0.057 0.065 −0.88

FLOYD County 0.037 0.025 1.46 −0.040 0.030 −1.34

FORSYTH County −0.036 0.094 −0.39 0.001 0.113 0.01

FRANKLIN County −0.035 0.059 −0.61 −0.038 0.070 −0.55

FULTON County −0.017 0.007 −2.44 0.029 0.009 3.44

GILMER County −0.043 0.075 −0.58 −0.190 0.090 −2.11

GLASCOCK County 0.320 0.142 2.25 −0.196 0.170 −1.15

GLYNN County 0.011 0.029 0.39 −0.073 0.035 −2.08

GORDON County −0.018 0.046 −0.39 −0.038 0.056 −0.68

GRADY County −0.021 0.041 −0.51 0.055 0.050 1.10

GREENE County 0.079 0.049 1.61 −0.098 0.059 −1.67

GWINNETT County −0.065 0.021 −3.10 −0.068 0.025 −2.72

HABERSHAM County 0.061 0.052 1.16 0.008 0.063 0.13

HALL County 0.033 0.031 1.04 0.068 0.038 1.80

HANCOCK County −0.018 0.054 −0.33 −0.123 0.065 −1.89

HARALSON County 0.052 0.059 0.87 −0.090 0.071 −1.27

HARRIS County −0.069 0.078 −0.89 0.102 0.094 1.08

HART County 0.024 0.044 0.54 0.005 0.053 0.10

HEARD County 0.055 0.091 0.61 −0.166 0.109 −1.52

HENRY County −0.042 0.043 −0.97 0.001 0.052 0.02

HOUSTON County −0.045 0.023 −1.95 0.010 0.028 0.37

IRWIN County −0.003 0.068 −0.04 −0.081 0.082 −0.99

JACKSON County −0.096 0.050 −1.93 0.052 0.060 0.88

JASPER County 0.087 0.075 1.16 −0.077 0.090 −0.86

JEFF DAVIS County 0.149 0.066 2.25 −0.042 0.080 −0.53

JEFFERSON County 0.066 0.037 1.82 0.069 0.044 1.57

JENKINS County 0.114 0.053 2.15 0.095 0.064 1.49

JOHNSON County 0.121 0.055 2.22 0.035 0.065 0.53

JONES County 0.044 0.057 0.77 −0.128 0.069 −1.86

LAMAR County −0.001 0.061 −0.02 −0.054 0.073 −0.74

LANIER County 0.047 0.094 0.50 −0.021 0.112 −0.19
Table A.13 (Continued)

136

Independent variables

Return to employment Return to TANF

Parameter

estimate

Standard

error t-statistic

Parameter

estimate

Standard

error t-statistic

LAURENS County 0.042 0.028 1.52 −0.015 0.033 −0.44

LEE County 0.023 0.060 0.39 −0.052 0.072 −0.72

LIBERTY County −0.043 0.031 −1.39 −0.032 0.037 −0.86

LINCOLN County −0.039 0.084 −0.46 −0.172 0.101 −1.70

LONG County −0.058 0.100 −0.58 0.117 0.120 0.98

LOWNDES County 0.016 0.019 0.82 0.017 0.023 0.72

LUMPKIN County −0.077 0.108 −0.71 −0.094 0.130 −0.72

MCDUFFIE County 0.052 0.036 1.43 0.052 0.043 1.19

MCINTOSH County 0.038 0.067 0.57 −0.179 0.081 −2.22

MACON County 0.099 0.038 2.58 −0.041 0.046 −0.90

MADISON County 0.129 0.053 2.43 −0.054 0.064 −0.85

MARION County 0.112 0.082 1.36 −0.001 0.098 −0.01

MERIWETHER County 0.015 0.049 0.30 −0.109 0.059 −1.84

MILLER County −0.148 0.069 −2.13 0.125 0.083 1.50

MITCHELL County 0.021 0.032 0.66 0.134 0.039 3.45

MONROE County −0.121 0.084 −1.44 −0.148 0.101 −1.47

MONTGOMERY County −0.026 0.071 −0.37 0.001 0.085 0.01

MORGAN County −0.003 0.070 −0.04 −0.028 0.084 −0.34

MURRAY County 0.032 0.063 0.51 −0.140 0.075 −1.85

MUSCOGEE County −0.003 0.012 −0.27 0.014 0.014 0.97

NEWTON County −0.024 0.032 −0.75 −0.068 0.039 −1.76

OCONEE County 0.009 0.084 0.11 0.056 0.101 0.56

OGLETHORPE County −0.011 0.078 −0.14 −0.122 0.094 −1.30

PAULDING County 0.015 0.056 0.27 −0.120 0.067 −1.80

PEACH County 0.034 0.036 0.94 0.076 0.043 1.77

PICKENS County 0.091 0.080 1.14 −0.129 0.096 −1.34

PIERCE County 0.033 0.067 0.48 −0.049 0.081 −0.60

PIKE County −0.091 0.072 −1.26 −0.018 0.086 −0.21

POLK County −0.034 0.042 −0.80 −0.107 0.050 −2.12

PULASKI County −0.142 0.062 −2.30 0.045 0.074 0.60

PUTNAM County 0.047 0.064 0.73 −0.016 0.077 −0.20

QUITMAN County −0.157 0.265 −0.59 −0.314 0.317 −0.99

RABUN County −0.006 0.104 −0.06 −0.072 0.125 −0.58

RANDOLPH County −0.005 0.057 −0.09 0.093 0.069 1.36

RICHMOND County 0.018 0.012 1.54 0.083 0.014 5.92

ROCKDALE County −0.036 0.042 −0.87 −0.184 0.050 −3.68

SCHLEY County −0.139 0.132 −1.05 −0.120 0.159 −0.76

SCREVEN County 0.023 0.049 0.48 −0.068 0.058 −1.17

SEMINOLE County −0.038 0.053 −0.72 0.182 0.063 2.86

SPALDING County 0.016 0.027 0.59 −0.046 0.033 −1.41

STEPHENS County 0.081 0.044 1.86 −0.100 0.052 −1.91

STEWART County −0.028 0.065 −0.43 0.178 0.078 2.28

SUMTER County 0.027 0.024 1.12 0.064 0.029 2.17

TALBOT County 0.001 0.075 0.01 −0.037 0.090 −0.42

TALIAFERRO County 0.045 0.094 0.48 0.030 0.113 0.27

TATTNALL County −0.047 0.047 −0.99 0.109 0.057 1.91

TAYLOR County 0.037 0.061 0.61 0.109 0.073 1.50

TELFAIR County 0.106 0.060 1.77 0.040 0.072 0.55

TERRELL County −0.029 0.038 −0.76 0.154 0.045 3.41

THOMAS County −0.016 0.028 −0.56 0.060 0.033 1.80

TIFT County −0.002 0.028 −0.06 0.079 0.034 2.36

TOOMBS County −0.037 0.035 −1.06 −0.010 0.042 −0.23

TOWNS County −0.326 0.167 −1.95 −0.259 0.201 −1.29
Table A.13 (Continued)

137

Independent variables

Return to employment Return to TANF

Parameter

estimate

Standard

error t-statistic

Parameter

estimate

Standard

error t-statistic

TREUTLEN County 0.071 0.084 0.85 −0.025 0.101 −0.25

TROUP County −0.014 0.030 −0.47 −0.044 0.036 −1.24

TURNER County −0.001 0.046 −0.02 −0.046 0.055 −0.83

TWIGGS County 0.015 0.073 0.20 0.103 0.088 1.17

UNION County 0.023 0.074 0.31 0.073 0.089 0.82

UPSON County 0.046 0.041 1.11 −0.056 0.050 −1.12

WALKER County −0.029 0.036 −0.80 −0.110 0.044 −2.53

WALTON County −0.024 0.037 −0.66 −0.043 0.044 −0.98

WARE County −0.036 0.031 −1.19 −0.002 0.037 −0.06

WARREN County 0.103 0.061 1.69 −0.050 0.073 −0.69

WASHINGTON County −0.054 0.034 −1.58 0.161 0.041 3.90

WAYNE County 0.038 0.042 0.90 −0.102 0.051 −2.01

WEBSTER County −0.269 0.118 −2.27 0.111 0.142 0.78

WHEELER County 0.138 0.084 1.64 −0.129 0.101 −1.27

WHITE County −0.198 0.086 −2.30 0.170 0.103 1.64

WHITFIELD County 0.089 0.041 2.18 −0.059 0.049 −1.19

WILCOX County −0.085 0.067 −1.26 0.095 0.081 1.18

WILKES County 0.034 0.061 0.56 0.057 0.073 0.78

WILKINSON County 0.083 0.063 1.33 −0.050 0.075 −0.66

WORTH County 0.064 0.033 1.91 0.176 0.040 4.40

Observations 20,369 20,369

R-squared 0.1878 0.1539

Adjusted R-squared 0.1773 0.1431
138

Table A.14 Linear Probability Models of Return to Employment and TANF, with Beneficiary Indicators,

among Newly Unemployed TANF-Leaver UI Applicants, Using Data from Michigan

Independent variables

Returned to employment Returned to TANF

Parameter

estimate

Standard

error t-statistic

Parameter

estimate

Standard

error t-statistic

Intercept 1.131 0.214 5.28 0.447 0.253 1.76

Monetarily eligible UI claim −0.273 0.195 −1.40 0.152 0.231 0.66

Nonmonetarily eligible UI claim 0.045 0.015 3.01 −0.121 0.018 −6.89

Weekly benefit amount 0.000 0.000 2.64 0.000 0.000 0.52

Entitlement length (weeks) 0.001 0.002 0.39 −0.005 0.002 −2.24

UI beneficiary 0.023 0.015 1.52 −0.094 0.018 −5.25

Age as of BYB, 24 or Less 0.061 0.011 5.37 0.020 0.013 1.47

 25–44 −0.013 0.005 −2.77 −0.008 0.005 −1.39

 45 or older −0.096 0.023 −4.20 −0.001 0.027 −0.03

Gender, male −0.022 0.014 −1.60 −0.131 0.016 −8.16

Gender, female 0.007 0.004 1.60 0.042 0.005 8.16

Race, white −0.004 0.009 −0.50 −0.061 0.010 −6.08

Race, black 0.003 0.009 0.33 0.069 0.011 6.42

Race, Hispanic 0.009 0.031 0.29 −0.034 0.036 −0.93

Race, other 0.020 0.054 0.38 −0.052 0.064 −0.82

Education, less than high school −0.021 0.011 −1.89 0.048 0.013 3.67

Education, high school grad./GED 0.010 0.007 1.45 −0.015 0.008 −1.90

Education, some college 0.010 0.012 0.83 −0.018 0.014 −1.31

Education, college graduate or higher −0.044 0.034 −1.29 −0.029 0.040 −0.70

Base period earnings ($1,000) −0.001 0.002 −0.65 −0.000 0.002 −0.26

Base earnings less than $10,000 0.019 0.020 0.97 0.001 0.023 0.06

Employed 4 qtrs. or less before BYB −0.104 0.041 −2.57 −0.015 0.048 −0.32

 5–8 qtrs. −0.002 0.017 −0.11 0.017 0.020 0.84

 9–12 qtrs. 0.014 0.011 1.22 −0.005 0.013 −0.42

Quarters, TANF exit to unemployment −0.054 0.005 −11.20 −0.017 0.006 −2.94

Had multiple employers in any base qtr. 0.063 0.014 4.65 0.015 0.016 0.95

Agriculture, forestry, fishing 0.004 0.090 0.05 −0.089 0.107 −0.83

Mining −0.269 0.225 −1.19 0.012 0.266 0.04

Utilities 0.110 0.275 0.40 −0.142 0.325 −0.44

Construction 0.021 0.032 0.64 0.012 0.038 0.30

Manufacturing −0.025 0.020 −1.25 0.020 0.023 0.84

Wholesale trade −0.096 0.044 −2.15 0.075 0.052 1.43

Retail trade −0.002 0.015 −0.16 0.007 0.017 0.41

Transportation, warehousing −0.000 0.042 −0.01 0.018 0.049 0.36

Information −0.013 0.053 −0.23 −0.084 0.063 −1.34

Finance and insurance 0.004 0.039 0.09 −0.033 0.046 −0.73

Real estate, rental, leasing −0.086 0.047 −1.82 −0.081 0.056 −1.46

Professional, scientific, technical −0.010 0.037 −0.27 −0.043 0.044 −0.98

Company/enterprise management 0.287 0.147 1.95 0.021 0.174 0.12

Admin., support and waste mgmt. −0.001 0.014 −0.04 −0.001 0.017 −0.05

Educational services 0.088 0.042 2.11 −0.142 0.050 −2.87

Health care/social assistance −0.013 0.016 −0.80 0.004 0.019 0.18

Art, entertainment, recreation 0.015 0.048 0.30 −0.056 0.057 −1.00

Accommodation and food services 0.044 0.018 2.47 0.019 0.021 0.92
Table A.14 (Continued)

139

Independent variables

Returned to employment Returned to TANF

Parameter

estimate

Standard

error t-statistic

Parameter

estimate

Standard

error t-statistic

Other services (except publ. admin.) −0.053 0.037 −1.43 0.049 0.044 1.11

Public administration 0.045 0.058 0.77 −0.050 0.069 −0.73

Unclassifiable −0.034 0.080 −0.42 −0.072 0.095 −0.76

Industry missing 0.023 0.034 0.68 0.024 0.040 0.60

Professional, technicala −0.010 0.021 −0.47 −0.018 0.025 −0.71

Clerical, sales 0.021 0.014 1.50 0.004 0.016 0.22

Services −0.011 0.019 −0.58 −0.018 0.022 −0.80

Agriculture, forestry, fish −0.040 0.028 −1.45 −0.069 0.033 −2.08

Processing 0.024 0.029 0.81 −0.036 0.034 −1.05

Machine trades 0.019 0.017 1.11 0.009 0.020 0.44

Bench work −0.025 0.021 −1.17 0.068 0.025 2.70

Structural work −0.015 0.019 −0.82 −0.001 0.022 −0.04

Miscellaneous −0.011 0.016 −0.68 0.012 0.018 0.66

Search-exempt, went back to worka 0.179 0.057 3.16 −0.056 0.067 −0.83

Employment (10,000), month of BYB −0.001 0.001 −1.76 0.002 0.001 2.52

Year-to-year pct. change in employment 0.003 0.006 0.57 0.004 0.007 0.59

Months tenure at sep. employer −0.000 0.000 −0.35 0.000 0.000 0.88

Employed at filing 0.007 0.006 1.18 0.003 0.007 0.35

Number of dependents (for taxes) −0.001 0.005 −0.29 0.010 0.006 1.63

Adults on case at TANF exit 0.002 0.011 0.20 0.004 0.014 0.32

Number of children under age 6 at exit 0.012 0.008 1.40 0.038 0.010 3.87

Disabled child/spouse on case before exit −0.017 0.030 −0.57 0.051 0.035 1.44

Classified as incapacitated before exit −0.050 0.030 −1.69 0.036 0.035 1.02

Received work deferral before exit −0.022 0.027 −0.79 −0.005 0.032 −0.14

Ineligible grantee before exit 0.004 0.039 0.11 0.112 0.046 2.42

MWAID = 2, Region 7B −0.068 0.050 −1.35 0.038 0.059 0.64

MWAID = 3, Calhoun ISD −0.055 0.046 −1.20 0.053 0.054 0.98

MWAID = 4, Saginaw-Midland-Bay −0.014 0.035 −0.40 0.107 0.041 2.60

MWAID = 5, Berrien-Cass-Van Buren −0.046 0.042 −1.09 0.045 0.050 0.91

MWAID = 6, Central UP −0.007 0.060 −0.12 0.058 0.071 0.82

MWAID = 9, Eastern UP 0.021 0.075 0.28 0.111 0.089 1.25

MWAID = 10, Genesee-Shiawassee −0.016 0.025 −0.63 0.077 0.029 2.62

MWAID = 11, Central −0.042 0.049 −0.87 0.056 0.058 0.97

MWAID = 13, Thumb −0.016 0.049 −0.32 0.159 0.058 2.75

MWAID = 14, Kalamazoo-St. Joseph 0.026 0.045 0.56 0.044 0.054 0.82

MWAID = 16, West Central −0.050 0.051 −0.97 0.056 0.061 0.92

MWAID = 17, Capital −0.054 0.034 −1.59 −0.044 0.040 −1.12

MWAID = 19, Macomb-St. Clair −0.055 0.026 −2.13 −0.047 0.030 −1.55

MWAID = 20, Muskegon-Oceana −0.033 0.043 −0.78 0.194 0.050 3.84

MWAID = 21, North East −0.062 0.056 −1.11 0.057 0.066 0.87

MWAID = 22, North West −0.102 0.052 −1.94 0.057 0.062 0.93

MWAID = 23, Oakland County 0.114 0.035 3.23 −0.156 0.042 −3.72

MWAID = 26, Western UP −0.070 0.073 −0.95 0.181 0.087 2.09

MWAID = 29, Livingston County 0.055 0.115 0.47 −0.101 0.136 −0.74

MWAID = 30, Washtenaw County 0.006 0.065 0.10 0.100 0.076 1.31

MWAID = 31, Wayne-Monroe 0.040 0.034 1.18 −0.076 0.040 −1.88

MWAID = 32, Ottawa County 0.022 0.059 0.38 −0.023 0.070 −0.33

MWAID = 33, ACSET 0.027 0.028 0.98 0.034 0.033 1.06

MWAID = 34, South Central −0.039 0.043 −0.91 −0.018 0.051 −0.36
Table A.14 (Continued)

