U.S. GOVERNMENT PUBLISHING OFFICE

32–988 PDF WASHINGTON : 2018

S. Hrg. 115–393 

EXAMINATION OF THE EFFECT OF REGULATORY 

POLICY ON THE ECONOMY AND BUSINESS 

GROWTH 

HEARING 

BEFORE THE

SUBCOMMITTEE ON 

REGULATORY AFFAIRS AND FEDERAL 

MANAGEMENT 

OF THE

COMMITTEE ON 

HOMELAND SECURITY AND 

GOVERNMENTAL AFFAIRS 

UNITED STATES SENATE 

ONE HUNDRED FIFTEENTH CONGRESS 

SECOND SESSION 

SEPTEMBER 27, 2018 

Available via http://www.govinfo.gov 

Printed for the use of the Committee on Homeland Security 

and Governmental Affairs 

( 
(II) 

COMMITTEE ON HOMELAND SECURITY AND GOVERNMENTAL AFFAIRS 

RON JOHNSON, Wisconsin, Chairman 

ROB PORTMAN, Ohio 

RAND PAUL, Kentucky 

JAMES LANKFORD, Oklahoma 

MICHAEL B. ENZI, Wyoming 

JOHN HOEVEN, North Dakota 

STEVE DAINES, Montana 

JON KYL, Arizona 

CLAIRE MCCASKILL, Missouri 

THOMAS R. CARPER, Delaware 

HEIDI HEITKAMP, North Dakota 

GARY C. PETERS, Michigan 

MAGGIE HASSAN, New Hampshire 

KAMALA D. HARRIS, California 

DOUG JONES, Alabama 

CHRISTOPHER R. HIXON, Staff Director 

MARGARET E. DAUM, Minority Staff Director 

LAURA W. KILBRIDE, Chief Clerk 

SUBCOMMITTEE ON REGULATORY AFFAIRS AND FEDERAL 

MANAGEMENT 

JAMES LANKFORD, Oklahoma, Chairman 

ROB PORTMAN, Ohio 

MICHAEL B. ENZI, Wyoming 

STEVE DAINES, Montana 

JON KYL, Arizona 

HEIDI HEITKAMP, North Dakota 

THOMAS R. CARPER, Delaware 

MAGGIE HASSAN, New Hampshire 

KAMALA D. HARRIS, California 

JOHN CUADERES, Staff Director 

JAMES MANN, Senior Counsel 

ERIC BURSCH, Minority Staff Director 

ANTHONY PAPIAN, Minority Professional Staff Member 

MALLORY NERSESIAN, Subcommittee and Document Clerk 
(III) 

C O N T E N T S 

Opening statement: Page 

Senator Lankford .............................................................................................. 1 

Senator Heitkamp ............................................................................................ 2 

Senator Carper ................................................................................................. 17 

Prepared statement: 

Senator Lankford .............................................................................................. 31 

WITNESSES 

THURSDAY, SEPTEMBER 27, 2018 

Hon. Howard Shelanski, Professor of Law, Georgetown University Law Center .......................................................................................................................... 5

Dustin Chambers, Ph.D., Professor of Economics, Department of Economics 

and Finance, Franklin P. Perdue School of Business, Salisbury University .. 7 

Karen Kerrigan, President and Chief Executive Officer, Small Business and 

Entrepreneurship Council ................................................................................... 8 

Maria Ghazal, Senior Vice President and Counsel, Business Roundtable ......... 10 

ALPHABETICAL LIST OF WITNESSES

Chambers, Dustin: 

Testimony .......................................................................................................... 7 

Prepared statement with attachment ............................................................. 38 

Ghazal, Maria: 

Testimony .......................................................................................................... 10 

Prepared statement .......................................................................................... 119 

Kerrigan, Karen: 

Testimony .......................................................................................................... 8 

Prepared statement .......................................................................................... 112 

Shelanski, Hon. Howard: 

Testimony .......................................................................................................... 5 

Prepared statement .......................................................................................... 33 

(1) 

1The prepared statement of Senator Lankford appears in the Appendix on page 31. 

EXAMINATION OF THE EFFECT OF 

REGULATORY POLICY ON THE ECONOMY AND 

BUSINESS GROWTH 

THURSDAY, SEPTEMBER 27, 2018 

U.S. SENATE, SUBCOMMITTEE ON REGULATORY, AFFAIRS AND FEDERAL MANAGEMENT, OF THE COMMITTEE ON HOMELAND SECURITY

AND GOVERNMENTAL AFFAIRS, Washington, DC. 

The Subcommittee met, pursuant to notice, at 10:05 a.m., in 

room SD–342, Dirksen Senate Office Building, Hon. James 

Lankford, Chairman of the Subcommittee, presiding. 

Present: Senators Lankford, Heitkamp, and Carper. 

OPENING STATEMENT OF SENATOR LANKFORD1

Senator LANKFORD. Good morning, everyone. Welcome. I know 

this is the most anticipated hearing of the day on the Hill. [Laughter.] 

I appreciate you all being here. This is today’s Subcommittee 

hearing titled ‘‘Examination of Regulatory Policy on the Economy 

and Business Growth.’’ We are examining the Administration’s regulatory policy and how it has influenced the economy. 

As we begin this conversation, it is important to be clear that 

well-written regulations are a necessary facet of an orderly society. 

This is not an anti-regulation hearing. It is how it is done, what 

is done, how often do they put out, and, quite frankly, it is my belief that well-designed regulations bring clarity for individuals and 

businesses alike. It provides safety, it provides boundaries, it provides a clear path for where we are going to go in business in the 

future. 

Regulations are necessary to carry out the laws passed by Congress, and they must be promulgated carefully and in a deliberate 

manner with thorough analysis done on the front end to avoid lawsuits and delays on the back end. 

However, over the years through multiple Administrations, there 

has been an onslaught of regulations. Some became a drag on our 

economy. The new term ‘‘regulatory burden’’ has been used to describe how regulations affected both small and large businesses 

and the economy in general. 

Like most Members of Congress, I can attest that over the years 

I held many meetings with constituents, not to talk about a single 
2 

problem regulation but, instead, about the accumulation of regulations and the effect that has had for them. Quite frankly, many of 

my constituents in Oklahoma just a few years ago would sit down 

with me and I would say, ‘‘What is it that you want to talk to me 

about?’’ and they would say, ‘‘I do not have a specific thing. I just 

want you to make it stop because we cannot keep up.’’ 

How big is the regulatory burden has been the challenge. As a Nation, we spend nearly $2 trillion a year on regulatory compliance. There is a question to say: Is all that wrong? No. There are 

a lot of safety issues; there are a lot of things that are perfecting 

our way of handling civil rights and such that are exceptionally important to us to be able to maintain. We have to be able to figure 

out how to be able to do it wisely and well. 

This Administration, through various Executive Orders (EO) and 

policy changes, has taken significant steps to reform the administrative process. These actions have spurred a marked increase in 

optimism from individuals and businesses, which is strengthening 

our economy and lowering unemployment. 

According to many economists, the recent increases in gross domestic product (GDP) are partially the result of the certainty that 

comes through regulatory stability. 

While I applaud the Administration’s focus on breaking the cycle 

of piling one regulation on top of another, the Executive Branch 

alone cannot provide long-term regulatory stability. That responsibility rests with Congress. 

This Committee has debated legislation that will set clear guidelines for agencies—not to dictate a particular outcome, but simply 

to require them to complete thorough analysis before they issue a 

rule. 

Commonsense things such as measuring the full impact of a rule, 

consulting with State, local, and tribal governments, and listening 

to small business owners at all stages of the process are just a few 

of the ideas that Congress needs to address and pass. 

I am optimistic that there are areas of agreement, as Senator 

Heitkamp have talked about often. There are ways that Congress 

can work together with the Executive Branch to bring long-term 

regulatory stability, which will add to GDP; that means jobs for 

Americans, and that means increased wages for Americans. And it 

also helps provide a buffer on economic recession. 

I have termed this Subcommittee as the ‘‘nerdiest Subcommittee 

in the Senate,’’ and we are probably going to prove it again today. 

But this conversation is important to us, and it will be important 

to people in ways that they will never understand as we just deal 

with the availability of jobs, the wages for jobs, and the expansion 

of business in the days ahead. 

With that, I recognize Ranking Member Heitkamp for her opening remarks. 

OPENING STATEMENT OF SENATOR HEITKAMP 

Senator HEITKAMP. Thank you, Chairman Lankford. 

This is such an important area, and I completely concur in what 

Senator Lankford said. I think that you see a business optimism 

that is a result of a sense that at least someone is going to listen 

to us about regulation. At least we have a chance. 
3 

The question we have to ask is: How permanent is that? How can 

we reestablish some kind of permanent solutions to the problems 

whether they are dealing with systemic regulatory reform or 

whether they are dealing with individual regulations? 

When you look at what has been happening in the rollback of individual regulations, obviously the courts are playing a role today 

in stays and in questioning whether those are the regulations. A 

good example is the Clean Power Plan (CPP). I think the Clean 

Power Plan was folly. I think that it was wrongly decided at the 

Environmental Protection Agency (EPA). It needed to be rolled 

back. 

Now we are in this situation where we have a period of time to 

try and fix the problem, to respond to the Massachusetts case, and 

actually have a regulation that works. Instead, we are in litigation. 

And so there are two changes for that: one, systemic reform, because I have reminded my colleagues especially on my side of the 

aisle: Why would you ever want to be the party of irrational regulation, duplicative regulation? Why would you ever want to be headed in that direction? 

The challenge that we have is making sure we have the right 

regulation. But we also have a challenge here in making sure that 

Congress does its job. 

When you see years and years and years of litigation on the Waters of the United States—it has been in litigation for probably 30 

years. At what point do we say enough is enough and we are going 

to provide congressional direction? Millions of dollars spent in litigation, uncertainty which swings with the political winds. And so 

what we want to talk about is how to do this right, and I think 

Senator Lankford and I are genuinely interested in what you have 

to say, genuinely interested in how we can get this done. 

And the last thing I am going to say, it is something that we 

kind of went through yesterday, which is we can get in our corners 

and get that bill that might make a nice 30-second ad that you 

could say, ‘‘Look what I have done.’’ But you are not doing anything 

by introducing a bill. You are not doing anything by getting a bill 

on a partisan vote out of committee. You have to roll up your 

sleeves and get the work done, and that means working across the 

aisle, coming to some kind of general terms, and solving this problem. 

And so I look forward to your testimony. I look forward to continuing to work with Senator Lankford. We definitely have had 

some exciting—well, exciting by our standards, I guess. 

Senator LANKFORD. By our standards. 

Senator HEITKAMP. Yes, by our standards—exciting conversations about how to solve these issues, and I want to thank you all 

for your commitment. You teased a little bit about this is the most 

exciting hearing. It may be one of the most important hearings 

when you look at the public, when you look at the business, when 

you look at consumers, when you look at the citizens. This is the 

kind of work that they want us to do. 

And so welcome, all of you, and thank you so much for your time. 

Senator LANKFORD. Thank you, Senator Heitkamp. 
4 

Let me proceed to the witness testimony, and I am going to introduce all four of you and then allow the four of you to actually give 

testimony. 

Howard Shelanski is the former Administrator of the Office of Information and Regulatory Affairs (OIRA), a post that he held from 

2013 until January 2017. From 2009 to 2011, Mr. Shelanski served 

as the Deputy Director of the Federal Trade Commission’s Bureau 

of Economics and served as Director there from 2012 to 2013. Mr. 

Shelanski has also served as the Chief Economist of the Federal 

Communications Commission and Senior Economist on President 

Obama’s Council of Economic Advisers. He is currently a professor 

of law at Georgetown University Law Center and has been in frequent conversations here for us. We are very grateful to be able to 

have you back here as a private citizen. Thanks for all your service 

to the Nation before in public office, and we are always grateful to 

have another redhead on the panel and in the conversation, but we 

really do appreciate your bringing your insight back to this conversation again. 

Dustin Chambers is a professor of economics at the Perdue 

School of Business at Salisbury University, a senior affiliated scholar for the Mercatus Center at George Mason University, and a policy adviser at the Heartland Institute. Dr. Chambers has published 

widely on topics of income inequality, poverty, and economic 

growth. He earned his M.A. in economics from UCLA and his Ph.D. 

in economics from the University of California at Riverside. Thank 

you for being here. 

Karen Kerrigan is the president and Chief Executive Officer 

(CEO) of the Small Business & Entrepreneurship (SBE) Council 

and is the group’s chief advocate for its members. She regularly 

writes and testifies on key issues impacting entrepreneurs and the 

economy and has been appointed to numerous Federal advisory 

boards, including the National Women’s Business Council and regularly leads roundtables at the White House Economic Summits. 

Thank you for being here and for testifying today. 

Maria Ghazal is senior vice president and counsel for the Business Roundtable where she directs strategic initiatives across the 

organization and oversees policy development and advocacy for 

Business Roundtable Corporate Governance and Smart Regulation 

Committees. Prior to joining Business Roundtable in 2005, Ms. 

Ghazal was director of health policy at the American Benefits 

Council, served as director of government relations at Verizon, and 

worked as a legislative assistant in the Metropolitan Life Insurance 

Company. Her career began as an aide to Senator Daniel Patrick 

Moynihan. That is quite a heritage as well. 

Thank you to all of you for being here and for your preparation. 

We have received your written testimony and are grateful to be 

able to get oral testimony as well. 

It is the custom of the Subcommittee to swear in all witnesses 

that appear before us, so if you do not mind, would you please 

stand and raise your right hand? Do you swear that the testimony 

you are about to give before this Subcommittee will be the truth, 

the whole truth, and nothing but the truth, so help you, God? 

Mr. SHELANSKI. I do. 

Mr. CHAMBERS. I do. 
5 

1The prepared statement of Mr. Shelanski appears in the Appendix on page 33. 

Ms. KERRIGAN. I do. 

Ms. GHAZAL. I do. 

Senator LANKFORD. Thank you. You may be seated. Please let 

the record reflect that all witnesses answered in the affirmative. 

Mr. Shelanski, you will kick us off today with your testimony. 

Thank you again for being here, and we look forward to receiving 

that. 

TESTIMONY OF THE HONORABLE HOWARD SHELANSKI,1 PROFESSOR OF LAW, GEORGETOWN UNIVERSITY LAW CENTER 

Mr. SHELANSKI. Thank you very much, Chairman Lankford. 

Chairman Lankford, Ranking Member Heitkamp, thank you very 

much for inviting me to testify before you today. It is always an 

honor, and particularly so given the importance of the issues that 

we are going to be discussing. I commend the Subcommittee for its 

continued hard work on issues that are of vital importance and 

that are not always easy. 

I wish to make three general points in my oral testimony today. 

The first is that regulation must be done carefully, with rigorous 

attention to costs and benefits. 

The second is that regulation should take account of how its 

costs might differ for entities of varying sizes. 

And the third is that the same careful assessment of costs and 

benefits that applies to rulemaking should apply to deregulation. 

The criteria for any regulatory reform should be whether it advances the above three principles and whether it is neutral in its 

impact on the weighing of regulatory costs and benefits. 

One of the signature achievements of the United States regulatory system over the past 40 years has been the increasingly central role of cost-benefit analysis. When President Reagan signed 

Executive Order 12291 in 1981, he established the process of centralized review of Executive Branch regulations based on cost-benefit principles. 

Despite concern in many quarters about the centrality of costbenefit analysis that emerged under President Reagan’s Executive 

Order, when President Clinton took office in 1993, instead of repealing Executive Order 12291, he revised and updated the order 

into Executive Order 12866. That order, Executive Order 12866, remains in force today, affirmed and expanded by Executive Orders 

from Republican and Democratic Administrations alike. 

For purposes of this hearing, I want to focus on two core principles of Executive Order 12866: that the benefits of any regulation 

must justify the costs the rule imposes on society, and that agencies should regularly review the continuing effectiveness of the 

rules they already have on the books. Regulatory reform should 

neither get in the way of sound assessment of costs and benefits 

nor put an undue thumb on the scales toward one side of that balance. 

For cost-benefit analysis to be meaningful, agencies need to take 

both costs and benefits seriously. Unfortunately, polarized arguments that emphasize one of those values while ignoring the other 

too often characterize debates over regulation. For example, regu-
6 

latory advocates have often opposed weighing quantified economic 

costs against health and safety benefits. Despite occasional statements from advocates that we should never trade lives for lower social costs, we do it every day. The speed limit of 15 miles per hour 

would save many thousands of lives, but society would not bear the 

costs, nor should it, of such a policy. 

Regulatory costs are there for an inherent factor in societal decisions about what kinds of rules it wants, and even if there is no 

requirement—and I do not believe there should be—that a rule’s 

quantifiable benefits always exceed its quantifiable costs, rigorous 

analysis of regulatory costs allows society to know how much it is 

paying for the policies and protections it chooses. 

On the other side of the debate, advocates of non-regulation or 

deregulation sometimes focus too exclusively on the costs of a given 

rule, without acknowledging or accurately accounting for the very 

real benefits to society that could be lost. For example, when the 

EPA set forth to reform the Clean Power Plan rules—and those 

rules might indeed have been in need, as Senator Heitkamp stated 

in her opening statement, of some revisiting and some reform— 

there was very little discussion of the benefits that the rule would 

bring in a lot of the advocacy surrounding that repeal. Indeed, 

when the EPA Administrator went public with the plans, Chris 

Wallace, while interviewing him on television, pointed out that that 

rule was predicted to eventually eliminate 90,000 asthma attacks, 

300,000 missed school and work days, and 3,600 premature deaths 

each year. Mr. Wallace’s simple question was: What was the EPA’s 

plan to make sure that society got those benefits at the same time 

that the costs of the rule were being reformed? 

At that point there was not a very good answer to that question. 

There needs to be a good answer to the question of the foregone 

benefits and not too narrow a focus on the costs that would be 

saved from deregulatory efforts. 

Beyond serving as illustrative anecdotes, the above examples also 

hint at an important challenge for cost-benefit analysis, and one to 

which regulatory reform should be attuned: Regulatory costs are 

often more salient and easier to quantify than regulatory benefits. 

Regulatory benefits often accrue far in the future and are spread 

broadly across millions of individuals. Moreover, the benefits of regulation, especially to any given individual, might be uncertain. Regulatory benefits can, therefore, be less salient for people. 

The fact that costs can be more readily quantifiable and more 

likely to regulate stakeholder advocacy than benefits is important 

because it suggests that the legislative creation of new requirements for the regulatory process might not fall symmetrically on 

the cost and benefit sides of the ledger. Therefore, while the most 

important thing for regulatory reform is to ensure that it advances 

analysis of both costs and benefits in rulemaking, it is also important to ensure that legislation that is neutral on its face does not, 

in actual practice, improperly tilt the analysis of costs and benefits 

in a way that harms society over time. 

I see that my time is up. I will reserve my comments on the 

other matters for your questions. Thank you. 

Senator LANKFORD. Thank you. Mr. Chambers. 
7 

1The prepared statement of Mr. Chambers appears in the Appendix on page 38. 

TESTIMONY OF DUSTIN CHAMBERS, PH.D.,1 PROFESSOR OF 

ECONOMICS, DEPARTMENT OF ECONOMICS AND FINANCE, 

FRANKLIN P. PERDUE SCHOOL OF BUSINESS, SALISBURY 

UNIVERSITY 

Mr. CHAMBERS. Good morning, Chairman Lankford, Ranking 

Member Heitkamp, and the not-in-attendance Members of the 

Committee. I thank you for inviting me to testify this morning. 

Regulations that protect health, safety, and the environment are 

absolutely necessary, as Senator Lankford stated in his opening remarks. However, red tape, to paraphrase Laura Jones, are rules 

and policies that do little to serve the public interest while creating 

financial costs or frustration to producers and consumers, including 

outdated, redundant, inconsistent, and needlessly complex rules. 

My testimony today focuses on three unintended consequences of 

an expanding and complex body of Federal regulation: 

One, the unchecked growth of regulation, especially when it includes red tape, reduces economic growth, the economy, and reduces living standards for most Americans; 

Two, regulatory accumulation harms small businesses; 

And, three, the buildup of Federal regulation increases poverty 

rates and increases consumer prices paid by all, especially the 

poorest consumers. 

To address my first point, a 2016 study by Coffey, McLaughlin, 

and Peretto used RegData, a state-of-the-art database which identifies regulatory restrictions by industry to estimate the impacts of 

regulations on the U.S. economy. They found that regulations 

trimmed U.S. economic growth between 1977 and 2012 by about 

0.8 percentage points annually. Now, that might seem like a small 

number, but to put it in perspective, if the quantity of regulations 

on the books had been held constant between 1980 and 2012—and 

that does not preclude improving the regulations over time, just 

not increasing the total number in the aggregate—they estimate 

that the economy would have been $4 trillion larger in 2012, or 25 

percent bigger, than what we actually experienced. If you divide 

that by the population, that is $13,000 additional income for every 

man, woman, and child in the United States. Their findings were 

consistent with other studies and demonstrates the unintended impact of costly and ineffective regulations on the U.S. economy. 

To address my second point, there is disturbing evidence that 

small businesses are more negatively impacted by accumulating 

regulations than their larger competitors. In a 2017 study, Bailey 

and Thomas found that rising levels of Federal regulations are associated with reductions in both the formation of new firms and 

new employee hiring. Interestingly, when controlling for firm size, 

this effect appears to only apply to smaller firms. 

In a similar study released this year, I and two colleagues also 

found that a 10-percent increase in Federal regulation is associated 

with a loss of about 25,000 small businesses. Clearly, the burden 

of complying with costly and ineffective regulations harms small 

business. 

Finally, to address my third point, I and two co-authors found a 

positive relationship between Federal regulations and poverty rates 
8 

1The prepared statement of Ms. Kerrigan appears in the Appendix on page 112. 

at the State level. Specifically, we discovered that a 10-percent increase in the Federal regulatory burden at the State level is associated with a 2.5-percent increase in that State’s poverty rate. This 

result implies that a 10-percent across-the-board reduction in Federal regulations, particularly one aimed at red tape, would lift an 

estimated 1 million people above the poverty line. 

Unfortunately, the regressive effects of regulatory accumulation 

do not stop there. They also harm poor households in the form of 

higher consumer prices. In a 2018 study, I and two colleagues estimated that a 10-percent increase in Federal regulations is associated with a 1-percent increase in overall consumer prices. We also 

determined that the poorest households spent a larger share of 

their income on the most heavily regulated goods and faced an average inflation rate that was 18 percent greater than households 

in the top income category. These results demonstrate that red 

tape harms the poor both directly by boosting the poverty rate and 

indirectly by driving up the price of items frequently purchased by 

the poor. 

In closing, given that the unintended consequences of unchecked 

regulatory expansion, which include lower rates of economic 

growth, reduced entrepreneurship, higher rates of poverty, and 

higher prices for all consumers, especially the poor, the need for 

meaningful regulatory reform which slashes red tape but not highquality fundamental regulation while preserving rules that protect 

workers, consumers, and the environment should be apparent. 

Moreover, the ability to stimulate the economy without impacting 

the Federal budget or the national debt through increased spending 

or tax cuts is especially appealing. 

Thank you. 

Senator LANKFORD. Thank you. Ms. Kerrigan. 

TESTIMONY OF KAREN KERRIGAN,1 PRESIDENT AND CHIEF 

EXECUTIVE OFFICER, SMALL BUSINESS & ENTREPRENEURSHIP COUNCIL 

Ms. KERRIGAN. Thank you Chairman Lankford and Ranking 

Member Heitkamp for holding this important hearing on regulatory policy and its impact on the economy and business growth. 

I am honored to be able to represent the Small Business & Entrepreneurship Council and our members this morning. And also 

thank you for your work on advancing reforms that will improve 

and modernize the regulatory process. SBE Council and our members appreciate your leadership in this critical area. 

Current regulatory policy and the general direction of policy have 

been very positive for small businesses. Entrepreneurs feel liberated in a sense that they can focus more intently on growing their 

businesses rather than being preoccupied by new regulatory 

threats that could impact costs and competitiveness. Their positivity is strong, as reported by all the key surveys that measures 

small business optimism. It is historically high, by some measures, 

and this is not only reflected in how entrepreneurs feel about the 

business climate, but also in their own businesses’ bottom line and 
9 

performance due to increased sales and revenues and opportunities 

for expansion. 

This, of course, has translated into more hiring, investment, improved wages, and expanded opportunities for workers. Our members and small business owners tell us their optimism and the improved business environment are directly tied to Federal policy, 

and one of the key pieces is the change in regulatory policy. Again, 

it has been a welcome development. 

The President’s Executive Orders on streamlining regulation and 

cutting red tape combined with movement in the Congress on 

broad regulatory reform and legislation that passed and already 

signed by the President on specific areas—for example, reforms to 

improve lending—have made good on the regulatory signals that 

were sent to small businesses about where Federal policy and actions would be headed at the beginning of the new Administration 

and the 115th Congress. These signals, and subsequent action, 

have provided a very powerful boost to entrepreneurs and small 

businesses. 

We are pleased that the agencies are following through on the 

Executive Orders. In addition, the Small Business Administration 

(SBA) Office of Advocacy has stepped up to assist with implementation. Their activity with a focus on small business engagement is 

ongoing and has been very effective. And I applaud the Acting 

Chief Counsel Major Clark for his leadership and work. 

While concern about government regulation has diminished 

somewhat for small business owners, it remains a priority issue 

and challenge for many. So there is still work to be done in this 

regard, and we believe that, in addition to agencies continuing 

their efforts to weed out and fix regulatory burdens, Congress can 

play a big part by finishing the work it has started on regulatory 

reform. This would be a dynamic sequence that would promote regulatory stability and ensure that robust economic growth continues. 

SBE Council is very supportive of the reform bills advanced by 

the broader Committee, and we are particularly passionate about 

S. 584, the Small Business Regulatory Flexibility Improvements 

Act. The key pieces of this bill to explore and document the rationale, objective, and legal basis, costs, potential ripple effects, unintended consequences of proposed regulatory actions, and engaging 

small business owners in this process all on the front end we believe will produce smarter regulation. 

The additions the bill makes to the final regulatory flexibility 

analysis providing the Chief Counsel, Office of Advocacy, with more 

tools and power, the periodic review of rules, bringing IRS regulations under this process, and providing the waiver of fines for small 

businesses with respect to first-time paperwork violations all add 

together to make the regulatory process more accountable, transparent, and friendly to small businesses. 

We believe it is important for Congress and the Administration 

to stay on a reform-minded path as regulatory stability and consistency will help to sustain strong economic growth and competence 

that we are now experiencing. 

We need to restore strong entrepreneurship. The data shows that 

we are on that path. But what are being called ‘‘psychological 

scars’’ from the financial crisis and its aftermath remain with us, 
10 

1The prepared statement of Ms. Ghazal appears in the Appendix on page 119. 

which has created an aversion to risk. A long-lasting and strong 

economic expansion will fuel confidence, which will encourage more 

people to take the risk of starting a business. Regulatory stability 

and a better regulatory system will help greatly in this regard. 

So thank you again for having SBE Council with you here this 

morning, and I look forward to our discussion. 

Senator LANKFORD. Thank you. Ms. Ghazal. 

TESTIMONY OF MARIA GHAZAL,1 SENIOR VICE PRESIDENT 

AND COUNSEL, BUSINESS ROUNDTABLE 

Ms. GHAZAL. Good morning, Chairman Lankford and Ranking 

Member Heitkamp. Thank you for inviting me to this important 

hearing on the economic effects of regulatory policy. 

Business Roundtable is an association of chief executive officers 

of America’s leading companies. We work to promote a thriving 

U.S. economy and expanded opportunity for all Americans through 

sound public policy. Business Roundtable CEOs support an approach to regulation that meets regulatory goals and promotes economic growth and job creation. We call this approach ‘‘smart regulation.’’ Our members believe that smart regulation can be achieved 

by reforming three key areas: the process for issuing regulations 

and guidance, the extensive overlap among agency jurisdictions, 

and the system for permitting major infrastructure projects. 

The Trump Administration is taking major steps in each of these 

areas. I will describe how those actions are already producing improvements, and I will also highlight ways that Congress—starting 

with this Subcommittee—could codify those improvements and do 

things the Executive Branch cannot. 

The first needed improvement is reforming the process for 

issuing regulations and guidance documents. By creating uncertainty and imposing enormous costs, the current system obstructs 

innovation, investment, and compliance. The President has made 

great progress through a pair of Executive Orders that establish a 

one-in, two-out goal for every significant new regulation and that 

institutionalize his regulatory reform agenda. The Administration 

also broke new ground when the Treasury Department and the Office of Management and Budget (OMB) issued a memorandum of 

agreement enabling OMB to review certain tax rules. 

Business Roundtable members are encouraged by this dramatic 

shift in regulatory philosophy. After five consecutive years, regulatory costs are no longer the top cost pressure for CEOs, and our 

CEO Economic Outlook Survey reached an all-time high earlier 

this year. 

The single most important action Congress could take to codify 

these improvements would be to enact the Regulatory Accountability Act (RAA). Most importantly, the RAA would require agencies to engage with affected stakeholders before developing a proposed rule, ensure that agencies consider the costs and benefits of 

proposed rules, and make sure that the benefits justify the cost, extend these requirements to independent agencies, and require that 

major rules include a framework for evaluating how well the rule 

has actually achieved its goals. 
11 

The second needed improvement is to reduce the widespread jurisdictional overlaps among U.S. regulatory agencies. Too often, 

firms are subject to multiple requirements from multiple agencies 

on a single issue. In June, the Administration issued a bold plan 

proposing 32 structural reforms to the Federal Government. These 

include, for example, consolidating the food safety responsibilities 

of the Food and Drug Administration (FDA) and the U.S. Department of Agriculture (USDA). Individual agencies are also taking 

steps to rationalize their operations. Business Roundtable members 

are enthusiastic about several of these reforms, and we are optimistic that the Administration may be able to make new progress 

in reducing regulatory overlaps. 

