The Regressive Effects of Federal Regulation and a Roadmap for Reform

Testimony before Senate Subcommittee on Regulatory Affairs and Federal Management

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 roadmap 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 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, 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.[1] 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 of federal 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.[3]

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.[4] Prior to RegData, anyone seeking to manually analyze a single year of the CFR would have to read a volume of pages that, when laid 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 of RegData (version 3.0) has identified just under 1.1 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 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,[8] 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 1947 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 well-intentioned government program.


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.[9] 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),[10] 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.[11]


Furthermore, businesses located in poorer areas tend to be smaller than those located in more affluent areas,[12] implying that any disparate negative effects of regulations are likely to be amplified in the most economically vulnerable communities. In a recent study,[13] 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.


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.”[16] 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 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]


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.

[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,” Competitive 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.

[4] QuantGov, “The History of RegData,” accessed September 20, 2018,

[5] QuantGov, “The QuantGov Regulatory Clock,” accessed September 20, 2018,

[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,

[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).

[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, “Criteria Used to Define a Small Business in Determining Thresholds for the Application of Federal Statutes” (Working Paper, RAND Corporation, Santa 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] Dustin 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).

[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).

[18] See Jones (2015).