The latest Economic Report of the President highlights the importance of studying cumulative regulatory costs.
The Council of Economic Advisers (CEA) published its annual Economic Report of the President in March of this year. The document runs over 700 pages and spans numerous economic issues, but it devotes about 62 pages to discussing the Trump Administration’s focus on deregulation and the economic reasoning behind those efforts.
Among other regulatory issues discussed in the report, the report rightly discusses the importance of paying closer attention to the cumulative costs of regulation, including their interactive and unintended effects. This issue in regulatory policy is a critical area of study and source of real-world impact.
Although the number of new regulations issued each year fluctuates, the total amount of regulation in the U.S. economy has steadily risen, according to multiple measures. CEA uses the annual Reports to Congress by the Office of Information and Regulatory Affairs (OIRA) to calculate the “simple accumulation—ignoring interactions—of the costs of federal regulatory actions.”
Even though these data depict the general trend in regulation and simple measures of its economic impact, comprehensive methods for evaluating the cumulative economic effects of regulation are currently lacking. As a result, CEA’s report presents “a framework to analyze the cumulative economic impact of regulatory actions on the U.S. economy,” which incorporates interactions among regulations.
The report introduces an economic framework to help illuminate the range of effects of regulation. This article breaks down the framework into the following points:
(1) Regulations impose economic effects, such as by affecting “productivity, wages, and profits;”
(2) In response to compliance costs and changed incentives, capital and labor move and reallocate within a regulated industry and across the broader economy;
(3) These movements in capital and labor also affect productivity, wages, and profits in other sectors and the whole economy;
(4) The economic impacts of regulation, combined with the effects of tax policy and other factors that distort market conditions, can accumulate in multiplicative or exponential ways within an industrial sector or throughout the economy; and
(5) These interactive effects occur through “convex deadweight costs,” related to economic inefficiency, which exceed the regulatory costs associated with a single rule (or set of rules).
The concept of convex deadweight costs implies that “a new regulatory action that increases regulatory costs by 10 percent increases the cumulative regulatory cost burden by more than 10 percent.” In other words, the cumulative effects of regulation are nonlinear.
For decades, agencies have undertaken to assess the costs and benefits of new regulatory actions, but the drafters of CEA’s report argue that the current process is too narrowly focused on individual regulations and leaves out certain economic effects because “the regulatory whole is greater than the sum of its parts.”
CEA is not alone in its analysis of cumulative regulatory costs. Two papers from the Mercatus Center illustrate how “regulatory overload”—or the consequences of regulatory accumulation on incentives and behaviors—can negatively affect compliance and safety. Relatedly, a 2013 paper by Michael Mandel and Diana G. Carew offers three explanations for how regulatory accumulation could create unique costs—when the buildup of rules “blocks” growth and innovation, where conflicting, overlapping, and redundant rules create unanticipated results, and where management redirects company time and resources from innovation to compliance activities.
CEA’s recent report highlights two key sources of underestimated costs. First, benefit-cost analyses are conducted for only a subset of all rules—those regulatory actions that are considered “significant.”
Second, even for significant regulatory actions, the full opportunity cost for each rule is not captured because the impact of interactions and convex deadweight costs rarely make it into regulatory impact analyses.
The report’s economic framework suggests looking both at the cumulative burden within an industry—“how businesses experience cumulative burdens” and the compounding effect of multiple regulatory actions—as well as the costs along the supply chain—how “the accumulation of taxes and regulatory actions” affect the aggregate supply and demand curves for capital and labor.
CEA also discusses a 2016 Congressional Research Service report that delineates the two main methods of estimating regulatory costs—“bottom-up” and “top-down” approaches. The bottom-up approach aggregates the monetized estimates of costs and benefits for individual rules to create a government-wide sum. The top-down approach estimates regulatory costs using econometric modeling and proxy measures of regulation.
OIRA’s annual Reports to Congress—one example of the bottom-up approach—aggregate the estimated costs and benefits of major federal rules over the previous ten years. Although these reports do offer a benchmark for the trend of aggregate regulatory costs and benefits, OIRA acknowledges that they may not provide an accurate picture of the actual size of regulatory impacts. For instance, each report only considers a subset of all rules, not all costs and benefits can be quantified, and those that are quantified are not necessarily comparable across rules because agencies use different methodologies, assumptions, and even definitions of costs.
But CEA addresses another key analytical limitation of building bottom-up cost estimates, namely “that the cumulative burden of multiple regulatory actions exceeds the simple sum of costs when each action is considered one by one.” In other words, an approach that leaves out interactive effects may not accurately capture the full impact of regulation.
In contrast, “top-down” approaches essentially derive regulatory costs and their effects through the construction of proxy measures and estimation through statistical analysis. As a case study, the Congressional Research Service report summarizes a 2014 report for the National Association of Manufacturers that estimates total regulatory costs by using a regulation index as a proxy measure in the regression model. But such top-down studies have their own limitations, particularly “conceptual and methodological hurdles,” notes the Congressional Research Service.
Nevertheless, such limitations should not preclude new and improved methods of estimating the cost of regulation. Considering new ways to model the effects of regulation on economic outcomes is an important area of research with substantial policy implications.
One example is a 2016 working paper by Bentley Coffey, Patrick McLaughlin, and Pietro Peretto, which estimates the effects of federal regulation on value added to GDP with a panel dataset of 22 industries from 1977 to 2012. A key contribution of the paper by Coffey and his co-authors is the “careful combination” of an endogenous growth model with data measuring regulation across sectors and over time, which allows the authors to estimate the effects of regulation on firms’ investment decisions and economic growth. This approach permits comparison between the observed level of regulation and a counterfactual—a hypothetical version of the world depicting a different level of regulation.
Compared against the observed results, the paper simulates that “the economy would have been about 25 percent larger than it was in 2012” in the counterfactual state of the world where regulations were pegged at 1980 levels. A key insight that emerges from the research is that regulatory accumulation affects the growth rate of an economy, rather than simply imposing “static costs associated with individual interventions.”
Despite the important focus on cumulative costs, reducing costs is not the only objective of regulatory actions and reforms. First, regulations often address systemic social problems, rather than economic efficiency, and are desirable for reasons beyond economic growth. For instance, CEA categorizes regulations that promote environmental quality as an example where the benefits of public goods often justify associated productivity tradeoffs.
Second, the presence of cumulative costs is not necessarily a reason to avoid regulating. Instead, the regulatory process should encourage agencies to consider how a new regulatory action might have larger implications than the immediate effects of the rule.
CEA’s report serves an important purpose by directing attention to the issue of cumulative regulatory costs, which have gone largely unaddressed in regulatory analysis and decision-making. Because of its considerable policy implications, CEA’s framework should be carefully evaluated—and even rigorously challenged. But contemplating how cumulative costs should be integrated into regulatory analysis is critical to spurring academic and policy debates on the path forward.