This Subcommittee and its parent Committee can play a key 

oversight role here, identifying overlap problems and engaging 

agencies, including independent agencies, to address them. To assist you in the process, Business Roundtable will release a white 

paper later this year describing the problem and highlighting options to reduce these overlaps. Our examples will include memorandum of understanding (MOUs), interagency working groups, 

lead regulators, and joint rulemaking. 

The third needed improvement is to streamline and expedite approval processes for major infrastructure projects. Gaining approval 

to build a new bridge or factory typically involves multiple Federal 

agencies with overlapping jurisdictions, no real deadlines, and no 

single entity in charge. Congress took a huge step forward when 

it passed FAST–41, a bipartisan bill that, of course, originated in 

this Subcommittee. 

The Administration is also accelerating and rationalizing the 

process of permitting infrastructure projects. Most significantly it 

has issued a new Executive Order and a related memorandum of 

understanding, and these two do three things: first, they establish 

a 2-year goal for completing all Federal environmental reviews and 

decisions for major infrastructure projects; second, mandate that 

agencies reach one Federal decision; and, third, extend elements of 

FAST–41 to all projects subject to the National Environmental Policy Act (NEPA) and involving more than one agency. Business 

Roundtable CEOs strongly support all of these actions. 

The most important thing that Congress could do in this area 

would be to enact a FAST–41 Amendments Act that would repeal 

the 7-year sunset contained in FAST–41; codify the 2-year goal for 

environmental reviews; and allow projects under FAST–41 to be 

prioritized. 

Thank you for this opportunity to testify before the Subcommittee. This Subcommittee has led the way in focusing attention on the Federal rulemaking process and has proposed commonsense bipartisan ideas for reform. We thank you for your hard 

work, and I look forward to your questions. 

Senator LANKFORD. Thank you. We look forward to the questions. How about that? We are grateful to be able to have the dialogue and all of your input on it. 

Let me just open this up, and we will just dialogue back and 

forth on this. We will not necessarily have a clock. This will be an 

ongoing dialogue for all of us. 
12 

Mr. Shelanski, I mentioned to you before how grateful we are to 

have you back again and the insight that you bring to this. The 

cost-benefit item is a big issue because defining costs and benefits 

has been such a challenge. So I want to open this up to several 

pieces of this cost-benefit conversation. 

One is: What do you see as the primary portion on determining 

cost-benefit? Should they be equal? In other words, if the cost is 

over 10 years, should the benefits also evaluate over 10 years? Because at times some rules said we are going to look at the cost for 

10 years but the benefits for 50. So should they be equal in trying 

to get that kind of percentage? Should they be limited in scope? So, 

for instance, do you look at the cost-benefit based on the United 

States or globally? That is another big challenge that we have. And 

the biggest issue that I see with this is trying to evaluate the benefits long term. 

I do not know how you handle weather forecasting, but I am 

much more trusting of the forecast 2 days from now than I am 

hearing the weatherman say this is what the weather is going to 

be like 2 years from now. Sometimes when we do a benefit analysis, we are asking an economist to give us a guess what the benefit will be 20 years from now, and that is tough to swallow with 

so many different elements in it. It depends completely on the 

model. So sometimes picking the model really determines your outcome because if I pick the right model, I am going to get the outcome I want, because the benefits will show anything depending on 

who I model it through. 

So I know those are some big issues on cost-benefit, but we have 

some big issues around that that we have to help provide some definition on. So scope, time, equal amounts, and then how do you 

pick that model for the benefit? 

Mr. SHELANSKI. Thank you, Senator. Those are clearly core and 

very difficult questions. Let me start with time. 

I do not think that it should be a requirement that the benefits 

are measured over the same timeframe, for example, as the costs. 

And the only reason that I would say there can be a very systematic difference between the two, regulation often entails a high 

fixed cost of compliance—— 

Senator LANKFORD. Up front. 

Mr. SHELANSKI. Up front—that might be put in place over a 

number of years and where the incremental costs then, once you 

have that compliance system in place, might be somewhat lower. 

There are a lot of issues that arise out of that, things that we need 

to be careful about. 

Benefits might accrue immediately, so I think in something like 

workplace safety, those are the kinds of things where workplace 

safety should sort of happen immediately. Putting in place a different perimeter around a dangerous substance or machine should 

fairly quickly lead to a reduction in industries. If it does not, we 

should figure out whether the rule is properly designed. 

Other kinds of rules go after activities for which the payoff is 

far in the future. So let us take respirable coal dust as an example—a very important issue to make sure that mines are as safe 

as possible for coal miners. We need to have the best available 

science and economics to make sure that the requirements that are 
13 

put in place really do meaningfully reduce that respirable coal dust 

and do not go to some absurd standard that really is not achievable 

or not scientifically justified. But the benefits, the payoff from that, 

there is going to be a reduction in emphysema and conditions like 

that that are far in the future. And so you are making forecasts 

about the relationship between dust breathed today, the thing for 

which the cost put in place that will be reduced in a fairly short 

order and for which the compliance costs will be incurred over a 

short order, with speculation about benefits based on the best 

available epidemiological evidence and scientific evidence far in the 

future. 

If we were to discount the ability to count those benefits, we 

would never find justification for putting in place a shorter-term 

cost. 

Senator LANKFORD. But let me just pause for a second. If you are 

going to look at, let us say, a 50-year time period and let us see 

the benefit, why would you do a 10-year cost and a 50-year time 

period? If you are going to look at benefits for 50 years, should you 

not look at costs over that same 50-year timeframe? 

Mr. SHELANSKI. So absolutely you should. You just may run into 

circumstances—and I think there could be a number of them, a 

number of cases where you could imagine the costs actually cease 

to continue to accrue after a certain point. And so the emphasis 

would be on this is going to cost us a ton in 4, 5, or 10 years, let 

us not look at the benefits beyond that timeframe. Will the benefits 

over that—and all I am saying is we should not artificially cut 

short now. If we were to continue the cost, absolutely we 

should—— 

Senator LANKFORD. And that is what I am saying, just trying to 

keep some equal time percentage. And part of the challenge is, 

again, you have been on both sides of this to be able to study it 

and look at it and to be able to be on the implementing side as 

well. The challenge that we have is trying to be able to figure out 

when a regulator puts out a cost-benefit analysis, they could look 

at the benefit and say: If I get so many years out, then the benefits 

will outweigh the cost; so on this particular rule, I want the benefits to be a 50-year; on this one I want it to be a 10-year look. And 

you can weigh that based on what you are hoping to get as far as 

the outcome. 

Mr. SHELANSKI. And as long as you were taking full account of 

the costs over whatever period you choose for the benefits, then I 

think that that is fine. But there is one other really important aspect of that that you got at in your original questions. I do not 

think the models should be so malleable that they can just be 

cherrypicked by the regulator, and this is something that certainly 

during my time at OIRA was maybe one of the harder discussions 

we had with a number of agencies. 

One can build a model to do just about anything and some very 

modest initial assumptions can actually lead to very significant 

long-term effects, get you very big costs or very big benefits. 

So what we want to make sure of and what I think any regulatory reform should be designed to help ensure is that the selection of the models, the data, the information that feeds into the 
14 

models is done on rigorous, neutral, and objective principles insofar 

as possible. 

Now, that does not necessarily mean that there should be a sort 

of one-size-fits-all rule for what kind of data can be used. Sometimes there are great harms for which there is relatively modest 

data. But I think the best available science and economics standard 

that is articulated in the Executive Orders, that is articulated in 

OMB’s Circular A–4, I think that is a very good standard. 

Now, sometimes best available will not be good enough. Even 

that will be too weak and that will be too speculative. And in that 

case, we are not ready to regulate. We need to learn more. But 

sometimes there is enough. It may not be the highest level of certainty, but it is sufficient. But it has to be the best available. You 

cannot say this is pretty good, there is a better one, but it does not 

give me my results. 

Senator LANKFORD. Right. I want to make one more comment; 

then I want to shift over to Senator Heitkamp on this. It has been 

a dialogue that we have had several times around this dais with 

multiple different witnesses, that when we talk about a model, they 

will respond to me, ‘‘Well, this is the best model that is out there,’’ 

or ‘‘This is the only model that is out there. And it says X, Y, Z, 

and so we are going to get this benefit and so we are going to do 

it.’’ 

My response to that is typically: ‘‘So what you are saying is more 

places need to create more models to get more competition in this 

area. If industry, if consumer groups, if other are not creating models, then there is no competing model. And until there is a competing model, this is the one we are going to go with.’’ And typically the answer is, ‘‘Yes, we only have one model,’’ or ‘‘This is the 

one that is used by certain magazines, and so this is the one that 

we go with.’’ 

Somehow we have to get greater competition in the economic 

models, and I am sure every economist in the country is somehow 

excited about the new entrepreneurial opportunities that I am presenting there. But we have to get more voices into this because, for 

instance, on the cost-benefit analysis, you take any rule and say, 

well, if we do this, it also creates this certain benefit for a child 

with asthma or whatever it may be in the future. I do not know 

of any of them that also would take Mr. Chambers’ research and 

would say, yes, I know, but it also reduces their poverty, which 

means they will have greater access to housing and food and transportation and greater job opportunities. So does that weigh in the 

model? And I do not know of any of them that do. And, Mr. Chambers, you may know of some of them that do, but they tend to look 

at this may affect asthma, but, yes, what will it do to heart disease 

and other things because they have better access to better-quality 

food and to be able to get that shift? 

It is the challenge of trying to get an economic model that includes everything, and one of the things that we have to have is 

greater access to more modeling on this to be able to have greater 

conversation among economists and to get better data and information. I do not know how we get there initially, but we have to be 

able to work toward that. Senator Heitkamp. 
15 

Senator HEITKAMP. And I am not here to pick a fight, but, Mr. 

Chambers, if you look historically—and as somebody who has been 

a student of environmental changes—isn’t it true that people living 

in poverty experienced environmental degradation in their communities at higher rates historically? 

Mr. CHAMBERS. It is a very interesting question. It is not one 

that I have studied myself, so I really cannot—— 

Senator HEITKAMP. But my point to you is that if you take this 

to the extreme and you eliminate regulation, we have seen that. 

We have seen it in the 1930s, the 1940s, and the 1950s where hazardous waste sites were typically located in lower-income neighborhoods, where lower-income people suffered a higher rate of health 

care conditions resulting from environmental conditions, where 

people working in blue-collar jobs suffered higher rates of injury in 

the workforce, so I am not picking a fight with you. I do not disagree that overregulation and unnecessary regulation can lead to 

consequences of increasing costs for goods and services. But, we 

need to be a little careful because historically, I will tell you, the 

most injured people from the lack of attention to externalities and 

what was happening in the externalities came to people in poverty. 

I do not think anyone sitting here who is a student of history would 

disagree with that. 

Mr. CHAMBERS. Well, I would not interpret my research as giving 

anyone carte blanche to just eliminate all regulations. 

Senator HEITKAMP. Right. 

Mr. CHAMBERS. I would agree with you, one needs to preserve 

regulations that protect the poor, the environment, vulnerable populations. But I think what my research shows is that there is this 

unintended feedback effect that we need to be cognizant of and that 

we need to dial in and find truly wasteful and inefficient regulations. 

Senator HEITKAMP. So let us go back to the coal dust problem. 

A lot of people will look at that as respiratory, but coal dust is a 

dangerous explosive. And so when do we do a cost-benefit analysis 

on the potential that not implementing policies to the lowest common denominator that is possible at the time while we still continue to allow coal mining, which I think we should, but we have 

that embedded catastrophic event that could happen, Mr. 

Shelanski, that creates that kind of nuance in regulatory cost-benefit analysis. 

So take a sugar factory. Sugar is explosive. Take an anhydrous 

factory, which we now find out that that was done on purpose, but 

there was an overregulation response to what happened there. So 

we have to find that balance, the balance in your example of 15 

miles an hour on the freeway. Everyone would think that is crazy, 

but yet it probably would prevent most freeway deaths. But we are 

willing to accept some risk to basically improve the benefits to the 

economy and the benefits to convenience and whatever else that we 

are measuring. 

So how do we deal with the catastrophic event, the potential of 

a catastrophic event? And that is for you, Mr. Shelanski. 

Mr. SHELANSKI. Thank you very much, Senator Heitkamp. Catastrophic events are a very difficult thing to take into account. I will 

tell you how I think we should take them into account. I will give 
16 

you an example. And I will tell you how we should not take them 

into account. 

One approach is a precautionary principle to say that we must 

regulate to the level where we eliminate all possibility of the catastrophic event. That is something that is used in a number of 

places, but it is an extremely costly way to proceed. And it is a very 

tough thing for society to say, look, certain activities have this 

small tail risk of something catastrophic happening. But it is a 

beneficial economic activity for society. If we regulate it to the 

point that we eliminate all possible risk, we will raise the price of 

the product; we will reduce the ability of businesses to survive in 

the industry; we will reduce employment; we will reduce all the follow-on growth that comes from use of that product. Anhydrous is 

a very good example. Bakken crude, if I may, is a very good example. So if we were to eliminate all tail risks through a precautionary principle, my own view is that is too costly a way to proceed. 

So how should we proceed? You can put a probability value on 

these very tail end risks, and you can assess that what the costs 

of those tail end risks are. You can model them, or you can use real 

examples of where there has been an explosion, what was the damage to life and property? And you can figure out, OK, in our costbenefit analysis of whether or not a rule should be put in place, we 

can take the expected value or the expected harm from that tail 

risk, and we can build it into our expected benefits from the rule. 

The example I will give you of where we went through this process was the tank car rule that the Department of Transportation 

(DOT) did over the course of the Obama Administration. This was 

one of the most hard-fought rules. You had these terribly compelling things that have happened and destroyed communities because 

of explosions of tank cars. 

Now, in almost every one of those cases, there was some interesting additional factor like a very high rate of speed or an engineer that had left the locomotive, things like—and was not able to 

brake in time. There were human factors, there were additional 

factors. But you could not get away from the fact that had there 

been a different kind of tank car, a different kind of substance in 

the tank, you would have reduced that. 

So there was a rush to immediately regulate and solve all the 

problems, and the initial rule that came across would have made 

it almost impossible to get crude out of the Bakken because basically the existing stock of tank cars would have been deemed unavailable. It would have required rail companies to put in place 

braking systems that were unproven and extremely costly. And it 

would have put in place rates of speed on the rail lines that would 

have made it impossible for food distribution centers to get food 

from all around the country because, guess what? We run different 

kinds of freight on the same rails, and if you are running one train 

at 18 miles per hour, you are going to stack everything up behind 

it. 

So unpacking all of those costs made it immediately clear that 

eliminating the tail risk was going to be far too costly. So we said, 

OK, putting in place, and this sounds like a heartless and cold 

thing to do, but it is what we do in regulation. You have the value 
17 

of a statistical life. What is the value of the life lost? You put a 

number on that. It is usually around $10 million. What about the 

injury? What about the cost of property? What do we think the average cost of one of these events will be? The probability is extremely low. Let us multiply it by that cost and factor that into our 

cost-benefit analysis and see where that takes us on the safety 

spectrum. And I think we ultimately got to a non-precautionary but 

nonetheless beneficial safety standard. 

Senator HEITKAMP. I want to make a point about that regulation 

before I turn it back to the Chairman. Early on, even before the 

high-profile events, there was a request to DOT to regulate, to sit 

down with us and let us—we know we needed a new generation of 

tank cars. DOT did not engage, and as a result, the industry created their own standard and started building new tank cars, all of 

which, because of the failure to address this issue before the catastrophic events, all which led to increased costs and retrofits. 

And so it is an example that I frequently use which is the lack 

of engagement by regulators can sometimes also increase the eventual cost of regulation, because you have not given the certainty 

and things change. And so I think it is a great example of kind of 

the challenges that we have. None of us want to be heartless, but 

the challenge that we have in trying to identify that area of risk. 

And I just want to say one other thing. Way too often these kinds 

of regulations come in the aftermath of a catastrophic event or the 

aftermath of something that intervened that now there is a big 

rush to judgment. 

Probably a good example of that is Dodd-Frank. We just rolled 

back some Dodd-Frank regulations because it went way too far. So 

we have to have a more orderly process so it is not reactive, it is 

proactive in terms of how we need to address these issues. 

Senator LANKFORD. Thank you. Senator Carper. 

OPENING STATEMENT OF SENATOR CARPER 

Senator CARPER. Thanks, Mr. Chairman. Good morning, everyone, thanks for joining us. I enjoyed reading about your backgrounds, especially Howard, whom I have actually known for a 

while. It is nice to see you all; especially I want to welcome you 

back. You have sat at this table more than a few times, as I recall, 

and oftentimes giving us good advice, and we will ask for some 

more of that today. 

Hi, Howard. Do you think there is any prospect for consensus on 

this panel? I understand this is like we have one minority witness 

and three majority witnesses. I am told they are especially smart 

and eager to find consensus on tough issues. Where do you think 

the consensus lies with this panel maybe on some of these subjects 

that we are talking about today? 

Mr. SHELANSKI. I actually think there is quite a bit of consensus. 

Senator CARPER. I love that. Do you want to talk about it? 

Mr. SHELANSKI. So I would say that there is going to be some 

significant difference in what we think the impacts of regulatory 

burden are, but no difference of opinion on—or the magnitude of 

those regulatory burdens and the extent to which we can tie certain effects to those regulatory burdens, but there is no disagreement on this panel that regulatory burdens are to be minimized 
18 

consistently with achieving health and welfare benefits for society. 

There is no difference of opinion on this panel about the need to 

be sensitive to the differing impacts of regulation on businesses of 

different sizes and the need to preserve the economic growth and 

access to economic opportunity that comes through small businesses. And I think that there is, fortunately—and this is something that would not have been the case maybe a few years 

ago—no difference of opinion on this panel about the need for rigorous and careful cost-benefit analysis and good data. 

Senator CARPER. Good. I do not usually ask yes or no questions, 

but I will in this case. Dr. Chambers, are you a professor at Salisbury University? 

Mr. CHAMBERS. That is correct, Senator. 

Senator CARPER. Is that just south of Delmar, Delaware? 

Mr. CHAMBERS. Right. We are about 15 minutes south of Delaware. 

Senator CARPER. Delmar, Delaware, part of Delmar is in Delaware; part of it is in Maryland. We describe Delmar as the town 

that is ‘‘too big for one State,’’ so we are happy that you are here. 

I am going to ask each of you, do you agree with anything Howard has said? Do you agree with anything he just said in terms of 

consensus? 

Mr. CHAMBERS. Generally, yes. 

Senator CARPER. OK. Ms. Kerrigan. 

Ms. KERRIGAN. Yes, absolutely, particularly the piece on disparate impact on small businesses and entrepreneurship. 

Senator CARPER. Good. Ms. Ghazal? 

Ms. GHAZAL. We definitely agree, particularly on economic 

growth. 

Senator CARPER. OK, good. I will start and I will just go down 

the line. We will start again with Howard. Any thoughts about 

what we ought to be doing here in Congress to better ensure that 

we are adequately overseeing the regulatory rollback activity that 

is occurring in this Administration? 

Mr. SHELANSKI. Thank you, Senator. 

I have a few thoughts. First of all, I do think that regulatory reform is a worthy legislative endeavor, and you know, there was certainly controversy about that. I do not think I was allowed to come 

out and say that plainly when I was in office. 

Senator CARPER. But now you are a free man. 

Mr. SHELANSKI. And Senator Lankford and I and Senator 

Heitkamp and I had conversations at that time. I do think that 

there are some things that could be fixed. I do think that independent agencies should not have any less of an obligation to justify the costs and benefits of their rules. 

Senator CARPER. We seem to be hearing that more and more. 

Mr. SHELANSKI. Yes, and I have always thought that. I never 

wanted to have them under my jurisdiction as though I were administrator for a number of reasons. But they should have the 

same requirements. And I do think that there are things that are 

in the Executive Order that could be usefully elevated to codification. So I do think that there are some things that really could be 

done, and that would prevent agencies that would seek to potentially bypass OIRA review and the rigor there. 
19 

Senator LANKFORD. Just for the record, may I interrupt for just 

a moment? When you said some things in the Executive Order, 

there are about 14,000 Executive Orders. Can you name which 

one—— 

Mr. SHELANSKI. Let me be very clear. For OIRA Administrators, 

there is one Executive Order. 

Senator LANKFORD. 12866. 

Mr. SHELANSKI. It is 12866. 

Let me talk about another one that I really like: 13777 that this 

Administration, that President Trump’s Administration has issued. 

I think the effort to create a regulatory review officer in each agency that has responsibility and accountability and a reporting obligation and a mandate to make retrospective review an ongoing 

function within the agencies is an excellent one, so long as the resources are provided along with that. 

In the Obama Administration, we sought to do that under Executive Orders 13610 and 13563. We got together the Deputy Secretaries. We got them to create these working groups. We required 

them to report every 6 months on their retrospective review efforts. 

The President himself was quite engaged in those. 

Senator CARPER. Yes, he was. 

Mr. SHELANSKI. He came to one of those meetings and really emphasized that this was personally important to him. I think that 

many of the things in 13777 are worthy permanent objectives of 

agencies. 

An Executive Order I would not like to see codified and one that 

I have strong differences with, on the other hand, is 13771, the 

PAYGO two-for-one kind of rule. I would be happy to expand on 

why not, but I do think there are significant problems. Even if one 

can understand that as an incentivizing device to observe a regulatory budget and to be careful about issuing new rules, I think 

any kind of forced mandate to repeal rules is actually contrary to 

cost-benefit principles because we should look at a rule, if it is still 

having benefits that exceed its costs, we might want to fix it to 

make those benefits even higher and those costs even lower. But 

it makes no sense to have some kind of forced requirement to repeal those rules unless there is really compelling evidence that we 

have hit a level of cumulative regulation where, when looked at as 

a whole, the marginal benefits of that one rule are coming at some 

greater cost to GDP. 

I do not see the evidence of that. I have not seen in the economic 

literature sufficiently robust evidence of that. That is an area 

where we do need more competition and economic research and additional empirical research, and I really commend Dustin for being 

one of the few people who is out there contributing very actively 

to that empirical literature. But I do not like the two-for-one Executive Order. 

Senator CARPER. Good. Thank you. I am out of time. Could I just 

ask one of the witnesses to just kind of respond to—OK, thanks. 

I will go to one of my other 12 hearings that are underway. 

Senator HEITKAMP. You have a lot of people behind you. 

Senator CARPER. I can see. I just have a question of Ms. Ghazal. 

Would you respond to some of what Mr. Shelanski just said. Do you 
20 

think he is off his rocker? Do you have anything that you think you 

might agree with? 

Ms. GHAZAL. There is much we agree with, but I guess the point 

I want to make on behalf of my members is that it is not really 

any one single regulatory change that has made the difference in 

how CEOs are feeling at the Business Roundtable. It is really the 

whole direction. So it is partly one in, two out, and there are definitely some aspects of Executive Order 13777, particularly the 

things that Howard talked about. But it is more than the whole 

sentiment. Our President and CEO, Josh Bolten, recently said the 

same thing, that it is really the sentiment that business leaders no 

longer have to anticipate the next regulatory hammer. There is a 

lot more certainty, the fact that all the agencies were asked to ask 

for comments and looking at what is on the books. So it is the 

whole change in philosophy. 

Now, we also like the regulatory officer idea—the regulatory task 

force. We like that, again, the Administration has asked for input 

on regulations. We very much like the Executive Order on permitting and all the aspects of that. But, again, I think our bigger point 

today is to say that it is the entire philosophy that has changed 

and really brought a different sentiment. 

Senator CARPER. All right. Thanks. I wish I had time for Ms. 

Kerrigan and Dr. Chambers, but I probably do not. I do not want 

to get on the bad side of my colleagues here who were kind enough 

to let me—Ms. Kerrigan, did you want to just quickly say something? Please. 

Ms. KERRIGAN. Well, I think in terms of looking at the Executive 

Orders and what the agency is doing, I think there is a role for 

Congress to see what the outcome is. For example, there are a lot 

of positive things that are happening because of the Executive 

Order. Specifically, the SBA Office of Advocacy has been doing a 

lot of small business outreach, and they have identified scores and 

scores and scores of specific regulations that are candidates for potential reform, repeal some type of changes. And all that feedback 

is going right to the heads of the agencies, as well as the Department of Treasury, so Advocacy is communicating with all the Federal agencies: Here are things that you can do to help small business. And it would be great to have some type of accountability in 

terms of, well, what are the agencies doing and the feedback that 

they are getting from small businesses on these specific regulations 

and how they could be made better, how could they be reformed, 

repealed, or whatever. 

Senator CARPER. All right. Thank you. 

My time has more than expired. I would just like to conclude 

with—I have talked about this in the Environment and Public 

Works Committee, which is one of my other committees. About 10 

or 12 years ago, I think, Senator Lamar Alexander and I—and 

maybe George Voinovich from Ohio—were meeting with utility 

CEOs from—there were, I do not know, about seven of them from 

all over the country, and we were talking about legislation to reduce the emissions of sulfur dioxide, nitrogen dioxide, mercury, and 

CO2, and we have been talking about—the President has a proposal called ‘‘Clear Skies.’’ He called it ‘‘Clear Skies.’’ And Lamar, 

and I think George, and I had a proposal called ‘‘Really Clear 
21 

Skies.’’ And we got to about the end of the hour-long discussion, 

and one of the CEOs just like said, ‘‘All right. Here is what you 

should do.’’ It was like he gave the benediction. He said to us, 

‘‘Here is what you should do with respect to these emissions from 

utilities.’’ He said, ‘‘Tell us what the rules are going to be. Give us 

a reasonable amount of time and some flexibility, and get out of the 

way.’’ 

That is really what he said. ‘‘Tell us what the rules are going to 

be. Give us a reasonable amount of time and some flexibility, and 

just get out of the way’’—which I think is what EPA in the last Administration tried to do with the Clean Power Plan, which has an 

implementation that is over 20 years to actually do it. And I think 

there are not a whole lot of my colleagues here, but this is hugely 

important stuff. And I just want to commend our Chair and our 

Ranking Member for pulling us together, and thank you very much 

for coming in. We will probably come back to you, especially the 

folks who live in our neighborhood, come back to you again to follow up on this conversation. But thanks. Great to see you all. 

Thank you. 

Senator LANKFORD. Thanks, Senator Carper. 

Ms. Kerrigan, let me ask you a little bit about small business. 

I want to drill down on that a little bit more. What would help 

small businesses right now on the regulatory side as far as a 

framework that went around them? And let me give you some 

ideas that have been kicked around. 

One is to make sure that what the small business advocacy folks 

have asked for actually happens, and that is, small business folks 

are at the table when there is a dialogue about a rule. Would that 

help? And how would that work when a new regulation is being 

proposed to really make sure that small businesses are there? 

Ms. KERRIGAN. I think it is vital that small businesses and entrepreneurs be at the table at the very early end of the regulatory 

process, that the regulators hear from them directly in terms of 

what their ideas are for regulating or a specific regulation they 

may have proposed, so that they can get their feedback in terms 

of—and perhaps good feedback as well. I mean, it is not all about 

cost. It is not all about this is going to kill us. Ways that they can 

make the regulation better, and perhaps some of the unintended 

consequences I think is very important to look at, and indirect 

costs. 

Senator LANKFORD. Let me drill down on that because that was 

actually going to be my next question. When you talk to a small 

business person, they do not break up direct costs and indirect 

costs because indirect costs affect them just as much as direct costs 

do. But that is a challenge for regulators and for folks that are developing the model to be able to get direct and indirect, because it 

is hard to be able to determine what is indirect. How would you 

recommend that? Because for a small business, that is a really big 

issue for them. 

Ms. KERRIGAN. Well, when you are talking to a small business 

owner and you are talking to them about a proposed regulation, a 

good example is this: If there is a financial regulation or a banking 

regulation or something like that, what you have to build into that 

is, again, the indirect costs in terms of what does that mean for 
22 

capital access or availability of lending. It does have a huge impact 

on this sector, not only small businesses but also startups that 

need that type of capital to start and grow. 

So I think just talking to business owners about—any industry 

in general, about how that is going to—the ripple effects and identifying those ripple effects, then you can begin to include that into 

the model. I am thinking a lot about access to capital because there 

are so many regulations, either on the books, obviously ones that 

have been changed through the last banking reform bill that 

passed, because that is just one of those issues that really does not 

look at what the impact would be on lending and capital. 

Senator HEITKAMP. I just have one quick question, because I 

have to get to another appointment. But, one of the concerns that 

I have—and you all have talked about the optimism and everything 

that is going on right now, that can change tomorrow—not tomorrow, but it can change with a political change. And so our job is 

to provide systemic, long-term certainty so that you know what the 

rules are and that we can advance them, whether it is for small 

business, whether it is for large business, and I am the prime sponsor on RAA. We have been doing a lot on trying to codify—got beat 

up pretty bad on the independent agencies, then beat up pretty bad 

on a lot of this. But I am committed to doing it, but we have to 

be realistic about what we can get done in this time period. And 

I would really recommend that people not live in a world where 

you are going to let political wins decide how we are going to manage this issue. We have to come to some kind of broader consensus, 

and that is what is critically important for me. 

I said it yesterday. I said, that is good, and it may be perfect 

from someone’s standpoint, but I want to get something done. And 

so I think it is that getting something done that we can figure out 

what is in the middle that really does work. 