140

Independent variables

Returned to employment Returned to TANF

Parameter

estimate

Standard

error t-statistic

Parameter

estimate

Standard

error t-statistic

Year and qtr. of BYB, 2001:1 −0.140 0.068 −2.04 0.032 0.081 0.39

Year and qtr. of BYB, 2001:2 −0.041 0.041 −1.00 0.028 0.048 0.59

Year and qtr. of BYB, 2001:3 −0.082 0.031 −2.64 0.048 0.037 1.31

Year and qtr. of BYB, 2001:4 0.003 0.022 0.14 0.005 0.026 0.21

Year and qtr. of BYB, 2002:1 0.009 0.023 0.38 0.007 0.027 0.25

Year and qtr. of BYB, 2002:2 −0.003 0.022 −0.15 0.049 0.026 1.89

Year and qtr. of BYB, 2002:3 −0.009 0.020 −0.45 0.023 0.024 0.97

Year and qtr. of BYB, 2002:4 0.054 0.020 2.73 −0.017 0.024 −0.74

Year and qtr. of BYB, 2003:1 0.067 0.022 3.02 0.023 0.026 0.86

Year and qtr. of BYB, 2003:2 0.061 0.027 2.25 −0.025 0.032 −0.79

Year and qtr. of BYB, 2003:3 0.067 0.030 2.22 −0.032 0.036 −0.90

Year and qtr. of BYB, 2003:4 0.022 0.034 0.65 −0.022 0.040 −0.54

Year and qtr. of BYB, 2004:1 0.001 0.040 0.02 −0.074 0.047 −1.57

Year and qtr. of BYB, 2004:2 −0.090 0.047 −1.91 −0.055 0.056 −0.98

Year and qtr. of BYB, 2004:3 −0.218 0.055 −3.98 −0.061 0.065 −0.94

Year and qtr. of BYB, 2004:4 −0.348 0.068 −5.11 −0.144 0.080 −1.79

Year and qtr. of BYB, 2005:1 −0.419 0.101 −4.13 −0.235 0.120 −1.96

Observations 3,843 3,843

R-squared 0.2236 0.1820

Adjusted R-squared 0.2029 0.1601 a

The Michigan Unemployment Agency uses the occupation (DOT) code to indicate job search exemption and return to work 

to prior employment. If a client is job search–exempt, his or her DOT code retains the first significant digit, but the remaining 

eight digits are set to zero. If the client subsequently returns to his or her prior employer, the DOT code is set to all zeros. 

Therefore, while the occupation codes plus the indicator for search exemption and returning to past employment form an 

exhaustive partition, the occupation code parameter estimates are not fully representative of the category because they exclude 

persons who were job search–exempt and went back to prior employment.
141

Table A.15 Linear Probability Models of Return to Employment and TANF, with Beneficiary Indicators,

among Newly Unemployed TANF-Leaver UI Applicants, Using Data from Ohio

Independent Variables

Returned to employment Returned to TANF

Parameter

estimate

Standard

error t-statistic

Parameter

estimate

Standard

error t-statistic

Intercept 1.150 0.120 9.62 0.723 0.136 5.32

Monetarily valid UI claim −0.017 0.014 −1.18 0.029 0.016 1.85

Weekly benefit amount −0.000 0.000 −1.11 −0.000 0.000 −2.88

Entitlement length −0.008 0.004 −1.84 −0.007 0.005 −1.40

UI beneficiary 0.091 0.011 8.67 −0.151 0.012 −12.63

Age 18–24 0.054 0.009 6.26 0.050 0.010 5.12

 25–44 −0.013 0.004 −3.61 −0.015 0.004 −3.53

 45+ −0.123 0.019 −6.32 −0.084 0.022 −3.82

Gender, male 0.020 0.014 1.49 −0.080 0.016 −5.18

Gender, female −0.004 0.003 −1.49 0.016 0.003 5.18

Race, white −0.008 0.007 −1.24 −0.034 0.007 −4.59

Race, black 0.010 0.005 2.00 0.027 0.006 4.55

Race, Hispanic −0.054 0.024 −2.26 0.017 0.027 0.62

Race, other −0.033 0.044 −0.76 −0.047 0.050 −0.95

Education, less than high school 0.005 0.005 0.94 0.010 0.005 1.84

Education, high school graduate/GED −0.006 0.005 −1.20 −0.004 0.005 −0.74

Education, some college 0.020 0.020 0.98 −0.059 0.023 −2.56

Education, bachelor’s degree or higher −0.065 0.058 −1.12 −0.038 0.066 −0.58

Base period earnings ($1,000) 0.002 0.001 1.42 0.005 0.002 3.34

Base period earnings less than $10,000 −0.006 0.014 −0.45 −0.011 0.016 −0.68

Employed 4 qtrs. or less before BYB −0.131 0.015 −8.58 −0.063 0.017 −3.61

 5–8 qtrs. −0.029 0.007 −3.96 −0.042 0.008 −5.15

 9–12 qtrs. 0.032 0.004 8.12 0.029 0.004 6.43

Qtrs., TANF exit to new unemployment −0.044 0.003 −14.74 −0.011 0.003 −3.13

Multiple employers in any base qtr. 0.060 0.009 6.63 0.022 0.010 2.13

Employment (10,000), month of BYB −0.000 0.000 −1.62 −0.003 0.000 −9.35

Total eligible adults at last payment −0.016 0.012 −1.37 −0.065 0.013 −4.89

Total eligible children (6–17) at last pmt. 0.008 0.004 1.93 −0.003 0.005 −0.54

Total eligible children < 6 at last payment 0.019 0.006 3.22 0.012 0.007 1.76

Exempt, caring for child under age 1 −0.031 0.021 −1.44 −0.044 0.024 −1.81

Has access to motor vehicle 0.003 0.010 0.26 −0.025 0.011 −2.22

Person is AG payee −0.002 0.019 −0.12 0.017 0.022 0.81

Person is parent of minor child in AG −0.039 0.022 −1.75 0.153 0.025 6.04

Marital status, single 0.012 0.004 3.04 −0.000 0.004 −0.04

Marital status, married −0.032 0.012 −2.68 0.035 0.014 2.56

Marital status, divorced/abandoned −0.000 0.015 −0.01 −0.033 0.017 −1.98

Marital status, separated −0.025 0.014 −1.76 −0.023 0.016 −1.44

Marital status, widow/widower −0.051 0.068 −0.75 −0.109 0.078 −1.40

Appalachian area county −0.027 0.015 −1.83 −0.055 0.017 −3.32

Metropolitan area county 0.003 0.004 0.66 0.042 0.005 8.36

Other area county 0.006 0.011 0.54 −0.108 0.012 −8.96
Table A.15 (Continued)

142

Independent Variables

Returned to employment Returned to TANF

Parameter

estimate

Standard

error t-statistic

Parameter

estimate

Standard

error t-statistic

Year and quarter of BYB, 2000:2 −0.012 0.058 −0.21 0.235 0.066 3.55

Year and quarter of BYB, 2000:3 −0.038 0.033 −1.15 0.203 0.038 5.35

Year and quarter of BYB, 2000:4 0.034 0.021 1.64 0.194 0.023 8.26

Year and quarter of BYB, 2001:1 −0.005 0.017 −0.30 0.136 0.019 7.17

Year and quarter of BYB, 2001:2 0.011 0.016 0.71 0.091 0.018 4.98

Year and quarter of BYB, 2001:3 −0.015 0.015 −1.01 0.062 0.017 3.58

Year and quarter of BYB, 2001:4 0.064 0.013 4.96 0.036 0.015 2.44

Year and quarter of BYB, 2002:1 0.021 0.012 1.74 −0.007 0.014 −0.48

Year and quarter of BYB, 2002:2 0.045 0.015 3.04 −0.065 0.017 −3.82

Year and quarter of BYB, 2002:3 0.076 0.017 4.44 −0.031 0.019 −1.62

Year and quarter of BYB, 2002:4 0.066 0.018 3.74 −0.081 0.020 −4.03

Year and quarter of BYB, 2003:1 0.018 0.019 0.94 −0.090 0.022 −4.08

Year and quarter of BYB, 2003:2 −0.009 0.022 −0.42 −0.134 0.025 −5.29

Year and quarter of BYB, 2003:3 −0.170 0.025 −6.82 −0.143 0.028 −5.06

Year and quarter of BYB, 2003:4 −0.213 0.028 −7.65 −0.162 0.032 −5.13

Year and quarter of BYB, 2004:1 −0.224 0.034 −6.64 −0.207 0.038 −5.40

Year and quarter of BYB, 2004:2 −0.328 0.046 −7.11 −0.260 0.053 −4.95

Year and quarter of BYB, 2004:3 −0.366 0.087 −4.19 −0.340 0.099 −3.42

Observations 8,836 8,836

R-squared 0.1908 0.1346

Adjusted R-squared 0.1862 0.1297
143

Table A.16 Linear Probability Models of Return to Employment and TANF, with Beneficiary and 

Exhaustion Indicators among Newly Unemployed TANF-Leaver UI Applicants, Using Pooled 

Data from Florida, Georgia, Michigan, and Ohio

Independent variables

Return to employment Return to TANF

Parameter

estimate

Standard

error t-statistic

Parameter

estimate

Standard

error t-statistic

Intercept 0.855 0.021 40.64 0.533 0.025 21.53

Monetarily eligible UI claim 0.024 0.008 3.19 0.051 0.009 5.71

Nonmonetarily eligible UI claim 0.005 0.004 1.19 −0.063 0.005 −13.28

Weekly benefit amount 0.000 0.000 4.08 −0.000 0.000 −5.27

WBA at maximum −0.025 0.010 −2.57 −0.023 0.011 −2.04

Entitlement length 0.000 0.001 0.71 −0.002 0.001 −2.03

UI beneficiary but not exhausteea 0.082 0.005 15.93 −0.140 0.006 −23.22

Exhausted regular UIa 0.017 0.005 3.38 −0.072 0.006 −12.33

Age 24 or less 0.066 0.003 19.34 0.052 0.004 13.01

 25–49 −0.012 0.001 −10.50 −0.010 0.001 −7.46

 50 or older −0.135 0.008 −16.52 −0.099 0.010 −10.28

Gender, male −0.012 0.005 −2.34 −0.098 0.006 −16.57

Gender, female 0.002 0.001 2.34 0.016 0.001 16.57

Race, white −0.013 0.003 −4.04 −0.058 0.004 −15.59

Race, black 0.012 0.002 7.19 0.031 0.002 16.07

Race, Hispanic −0.030 0.006 −4.98 −0.025 0.007 −3.46

Race, other −0.028 0.014 −2.03 −0.017 0.016 −1.05

Base period earnings ($1,000) 0.000 0.000 0.33 0.000 0.000 1.47

Base period earnings < $10,000 −0.001 0.006 −0.11 −0.000 0.007 −0.06

4 or fewer qtrs. of employment before BYB −0.090 0.006 −16.12 −0.026 0.007 −3.90

5–8 qtrs. −0.008 0.003 −3.14 −0.004 0.003 −1.18

9–12 qtrs. 0.025 0.002 12.82 0.008 0.002 3.47

Qtrs. TANF exit to new unemployment −0.046 0.001 −51.26 −0.030 0.001 −28.54

Had multiple employers in any base qtrs. 0.052 0.004 13.65 0.014 0.004 3.19

Agriculture, forestry, fishing 0.079 0.019 4.13 −0.063 0.023 −2.79

Mining 0.003 0.090 0.03 −0.039 0.106 −0.37

Utilities 0.111 0.074 1.50 −0.035 0.087 −0.40

Construction 0.007 0.011 0.62 −0.007 0.013 −0.52

Manufacturing 0.010 0.005 2.08 0.004 0.006 0.74

Wholesale trade −0.018 0.010 −1.70 −0.026 0.012 −2.10

Retail trade 0.004 0.005 0.80 0.006 0.005 1.06

Transportation, warehousing 0.020 0.012 1.77 −0.008 0.014 −0.59

Information −0.005 0.014 −0.35 −0.026 0.017 −1.57

Finance and insurance −0.020 0.013 −1.55 −0.026 0.015 −1.74

Real estate, rental, leasing −0.030 0.015 −1.97 −0.001 0.018 −0.08

Professional, scientific, technical −0.018 0.013 −1.44 −0.038 0.015 −2.55

Company/enterprise management 0.017 0.032 0.54 0.005 0.037 0.13

Admin., support and waste mgmt. 0.012 0.004 2.99 −0.004 0.005 −0.84

Educational services −0.002 0.013 −0.14 −0.047 0.015 −3.17

Health care/social assistance 0.000 0.005 0.03 0.006 0.006 0.95

Art, entertainment, recreation 0.013 0.021 0.60 −0.032 0.025 −1.28

Accommodation and food services 0.021 0.005 4.42 0.021 0.006 3.75

Other services (except publ. admin.) −0.036 0.011 −3.26 −0.011 0.013 −0.84

Public administration −0.043 0.013 −3.31 0.001 0.015 0.09
Table A.16 (Continued)

144

Independent variables

Return to employment Return to TANF

Parameter

estimate

Standard

error t-statistic

Parameter

estimate

Standard

error t-statistic

Unclassifiable −0.022 0.024 −0.95 0.008 0.028 0.30

Missing −0.089 0.009 −10.36 0.016 0.010 1.57

Unemployment rate, month of BYB 0.003 0.001 2.47 0.020 0.002 11.94

Unemployment rate ∆ BYB to BYE −0.002 0.002 −1.01 0.016 0.003 6.11

Florida 0.003 0.004 0.75 −0.022 0.004 −5.16

Georgia −0.016 0.003 −5.40 −0.017 0.004 −4.78

Michigan 0.039 0.008 4.74 0.080 0.010 8.20

Ohio 0.021 0.007 3.17 0.051 0.008 6.62

YYYY:Q of BYB, 1996:2 −0.094 0.042 −2.22 0.020 0.050 0.41

YYYY:Q of BYB, 1996:3 −0.010 0.025 −0.38 0.055 0.030 1.87

YYYY:Q of BYB, 1996:4 0.028 0.020 1.41 0.010 0.023 0.43

YYYY:Q of BYB, 1997:1 0.001 0.017 0.06 −0.050 0.020 −2.52

YYYY:Q of BYB, 1997:2 0.013 0.014 0.87 −0.050 0.017 −2.97

YYYY:Q of BYB, 1997:3 0.040 0.013 3.12 −0.081 0.015 −5.38

YYYY:Q of BYB, 1997:4 0.088 0.012 7.12 −0.094 0.015 −6.44

YYYY:Q of BYB, 1998:1 0.043 0.013 3.28 −0.105 0.016 −6.76

YYYY:Q of BYB, 1998:2 0.097 0.012 8.06 −0.057 0.014 −4.02

YYYY:Q of BYB, 1998:3 0.093 0.012 7.99 −0.073 0.014 −5.34

YYYY:Q of BYB, 1998:4 0.093 0.012 7.96 −0.071 0.014 −5.17

YYYY:Q of BYB, 1999:1 0.076 0.012 6.54 −0.056 0.014 −4.13

YYYY:Q of BYB, 1999:2 0.038 0.011 3.36 0.002 0.013 0.14

YYYY:Q of BYB, 1999:3 0.042 0.010 4.13 0.012 0.012 0.97

YYYY:Q of BYB, 1999:4 0.038 0.011 3.31 0.033 0.013 2.47

YYYY:Q of BYB, 2000:1 0.016 0.011 1.51 0.012 0.012 0.93

YYYY:Q of BYB, 2000:2 0.011 0.010 1.14 0.029 0.012 2.47

YYYY:Q of BYB, 2000:3 0.023 0.009 2.58 0.031 0.010 2.98

YYYY:Q of BYB, 2000:4 0.018 0.009 2.03 0.050 0.011 4.63

YYYY:Q of BYB, 2001:1 −0.006 0.008 −0.68 0.029 0.010 3.02

YYYY:Q of BYB, 2001:2 −0.006 0.008 −0.73 0.041 0.009 4.57

YYYY:Q of BYB, 2001:3 −0.033 0.007 −4.68 0.024 0.008 2.92

YYYY:Q of BYB, 2001:4 −0.018 0.007 −2.71 0.020 0.008 2.57

YYYY:Q of BYB, 2002:1 −0.035 0.007 −4.91 −0.017 0.008 −1.99

YYYY:Q of BYB, 2002:2 −0.044 0.008 −5.61 −0.011 0.009 −1.17

YYYY:Q of BYB, 2002:3 −0.036 0.009 −4.07 0.022 0.010 2.17

YYYY:Q of BYB, 2002:4 −0.023 0.010 −2.34 0.013 0.012 1.10

YYYY:Q of BYB, 2003:1 −0.075 0.013 −5.68 0.017 0.016 1.09

YYYY:Q of BYB, 2003:2 −0.088 0.015 −5.77 0.008 0.018 0.47

YYYY:Q of BYB, 2003:3 −0.100 0.017 −5.77 0.014 0.020 0.68

YYYY:Q of BYB, 2003:4 −0.118 0.020 −5.87 0.003 0.024 0.15

YYYY:Q of BYB, 2004:1 −0.116 0.025 −4.64 −0.024 0.030 −0.83

YYYY:Q of BYB, 2004:2 −0.213 0.031 −6.84 −0.004 0.037 −0.11

YYYY:Q of BYB, 2004:3 −0.330 0.043 −7.64 −0.033 0.051 −0.64

YYYY:Q of BYB, 2004:4 −0.442 0.057 −7.72 −0.046 0.067 −0.68

YYYY:Q of BYB, 2005:1 −0.471 0.096 −4.93 −0.195 0.112 −1.73

Observations 45,165 45,165

R-squared 0.1652 0.1110

Adjusted R-squared 0.1637 0.1095

NOTE: BYB = benefit year beginning; BYE = benefit year ending. a

Parameter estimate for UI exhaustees is significantly different from the estimate for other UI beneficiaries who do not exhaust 

