The idea of a moratorium on regulation may sound like a blunt policy instrument to address the perceived negative effects of regulation on the economy. However, new research from the American Action Forum (AAF) finds that state moratoria on regulation provide gains to employment, wages, and small business growth. An average state implementing a moratorium would gain more than 15,600 jobs and create 2,800 new small businesses. In addition, a moratorium could increase total wages by more than $129 million per quarter.

New administrations often implement “soft” regulatory moratoria during the transition between different governors or presidents. For example, at the start of his term in 2009, President Obama’s then-Chief of Staff Rahm Emanuel requested all agencies to refrain from publishing new regulations until the administration’s new appointees had an opportunity to review them. He also asked agencies to pull back any regulations that had been submitted for formal publication and consider extending the effective date of rules that had been published. The result of this soft moratorium was that the new administration didn’t approve a major regulation for almost two months and then proceeded to pass five significant regulations during the next twenty days.

Now, the attention on regulatory moratoria has turned to the states, with ten governments (Arizona, Florida, Indiana, Maine, North Carolina, New Jersey, New Mexico, Nevada, Tennessee, and Washington) imposing soft or hard bans on regulation during the past five years. Although more comprehensive retrospective review with sound cost-benefit analysis components might be a preferred policy option, many Governors from across the nation view limiting pricey new rules as a way to kick-start economic growth. Just as states promise tax moratoria for some new businesses, the idea of a grace period for new regulations has also gained popularity.

Methods

To analyze the impact of a regulatory moratorium on small business growth, employment, and pay, we estimate the change in employment, establishments, and total wages that occur when a state government enforces a regulatory moratorium. We employ state-level data from the Bureau of Labor Statistics’ Quarterly Census of Employment and Wages and use average annual levels in each state and year from 2003 to 2012.[1]

Using these data, we perform a series of fixed effects regressions that estimate the impact of regulatory moratoria on the logs of employment, establishments, and total wages in firms with fewer than five workers, those with 5 to 9, those with 10 to 19, and those with 20 to 49. Each regression contains both state and year effects. The use of state effects controls for characteristics that vary across industries, but not over time, and the use of year effects controls for factors that vary over time, but not by state. The year effects help account for macroeconomic forces during this period, such as loss in employment due to the Great Recession.

Moratorium Variable

We measure the impact of a regulatory moratorium using a binary variable. The variable equals 1 in each year that a state enforced a regulatory moratorium and 0 for each year that it did not. For instance, Arizona instituted a regulatory moratorium from 2009 to present. So from 2009 to 2012, the moratorium binary variable equals 1. In all years prior to that in the data set, 2003 to 2008, the moratorium variable equals 0.

Controlling for Education

In our model, we control for additional factors that may influence employment and pay. One important factor that contributes to labor market performance is education. A state with a highly educated population likely has a very skilled workforce and faster growing businesses, which results in low unemployment and rapid job creation. Likewise, a state with an uneducated population likely has a low skilled workforce, resulting in limited innovation, stagnant business growth, and little job creation. Thus it is important to hold workforce skill levels constant when measuring the impact of a regulatory moratorium. To account for education, we include a variable for the percent of working-age adults (25 years and older) who have a bachelor’s degree.[2]

Moratorium and Education Interaction Term

The model also controls for the possibility that the relationship between regulatory moratorium and small business performance depends on the population’s education level. For instance, the impact of instituting a regulatory moratorium on small business employment could be smaller when a larger number of people graduated from college and already have stable jobs and income. To address this issue, the regression model contains an interaction term, which is the product of the moratorium and the education variables.

Additional Controls

In addition to education, we control for other factors that may influence growth in small businesses, employment, and pay. We include a variable for the percentage of workers employed in the services industry, as this helps to control for state industrial mix.[3] We also control for the state’s top marginal tax rate[4] and population.[5]

Finally, any fixed effects model can face the problem of autocorrelation, in which a variable is correlated with itself over time and biases the results. Our model addresses this issue by using heteroskedasticity- and autocorrelation-consistent standard errors.

Results

Assuming average education levels, our results suggest that in any year between 2003 and 2012 enforcing a moratorium was associated with a 2.4 percent increase in the number of people working for businesses with fewer than 5 workers, a 1.9 percent increase in the number of people working for businesses with 5 to 9 employees, a 1.5 percent increase in people working in businesses with 10 to 19 workers, and a 1.2 percent increase in employment in businesses with 20 to 49 workers.

It appears that the boon in small business jobs is a result of growth in the number of small business establishments. Moratoria are significantly associated with a 1.9 percent increase in the number of establishments with 5 to 9 workers, a 1.3 percent increase in the number with 10 to 19, and a 1.1 percent increase in the number with 20 to 49.

Meanwhile, our results indicate that total quarterly earnings in a state (number of jobs multiplied by quarterly pay) greatly benefit from a moratorium as well. We find that enforcing a regulatory moratorium is associated with a 1.9 percent increase in total wages in businesses with 5 to 9 workers, a 1.6 percent increase in businesses with 10 to 19 workers, and a 0.8 percent increase in those with 20 to 49 workers. Interestingly, for businesses with fewer than five workers, our model yields positive, but statistically insignificant relationships between a moratorium and establishments and total wages.

Implications

The real life implications of regulatory moratoria are profound for small businesses with fewer than fifty employees.

We also find that regulatory moratoria result in growth in the number of establishments and total wages, the implications of which mirror the increases in jobs. Our results indicate that an average state would gain over 2,800 small and medium size businesses. In each category, the gains in small businesses range from 140 additional businesses that employ 20 to 49 workers to 1,852 additional businesses that employ less than 5 workers. Additionally, in states that enforce regulatory moratoria, residents would take home an additional $129,500,000 per quarter on average. The gains in take home pay range from over $24,000,000 in businesses with fewer than 5 workers to over $40,000,000 in businesses with 10 to 19 workers.

Conclusion

Although there are several regulatory reform options in every administration’s toolbox, evidence reveals that there are few ill effects from adopting a moratorium on new rules. With the chance to create 15,600 jobs in the average state and generate $129 million in higher wages, placing sensible limits on regulation could spur modest economic growth.