And so my great apologies. This has been a great panel. Mr. 

Chairman, thank you so much, and all of you for your time and 

your continued involvement. I am trying to make this business climate even better for Americans long term, but also recognizing the 

critical importance that regulation plays in health and safety in 

our country. 

Senator LANKFORD. Thank you, Senator Heitkamp. 

OK. We are going to go into a speed round because I want to 

cover a bunch of different topics with you as well. And let me just 

make a comment about what Senator Heitkamp was saying on consistency. Consistency is extremely important for business and for 

planning. Anytime you are investing capital, you want to know 

what the regulations are now and what they are going to be, and 

if there is a perception that the next Administration is going to 

change the rules based on their political perspective, you cannot invest any capital, you cannot do any planning. And we are not in 

best science land anymore where you started, Mr. Shelanski, before 

saying let us get best science and information. If each Administration is changing their perspective on regulations and it is their 

‘‘best science of the day,’’ that is not best science. That is politics. 

That is I go out and find the model that helps me to do what I 

want to do and then I do it. We are not in best science. So I do 

want to bounce a couple questions off quickly. 
23 

Mr. Shelanski, I had asked Ms. Kerrigan about direct and indirect costs. It is one thing for the small business owner who sees 

it. It is a different thing for a regulator trying to be able to manage 

how you set a policy in place for counting direct and indirect costs. 

Small businesses are disproportionately affected by that. Mr. 

Chambers talked about that. Ms. Kerrigan talked about that. How 

do we manage the issue on small businesses in direct and indirect 

costs when a new regulation is coming down, not just making sure 

they are heard, but helping calculate the costs. 

Mr. SHELANSKI. Thank you, Senator. So I do think it is very important to think about the fact that small businesses are not just 

producers; they are consumers of all kinds of inputs that they have 

to buy for their businesses. So the industries that produce those inputs, to the extent that they may have regulations that raise the 

cost of what they are providing, they are raising the costs of small 

businesses. And what we need to figure out is two things: whether 

or not they are raising the costs to the point that the viability and 

the access to the marketplace for those small businesses is being 

compromised; and, second of all, whether the position of small businesses versus large firms that can better absorb those costs is 

being compromised so they become not only less viable but, even 

if still viable, less competitive with large firms. 

I think this is something that is an important consideration. You 

do not always have good data, but I think it is absolutely consistent 

with the existing Executive Orders for Executive Branch regulation 

and the existing OMB circulars for those secondary costs to be considered. 

Given that secondary benefits are often considered in rulemaking, I do not see any basis for an asymmetry when it comes 

to costs. 

Senator LANKFORD. OK. That is very helpful. Let me ask you another quick question on it. Small businesses often ask for a warning the first time rather than a fine from a regulator. I know that 

you are helping in the writing portion, not in the implementation 

portion on it as well. But does anyone see an issue with the exception of health and safety issues—I am not talking about an OSHA 

violation, but with the exception of that, do you see an issue with 

small businesses getting a warning the first time there is a violation rather than a fine the first time there is a violation? 

Mr. SHELANSKI. I think there could be good grounds for that for 

certain kinds of paperwork violations. 

Senator LANKFORD. Again, this is not a health and safety issue. 

Mr. SHELANSKI. That is right. These companies do not tend to 

have, to the extent large companies do, whole parts of their business that are entirely devoted to dealing with paperwork and interactions with the Federal Government. They are, therefore, likely to 

make mistakes. It might be the very same person who is in charge 

with key managerial decisions and operational decisions in the 

company that has to come up to speed with the new rule. 

Senator LANKFORD. It is one of my favorite things to do in a 

small business meeting, is to ask: ‘‘How many people got up this 

morning and read the Federal Register?’’ 

Mr. SHELANSKI. Right. 
24 

Senator LANKFORD. So far it has been zero of all the places that 

I have gone and asked that question. Small business folks do not 

have someone reading the Federal Register every day, but yet 

there is this assumption: We wrote it in the Federal Register; you 

should know this regulation; here is a fine. 

Mr. SHELANSKI. Certainly for rules that have only been out for 

a limited period of time, I could see a case where that would be 

a fair outcome. 

Senator LANKFORD. OK. Ms. Kerrigan, do you have a comment 

on that? 

Ms. KERRIGAN. Mr. Shelanski I think said it best, and, yes, a lot 

of business owners really do not know that there are changes in 

a whole range of different types of rules. I think that first-time forgiveness would be terrific for sure. 

Senator LANKFORD. OK. All right. This is very helpful. 

Ms. Ghazal, I made a comment that was a broad comment about 

the growth of business based on the stability of regulations. Do you 

want to add to that at all? I know this has been an issue for the 

Business Roundtable. 

Ms. GHAZAL. Yes, thank you. Certainty and knowing that things 

will not change really can help with planning. So with planning— 

and, again, I mentioned this in my testimony. We survey the CEOs 

quarterly, and we ask them about capital spending, investment, 

and sales and employment. So we ask that four times a year. It is 

definitely up. We think a lot of that is due to the regulatory environment. And with certainty, we can build confidence because we 

do believe that certainty helps with planning; it helps with all of 

those aspects of growth. 

Senator LANKFORD. How do you manage cumulative costs of regulations? Significant regulations have obviously significantly 

slowed as well under this Administration. It has made an incredible difference as far as people getting caught up on it. But the constant statement I hear over and over again is the cumulative effects. This is clearly in OIRA’s window to try to determine what are 

all the regulations coming from everybody’s area. How do you all 

manage that as far as calculate that? 

Ms. GHAZAL. It is difficult. I mean, it is something we hear from 

our members all the time, that that is one of the big challenges. 

If you ask anyone to say what is your least favorite regulation, 

your favorite regulation—we represent all industries with our 

CEOs—but it is definitely a sentiment that it is all of the regulations put together. 

The other issue that comes up quite often is what I mentioned 

on the overlapping jurisdiction and feeling that you are being regulated on one area by multiple places. 

Senator LANKFORD. Mr. Shelanski, how does that get solved? Because this is a constant thing. And Ms. Ghazal talked about, for 

instance, infrastructure construction. The first thing that I hear 

from State and local entities when they talk about infrastructure, 

let us say a highway construction process, is how long it takes and 

how many people and it is linear in your permitting. And if it is 

a county project, it will take 6 months; if it is a Federal project, 

the same project, same area, will take 4 years, and 31⁄2 of that is 
25 

permitting. How do we solve that with just the regulatory issues 

they have to deal with? 

Mr. SHELANSKI. So I think a number of the things that Maria set 

out earlier make just basic common sense. So I would just suggest 

a couple of things: a deadline and a unified single Federal opinion, 

for example, a Federal agency opinion on an environmental permitting issue. 

Senator LANKFORD. When you say a deadline, everybody says, 

yes, but what if I bring additional information to bear, what if 

there is a lawsuit, what if there is—and it goes on and on and on. 

Deadlines do not seem to be deadlines to actually get things resolved. 

Mr. SHELANSKI. Right, and I do not have an answer for you today 

about exactly how one writes that, but I do know that there is lots 

of discretionary ability to lengthen the permitting process. There is 

also sequencing of processes that could be parallel. And then, of 

course, there is the confusion of two different outcomes, even from 

two different offices of the same agency. Those kinds of things have 

to be prevented, and also the sheer number of Federal permits that 

could be required for a single project, and this is something that 

I think Administrations from both sides of the aisle have recognized as a problem. 

Senator LANKFORD. Who manages that? 

Mr. SHELANSKI. Well, so OMB has tried to take the lead in managing through the management side by creating a centralized sort 

of permitting overseer. That had to be done within the structure 

of the existing Executive Branch agencies, and at least during my 

time, there was an effort to put this in the Department of Transportation. 

I think there may well need to be in the first instance—and I 

know this is a bit of a scary word, it does not have the best history—a task force that figures out exactly how many steps are 

there. That has actually been done. Where can we cut the duplication? And then figure out, give somebody the job of basically centralizing and managing the traffic on that permitting. 

Senator LANKFORD. Let me try to clarify this. Are you recommending an entity like OIRA but on permitting? What OIRA does 

for regulations, this entity does for permitting. Or are you recommending that basically OMB creates a set of rules and then we 

function under the rules? 

Mr. SHELANSKI. I think you are going to need somebody who has 

the accountability, who has to come in and implement legislation 

or implement Executive Orders, appear before you and explain 

what they are doing. 

I might make a suggestion that OIRA is not a bad structure in 

which to embed that. There would need to be a new branch in 

OIRA with a serious SES leader who is responsible for that. I think 

that that could be well done, but it would require, I think, some 

legislative help. 

The only other thing I would add is that de-duplication of regulatory jurisdiction is another way to get at both the accumulation 

of regulation and the overlapping permitting issues that come in 

there. The example you gave of USDA and FDA on food safety, I 

cannot tell you how many days of my life I will never get back try-
26 

ing to manage collisions on food safety rules between two different 

issues. There we need some statutory help, but that is another way 

to get at the issue. 

Senator LANKFORD. I would also tell you, I cannot name the 

number of projects that I have had someone in my State call me 

on and to say, ‘‘I am doing my third NEPA review on the same 

project. I was required to do it at the beginning. Then it took too 

long and it expired, and I am still waiting on more Federal permitting, and I had to do another one. And then we got all the way to 

the end of it, and they wanted another one. How many of these do 

I have to do for the same project?’’ I have heard that over and over 

and over again. So this issue about how do we manage the permitting is an unknown, and no one knows which agency to go to first 

and which one is primary in it. And is it FERC that handles that 

first? Is it the Corps of Engineers that handles that? Is it somebody 

else? Where do I go for it? That does have to be resolved. 

Mr. SHELANSKI. If I could just impose for 30 seconds to give a 

specific example of how that might be dealt with. Right now, because of the way the statutes are written, if you have gone too 

long, your data has expired, and your previous authorization is no 

longer valid. 

One thing that could be done is to shift the burden to the agency 

to explain why there really needs to be a new review, and then 

that request for a new review could be run through this hypothetical new office, wherever it is located, with the burden on the 

agency to justify it. That would cut down on this impossible Catch22. 

Senator LANKFORD. Would you just be then waiting for 6 months 

until that agency answers the question on why they do not have 

to do it again? 

Mr. SHELANSKI. Give the agency 30 days or 60 days, or else they 

forgo the right to require it. 

Senator LANKFORD. OK. Let me ask you a question, Mr. 

Shelanski, and I know I am picking on you in some of these things 

as well. But the implementation of rules, when they are first written, and the speed of how they are done and getting the input— 

Ms. Ghazal talked openly about trying to get people—and Ms. 

Kerrigan did as well—about trying to get people to the table to get 

input early, because if you get input early, once the rule is put in 

place, it is a better rule when it is put in place. But you also have 

fewer lawsuits, and it is less cost to the taxpayer and less drama 

as it goes through the litigation process, gets kicked out, starts all 

over again, and goes through everything else. 

How do we avoid that? Do we have a greater need for advance 

notice of proposed rulemaking (ANPRM)? What do we need to do 

to get more input to make sure it is written correctly the first time 

and have fewer lawsuits on the back side? 

Mr. SHELANSKI. So I would start by saying that I think the system we have in place is better than people often give it credit for. 

Certainly the notice and comment, the proposed rule, final rule sequence under the Administrative Procedures Act, putting aside 

OIRA review, I think especially when one looks at comparative systems around the world, does afford a lot more opportunity for early 

engagement. But what you have to make sure of—and this is 
27 

where things sometimes break down—is that the engagement is 

really meaningful. And, of course, your engagement is after the fact 

at that point. It is after an agency might have invested months or 

years in doing the work, and the agency will necessarily be more 

reluctant to change in the face of those comments. 

So I do think that the notice of inquiry and the ANPRM process, 

especially on major rules, really can be quite helpful. And in my 

own view, requiring an ANPRM for major rules—and we might 

want to think about how to define those because 100 million in a 

lot of ways seems fairly low. As I like to tell people, it is the average annual revenue of just two Walmart stores. But major rules 

might be a place where agencies should presumptively do a notice 

of inquiry, presumptively do an ANPRM so that stakeholders of all 

kinds—and there should be, I think, a requirement that small businesses have a seat at that table, are involved early. That would cut 

down on litigation. 

The objection that you will hear to this is that the early access 

will be only on one side. You will get the people who would bear 

the cost of the regulation, not the public that might bear the benefits. So the process would have to make sure to bring in people who 

will be advocating equally for the benefit side of that, and I think 

that is an extremely important aspect of the process. But without 

it being an all-the-time requirement essential mandate, I do think 

that a greater use and a presumptive use of ANPRM in major rules 

is something that could help the process. 

Senator LANKFORD. I know we have been going about an hour 

and a half, and I want to be merciful to you in this process as well 

where I pull things together, and I do appreciate all of your written 

testimony. It is extremely helpful, and the dialogue, to be able to 

have it. And so thank you for submitting that. But I do want to 

provide one last opportunity if somebody else wanted to be able to 

get something on the record orally, to still be able to share that so 

we can get that on the record. Mr. Chambers. 

Mr. CHAMBERS. Just a very cautionary note. If we look at the 

British Columbia experience, they initially sought to reduce regulatory restrictions—not regulations but actual regulatory restrictions—by 33 percent, and they achieved that goal within 2 years. 

If they were running into a situation where they were being forced 

to jettison rules for which the benefits exceeded the costs, one 

would have expected them to put the brakes on very hard at that 

point. But they continued that process and ultimately ended up reducing total regulatory restrictions by 43 percent. 

What proportion of the CFR is red tape for which costs exceed 

benefits? Truly nobody knows the answer to that question at this 

point. But I think the idea of a hair-cutting exercise, which injects 

discipline into the process would be beneficial—and you like to emphasize, Senator, the value of competition. Make regulations compete against one another so that at least the underperformers can 

be weeded out and there is a mechanism to force that to happen. 

That is what I would suggest, and I think that the government 

needs to research this more carefully. I do not know, a panel or 

what entity or mechanism should do that, but I think a long and 

hard look is needed to try to inventory these restrictions and then 

try to figure out what would be a fair and appropriate level of re-
28 

duction. The Canadians did it with interns. Mercatus is doing it 

with computers. You would need a lot of human interaction, obviously, to do a RAI type analysis on each one. But I think there 

needs to be a very close examination of that and some determination made in that regard. 

Senator LANKFORD. Dr. Chambers, we will count on folks like 

you and some of your colleagues to be able to take a hard look at 

some of these things, to be able to bring us good data, and the case 

study of that is appearing in front of our eyes, and it is the United 

Kingdom (U.K.) leaving Brexit as they rewrite all of their regulations to be able to determine the difference between U.K. under 

European regulations and U.K. under regulations, whatever they 

are going to do in the days ahead to be able to figure out what happens to their economy, to poverty, to safety, to health, all those 

things. There will be a side-by-side that is very unique in the modern age to be able to see how the same economy functions under 

two different sets of regulations in the days ahead, and I look forward to a chance to see that research—not to assign you homework, but that type of project just absolutely needs to be done in 

the days ahead. 

Anyone else need to be able to add something to end orally? Ms. 

Kerrigan. 

Ms. KERRIGAN. Just one final thing is there is wisdom in the 

crowd, and we believe public engagement is an important driver of 

good regulatory outcomes. So one of the things that you all may 

want to consider, too, is to perhaps allow response comments to 

comments and to sort of get that interaction going. I think that 

would be very appropriate in the regulatory system. 

And then, finally, I very strongly feel or we feel that no major 

rules should be issued without a plan for future review. I mean, 

what does success look like? How do we measure that we set out 

to do what we said we are going to do in this regulation, and did 

it achieve its intended purpose? 

Senator LANKFORD. Yes, that is something that Senator 

Heitkamp and I have talked about often, what she calls ‘‘prospective-retrospective review,’’ that we plan to look back. 

Ms. KERRIGAN. Yes. 

Senator LANKFORD. OK. Thank you. Ms. Ghazal. 

Ms. GHAZAL. Just one last word on the Regulatory Accountability 

Act, and we cannot let the opportunity pass. So much of what we 

talked about today would be solved if we could just pass that, enact 

it. Whether it is the early engagement with we very much agree, 

small business, we want them. They are our customers, they are 

our suppliers, they are families of our employees. We want them 

at the table, and we think the best way is through enactment of 

the RAA. The same with also looking back, is the regulation doing 

what it intended? 

Senator LANKFORD. OK. Thank you. For all of you today, thank 

you again for being here and for contributing to the ongoing work 

that you do. 

This does conclude today’s hearing. The hearing record will remain open for 15 days until the close of business on October 12th 

for the submission of statements and questions for the record. 

This hearing is adjourned. 
29 

[Whereupon, at 11:32 a.m., the Subcommittee was adjourned.] 

(31) 

A P P E N D I X 
32 

T!,;s administration, through various Executive Orders and policy changes, has taken 

significant steps to reform the administrative process. 

These actions have spurred a marked increase in optimism from individuals and businesses, 

which has resulted in a strong and vibrant economy and lower unemployment 

According to many economists, the recent increases in Gross Domestic Product are the result 

of the certainty that comes through regulatory stability. 

With regulatory relief, businesses have the confidence to plan for the future, re-invest in their 

business, and hire more employees. 

While I applaud the administration's focus on breaking the cycle of piling one regulation on 

top of another. the Executive branch alone cannot provide long-term regulatory stability. 

That responsibility rests with Congress. 

Businesses face uncertainty that comes from one administration to the next. This 

administration has very different priorities from the last one and the next administration may 

very well have di!Ierent priorities from this one. 

This drastic swinging of the pendulum needs to stop. 

'this committee has debated legislation that will set clear guidelines for agencies- not to 

dictate a particular outcome, but simply to require them to complete thorough analysis before 

issuing a rule. 

Common sense things such as measuring the full impact of a rule, consulting with state and 

local governments, and listening to small business owners at all stages of the process are just 

a lew ideas Congress needs to pass. 

I'm optimistic we can find areas of agreement that Congress can act on to provide long-term 

regulatory stability, which in turn will add to GDP and act as a natural defense to possible 

economic recession. 

I've called this the "nerdiest Subcommittee in the Senate" and this morning's conversation 

should live up to that standard. 

With that, I recognize Ranking Member Heitkamp for her opening remarks. 
33 

Hearing before the Homeland Security and Government Affairs 

Subcommittee on Regulatory Affairs and Federal Management 

September 27,2018 

"Examination of the Effects of Regulatory Policy on the Economy and 

Business Growth" 

Testimony of Howard Shelanski 

Chairman Lankford, Ranking Member Heitkamp, and members of the 

subcommittee: 

Thank you for inviting me to testifY before you today. My background as a 

government official, scholar, and practicing lawyer informs my perspective on the 

importance of a sound regulatory system for the U.S. economy and for the health and 

welfare of all Americans. I am currently a Professor of Law at Georgetown University 

and a partner in the law firm of Davis Polk & Wardwell LLP. From July 2013 through 

January of2017, I served as Administrator of the Office oflnformation and Regulatory 

Affairs at the White House. In that capacity, I dealt first hand with the review of new 

regulations and the retrospective assessment of rules already on the books. My previous 

government positions include serving as Director of the Federal Trade Commission's 

Bureau ofEconomics, ChiefEconomist of the Federal Communications Commission, 

and a Senior Economist for the President's Council of Economic Advisors. From 1997 to 

2009 I was on the faculty of the University of California at Berkeley, and before that I 

practiced law in Washington D.C. and served as a law clerk to Justice Antonin Scalia, to 

Judge Stephen F. Williams of the U.S. Court of Appeals, and to Judge Louis H. Pollak of 

the United States District Court in Philadelphia. I am the author or co-author of numerous 

articles and books related to antitrust and regulation. 

I wish to make three points in my testimony today: (I) regulation must be done 

carefully, with rigorous attention to costs and benefits; (2) regulation should take account 

of how its costs might differ for entities of varying sizes; and (3) the same careful 

assessment of costs and benefits that applies to rulemaking should apply to deregulation. 

The criteria for any regulatory reform should be whether it advances the above three 

principles and whether it is neutral in its impact on the weighing of regulatory costs and 

benefits. 

Sound regulation requires rigorous assessment of both benefits and costs 

One of the signature achievements of the U.S. regulatory system over the past 40 

years has been the increasingly central role of cost-benefit analysis. When President 

Reagan signed Executive Order 12291 in 1981, he established the process of centralized 

review of Executive Branch Regulations based on cost-benefit principles. EO 12291 met 

with a cold reception in many quarters on grounds that it would be barrier to sound policy 

and a one-way ratchet toward deregulation. Cost-benefit analysis of federal rules, and the 
34 

Office of Information and Regulatory Affairs (OIRA) tasked with implementing that 

analysis, nonetheless became firmly established. When President Clinton took Office in 

1993, instead of repealing EO 12291 he revised and updated the order into EO 12866 and 

signed amendments to the Paperwork Reduction Act strengthening OIRA. EO 12866 

remains in force to this day, affirmed and expanded by Executive Orders from 

Republican and Democratic administrations alike. 

For purposes of this hearing, I wish to focus on two core principles of EO 12866: 

(I) that the benefits of any regulation must justifY the costs the rule imposes on society; 

and (2) that agencies should regularly review the continuing effectiveness of the rules 

they already have on the books. For purposes of this hearing, I put aside the important 

questions of how well agencies have implemented these two principles and of what 

analytical methods agencies should use. I focus instead on why it is important that 

regulatory reform neither get in the way of sound assessment of costs and benefits nor put 

an undue thumb on the scales toward one side of that balance. 

For cost-benefit analysis to be meaningful, agencies need to take both costs and 

benefits seriously. Unfortunately, polarized arguments that emphasize one of those values 

while ignoring the other too often characterize debates over regulation. For example, 

regulatory advocates have often opposed weighing quantified, economic costs against 

health and safety benefits. Despite occasional statements from advocates that we should 

never trade Jives for lower social costs, however, we do it every day. A speed limit of 15 

miles per hour would save thousands of lives and prevent countless injuries every year, 

yet society would not tolerate the costs of such a rule and no one has seriously proposed 

such a policy. Regulatory costs are therefore an inherent factor in societal decisions about 

what kinds of rules it wants. Even if there is no requirement (and there should not be) that 

a rule's quantifiable benefits always exceed its quantifiable costs, rigorous analysis of 

regulatory costs allows society to know how much it is paying for the policies and 

protections it chooses. 

On the other side of the debate, advocates of non-regulation or deregulation 

sometimes focus too exclusively on the costs of a given rule, without acknowledging or 

accurately accounting for the very real benefits to society that would be lost. In one 

recent, high-profile example, then-EPA Administrator Scott Pruitt went on television to 

promote the EPA's planned repeal of the Obama Administration's Clean Power Plan 

regulations, without mentioning the predicted benefits of those rules. Fox News 

interviewer Chris Wallace pointed out to Mr. Pruitt that the EPA had predicted that those 

rules would eventually eliminate 90,000 asthma attacks, 300,000 missed school and work 

days, and 3,600 premature deaths each year. Mr. Pruitt offered no new analysis to refute 

those benefit figures and had little answer when Mr. Wallace asked him: "without the 

Clean Power Plan, how are you going to prevent such things?" Ignoring regulatory 

benefits cheats society out of sound and desirable rules. 

Beyond serving as illustrative anecdotes, the above examples also hint at an 

important challenge for cost benefit analysis, and one to which regulatory reform should 

be attuned: regulatory costs are often more salient and easier to quantifY than regulatory 

benefits. Regulatory benefits often accrue far in the future and are spread broadly across 

2 
35 

millions of individuals. Moreover, the benefits of regulation, especially to any given 

individual, might be uncertain. For example, the 3600 premature deaths that the EPA 

predicted the Clean Power Plan rules would eliminate were an estimate from a range of 

possible outcomes. Any individual might reasonably be skeptical that she herself would 

be one of the people to live longer were emissions to be reduced-a benefit that in any 

case would likely seem quite remote in time. Regulatory benefits can therefore be less 

salient for people, and their precise level less certain, even when they are large and 

reasonably likely in the aggregate. Regulatory costs, in contrast, are more likely to be 

more salient and quantifiable. The costs of regulatory compliance are usually more 

measurable, more concentrated in where they fall, and more proximate in time than the 

benefits are. Businesses and other stakeholders are therefore more likely to have hard 

information about costs and strong motivation to oppose them. 

The fact that businesses might have access to more quantifiable cost information 

and be highly motivated to push for lower costs is not a criticism-we want reliable cost 

information, and we want the parties with the best access to that information to have 

incentive to engage in the regulatory process. But the fact that costs can be more readily 

quantifiable and more likely to motivate stakeholder advocacy than benefits is important 

because it suggests that the legislative creation of new requirements for the regulatory 

process might not fall symmetrically on the cost and benefit sides of the ledger. Therefore, 

while the most important thing for regulatory reform is to ensure that it advances analysis 

of both costs and benefits in rulemaking, it is also important to ensure that legislation that 

is neutral on its face does not, in actual practice, improperly tilt the analysis of costs and 

benefits in a way that harms society over time. 

Regulation should not disadvantage small businesses 

Regulations should not presumptively exempt small businesses from compliance. 

When there is a strong case that an activity causes harm, that a regulation can effectively 

reduce that harm, and that the costs of reducing the harm are justified by the benefits, 

then there could be a sound basis for applying the rule to all entities that engage in the 

harm-causing activity. That said, the fact that aggregate benefits justify aggregate costs 

does not mean that the costs fall proportionately on firms regardless of size. Larger firms 

might well be in a better position to absorb the fixed costs of regulatory compliance than 

small firms, and those fixed costs might not always vary terribly much for big and small 

firms. A large firm might be able to absorb regulatory costs that might put a small firm 

out of business or at a competitive disadvantage. For small firms that might later want to 

enter the industry at issue, the regulatory compliance costs might be a high barrier that 

prevents them from coming into the marketplace. 

Because small businesses are an important engine of both economic growth and 

economic opportunity, agencies should, to the extent possible, calibrate regulation so that 

it does not impede the creation and viability of small enterprises. Processes put in place to 

assess small business impacts should not become a rate-determining step in promulgation 

of a new rule, however. When a rule is well justified under the principles of the relevant 

statutes and executive orders, the public should get the regulatory benefits even if the 

3 
36 

rule's applicability to properly defined small businesses might be staged, deferred, 

modified, or subject to additional analysis. 

The same principles that apply to making new rules should apply to 

retrospective review or repeal of existing rules 

Retrospective review of regulation is an important, but often neglected, element 

of a healthy regulatory system. The assessment of rules already on the books to ensure 

that they are still achieving their objectives, and doing so at acceptable cost, ensures 

accountability and prevents the accumulation of unwarranted regulatory costs. 

Retrospective review has been a bipartisan aspiration, and was the subject of President 

Obama's EOs 13563 and President Trump's EO 13777. The latter executive order puts in 

place a process that, if faithfully executed according to the principles expressly set forth 

in the text of the order, would launch a more focused and accountable process for 

retrospective reviews. Notably, EO 13777 specifically invokes EO 12866 and EO 13563 

as documents whose principles the regulatory reform process should follow. To the 

extent that this means regulatory review should incorporate sound cost-benefit principles, 

and make use of the best-available science and economics-as those previous executive 

orders require-then I think EO 13777 puts retrospective review on solid ground. If 

benefits that justifY costs are a sufficient basis for a new rule, then benefits that continue 

to justifY costs would be equal reason to keep an existing rule on the books. The costbenefit principles for regulation and deregulation should be generally the same. 

For that reason, regulatory reforms that take the form of "one in, one out" or, as in 

the case of EO 13771, "one in, two out" may be in tension with sound cost-benefit 

analysis. If one generally believes that there are many rules whose costs exceed their 

benefits, then a "pay go" mandate that new rules must be accompanied by repeal of old 

rules makes sense. The pay-go principle then functions as a regulatory budgeting 

mechanism that forces agencies to do the hard work of retrospective review. If, on the 

other hand, rules have been well developed according to the principles of EO 12866 in 

the first place, a forced repeal mechanism makes little sense, and will have the effect of 

preventing agencies from issuing beneficial new rules and/or forcing agencies to repeal 

rules that are still doing good for society. There is little evidence, and indeed evidence to 

the contrary from previous retrospective review efforts, that there is an existing stock of 

costly, ineffective regulations to be readily and efficiently repealed. Moreover, to date 

there is to date little, generally accepted economic evidence that regulation imposes so 

high an aggregate economic burden on the U.S. economy that it would be better for 

society to forego the benefits of that regulation, and indeed a number of facts to suggest 

the contrary. For that reason, retrospective review should be an important, embedded 

feature of our regulatory system, but without mandatory outcomes that are contrary to 

sound cost benefit analysis. 

Conclusion 

Regulatory reform that reinforces the principles ofthc executive orders that have 

guided regulatory review by all administrations since President Reagan could benefit 

American citizens and businesses alike. There is room for regulatory reform to improve 

4 
37 

and reinforce the principles of cost-benefit analysis and the use of the best economic and 

scientific information; to improve the flexibility of regulation in its application to small 

businesses; and to further institutionalize and advance the process of retrospective review 

of regulation. The challenge lies in the details, for any such reform must achieve its 

objectives without systematically shifting the balance against regulatory benefits, and 

without so burdening the rulemaking process that even clearly beneficial rules become 

difficult for agencies to propose and publish in an effective manner. 