UI entitlement in both models at the 95 percent confidence level in a two-tailed test.
145

Table A.17 Linear Probability Models of Return to Employment and TANF, with Beneficiary Indicators,

among Newly Unemployed TANF-Leaver UI Applications Fully Eligible for Benefits, Using 

Pooled Data from Florida, Georgia, Michigan, and Ohio

Independent variables

Return to employment Return to TANF

Parameter

estimate

Standard

error t-statistic

Parameter

estimate

Standard

error t-statistic

Intercept 0.862 0.028 30.94 0.569 0.032 18.02

Weekly benefit amount 0.000 0.000 3.13 −0.000 0.000 −5.52

WBA at maximum −0.020 0.014 −1.48 0.002 0.016 0.12

Entitlement length 0.001 0.001 1.36 −0.003 0.001 −2.49

UI beneficiary 0.047 0.008 6.18 −0.105 0.009 −12.21

Age 24 or less 0.064 0.006 10.24 0.054 0.007 7.60

 25–49 −0.006 0.002 −3.13 −0.006 0.002 −3.18

 50 or older −0.125 0.011 −10.94 −0.086 0.013 −6.62

Gender, male 0.003 0.007 0.37 −0.071 0.008 −8.37

Gender, female −0.001 0.002 −0.37 0.015 0.002 8.37

Race, white −0.022 0.006 −3.74 −0.052 0.007 −8.00

Race, black 0.015 0.003 5.34 0.024 0.003 7.76

Race, Hispanic −0.024 0.008 −2.86 −0.015 0.010 −1.54

Race, other −0.017 0.021 −0.85 −0.017 0.023 −0.75

Base period earnings ($1,000) 0.000 0.000 0.50 0.001 0.000 1.34

Base period earnings < $10,000 0.010 0.009 1.10 −0.009 0.010 −0.91

4 or fewer qtrs. employed before BYB −0.082 0.010 −8.46 −0.043 0.011 −3.90

5–8 qtrs. −0.007 0.005 −1.66 −0.005 0.005 −0.94

9–12 qtrs. 0.019 0.003 6.46 0.010 0.003 3.14

Qtrs. TANF exit to unemployment −0.046 0.001 −33.68 −0.030 0.002 −19.34

Multiple employers in a base qtr. 0.045 0.006 7.25 0.013 0.007 1.88

Agriculture, forestry, fishing 0.090 0.024 3.81 −0.108 0.027 −4.01

Mining 0.141 0.138 1.02 −0.137 0.156 −0.88

Utilities 0.102 0.123 0.83 −0.096 0.139 −0.69

Construction −0.008 0.015 −0.53 −0.011 0.017 −0.62

Manufacturing 0.018 0.007 2.45 −0.008 0.008 −1.03

Wholesale trade −0.020 0.015 −1.27 −0.011 0.017 −0.62

Retail trade 0.004 0.008 0.44 0.014 0.009 1.47

Transportation, warehousing 0.012 0.018 0.66 −0.012 0.021 −0.58

Information −0.006 0.023 −0.28 −0.004 0.026 −0.15

Finance and insurance −0.035 0.022 −1.58 0.020 0.025 0.81

Real estate, rental, leasing −0.045 0.026 −1.73 0.018 0.029 0.63

Professional, scientific, technical −0.010 0.018 −0.53 −0.019 0.021 −0.92

Company/enterprise management −0.005 0.053 −0.10 0.028 0.060 0.47

Admin., support and waste mgmt. 0.022 0.007 3.32 −0.002 0.007 −0.22

Educational services 0.037 0.018 2.06 −0.062 0.021 −3.01

Health care/social assistance −0.004 0.009 −0.46 0.004 0.010 0.42

Art, entertainment, recreation −0.015 0.033 −0.46 0.004 0.038 0.11

Accommodation and food services 0.020 0.009 2.19 0.022 0.010 2.18

Other services (except publ. admin.) −0.047 0.018 −2.70 −0.001 0.020 −0.07

Public administration −0.045 0.019 −2.38 0.021 0.021 0.98

Unclassifiable 0.031 0.037 0.83 0.016 0.041 0.38

Missing −0.119 0.014 −8.53 0.021 0.016 1.32
Table A.17 (Continued)

146

Independent variables

Return to employment Return to TANF

Parameter

estimate

Standard

error t-statistic

Parameter

estimate

Standard

error t-statistic

Unemployment rate, month of BYB 0.002 0.002 0.97 0.017 0.002 7.04

Unemployment rate ∆ BYB to BYE −0.007 0.003 −2.10 0.014 0.004 3.60

Florida −0.000 0.006 −0.08 −0.014 0.006 −2.16

Georgia −0.016 0.004 −3.66 0.001 0.005 0.26

Michigan 0.071 0.014 5.17 0.037 0.016 2.38

Ohio 0.060 0.017 3.43 0.031 0.020 1.56

YYYY:Q of BYB, 1996:2 −0.063 0.068 −0.92 −0.042 0.077 −0.55

YYYY:Q of BYB, 1996:3 −0.016 0.041 −0.38 0.107 0.047 2.27

YYYY:Q of BYB, 1996:4 −0.000 0.031 −0.01 −0.015 0.035 −0.42

YYYY:Q of BYB, 1997:1 0.006 0.026 0.22 −0.076 0.029 −2.59

YYYY:Q of BYB, 1997:2 0.011 0.023 0.46 −0.028 0.026 −1.08

YYYY:Q of BYB, 1997:3 0.032 0.019 1.73 −0.090 0.021 −4.26

YYYY:Q of BYB, 1997:4 0.078 0.019 4.15 −0.113 0.021 −5.30

YYYY:Q of BYB, 1998:1 0.041 0.020 2.05 −0.099 0.023 −4.38

YYYY:Q of BYB, 1998:2 0.101 0.018 5.46 −0.067 0.021 −3.22

YYYY:Q of BYB, 1998:3 0.102 0.016 6.20 −0.057 0.019 −3.07

YYYY:Q of BYB, 1998:4 0.094 0.017 5.44 −0.065 0.020 −3.33

YYYY:Q of BYB, 1999:1 0.101 0.017 5.84 −0.074 0.020 −3.77

YYYY:Q of BYB, 1999:2 0.054 0.017 3.19 −0.013 0.019 −0.67

YYYY:Q of BYB, 1999:3 0.048 0.015 3.14 −0.005 0.017 −0.30

YYYY:Q of BYB, 1999:4 0.012 0.018 0.67 −0.003 0.020 −0.14

YYYY:Q of BYB, 2000:1 0.020 0.017 1.16 −0.012 0.019 −0.61

YYYY:Q of BYB, 2000:2 0.019 0.016 1.21 0.024 0.018 1.39

YYYY:Q of BYB, 2000:3 0.010 0.014 0.72 0.018 0.016 1.10

YYYY:Q of BYB, 2000:4 −0.008 0.015 −0.53 0.046 0.017 2.76

YYYY:Q of BYB, 2001:1 −0.013 0.014 −0.95 0.030 0.016 1.87

YYYY:Q of BYB, 2001:2 −0.017 0.013 −1.34 0.032 0.014 2.23

YYYY:Q of BYB, 2001:3 −0.026 0.012 −2.26 0.021 0.013 1.61

YYYY:Q of BYB, 2001:4 −0.044 0.011 −4.04 0.025 0.012 2.03

YYYY:Q of BYB, 2002:1 −0.047 0.013 −3.59 −0.017 0.015 −1.16

YYYY:Q of BYB, 2002:2 −0.053 0.014 −3.78 0.017 0.016 1.07

YYYY:Q of BYB, 2002:3 −0.041 0.016 −2.48 0.054 0.019 2.91

YYYY:Q of BYB, 2002:4 −0.012 0.018 −0.68 0.034 0.020 1.69

YYYY:Q of BYB, 2003:1 −0.068 0.020 −3.35 0.065 0.023 2.83

YYYY:Q of BYB, 2003:2 −0.070 0.024 −2.92 0.064 0.027 2.37

YYYY:Q of BYB, 2003:3 −0.074 0.026 −2.86 0.104 0.029 3.53

YYYY:Q of BYB, 2003:4 −0.112 0.031 −3.64 0.037 0.035 1.07

YYYY:Q of BYB, 2004:1 −0.135 0.039 −3.47 0.045 0.044 1.02

YYYY:Q of BYB, 2004:2 −0.184 0.045 −4.04 0.007 0.052 0.13

YYYY:Q of BYB, 2004:3 −0.358 0.071 −5.03 0.020 0.081 0.24

YYYY:Q of BYB, 2004:4 −0.538 0.081 −6.66 −0.006 0.092 −0.06

YYYY:Q of BYB, 2005:1 −0.509 0.160 −3.19 −0.115 0.181 −0.64

Observations 17,054 17,054

R-squared 0.1853 0.0900

Adjusted R-squared 0.1816 0.0859

NOTE: BYB = benefit year beginning. BYE = benefit year ending.
147

Table A.18 Linear Probability Models of Return to Employment and TANF, with Beneficiary and 

Exhaustion Indicators, among Newly Unemployed TANF-Leaver UI Applicants Fully Eligible 

for Benefits, Using Pooled Data from Florida, Georgia, Michigan, and Ohio

Independent variables

Return to employment Return to TANF

Parameter

estimate

Standard

error t-statistic

Parameter

estimate

Standard

error t-statistic

Intercept 0.875 0.028 31.44 0.555 0.032 17.60

Weekly benefit amount 0.000 0.000 3.62 −0.001 0.000 −5.99

WBA at maximum −0.021 0.014 −1.57 0.003 0.015 0.20

Entitlement length 0.000 0.001 0.47 −0.002 0.001 −1.65

UI beneficiary not an exhausteea 0.085 0.008 9.95 −0.145 0.010 −15.10

UI exhausteea 0.015 0.008 1.89 −0.071 0.009 −7.62

Age 24 or less 0.062 0.006 9.97 0.056 0.007 7.90

 25–49 −0.005 0.002 −3.02 −0.007 0.002 −3.29

 50 or older −0.122 0.011 −10.68 −0.089 0.013 −6.90

Gender, male −0.001 0.007 −0.09 −0.067 0.008 −7.95

Gender, female 0.000 0.002 0.09 0.014 0.002 7.95

Race, white −0.025 0.006 −4.28 −0.049 0.007 −7.50

Race, black 0.016 0.003 5.61 0.024 0.003 7.53

Race, Hispanic −0.022 0.008 −2.61 −0.017 0.010 −1.78

Race, other −0.019 0.020 −0.91 −0.016 0.023 −0.69

Base period earnings ($1,000) 0.000 0.000 0.56 0.000 0.000 1.29

Base period earnings < $10,000 0.008 0.009 0.90 −0.007 0.010 −0.72

4 or fewer qtrs. employed before BYB −0.082 0.010 −8.52 −0.042 0.011 −3.87

5–8 qtrs. −0.007 0.004 −1.61 −0.005 0.005 −1.00

9–12 qtrs. 0.019 0.003 6.45 0.011 0.003 3.17

Qtrs. from TANF exit to new unempl. −0.046 0.001 −33.91 −0.030 0.002 −19.26

Multiple employers in a base qtr. 0.043 0.006 7.01 0.015 0.007 2.14

Agriculture, forestry, fishing 0.093 0.024 3.91 −0.110 0.027 −4.11

Mining 0.140 0.137 1.02 −0.137 0.156 −0.88

Utilities 0.100 0.123 0.81 −0.094 0.139 −0.68

Construction −0.009 0.015 −0.60 −0.010 0.017 −0.57

Manufacturing 0.016 0.007 2.26 −0.007 0.008 −0.85

Wholesale trade −0.019 0.015 −1.25 −0.011 0.017 −0.65

Retail trade 0.004 0.008 0.46 0.014 0.009 1.46

Transportation, warehousing 0.010 0.018 0.56 −0.010 0.020 −0.49

Information −0.004 0.022 −0.19 −0.006 0.025 −0.24

Finance and insurance −0.035 0.022 −1.56 0.020 0.025 0.79

Real estate, rental, leasing −0.043 0.026 −1.65 0.016 0.029 0.55

Professional, scientific, technical −0.008 0.018 −0.46 −0.021 0.021 −0.98

Company/enterprise management −0.012 0.053 −0.22 0.035 0.060 0.59

Admin., support and waste mgmt. 0.019 0.006 2.98 0.001 0.007 0.11

Educational services 0.036 0.018 1.98 −0.060 0.021 −2.94

Health care/social assistance −0.006 0.009 −0.66 0.006 0.010 0.61

Art, entertainment, recreation −0.012 0.033 −0.36 0.000 0.038 0.01

Accommodation and food services 0.016 0.009 1.79 0.026 0.010 2.57

Other services (except publ. admin.) −0.046 0.018 −2.62 −0.003 0.020 −0.15

Public administration −0.044 0.019 −2.33 0.020 0.021 0.93

Unclassifiable 0.034 0.036 0.92 0.013 0.041 0.31
Table A.18 (Continued)

