Donate Today

Methodological Note: Estimating the Effects of Federal Regulation on the States

The following note briefly describes the methodology used to estimate the negative impacts of higher federal regulations on poverty rates, employment levels, and consumer prices, as reported in the Snapshots of State Regulations, 2024 Edition.

Additional People Living in Poverty

Chambers, McLaughlin, and Stanley (2019) find that states with a higher incidence of binding federal regulations (as measured by the FRASE index1) tend to exhibit higher poverty rates.  Specifically, a 10 percent increase in the effective federal regulatory burden upon a state is associated with about a 2.5 percent increase in the poverty rate. Multiplying the poverty elasticity measure (0.25 percent increase in poverty per 1.00 percent increase in regulation) by the increase in the FRASE index in a given state between 1997 and 2017 (the longest period for which this data is available) yields the percentage increase in the poverty rate owing to regulation in that state (denoted poverty growth). 

Next, we deflate the actual number of people living below the poverty line in a given state (US Census Bureau 2023a) by the estimated growth in poverty due to federal regulations (i.e., (Actual Poverty in 2022) / (1 + poverty growth)). This yields a counterfactual estimate of the number of people living in poverty in the absence of increased federal regulations. Subtracting this counterfactual value from the actual poverty level yields an estimate of the additional people living in poverty due to federal regulation growth between 1997 and 2017. 

To illustrate this calculation, consider Alabama. Between 1997 and 2017, binding federal regulations (as measured by the FRASE index) increased by 130 percent. Since each 1 percent increase in regulations is associated with a 0.25 percent increase in the poverty rate, a 130 percent increase in binding federal regulations is associated with a 32.5 percent increase in the poverty rate (130% x 0.25 = 32.5%). According to the Census Bureau’s latest estimates for Alabama (at the time of publication), 798,469 people lived below the poverty line in 2022. This figure is 32.5 percent larger than what it would have been in the absence of additional binding federal regulations. In other words, the level of poverty could have been as low as 602,618 people (798,469 / 1.325). The difference in these two levels of poverty is 195,851 additional people living in poverty.

Lost Jobs Annually

Chambers, McLaughlin, and Richards (2018) find that a 10 percent increase in the number of federal regulatory restrictions pertaining to a particular industry is associated a corresponding 0.55 percent reduction in small firm employment. (Following Small Business Administration classifications, Chambers, McLaughlin, and Richards define small firms as businesses with fewer than 500 employees.) Between 1999 and 2015, federal regulations (as measured by RegData2) increased on average by 3.78 percent per year. Therefore, multiplying the employment elasticity measure (0.0547 percent reduction in small business employment within an industry-wide 1 percent increase in regulation) by the average increase in national industry-level regulation as measured in RegData (3.78 percent) yields the annual percentage reduction in small business employment owing to regulation: 0.206766 percent. Multiplying this value by the number of small business employees in a given state yields the average number of small business jobs lost annually in that state. To illustrate this calculation, consider Arizona, which had 1,112,573 small business jobs in 2021 according to the US Census Bureau (2023b).[1] The average annual increase in federal regulations is responsible for 2,300 lost jobs annually (1,112,573 x 0.00206766) in the Grand Canyon State.

Higher Prices

Chambers, Collins, and Krause (2019) find that a 10 percent increase in federal regulations is associated with a 0.9 percent increase in consumer prices. Between 1999 and 2015, federal regulations (as measured by RegData) increased on average by 3.78 percent per year. Therefore, multiplying the price elasticity measure (0.09 percent increase in consumer prices per 1.00 percent increase in regulation) by the average increase in national industry-level regulation (3.78 percent) yields the annual percentage increase in consumer prices owing to regulation (0.3402 percent). Over the same period, the annual inflation rate in the US equaled 2.19 percent, and the overall price level grew by approximately 41.43 percent over that 16-year period of 1999 to 2015). Had regulations not grown over this period, the observed inflation rate should have been 1.85 percent (2.19 – 0.3402). Had prices grown at that lower rate between 1999 and 2015, the overall price level would have grown by 34.08 percent. The difference in gross price appreciation over this period equals 7.35 percent (41.43 - 34.08).

References

Chambers, Dustin Chambers, Courtney A. Collins, and Alan Krause. 2019. “How Do Federal Regulations Affect Consumer Prices? An Analysis of the Regressive Effects of Regulation.” Public Choice 180 
(1–2): 57–90.

Chambers, Dustin, Patrick A. McLaughlin, and Laura Stanley. 2019. “Regulation and Poverty: An Empirical Examination of the Relationship between the Incidence of Federal Regulation and the Occurrence of Poverty across the US States,” Public Choice 180 (1–2): 131–44.

Chambers, Dustin, Patrick A. McLaughlin, and Tyler Richards. 2018. “Regulation, Entrepreneurship, and Firm Size.” Mercatus Working Paper, Mercatus Center at George Mason University, Arlington, VA.

United States Census Bureau. 2023a.  “SAIPE State and County Estimates for 2022” (dataset). Washington, DC. https://www.census.gov/programs-surveys/saipe/data/datasets.html.

United States Census Bureau. 2023b. “2021 SUSB Annual Datasets by Establishment Industry.” Washington, DC. https://www.census.gov/data/datasets/2021/econ/susb/2021-susb.html.

Notes
  1. The FRASE index is an industry-weighted measure of federal regulation incidence at the state level. Conceptually, if a state’s economy is more dependent upon industries that are heavily regulated by the federal government (e.g., chemical manufacturing), that state will have a higher FRASE index. See Federal Regulations and State Enterprise (FRASE) (database), QuantGov, Mercatus Center at George Mason University, Arlington, VA, https://www.quantgov.org/50states.
  2. RegData is a Mercatus project that seeks to measure regulation by quantifying the number of regulatory restrictions in a given jurisdiction. Regulatory restrictions are a metric designed to act as a proxy for the number of prohibitions and obligations contained in regulatory text, as indicated by the number of occurrences of the words and phrases shall, must, may not, required, and prohibited in each state’s regulations. See State RegData (database), QuantGov, Mercatus Center at George Mason University, Arlington, VA, https://www.quantgov.org/state-regdata.