5 
38 

Ill MERCATUS CENTER 

~~~ George Mason University TESTIMONY 

THE REGRESSIVE EFFECTS OF FEDERAL REGULATION AND A 

ROADMAPFORREFORM 

Dustin Chambers 

Senior Affiliated Scholar, Mercatus Center at George Mason University 

Professor of Economics, Perdue School of Business at Salisbury University 

Senate Committee on Homeland Security and Governmental Affairs, Subcommittee on Regulatory Affairs and Federal 

Management 

Examination of the Effects of Regulatory Policy on the Economy and Business Growth 

September 27, 2018 

Good morning, Chairman Lankford, Ranking Member Heitkamp, and the members of the committee, I 

thank you for inviting me to testify. 

My name is Dustin Chambers, and I am a professor of economics at Salisbury University and a senior 

affiliated scholar with the Mercatus Center at George Mason University. My research focuses on 

income inequality, economic growth, and the regressive effects of regulation. Any statements I make 

reflect only my opinion and do not necessarily reflect the opinions of Salisbury University or the 

Mercatus Center. 

I would like to begin by thanking Chairman Lankford and Ranking Member Heitkamp for their 

leadership in holding this hearing focusing on the often overlooked topic of regulatory policy, I am 

honored to be invited to speak on the panel this morning for what I hope to be a productive discussion 

on regulatory reform. 

My testimony today focuses on three unintended consequences of an expanding and complex body of 

federal regulations: 

1. Regulations reduce economic growth and GDP, thereby reducing living standards for most 

Americans. 

2. Regulations harm small business. 

3. Regulations increase poverty rates and disproportionately increase consumer prices paid by 

the poor. 

I conclude testimony by sketching a possible road map for reform based on the British Columbia Model. 

I am happy to answer any relevant questions you have to the best of my knowledge. 

THE NEGATIVE IMPACT OF FEDERAL REGULATIONS ON GOP 

The creation and enforcement of regulation is an important function of government, Regulations, when 

appropriately applied, can protect consumers from harmful products, workers from unsafe conditions, 

promote stewardship of the environment, and protect citizens from government excesses. Ideally, 

For more information or to meet with the scholar, contact 

Mercatus Outreach, 703-993-4930, mer·catusorutr<racrr(iifn1erc:atus.qrnu.•edu 

Mercatus Center at George Mason University, 3434 Washmgton Btvd., Virginia 22201 

The ideas presented in th1s document do not represent official positions of the Mercatus Center or George Mason University. 
39 

government regulation should concisely and clearly articulate guide rails for public and private 

conduct, thus establishing universally understood "rules of the game." Government regulation that 

extends beyond these limited and prudential functions are difficult to justify on economic grounds, and 

can act as a drag on economic growth. 

As long as ago as 1979, Milton Friedman openly speculated that declining US productivity was due in 

part to rising federal regulation. Lacking a precise measure of regulation, Friedman, like many 

observers, used page counts in the Federal Register as an indirect measure of the pace of annual 

regulatory growth. In 1936, its inaugural year, the Register comprised a mere 2,599 pages. Just 30 years 

later, the 1966 Federal Register had expanded to 16,850 pages, a 6.4 percent average annual growth rate 

over the period.' By 2016, the page count in the Federal Register reached its zenith, peaking at 95,894 

pages, a 3.5 percent average rate of annual increase over the half century since 1966. In 2017, the page 

count of the Federal Register shrank to 61,950 pages, still a large number by any standard, but the 

slimmest volume since 1993.2 

The Federal Register is a crude proxy for federal rule rulemaking because it contains proposed new 

rules and rule rollbacks and because rules vary in length. Consequently, regulation researchers began 

using page counts in the Code of Federal Regulations (CFR) which codifies the total stock offederal 

regulation. A 2013 study using this improved measure of total regulation to estimate the effect of federal 

regulation on physical capital, labor, US productivity, and ultimately GDP, concluded that federal 

regulations reduced the annual rate of US economic growth by 2 percentage points between 1949 and 

2005, and that the cumulative loss of output between 1949 and 2011 equaled a staggering $38.8 trillion.' 

While an improvement over the Federal Register, the use of page counts in the CFR suffers from many 

shortcomings. First, page counts are an imprecise measure of total regulatory rules. Second, and more 

importantly, total measures of regulation do not tell researchers the industries to which the regulations 

apply. Ideally, regulation counts should be matched by industry so that we can trace the impact of rule 

changes with more microeconomic granularity. This became possible through the use of computers and 

machine learning, resulting in the release of RegData 1.0 in 2012.< Prior to RegData, anyone seeking to 

manually analyze a single year of the CFR would have to read a volume of pages that, when ]aid out end 

to end, spans over 20 miles and contains nearly 104 million words. For a full-time employee reading 250 

words per minute, this is a 3.3 year task.5 The latest version ofRegData (version 3.0) has identified just 

under l.l million regulatory restrictions and probabilistically matched these restrictions to industries up 

to the 6-digit North American Industrial Classification System (NAICS) code level.6 Using this treasure 

trove of new data, researchers have begun to more accurately estimate the impact of regulations on 

GDP, small businesses, consumer prices, and poverty. 

A 2016 research study using RegData found that regulations trimmed about 0.8 percentage points from 

the annual rate of US economic growth between 1977 and 2012.7 To put this finding into perspective, if 

1 Milton Friedman and Rose Friedman. Free to Choose (New York: Harcourt. 1979). 2 Clyde Wayne Crews, "Trump Regulations: Federal Register Page Count Is Lowest in Quarter Century," CompetWve Enterprise 

Institute. December 29. 2017. 3 John W. Dawson and John J. Seater, "Federal Regulation and Aggregate Economic Growth," Journal of Economic Growth 18, 

no. 2 (2013): 137-77. 

'QuantGov, "The History of RegData." accessed September 20,2018. https://quantgov.org/regdata/history/. 

5 QuantGov. "The QuantGov Regulatory Clock," accessed September 20, 2018, https:/ /quantgov.org/charts/the-quantgovregulatory-clock/. 

6 Patrick A. Mclaughlin and Oliver Sherouse. "RegData 2.2: A Panel Dataset on US Federal Regulations." Public Choice. Online 

First Articles (2018): 1-13. https:/ /link.springer.com/article/10.1007%2Fsll127-018·0600-y. 

7 Bentley Coffey. Patrick Mclaughlin, and Pietro Peretto estimated the effect of federal regulations using a 22-industry model of 

the US economy. See Bentley Coffey. Patrick A. Mclaughlin. and Pietro Peretto. "The Cumulative Cost of Regulations" 

(Mercatus Working Paper, Mercatus Center at George Mason University. Arlington. VA, 2016). 

2 
40 

the total number of regulations had been frozen between 1980 and 2012, the US economy would have 

been $4 trillion (or 25 percent) larger in 2012 than what we actually experienced. In per capita terms, 

the lost output in 2012 alone equaled just under $13,000. Both of the foregoing studies," despite using 

very different measures of regulation and very different models of the US economy, reach very similar 

conclusions: regulations produce a serious drag on economic growth rates resulting in very large losses 

in cumulative output over the long run. Even deceptively small reductions in the rate of economic 

growth, when compounded over several decades, have a profound impact-this is reflected in the quote 

often attributed to Albert Einstein describing compound interest as the most powerful force in the 

universe. Indeed, if the long-run rate of real economic growth, which averaged 3.2 percent between 

194 7 and 2018, were to be increased by 0.8 percentage points (from 3.2 percent to 4.0 percent), the 

resulting fast-growth US economy would be just over twice as large as our slower growing economy in a 

century. Such profound growth will likely do more for to eliminate absolute poverty than any wellintentioned government program. 

THE NEGATIVE IMPACT OF FEDERAL REGULATIONS ON SMALL BUSINESSES 

Although the overall cost of regulations is substantial, there is new and disturbing evidence suggesting 

that smaller businesses shoulder a disproportionate share of the compliance costs borne by private 

industry." Regulation reduces both employment growth and total new firm creation at the industry 

level. Specifically, a 10 percent increase in federal regulations is associated with a 0.47 percent 

reduction in new firm formation and a 0.63 percent reduction in new hires. Interestingly, when 

controlling for firm size, this effect is only statistically significant for small firms. Moreover, the rate of 

large firm deaths (i.e., failures or exits) actually declines in response to rising regulation, suggesting that 

large firms are better suited to survive the pressures of higher regulation. In a similar study published 

this year (2018),'0 I, with my coauthors, find that rising regulations have a disparate impact on small 

businesses within an affected industry. In particular, a 10 percent increase in federal regulations is 

associated with a 0.5 percent reduction in total small firms, while the impact on large firms is 

statistically insignificant. Moreover, consecutive years of rising regulation within an industry has a 

compounding effect, wherein the negative effects of higher regulations are amplified if preceded by one 

or two years of above-average regulation growth. For example, a 10 percent increase in industry 

regulations, if preceded by two years of above average growth in regulations, is associated with a 1 

percent decline in the total number of very small firms (firms with fewer than five employees). 

It is reasonable to suspect that large firms can more easily afford to hire compliance-related personnel 

(e.g., lawyers and accountants) and spread the resulting compliance costs over a larger volume of 

output than small firms and especially sole proprietorships (where compliance burdens fall squarely on 

owners). This may hasten the exit of some entrepreneurs or deter the entry of new firms. 

Unfortunately, many policymakers mistakenly assume that small businesses are not harmed by 

regulation due to small business exemptions. Despite Congressional efforts like the Regulatory 

Flexibility Act of 1980 and the Small Business Regulatory Enforcement Fairness Act of 1996, small 

businesses still must spend time and money reviewing new rules to determine if those rules apply to 

their business, and if so, apply for exemptions or waivers, which still must be granted by regulators. 

Researchers who have studied this issue have found that small business concessions vary greatly by 

regulatory area and that their overall effectiveness is mixed.U 

8 Dawson and Seater, "Federal Regulation and Aggregate Economic Growth"; Coffey, McLaughlin, and Peretto, "The Cumulative 

Cost of Regulation.'' 9 James Bailey and Diana Thomas, "Regulating Away Competition: The Effect of Regulation on Entrepreneurship and 

Employment" (Mercatus Working Paper, Mercatus Center at George Mason University, Arlington, VA, 2015). 10 Dustin Chambers, Patrick A. Mclaughlin, and Tyler Richards, "Regulation Entrepreneurship, and Firm Size" (Mercatus Working 

Paper, Mercatus Center at George Mason University, Arlington, VA, 2018). 11 For small business concessions by regulatory area, see Ryan Keefe, Susan Gates, and Eric Talley, "Criterfa Used to Define a 

Small Business in Determining Thresholds for the Application of Federal Statutes" (Working Paper, RAND Corporation, Santa 

3 
41 

THE REGRESSIVE EFFECTS OF FEDERAL REGULATIONS 

Furthermore, businesses located in poorer areas tend to be smaller than those located in more affluent 

areas,U implying that any disparate negative effects of regulations are likely to be amplified in the most 

economically vulnerable communities. In a recent study," I, with my coauthors, find that more federal 

regulations are associated with higher poverty rates at the US state level. Specifically, we find that a 10 

percent increase in the federal regulatory burden on a state is associated with a 2.5 percent increase in 

the state poverty rate. Unfortunately, the regressive effects of federal regulations also harm poorer 

households in the form of higher consumer prices. 

In another 2018 study,14 we combined regulation data from RegData with consumer expenditure and 

pricing data from the Bureau of Labor Statistics, and estimated that a 10 percent increase in federal 

regulations is associated with a 1 percent increase in consumer prices. Although this result is 

predictable, as regulatory compliance is costly and firms will attempt to pass these costs onto 

consumers in the form of higher prices, we also determined that the poorest households (those in the 

bottom 20 percent of the income distribution) spent on average a larger share of their income on the 25 

most heavily regulated goods than any other income group. Not surprisingly, these poor households 

faced an average inflation rate of 2.46 percent per year, far higher than the 2.08 percent average 

inflation rate experienced by households in the top 20 percent of the income distribution. These 

findings are particularly disturbing given that one of the principal goals of government regulation is the 

protection of vulnerable populations. Well-designed and appropriate regulations notwithstanding, this 

result underscores the need to reduce unnecessary red tape from the body of administrative law. 

A ROADMAP FOR REFORM: THE BRITISH COLUMBIA MODEL 

The United States needs to achieve lasting reform without radical policy reversals between 

administrations. Fortunately, the regulatory reform undertaken in the Canadian province of British 

Columbia in 2002 provides a roadmap for US policy makers. 

Following the election of a reformist government in 2001, British Columbia (BC) sought to reduce the 

number of regulatory requirements, which initially stood at just over 382,000, by an ambitious 33 

percent.15 To achieve this goal, two regulatory restrictions were to be removed for every new rule 

imposed. Once the target reduction of one-third was achieved, the policy switched to a one-in-one-out 

rule. All newly proposed regulatory rules were required to be "necessary, outcome-based, transparently 

developed, cost-effective, evidence-based, and support[ive of] the economy and small business."" The 

reform process was decentralized, and each agency was tasked with achieving the mandated regulatory 

goals. The BC government successfully engaged with private individuals and firms to help identify 

ineffective and burdensome rules. Finally, and perhaps most importantly, the BC government 

successfully changed the culture of its own bureaucracy by shifting the focus of regulators' energy from 

the drafting of new rules to the ongoing management of a regulatory portfolio. Such an approach not 

only institutionalizes reform efforts, but also ensures that (1) regulators must constantly reevaluate past 

regulatory rules and eliminate poor performers, and (2) regulators cannot create new rules unless their 

Monica, CA. August 2005); for the effectiveness of small business concessions, see Dixon et al., "The Impact of Regulation and 

Litigation on Small Business and Entrepreneurship·· (Working Paper. RAND Corporation, Santa Monica, CA. February 2006). 12 Kugler et al., Entrepreneurship in Low-Income Areas (Washington, DC: US Small Business Administration. September 2017). 13 Dustin Chambers, Patrick A. Mclaughlin, and Laura Stanley, "Regulation and Poverty: An Empirical Examination of the Relationship 

between the Incidence of Federal Regulation and the Occurrence of Poverty across the States,"' Public Choice (forthcoming). 14 Dustfn Chambers, Courtney Collins, and Alan Krause, "How Do Federal Regulations Affect Consumer Prices? An Analysis of 

the Regressive Effects of Regulation,'" Public Choice (forthcoming). 15 For a detailed description of the British Columbia Model, see Laura Jones Cutting Red Tape in Canada: A Regulatory Reform 

Model for the United States (Mercatus Research, Mercatus Center at George Mason University, Arlington. VA. 2015). 16 Cutting Red Tape in Canada: A Regulatory Reform Model for the United States (Arlington, VA: Mercatus Center at George 

Mason University, 2015). 

4 
42 

net benefits (i.e. benefits net of costs) exceed the performance of the least effective current rule, which 

is initially a weaker standard than a simple cost-benefit test when "red tape" remains, but gradually 

transitions into a stricter standard once regulators have effectively eliminated all "red tape."17 

Economist Laura Jones reports that following the implementation of these reforms, BC reduced 

regulatory requirements by 37 percent, the number of business incorporations rose while the number of 

business bankruptcies declined, and the province's rate of economic growth went from below average 

before the election of reformers (1992 to 2000) to above average in the six years after reform (2002 to 

2008), all without adverse effects on environmental quality.18 

CONCLUSION 

In view of the unintended consequences of excessive red tape, which include lower rates of economic 

growth, reduced small business formation and entrepreneurship, higher rates of poverty, and higher 

prices for all consumers (especially the poorest), the nonpartisan and urgent need for regulatory reform 

that slashes red tape while preserving rules that protect workers, consumers, and the environment 

should be apparent. Moreover, the ability to stimulate the economy without impacting the federal 

budget or the national debt through increased spending or tax cuts is especially appealing. 

ATTACHMENTS (2) 

Dustin Chambers, Patrick A. McLaughlin, and Tyler Richards, "Regulation, Entrepreneurship, and 

Firm Size" (Mercatus Working Paper) 

Dustin Chambers, Patrick A. McLaughlin, and Laura Stanley, "Regulation and Poverty: An Empirical 

Examination of the Relationship between the Incidence of Federal Regulation and the Occurrence of 

Poverty across the States" (Mercatus Working Paper) 

17 This is an especially important property given recent research, which calls into question the quality of regulatory impact 

analysis (RIA) performed by federal agencies. See for example, Jerry Ellig, ''Evaluating the Quality and Use of Regulatory 

Impact Analysis: The Mercatus Center's Regulatory Report Card, 2008-2013" (Mercatus Working Paper, Mercatus Center at 

George Mason University, Arlington, VA, 2016). 

"See Jones (2015). 

5 
43 

Regulation, 

Entrepreneurship, 

and Firm Size 

Dustin Chambers, Patrick A. Mclaughlin, 

and Tyler Richards 

MERCATUS WORKING PAPER 

A If studies m the Mercatus Workmg Paper series have followed a ngorous process of academic evafualion, 

includrng (except where otherwise noted) at feast one doubfe·blmd peer review. Working Papers present an 

author's provrstonal findings, which, upon further consrderat:on and revision, are !rke!y to be repubtt~'ihed man 

academic journal. The opmtons expressed in Mercatus Working Papers are the authors' and do not represent 

official positions of the Mercatus Center or George Nason Unrversity. 

MERCATUS CENTER 

George Mason University 3434 Washington Blvd .. 4th Floor, Arlmgton, Virginia 22201 

www.mercatus.org 
44 

Dustin Chambers, Patrick A. McLaughlin, and Tyler Richards. "Regulation, Entrepreneurship, 

and Firm Size." Mercatus Working Paper, Mercatus Center at George Mason University, 

Arlington, VA, 2018. 

Abstract 

We investigate whether regulatory growth disproportionately burdens small businesses relative to 

large businesses. Using panel data from RegData 3.0 and exploiting variation across industries 

over time, we empirically estimate the relationship between regulatory growth and growth in the 

number of small and large firms. Controlling for other factors, we find that a I 0 percent increase in 

regulatory restrictions on a particular industry is associated with a reduction in the total number of 

small firms within that industry by about 0.5 percent, while simultaneously having no statistically 

significant association with the number oflarge firms in that industry. We also find that these 

magnitudes are amplified when this regulatory growth follows previous years of high regulatory 

growth, implying that unrelenting regulatory increases harm small businesses at an escalating rate. 

JEL codes: C23, D73, LSI 

Keywords: entrepreneurship, regulation, regulatory accumulation, small business, finn size, 

industry concentration 

Author Affiliation and Contact Information 

Dustin Chambers 

Senior Affiliated Scholar, Mercatus Center at George Mason University 

Professor of Economics, Perdue School of Business, Salisbury University 

dlchambers@salisbury.edu 

Patrick A. McLaughlin 

Director of the Program for Economic Research on Regulation 

Mercatus Center at George Mason University 

pmclaughlin@mercatus.gmu.edu 

Tyler Richards 

Research Coordinator 

Mercatus Center at George Mason University 

trichards@mercatus.gmu.edu 

© 2018 by Dustin Chambers, Patrick A. McLaughlin, Tyler Richards, and the Mercatus Center at 

George Mason University 

This paper can be accessed at https://www.mercatus.org/publications/regulation 

-entrepreneurship-firm-size 
45 

I. Introduction 

Regulation, Entrepreneurship, and Firm Size 

Dustin Chambers, Patrick A. McLaughlin, and Tyler Richards 

Regulations, by their nature, generate costs and benefits for the entities they affect. These effects 

can accrue in different ways and to different groups. Some of the effects are estimated in 

regulatory impact analyses prepared by the agencies responsible for the regulations. However, as 

regulations build up over time, their accumulation may have more significant effects than 

agencies are able to impute in their analyses of individual rules. Furthermore, the effects of 

accumulation may impact some groups more than others because of certain group characteristics. 

In this paper, we focus on discovering whether increases in regulations disproportionately burden 

small businesses as compared with large businesses. In particular, we seek to determine whether 

increases in regulations that apply to individual industries reduce the number of small firms in 

those industries, while having less of an effect on their larger competitors. 

Regulatory costs come in many forms, but a common manifestation is compliance 

costs-the costs that businesses must incur in order to fulfill regulatory obligations. Compliance 

costs might include filling out paperwork, purchasing new equipment to meet mandated 

standards, or paying lawyers to advise on compliance strategies, just to name a few examples. 

Such compliance activities may have economies of scale that allow large businesses to navigate 

the regulatory landscape more easily than small businesses. For instance, large businesses are 

likely to have lawyers on payroll, while small businesses may be limited to contracting for legal 

services. Not only is the same legal advice likely to cost more from a contractor than from a fulltime hire, but the contracted lawyer must spend extra time learning the specific details of the 

business-knowledge a lawyer on payroll would already have when compliance issues arise. 

3 
46 

Moreover, the costs of many regulations are fixed rather than purely variable (per-unit) costs, 

and larger businesses are able to spread fixed costs over a larger volume of output. In other 

words, if regulations apply equally to all businesses within an industry, we should expect that the 

relative costs of compliance--meaning the costs relative to the size of the business-will be 

larger for small businesses than for large businesses. 

If the burden of regulations falls disproportionately on small businesses, this burden is 

likely to have ripple effects throughout the economy owing to the importance of small businesses 

for employment, innovation, and economic opportunity. Small businesses represent a large portion 

of the US economy, both in terms of the number of businesses and in terms of the workforce. 

According to the US Census Bureau's "Statistics of US Businesses" (SUSB), businesses with 

fewer than 500 employees-the definition of a small business used by the Small Business 

Administration (SBA)-account for 99.7 percent of US businesses and 47.5 percent of US 

employment (SBA 20 17). Furthermore, research has shown not only that small businesses exhibit 

roughly the same rate of innovative activity per worker as large businesses, but that in some 

industries small businesses are more innovative than their larger counterparts (Audretsch 1995). 

In addition to these macroeconomic implications, the burden of regulatory costs on small 

businesses may also have important distributional effects based on income. Low-income areas 

tend to have smaller businesses than other areas (Kugler et al. 20 17), meaning that any 

disproportionately high costs for small businesses are likely to hit these low-income areas 

hardest. Small businesses are also an important mechanism for economic mobility, specifically 

for low-income households with little access to capital. To the extent that regulations hurt small 

businesses or create barriers to entry for such businesses, they may also limit the economic 

opportunities available to low-income households. 

4 
47 

In order to mitigate these potential problems, Congress has built some relief mechanisms 

for small businesses into the regulatory process. For example, the Regulatory Flexibility Act of 

1980 and the Small Business Regulatory Enforcement Fairness Act of 1996 instruct federal 

agencies to attempt to determine a regulation's economic impact on small entities and explore 

alternatives that might reduce that impact, including partial or total exemptions for small 

businesses (although these statutes allow the agency to determine what constitutes a small 

business under the specific circumstances). However, we know little beyond limited anecdotal 

evidence about the extent of small business exemptions or their characteristics, because there 

currently exists no way to scour the federal regulatory code for all exemptions and their details. 

Furthern10re, exemptions that do exist may not constitute complete cost savings-some are only 

partial exemptions, and even full exemptions may involve compliance costs because businesses 

must determine whether they are eligible for the exemptions and must file for them. 

The idea that regulatory burdens may fall disproportionately on small businesses is not 

new to the academic literature. However, limited data on the breadth and incidence of federal 

regulation have made empirical testing of the concept difficult at best. A few studies have 

attempted to look at the general effects of regulations on small businesses (Hopkins 1995; Crain 

and Hopkins 2001; Kitching, Hart, and Wilson 2015; Crain and Crain 2014), and others have 

analyzed specific case studies or anecdotes (Adler 1993; Becker 2005; Dean, Brown, and Stango 

2000). While these studies are infonnative, the robustness of their results is debatable because 

they either lack a good measure of the incidence of regulation or require extrapolating to the 

entire economy from a single industry. However, a novel database called RegData, which 

quantifies federal regulatory restrictions within the Code of Federal Regulations (CFR) and 

identifies the industries those restrictions directly impact, allows us to empirically test the effects 

5 
48 

of regulations on small businesses with more granularity and robustness (McLaughlin and 

She rouse 20 17). 

This study is the first to estimate how changes in the stock of regulations influence the 

number businesses of varying sizes across industries. In particular, we evaluate how increases in 

the number of regulatory restrictions that apply to individual industries affect the number of 

small firms and large firms in those industries between 1998 and 2015. We also evaluate the 

effect of increases in regulatory restrictions during that time period on total employment in small 

and large finns from those industries. Controlling for other factors, we find that a 10 percent 

increase in regulatory restrictions on a particular industry is associated with a reduction of 

0.432-0.565 percent in the total number of small firms in that industry, but the same increase is 

not associated with any change in the number oflarge firms in that industry. The reduction in 

small firms rises to 1. 00-1.54 percent when the industry has experienced above-average 

regulatory growth over the previous two years. We also find that a l 0 percent increase in 

regulatory restrictions on an industry is associated with a 0.410-·0.547 percent reduction in total 

employment within small firms in that industry. However, when industries endure two 

consecutive years of above-average regulatory growth, we find statistically significant reductions 

in employment for firms of all sizes within that industry, including large firms. 

This paper is organized as follows. Section 2 provides a review of the existing literature 

on the effects of regulations on small businesses. Section 3 describes the data used in the study. 

Section 4 provides exploratory analysis of the differing effects of regulations on small and large 

businesses. Section 5 describes the formal regression model. Section 6 presents the estimation 

results. Finally, section 7 concludes with a discussion of the topic and results. 

6 
49 

2. Literature Review 

Our study is the first in the literature to address how changes in the stock of regulations influence 

the number of businesses of different sizes across industries. The lack of existing research likely 

reflects the fact that, before RegData, there existed no comprehensive panel of federal regulatory 

restrictions that was based on the North American Industry Classification System (NAICS). 

Consequently, the bulk of the existing literature focuses on either the general impact of federal 

regulations on all small businesses or industry-specific case studies. General studies risk 

conflating the effects of other factors with those of regulations, and case studies paint only part 

of the picture. Moreover, much of the literature on small businesses and regulation has relied on 

surveys of small business owners, who are asked to give potentially biased feedback concerning 

the monetary and time burdens of compliance. 

Nevertheless, a large body of research exists on whether and how regulations affect small 

businesses. Bradford (2004) develops a mathematical model of how regulatory costs and benefits 

affect businesses of different sizes, with the aim of determining whether small business 

exemptions are justified. However, he falls short of providing a general answer to that question 

owing both to uncertainty about the compounding effects of many regulations and to case-bycase considerations regarding transaction costs. Becker (2005) presents a case study of 

asymmetric enforcement of the Clean Air Act, which exempts small businesses from many 

regulations. He finds that many asymmetries exist in enforcement, some favoring small 

businesses and some favoring large businesses. Thus, he is unable to draw any conclusions 

regarding whether regulations favor small businesses specifically. Dean, Brown, and Stango 

(2000) conduct a different study on the effects of enviromnental regulations on small businesses, 

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50 

finding that greater intensity of regulation is associated with fewer small business formations but 