148

Independent variables

Return to employment Return to TANF

Parameter

estimate

Standard

error t-statistic

Parameter

estimate

Standard

error t-statistic

Missing −0.100 0.014 −7.12 0.001 0.016 0.04

Unemployment rate, month of BYB 0.002 0.002 1.15 0.017 0.002 6.89

Unemployment rate ∆ BYB to BYE −0.006 0.003 −1.91 0.013 0.004 3.42

Florida −0.002 0.006 −0.38 −0.012 0.006 −1.88

Georgia −0.014 0.004 −3.17 −0.001 0.005 −0.21

Michigan 0.068 0.014 5.01 0.040 0.015 2.55

Ohio 0.052 0.017 3.00 0.039 0.020 1.98

YYYY:Q of BYB, 1996:2 −0.062 0.068 −0.91 −0.044 0.077 −0.57

YYYY:Q of BYB, 1996:3 −0.011 0.041 −0.27 0.101 0.047 2.16

YYYY:Q of BYB, 1996:4 0.000 0.031 0.01 −0.015 0.035 −0.43

YYYY:Q of BYB, 1997:1 0.002 0.026 0.08 −0.072 0.029 −2.46

YYYY:Q of BYB, 1997:2 0.008 0.023 0.35 −0.025 0.026 −0.97

YYYY:Q of BYB, 1997:3 0.029 0.019 1.57 −0.087 0.021 −4.11

YYYY:Q of BYB, 1997:4 0.070 0.019 3.72 −0.104 0.021 −4.89

YYYY:Q of BYB, 1998:1 0.034 0.020 1.69 −0.091 0.023 −4.03

YYYY:Q of BYB, 1998:2 0.091 0.018 4.94 −0.057 0.021 −2.73

YYYY:Q of BYB, 1998:3 0.092 0.016 5.61 −0.046 0.019 −2.50

YYYY:Q of BYB, 1998:4 0.084 0.017 4.87 −0.055 0.020 −2.79

YYYY:Q of BYB, 1999:1 0.089 0.017 5.19 −0.062 0.020 −3.15

YYYY:Q of BYB, 1999:2 0.052 0.017 3.06 −0.010 0.019 −0.54

YYYY:Q of BYB, 1999:3 0.044 0.015 2.89 −0.001 0.017 −0.05

YYYY:Q of BYB, 1999:4 0.008 0.018 0.45 0.001 0.020 0.07

YYYY:Q of BYB, 2000:1 0.018 0.017 1.05 −0.010 0.019 −0.50

YYYY:Q of BYB, 2000:2 0.020 0.015 1.27 0.023 0.018 1.33

YYYY:Q of BYB, 2000:3 0.013 0.014 0.94 0.014 0.016 0.90

YYYY:Q of BYB, 2000:4 −0.004 0.015 −0.26 0.042 0.017 2.50

YYYY:Q of BYB, 2001:1 −0.009 0.014 −0.62 0.025 0.016 1.55

YYYY:Q of BYB, 2001:2 −0.012 0.013 −0.94 0.027 0.014 1.86

YYYY:Q of BYB, 2001:3 −0.021 0.012 −1.80 0.015 0.013 1.17

YYYY:Q of BYB, 2001:4 −0.040 0.011 −3.69 0.021 0.012 1.69

YYYY:Q of BYB, 2002:1 −0.045 0.013 −3.49 −0.019 0.015 −1.27

YYYY:Q of BYB, 2002:2 −0.054 0.014 −3.85 0.018 0.016 1.14

YYYY:Q of BYB, 2002:3 −0.037 0.016 −2.27 0.050 0.019 2.71

YYYY:Q of BYB, 2002:4 −0.010 0.018 −0.58 0.032 0.020 1.59

YYYY:Q of BYB, 2003:1 −0.066 0.020 −3.24 0.063 0.023 2.72

YYYY:Q of BYB, 2003:2 −0.065 0.024 −2.72 0.059 0.027 2.17

YYYY:Q of BYB, 2003:3 −0.066 0.026 −2.53 0.095 0.029 3.22

YYYY:Q of BYB, 2003:4 −0.102 0.031 −3.30 0.026 0.035 0.74

YYYY:Q of BYB, 2004:1 −0.131 0.039 −3.36 0.040 0.044 0.91

YYYY:Q of BYB, 2004:2 −0.176 0.045 −3.89 −0.001 0.051 −0.03

YYYY:Q of BYB, 2004:3 −0.355 0.071 −4.99 0.015 0.080 0.19

YYYY:Q of BYB, 2004:4 −0.535 0.081 −6.65 −0.009 0.091 −0.09

YYYY:Q of BYB, 2005:1 −0.506 0.159 −3.18 −0.119 0.180 −0.66

Observations 17,054 17,054

R-squared 0.1898 0.0946

Adjusted R-squared 0.1860 0.0904

NOTE: BYB = benefit year beginning. BYE = benefit year ending. a

Parameter estimate for UI exhaustees is significantly different from the estimate for other UI beneficiaries who do not exhaust 

UI entitlement, in both models at the 95 percent confidence level in a two-tailed test.
149

Table A.19 Rates of Self-Sufficiency and TANF Dependency among Newly Unemployed TANF-Leavers,

Using Data from Floridaa

Group

Sample

size

Employed and 

no TANF

(self-sufficient)

Employed

with TANF

(working poor)

TANF and no

employment

(TANFdependent)

No TANF 

and no 

employment

(inactive)

Newly unemployed TANF leavers 43,113 0.519 0.268 0.044 0.169

UI applicants 15,177 0.434 0.257 0.072 0.237

 Monetarily eligible 14,547 0.434 0.255 0.072 0.239

 Monetarily ineligible

 Nonmonetarily eligible 6,962 0.488 0.199 0.067 0.246

 Quit prior employment 3,073 0.347 0.325 0.078 0.250

 Discharged/fired 5,142 0.412 0.294 0.076 0.218

 UI beneficiaries 9,385 0.472 0.215 0.066 0.247

 Not UI beneficiaries 5,792 0.372 0.324 0.082 0.222

 UI-eligible and UI beneficiary 5,839 0.495 0.186 0.064 0.255

 UI-eligible and not UI beneficiary 810 0.451 0.257 0.081 0.211

UI nonapplicants 27,936 0.566 0.274 0.029 0.131

 Pseudomonetarily eligibleb 18,764 0.586 0.215 0.032 0.166

 Pseudomonetarily ineligibleb 7,713 0.516 0.402 0.023 0.060 a

This table excludes persons who applied for UI after the first quarter of 2004 (the last quarter of TANF data). It also excludes 

persons who returned to TANF prior to UI application or had interim employment before applying for UI. b

Based on wage records for the first four of the five quarters prior to the quarter of new unemployment and the applicable UI law.
150

Table A.20 Rates of Self-Sufficiency and TANF Dependency among Newly Unemployed TANF-Leavers,

Using Data from Georgiaa

Group

Sample

size

Employed and

no TANF

(self-sufficient)

Employed 

with TANF

(working poor)

TANF and no

employment

(TANFdependent)

No TANF 

and no 

employment

(inactive)

Newly unemployed TANF leavers 118,316 0.538 0.259 0.053 0.150

UI applicants 21,872 0.471 0.302 0.062 0.165

 Monetarily eligible 19,378 0.480 0.293 0.063 0.165

 Monetarily ineligible

 Nonmonetarily eligible 10,274 0.510 0.277 0.052 0.161

 Quit prior employment 3,649 0.434 0.354 0.068 0.144

 Discharged/fired 7,412 0.442 0.328 0.073 0.157

 UI beneficiaries 10,613 0.552 0.235 0.050 0.164

 Not UI beneficiaries 11,259 0.395 0.366 0.073 0.166

 UI-eligible and UI beneficiary 6,101 0.573 0.220 0.046 0.161

 UI-eligible and not UI beneficiary 3,006 0.411 0.360 0.065 0.165

UI nonapplicants 96,444 0.553 0.249 0.051 0.147

 Pseudomonetarily eligibleb 74,057 0.578 0.231 0.045 0.145

 Pseudomonetarily ineligibleb 22,387 0.473 0.307 0.069 0.151 a

This table excludes persons who applied for UI after the fourth quarter of 2004 (the last quarter in which wage data was 

available for Georgia). This also excludes persons who returned to TANF prior to UI application or had interim employment prior 

to filing for UI. b

Based on wage records for the first four of the five quarters prior to the quarter of new unemployment and the applicable UI 

law.
151

Table A.21 Rates of Self-Sufficiency and TANF Dependency among Newly Unemployed TANF-Leavers,

Using Data from Michigana

Group

Sample

size

Employed and

no TANF

(self-sufficient)

Employed 

with TANF

(working poor)

TANF and no

employment

(TANFdependent)

No TANF 

and no 

employment

(inactive)

Newly unemployed TANF leavers 20,358 0.378 0.357 0.092 0.172

UI applicants 4,091 0.377 0.353 0.099 0.171

 Monetarily eligible 4,013 0.382 0.356 0.100 0.162

 Monetarily ineligible

 Nonmonetarily eligible 1,571 0.482 0.280 0.052 0.186

 Quit prior employment 731 0.293 0.398 0.107 0.202

 Discharged/fired 1,789 0.320 0.399 0.136 0.145

 UI beneficiaries 2,633 0.438 0.313 0.077 0.172

 Not UI beneficiaries 1,458 0.267 0.425 0.138 0.170

 UI-eligible and UI beneficiary 1,381 0.509 0.275 0.049 0.167

 UI-eligible and not UI beneficiary 115 0.357 0.417 0.096 0.130

UI nonapplicants 16,267 0.378 0.359 0.091 0.173

 Pseudomonetarily eligibleb 10,637 0.400 0.320 0.087 0.194

 Pseudomonetarily ineligibleb 5,630 0.337 0.432 0.098 0.133 a

This table excludes persons who applied for UI after the first quarter of 2005 (the last quarter in which wage data was 

available for Michigan). It also excludes persons who returned to TANF prior to UI application or had interim employment 

prior to filing for UI. b

Based on wage records in the first four of the five quarters prior to new unemployment and the applicable UI law.
152

Table A.22 Rates of Self-Sufficiency and TANF Dependency among Newly Unemployed TANF-Leavers,

Using Data from Ohioa

Group

Sample

size

Employed and

no TANF

(self-sufficient)

Employed 

with TANF

(working poor)

TANF and no

employment

(TANFdependent)

No TANF 

and no 

employment

(inactive)

Newly unemployed TANF leavers 59,932 0.354 0.383 0.096 0.167

UI applicants 8,848 0.366 0.347 0.100 0.187

 Monetarily eligible 6,112 0.367 0.337 0.102 0.194

 Monetarily ineligible

 Nonmonetarily eligible 2,075 0.426 0.380 0.074 0.120

 Quit prior employment 751 0.321 0.394 0.116 0.169

 Discharged/fired 1,561 0.316 0.466 0.099 0.119

 UI beneficiaries 2,780 0.462 0.283 0.061 0.195

 Not UI beneficiaries 6,068 0.322 0.377 0.118 0.183

 UI-eligible and UI beneficiary 556 0.579 0.277 0.047 0.097

 UI-eligible and not UI beneficiary 84 0.369 0.393 0.083 0.155

UI Nonapplicants 51,084 0.352 0.389 0.095 0.164

 Pseudomonetarily eligibleb 30,620 0.360 0.359 0.094 0.187

 Pseudomonetarily ineligibleb 20,464 0.340 0.434 0.096 0.130 a

This table excludes persons who applied for UI after the third quarter of 2004 (the last quarter in which wage data was 

available for Ohio). This also excludes persons who returned to TANF prior to UI application or had interim employment 

prior to filing for UI. b

Based on wage records in the first four of the five quarters prior to the quarter of new unemployment and the applicable UI 

law.
153

Table A.23 Linear Probability Models of Self-Sufficiency and TANF Dependency, with Beneficiary Indicators, among Newly U

Leaver UI Applicants, Using Pooled Data from Florida, Georgia, Michigan, and Ohio

Independent variables

Employment and no TANF

(self-sufficient)

Employment and TANF

(working poor)

TANF and no employment

(TANF-dependent)

N

Parameter

estimate t-statistic

Parameter

estimate t-statistic

Parameter

estimate t-statistic

P

Intercept 0.359 13.86 0.488 20.80 0.053 3.80 

Monetarily eligible UI claim −0.014 −1.50 0.038 4.52 0.013 2.51 

Nonmonetarily eligible UI claim 0.053 10.70 −0.049 −10.94 −0.013 −4.81 

Weekly benefit amount 0.000 5.24 −0.000 −2.68 −0.000 −3.87 

WBA at maximum −0.013 −1.05 −0.011 −1.01 −0.014 −2.17 

Entitlement length 0.003 4.50 −0.002 −3.54 0.000 0.98 

UI beneficiary 0.120 22.72 −0.072 −15.08 −0.032 −11.46 

Age 24 or less −0.003 −0.76 0.070 18.47 −0.019 −8.62 

 25–49 0.003 1.82 −0.015 −11.61 0.005 6.72 

 50 or older −0.023 −2.30 −0.114 −12.45 0.017 3.09 

Gender, male 0.079 12.74 −0.088 −15.71 −0.012 −3.76 

Gender, female −0.013 −12.74 0.015 15.71 0.002 3.76 

Race, white 0.043 11.10 −0.054 −15.38 −0.006 −2.64 

Race, black −0.019 −9.34 0.030 16.45 0.001 1.33 

Race, Hispanic −0.002 −0.28 −0.030 −4.36 0.006 1.58 

Race, other −0.011 −0.62 −0.017 −1.09 −0.001 −0.12 

Base period earnings ($1,000) −0.000 −0.63 0.000 0.91 0.000 1.25 

Base period earnings < $10,000 −0.003 −0.38 0.003 0.51 −0.005 −1.33 

4 or fewer qtrs. employment before BYB −0.039 −5.65 −0.051 −8.22 0.026 7.00 

5–8 qtrs. −0.001 −0.38 −0.007 −2.43 0.004 2.09 

9–12 qtrs. 0.009 3.88 0.016 7.25 −0.008 −6.19 

Quarters, TANF exit to unemployment −0.010 −9.06 −0.036 −35.88 0.006 9.82 

Multiple employers in any base qtr. 0.020 4.23 0.033 7.85 −0.020 −8.11 

Agriculture, forestry, fishing 0.131 5.53 −0.052 −2.44 −0.010 −0.76 

Mining 0.041 0.37 −0.040 −0.40 0.003 0.05 

Utilities 0.095 1.04 0.021 0.25 −0.060 −1.23 

Construction 0.008 0.62 −0.000 −0.01 −0.008 −1.09 
Table A.23 (Continued)

154

Independent variables

Employment and no TANF

(self-sufficient)

Employment and TANF

(working poor)

TANF and no employment

(TANF-dependent)

N

Parameter

estimate t-statistic

Parameter

estimate t-statistic

Parameter

estimate t-statistic

P

Manufacturing 0.011 1.85 0.001 0.17 0.001 0.41 

Wholesale trade 0.008 0.61 −0.026 −2.27 0.001 0.20 

Retail trade −0.001 −0.16 0.005 0.94 0.001 0.24 

Transportation, warehousing 0.024 1.70 −0.004 −0.28 −0.005 −0.60 

Information 0.017 0.97 −0.022 −1.39 −0.004 −0.43 

Finance and insurance 0.005 0.32 −0.025 −1.73 −0.002 −0.19 

Real estate, rental, leasing −0.026 −1.39 −0.004 −0.25 0.003 0.33 

Professional, scientific, technical 0.014 0.92 −0.033 −2.35 −0.004 −0.47 

Company/enterprise management −0.021 −0.53 0.041 1.16 −0.040 −1.91 

Admin., support and waste mgmt. 0.014 2.79 −0.001 −0.18 −0.004 −1.58 

Educational services 0.037 2.39 −0.038 −2.68 −0.010 −1.26 

Health care/social assistance −0.000 −0.05 0.001 0.16 0.004 1.29 

Art, entertainment, recreation 0.051 1.93 −0.039 −1.64 0.008 0.59 

Accommodation and food services −0.000 −0.04 0.023 4.27 −0.003 −0.99 

Other services (except publ. admin.) −0.009 −0.70 −0.026 −2.14 0.015 2.09 

Public administration −0.036 −2.26 −0.007 −0.52 0.009 1.12 

Unclassifiable −0.031 −1.08 0.009 0.36 −0.002 −0.11 

Missing −0.121 −11.57 0.019 1.95 0.012 2.07 

Unemployment rate, month of BYB −0.012 −6.77 0.015 9.58 0.005 5.24 

Unemployment rate ∆ BYB to BYE −0.014 −4.98 0.011 4.46 0.005 3.57 

Florida 0.019 4.12 −0.016 −3.83 −0.007 −2.80 

Georgia 0.001 0.15 −0.018 −5.47 0.003 1.57 

Michigan −0.028 −2.78 0.069 7.41 0.010 1.91 

Ohio −0.024 −2.94 0.048 6.61 −0.001 −0.30 

YYYY:Q of BYB, 1996:2 −0.054 −1.05 −0.039 −0.82 0.059 2.12 

YYYY:Q of BYB, 1996:3 −0.076 −2.47 0.066 2.36 −0.010 −0.59 

YYYY:Q of BYB, 1996:4 −0.018 −0.75 0.046 2.12 −0.037 −2.90 

YYYY:Q of BYB, 1997:1 0.033 1.61 −0.030 −1.61 −0.022 −1.95 

YYYY:Q of BYB, 1997:2 0.053 2.99 −0.038 −2.39 −0.014 −1.47 

YYYY:Q of BYB, 1997:3 0.091 5.80 −0.048 −3.41 −0.035 −4.17 

YYYY:Q of BYB, 1997:4 0.155 10.19 −0.061 −4.41 −0.039 −4.82 

YYYY:Q of BYB, 1998:1 0.120 7.39 −0.072 −4.92 −0.037 −4.24 

YYYY:Q of BYB, 1998:2 0.126 8.51 −0.023 −1.68 −0.041 −5.15 

YYYY:Q of BYB, 1998:3 0.141 9.85 −0.041 −3.15 −0.039 −5.16 
Table A.23 (Continued)

155

Independent variables

Employment and no TANF

(self-sufficient)

Employment and TANF

(working poor)

TANF and no employment

(TANF-dependent)

N

Parameter

estimate t-statistic

Parameter

estimate t-statistic

Parameter

estimate t-statistic

P

YYYY:Q of BYB, 1998:4 0.142 9.87 −0.042 −3.22 −0.036 −4.70 

YYYY:Q of BYB, 1999:1 0.120 8.44 −0.037 −2.84 −0.028 −3.65 

YYYY:Q of BYB, 1999:2 0.019 1.38 0.021 1.65 −0.021 −2.84 

YYYY:Q of BYB, 1999:3 0.019 1.55 0.025 2.19 −0.016 −2.34 

YYYY:Q of BYB, 1999:4 0.006 0.46 0.034 2.64 −0.003 −0.40 

YYYY:Q of BYB, 2000:1 0.005 0.35 0.013 1.10 −0.003 −0.44 

YYYY:Q of BYB, 2000:2 −0.014 −1.12 0.024 2.15 0.006 0.94 

YYYY:Q of BYB, 2000:3 −0.007 −0.66 0.029 2.88 0.004 0.73 

YYYY:Q of BYB, 2000:4 −0.028 −2.54 0.045 4.42 0.007 1.11 

YYYY:Q of BYB, 2001:1 −0.033 −3.29 0.026 2.76 0.006 1.17 

YYYY:Q of BYB, 2001:2 −0.039 −4.16 0.031 3.70 0.012 2.31 

YYYY:Q of BYB, 2001:3 −0.049 −5.69 0.014 1.77 0.013 2.75 

YYYY:Q of BYB, 2001:4 −0.036 −4.38 0.016 2.11 0.007 1.54 

YYYY:Q of BYB, 2002:1 −0.013 −1.48 −0.023 −2.88 0.007 1.53 

YYYY:Q of BYB, 2002:2 −0.011 −1.10 −0.034 −3.91 0.024 4.71 

YYYY:Q of BYB, 2002:3 −0.034 −3.13 −0.004 −0.38 0.028 4.88 

YYYY:Q of BYB, 2002:4 −0.031 −2.53 0.005 0.49 0.010 1.49 

YYYY:Q of BYB, 2003:1 −0.082 −5.02 0.005 0.33 0.014 1.58 

YYYY:Q of BYB, 2003:2 −0.083 −4.40 −0.009 −0.53 0.021 2.11 

YYYY:Q of BYB, 2003:3 −0.099 −4.66 −0.007 −0.38 0.028 2.50 

YYYY:Q of BYB, 2003:4 −0.102 −4.12 −0.021 −0.91 0.029 2.17 

YYYY:Q of BYB, 2004:1 −0.080 −2.60 −0.038 −1.36 0.016 0.94 

YYYY:Q of BYB, 2004:2 −0.195 −5.09 −0.024 −0.70 0.027 1.32 

YYYY:Q of BYB, 2004:3 −0.237 −4.47 −0.097 −2.02 0.070 2.47 

YYYY:Q of BYB, 2004:4 −0.362 −5.13 −0.082 −1.28 0.038 1.00 

YYYY:Q of BYB, 2005:1 −0.322 −2.74 −0.141 −1.32 −0.062 −0.98 

Observations 45,165 45,165 45,165 

R-squared 0.0626 0.1203 0.0250 

Adjusted R-squared 0.0609 0.1188 0.0233 

NOTE: BYB = benefit year beginning. BYE = benefit year ending.
156

Table A.24 Linear Probability Model of Return to Employment among All Newly Unemployed TANFLeavers, Using Pooled Data from Florida, Georgia, Michigan, and Ohioa

Independent variable

Model 1: all states Model 2: Ex-Floridab Model 3: ex-Floridab

Parameter

estimate t-statistic

Parameter

estimate t-statistic

Parameter

estimate t-statistic

Intercept 0.864 216.05 0.830 183.88 0.814 138.57

UI Nonbeneficiary applicant −0.036 −13.22 −0.023 −7.42 −0.026 −8.30

UI beneficiary 0.002 0.76 0.031 9.15 0.034 10.00

Age 24 or Less 0.051 40.34

 25–44 −0.023 −26.87

 45+ −0.123 −30.11

Race, white −0.022 −17.45

Race, black 0.015 18.92

Race, Hispanic −0.044 −6.69

Race, other −0.002 −0.17

Adults on case at exit −0.008 −4.70

Children (< 18) on case at exit 0.006 6.99

Base period earnings ($1,000) 0.002 6.21 0.002 5.65 0.003 9.44

High qtr. wages in base ($1,000) −0.001 −1.74 −0.001 −1.90 −0.002 −6.07

Base period earnings < $10,000 0.006 1.94 0.009 2.64 0.004 1.36

TANF payment before exit ($100) 0.001 2.10 0.001 2.89 0.000 1.02

Qtrs., TANF exit to new unemployment −0.043 −121.60 −0.041 −100.80 −0.041 −101.01

Qtrs. employed preexit (of 12) 0.011 42.57 0.012 42.72 0.013 44.03

Avg. qtr. earn., 3 yrs. preexit ($1,000) −0.008 −17.59 −0.007 −14.29 −0.004 −7.48

Multiple employers, exit to unempl. 0.071 37.83 0.070 33.29 0.062 29.60

Florida 0.032 14.86

Georgia −0.012 −9.95 −0.006 −5.14 −0.011 −8.45

Michigan 0.014 3.90 0.021 5.87 0.023 6.24

Ohio −0.004 −2.23 0.005 2.61 0.013 6.52

Unemployment rate at TANF exit 0.003 4.47

Unemployment rate ∆ exit to unempl. 0.000 0.36

Qtr. of TANF exit, 1st 0.009 5.45 0.008 3.99 0.006 3.28

Qtr. of TANF exit, 2nd 0.002 1.74 0.001 0.90 0.004 2.49

Qtr. of TANF exit, 3rd −0.003 −2.44 −0.003 −2.22 −0.005 −3.11

Qtr. of TANF exit, 4th −0.008 −5.00 −0.005 −2.74 −0.005 −2.75

Year of exit, 1996 0.086 30.85 0.082 29.30 0.088 30.53

Year of exit, 1997 0.101 39.66 0.101 39.89 0.106 40.86

Year of exit, 1998 0.058 22.06 0.068 22.66 0.069 22.95

Year of exit, 1999 0.003 1.46 0.001 0.31 −0.002 −0.49

Year of exit, 2000 −0.043 −27.03 −0.049 −24.88 −0.050 −24.98

Year of exit, 2001 −0.060 −32.00 −0.064 −34.05 −0.067 −34.44

Year of exit, 2002 −0.088 −11.28 −0.092 −11.62 −0.098 −12.31

Observations 221,940 182,715 182,669

R-squared 0.1035 0.0953 0.1084

Adjusted R-squared 0.1034 0.0952 0.1082

a

Excludes persons who returned to TANF prior to UI application or had interim employment prior to filing for UI.

b

Model 2 uses the same control variables as Model 1 to help assess whether differences between Model 1 and the final model 

(Model 3) are due to the exclusion of the Florida data or the additional right-side control variables. 
157

Table A.25 Linear Probability Model of Return to TANF among All Newly Unemployed TANF-Leavers, 

Using Pooled Data from Florida, Georgia, Michigan, and Ohioa

Independent variable

Model 1: all states Model 2: ex-Floridab Model 3: ex-Floridab

Parameter

estimate t-statistic

Parameter

estimate t-statistic

Parameter

estimate t-statistic

Intercept 0.392 83.39 0.389 73.27 0.406 59.40

Nonbeneficiary UI applicant 0.124 38.27 0.119 32.42 0.102 28.13

UI beneficiary 0.025 7.58 0.010 2.49 0.002 0.51

Age 24 or Less 0.054 37.14

 25–44 −0.032 −32.36

 45+ −0.046 −9.73

Race, white −0.061 −42.07

Race, black 0.040 43.63

Race, Hispanic −0.036 −4.68

Race, other −0.083 −6.84

Adults on case at exit −0.089 −43.84

Children (< 18) on case at exit 0.019 21.04

Base period earnings ($1,000) −0.006 −18.28 −0.006 −16.32 −0.005 −12.39

High qtr. wages in base ($1,000) 0.007 15.57 0.007 14.37 0.005 10.14

Base period earnings < $10,000 0.042 12.50 0.041 10.73 0.036 9.52

TANF payment before exit ($100) 0.005 15.21 0.005 15.66 0.004 10.58

Qtrs., TANF exit to new unemployment −0.021 −49.89 −0.021 −44.62 −0.023 −48.29

Qtrs. employed preexit (of 12) 0.004 12.51 0.005 15.09 0.005 14.71

Avg. qtr. earn., 3 yrs. preexit ($1,000) −0.009 −16.41 −0.007 −12.43 −0.003 −5.19

Multiple employers, exit to unempl. 0.036 16.34 0.038 15.42 0.032 13.09

Florida −0.059 −23.35

Georgia −0.007 −5.13 −0.012 −8.23 −0.016 −10.70

Michigan 0.040 9.70 0.025 6.07 0.007 1.70

Ohio 0.042 18.59 0.015 6.20 0.029 12.11

Unemployment rate at TANF exit 0.014 18.66

Unemployment rate ∆ exit to unempl. 0.007 7.26

Qtr. of TANF exit, 1st −0.019 −9.57 −0.010 −4.22 −0.018 −7.67

Qtr. of TANF exit, 2nd 0.001 0.44 0.000 0.18 0.007 3.93

Qtr. of TANF exit, 3rd 0.006 3.49 0.006 3.40 0.005 2.99

Qtr. of TANF exit, 4th 0.011 5.99 0.001 0.56 0.001 0.60

Year of exit, 1996 −0.101 −30.79 −0.100 −30.31 −0.106 −31.73

Year of exit, 1997 −0.118 −39.42 −0.120 −40.25 −0.129 −42.78

Year of exit, 1998 −0.052 −16.93 −0.076 −21.50 −0.090 −25.42

Year of exit, 1999 0.024 8.90 0.021 5.15 0.008 2.06

Year of exit, 2000 0.057 30.14 0.084 36.27 0.096 40.76

Year of exit, 2001 0.044 20.15 0.052 23.41 0.058 25.39

Year of exit, 2002 0.048 5.21 0.046 4.98 0.046 4.94

Observations 221,940 182,715 182,669

R-squared 0.0801 0.0832 0.1136

Adjusted R-squared 0.0800 0.0831 0.1135 a

Table excludes persons who returned to TANF prior to UI application or had interim employment prior to filing for UI. b

Model 2 uses the same control variables as Model 1 to help assess whether differences between Model 1 and the final model 

(Model 3) are due to the exclusion of the Florida data or the additional right-side control variables.
158

Table A.26 Linear Probability Model of Return to Employment without TANF (self-sufficiency) among All 

Newly Unemployed TANF-Leavers, Using Pooled Data from Florida, Georgia, Michigan, and 

Ohioa

Independent variable

Model 1: all states Model 2: ex-Floridab Model 3: ex-Floridab

Parameter

estimate t-statistic

Parameter

estimate t-statistic

Parameter

estimate t-statistic

Intercept 0.523 106.53 0.499 91.11 0.467 65.44

Nonbeneficiary UI applicant −0.132 −39.07 −0.119 −31.35 −0.107 −28.38

UI beneficiary −0.020 −5.94 0.012 2.86 0.019 4.65

Age 24 or Less −0.015 −10.01

 25–44 0.014 13.32

 45+ −0.041 −8.23

Race, white 0.036 23.30

Race, black −0.022 −23.02

Race, Hispanic −0.016 −1.97

Race, other 0.054 4.25

Adults on case at exit 0.070 33.28

Children (< 18) on case at exit −0.012 −12.31

Base period earnings ($1,000) 0.006 17.23 0.006 15.75 0.006 14.42

High qtr. wages in base ($1,000) −0.006 −13.08 −0.006 −12.45 −0.005 −11.08

Base period earnings < $10,000 −0.035 −9.90 −0.030 −7.59 −0.028 −7.19

TANF payment before exit ($100) −0.003 −10.43 −0.004 −10.47 −0.003 −7.68

Qtrs., TANF exit to new unemployment −0.014 −31.82 −0.011 −22.02 −0.010 −19.79

Qtrs. employed pre-TANF exit (of 12) 0.004 14.03 0.004 11.94 0.005 12.92

Avg. qtr. earn., 3 yrs. preexit ($1,000) 0.002 3.93 0.002 2.65 0.000 0.26

Multiple employers, exit to unempl. 0.017 7.55 0.014 5.31 0.014 5.51

Florida 0.066 24.87

Georgia −0.003 −2.09 0.003 2.32 0.004 2.32

Michigan −0.019 −4.34 −0.003 −0.60 0.014 3.21

Ohio −0.034 −14.45 −0.006 −2.42 −0.012 −4.86

Unemployment rate at TANF exit −0.009 −11.22

Unemployment rate ∆ exit to unempl. −0.004 −3.98

Qtr. of TANF exit, 1st 0.025 12.36 0.017 7.10 0.023 9.54

Qtr. of TANF exit, 2nd −0.000 −0.07 −0.001 −0.40 −0.005 −2.61

Qtr. of TANF exit, 3rd −0.008 −4.59 −0.008 −4.41 −0.008 −4.38

Qtr. of TANF exit, 4th −0.016 −8.16 −0.005 −2.25 −0.005 −2.48

Year of exit, 1996 0.151 44.01 0.145 42.84 0.155 44.47

Year of exit, 1997 0.181 58.22 0.183 59.61 0.194 61.77

Year of exit, 1998 0.088 27.50 0.117 32.16 0.130 35.28

Year of exit, 1999 −0.019 −6.76 −0.021 −5.11 −0.012 −2.87

Year of exit, 2000 −0.081 −41.41 −0.109 −45.25 −0.119 −48.45

Year of exit, 2001 −0.085 −36.80 −0.094 −41.16 −0.102 −42.93

Year of exit, 2002 −0.106 −11.02 −0.108 −11.21 −0.111 −11.49

Observations 221,940 182,715 182,669

R-squared 0.0693 0.0787 0.0898

Adjusted R-squared 0.0692 0.0786 0.0896 a

Table excludes persons who returned to TANF prior to UI application or had interim employment prior to filing for UI. b

Model 2 uses the same control variables as Model 1 to help assess whether differences between Model 1 and the final model 

(Model 3) are due to the exclusion of the Florida data or the additional right-side control variables.
159

Table A.27 Linear Probability Models of Return to Employment and TANF (i.e., working poor) among All 

Newly Unemployed TANF-Leavers, Based on Pooled Data from Florida, Georgia, Michigan, and 

Ohioa

Independent variable

Model 1: all states Model 2: ex-Floridab Model 3: ex-Floridab

Parameter

estimate t-statistic

Parameter

estimate t-statistic

Parameter

estimate t-statistic

Intercept 0.341 75.85 0.331 65.17 0.347 53.06

UI applicant but not a beneficiary 0.095 30.95 0.096 27.26 0.081 23.54

UI beneficiary 0.023 7.16 0.019 5.05 0.015 3.91

Age 24 or less 0.066 47.20

 25–44 −0.036 −38.71

 45+ −0.082 −18.07

Race, white −0.057 −41.14

Race, black 0.037 42.16

Race, Hispanic −0.028 −3.86

Race, other −0.056 −4.79

Adults on case at exit −0.079 −40.58

Children (< 18) on case at exit 0.017 19.73

Base period earnings ($1,000) −0.004 −13.30 −0.004 −11.98 −0.003 −7.27

High qtr. wages in base ($1,000) 0.005 12.75 0.005 11.75 0.003 6.66

Base period earnings < $10,000 0.040 12.55 0.038 10.55 0.033 9.07

TANF payment before exit ($100) 0.004 13.28 0.004 13.88 0.003 9.30

Qtrs. TANF exit to new unemployment −0.029 −73.45 −0.030 −65.89 −0.031 −69.18

Qtrs. employed pre-TANF exit (of 12) 0.007 22.55 0.008 25.10 0.008 25.46

Avg. qtr. earn., 3 yrs. preexit ($1,000) −0.011 −19.95 −0.009 −15.58 −0.004 −7.01