no change in large business formations. 

Crain and Crain (2014), looking at the costs of regulations for small businesses, measure 

regulatory cost incidence by evaluating the cost of regulatory compliance for various industries 

and determining the cost per employee for small businesses (those with fewer than 50 

employees), medium businesses (50 to 99 employees), and large businesses (100 or more 

employees). They find that, across all industries, the compliance cost per employee is $11,724 

for small businesses, $10,664 for medium businesses, and $9,083 for large businesses. The 

National Federation oflndependent Business (NFIB), a US association of small businesses, 

provides some insight into the costs as perceived by small business owners. The association 

recently released the results of a questionnaire in which it asked its members to rate 75 potential 

business problems related to the marketplace and government activities on the basis of each 

problem's severity. "Unreasonable government regulations" was rated the second-most-severe 

problem, trailing behind only the cost of health insurance (Wade 2016). 

Kitching, Hart, and Wilson (20 15), however, suggest that by treating regulation as a static 

and negative influence (e.g., by considering only the one-time costs of purchasing new 

technology or filling out paperwork), small business owners and much of the existing literature 

overlook the positive effects of regulation on business performance. They argue that regulation is 

in fact a dynamic force that can benefit or harm businesses as they adapt to the new regulations 

and interact with stakeholders, but that the dynamic effects (including the benefits) may be less 

apparent than the static effects. These dynamic effects include changes such as new opportunities 

created by the adoption of new mandated business practices and technologies and entrepreneurial 

opportunities created by changes in the market structure due to regulatory effects. 

8 
51 

Regarding the cwnulative costs of regulations, Bradford (2004, 28) argues that they may 

be less than the swn of the individual (marginal) costs of compliance with each regulation. This 

stems from the fact that some regulations overlap: 

For example, one of the costs of the Americans with Disabilities Act is training a firm's 

hiring personnel, who must learn what hiring practices are disallowed by the Act. The 

Equal Employment Opportunity Act imposes a similar cost, but with respect to women 

and minorities rather than the disabled. To the extent that personnel training for the two 

statutes can be combined, the overall training cost may be less than what it would cost to 

train people under each statute separately. Paperwork and labeling requirements may 

involve similar economies. 

Thus, Bradford argues that the cumulative costs of regulations are increasing at a declining rate. 

This is in sharp contrast to Adler (1993), who argues that regulations have a compounding effect 

on costs: 

The problem is not so much with any specific regulation as it is with the overall 

phenomenon .... The cumulative impact of regulatory efforts is to depress economic 

activity, retard job creation, and stifle the entrepreneurial spirit. When regulations are 

issued with little regard for their marginal impact when added to existing requirements, 

their results can be particularly oppressive. Regulations are like straws that eventually 

break the camel's back. 

Nonetheless, both authors predict that the total regulatory burden is not simply the swn of 

the compliance costs projected by regulatory agencies, but rather a function of the buildup of 

regulations over time. Neither author, however, addresses the two central questions of our paper: 

First, does the pace of short-run changes in federal regulations differentially impact the number 

of small and large firms within an industry? Second, how do these changes impact total 

employment for small and large firms within an industry? Thus, our paper advances the literature 

in several key ways. First, we look at the impact of regulatory flow rather than the overall level 

of regulation. Second, we examine enterprises of all sizes, not just small businesses. Finally, we 

use objectively generated and unbiased measures of regulation to estimate effects over nearly 

two decades (1998-2015). 

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52 

3. Data 

For our measure of federal regulation, we use RegData 3.0, which quantifies regulation from the 

CFR for the years 1970-2016 (McLaughlin and Sherouse 2017). To obtain this measure, RegData 

first searches the CFR for restrictive words, such as "shall" or "must." It then uses a machine 

learning model to assign probabilities that an industry is likely to be affected by each restriction. 

These industries are identified using NAICS industry codes (Al-Ubaydli and McLaughlin 2017). 

The model is trained to identify industries by looking for textual similarities between a rule in the 

CFR containing specific restrictions and a set of rules and proposed rules published in the Federal 

Register that mention at least one NAICS industry by nan1e. RegData identifies these industries 

from the two-digit to six-digit NAICS levels, with two-digit being the broadest (e.g., 23-~ 

Construction) and six-digit being the narrowest (e.g., 238140-Masonry Contractors). 

We combine the data from RegData with the SUSB data, which provide the number of 

firms and total employment for businesses of various sizes within NAICS industries each year 

from 1998 to 2015. 1 SUSB defines a firm as "a business organization consisting of one or more 

domestic establishments in the same state and industry that were specified under common 

ownership or contro1."2 It defines size by the number of employees, grouping businesses into six 

categories: 0-4,5-9, 10-19,20-99, 100-499, and 500+ employees. SUSB also identifies 

industries from the two-digit to six-digit NAICS level, allowing for direct mapping to the 

RegData database. It is important to note that firms can move between categories over time for 

1 We chose SUSB over County Business Patterns for two reasons: ( l) SUSB has data at the finn and establishment 

levels, while CBP has data only at the establishment level (which means its data give a less accurate picture of the 

total number of"businesses"); and (2) the Census Bureau recommends that County Business Patterns data not be 

used as a time series. 2 See the SUSB glossary at https://www.census.gov/programs-surveys/susb/about/glossary.html. 

10 
53 

various reasons-for instance, they might hire additional workers, lay workers off, or merge with 

other firms. That said, firms only exist in a single category each year. 

Table 1 (page 33) provides the distribution of firms by size and year in the US between 

1998 and 2015, as reported by SUSB. Over this time period, very small businesses (o-4 

employees) constituted the bulk of all firms (61.21 percent), while all small firms (0-499 

employees), as defined by the SBA, represented more than 99 percent of all firms. Large firms 

(with 500 or more employees) represented less than one-third of one percent of all firms. 

Nonetheless, large firms were important sources of overall employment. Table 2 (page 34) 

provides the distribution of employment by firm size between 1998 and 2015, as reported by 

SUSB. Over this time period, large firms provided just under 51 percent of total employment, 

while all small firms (0-499 employees) provided the other 49 percent. The smallest firms (0-4 

employees) provided approximately 5 percent of all employment. 

In the regression analysis that follows in section 5, we match the RegData data and SUSB 

data with two indicators of the US business cycle: the unemployment rate and the US GDP gap. 

The unemployment rate, obtained from the St. Louis Federal Reserve, measures the US average 

rate of unemployment from 1998 to 2015 (OECD 2018). The GDP gap is a measure of how far the 

current level of US output is above or below its long-run trend. This measure is derived from 

annual real GDP data obtained from the St. Louis Federal Reserve (BEA 2018) and is decomposed 

into trend and cycle components. 3 The latter series (cycle) is interpreted to measure economic 

deviations from trend-that is, the business cycle (in billions of2009 chained dollars). Finally, we 

divide the cycle series by the trend measure to express the GDP gap as a percentage of full output. 

3 Because this is annual data, the smoothing parameter was set to 6.25 (A. = 6.25). 

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54 

For example, a positive value of 2 percent corresponds to economic output that is 2 percent above 

trend output (an economic expansion), while negative readings correspond to recessions. 

4. Exploratory Analysis 

Before specifYing and estimating the fonnal regression model, it is instructive to examine the 

data directly to find evidence of patterns within and relationships between the variables in our 

dataset. We begin by looking at the year-over-year rate of growth of industry-specific 

regulations, which averaged 3.83 percent between 1998 and 2015. This growth rate, while high, 

varied significantly by year (see table 3, page 35), with regulatory growth exceeding 5 percent 

per year on four occasions (2004, 2008,2012, and 2015). 

Moreover, we find that the burden of regulation falls disproportionately on smaller 

businesses. To explore this further, we use the SUSB firm size classifications to calculate the 

effective regulatory restrictions by finn size and year using weights based on the proportion of firms 

of a given size within an industry. For example, focusing on the smallest firms (0-4 employees), for 

each year (I) we first calculate the total number of small firms (F?-4 ) in our dataset: 

F o-4 _ ~Fo-4 t - L, t,i 1 (1) 

where i is an index of industry and Ft~i4 is a measure of the number of small firms in industry i in 

year 1. Next, we derive weights based on the share of all small fim1s that operate in a given 

industry, which reflects the distribution of small firms across industries: 

(2) 

For example, in 1998, there were 5,400,968 firms with 0-4 employees in our matched 

dataset. Of those small firms that year, 198,580 were in the wholesale trade sector (NAICS code 

12 
55 

42). Therefore, the share (w?,[4 ) of all small firms in the wholesale trade sector in 1998 equaled 

approximately 3.7 percent (i.e., 198,580/5,400,968 = 0.03677). Finally, we multiply these annual 

industry weights by the level of federal regulation that pertains to each industry (reg;,), and sum 

across industries: 

0-4 '\' 0-4 reg, = L w,,; ·reg;,. (3) 

Repeating this process for each firm size classification (i.e., 5-9 employees, 10-19 

employees, etc.), we derive the weighted regulatory restrictions by firm size for each year (see 

table 4, page 36).4 The resulting data enable us to determine whether regulatory restrictions tend 

to be higher in industries that have a higher concentration of small finns. The resulting regulation 

total represents the universe of regulations collectively faced by firms of a given size in a given 

year. Therefore, it is important to emphasize that no single firm faces the totality of these 

weighted restrictions, but rather this is a measure of regulation brought to bear collectively on all 

firms of a given size. 

We find that the smallest firms, defined as enterprises with four or fewer employees, 

faced a regulatory burden between 19 and 83 percent greater than that of their larger counterparts 

in 1998. By 2015, this imbalance had declined somewhat, but was nonetheless large, ranging 

from 15 to 48 percent. To show this more clearly, figure I (page 37) plots an index of weighted 

4 The drop in weighted regulations across all linn size classes between 2002 and 2003 was due to a change in 

Census Bureau methodology in the tabulation of SUSB statistics. Specifically, 2002 was the last year in which the 

1997 NAlCS code system was used. Beginning in 2003, SUSB switched to the 2002 NAICS code system, resulting 

in the loss of 43 sectors in our dataset and the addition of 195 new sectors. The Census Bureau updated the 

underlying NAICS code system again in 2008 and in 2012, but the updates resulted in few sectoral changes in our 

matched dataset, with net total finn changes of less than 1.5 percent in both transition years. 

l3 
56 

regulation by firm size, with I 00 corresponding to the level of regulation faced collectively by 

small firms in 1998 (25,633 weighted regulatory restrictions) 5 

There is also anecdotal evidence that federal regulations have a more erosive effect on 

small firms than on larger firms. Figure 2 (page 38) plots an index of total small firms (100 

corresponds to the total number of small firms in 1998) against the index of weighted regulations 

for small firms from figure 1 (I 00 corresponds to the level of regulation faced by small firms in 

1998) from 2003 to 2015.6 These results are intriguing even though the relationship between the 

level of small-finn entrepreneurship and federal regulations is beyond the scope of this paper. 7 

Specifically, there appears to be an inverse relationship between total firms and total weighted 

regulations, with the two series often moving in opposite directions (i.e., the total number of 

firms tends to fall during periods of regulatory buildup, while entrepreneurship increases during 

periods of deregulation). 

Granted, the first few years of the 21st century were a period of high growth followed by 

contraction (the Great Recession) and slow recovery; therefore one cannot credit regulations 

alone with the pattern of total small finns observed. However, it is worth noting that a similar 

pattern does not emerge when examining large firms with 500 or more employees (see figure 3, 

page 39). Despite a recession and surge of regulation, the pattern of growth for large firms is 

5 These measures do not take into account small business regulatory waivers, which exempt some small businesses 

(on a case-by-case basis) from specific regulations. Data about these waivers are not readily available, and 

regulations are costly irrespective of waivers. First, finns must stay apprised of, analyze, and understand all new 

regulations affecting their industry. Second, the costs of applying for a waiver (e.g., legal, consulting, and filing 

costs) may be substantial. Therefore, all applicable regulations are costly to firms, regardless of their enforcement. 6 We plot from 2003 onward because of the change in SUSB methodology between 2002 and 2003 discussed above. 7 Testing the relationship between the stock (or level) of finns and regulations would be an ambitious undertaking, 

as it would require the construction of a model that mimics the distributional structure of the US economy. Instead, 

in section 5, we test the relationship between growth in the total number offinns in a given industry and growth in 

federal regulations germane to that industry. This flow model necessarily eliminates any static or slow-evolving 

structural factors goveming firm size and distribution. yielding a model wherein growth in total finns is driven by 

regulatory changes and the business cycle. 

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57 

very different. While this may seem puzzling to some, it does fit a pattern consistent with the 

predictions of public choice theorists (see, for example, Stigler 1971 and Peltzman 1976, among 

others), who posit that large and more powerful firms often seek regulations, which act as 

barriers to entry to the industry by smaller firms, and so limit competition to existing firms. This 

pattern is also consistent with the theory that larger firms both possess the resources to cope with 

new regulations and can spread the costs of regulations over a larger volume of output. 

To show the extent to which weighted regulations are correlated with the number of firms 

of a given size, table 5 (page 40) provides the relevant correlation coefficients over the periods 

2003-2015 and 2009-2015. 

Given the sharp economic contraction of the Great Recession followed by the brisk pace 

of new regulation during the Obama administration, one would expect, a priori, a negative 

correlation between total firms and regulation. We do observe this pattern quite clearly in smaller 

firms (with fewer than 100 employees). However, large firms display the opposite behavior, with 

surging numbers of large firms alongside higher regulations. 

To further explore this issue, we set aside the total weighted regulation data by year and 

instead investigate the unweighted, industry-level regulation and firm data. As a first step, we 

calculate the year-over-year growth rate of the total number of firms of a given category size 

(e.g., 5--9 employees) between 1998 and 2015. Next, we group these growth observations by 

their corresponding rate of regulatory growth. Observations from industries experiencing the 

relatively lowest rates of regulatory growth within a given year (i.e., the bottom 25 percent) are 

assigned to the low-regulation-growth group, while observations from industries experiencing 

rapid regulatory growth within a given year (i.e., the. top 25 percent) are assigned to the highregulation-growth group. Next, we subdivide the low-regulation-growth group by size class and 

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58 

calculate the average growth rate in the total number of firms. This step is repeated for the highregulation-growth group. The results are plotted in figure 4 (page 41). Clearly, the total number 

of firms in industries with regulatory stability grew at a higher pace (or shrank at a slower pace) 

than the number of firms in industries deluged by new regulations. This suggests that finns 

operating in an environment with little regulatory growth are less likely to fail than their peers 

doing business in an envirournent with rapidly increasing regulations. 

As a final exploratory exercise before moving to the formal regression model, we ask this 

question: If finns within an industry are subjected to several consecutive years of growing 

regulatory burden, does the number of firms within that industry decline at a faster pace? To 

assess this question, we filter our dataset to include firms that experienced one, two, or three 

consecutive years of regulatory growth. Focusing specifically on the smallest firms (0-4 

employees), we find that both total firms and employment decline more rapidly with more 

consecutive years of regulatory growth (see figure 5, page 42). 

Moreover, this phenomenon is exacerbated when the rate of regulatory growth is higher. 

To demonstrate this, we repeat the exercise above, but this time focus on consecutive years of 

above average regulatory growth. The results for the smallest firms are similar but noticeably 

more pronounced (see figure 6, page 43). In the case of a single year of positive regulatory 

growth, the corresponding total number of small tirms within an industry shrinks by about 

0.31 percent (see figure 5). However, when finns experience a single year of above-average 

regulatory growth, the total number of small firms shrinks by 1.11 percent, which is over 3.5 

times the 0.31 percent rate of decline. To put this number into perspective, there were more than 

3.6 million firms with 0-4 employees in 2015. A decline of just 0.31 percent represents the loss 

of more than 11,000 firms. When regulatory growth extends to three consecutive years, the 

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59 

impacts are more pronounced: the corresponding total number of small firms within an industry 

shrinks by about 0.42 percent annually (see figure 5). However, when firms experience three 

consecutive years of above-average regulatory growth, the total number of small firms shrinks 

3.5 times more rapidly (1.47% vs. 0.42%). If such a drastic decline were to befall all very small 

firms in 2015, the result would be the loss of more than 53,000 businesses. 

Turning to the employment statistics of the smallest firms, a single year of positive 

regulatory growth is associated with a 0.02 percent decline in employment, while three 

consecutive years of regulatory growth is associated with a 0.19 percent decline in employment 

each year (see figure 5). To put this into perspective, nearly 5.9 million people were employed 

by small firms in 2015. A decline of just 0.19 percent would represent the loss of just over 

11,000 jobs. When regulatory growth increases to above-average levels, the effects are 

amplified. For a single year of above-average regulatory growth, small business employment 

recedes by 0.69 percent. Increasing the duration to three consecutive years of above-average 

regulatory growth, the employment shrinkage rate increases to 1.05 percent. If all very small 

firms (0-4 employees) were to face a decline of this magnitude, the job losses in 2015 would 

exceed 61,000 jobs. Clearly, the flow of new regulations is associated with sharp changes in both 

the number of and employment in very small firms. As firms face longer spells of regulatory 

growth (i.e., two or three consecutive years), these effects become more pronounced. Moreover, 

if the intensity of regulatory growth is increased (i.e., if growth is above average), the effects are 

greater still. 

Next, we build a more formal regression model to estimate more precisely the effect of 

changes in federal regulations on the number of businesses. 

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60 

5. Regression Analysis 

As previously mentioned, building a model that explains the structure of the US economy and its 

distribution of firms of varying sizes by industry would be a monumental task and is beyond the 

scope of this paper. Instead, we seek to model changes in the number of firms over time-that is, 

we are concerned with the flow rather than the stock of firms by industry. This approach is 

advantageous in that any invariant or slowly evolving characteristic that influences the level of 

firms by size within an industry will exert little or no effect on the annual growth rate of finns. 

Our focus on the flow of regulations yields a simpler framework wherein the growth rate of total 

finns is regressed on exogenous factors that drive (or accelerate) that growth. Given that the rate 

of growth of the total number of firms within an industry naturally fluctuates over time with the 

business cycle and changing competitive pressures, we specifically control for the effects of 

these exogenous factors when estimating the impact of regulations on the number of firms. Our 

preferred model takes the form of the following fixed effects panel: 

FirmGrowth;t = a; + {3 · RegGrowthit + X;,B + uit, (4) 

where i is the cross-sectional NAICS industry index; tis the time period index; FirmGrowth;t is 

the year-over-year growth rate in the total number of finns in industry i; a; is an industryspecific fixed effect (which captures any differences in the long-run rate of growth of the 

industry due to exogenous changes in relative competitiveness, consumer demand, etc.); 

RegGrowth;t is the year-over-year growth rate in the number federal regulatory restrictions that 

pertain to industry i; X;t is a matrix of control variables, including the US rate of unemployment 

and the US GDP gap (both of which capture business cycle conditions); and U;t is a mean-zero 

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61 

error term.8 Given our model specification, the coefficient on regulatory growth (i.e., {3) is an 

elasticity measure equal to the percent change in the number of firms for a 1 percent change in 

regulations.9 This growth elasticity of regulation, which we believe to be negative, reveals the 

sensitivity of firms (of a given size class) to increases in the rate of regulation. 

Analogously to model (4) above, we also estimate the impact of federal regulatory 

growth on the growth rate of employment (EmploymentGrowthit) within various industries by 

replacing the FirmGrowthit dependent variable with EmploymentGrowthit• and we label the 

result model (5): 

EmploymentGrowthit = a; + {3 • RegGrowthie + XieB + uit· (5) 

We consider three firm-size classifications: (I) 0-4 employees, (2) 0-499 employees, and 

(3) 500 or more employees. These categories correspond to the smallest firms (0-4 employees), 

all small firms as defined by the SBA (0-499 employees), and large firms (500 or more 

employees). Given the exploratory results above, there is reason to believe that the impact of 

regulations on firms depends on firm size, and this hypothesis is testable given our firm size 

classifications. 

Although we control for the common influence of the US business cycle on firms across 

industries, it is reasonable to anticipate that exogenous shocks may influence multiple industries 

simultaneously. Because of this, industry panels should exhibit cross-sectional dependence. 

While common exogenous shocks do not bias coefficient point estimates, they do impact 

8 Model (4) does not include a period fixed effect term, as the business cycle covariates already capture temporal 

fluctuations in the growth rate of total firms. Indeed, the fixed effects are so highly correlated with the business 

cycle measures that including period fixed effects within the model results in singularity problems (i.e., the 

projection matrix is not well defined and the regression coefficients cannot be calculated). 9 In log-log models, the dependent variable, say ln(y), is regressed on a covariate of interest, say ln(x), and other log 

transformed co variates. The coefficient on ln(x) has an elasticity interpretation: it reveals the percent change in y that 

results from a 1 percent change in x. If this model is first differenced, we now regress 6ln(y) on 6ln(x) and the first 

difference of the remaining logged covariates. Note that the coefficient on 6ln(x) remains unchanged by the 

transformation and therefore retains the same elasticity interpretation. 

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62 

coefficient standard errors and therefore inferential test statistics. Following common empirical 

practice, we compensate by utilizing White robust (cross-sectional) standard errors in assessing 

the statistical significance of coefficient estimates. 

6. Estimation Results 

Table 6 (page 44) reports the baseline regression estimates of models (4) and (5) for small and 

large firms. Colunms (1) to (3) report the results for model (4)-that is, the impact of regulatory 

growth on the growth rate of the total number of firms of a given size within a given industry. In 

column (1), the coefficient on regulatory growth equals -0.0565 and is statistically significant at 

the I percent level. This coefficient indicates that a 1 percent increase in federal regulations is 

associated with a 0.0565 percent reduction in the number of very small firms (with 0-4 

employees). To put this into perspective, a hypothetical! 0 percent across-the-board increase in 

regulations (which is approximately equal to one standard deviation) would be associated with a 

0.565 percent reduction in the total number of small firms. In 2015, there were more than 3.6 

million small firms-therefore a 0.565 percent reduction represents the elimination of almost 

21,000 small businesses. However, this is probably an optimistic assessment. Both the preceding 

exploratory analysis and the regression results suggest that the marginal impact of regulatory 

growth increases with the size of the regulatory growth. 

Continuing with column (1), the coefficient on unemployment equals -0.3270, implying 

that a 1 percentage point increase in the US national rate of unemployment is associated with a 

reduction in the rate of growth in the number of small firms within an industry by 0.3270 

percentage points. Although the sign of this coefficient estimate makes economic sense-a 

sagging economy with rising unemployment likely coincides with the failure of many small 

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63 

businesses-it is statistically insignificant. Finally, the coefficient on the GDP gap10 equals 

0.0407, implying that each l percent increase in real US cyclical output above trend is associated 

with an increase in the rate of growth in the number of small firms by 0.0407 percentage points. 

This too makes economic sense: a booming economy should not only reduce the likelihood of 

business failure, but also encourage the formation of new startups. As with unemployment, this 

coefficient, while consistent with a priori expectations, is statistically insignificant. 

Turning to the broadest measure of small business used by the SBA-that is, firms with 0 

to 499 employees (see column 2)-the coefficient on regulatory growth equals -0.0423 and is 

statistically significant at the 5 percent level. This coefficient indicates that a l percent increase 

in federal regulations is associated with a 0.0423 percent reduction in the number of small firms 

(with between 0 and 499 employees). The coefficients on unemployment and the GDP gap are 

similar in to those reported in column (1), with the notable exception that the coefficient on 

unemployment is statistically significant at the 10 percent level. Interestingly, when we tum to 

large businesses-that is, firms with 500 or more employees (see column 3)-regulatory growth 

fails to have a statistically significant impact on the total number of firms. Clearly, large firms, in 

stark contrast to small firms, appear to be less susceptible to failure in environments of high 

regulatory growth. 

To measure the impact of federal regulatory growth on total sectoral employment in firms 

of varying sizes, estimates of model (5) are provided in columns (4) through (6) of table 6. For 

very small firms (with 0-4 employees), a I percent increase in federal regulations is associated 

with a 0.0410 percent reduction in employment among the small firms in the affected industry. 

10 The GDP gap equals the cyclical component of US real GDP derived via the Hodrick-Prescott filter. Measured in 

billions ofreal2009 dollars, positive values for the GDP gap correspond to periods of economic expansion while 

negative values correspond to periods of recession. 

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64 

As before, we can demonstrate the importance ofthis finding by considering a 10 percent acrossthe-board increase in federal regulations, which is associated with a 0.410 percent decline in 

small business employment. In 2015, nearly 5.9 million people were employed by very small 

businesses (with 0-4 employees). A 0.410 percent reduction in employment would result in the 

loss of just over 24,000 jobs. 

For all small businesses (0-499 employees), a 1 percent increase in federal regulations is 

associated with a 0.0547 percent reduction in employment among the small firms in the affected 

industry. Again, this may seem like a low value, but a 10 percent across-the-board increase in 

federal regulations is associated with a loss of more than 322,000 jobs, on the basis of2015 

employment levels. We again find that regulatory growth does not have a statistically significant 

impact on large firms: the coefficient for employment among large firms is statistically 

insignificant. 

Taken together, these results paint an important picture. First, when federal regulations are 

increased within a given industry, both the level of employment and the total number of firms are 

reduced by a similar rate, roughly 0.5 percent per 10 percent increase in regulations. Second, these 

unintended consequences fall squarely on small firms with fewer than 500 employees. And 

finally, relatively large firms with 500 or more employees are not negatively affected in a 

statistically significant way. However, this is probably an optimistic assessment. Both the 

preceding exploratory analysis and the regression results described below suggest that the 