Multiple employers, exit to unempl. 0.054 25.41 0.057 23.88 0.048 20.59

Florida −0.034 −13.96

Georgia −0.009 −6.57 −0.010 −7.07 −0.014 −10.13

Michigan 0.033 8.22 0.023 5.86 0.009 2.10

Ohio 0.030 13.81 0.011 4.94 0.025 11.16

Unemployment rate at TANF exit 0.011 16.27

Unemployment rate ∆ exit to unempl. 0.004 4.67

Qtr. of TANF exit, 1st −0.016 −8.66 −0.009 −4.11 −0.016 −7.48

Qtr. of TANF exit, 2nd 0.003 1.63 0.002 1.24 0.008 5.09

Qtr. of TANF exit, 3rd 0.004 2.85 0.005 2.78 0.003 1.99

Qtr. of TANF exit, 4th 0.008 4.47 −0.000 −0.01 0.000 0.23

Year of exit, 1996 −0.065 −20.65 −0.064 −20.20 −0.068 −21.14

Year of exit, 1997 −0.081 −28.34 −0.082 −28.89 −0.088 −30.76

Year of exit, 1998 −0.031 −10.42 −0.049 −14.57 −0.060 −17.91

Year of exit, 1999 0.023 8.69 0.022 5.79 0.010 2.69

Year of exit, 2000 0.038 21.21 0.059 26.74 0.068 30.48

Year of exit, 2001 0.025 11.74 0.030 14.16 0.035 15.94

Year of exit, 2002 0.018 2.01 0.016 1.76 0.013 1.49

Observations 221,940 182,715 182,669

R-squared 0.0781 0.0792 0.1112

Adjusted R-squared 0.0780 0.0791 0.1111 a

Table excludes persons who returned to TANF prior to UI application or had interim employment prior to filing for UI. b

Model 2 uses the same control variables as Model 1 to help assess whether differences between Model 1 and the final model 

(Model 3) are due to the exclusion of the Florida data or the additional right-side control variables.
160

Table A.28 Linear Probability Model of Return to TANF and No Employment (i.e., TANF dependency) 

among All Newly Unemployed TANF-Leavers, Based on Pooled Data from Florida, Georgia, 

Michigan, and Ohioa

Independent variable

Model 1: all states Model 2: ex-Floridab Model 3: ex-Floridab

Parameter

estimate t-statistic

Parameter

estimate t-statistic

Parameter

estimate t-statistic

Intercept 0.052 21.09 0.058 20.54 0.060 16.10

UI applicant but not a beneficiary 0.028 16.75 0.023 11.92 0.020 10.42

UI beneficiary 0.002 1.43 −0.009 −4.39 −0.013 −5.95

Age 24 or less −0.012 −14.69

 25–44 0.005 8.53

 45+ 0.036 13.92

Race, white −0.004 −5.11

Race, black 0.003 6.21

Race, Hispanic −0.008 −1.83

Race, other −0.028 −4.18

Adults on case at exit −0.010 −9.37

Children (< 18) on case at exit 0.002 4.04

Base period earnings ($1,000) −0.002 −10.72 −0.002 −9.13 −0.002 −10.06

High qtr. wages in base ($1,000) 0.001 6.53 0.001 5.87 0.002 6.99

Base period earnings < $10,000 0.002 1.00 0.002 1.20 0.003 1.56

TANF payment before exit ($100) 0.001 4.87 0.001 4.48 0.001 3.13

Qtrs. TANF exit to new unemployment 0.008 38.83 0.009 34.50 0.008 32.90

Qtrs. employed pre-TANF exit (of 12) −0.003 −17.32 −0.003 −16.72 −0.003 −17.76

Avg. qtr. earn, 3 yrs. preexit ($1,000) 0.001 5.06 0.001 4.62 0.001 2.77

Multiple employers, exit to unempl. −0.018 −15.21 −0.018 −13.92 −0.016 −12.16

Florida −0.025 −19.25 . . . .

Georgia 0.002 2.19 −0.002 −2.76 −0.002 −1.88

Michigan 0.008 3.55 0.002 0.87 −0.001 −0.56

Ohio 0.012 10.38 0.003 2.78 0.003 2.66

Unemployment rate at TANF exit 0.002 5.75

Unemployment rate ∆ exit to unempl. 0.003 5.16

Qtr. of TANF exit, 1st −0.003 −2.51 −0.001 −0.54 −0.001 −0.98

Qtr. of TANF exit, 2nd −0.002 −2.14 −0.002 −1.87 −0.002 −1.72

Qtr. of TANF exit, 3rd 0.001 1.49 0.001 1.40 0.002 2.01

Qtr. of TANF exit, 4th 0.003 3.31 0.001 1.06 0.001 0.71

Year of exit, 1996 −0.036 −21.28 −0.036 −20.62 −0.039 −21.31

Year of exit, 1997 −0.037 −23.74 −0.038 −23.70 −0.040 −24.76

Year of exit, 1998 −0.021 −13.42 −0.027 −14.19 −0.029 −15.35

Year of exit, 1999 0.002 1.15 −0.002 −0.73 −0.002 −0.93

Year of exit, 2000 0.019 18.99 0.025 20.07 0.027 21.52

Year of exit, 2001 0.020 17.16 0.022 18.51 0.023 18.77

Year of exit, 2002 0.030 6.32 0.031 6.19 0.032 6.49

Observations 221,940 182,715 182,669

R-squared 0.0226 0.0231 0.0262

Adjusted R-squared 0.0225 0.0229 0.0261 a

Table excludes persons who returned to TANF prior to UI application or had interim employment prior to filing for UI. b

Model 2 uses the same control variables as Model 1 to help assess whether differences between Model 1 and the final model 

(Model 3) are due to the exclusion of the Florida data or the additional right-side control variables.
161

Table A.29 Linear Probability Model of Return to Neither Employment nor TANF (i.e., inactivity) among 

All Newly Unemployed TANF-Leavers, Based on Pooled Data from Florida, Georgia, Michigan,

and Ohioa

Independent variable

Model 1: all states Model 2: ex-Floridab Model 3: ex-Floridab

Parameter

estimate t-statistic

Parameter

estimate t-statistic

Parameter

estimate t-statistic

Intercept 0.085 23.86 0.112 28.25 0.127 24.49

UI applicant but not a beneficiary 0.008 3.32 −0.000 −0.06 0.005 1.97

UI beneficiary −0.005 −1.84 −0.022 −7.27 −0.021 −7.10

Age 24 or less −0.039 −35.33

 25–44 0.018 24.43

 45+ 0.087 24.25

Race, white 0.026 23.49

Race, black −0.018 −25.95

Race, Hispanic 0.051 8.92

Race, other 0.029 3.18

Adults on case at exit 0.018 12.05

Children (< 18) on case at exit −0.008 −10.84

Base period earnings ($1,000) 0.000 0.41 0.000 0.08 −0.001 −3.52

High qtr. wages in base ($1,000) −0.001 −2.55 −0.001 −2.02 0.001 1.89

Base period earnings < $10,000 −0.007 −2.88 −0.011 −3.85 −0.008 −2.66

TANF payment before exit ($100) −0.001 −5.74 −0.002 −6.48 −0.001 −3.40

Qtrs. TANF exit to new unemployment 0.035 110.24 0.032 89.99 0.033 91.24

Qtrs. employed preTANF exit (of 12) −0.008 −36.01 −0.009 −36.64 −0.009 −37.32

Avg. qtr. earn., 3 yrs. preexit ($1,000) 0.007 16.33 0.006 12.95 0.003 6.51

Multiple employers, exit to unempl. −0.054 −32.14 −0.052 −27.93 −0.046 −24.94

Florida −0.007 −3.45

Georgia 0.010 9.71 0.008 7.80 0.012 10.95

Michigan −0.021 −6.86 −0.022 −7.29 −0.022 −6.69

Ohio −0.008 −4.66 −0.009 −4.95 −0.017 −9.31

Unemployment rate at TANF exit −0.005 −9.20

Unemployment rate ∆ exit to unempl. −0.003 −4.11

Qtr. of TANF exit, 1st −0.006 −4.41 −0.007 −4.16 −0.005 −3.02

Qtr. of TANF exit, 2nd −0.001 −0.49 0.000 0.31 −0.002 −1.60

Qtr. of TANF exit, 3rd 0.002 1.73 0.002 1.53 0.003 2.09

Qtr. of TANF exit, 4th 0.005 3.35 0.004 2.36 0.004 2.62

Year of exit, 1996 −0.050 −20.07 −0.046 −18.61 −0.049 −19.43

Year of exit, 1997 −0.064 −28.31 −0.063 −28.46 −0.065 −28.71

Year of exit, 1998 −0.036 −15.60 −0.041 −15.65 −0.040 −15.08

Year of exit, 1999 −0.005 −2.45 0.001 0.17 0.004 1.23

Year of exit, 2000 0.025 17.34 0.024 13.98 0.023 12.99

Year of exit, 2001 0.040 24.21 0.042 25.52 0.044 25.70

Year of exit, 2002 0.058 8.35 0.061 8.80 0.065 9.34

Observations 221,940 182,715 182,669

R-squared 0.0848 0.0740 0.0874

Adjusted R-squared 0.0847 0.0739 0.0873 a

Table excludes persons who returned to TANF prior to UI application or had interim employment prior to filing for UI. b

Model 2 uses the same control variables as Model 1 to help assess whether differences between Model 1 and the final model 

(Model 3) are due to the exclusion of the Florida data or the additional right-side control variables.
162

Table A.30 Service Participation among TANF-Leavers in Georgiaa

Service description

TANF-leaver

(N = 152,278)

Newly unemployed

(N = 123,424)

Nonapplicants

(N = 96,254)

UI applicants

(N = 27,166)

UI beneficiarie

(N = 13,335)

n Rate n Rate n Rate n Rate n Rate 

Resume workshop 33 0.000 71 0.001 10 0.000 80 0.004 69 0.0

Other workshop 294 0.002 428 0.004 94 0.001 409 0.021 342 0.0

Stress/finance workshopb 5 0.000 13 0.001 1 0.000 13 0.007 12 0.0

Orientation 1,456 0.010 3,241 0.026 247 0.003 3,881 0.143 3,485 0.2

Orientation w/workshopb 199 0.010 1,379 0.047 176 0.008 1,285 0.161 1,108 0.2

Serv. needs evaluationb 6,532 0.047 6,841 0.070 2,568 0.033 5,380 0.271 3,576 0.3

Serv. needs evaluationb 1,211 0.062 3,599 0.123 1,045 0.049 2,627 0.330 1,797 0.4

Test (proficiency) 132 0.001 98 0.001 48 0.000 68 0.003 39 0.0

Test (CAPS) 19 0.000 22 0.000 7 0.000 12 0.000 11 0.0

Test (NATB) 7 0.000 4 0.000 1 0.000 2 0.000 1 0.0

Test (ABLE) 0 0.000 4 0.000 2 0.000 2 0.000 1 0.0

Test (USES interest) 4 0.000 5 0.000 1 0.000 6 0.000 4 0.0

Test (other) 95 0.001 92 0.001 30 0.000 66 0.002 44 0.0

Job search workshopb 3,271 0.024 4,152 0.043 1,278 0.016 3,635 0.183 2,715 0.2

 Re-place yourself 82 0.003 414 0.012 42 0.002 394 0.042 347 0.0

 Financial/stress 184 0.006 469 0.013 99 0.004 363 0.039 312 0.0

 Resume 37 0.001 237 0.007 26 0.001 217 0.023 204 0.0

 Internet 19 0.001 91 0.003 13 0.000 81 0.009 73 0.0

 Interviewing 44 0.001 253 0.007 33 0.001 212 0.023 194 0.0

 Retention 9 0.000 49 0.001 12 0.000 35 0.004 25 0.0

 Applications 37 0.001 189 0.005 37 0.001 156 0.017 134 0.0

 Networking 16 0.001 165 0.005 19 0.001 147 0.016 139 0.0

 Other 262 0.009 844 0.023 272 0.010 542 0.058 357 0.0

 Orientation 202 0.007 1,380 0.038 177 0.007 1,289 0.139 1,112 0.2

Job finding club 61 0.000 106 0.001 35 0.000 61 0.002 27 0.0

Job search planning 6,032 0.040 8,730 0.071 2,630 0.027 6,960 0.256 4,199 0.3

Order search LO CTAC 17,035 0.112 18,735 0.152 6,858 0.071 13,701 0.504 7,069 0.5

Order search no LO CTAC 1,953 0.014 1,679 0.017 725 0.009 1,149 0.058 731 0.0

Resume preparation 1,222 0.008 1,819 0.015 633 0.007 1,330 0.049 818 0.0

LMI 12,917 0.085 17,080 0.138 5,869 0.061 13,151 0.484 6,756 0.5

Call-in job order 3,754 0.025 3,477 0.028 1,450 0.015 2,317 0.085 1,341 0.1
Table A.30 (Continued)

163

Service description

TANF-leaver

(N = 152,278)

Newly unemployed

(N = 123,424)

Nonapplicants

(N = 96,254)

UI applicants

(N = 27,166)

UI beneficiarie

(N = 13,335)

n Rate n Rate n Rate n Rate n Rate 

O*NET interest profilerb 11 0.003 4 0.001 6 0.004 4 0.0

O*NET work importance 2 0.000 0 0.000 1 0.001 0 0.0

O*NET ability profiler 0 0.000 0 0.000 0 0.000 0 0.0

Job referral long term 23,000 0.151 20,014 0.162 10,030 0.104 10,855 0.400 5,514 0.4

Job referral medium term 4,571 0.030 4,195 0.034 1,941 0.020 2,404 0.088 1,268 0.0

Job referral short term 470 0.003 554 0.004 249 0.003 304 0.011 161 0.0

Supportive service referral 859 0.006 986 0.008 363 0.004 718 0.026 448 0.0

Job development 3,292 0.022 3,293 0.027 1,431 0.015 2,058 0.076 1,138 0.0

Job search assistance (ES) 5,295 0.035 5,885 0.048 1,866 0.019 4,340 0.160 2,528 0.1

Job search assistance (VET) 22 0.000 61 0.000 19 0.000 35 0.001 20 0.0

Career/vocational guidance 262 0.002 248 0.002 101 0.001 160 0.006 97 0.0

Bonding assistance 62 0.000 76 0.001 31 0.000 53 0.002 28 0.0

Assigned case manager 26 0.000 30 0.000 14 0.000 19 0.001 9 0.0

Orientation 0 0.000 0 0.000 0 0.000 0 0.000 0 0.0

REU/profiled 1,534 0.010 3,661 0.030 51 0.001 4,709 0.173 4,085 0.3

Individual counseling 6,313 0.041 6,779 0.055 2,451 0.025 5,368 0.198 3,677 0.2

Group counseling 738 0.005 1,522 0.012 262 0.003 1,672 0.062 1,497 0.1

Customer service plan 5,777 0.038 6,483 0.053 2,273 0.024 5,217 0.192 3,615 0.2

In-depth assessmentb 40 0.002 61 0.002 33 0.002 32 0.004 14 0.0

Service coordination 53 0.000 92 0.001 48 0.000 45 0.002 19 0.0

Expanded workshopb 2,100 0.022 2,542 0.024 1,279 0.016 1,264 0.054 455 0.0

WIA registrationb 167 0.001 287 0.002 125 0.001 168 0.006 115 0.0

WIA service assignmentb 234 0.002 338 0.003 155 0.002 181 0.007 118 0.0

WIA registration exitb 133 0.004 75 0.002 44 0.002 26 0.003 16 0.0

Referred to training 589 0.004 1,081 0.009 311 0.003 866 0.032 616 0.0

Placed in training 16 0.000 8 0.000 4 0.000 3 0.000 2 0.0

Successful training exit 3 0.000 3 0.000 3 0.000 0 0.000 0 0.0

Initial ERP 1,482 0.010 3,868 0.031 164 0.002 4,685 0.172 4,354 0.3

2nd ERP 760 0.005 2,677 0.022 172 0.002 3,187 0.117 3,060 0.2

3rd ERP 483 0.003 2,113 0.017 158 0.002 2,415 0.089 2,365 0.1
Table A.30 (Continued)

164

Service description

TANF-leaver

(N = 152,278)

Newly unemployed

(N = 123,424)

Nonapplicants

(N = 96,254)

UI applicants

(N = 27,166)

UI beneficiarie

(N = 13,335)

n Rate n Rate n Rate n Rate n Rate 

4th ERP 262 0.002 1,310 0.011 116 0.001 1,269 0.047 1,258 0.0

17-week contact 134 0.001 624 0.005 71 0.001 456 0.017 454 0.0

Internet registrationb 7 0.000 2 0.000 1 0.000 2 0.000 1 0.0

NOTE: blank cells = data not applicable. a

Participation in employment services is counted relative to a reference date. Reference date definitions differ depending on the participant group. 

reference date is the quarter of TANF exit. For TANF-leavers who become newly unemployed and those who do not apply for UI benefits, the refere

first occurrence of unemployment subsequent to TANF exit. For UI applicants, the reference date is the quarter in which the Benefit Year Begin (BY

participation is counted if there is a record of participation between the full calendar quarter prior to a reference date and one full calendar quarter afte

time frame three calendar quarters long. b

The sample size upon which the participation rate is calculated for this service is smaller than shown for the category, because service data for the c

throughout the entire interval in which TANF exit, new unemployment, and UI application are observed.
165

Table A.31 Service Participation Among TANF-Leavers in Ohioa

Service description

TANF-leaver

(N = 82,860)

Newly 

unemployed

(N = 62,200)

Nonapplicants

(N = 51,084)

UI applicants

(N = 11,101)

UI beneficiar

(N = 3,336

N Rate N Rate N Rate N Rate Actual R

Assessment interview 456 0.006 405 0.007 241 0.005 154 0.014 68 0

Employability development/plan 35 0.000 22 0.000 10 0.000 11 0.001 4 0

Career guidance 119 0.001 95 0.002 51 0.001 40 0.004 14 0

Assigned case mgmt. (veterans) 3 0.000 5 0.000 3 0.000 2 0.000 1 0

Received case mgmt. (veterans) 21 0.000 19 0.000 11 0.000 7 0.001 3 0

Assigned/received case mgmt. (veterans) 19 0.000 11 0.000 9 0.000 3 0.000 1 0

Released, case mgmt. (veteransb) 0 — 0 0.000 0 0.000 0 0.000 0 0

Federal bondingb 0 — 0 0.000 0 0.000 0 0.000 0 0

Job development contact 158 0.002 114 0.002 70 0.001 49 0.004 15 0

Job finding club 8 0.000 5 0.000 3 0.000 2 0.000 2 0

Job search planning 1,835 0.022 2,424 0.039 867 0.017 1,673 0.151 512 0

Job search workshop 157 0.002 166 0.003 92 0.002 64 0.006 32 0

Provision of specific LMI info 3,952 0.048 3,358 0.054 1,775 0.035 1,636 0.147 527 0

Resume assistance 459 0.006 392 0.006 224 0.004 154 0.014 70 0

Job seeker match 7,513 0.091 8,469 0.136 3,916 0.077 5,047 0.455 1,485 0

Matched but not referred 824 0.010 586 0.009 376 0.007 199 0.018 95 0

DVOP/LVERc 1,763 0.021 1,656 0.027 877 0.017 807 0.073 287 0

DVOP/LVER follow-upc 113 0.001 109 0.002 57 0.001 48 0.004 23 0

Placed, federal training 4 0.000 5 0.000 5 0.000 0 0.000 0 0

Placed, other federal training 1 0.000 2 0.000 0 0.000 0 0.000 0 0

Placed, other state/local trainingb 0 — 0 0.000 0 0.000 0 0.000 0 0

Reemployment serviceb 0 — 3 0.001 0 0.000 3 0.003 2 0

Referral deletedb 0 — 0 0.000 0 0.000 0 0.000 0 0

Referral to other federal training 17 0.000 18 0.000 9 0.000 10 0.001 8 0

Referral to other state/local training 63 0.001 60 0.001 24 0.000 32 0.003 18 0

Referral to educational services 62 0.001 88 0.001 56 0.001 31 0.003 13 0

Placement 1,913 0.023 1,366 0.022 1,001 0.020 370 0.033 112 0

Referral

 Verification requested 1,224 0.015 722 0.012 457 0.009 235 0.022 98 0

 WIA services 25 0.000 35 0.001 24 0.000 15 0.001 10 0

 Child careb 0 — 0 0.000 0 0.000 0 0.000 0 0

 Emergency financial servicesb 0 — 0 0.000 0 0.000 0 0.000 0 0

 Health and medical servicesb 0 — 0 0.000 0 0.000 0 0.000 0 0

 Legal servicesb 0 — 0 0.000 0 0.000 0 0.000 0 0

 Relocation assistanceb 0 — 0 0.000 0 0.000 0 0.000 0 0
Table A.31 (Continued)

16

6

Service description

TANF-leaver

(N = 82,860)

Newly 

unemployed

(N = 62,200)

Nonapplicants

(N = 51,084)

UI applicants

(N = 11,101)

UI beneficiar

(N = 3,336

N Rate N Rate N Rate N Rate Actual R

 Residential supportb 0 — 0 0.000 0 0.000 0 0.000 0 0

 Veteran supportive servicesb 0 — 2 0.001 1 0.001 1 0.001 1 0

 Other supportive service 409 0.005 374 0.006 222 0.004 162 0.015 67 0

Job referral 5,731 0.069 3,770 0.061 2,531 0.050 1,221 0.110 463 0

Federal trainingb 0 — 0 0.000 0 0.000 0 0.000 0 0

Status change (from/to) 13,474 0.163 12,848 0.207 7,359 0.144 6,003 0.541 1,736 0

Tax credit eligibility determinationb 0 — 0 0.000 0 0.000 0 0.000 0 0

Testing 13 0.000 6 0.000 6 0.000 0 0.000 0 0

Terminated, federal trainingb 0 — 0 0.000 0 0.000 0 0.000 0 0

Terminated, other federal training 1 0.000 0 0.000 0 0.000 1 0.000 0 0

Terminated, other state/local training 1 0.000 0 0.000 0 0.000 0 0.000 0 0

Updated registration 8,636 0.104 10,153 0.163 5,034 0.099 5,595 0.504 2,007 0

Registration 3,541 0.043 4,148 0.067 1,745 0.034 2,649 0.239 720 0

Obtained employment 2,028 0.024 1,901 0.031 1,203 0.024 378 0.034 139 0

Initial assessmentb 0 — 164 0.019 121 0.020 44 0.017 11 0

One-Stopb

 Other services 0 — 2 0.001 1 0.001 3 0.003 1 0

 Career counsel 0 — 0 0.000 0 0.000 0 0.000 0 0

 Core service—WIA 0 — 0 0.000 0 0.000 0 0.000 0 0

 Vocational guidance services 0 — 0 0.000 0 0.000 0 0.000 0 0

 Employment planning 0 — 0 0.000 0 0.000 0 0.000 0 0

 Initial assessment 0 — 0 0.000 0 0.000 0 0.000 0 0

 Skills assessment 0 — 0 0.000 0 0.000 0 0.000 0 0

 Job hunter workshop 0 — 0 0.000 0 0.000 0 0.000 0 0

 Testing 0 — 0 0.000 0 0.000 0 0.000 0 0

 Refer to other services 0 — 1 0.000 1 0.001 0 0.000 0 0

Referralb

 WIA adult 0 — 0 0.000 0 0.000 0 0.000 0 0

 WIA youth 0 — 0 0.000 0 0.000 0 0.000 0 0

 Labor exchange, Wagner-Peyser 0 — 0 0.000 0 0.000 0 0.000 0 0

 WIA adult education 0 — 0 0.000 0 0.000 0 0.000 0 0

 WIA VOC rehab 0 — 0 0.000 0 0.000 0 0.000 0 0

 Older Americans 0 — 0 0.000 0 0.000 0 0.000 0 0

 Welfare-to-work 0 — 0 0.000 0 0.000 0 0.000 0 0

 TAA or NAFTA-TAA 0 — 0 0.000 0 0.000 0 0.000 0 0

 Veterans E/T programs 0 — 0 0.000 0 0.000 0 0.000 0 0

 Community Service Block Grant 0 — 0 0.000 0 0.000 0 0.000 0 0
Table A.31 (Continued)

167

Service description

TANF-leaver

(N = 82,860)

Newly 

unemployed

(N = 62,200)

Nonapplicants

(N = 51,084)

UI applicants

(N = 11,101)

UI beneficiar

(N = 3,336

N Rate N Rate N Rate N Rate Actual R

 HUD E/T programs 0 — 0 0.000 0 0.000 0 0.000 0 0

 Unemployment insurance 0 — 0 0.000 0 0.000 0 0.000 0 0

 TANF program 0 — 0 0.000 0 0.000 0 0.000 0 0

 Job Corps. 0 — 0 0.000 0 0.000 0 0.000 0 0

 CCC 0 — 0 0.000 0 0.000 0 0.000 0 0

 MSFW 0 — 0 0.000 0 0.000 0 0.000 0 0

 Other federal/state/local program 0 — 0 0.000 0 0.000 0 0.000 0 0

Access to LMIb 0 0.000 0 0.000 0 0.000 1 0.000 1 0

Assistance with WTW eligibility/aidb 0 — 0 0.000 0 0.000 0 0.000 0 0

ETP performance infob 0 — 0 0.000 0 0.000 0 0.000 0 0

Info on supportive servicesb 0 0.000 0 0.000 0 0.000 1 0.000 1 0

Local area performance infob 0 — 0 0.000 0 0.000 0 0.000 0 0

Info on unemploymentb 0 — 0 0.000 0 0.000 1 0.001 1 0

Initial assessment 0 0.000 3 0.000 2 0.000 1 0.000 1 0

WIA eligibility 0 0.000 4 0.000 3 0.000 1 0.000 1 0

Outreach, intake, and orientation 0 0.000 5 0.000 4 0.000 1 0.000 1 0

One-Stop registrationb 0 — 0 0.000 0 0.000 1 0.002 0 0

One-Stop resource roomb 0 — 3 0.002 1 0.001 2 0.004 0 0

Case mgmt. transfer (veterans)b 0 — 0 0.000 0 0.000 0 0.000 0 0

Chg. case manager (veterans)b 0 — 0 0.000 0 0.000 0 0.000 0 0

Training interrupted (veterans)b 0 — 0 0.000 0 0.000 0 0.000 0 0

Career/resource center servicesb 0 — 0 0.000 0 0.000 0 0.000 0 0

Internet search instructionb 0 — 0 0.000 0 0.000 0 0.000 0 0

UC claimant status changeb 0 — 3 0.002 0 0.000 20 0.042 6 0

Completed OTAPb 0 — 0 0.000 0 0.000 0 0.000 0 0

NOTE: — = data not available a

TANF-leavers are defined as having participated in a given service if the data show a record of participation in the full calendar quarter prior to a re

full calendar quarter after that reference point. For TANF-leavers, the reference date is the quarter of TANF exit. For TANF-leavers who become ne

newly unemployed who do not apply for UI benefits, the reference point is the quarter of the first occurrence of new unemployment subsequent to TA

the reference date is the quarter in which the Benefit Year Begin (BYB) date occurs. b

Sample size upon which the participation rate is calculated for this service (or service category, such as One-Stop or Referral) is smaller than show

because of service data not being available throughout the entire interval in which TANF exit, new unemployment, or UI application are observed. c

DVOP: Disabled Veterans Outreach Program; LVER: Local Veterans Employment Representative.
168

Table A.32 Models of Return to Employment and TANF, Introducing Employment Services Participation as 

Explanatory Variablesa

Independent variables

Return to employment Return to TANF

Parameter

estimate t-statistic

Parameter

estimate t-statistic

Intercept 0.886 97.08 0.342 32.87

UI beneficiary 0.014 2.39 −0.011 −1.69

Nonbeneficiary UI applicant −0.083 −16.25 0.081 13.84

Assessment, service needs evaluation 0.026 2.42 0.138 11.38

Job search assistance 0.023 3.10 0.049 5.82

Job referral 0.065 14.14 0.061 11.63

Individual counseling 0.017 1.40 0.062 4.48

Customer service plan −0.020 −1.50 −0.010 −0.70

Expanded workshop 0.038 3.20 0.311 22.95

Assessment × UI nonbeneficiary 0.002 0.12 −0.056 −2.78

Job search assistance × UI nonbeneficiary 0.008 0.73 0.009 0.74

Job referral × UI nonbeneficiary 0.042 4.76 −0.029 −2.85

Individual counseling × UI nonbeneficiary 0.006 0.28 −0.041 −1.69

Customer service plan × UI nonbeneficiary −0.016 −0.70 0.024 0.92

Expanded workshop × UI nonbeneficiary −0.003 −0.15 −0.022 −0.93

Assessment × UI beneficiary −0.037 −2.36 −0.120 −6.79

Job search assistance × UI beneficiary −0.024 −2.21 −0.041 −3.26

Job referral × UI beneficiary −0.016 −1.75 −0.026 −2.53

Individual counseling × UI beneficiary 0.013 0.50 −0.064 −2.15

Customer service plan × UI beneficiary −0.013 −0.49 0.052 1.71

Expanded workshop × UI beneficiary −0.021 −0.87 0.010 0.38

Age 24 or Less 0.044 27.17 0.053 29.14

 25–44 −0.015 −15.06 −0.032 −27.74

 45 or older −0.114 −24.66 −0.008 −1.46

Race, white −0.029 −13.22 −0.059 −23.74

Race, black 0.012 13.62 0.025 24.96

Race, Hispanic −0.043 −3.94 −0.073 −5.92

Race, other 0.017 1.08 −0.063 −3.62

Adults on case at exit −0.006 −2.62 −0.071 −27.48

Children < age 18 on case at exit 0.004 4.15 0.021 18.95

Qtrs., TANF exit to new unemployment −0.037 −71.28 −0.020 −33.04

Qtrs. of employment before TANF exit (of 12) 0.010 27.78 0.002 4.31

Avg. qtrly. earnings, 3 yrs. before exit −0.002 −4.51 −0.001 −1.21

Multiple employers in any qtr. before unempl. 0.051 18.70 0.018 5.86

Base period earnings ($1,000) 0.005 12.30 −0.003 −7.22

High quarter earnings in base ($1,000) −0.004 −9.70 0.003 5.91

Base period earnings < $10,0000 −0.000 −0.02 0.043 9.54
Table A. 32 (Continued)

169

Independent variables

Return to employment Return to TANF

Parameter

estimate t-statistic

Parameter

estimate t-statistic

Amount of last TANF payment 0.000 0.66 0.005 10.64

On multiple cases at exit 0.096 1.75 0.196 3.13

Ind. (NAICS): agriculture, forestry, fishing 0.019 1.35 0.010 0.62

Ind. (NAICS): mining −0.097 −1.34 0.102 1.24

Ind. (NAICS): utilities −0.020 −0.43 −0.074 −1.41

Ind. (NAICS): construction −0.023 −2.90 −0.001 −0.14

Ind. (NAICS): manufacturing −0.008 −2.35 0.022 6.04

Ind. (NAICS): wholesale trade −0.007 −1.04 0.009 1.15

Ind. (NAICS): retail trade 0.000 0.07 −0.004 −1.43

Ind. (NAICS): transportation, warehousing −0.001 −0.15 −0.017 −1.89

Ind. (NAICS): information −0.023 −2.52 −0.023 −2.25

Ind. (NAICS): finance and insurance −0.025 −2.80 −0.063 −6.13

Ind. (NAICS): real estate, rental, leasing 0.003 0.26 −0.023 −1.92

Ind. (NAICS): professional, scientific, technical −0.027 −2.52 −0.061 −5.04

Ind. (NAICS): company/enterprise management −0.037 −0.59 −0.026 −0.35

Ind. (NAICS): admin., support and waste mgmt. −0.013 −4.82 −0.001 −0.33

Ind. (NAICS): educational services 0.053 8.90 −0.059 −8.72

Ind. (NAICS): health care/social assistance 0.011 3.69 −0.022 −6.54

Ind. (NAICS): art, entertainment, recreation 0.015 0.93 −0.028 −1.48

Ind. (NAICS): accommodation and food services 0.008 3.54 0.033 12.73

Ind. (NAICS): other services (except publ. admin.) −0.013 −1.94 −0.016 −2.17

Ind. (NAICS): public administration −0.011 −1.64 −0.025 −3.15

Ind. (NAICS): unclassifiable 0.061 2.72 −0.057 −2.23

Unemployment rate at TANF exit −0.007 −5.36 0.002 1.39

Chg. in unempl. rate, exit-to-new unempl. −0.010 −8.80 0.004 3.26

Observations 112,825

R-squared 0.1124

Adjusted R-squared 0.1105 a

Models also include a complete set of indicator variables for year and quarter of TANF exit for employment and county of 

residence.
170

Table A.33 Models of Return to Employment and TANF among Newly Unemployed TANF-Leavers in Ohio,