marginal impact of higher regulatory growth is neither constant over time nor constant in intensity 

when industries are subjected to consecutive periods of above-average regulatory growth. 

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6.1. The Impact of Regulations on Firms Pre- and Post-2008 

In the wake of the financial crisis of 2008 and the change of presidential administrations, the 

sensitivity of small businesses to increases in federal regulations appears to be more pronounced, 

with the growth rate of the total number of small firms exhibiting large negative correlations 

with regulatory growth, in marked contrast to that of large firms, which appeared to thrive in this 

high-regulatory-growth enviroument. To more formally test this phenomenon, we estimate the 

following variant of model (4): 

FirmGrowth1t =a; +a· ot<OB + ({11 + {12 • ot<oa) · RegGrowthit + X;tB + uit• (6) 

where the dummy variable ot<oa equals 1 for all years before 2008. Entering model (6) in this 

way, the dummy variable acts as both an intercept and slope dummy, allowing the impact of 

regulatory growth on growth of the number of firms to vary over the two time periods. For the 

pre-2008 period, the coefficient {32 captures the change in this important regulation-firm 

elasticity measure. We therefore use a one-sided !-test on {12 to determine whether regulatory 

growth is associated with less firm attrition in the pre-2008 time period (or, equivalently, 

whether there was more associated firm attrition from 2008 onward): 

Ho:fJz$0 

H1:flz>O. 

Under this formulation of the test, our a priori expectations are captured by the alternative 

hypothesis (H1 ), whereby the coefficient on regulatory growth is larger in the pre-2008 period 

({11 + {12 ) and smaller from 2008 onward ({11). The null hypothesis is therefore a "straw man" 

which, if rejected, supports our theory. 

Analogously to model ( 6) above, we also estimate the impact of federal regulatory 

growth on the growth rate of employment (EmploymentGrowth;t) within various industries by 

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66 

replacing the FirmGrowthit dependent variable with EmploymentGrowthit• and we label the 

result model (7): 

EmploymentGrowthit = ai + a · Ot<os + (/f1 + /32 • Ot<os) · RegGrowthit + XitB + uit. (7) 

Table 7 (page 45) reports the estimation results of models (6) and (7). Looking first at the 

impact of regulations on the total number of firms of various sizes (i.e., columns 1 to 3), the 

results are in line with our expectations. In the smallest firms (0-4 employees), the regulation 

coefficient (/f1) equals -0.0854 and is significant at the 1 percent level. This implies that from 

2008 onward, a I percent increase in industry regulations is associated with a 0.0854 percent 

decline in very small firms within that industry. In line with our expectations, the slope dummy 

coefficient (/f2 ), which equals 0.0700, is positive and statistically significant at the 10 percent 

level (its two-sided p-value equals 0.0893). Conducting the one-sided hypothesis test outlined 

above, we reject the hypothesis that {32 is weakly negative at the 5 percent level and accept the 

alternative hypothesis that regulatory growth is associated with less firm attrition in the pre-2008 

time period. 

Our model predicts that in the pre-2008 period, a 1 percent increase in industry 

regulations is associated with a 0.0154 percent decline in very small firms within that industry. 

While statistically significant, this result is economically insignificant-that is, the result is tiny 

in absolute magnitude and close to zero. Among all small businesses (0-499 employees), the 

results are very similar. Both regulation slope coefficients possess the correct signs and are 

statistically significant at the 1 percent level. Therefore, we also reject the hypothesis that /f2 is 

weakly negative at the l percent level and accept the alternative hypothesis that regulatory 

growth is associated with less small business attrition in the pre-2008 time period. Therefore, our 

model predicts that from 2008 onward, a 1 percent increase in industry regulations is associated 

24 
67 

with a 0.0811 percent decline in the number of small firms within that industry. Our model also 

predicts that in the pre-2008 period, a I percent increase in industry regulations is associated 

with a 0.0104 percent increase in very small firms within that industry. As before, while 

statistically significant, this result is economically insignificant. Hence, there is a stark difference 

in the sensitivity of small businesses to increases in federal regulations in the periods before and 

after 2008. Finally, the number of large firms within a given industry does not appear to be 

negatively impacted by regulatory growth either before or after 2008. 

Turning to the effect of regulations on industry employment over these time periods (i.e., 

columns 4 to 6), we find results similar to those reported in columns (1) to (3). Specifically, for 

the period of2008 and beyond, regulations have a negative and statistically significant impact on 

small firm employment, with coefficient estimates ranging from -0.0770 for the smallest firms 

(0-4 employees) to -0.1065 for all small firms (0-499 employees). These values are quite large 

and imply that a I 0 percent increase in industry-specific regulation is associated with a nearly 1.1 

percent reduction in the level of employment in small firms. In line with our expectations, the 

slope dummy coefficient ({32 ) is positive and statistically significant at the 5 percent level in both 

of the small business regression models (see columns 4 and 5). For both the smallest firms (0-4 

employees) and all small firms (0-499 employees), we conduct the one-sided hypothesis test 

outlined above and reject the hypothesis that {32 is weakly negative at the 5 percent and I percent 

levels respectively, and in both cases accept the alternative hypothesis that regulatory growth is 

associated with greater small firm employment losses from 2008 onward. 

25 
68 

6.2. The Impact of Consecutive Spells of Above-Average Regulatory Growth 

Not surprisingly, our exploratory analysis suggests that when businesses are subjected to several 

consecutive years of above-average regulatory growth, the negative impact of additional regulatory 

increases is amplified. To formally test this hypothesis, we modify model (4) as follows: 

FirmGrowthit = ai +a· lihigh + ({31 + {J2 ·lihigh) · RegGrowthit + XitB + uit• (8) 

where the dummy variable lihigh equals 1 when the two preceding years experienced aboveaverage growth in industry-specific federal regulations (i.e., 

RegGrowthit-l and RegGrowthit-z > 3.83%). This dummy variable enters as both an 

intercept and slope dummy, allowing the impact of regulatory growth on growth of the number 

of firms to vary depending on the severity of past regulatory growth episodes. For cases where 

industries endure prior consecutive years of above-average regulatory growth, {J1 + {J2 captures 

this high-stress elasticity measure while {J1 captures the regulation-firm elasticity in all other 

cases. We therefore use a one-sided t-test on {J2 to detennine whether regulatory growth is 

associated with greater firm attrition following two consecutive years of high regulatory growth: 

Ho: fJz 2: 0 

Hl:fJz < 0. 

Under this formulation of the test, our a priori expectations are captured by the alternative 

hypothesis (H1 ), whereby the coefficient on regulatory growth ({J1 + {J2 ) is smaller (i.e., "more 

negative") following two consecutive years of high regulatory growth. The null hypothesis is 

therefore a "straw man" which, if rejected, supports our theory. 

Analogously to model (8) above, we also estimate the impact of federal regulatory 

growth on the growth rate of employment (EmploymentGrowthit) within various industries by 

26 
69 

replacing the FirmGrowthit dependent variable with EmploymentGrowthit• and we label the 

result model (9): 

EmploymentGrowthit = ai +a. a high + (f31 + fJz . a high) . RegGrowthit + XitB + Uit• (9) 

Table 8 (page 46) reports the estimation results of models (8) and (9). Looking first at the 

impact of regulatory growth on small firms (with 0--4 employees), we see that an increase in 

current regulations has a negative and statistically significant impact on the total number of small 

firms, regardless of the severity of prior regulatory growth. Both the coefficient on regulatory 

growth ({Jt) and the high regulation slope dummy coefficient ((32) are negative and statistically 

significant at the 5 percent level. Therefore, we reject the above null hypothesis that consecutive 

years of high regulatory growth are associated with less firm attrition. In the case of two prior 

years of high consecutive regulatory growth, the regulation-firm elasticity measure equals 

-0.154 (i.e., (31 + (32 ). This implies that if an industry is recovering from prior back-to-back 

years of above-average regulatory growth, each additional 1 percent increase in federal 

regulations in the current period is associated with a 0.154 percent reduction in the number of 

very small firms. In other words, a 10 percent across-the-board increase in federal regulations 

would reduce the number of very small firms by 1.54 percent, which is equivalent to over 56,000 

very small finns in 20 15. 

Clearly, higher regulatory growth hurts very small firms, but the unintended 

consequences compound with repeated years of steep regulatory growth. For all small firms (0-

499 employees), the results are very similar. Specifically, both the coefficient on regulatory 

growth ((31) and the high regulation slope dummy coefficient ((32) are negative and statistically 

significant at the 10 percent level. Therefore, we reject the above null hypothesis that 

consecutive years of high regulatory growth are associated with less firm attrition. In the case of 

27 
70 

two prior years of high consecutive regulatory growth, the regulation-firm elasticity measure 

equals -0.1 (i.e., f31 + {32). This implies that if an industry is recovering from prior back-to-back 

years of above-average regulatory growth, each additional 1 percent increase in federal 

regulations in the current period is associated with a 0.1 percent reduction in the number of all 

small firms. In other words, a 10 percent across-the-board increase in federal regulations would 

reduce the number of small firms by 1 percent, which is equivalent to just under 59,000 small 

firms in 2015. For large firms (500 or more employees), both elasticity measures are statistically 

insignificant. Thus, bouts of prolonged regulatory growth are more negatively associated with 

the loss of small businesses than of large businesses. 

Lastly, we examine the employment impacts of consecutive years of regulatory growth 

on small and large firms (see columns 4 to 6). Overall, the results are somewhat mixed. For both 

very small finns (0-4 employees) and large firms (more than 500 employees), the estimated high 

regulation slope dummy coefficients ({32) are negative and statistically significant at the 

5 percent level. Therefore, for both of these size classes we reject the above null hypothesis that 

consecutive years of high regulatory growth are associated with lower employment losses. 

Moreover, the coefficient on regulatory growth ({31 ) has the correct sigu but is statistically 

insignificant in the regressions for both very small finns (0-4 employees) and large firms (500 or 

more employees). Therefore, a lO percent across-the-board increase in all regulations (when 

preceded by two consecutive years of above-average regulations) is associated with a 

0.959 percent decline in very-small-firm employment and a 1.362 percent decline in large-firm 

employment. In 2015, this corresponds to job losses totaling over 56,000 and 887,000, 

respectively. For the group of all small businesses (0--499 employees), the high regulation slope 

28 
71 

dummy coefficient ({J2 ) is statistically insignificant. While this result is puzzling, the coefficient 

on overall regulatory growth ({J1 ) has the correct sign and is statistically significant. 

7. Discussion 

Economic theory tells us that regulations, if applied equally to businesses of all sizes, are likely 

to disproportionately harm smaller businesses. While some relief mechanisms for smaller 

businesses do exist, the extent of their availability is still unknown, let alone the degree to which 

they actually balance the burden of regulations across businesses of different sizes. Although the 

disparate effects of regulatory costs on businesses of different sizes have long been discussed in 

the political and academic realms, little work has been done to empirically test the existence and 

magnitude of such effects. This paper begins to fill this gap in the academic literature, and 

contributes information to the political debate in a way that might improve our knowledge of the 

true effects of regulations, particularly as they continue to accumulate. 

Controlling for relevant factors, we test how increases in regulation on specific industries 

are associated with the number of firms and the employment in firms of various sizes within 

those industries. We find that increases in industry-specific regulations are associated with 

decreases in the number of and employment in small firms within those industries, while having 

no association with changes experienced by large firms. These declines in the number of firms 

and in employment are also amplified when they follow previous years of regulatory growth, 

implying that regulatory increases disproportionately burden small businesses at an increasing 

rate. We also find that these developments are not statistically significant in the lead-up to the 

2008 financial crisis, but are statistically significant in the period following the crisis. Because 

the post-financial crisis period was one of high regulatory growth, this provides further evidence 

29 
72 

that the negative effects of regulation are not constant but are amplified during periods of 

abnormally high regulatory growth. 

Existing research already shows that regulations are associated with disproportionately 

high costs for lower-income households. The disproportionate burdens on these households come 

in forms such as lower wages (Bailey, Thomas, and Anderson 20 18) and higher prices for 

household goods (Chambers, Collins, and Krause 2017). Chambers, McLaughlin, and Stanley 

(2018) show that entry regulations (rules that set requirements for starting businesses and 

entering markets) increase income inequality. Furthermore, Coffey, McLaughlin, and Peretto 

(20 16) show that regulatory accumulation reduces economic growth, slowing the process that 

creates wealth for the entire society, including lower-income households. 

Our study advances this research by showing how regulatory accumulation appears to 

harm small businesses relative to their larger competitors. Since small businesses are more 

common in low-income areas, and because these businesses may often provide low-income 

households with opportunities for economic advancement, any negative effects of regulations on 

small businesses add to this list of harmful regressive effects. Taken together, these studies 

indicate that we must consider not only the costs and benefits of regulations on the parties 

immediately affected, but also the disproportionate effects of regulations and regulatory 

accumulation on specific groups. Consideration of these costs is essential for understanding the 

true individual and cumulative effects of regulations, and for ensuring a fair economic system. 

30 
73 

References 

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Small Business." Policy Analysis No. 200, Cato Institute, Washington, DC, December 

22. 

Al-Ubaydli, Omar, and Patrick A. McLaughlin. 2017. "RegData: A Numerical Database on 

Industry-Specific Regulations for All United States Industries and Federal Regulations, 

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Audretsch, David B. 1995. Innovation and Industry Evolution. Cambridge, MA: MIT Press. 

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Bailey, James B., Diana W. Thomas, and Joseph R. Anderson. 2018. "Regressive Effects of 

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Becker, Randy. 2005. "Air Pollution Abatement Costs under the Clean Air Act: Evidence from 

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Bradford, Steven. 2004. "Does Size Matter? An Economic Analysis of Small Business 

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Chambers, Dustin, Courtney A. Collins, and Alan Krause. 2017. "How Do Federal Regulations 

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Chambers, Dustin, Patrick A. McLaughlin, and Laura Stanley. 2018. "Barriers to Prosperity: The 

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Coffey, Bentley, Patrick A. McLaughlin, and Pietro F. Peretto. 2016. "The Cumulative Cost of 

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Crain, W. Mark, and Thomas D. Hopkins. 2001. The Impact of Regulatory Costs on Small Firms. 

Washington, DC: Office of Advocacy, Small Business Administration, October. 

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Dean, Thomas J., Robert L. Brown, and Victor Stango. 2000. "Environmental Regulation as a 

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Kitching, John, Mark Hart, and Nick Wilson. 2015. "Burden or Benefit? Regulation as a 

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Journal33,no.2: 130-47. 

Kugler, Maurice, Marios Michaelides, Neha Nanda, and Cassandra Agbayani. 2017. 

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McLaughlin, Patrick A., and Oliver Sherouse. 2017. "QuantGov-a Policy Analytics Platform." 

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Research Foundation, August. 

32 
75 

Table 1. Distribution of Firms by Size in the US, 1998-2015 

Year Total 0--4 <500 500+ 

1998 5,579,177 3,376,351 1,011,849 5,562,799 16,378 

1999 s,so1;743 3r3S.9,l61 1,012.;9.54 5,591,003 16,740 

2000 5,652,544 3,396,732 1,021,210 617,087 515,977 84,385 5,635,391 17,153 

2001 5,65Ul4 3;401,676 1,019,105 61$~064 518,158' 85,3D4 5,640,407 17,367 

2002 5,697,759 3,465,647 1,010,804 613,880 508,249 82,334 5,680,914 16,845 

2003 5,767,127 3,504A32 1,025~49:7 620,~87 515,056 84,829 5,750,201 16,926 

2004 5,885,784 3,579,714 1,043,448 632,682 526,355 86,538 5,868,737 17,047 

2005 5,983,546 3/)77,879 1,050,062 629-,946 s:w,as? 81,185 17,477 

2006 6,022,127 3,670,028 1,060,787 646,816 535,865 90,560 6,004,056 18,071 

2007 6,049,655 :vos,ns 1,060,250 6~4,842: 532,391 88,586 6,031)344 18,311 

2008 5,930,132 3,617,764 1,044,065 633,141 526,307 90,386 5,911,663 18,469 

2009 5~767,30:6 '3,558,708 1~001,313 610,777 495,673 83,326 5,749,797 17,509 

2010 5,734,538 3,575,240 968,075 617,089 475,125 81,773 5,717,302 17,236 

2011 5;684,424 3,531,058-' 9781993 592,963 481,496 81,243 5,666,753 17,671 

2012 5,726,160 3,543,991 992,716 593,641 494,170 83,423 5,707,941 18,219 

201.3- ,5,775,055 3,575,290 992,281 600,551 50'3,033 85,264 5,756,419 18,6'36 

2014 5,825,458 3,598,185 998,953 608,502 513,179 87,563 5,806,382 19,076 

13.2018, 

https:/iwww.census.gov/programs~survcyslsusb/data!tablcs.html. 

33 
76 

Table 2. Distribution ofEmpJoyment by Firm Size in the US, 1998--2015 

Year Total o-4 S-9 10-19 <20 20-99 10D--499 <500 500+ 

1998 108,117,731 5,584,470 6,643,285 8,047,650 20,275,405 19,377,614 15,411,390 55,064,409 53,053,322 

1999 110,705~661 S-,606,302 6,652;3'70 8,~29,615 20,388,28'7 19,703,1$2 15,63.'7,64.3 55,7:.!'9,092 54-,976,569 

2000 114,064,976 5,592,980 6,708,674 20,587,385 20,276,634 16,260,025 57,124,044 56,940,932 

2001 115,061,184 5,630,017 6,698~077 20,602,635 20,370,447 16,410,367 57,3-83.449 57,577,735 

2002 112,400,654 5,697,652 6,639,666 8,246,053 20,583,371 19,874,069 15,908,852 55,366,292 56,034,362 

2003 113,398,043 5,7-68,407 6,732,132 8,329,813 20,830,3:54 20,186,9$9 1$,430,2:1.9 57,447,570 SS,950A73 

2004 115,074,924 5,844,637 6,852,769 8,499,681 21,197,087 20,642,614 16,757,751 58,597,452 56,477,472 

2005 116,317,003 5,936,859 6,898,483 8,453,854 21,289,196 20.444>349 16,911,040 58,644,585 57,672,4Ut 

2006 119,917,165 5,959,585 6,973,537 8,676,398 21,609,520 21,076,875 17,537,345 60,223,740 59,693,425 

:1.007 120,604,265 6,139,469- 6,974,$91 8,656,182 z-:c770,236 20,922,960 17,173,728 59,866,924 60,737,341 

:/.008 120,903,551 6,086,291 6,878,051 8,497,391 21,461,733 20,684,691 17,547,567 59,693,991 61,209,560 

2009 114,509,626 5,966,190 6,580,~30 8,19l,lS9 zo,ns,sos 19,389,940 16~1:53.,254 56,2.81)503 58/2:2:8,123 

2010 111,970,095 5,926,452 6,358,931 8,288,385 20,573,768 18,554,372 15,868,540 54,996,680 55,973,415 

20l.l 113,425,965 5,857,662 6,431,931 7,961,28! 20,250,874 18,880,001 15,867,4~7 54,998,312 58,427,653 

2012 115,938,468 5,906,506 6,527,943 7,974,34{) 20,408,789 19,387,24'9 16,266,855 56,062,893 59,875,575 

201:; 118,2.66,253 5)926,660 6,523,516 8,058,077 20,S:08,253 19,697,707 16,'617,417 56,823,3:77 61,442,876 

2014 121,069,944 5,940,248 6,570,776 8,176,519 20,687,543 20,121,588 17,085,461 57,894,592 63,175,352 

34 
77 

Table 3. Annual Growth of Industry-Specific Regulations 

Year Regulatory growth(%) Year Regulatory growth (%) 

1999 3.13 2008 5.09 

2000 0.&2 2009 3.46 

2001 3.76 2010 4.82 

4002 3.06 2011 4.54 

2003 3.06 2012 6.70 

·'2004 6.02 2013. '3.62 

2005 3.49 2014 2.95 

2006 2.37 2015 s:ss 2007 1.73 

Note: Table displays average year-over-year rate of growth of industry-specific regulations. 

Source: RcgData 3.0. 

35 
78 

Table 4. Weighted Regulatory Restrictions by Year 

1999 2$,681 Z1,819 21,321 20,228 

2000 26,300 22,446 21,889 20,906 18,367 15,099 

2001 :26,864 2:2,989 22A96 2:1,553 18}973 15,562 

2002 27,400 23,186 22,603 21,764 19,123 16,098 

2003 22,250 18,765 18,327 17,$65 17,'152 14,880 

2004 22,750 19,353 18,770 18,239 17,423 15,083 

2005 23,233 19,741 19,204 18,803 17,870 15,428 

2006 23,599 20,133 19,698 19,162 18,213 15,815 

2007 24,56.1 20,070 20,09'~ 1~,487 18,313 16,036 

2008 25,169 21,382 20,227 18,791 16,401 

2009 2:6,033 21,907 20,960 19,118 16,702 

2010 26,558 22,390 21,930 21,476 19,463 17,138 

2011 27;714 23,176 22:,651 22,200 20,172 17,686 

2012 29,290 24,439 24,111 23,727 21,565 18,889 

2013 29,790 24,990 24,585 .(4,225 22,071 19,378 

2014 30,508 25,648 25,143 24,784 22,774 19,862 

13,2018, 

36 
79 

Figure 1. Index of Weighted Regulation by Firm Size 

120 

500-+ 

110 

100 

90 

80 

70 

60 

50 

Note: For each finn size category (e.g., 10~!9 employees), the corresponding weighted regulations (see table 4) are divided by the weighted regulations for small 

finns in 1998 (25,633 weighted regulatory restrictions), and the result!ng ratio is multiplied by 100. Thus. the indexes are relative measures equal to 100 when 

the regulatory burden equals that faced by small firms in 1998. 

Source: US Census Bureau, "Statistics of US Businesses: Annual Data Tables by Establishment lndustry," accessed February 13,2018, 

https://www.ccnsus.gov/programs~surveys/susb/data/tables.html; Reg Data 3.0; authors' calculations. 

37 
80 

Figure 2. Total Small Firms vs. Small Firm Index of Weighted Regulation 

155 

145 

135 

125 

115 

105 

95 

85 

2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 

Note: The index of small finns equals the total number of smaU firms each year divided by the number of small firms in 1998, and this ratio is multiplied by 100 

The regulation index is the firm~size-wcightcd measure of regulations faced by small firms divided by the weighted regulations for small firms in 1998 (25,633 

weighted regulatory restrictions); again, the resulting ratio is multiplied by 100. 

Source: US Census Bureau. "Statistics of US Businesses: Annual Data Tables by Establishment Industry," accessed February 13,2018, 

https:J/www.ccnsus.gov/programs-survcysisusb/data/tab!es.html; RegData 3.0; authors' calculations. 

38 
81 

Figure 3. Total Large Firms vs. Large Firm Index of Weighted Regulation 

145 

135 

125 

115 

105 

95 

85 

2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 

Note: The index of large finns equals the total number of large firms each year divided by the number of large firms in 1998, and this ratio is multiplied by 100. 

The regulation index is the finn-size-weighted measure of regulations faced by large firms divided by the weighted reg\llntions for large finns in 1998 (14,026 

weighted regulatory restrictions); again, the resulting ratio is multiplied by 100. 

Source: US Census Bureau, "Statistics of US Businesses: Annual Data Tables by Establishment Industry," accessed February 13, 2018, 

https://www.ccnsus.gov/programs-surveys/susb/data/tables.html; RcgData 3.0; authors' calculations. 

39 
82 

Table 5. Correlation between Total Firms of Varying Sizes and Weighted Regulation 

Period D-4 

2003-2015 

2009-2015 

-0,323 

-0.283 

Source: US Census Bureau, "Statistics of US Businesses: Annual Data Tables by Establishment Industry," accessed February 13,2018, 

https:/fwww.census.gov/programs-survcys/susb/data/tab!es.html; RegData 3.0; Authors' calculations. 

40 
83 

Figure 4. Growth of Total Firms in Industries with High vs.l.,ow Regulatory Growth 

10 

0.5 

0.0 

t:. 

'~ -0,5 

~ 0 

-1.0 

-

I ·15 

·20 

·2.5 

• low regulation growth 

• high regulation growth 

-I -I 

0-4 employees 5-9 employees 

~~ 

10-19 

employees 

20-99 

employees 

I 

100-499 

employees 

SOOt 

employees 

Note: For each finn size category, the average year-over-year growth rate oftotal firms within each industry was calculated. Industry-year observations for which 

the corresponding rate of regulatory growth was !ow (in the bottom quartile for the entire sample} were grouped and the overall average growth rate of total finns 

for the group was calculated. This procedure was repeated for the high regulatory growth group (in the top quartile). 

Source: US Census Bureau, "Statistics of US Businesses: Annual Data Tables by Establishment Industry," accessed February 13,2018, 

https://www.ccnsus.gov/programs-survcys!susb/data/tablcs.htm!; RcgData 3.0; m1thors' calculations. 

41 
84 

Figure 5. Impact of Consecutive Years of Regulatory Growth on Very Small Firms 

firms employment 

0.00 

-0.05 

-0.10 

-0.15 

~ 

1" -0.20 

I -0.25 

i -0.30 

•lyenr m3 year 

-0.35 

-040 

-0.45 

Note: Small finns with 0-4 employees were grouped on the basis of whether they experienced regulatory growth for one year, two consecutive years, or three 

consecutive years. The overall average growth rate of (I) total number of finns and (2) total employment was then calculated for each group 

Source: US Census Bureau, "Statistics of US Businesses: Annual Data Tables by Establishment Industry," accessed February 13,2018, 

http~://www.ccnsus.gov/programs-survcys/susb/dataltablcs.html; RcgData 3.0; authors' calculations. 

42 
85 

Figure 6. Impact of Consecutive Years of Above-Average Regulatory Growth on Very Small Firms 

firms employment 

DO 

"0.2 

-0.4 

-0.8 

-10 

-12 

-1.4 

-16 

Note: Small finns with 0-4 employees were grouped on the basis of whether they experienced above-average regulatory growth for one year. two consecutive 

years, or three consecutive years. The overall average growth rate of (I) total number of firms and (2) total employment was then calculated for each group. 

Source: US Census Bureau, "Statistics of US Businesses: Annual Data Tables by Establishment Industry," accessed February 13, 2018, 

https://www.ccnsus.gov/programs-survcys/susb/dataltables.html; RegData 3.0: authors' calculations. 

43 
86 

Table 6. Baseline Regression Estimates of Models (4) and (5) for Small and Large Firms 

(0.0203) (0.0206) (0.0317) (0.0211) (0.0295) (0.0409) 

Unemployment -0.3270 -0.3930* -0.1412 -0.3694 -0.6023"* -0.2705 

(0.2343) (0.2049) (0.4470) {0.2758) (0.3098) (0.5416) 

GOP gap 0.0407 0.1439 0.7270 0.1257 0.5756 1.6215** 

{0.3903) (0.3928) (0.7451) (0.4969) (0.6859) (0.8045) 

Observations 10,226 10,226 10,226 10,226 10,226 10,226 

Goodness of fit 0.149 0.194 0.103 0.135 0.166 0.166 

Notes: Dependent variable is the year-over-year growth rate of the total number nffirms or total employment. Intercept included but not reported. Industryspecific fixed effects included but not reported. White robust cross-section standard errors in parentheses. ***,**,and* denote I percent, 5 percent, and 10 

percent statistical significance, respectively. 

Source: US Census Bureau, "Statistics of US Businesses: Annual Data Tables by Establishment Industry," accessed February 13,2018, 

https://www.ecnsus.gov/programs-surveys/susb/data/tablcs.html; RegData 3.0; authors' calculations. 

44 
87 

Table 7. Marginal Impact of Regulations (Pre- and Post-2008) in Models (6) and (7) for Small and Large Firms 

Variables 

Pre-2008 dummy 0.6089 

(0.8678) {0.5696) {1.0116) (1.0224) (1.678) 

Regulatory growth -0.0854*"'"' -0.0811*'"* -0.0616 -0.0770*'" -0.1065""" -0.0861 

(0.0331) (0.0289) (0.0517) (0.0319) (0.0435) (0.0712) 

Regulatory growth x pre-2008 dummy 0.0700* 0.0915*** 0.0545 0.0863** 0.1186** 0.0799 

(0.0412) (0.0323) (0.0608) (0.0432) (0.0474) (0.0798) 

Unemployment 0.0348 -0.1124 -0.2388 0.0015 -0.5294 -1.0407 

(0.3127) (0.2296) (0.4692) (0.4015) (0.4176) (0.7265) 

GDPgap 0.2908 0.3528 0.6890 0.3879 0.6681 1.1812 

{0.3971) {0.3863) {0.7415) (0.5553) (0.7389) (0.8609) 

Observations 10,226 10,226 10,226 10,226 10,226 10,226 

Goodness of fit 0.151 0.197 0.104 0.137 0.169 0.169 

Notes: Dependent variable is the year~ovcr~ycar growth rate of the total number of firms or total employment. Intercept included but not reported_ Industry~ 

specific fixed effects included but not reported. White robust cross~section standard errors in parentheses.* .... ,**, and* denote 1 percent, 5 percent, and 10 

percent statistical significance, respectively. 

Source: US Census Bureau, "Statistics of US Businesses: Annual Data Tables by Establishment Industry," accessed Fcbntary l3, 2018, 

https://www.census.gov/programs-surveys/susb/data!tables.htm!; RegData 3.0; authors' calculations. 

45 
88 

Table 8.Impact of Consecutive Years of Above-Average Regulations on Small and Large Firms in Models (8) and (9) 

(0.4889) {0.7594) (0.6562) (0.4600) 

Regufatory growth -0.0448** -0.0355* -0.0320 -0 0309 -0.0499* -0.0320 

(0.0208) (0.0211) (0.0342) {0.0220) (0.0271) {0.0379) 

Regulatory growth x high growth dummy -0.1092** -0.0645* -0.0454 -0.0959** -0.0448 -0.1362** 

(0.0471) (0.0349) (0.0627) (0.0484) {0.0425) {0.0614} 

Unemployment -0.3290 -0.3933. -0.1471 -0.3684 -0.6040* -0.2793 

{0.2334) (0.2039) (0.4417) (0.2770) {0-3087) {0.5450) 

GDP gap 0.0338 0,1410 0.7166 0.1236 0.5715 1.6036 ... 

(0.3932) {0.3952) {0.7371) (0.4994) (0.6857) (0.8104) 

Observations 10,226 10,226 10,226 10,226 10,226 10,226 

Goodness of fit 0.150 0.194 0.104 0.136 0.166 0.167 

Note: Dependent variable is the year-over-year growth rate of the total number of small firms or total employment. Intercept included but not reported. Industry 

specific fixed effects included but not reported. White robust cross-section standard errors in parentheses. The high growth dummy equals one if the industry 

experienced two consecutive prior years of above-average regulatory growth.***,**, and • denote 1 percent, 5 percent, and 10 percent statistical significance, 

respectively. 

Source: US Census Bureau, "Statistics of US Businesses: Annual Data Tables by Establishment Industry," accessed February 13,2018, 

https://www.ccnsus.gov/programs-surveys/susb/data/tab!cs.html; RegData 3.0; authors' calculations. 

46 
89 

Regulation and Poverty 

An Empirical Examination of the Relationship 

between the Incidence of Federal Regulation and the 

Occurrence of Poverty across the States 

Dustin Chambers, Patrick A. Mclaughlin, 

and Laura Stanley 

MERCATUS WORKING PAPER 

process of academic evaluation, 

at feast one Working Papers present an 

author's proviSional findings, which. upon further consideratron and rev1sion. are ltkely to be republished in an 

academtc journal. The opinions expressed in Mercatus not represent 

~~~ MERCATUS CENTER 

~~~ George Mason University 3434 Washington Blvd, 4th Floor, Arlington, Virginia 22201 

www.mercatus.org 
90 

Dustin Chambers, Patrick A. McLaughlin, and Laura Stanley. "Regulation and Poverty: An 

Empirical Examination of the Relationship between the Incidence of Federal Regulation and the 

Occurrence of Poverty across the States." Mercatus Working Paper, Mercatus Center at George 

Mason University, Arlington, VA, 2018. 

Abstract 

We estimate the impact of federal regulations on poverty rates in the 50 US states using the 

recently created Federal Regulation and State Enterprise (FRASE) index, which is an 

industry-weighted measure of the burden of federal regulations at the state level. Controlling for 

many other factors known to influence poverty rates, we find a robust, positive, and statistically 

significant relationship between the FRASE index and poverty rates across states. Specifically, we 

find that a I 0 percent increase in the effective federal regulatory burden on a state is associated 

with an approximate 2.5 percent increase in the poverty rate. This paper fills an important gap in 

both the poverty and the regulation literature because it is the first paper to estimate the 

relationship between these variables. Moreover, our results have practical implications for federal 

policymakers and regulators, because the increased poverty that results from additional 

regulations should be considered when weighing the costs and benefits of additional regulations. 

JEL codes: D31, 132,138, K20, RIO 

Keywords: regulation, poverty, states, FRASE 

Author Affiliation and Contact Information 

Dustin Chambers 

Senior Affiliated Scholar, Mercatus Center at George Mason University 

Professor of Economics, Salisbury University 

dlchambers@salisbury .edu 

Patrick A. McLaughlin 

Director, Program for Economic Research on Regulation 

Mercatus Center at George Mason University 

pmclaughlin@mercatus.grnu.edu 

Laura Stanley 

Economist, Environmental Protection Agency 

stanley.laura@epa.gov 

© 2018 by Dustin Chambers and the Mercatus Center at George Mason University 

This paper can be accessed at https://www.mercatus.org/publications/federal-regulation-povertystates 
91 

Regulation and Poverty: 

An Empirical Examination of the Relationship between the 

Incidence of Federal Regulation and the Occurrence of Poverty across the States 

Dustin Chambers, Patrick A. McLaughlin, and Laura Stanley 

1. Introduction 

Poverty is one of the most pressing challenges that public policymakers face. Unfortunately, 

little consensus exists on how to remedy this stubbornly persistent problem. We argue in this 

paper that federal regulatory reform may offer a way forward. 

The link between poverty and regulatory policy has been widely neglected by 

economists. As such, this paper is the first to examine the relationship between poverty and 

federal regulations across the states. Although both regulation and poverty are interesting in their 

own right, we argue that there is an underappreciated connection between them that 

policymakers should consider when drafting new rules. Empirically estimating this relationship 

was impossible until recently because of the unavailability of state-level regulatory data. 

However, in this paper, we use the recently created Federal Regulation and State Enterprise 

(FRASE) index, which ranks the 50 states and the District of Columbia according to how federal 

regulations affect each state or district. Specifically, we characterize the association between 

poverty and regulation by exploiting variation across space and time in poverty rates and in the 

FRASE index among the states. Although variation in poverty rates is observational and remains 

to be explained, variation in the FRASE index arises by construction from two sources: 

(!)differences over time in the quantity of federal regulation targeting each industry in a state's 

3 
92 

economy and (2) year-to-year changes in the mix and relative importance of industries in each 

state (as measured by value added to the state's GDP). 1 

Before the release of the FRASE dataset, anyone seeking to research the impact of 

federal regulations at the state level faced a daunting task. The 2016 Code ofF ederal 

Regulations (CFR), which annually compiles all current federal regulations, spans 236 volumes 

and is more than 175,000 pages long (McLaughlin and Sherouse 2016). Manually reading the 

CFR, classifying each regulatory restriction by industry, and repeating this process for each prior 

year to construct a panel dataset would take decades? Fortunately, RegData, a suite of datamining and machine-learning algorithms developed by Al-Ubaydli and McLaughlin (2015) and 

McLaughlin and Sherouse (2016), has made it possible for computers to mine the CFR, identify 

regulatory restrictions, and probabilistically match these restrictions to the four-digit North 

American Industry Classification System industry codes to which they apply.3 

Although federal regulation applies to all states, each state's economy comprises a 

different mix of industries. As a result, regulations that affect a specific industry will affect states 

in different ways. To address this problem, McLaughlin and Sherouse, the makers of the FRASE 

index, matched and weighted national-level regulations (from RegData) by the relative 

importance of each industry to each state using input-output data available from the Bureau of 

Economic Analysis (BEA). 

We focus on regulations because economists have long recognized that they have both 

real and distributive effects on the economy. Friedman (1962) emphasizes that the relative 

1 For complete details on how the FRASE index is calculated, see the appendix to McLaughlin and Sherouse (2016, 

29-31). 

2 The Mercatus Center estimates that the average reader (reading at a rate of300 words per minute) would take 

nearly three years to read the current CFR if it were a full-time job: https://quantgov.org/regdata/the-code-of-federal 

-regulations-the-ultimate-longread/. 

' For more information on RegData, see https://quantgov.org/regdata/. 

4 
93 

distribution of income is a reflection of the operation of the market economy, given the initial 

endowments and preferences of participants and the success or failure of their individual 

economic decisions. Government policies, such as federal regulations, influence economic 

winners and thus the resulting income distribution. Higgs ( 1987) stresses that regulations reduce 

the sphere of private economic decision-making, because through regulations and restrictions, 

the government effectively makes choices for the private sector. Given that these predetermined 

choices are likely to be dynamically inefficient, the result is both reduced freedom and poorer 

long-run economic performance. 

Consistent with these theories, a growing number of recent papers empirically estimate 

the negative impact of federal regulations on the US economy. Using an older and less reliable 

measure of federal regulations (i.e., the number of pages in the CFR), Dawson and Seater (20 13) 

find that since 1949, the growth of federal regulations has significantly decreased the rate of US 

economic growth. Specifically, they estimate that the cumulative loss of output between 1949 

and 2011 totals $38.8 trillion. 4 Crain and Crain (2014) estimate that the annual cost offederal 

regulations equals $2 trillion. Coffey, McLaughlin, and Peretto (2016) find that iffederal 

regulations had been frozen in 1980 and subsequently never increased, the US economy would 

have been approximately 25 percent larger in 2015 than it actually was. Collectively, those 

results demonstrate that federal regulations represent a significant economic headwind that slows 

economic growth and reduces real incomes. Even in a best-case scenario whereby these impacts 

affect all income groups proportionately (i.e., there is no change in income inequality), the 

absolute income levels of low-income individuals would be reduced and there would be more 

4 To put that number into perspective, note that the nominal GDP in 2011 equaled $15.8 trillion (see http://www.bea 

.gov). Therefore, the cumulative impact of regulations from 1949 to 2011 was roughly 2.5 times the size of the US 

economy in 20 l J. 

5 
94 

people living below any absolute poverty threshold. Unfortunately, recent research finds ample 

evidence that regulations have regressive effects-that is, that regulations have a 

disproportionately negative impact on poorer households. 

There is a growing body of literature on the regressive effects of regulations. Such effects 

include costly risk mitigation, higher consumer prices, barriers to entry (such as those created by 

occupational licensure and startup regulations), and compliance costs and mandates. These 

strands of the literature both individually and collectively demonstrate that regulations 

disproportionately hurt the most vulnerable in society, including would-be entrepreneurs; those 

with less education, fewer skills, and less job experience; and those with less income and 

political clout. Therefore, it is not unreasonable to hypothesize that greater regulation, all else 

being equal, diminishes economic mobility and reduces the economic opportunities of 

low-income individuals, thereby making it harder to escape poverty. We next briefly summarize 

each of these facets of the literature on the regressive effects of regulation. 

Thomas (2012) argues that regulations aimed at reducing health and safety risks tend to 

be regressive. High-income earners, relative to low-income earners, have a higher willingness to 

pay to mitigate low-probability risks. When federal regulations target low-probability risksespecially those that are expensive to mitigate-all households pay for them in the form of lower 

wages and higher prices. These costs are disproportionately borne by low-income earners. 

Chambers, Collins, and Krause (2018) find empirical evidence that the poorest households spend 

a larger proportion of their income on goods and services that are heavily regulated, suggesting 

that the regulations have a regressive effect. 

Small business owners and would-be entrepreneurs are also disproportionately affected. 

Crain and Crain (2010) find that small businesses bear most of the costs of regulation. Chambers, 

6 
95 

McLaughlin, and Stanley (20 18) find that countries with more barriers to business entry tend to 

experience higher levels of income inequality. Chambers and Munemo (2017) find that nations 

with more startup regulations also have lower rates of entrepreneurship. Bailey, Thomas, and 

Anderson (2018) find that regulations lead to an increase in the relative demand for complianceoriented professionals (e.g., lawyers and accountants), which means lower wage growth and 

fewer job prospects for less educated, noncompliance workers. McLaughlin, Ellig, and Shamoun 

(2014) find that occupational licensing has a disparate impact on the economically vulnerable, 

including ethnic minorities. Kleiner and Krueger (2013) estimate that nearly one-third of workers 

were affected by occupational licensure regulations as of 2008. Taken together, these findings 

suggest that regulations diminish opportunities for social mobility and economic advancement, 

thus stranding many in a life of poverty. 

Although the previous literature on regulation has focused on its regressive impact on 

prices, entrepreneurship, or inequality, all of which are determinants of poverty, no study has 

provided a comprehensive analysis of the impact of regulation on poverty itself. This paper fills 

that gap in the literature by examining the regressive relationship between regulation and the 

poverty rate across US states. We find a significant and positive relationship between the FRASE 

index and poverty levels across states. Specifically, we find that a 10 percent increase in the 

effective federal regulatory burden on a state is associated with an approximate 2.5 percent 

increase in that state's poverty rate. 

In the remainder of the paper, we describe the benchmark empirical poverty rate model 

commonly used in the development literature, from which we build our model of interest. We 

discuss the data used in our analysis and present the regression results and associated robustness 

tests before concluding. 

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2. The Benchmark Empirical Model 

If a poverty line can be expressed as a threshold monetary value, Dhongde (2006) shows that the 

poverty rate (P) can be expressed as function of mean income (Y) and the Lorenz curve (f) by 

way of the following identity: 

P = f(Y,f(Y)). (l) 

In practice, data on the precise distribution of income are unavailable, so a summary 

measure of the relative income distribution, typically the Gini coefficient, is used as a proxy for 

the Lorenz curve. This yields the model below, wherein E captures variation in the poverty rate 

explained by the Lorenz curve but not the Gini coefficient: 

P = g(Y, Gini) +E. (2) 

Equation (2) represents the core functional relationship from which we derive the linear 

benchmark regression model. Following the development literature, this equation can easily be 

adapted to fit a panel framework. For example, Meng, Gregory, and Wang (2005) and 

Chambers, Wu, and Yao (2008) use a similar double-log benchmark model to study poverty 

rates in Chinese provinces: 

(3) 

where Ptt is the natural log of the poverty rate; a; is a cross-sectional fixed effect that captures 

idiosyncratic differences in the mean poverty rate for a province, state, or nation not otherwise 

explained by the other independent variables; l)t is an exogenous time trend (i.e., l)t = t); Ytt is 

the natural log of mean income; g initt is the natural log of the Gini coefficient; and Ett is a mean 

zero error term. Many papers in the development literature have sought to estimate the 

coefficient on log mean income (i.e., {12 ), also known as the growth elasticity of poverty. In this 

strand ofthe literature (see, for example, Adams 2004, Ram 2007, and Chambers and Dhongde 

8 
97 

2011 ), common practice is to take model (3) and transform it by way of a first difference. This 

exercise has the advantage of removing both the cross-sectional fixed effects (a;) and the 

exogenous trend, yielding a simpler regression model: 

(4) 

where deltas denote first differences-that is, ll.Ptt =Pit- Pit-lo ll.Ytt = Yit- Ytt-1• and 

lJ.gini1t = gini;t- ginitt-t· In the analysis to follow, we extend both benchmark specifications 

to estimate the relationship between regulatory burden and poverty across the US states. 5 

3. The Regulation-Poverty Empirical Model 

To estimate the impact of federal regulations on poverty across the 50 US states and the District 

of Columbia, we add the FRASE index to the benchmark models in section 2. Given the poverty 

decomposition formulated by Dhongde (2006), adding the FRASE index to the benchmark 

models implicitly assumes that when federal regulations are more burdensome in a given state, 

the result is a change in the underlying distribution of income. This assumption is consistent with 

the arguments of Friedman ( 1962) mentioned earlier. By influencing and affecting market 

outcomes, federal regulations likely affect the resulting income distribution (i.e., government 

policies help to influence the economic winners and losers). The literature also finds empirical 

evidence that regulations affect the overall level of output of an economy (see Dawson and 

Seater 2013, Crain and Crain 2014, and Coffey, McLaughlin, and Peretto 2016, among others), 

which suggests that including both the FRASE index and mean income in a linear regression 

model will likely introduce some multicollinearity. Although this effect does not bias the 

5 The decomposition of changes in poverty into changes in income distribution (inequality) and changes in mean 

income (growth) has a long history in development economics. It was first pioneered by Datt and Ravalli on ( 1992) 

and was later used by many subsequent scholars (see, for example, Bourguignon 2003). 

9 
98 

coefficient point estimates, it will inflate standard errors and reduce statistical significance. 

Adding the FRASE index to equation (3) yields the following: 

(5) 

where [rase it is the natural log of the FRASE index; the remaining variables retain their original 

specifications and interpretations. Adding the FRASE index to equation (4) yields the following: 

(6) 

where 6fraseit is the first difference of the natural log of the FRASE index; as before, the 

remaining variables retain their original specifications and interpretations. 6 Thus, equations ( 5) 

and (6) will serve as the benchmark regression models to test the empirical impact of federal 

regulatory burden upon the poverty rates of states. 

4. The Data 

The data we use on poverty come from the US Census Bureau and measure the proportion of 

households with incomes that fall below the poverty line, i.e., a threshold dollar amount, for a 

family of their size and composition. For example, in 2016, the poverty line for a four-person 

family consisting of two adults and two children equaled $24,339.7 The poverty line does not 

vary by state, and it is adjusted annually for inflation. The data on mean income are from the 

BEA and equal the real per capita GDP for each state in chained 2009 dollars.8 The Gini 

coefficient panel is an update of the one constructed by Frank (2009), which is derived from 

individual income tax filings from the Internal Revenue Service9 

6 Following common practice, we retain the period fixed effect in equation (6) despite its first-difference derivation. 7 Poverty rates and threshold values can be obtained from the Census Bureau website: http://www.census.gov/topics 

lincome-povertylpoverty.httnl. 

8 Data on real per capita GDP can be accessed at the BEA website: https:llwww.bea.gov/regionall. 9 The Gini panel can be downloaded from Frank's website: http://www.shsu.edu/eco_mwflinequality.httnl. 

10 
99 

Finally, we use the FRASE index, which measures the burden of federal regulations in a 

given state using state-specific industry weights, to determine the regulatory exposure. 10 The 

FRASE index relies on a combination of regulatory data from RegData and economic data from 

the BEA. To calculate the FRASE index score for each state, McLaughlin and Sherouse (2016) 

start with the number of regulatory restrictions targeting each industry, as estimated in the 

RegData 2.2 dataset. Those levels of industry-specific regulatory restrictions are then weighted 

according to each industry's importance to a particular state's private-sector economy relative to 

that industry's importance to the nation as a whole. Thus, if an industry contributes twice as 

much to a state's private sector as it does to the nation's, the restrictions count twice as much for 

that state. In this paper, we sum the result across all industries and scale the resulting score to 

that of the nation overall. 

The result shows the impact of federal regulation on states relative both to the nation and 

to other states. A FRASE index score of 1 means that federal regulations affect a state to 

precisely the same degree that they affect the nation as a whole. A score greater than 1 means 

that federal regulations have a higher impact on the state than on the nation, whereas a score less 

than 1 means that they have a lower impact on the state. 

The combined, balanced panel spans the period from 1997 to 2013 and includes all 50 US 

states plus the District of Columbia (867 observations). 11 Table 1 contains summary statistics for 

the benchmark dataset by state. The simple average poverty rate across the states between 1997 

and 2013 equals 12.56 percent, with the highest average rate equaling 19.22 percent (Mississippi) 

and the lowest average rate equaling 6.91 percent (New Hampshire). The simple average real per 

10 The FRASE index can be downloaded from the Mercatus Center's RegData website: https://quantgov.org 

/50states/. 

11 Going forward, we will treat the District of Columbia as a state: instead of referring to the "50 US States plus the 

District of Columbia," we will simply refer to the group as "the states." 

11 
100 

capita GDP across the states between 1997 and 2013 equals $46,939, with the highest average 

hailing from the District of Columbia ($156,40 1) and the lowest average coming from Mississippi 

($30,641). Frank's Gini coefficients are quite large, with the average value across all the states 

and time periods equaling 0.59. The lowest average Gini equals 0.55 (Iowa), and the highest 

average equals 0.66 (both Florida and New York). Finally, the simple average value of the 

FRASE index across the states and time periods equals 1.22, which implies that the states, on 

average, experienced a relative regulatory burden between 1997 and 2013 that was 22 percent 

higher than the US average in 1997. The state with the highest average FRASE index is Louisiana 

(2.03), whereas the state with the lowest average FRASE index is New Hampshire (0.82). 

Table 1. Mean Panel Values, 1997-2013 

Poverty rate Real GOP Gini FRASE 

Alaska 9.46 64,084 0.58 1.99 

Arizona 16.00 39,710 0.59 1.03 

Arkansas 16:87 34,342 0.60 1.2:4 

California 14.28 50,360 0.64 1.11 

Colorado 10.36 49,877 0:59 1.04 

Connecticut 8.81 62,613 0.64 1.19 

D~laware 10.23 63,123 0.56 1.04 

District of Columbia 18.48 156,401 0.62 0.91 

Florida 13.19 39,544 0.66 1.01 

Georgia 14.59 44,029 0.61 1.15 

Hawaii 10.72 47,303 0.56 1.02 

Idaho 12.31 34,372 0.61 1.23 

Illinois 11.85 50,152 0.61 1.12 

Indiana 11.57 42,015 0.57 1.60 

Iowa 9.60 43,478 0.55 1.31 

Kansas 11.85 42,317 0,58 1.42 

Kentucky 15.64 37,254 0.58 1.53 

Louisiana 18.01 44,826 0.62 2.03 

Maine 11.54 37,335 0.56 0.95 

Maryland 8.77 50,047 0.56 0.95 

Massachusetts 10.66 56,986 0.61 0.93 

Michigan 12.27 40,985 0.58 1.30 

Minnesota 8.86 49,495 0.57 1,04 

Mississippi 19.22 30,641 0.61 1.34 

Missouri 12.29 41,910 0.59 1.17 

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101 

Montana 14.34 34,908 0.62 1.36 

Nebraska 10.28 45,982 0.59 1.35 

Nevada 11.67 48,002 0.63 0.87 

New Hampshire 6.91 45,391 0.57 0.82 

New Jersey 8.90 54,893 0.60 L16 

New Mexico 18.8"5 39,232 0.60 1.23 

New York 15.03 56,932 0.66 1.07 

North Carolina 14.74 43,294 0 .. 58 1.37 

North Dakota 11.49 43,967 0.58 1.41 

Ohio 12.40 42,964 0.56 1.20 

Oklahoma 14.19 37,013 0.60 1.37 

Oregon 12.65 43,080 "0.58 1.00 

Pennsylvania 11.03 43,997 0.59 1.14 

Rhode Island 11.79 44,282 0.57 0.84 

South Carolina 14.30 36,335 0.59 1.13 

South Dakota 11.89 41,410 0.61 1.28 

Tennessee 15.16 40,331 0.60 1.19 

Texas 16.38 46,741 0.63 1.49 

Utah 9.20 40,785 0.58 1.09 

Vermont 9.45 39,484 0.58 0.96 

Virginia 9.74 49,809 0.57 1.09 

Washington 10,73 51,363 0.58 1.31 

West Virginia 16.09 33,219 0.56 1.61 

Wisconsin 10.06 43,523 0.56 1.04 

As a preliminary step, we calculate the correlation matrix for poverty, real per capita 

income, the Gini coefficient, and the FRASE index, all expressed as natural logarithms. The 

results (see table 2), though only anecdotal, are consistent with our prior expectations. 

Specifically, poverty is negatively correlated with log per capita income (-0. 146), implying that 

states with higher mean incomes exhibit less poverty. Likewise, log poverty is positively 

correlated with the log of the Gini coefficient (0.340), consistent with the notion that as income 

inequality rises, absolute living standards for the poorest households decline, thus increasing the 

poverty rate. Finally, log poverty is also positively correlated with the log of the FRASE index 

(0.335), implying that states that are effectively more federally regulated also possess higher 

poverty rates. 

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Table 2. Panel Correlation Table 

5. Benchmark Estimation Results 

5.1. Estimation Results for Equation (5) 

Table 3 reports the estimation results for five variants of equation (5). In column (1), the log 

poverty rate is regressed on a pooled constant (not reported), the log of the FRASE index, the log 

GDP per capita, and the log Gini coefficient. In line with prior expectations, the coefficient on the 

log FRASE index (0.2879) is positive and statistically significant at the 1 percent level. This 

finding implies that a 1 percent increase in binding federal regulations is associated with a 0.2879 

percent increase in the poverty rate. The coefficient on the log output has the appropriate sign 

(-0.2113) and is statistically significant at the 1 percent level, implying that a 1 percent increase 

in output reduces the poverty rate by just over 0.2 percent. Finally, the coefficient on the log Gini 

coefficient is positive and statistically significant at the 1 percent level ( 1.4849), implying that a I 

percent increase in income inequality increases the poverty rate by 1.4849 percent. 

Column (2) is the same as column (1) but includes a time trend, as is common practice in 

the literature. The estimation results change very little: the coefficient on the log FRASE index 

equals 0.2596 and is significant at the 1 percent level. The coefficients on the log output and the 

log Gini coefficient are nearly unchanged, and both remain statistically significant at the 1 

percent level. The added time trend is statistically insignificant. 

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Table 3. Equation (5) Estimation Results 

Variables 

log FRASE 0.2879*** 0.2596*** 0.2504*** 

(0.0390) (0.0170) (0.0205) (0,0929) (0.0903) 

Log output -0.2113*** -0.2224*** -0.2075*** -1.0313*** -0.8060*** 

(0.0237) (0.0241) (0,0277) (0.1164) (0.0684) 

Log Gini 1.4849*** 1.4057*** 1.6036*** -0.0543 -0.0087 

(0.1014) (0.1368) (0.1865) {0:1223) (0.1037) 

Time trend 0.0034 0.0200*** 

(0.0037) (0.0037) 

Fixed state effects No No No Yes Yes 

Fixed period effects No No Yes No Yes 

Observations 867 867 867 867 867 

Goodness of fit 0.222 0.224 0.277 0.837 0.860 

Notes: (l) Dependent variable is the log of the poverty rate; (2) intercept included but not reported; (3) White robust 

cross-section standard errors in parentheses; (4) ***,**,and* denote 1 percent, 5 percent, and 10 percent statistical 

significance, respectively. 

Column (3) is similar to column (2). but fixed period effects replace the time trend. The 

coefficient on the log FRASE index is virtually unchanged and remains statistically significant at 

the 1 percent leveL The coefficient on the log output also changes very little and remains 

statistically significant The coefficient on the log Gini coefficient remains significant at the 1 

percent level but increases in magnitude to 1.6036. 

Columns (4) and (5) include state fixed effects. The overall goodness of fit of these 

models ranges from 0.837 to 0.860, much larger than the R2 values reported in the first three 

columns (0.222 to 0.277). which ignore state-specific heterogeneity in the poverty rate. Column 

(4) includes a time trend, whereas column (5) uses fixed time period effects. In column (4), the 

coefficient on the log FRASE index equals 0.2125 and is significant at the 5 percent leveL This 

finding is similar to that in column (5), in which the coeflicient on the log FRASE index equals 

0.2373 and is statistically significant at the 1 percent leveL In both columns (4) and (5), the 

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coefficient estimate on the log output is negative and statistically significant at the 1 percent 

level, ranging in estimated value from -0.8060 to -1.0313. This finding implies that a 1 percent 

increase in the log per capita output reduces poverty by 0.8060 percent to 1.0313 percent. 

Finally, the coefficient on the log Gini coefficient is statistically insignificant in both columns (4) 

and (5). The coefficient on the time trend in column (4) is positive and statistically significant 

(0.02), implying that poverty rates are drifting 2 percent higher each year, all else being equal. 

5.2. Estimation Results for Equation (6) 

Column (I) of table 4 reports the estimation results for the baseline version of equation (6). 

Because taking the first difference of the model's variables eliminates state heterogeneity, only 

fixed period effects are considered. 12 The coefficient on the first difference of the log FRASE 

index (0.2944) is statistically significant at the 5 percent level and in line with the previous results 

from equation (5), suggesting that a I percent increase in binding regulations is associated with an 

approximate 0.3 percent increase in the poverty rate. The coefficient on the first difference of the 

log output is negative but statistically insignificant. Likewise, the coefficient on the first 

difference of the log Gini coefficient has the correct sign but is also statistically insignificant. 

12 Any exogenous trend variables become constants. 

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Table 4. Estimation Results for Equations (6)-(9) 

(0,136) (M339) (0.1315) (O.U51) (0.133£) (0.1267) (0.1224) (0.1235) 

t. (log output) -0.1102 -0.0701 -0.1035 -0.0837 -0.0614 -0.0693 -0.1065 -0.0609 

ID.1752) (0.2329) (0-18:71) (0.1702) (0.253S) (0.23£2) (0.1866) (0.2527) 

A(fogGini) 0.1825 0.0071 0.0347 -0.0063 0.0348 -0.0062 0.0242 0.0242 

(0.288) (0,2840) (0.2942) (Q.2675) (0.29!!7) (0.2877} (0.2976) (0.2971) 

8 (fog government) 0.0120 0.0522 0.0180 0.0566 

(0.1385) (0.1397) (0.!395) (0.141) 

e. (log high school) 0502.5 05064 0.4933 0.4974 

(0.5814) (0.57571 (0.5813) (0.5757) 

8. {log agticuftur.e) 0.0332: 0.0334 0.0279 0.0284 

(0.0257) (0.0262) (0.026!) (0.0269) 

Observations 816 800 750 800 750 800 750 750 

17 
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6. Robustness Results 

To ensure that our results are robust to the inclusion of other independent variables, we add three 

additional explanatory variables connnon to the poverty literature. Regardless of how these 

additional explanatory variables are added (individually, in pairs, or as a group), the regulation 

coefficient is consistent in sign and magnitude, averaging 0.2779, and statistically significant in 

all cases. In other words, a 1 percent increase in binding federal regulations is associated with 

increases in state-level poverty rates of just under 0.28 percent, which is consistent with our 

findings from the baseline model. 

6. I. Government Expenditures 

Following Chambers, Wu, and Yao (2008), we include the size of public expenditures relative to 

the size of the state economy as a proxy for the relative provision of public services and public 

goods and the overall size and scope of government within each state economy. 13 The resulting 

model, which builds on equation (6), is specified as follows: 

!lpit = fJ1 + flzi1Yit + f33!1giniit + f34!1{raseit + fls!!t.govit + T/t + uit• (7) 

where !lgovit is the first difference of the log of state government expenditures as a fraction of 

state GDP and "fit is a fixed-effect time period dunnny. Estimation results are provided in column 

(2) of table 4. Focusing on the variable of interest, the coefficient estimate on the first difference 

of the log of the FRASE index equals 0.2752 and is statistically significant at the 5 percent level. 

This is very consistent with the previous estimation results and suggests that a 1 percent increase 

in binding federal regulations is associated with increases in the state poverty rate of just under 

0.28 percent. 

"Government expenditures and state GDP data are obtained from the US BEA. 

18 
107 

6.2. Human Capital 

Following Chambers, Wu, and Yao (2008); Apergis, Dincer, and Payne (2011); and Johnson, 

Formby, and Kim (2011), we include a measure of educational attainment as a proxy for human 

capital levels within each state. In principle, states with more human capital should have less 

structural unemployment, higher labor force participation rates, and higher real eamings. 14 The 

resulting model, which builds on equation (6), is specified as follows: 

where tleducation;t is the first difference of the log of the high school completion rate (given as 

a percentage) and 17t is a fixed effect time period dummy. Estimation results are provided in 

column (3) of table 4. Focusing on the variable of interest, we find that the coefficient estimate 

on the first difference of the log of the FRASE index equals 0.3169 and is statistically significant 

at the 5 percent level. This finding is very consistent with the previous estimation results and 

suggests that a I percent increase in binding federal regulations is associated with increases in 

the state poverty rate of just under 0.32 percent. 

6.3. Agriculture 

Following Chambers, Wu, and Yao (2008), we include a measure of the relative size of the 

agricultural sector within each state. Given that highly agrarian and rural economies have lower 

wages and greater seasonality in employment patterns, we anticipate a positive relationship 

between the relative size of the agricultural sector and the poverty rate. 15 The resulting model, 

which builds on equation (6), is specified as follows: 

14 High school completion rate data are from the US Census Bureau and can be accessed at https://www.census.gov 

/topics/educationleducational-attainmentldata.html. 

15 Agricultural output (North American Industry Classitlcation System sector ll) and state GDP data are obtained 

from the US BEA. 

19 
108 

Llpit = P1 + {J2ilYit + {J3Llginiit + {J4Llfraseit + {J5Llagricultureit + 7Jt + uit• (9) 

where Llagricultureit is the first difference of the log of the output of the agricultural sector as a 

percentage of state GDP and 7Jt is a fixed effect time period dummy. Estimation results are 

provided in column (4) of table 4. Focusing on the variable of interest, we note that the 

coefficient estimate on the first difference of the log of the FRASE index equals 0.2332 and is 

statistically significant at the l 0 percent level. This finding is very consistent with the previous 

estimation results and suggests that a 1 percent increase in binding federal regulations is 

associated with increases in the state poverty rate of just over 0.23 percent. 

6.4. Combined Effects 

As a final robustness exercise, we include every pairing of the above explanatory variables (i.e., 

government expenditures, high school completion rates, and the relative size ofthe agricultural 

sector) in columns (5) to (7). The resulting coefficient estimates on the FRASE index range in 

value from 0.2338 to 0.3195 and are universally statistically significant. Finally, we include all 

three of these robustness variables in the augmented model (see column (8)). The resulting 

coefficient on the FRASE index equals 0.2845 and is statistically significant at the 5 percent leveL 

7. Conclusion 

Consistent with economic theory, previous empirical research has documented that regulations 

reduce real incomes and regressively affect consumer prices, entrepreneurship, and income 

inequality. Given these demonstrable effects, it is not unreasonable to suspect that regulations 

also increase poverty rates. However, no study has provided a comprehensive analysis of the 

impact of regulation on poverty. 

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109 

This paper fills this gap in the literature by being the first to examine the impact of 

federal regulations on poverty within the United States. Until recently, however, empirically 

estimating this relationship was impossible because of the unavailability of state-level regulatory 

data. But we use the FRASE index, which ranks the 50 states and the District of Columbia 

according to how federal regulations affect each state. Controlling for a large number of other 

factors known to influence poverty rates, we find a robust, positive, and statistically significant 

relationship between the FRASE index and the poverty rates across states. Specifically, we find 

that a 10 percent increase in the effective federal regulatory burden on a state is linearly 

correlated with an approximate 2.5 percent increase in that state's poverty rate. Although our 

analysis does not necessarily demonstrate a causal relationship, we find the relationship between 

federal regulation and state poverty rates to be robust to the inclusion of other explanatory 

variables common to the poverty literature, including government expenditures, human capital, 

and the relative size of the agricultural sector in each state. Consequently, we argue that there is a 

neglected and unappreciated connection between regulatory policy and poverty rates that 

policyrnakers and regulators should consider when drafting new rules. 

21 
110 

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Examination of the Effects of Regulatory Policy on the Economy 

and Business Growth 

Testimony by 

Karen Kerrigan 

President & CEO 

Small Business & Entrepreneurship Council 

Before the 

Subcommittee on Regulatory Affairs and Federal Management 

Committee on Homeland Security and Government Affairs 

United States Senate 

September 27, 2018 

The Honorable James Lankford, Chairman 

The Honorable Heidi Heitkamp, Ranking Member 

Protecting small business, promoting entrepreneurship 
113 

Chairman Lankford, Ranking Member Heitkamp and members of the subcommittee, thank you 

for holding this important hearing today and for the opportunity to provide testimony on the 

effects of regulatory policy on the economy and business growth. The Small Business & 

Entrepreneurship Council (SBE Council) is encouraged by the fact that federal agencies are 

taking steps to streamline and modernize rules, and examining how regulation may be impacting 

U.S. entrepreneurship and small business growth. The general direction of policy as well as a 

recent series of reform initiatives have helped to improve the U.S. policy ecosystem, and in turn 

have enabled startup activity and strong small business growth across the United States. 

My name is Karen Kerrigan and I serve as President & CEO ofSBE Council- a nonprofit, 

nonpartisan advocacy, research and education organization dedicated to protecting small 

business and promoting entrepreneurship. For nearly 25 years, SBE Council has worked on a 