Introducing Employment Services Participation as Explanatory Variables

Independent variables

Return to employment Return to TANF

Parameter

estimate

Standard

error t-statistic

Parameter

estimate

Standard

error t-statistic

Intercept 0.971 0.013 74.89 0.677 0.015 45.91

Job search planning −0.005 0.016 −0.31 −0.032 0.018 −1.78

Job seeker match 0.051 0.009 5.81 0.068 0.010 6.84

Veterans (DVOP/LVER) −0.005 0.016 −0.31 0.003 0.018 0.19

Placement 0.009 0.016 0.56 0.007 0.019 0.36

Referral 0.057 0.012 4.99 0.026 0.013 1.96

Job search planning × UI beneficiary −0.011 0.029 −0.39 0.054 0.033 1.65

Job seeker match × UI beneficiary −0.019 0.021 −0.93 −0.036 0.024 −1.50

Veterans (DVOP/LVER) × UI beneficiary 0.015 0.033 0.45 −0.035 0.037 −0.93

Placement × UI beneficiary 0.021 0.053 0.40 −0.098 0.060 −1.64

Referral × UI beneficiary 0.026 0.029 0.90 0.053 0.033 1.60

Job search planning × UI nonbeneficiary 0.011 0.023 0.51 0.004 0.026 0.15

Job seeker match × UI nonbeneficiary −0.012 0.015 −0.77 −0.013 0.017 −0.74

Veterans (DVOP/LVER) × UI nonbenef. 0.031 0.027 1.16 −0.007 0.030 −0.23

Placement × UI nonbeneficiary −0.001 0.040 −0.04 0.041 0.045 0.92

Referral × UI nonbeneficiary −0.011 0.025 −0.47 0.007 0.028 0.23

UI beneficiary 0.067 0.011 5.98 −0.077 0.013 −6.01

UI applicant but not a beneficiary −0.013 0.008 −1.65 0.017 0.009 1.87

Age 18–24 0.047 0.003 17.19 0.057 0.003 18.45

 25–44 −0.026 0.002 −12.93 −0.038 0.002 −16.87

 45+ −0.144 0.009 −15.73 −0.075 0.010 −7.16

Gender, male −0.018 0.005 −3.80 −0.114 0.005 −21.31

Gender, female 0.004 0.001 3.80 0.024 0.001 21.31

Race, white −0.010 0.002 −4.69 −0.040 0.002 −16.81

Race, black 0.015 0.002 6.40 0.045 0.003 17.49

Race, Hispanic −0.055 0.010 −5.69 0.001 0.011 0.10

Race, other −0.005 0.017 −0.32 −0.061 0.019 −3.18

Education, less than high school 0.006 0.002 3.79 0.019 0.002 10.21

Education, high school graduate/GED −0.007 0.002 −3.21 −0.023 0.003 −8.96

Education, some college −0.015 0.009 −1.66 −0.036 0.010 −3.47

Education, bachelor’s degree or higher −0.034 0.030 −1.13 −0.113 0.034 −3.30

Base period earnings ($1,000) 0.001 0.000 1.54 −0.002 0.001 −3.46

Base period earnings less than $10,000 0.010 0.007 1.56 0.004 0.007 0.50

Employed 4 qtrs. or less before unempl. −0.143 0.004 −33.60 −0.050 0.005 −10.30

5–8 qtrs. −0.010 0.003 −3.97 −0.013 0.003 −4.45

9–12 qtrs. 0.055 0.002 27.05 0.025 0.002 10.90

Quarters from exit to new unemployment −0.047 0.001 −64.94 −0.031 0.001 −37.82

Employment (1,000) at TANF exit −0.000 0.000 −0.98 −0.000 0.000 −19.82
Table A.33 (Continued)

171

Independent variables

Return to employment Return to TANF

Parameter

estimate

Standard

error t-statistic

Parameter

estimate

Standard

error t-statistic

Total eligible adults at last payment −0.020 0.004 −5.08 −0.089 0.005 −19.79

Total eligible children (6–17) at last pmt. 0.004 0.002 2.62 0.005 0.002 2.67

Total eligible children < 6 at last pmt. 0.012 0.002 5.31 0.013 0.003 4.78

Exempt, caring for child under age 1 −0.001 0.008 −0.16 −0.010 0.009 −1.11

Has access to motor vehicle −0.007 0.004 −1.81 −0.015 0.005 −3.13

Person is AG payee −0.031 0.007 −4.60 −0.036 0.008 −4.65

Person is parent of minor child in AG −0.029 0.007 −4.14 0.160 0.008 19.95

Marital status, single 0.008 0.001 6.00 0.005 0.002 3.40

Marital status, married −0.020 0.005 −4.09 0.014 0.005 2.55

Marital status, divorced/abandoned −0.023 0.006 −3.66 −0.037 0.007 −5.17

Marital status, separated −0.011 0.006 −1.91 −0.030 0.006 −4.63

Marital status, widow/widower −0.076 0.034 −2.22 −0.078 0.039 −2.01

Appalachian area county −0.020 0.005 −3.66 −0.048 0.006 −7.79

Metropolitan area county 0.002 0.002 0.79 0.036 0.002 15.83

Other area county 0.007 0.004 1.73 −0.072 0.005 −16.00

YYYYQ of TANF exit, 2000:2 0.015 0.004 4.24 0.042 0.004 10.10

YYYYQ of TANF exit, 2000:3 0.005 0.003 1.40 0.041 0.004 10.38

YYYYQ of TANF exit, 2000:4 −0.006 0.004 −1.79 −0.018 0.004 −4.30

YYYYQ of TANF exit, 2001:1 −0.018 0.004 −4.62 −0.060 0.004 −13.47

YYYYQ of TANF exit, 2001:2 0.003 0.004 0.72 −0.004 0.005 −0.82

YYYYQ of TANF exit, 2001:3 −0.001 0.004 −0.14 −0.016 0.005 −3.18

Observations 59,914 59,914

R-squared 0.1057 0.1057

Adjusted R-squared 0.1050 0.1050
172

Table A.34 Models of Services Impacts on Total Income and Its Components among Newly Unemployed 

TANF-Leavers in Georgia

Independent variables

Parameter estimatesa

Total

income

Earnings from

employment

TANF

income

UI

compensationb

Intercept 3,743.65** 3,436.07** 359.41** −1,899.40**

UI beneficiary 15.94 −1,454.95** −115.60** —

Nonbeneficiary UI applicant −2,514.95** −2,721.18** 222.97** —

Assessment, service needs evaluation 231.47 −59.63 302.50** 121.07**

Job search assistance 63.49 −63.91 131.66** 354.74**

Job referral 230.96** 120.35 80.60** 115.27**

Individual counseling −130.85 −267.94 131.35** 26.19

Customer service plan −523.31* −569.00** 27.55 117.85

Expanded workshop 334.13 −632.70** 967.42** −100.98

Assessment × UI nonbeneficiary −106.41 3.43 −97.09* —

Job search assistance × UI nonbeneficiary 55.70 17.32 31.02 —

Job referral × UI nonbeneficiary 966.36** 1,051.08** −76.31** —

Individual counseling × UI nonbeneficiary −417.79 −276.91 −141.97** —

Customer service plan × UI nonbeneficiary 977.77** 925.21* 25.06 —

Expanded workshop × UI nonbeneficiary 177.31 557.26 −368.39** —

Assessment × UI beneficiary −368.33 −803.01** −310.19** —

Job search assistance × UI beneficiary −486.81** −779.60** −127.73** —

Job referral × UI beneficiary 53.55 231.75 −59.58** —

Individual counseling × UI beneficiary 255.87 569.36 −117.56 —

Customer service plan × UI beneficiary −158.86 0.15 85.41 —

Expanded workshop × UI beneficiary 686.51 1,535.81** −373.16** —

Age 24 or less 29.47 -66.76** 98.86** −98.17**

 25–44 41.11* 102.33** −60.49** 16.22**

 45 or older −612.43** −632.95** −3.76 180.29**

Race, white −395.62** −270.59** −129.91** −13.09

Race, black 154.21** 99.92** 55.92** 4.80

Race, Hispanic −89.72 64.43 −142.88** 61.84

Race, other 1,082.67** 1,225.10** −118.61** −284.58*

Adults on case at exit −62.83 89.76* −152.94** −34.33

Children < age 18 on case at exit 31.23 −58.65** 92.22** −17.26*

Qtrs., TANF exit to new unemployment −152.82** −132.49** −14.00** 12.90*

Qtrs. of employment before TANF exit (of 12) 143.30** 145.47** 2.35** −4.02

Avg. qtrly. earnings, 3 yrs. before exit 95.11** 97.19** −1.85 −13.06

Multiple employers in any qtr. before unempl. 128.72** 112.68* 28.26** −139.32**

Weekly benefit amountb — — — 14.47**

UI entitlement (weeks)b — — — 58.53**

Base period earnings ($1,000)c 572.03** 557.27** −5.58** 43.92**

High quarter earnings in base ($1,000)c −568.98** −554.06** 4.82** −42.77**

Base period earnings < $10,0000c −178.05** −235.74** 102.67** 126.14**

Amount of last TANF payment 38.74** 19.07** 19.54** −6.50

On multiple cases at exit 2,578.00** 1,843.30 828.15** −526.77

Ind. (NAICS): agriculture, forestry, fishing −292.07 −296.33 18.96 184.62

Ind. (NAICS): mining 80.73 −315.55 329.65 910.67

Ind. (NAICS): utilities 3,418.52** 3,579.63** −159.52 290.05

Ind. (NAICS): construction −82.31 −115.49 2.02 7.93

Ind. (NAICS): manufacturing 158.32** 97.66 75.89** −168.56**
Table A.34 (Continued)

173

Independent variables

Parameter estimatesa

Total

income

Earnings from

employment

TANF

income

UI

compensationb

Ind. (NAICS): wholesale trade 0.22 −2.85 −1.95 35.54

Ind. (NAICS): retail trade −109.39** −100.18* −7.49 81.96**

Ind. (NAICS): transportation, warehousing 481.08** 516.30** −29.10 0.37

Ind. (NAICS): information 1,011.49** 1,023.32** −51.53* 88.57

Ind. (NAICS): finance and insurance 1,169.78** 1,293.21** −147.62** 90.58

Ind. (NAICS): real estate, rental, leasing −76.86 −34.30 −75.03** 19.38

Ind. (NAICS): professional, scientific, technical 739.07** 846.53** −140.43** 12.00

Ind. (NAICS): company/enterprise management 792.60 819.57 −35.18 747.75

Ind. (NAICS): admin., support and waste mgmt. −26.89 −30.88 −2.50 56.11**

Ind. (NAICS): educational services 1,089.99** 1,247.75** −146.25** 76.73

Ind. (NAICS): health care/social assistance 415.68** 470.37** −51.41** 85.76**

Ind. (NAICS): art, entertainment, recreation −342.15 −351.49 −6.58 126.73

Ind. (NAICS): accommodation and food svcs. −638.09** −700.72** 58.49** −22.78

Ind. (NAICS): other svcs. (except publ. admin.) −592.46** −534.82** −54.38** 83.25

Ind. (NAICS): public administration 653.83 717.93** −21.58 62.47

Ind. (NAICS): unclassifiable 325.91 481.09 −130.67** −354.66

Unemployment rate at TANF exit −122.86** −136.33 2.38 46.57**

Chg. in unempl. rate, exit-to-new unempl. −188.16** −205.66 5.17 50.59**

Observations 100,707 100,707 100,707 8,432

R-squared 0.1531 0.1546 0.1221 0.6361

Adjusted R-squared 0.1511 0.1526 0.1200 0.6261

NOTE: *Parameter estimate significantly different from zero at the 90 percent confidence level in a two-tailed test; ** parameter 

estimate significantly different from zero at the 95 percent confidence level in a two-tailed test. — = data not available. a

All models include indicator variables for year and quarter of exit from TANF and county of residence.

b

Sample for model of UI compensation was restricted to UI beneficiaries only.

c

For consistency between applicants and nonapplicants, the base period for both groups is defined as the first four of the five 

quarters prior to new unemployment.
174

Table A.35 Models of Services Impacts on Total Income and Its Components among Newly Unemployed 

TANF-Leavers in Ohio

Independent variables

Parameter estimates

Total

income

Earnings from

employment

TANF

income

UI

compensationa

Intercept 3,076.49** 2,052.85** 1,100.15** −2,638.20**

Job search planning −520.54** −439.23** −59.40 −108.38

Job seeker match −228.94** −271.82** 56.63 −2.76

Veterans (DVOP/LVER) 562.63** 490.15** 80.62 127.95

Placement −147.36 −104.90 −52.57 −529.78**

Referral 477.69** 409.05** 66.82 230.37**

Job search planning × UI beneficiary −438.96 −616.03 239.15**

Job seeker match × UI beneficiary −369.86 −77.48 −113.96

Veterans (DVOP/LVER) × UI beneficiary −161.73 −413.35 −30.04

Placement × UI beneficiary 1,201.51* 1,770.17** −37.38

Referral × UI beneficiary −597.26* −785.86** 1,18.31

Job search planning × UI nonbeneficiary 66.45 35.68 11.50

Job seeker match × UI nonbeneficiary 470.37** 447.74** 11.61

Veterans (DVOP/LVER) × UI nonbeneficiary −508.77 −411.95 −100.21

Placement × UI nonbeneficiary 708.96 520.01 179.60

Referral × UI nonbeneficiary 55.39 54.60 2.86

UI beneficiary 4,223.11** 1,851.59** −378.39**

UI applicant but not a beneficiary −871.89** −866.96** 9.94

Age 18–24 278.33** 98.62** 179.19** −117.65*

 25–44 −170.37** −41.70* −128.05** 26.29

 45+ −702.35** −537.72** −168.02** 110.37

Gender, male −10.97 181.74** −217.28** 20.01

Gender, female 2.34 −38.74** 46.31** −7.38

Race, white −149.38** −2.32 −148.93** −43.13

Race, black 155.32** −8.48 165.34** 49.86

Race, Hispanic −29.79 −40.62 20.39 −157.39

Race, other 474.11** 646.09** −177.66** 348.93

Education, less than high school −180.88** −211.57** 30.04** 2.17

Education, high school graduate/GED 229.88** 264.20** −31.44** −7.08

Education, some college 426.85** 531.16** −118.82** 41.52

Education, bachelor’s degree or higher 610.67 953.31** −422.07** 61.05

Weekly benefit amount — — — 20.10**

UI entitlement (weeks) — — — 86.13**

Base period earnings ($1,000)b 230.57** 217.52** 0.61 11.06
Table A.35 (Continued)

175

Independent variables

Parameter estimates

Total

income

Earnings from

employment

TANF

income

UI

compensationa

Base period earnings less than $10,000b 147.55* 95.34 10.79 247.17**

Employed 4 qtrs. or less before unempl. −641.56** −504.53** −166.60** 42.79

5–8 qtrs. −307.26** −235.98** −70.96** −76.43

9–12 qtrs. 531.63** 413.49** 130.87** 29.19

Quarters from exit to new unemployment −166.56** −113.55** −43.36** −20.02

Employment level (1,000) at TANF exit 0.01 0.55** −0.54** 0.11

Total eligible adults at last payment −267.75** −59.91 −208.41** 12.31

Total eligible children (6–17) at last pmt. 149.43** 31.68 118.92** −61.49**

Total eligible children < 6 at last pmt. 143.59** 18.54 124.69** −0.88

Exempt, caring for child under age 1 58.09 104.95 −45.74 −38.63

Has access to motor vehicle 147.46** 195.69** −50.16** 0.22

Person is AG payee −77.46 −48.01 −25.44 −0.29

Person is parent of minor child in AG 232.52** −161.97** 389.30** 11.93

Marital status, single 25.74 18.42 9.52* −6.41

Marital status, married 80.59 31.48 39.84** −96.77

Marital status, divorced/abandoned −145.40* −75.63 −73.94** 136.41

Marital status, separated −190.60** −115.25* −72.21** 87.77

Marital status, widow/widower −588.12 −522.41 −133.46 1,046.75**

Appalachian area county −369.36** −150.87** −209.50** −108.81

Metropolitan area county 127.42** −18.48 145.02** 36.45

Other area county −136.64** 136.84** −276.26** −42.04

YYYYQ of TANF exit, 2000:2 297.89** 130.91** 156.15** 173.88**

YYYYQ of TANF exit, 2000:3 101.25** -7.58 108.99** 50.56

YYYYQ of TANF exit, 2000:4 −159.39** −113.17** −44.30** 5.14

YYYYQ of TANF exit, 2001:1 −302.76** −108.05** −183.43** −188.29**

YYYYQ of TANF exit, 2001:2 −59.80 −43.32 −17.03 −92.81

YYYYQ of TANF exit, 2001:3 109.28** 175.22** −67.45 −53.35

Observations 52,926 52,926 52,926 1,916

R-squared 0.1300 0.0983 0.0666 0.4999

Adjusted R-squared 0.1291 0.0975 0.0658 0.4892

NOTE: * Parameter estimate significantly different from zero at the 90 percent confidence level in a two-tailed test; ** 

parameter estimate significantly different from zero at the 95 percent confidence level in a two-tailed test. — = data not 

available. a

Sample for model of UI compensation was restricted to UI beneficiaries only.

b

For consistency between UI applicants and nonapplicants, the base period for both groups is defined as the first four of the 

five quarters prior to new unemployment.
176
177

REFERENCES

Balducchi, David E., Randall W. Eberts, and Christopher J. O’Leary, eds. 2004. Labor 

Exchange Services in the United States: History, Effectiveness, and Prospects. 

Kalamazoo, MI: W.E. Upjohn Institute for Employment Research.

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