range of private sector and public policy initiatives to strengthen the ecosystem for healthy 

startup activity and small business growth. In addition to research and advocacy, SBE Council 

provides educational tools and content to help startups, small businesses, and entrepreneurs 

better compete and succeed in the marketplace. 

The direction of regulatory policy over the past eighteen months or more has had a positive 

impact on the economy and small businesses. Regulatory relief along with a lighter volume of 

new regulation have helped to markedly improve small business confidence and the outlook of 

entrepreneurs, which has translated into a better business environment, higher sales and revenues 

for small businesses, and expansion and growth opportunities for these firms. Policy matters for 

small businesses, and they view the current regulatory path as being a constructive one that has 

allowed them to focus more intently on business growth and take additional risk. 

Small Businesses Are Confident 

When it comes to small business confidence, various surveys show comparable findings: It is 

exceptionally high. 

• According to the third quarter 2018 Wells Fargo/Gallup Small Business Index survey 

(released on August 7, 2018), "small business optimism is at an all-time high." The report 

indicated that optimism has reached its highest level in the survey's 15-year history, as reflected 

in small business owner attitude about their finances and projected cash tlow: "78 percent of 

small business owners reported their financial situation today is very or somewhat good, and 

84 percent of business owners said they expect their financial situation will be very or 

somewhat good a year from now ... Over the next year, 77 percent expect their cash flow to 

be very or somewhat good." According to the report, credit conditions have also vastly 

improved. 

• The NFTB's Small Business Optimism Index for August 2018 found that optimism reached 

a new record in the survey's 45-year history. "topping the July J 983 high water mark." According 

to the report, high optimism is ''driven by small business owners executing on the plans they've 

put in place due to dramatic changes in the nation's economic policy." 

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114 

• The Spring 20.1S Bank of America Business Advantage Small Business Report (released 

April 26, 20 18) reported that "confidence in the economy- both at the national and local levels 

is the highest it's been since 2015 and the second-highest in the history of the report." 

An important take-a-way from these reports is that small business confidence has stayed strong 

and consistent for a solid stretch oftime, which is creating a virtuous circle of activity - such as 

expansion, hiring, wage increases and investment all of which are critical for innovation, 

higher quality jobs, and the overall economy and its competitiveness. It is essential that elected 

officials and policymakers stay on a reform-minded path, as stability and consistency will help to 

sustain the stronger growth and confidence we are experiencing, and ensure that individuals and 

families left behind benefit from this period of growth. 

Regulatory Signals 

For small businesses, the change in the direction on regulatory policy has been a welcome 

development. The President's Executive Orders on streamlining regulation and cutting red tape 

(EO 13771 and EO 13777), combined with actions by the Congress on broad regulatory reform, 

and in specific areas (like reforms to improve capital access, for example) have made good on 

the regulatory signals that were sent to small business owners about where federal policy and 

actions would be headed at the beginning of the new Administration and during the 115'h 

Congress. These signals, and subsequent action, have provided a very powerful boost to 

entrepreneurs and small businesses. 

As we know, Executive Orders (EOs) come and go with each Administration and as we've 

experienced over the past twenty-five years in our work with four different Administrations, 

presidential leadership is critical to ensuring EOs are followed, implemented and sustained. SBE 

Council )las seen meaningful action by the agencies to fulfill President Trump's directives to 

reduce red tape and examine existing rules for potential modernization, streamlining or repeal. 

SBE Council staff and our members have participated in many roundtable meetings and events to 

provide our ideas and feedback on reforms. And we are pleased that small business participation 

specifically is driving momentum for important reforms that address the pain points of small 

businesses, such as access to capital, affordable health coverage, and regulatory excess or 

uncertainties that have harmed small firms in specific industries. 

We are very pleased that the Small Business Administration (SBA) Office of Advocacy has 

stepped up to assist with these regulatory policy EOs by weighing in as an independent voice and 

platform for action for small businesses. Advocacy has conducted significant outreach to small 

businesses in order to identify regulations for federal agencies and departments that are ripe for 

relief and reform. This activity is ongoing and has been very effective. 

For example, in direct response to EO 13771 and EO 13777, Advocacy is making sure that 

entrepreneurs and small business owners are being heard by hosting regional roundtables as 

well as through an online portal to collect ideas and suggestion for regulatorv changes. SBE 

Council is very active in promoting these activities, as we are confident that Advocacy will finish 

the job by making sure the appropriate regulatory agencies and/or staff "hear" the specific 

concerns and ideas of small business owners. 

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115 

As we have observed by reading Advocacy's ongoing reports regarding their engagement with 

small business owners, they are hearing what SBE Council hears from small business owners on 

a daily basis- that entrepreneurs understand some regulation is necessary, but federal rules need 

to be fair, practical, right-sized and take into consideration the compliance burden that regulation 

imposes on small firms because they have limited resources and are disproportionately impacted by 

regulation. 

The list of regulations identified by small business owners at these regional roundtables held 

over the past thirteen months cover a very wide range. But this should come as no surprise to 

those who understand the role that small businesses play in the U.S. economy, as they dominate 

almost every sector. 

At these events, small business owners representing various industries addressed how specific 

regulations- whether described as outdated, inappropriate, too restrictive or one-size-fits-all 

undercut their competitiveness and make business operations more costly or difficult. In total 

(and this does not include comments provided via the online portal) at least 24 different agencies 

are mentioned, covering scores and scores of regulations. I commend the SBA Office and 

Advocacy, under the leadership of Acting Chief Counsel Major Clark, for this important work. 

The office is posting reports on a timely basis and communicating the findings from these 

roundtables to the leaders of federal agencies and departments, which include the specific 

regulations identified by small businesses (and how they might be reformed) so that government 

officials can make informed decisions about additional steps that lead to changes. 

The SBA Office of Advocacy has been an enduring bright spot for small businesses across 

Administrations and that is why we have supported reforms that increase their capacity, and 

therefore their positive impact for small businesses. 

Small Business and Effective Regulatory Reform 

While "government regulation" has diminished as a top concern for many small business owners, 

it is still viewed as overbearing by a sizable portion of the small business community. For 

example, in an August 2018 Bi-Annual Trends Report from Small Business Expo, more than 

half or 51% of respondents said there is too much government regulation. Forty-two percent of 

business owners say there are just enough regulations, and seven percent believe there isn't 

enough. We also have to keep in mind that regulatory burden varies greatly by industry and the 

location of a small business. Some states and localities impose a greater volume of regulation 

and mandates on businesses than others- which translate into higher costs. 

A less onerous regulatory environment is ideal for entrepreneurship and strong small business 

growth. This has become a widely shared principle that has spurred countries across the globe to 

improve their regulatory systems. As noted by Kristalina Georgieva, Chief Executive Officer, 

The World Bank in a foreword for the ''Doing Business 2018" report, which presents 

quantitative indicators on business regulation and the protection of property rights across 190 

economies: "Over the past decade, more than 60 economies have established regulatory reform 

committees that use the Doing Business indicators. As a result, governments have reported more 

than 3,180 regulatory reforms, including about 920 reforms that have been inspired by Doing 

Business." 

4 
116 

These refonns have largely been inspired, and led, by business leaders and government officials 

in these many countries who understand that it is important to lower government barriers to 

encourage investment and entrepreneurship. In addition to my work with SBE Council 

advocating for U.S. entrepreneurs and small businesses, 1 have traveled to many countries to help 

government leaders understand, create and implement policies to encourage entrepreneurship 

and small business growth. The good news is that massive reforms have been enacted across the 

globe to help spur entrepreneurship, attract foreign investment, and enable capital fonnation. In 

terms of the U.S., it is important that we never become complacent in this regard. We must 

continually improve our policy environment, and that includes our regulatory systems. As small 

business owners have been stating for many years, the federal regulatory system is often 

unresponsive to the needs of startups and small businesses and regulators need to seek their input 

at the front end ofthe regulatory process and continually review what is on the books. 

That is why SBE Council strongly supports the regulatory reform measures advanced by the 

Homeland Security and Government Affairs Committee, including the "Small Business 

Regulatory Flexibility Improvements Act" (S.584), which builds upon the success of the 

Regulatory Flexibility Act (RFA). It creates a more uniform process by which the RFA would 

apply to proposed rules, and its broader application and measures would result in smarter 

regulation and a more accountable regulatory system for small businesses. Even though the RF A 

has been inconsistently applied or ignored over the years, it has still saved small businesses 

billions (more than $130 billion) in regulatory costs since these savings started to be quantified 

in 1998. (According to the SBA Office of Advocacy in its Report on the Regulatory Flexibilitv 

Act, .FY 2017,$913.4 million in regulatory cost savings were realized for small businesses in 

2017.) SBE Council believes the federal government can do better. 

For regulations to be small-business friendly, the process must be an informed one that 

incorporates relevant information and data regarding their impact and practicality. Small 

businesses must be included in this process, and all agencies need to abide by this framework. 

S.584 does this by: 

• Requiring a full economic impact of proposed regulations by including both direct and indirect 

effects that are "reasonable foreseeable." 

• Modifying the rulemaking process to include an initial regulatory flexibility analysis requiring 

each to contain more detailed information about a proposed rule, including why agency action is 

being considered; the objectives and legal basis for the proposed rule; an estimate of the number 

and types of small entities to which the proposed rule will apply; the projected compliance 

requirements and the type of professional skills needed for such reporting; a list of existing 

federal rules that may duplicate, overlap or conflict with the proposed rule; the estimated 

cumulative impact (by agency) of the proposed rule; the disproportionate impact that a proposed 

rule may have on small businesses; and whether the proposed rule may impact access to credit. 

• Including within the final regulatory flexibility analysis a detailed description of any 

disproportionate economic impact on small entities or a specific class of small entities, the 

agency's response to comments for certification, a detailed statement including an economic 

5 
117 

assessment (a quantifiable or numerical description of the effects of the proposed or final rule 

and alternatives to the proposed or final rule) to support certification (or why quantification or 

numerical description is not practical or reliable), and readily available access to the analysis by 

the public. 

• Increasing the power and oversight authority for the Chief Counsel for Advocacy of the SBA 

to more effectively monitor the regulatory process for small businesses, obtain data related to 

impact and costs (including the effect of a proposed rule on startups), and engage with all 

relevant parties to ensure requirements are being fulfilled. 

• A periodic review of the rules, which includes the direct engagement of the small business 

community and agency accountability regarding the process and outcome of the review. 

• The waiver of fines for first-time violations of paperwork requirements by small businesses. 

• Soliciting input from affected small businesses or associations of small entities in preparing 

compliance guides. 

• Bringing IRS regulations under the RF A and SBREFA requirements. 

Sustaining Robust Growth 

Along with strong small business optimism, the economy has improved markedly under policies 

that have unleashed investment and more risk-taking activity. Sound regulatory policy is a vital 

to encouraging this productive activity and sustainable growth. Recent economic indicators 

continuet,o be very positive: 

• The July personal income report from the U.S. Bureau of Economic Analysis (BEA) released 

on August 30, continues a streak in growth which reinforces the growing strength of the U.S. 

economy. Since July 2016, real per capita disposable income experienced growth in 23 ofthe 

last 25 months with now !3 straight months of growth, rising from $42,726 (in 2012 dollars) in 

June 2017 to $43,769 in July 20 I 8. 

• The BEA released its second estimate of second quarter GnP on August 29'h. The topline 

revision of real GOP growth was positive, with the second quarter growth rate estimate moving 

from 4.1 percent to 4.2 percent. In a review of this data, SBE Council chief economist 

Raymond Keating observed that strong business investment (revised up from 7.3 percent to 8.5 

percent in the second quarter) was a key component of this upward revision. Strong investment 

means business owners and entrepreneurs are confident, which helps to strengthen productivity 

and wages. 

• The Federal Deposit Insurance Corporation's (FDIC's) latest guarterlv banking 

profile (released on August 23) shows that Community Banks are perfonning well, which is 

good news for small business lending. In fact, according to the FDIC report, small business 

lending has been on the rise with small commercial and industrial, and nonfann nonresidential 

(properties) loan balances at $632.5 billion in the second quarter. That was up from the end of 

2017 ($623 billion), and compared to $618.7 billion a year earlier. 

6 
118 

• The Bureau of Labor Statistics (BLS) September 7 second quarter productivity 

report (revised only slightly from the preliminary estimate in mid-August) shows rising 

productivity. Specifically, productivity rose by an annualized 2.9 percent rate, the best 

productivity performance since the first quarter of2015, and a big step up from 0.3 percent in the 

first quarter and -0.3 percent in the fourth quarter 2017. 

• As noted by Kevin Hassett, Chairman ofthe Council of Economic Advisors, in a September 10 

report on the economy, new businesses as measured bv applications for an employer 

identification number (EIN) have steadily increased on a quarterly basis with a surge in new 

activity, particularly in 2018. For example, EIN applications increased from 704,961 in 2015 Q I, 

to 725,012 in 2016 Ql, to 771,445 in 2017 Ql, to 852,991 in 2018 Ql. 

This fertile environment consisting of strong investment, solid consumer confidence, increased 

startup activity, improved revenues and sales for small businesses, an uptick in wages and 

stronger lending can be sustained with policies that generate certainty for businesses. 

Entrepreneurs and small business owners have a very favorable outlook moving forward, and 

SBE Council appreciates the work of this subcommittee and its leaders who have helped to 

create the environment tor entrepreneurial success and wish to do more on the regulatory retorm 

front to ensure economic growth and opportunity are sustained over the long term. 

Respectfully submitted by, 

Karen Kerrigan 

200 Lawyers I~oad :\W • #1506 • Vienna, VA 22183 • 703-242-5840 

www.sbecoundi.org • (ii)SHECoundl 

Protecting Small Business, Promoting Entrepreneurship 

7 
119 

PREPARED STATEMENT OF MARIA GHAZAL 

SENIOR VICE PRESIDENT AND COUNSEL 

BUSINESS ROUNDTABLE 

"EXAMINATION OF THE EFFECTS OF REGULATORY POLICY ON THE ECONOMY AND 

BUSINESS GROWTH" 

Before the 

U.S. SENATE COMMITTEE ON HOMELAND SECURITY AND GOVERNMENTAL AFFAIRS 

SUBCOMMITTEE ON REGULATORY AFFAIRS AND FEDERAL MANAGEMENT 

September 27, 2018 
120 

Good morning, Chairman Lankford, Ranking Member Heitkamp and Members of the 

Subcommittee. I am Maria Ghazal, Senior Vice President and Counsel of Business Roundtable. 

Thank you for inviting me to this important hearing to examine the effects of regulatory policy 

on the economy, business investment, economic growth and job creation. On this 10th 

anniversary of the beginning of the financial crisis, it is timely to look at policies that drive 

economic growth. I appreciate the opportunity to share with you the perspective of Business 

Roundtable. 

Business Roundtable is an association of Chief Executive Officers (CEOs) of America's leading 

companies working to promote a thriving U.S. economy and expanded opportunity for all 

Americans through sound public policy. Business Roundtable is the only national organization 

that exclusively represents chief executive officers. These CEO members lead companies with 

more than 14 million employees and more than $7 trillion in annual revenues. As major 

employers in every state, Business Roundtable CEOs are responsible for creating quality jobs 

with good wages. 

Business Roundtable supports a smarter approach to regulation- one that meets regulatory 

goals and promotes innovation, economic growth and job creation. We call this approach 

"smart regulation," and Business Roundtable formed a Committee focused exclusively on the 

topic. I oversee policy development and advocacy for this Committee. 

My testimony explains how smart regulation can be achieved by reforming three areas: the 

process by which the federal government issues regulations and guidance; the degree of 

overlap between agency regulatory jurisdictions; and the system for permitting major 

infrastructure projects. The Trump Administration is taking major steps to improve each of 

these three areas. I will describe how the Administration's actions are already producing 

improvements. I will then highlight ways in which Congress- starting with this Subcommittee 

-can codify and extend those actions. 

How to Promote Smart Regulation 

Federal regulations can ensure that all Americans can enjoy a clean environment; safe 

workplaces; fair treatment; quality health care; access to healthy food and water; and 

protection from unscrupulous, unfair or predatory business practices. But, too often federal 

regulatory and permitting processes unnecessarily discourage innovation and investment. 

Improvements are needed in three key areas: 

I. Improve the Regulatory Process 

The first·needed improvement is systematic reform of the process by which the federal 

government produces regulations and guidance documents. At present, the current system 

obstructs innovation, investment and compliance. Agencies often impose rigid one-size-fits-all 

requirements that cut off promising opportunities, or impose overly prescriptive rules that 

prevent better solutions. The current regulatory process also creates uncertainty. If companies 

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do not know what regulators will do, they understandably are reluctant to undertake major 

investments that often take years, if not decades, to execute and bear fruit. Finally, individual 

rules can also impose costs of hundreds of millions or even billions- of dollars on 

consumers, companies and other organizations each year. And while any individual regulation 

might be cost-effective, the cumulative impact of all regulations can be overwhelming. 

While a wide variety of process reforms would improve the manner in which federal agencies 

produce regulations and guidance, the most essential elements are: 

• Objective analysis to ensure that regulations are based on the best available 

information, to carefully and transparently consider the costs and benefits of proposed 

rules, and to make sure that the benefits justify the costs; 

• Early engagement with the affected stakeholders prior to development of a proposed 

rule, to better understand the issues involved and to gather recommendations for 

achieving regulatory goals most cost-effectively; and 

• Mechanisms for agencies to receive information and feedback from the regulated 

community about how well existing regulations are accomplishing their regulatory 

objectives. 

Together these actions- in effect, an improved quality control system for federal regulation -

will best ensure that regulations are well-constructed, narrowly tailored, supported by sound 

science and analysis, and fit for their intended purpose. 

II. Reduce Regulatory Redundancy and Overlap 

The second needed improvement is to reduce and rationalize the widespread jurisdictional 

overlaps among U.S. regulatory agencies. Too often, firms find themselves subject to multiple 

regulatory requirements from multiple agencies on a single issue, resulting in inefficiencies and 

higher compliance costs. In some cases, agencies may promulgate rules that are duplicative, 

inconsistent or conflicting, which leads to costs that reduce hiring and business investment. 

Reform will require Congress to allocate agency jurisdictions more clearly. Congress could also 

encourage a variety of helpful practices among agencies, such as negotiating memoranda of 

understanding. Business Roundtable will release a white paper later this year describing the 

problem of regulatory overlap, the negative effect this overlap has on U.S. businesses, and 

constructive solutions for both regulatory agencies and Congress to consider. 

Ill. Streamline and Expedite Permitting 

The third needed improvement is to streamline and expedite environmental reviews and other 

approval processes for major infrastructure projects. Business Roundtable CEOs strongly 

advocate changes that will "simplify, streamline and accelerate America's permitting process 

with the' goal of encouraging large-scale capital investments in the U.S. economy while 

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maintaining the nation's commitments to health, safety and soundness." 1 Gaining approval to 

build a new bridge or factory typically involves review by multiple federal agencies with 

overlapping jurisdictions and no real deadlines. Often, no single federal entity is responsible for 

managing the process or has the power to compel other agencies to act promptly. Even after a 

project is granted permits, lawsuits can still hold things up for years- or, worse, halt a halfcompleted construction project. 

Congress took a huge step forward when it passed title XLI of the Fixing America's Surface 

Transportation Act, generally referred to as FAST-41 2 - a bipartisan bill that originated in this 

committee. 3 But there is room for improvement, including extending FAST-41 reforms to a 

wider universe of projects and setting a presumptive deadline for reviews. 

The Trump Administration's Actions Thus Far 

Reforming the Regulatory Process 

The President made reducing regulatory burden one of his first priorities, and the 

Administration has made progress in that regard. One of the President's first Executive Orders 

(E.O. 13771) was to establish a 1-in, 2-out goal for every significant regulation proposed. By the 

Regulatory Actions Reviewed by OIRA 

Bush Obama Trump 

end of FY 2017, the Administration had eliminated 

67 regulations and adopted only three significant 

new regulations. As of mid-December 2017, the 

Administration withdrew or delayed 1,579 

rulemakings listed in the previous Administration's 

regulatory agenda. For FY 2018, the Administration 

announced plans to eliminate an additional 434 

regulations while issuing 131. According to the 

Office of Management and Budget (OMB), $8.1 

billion in regulatory savings were achieved in FY 

2017 and nearly $10 billion in savings are being 

forecast for FY 2018. The Administration did not 

provide any updated data when it released its 

Spring 2018 Regulatory Agenda, but a recent study 

found that, in the first 18 months of the Trump 

Administration, the number of significant proposed 

or final rules reviewed by the OMB fell by 70 

percent from the same period under the previous 

1 See Business Roundtable, Permitting Jobs and Business Investment: Streamlining the Federal Permitting Process {April 2012) at 

3. This report may be accessed at: 

https://www.businessroundtable.org/sites/ default/files/2012 _ 04_23 _ BRT _Permitting_Jobs_and_Business_lnvestment.pdf. 2 42 U.S.C. § 4370m et. seq. (2015). 

3 Similar reforms are embodied in the Water Resources Development Act (WRDA) (included as part of the Water Infrastructure 

Improvement for the Nation Act, Pub. L. No. 114-322, § 1156 et seq.), for water resources projects, and the balance of the FAST 

Act (Pub. L. No. 114-94), for surface transportation projects. 

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Administration, and fell more than 50 percent from the same period under the George W. Bush 

Administration (see graph). 4 

The President also issued an Executive Order (E.O. 13777) institutionalizing his regulatory 

reform agenda by requiring each agency to designate a Regulatory Reform Officer responsible 

for reviewing current regulations and making recommendations on how to modify them. 

Agencies are also required to solicit public comment on regulations in need of repeal or reform. 

Business Roundtable submitted comments on several regulations. 

The Administration also broke new ground when the Treasury Department and OMB issued a 

memorandum of agreement under which the OMS's Office of Information and Regulatory 

Affairs (OIRA) will review certain tax regulations. Further, the Environmental Protection Agency 

solicited early input on whether it should propose a rule to standardize its conduct of costbenefit analyses for significant rulemakings. 5 

Business Roundtable members are encouraged by these actions and believe the Administration 

is serious about reducing cumulative regulatory burdens. Every year since 2002, Business 

Roundtable has surveyed its member CEOs about their expectations for their companies' sales, 

capital spending and employment over the following six months. In the fourth quarter of the 

year, CEOs are also asked to rank the most significant cost pressures their companies face. 

Beginni(lg in 2012, CEOs cited regulatory costs as the top cost pressure for five consecutive 

years. last year, however, regulatory costs slipped to the second-largest cost pressure, 

overtaken by labor costs.6 We suspect the Administration's emphasis on reducing the 

regulatory burden facing U.S. businesses is a significant driver of this result. 

More generally, Executive Orders 13771 and 13777 have effectively limited new significant 

rulemaking to those that are really necessary (e.g., required by statute or national security 

considerations). This dramatic shift in regulatory philosophy has reduced regulatory costs and 

allowed our members to make decisions in a more certain, predictable environment. The result 

is heightened optimism in the business community as well as the overall economy, as is evident 

in a variety of business confidence indices (including the Business Roundtable CEO Economic 

Outlook, which reached an all-time high earlier this year). 7 The Dow Jones Industrial Average 

and the S&P 500 continue to reach record highs, unemployment has fallen in 2018 to its lowest 

level since late 2000, and initial jobless claims are at their lowest point since the late 1960s. 

Addressing the Problem of Regulatory Overlap 

In March 2017, the President instructed the OMB to develop a plan to improve the efficiency, 

4 Bridget C. E. Dooling, "Trump Administration Picks up the Regulatory Pace in its Second Year- Overall Pace Still Dramatically 

Slower than Prior Administrations," GW Regulatory Studies Center Regulatory Insight (Aug. 1, 2018), available at 

https://regulatorystudies.columbian.gwu.edu/sites/g/files/zaxdzs1866/f/downloads/Dooling_ Trump%27sFirst18Months.pdf. 

s 83 Fed. Reg. 27524 (June 13, 2018). Business Roundtable filed comments in this docket. See 

https://www.regulations.gov /document ?D=EPA-HQ-OA-2018-0107 -1186. 

5 See https:f/www.businessroundtable.org/resources/ceo-survey/2017 -Q4. 

7 See https://www.businessroundtable.org/resources/ ceo-survey /2018-Q1. 

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effectiveness and accountability of federal agencies by, among other things, eliminating or 

reorganizing unnecessary or redundant federal agencies. The result was a report, released this 

past June, "Delivering Government Solutions in the 21'1 Century.'' 8 Noting that "[m]any Federal 

organizations are effectively fulfilling their missions and serving citizens but doing so in ways 

that duplicate other Federal activities," 9 the plan proposes 32 structural reforms of the federal 

government. These include, for example, consolidating the food safety responsibilities of the 

Food & Drug Administration and the U.S. Department of Agriculture (USDA) within the USDA. 

As the report describes, while "some of the proposals are ready for agency implementation, 

others establish a vision for the Executive Branch that will require further exploration and 

partnership with the Congress.''10 

Individual agencies are also taking steps to rationalize their operations. A good example is the 

recent memorandum of understanding executed by the Federal Energy Regulatory Commission 

(FERC) and the Department of Transportation's Pipeline and Hazardous Materials Safety 

Administration to rationalize the safety review of liquefied natural gas pipelines during FERC 

permitting processes. 11 

Individual Business Roundtable members have expressed enthusiasm about both the food 

safety and pipeline safety reforms noted above, and our membership is optimistic that the 

Administration may be able to make significantly more progress on reducing regulatory overlap 

than its predecessors have. 

Improving Infrastructure Permitting 

The Administration is also accelerating and rationalizing the process of permitting infrastructure 

projects. Its most significant action has been issuance of Executive Order No. 13807, 

"Establishing Discipline and Accountability in the Environmental Review and Permitting Process 

for Infrastructure Projects." 12 This E.O. establishes a two-year goal for completing all federal 

environmental reviews and authorization decisions for major infrastructure projects. It also 

mandates that federal agencies involved in a project reach "One Federal Decision." This means 

that a lead agency will coordinate with all cooperating or participating agencies to reach one 

Record of Decision (ROD) under the National Environmental Policy Act (NEPA), and that all 

related federal approvals will be made within 90 days of issuance of the ROD. Finally, the E.O. 

extends elements of FAST-41 (e.g., permitting timetables and dispute resolution) to all projects 

subject to NEPA and involving more than one agency. 

To implement these mandates, the 12 agencies on the Federal Permitting Improvement 

Steering Council (FPISC) jointly issued a memorandum of understanding that took effect in 

'Available at https://www.performance.gov/GovReform/Reform-and-Reorg-Pian-Final.pdf. 

'ld. at 12. 10 !d. at4. 11 Available at https:/ /www. ferc.gov /legal/mou/2018/FERC·PHMSA·MOU.pdf?csrt=6200578797 45426299. 12 82 Fed. Reg. 40463 (August 24, 2017). 

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April2018. 13 In addition, the Council on Environmental Quality has gathered public input on 

whether to propose to revise its regulations implementing the procedural provisions of NEPA. 14 

Business Roundtable members strongly support all of these actions. 

Reforms Congress Could Act On 

While the Trump Administration takes important steps to improve the three areas discussed 

above, Congress could also act to codify those improvements and to take actions the President, 

alone, cannot. 

I. Regulatory Process Reforms 

The single most important action Congress could take to improve the federal regulatory process 

would be to enact the Regulatory Accountability Act (RAA). Business Roundtable strongly 

supports this bill. The Senate bill (S. 951) strikes the appropriate balance in reforming the 

process without unduly burdening agencies or their decision-making processes. Most 

importantly, the RAA would: 

• Promote earlier and greater public participation in the regulatory process; 

• Codify the requirements of E.O. 12866 regarding cost-benefit analysis for major rules, 

and require agencies to pick the most cost-effective alternative, unless the benefits of a 

less cost-effective alternative justify its choice or the authorizing statute specifies a 

different standard; 

• Extend this cost-benefit analysis requirement to independent agencies not now subject 

to E.O. 12866; 

• Require that major rules include a framework for evaluating the ultimate effects of the 

rule- i.e., did it achieve what Congress intended; and 

• Specify standards for agencies when they issue guidance documents. 

II. Reducing Regulatory Overlaps 

As noted earlier, Congress needs to address the many instances of regulatory overlap arising 

from the overlap of various statutes. In this regard, this Subcommittee and its parent 

Committee have important oversight responsibilities such as identifying specific examples of 

regulatory overlap and engaging with agencies to reduce the problem. It would be crucial for 

this oversight to include independent agencies, as they are a significant source of the problem. 

Options available to agencies to ameliorate overlap problems include: 

" See https://www. whitehouse.gov/wp-content/uploads/2018/04/MOU-One-Federai-Dedsion-m-18-13-Part-2-l.pdf. 14 83 Fed. Reg. 28591 (June 20, 2018). Business Roundtable filed comments in this docket. See 

https://www.regulations.gov /document ?D=CEQ-2018-0001-11957. 

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Æ 

Negotiating memoranda of understanding between regulatory agencies or interagency 

working groups to achieve better coordination. In particular, agencies could seek 

opportunities to use these cooperative mechanisms to: 

o Clarify their respective roles and responsibilities; 

o Articulate individual and shared regulatory goals; 

o Harmonize guidance provided to jointly-covered entities; 

o Standardize adjudication processes; 

o Coordinate regulatory activities, including data requests and examinations; and 

o Establish data-sharing agreements and uniform data collection formats. 

• Designating a lead regulator where multiple agencies have responsibility for oversight, 

with other regulators exercising both regulatory and enforcement deference to the lead 

regulator. 

• Conducting joint rulemakings in instances where new rules stretch across the 

jurisdiction of multiple agencies. Joint rulemakings ensure government-wide consistency 

and eliminate regulatory uncertainty. 

• Improving communication with those being regulated, including increasing the clarity 

and availability of guidance in regulatory areas prone to jurisdictional overlap. Agencies 

could also establish platforms to seek out input regarding the consequences of 

regulatory overlap, as well as potential solutions. 

111. Accelerating Permitting 

The most important action Congress could take in this area would be to enact a FAST-41 

Amendments Act that would: 

Repeal the seven-year sunset contained in FAST-41; 

Codify the two-year goal for environmental reviews established by E.O. 13807; 

• Allow projects under FAST-41 to be prioritized; 

• Require that some portion of the FAST-41 fees not be due until the final decision is made, 

and for the fee to be reduced if and to the extent the final decision is delayed; and 

• Repeal Section 11S03(b) of the FAST Act, which excludes from FAST-41 any project 

under a program administered by the Department of Transportation or any of its modal 

administrations or by any other agency under US Code Title 49. 

Once again, I appreciate the opportunity to testify before the Subcommittee today. This 

Subcommittee has led the way in focusing attention on the federal rule making process and has 

proposed a number of common-sense, bipartisan ideas for reforming this critical process. 

Thank you for the hard work that you do. I look forward to your questions.