Regulatory Benefits: Examining Agency Justification For New Regulations

This study attempts to shed some light on whether the benefits claimed by the federal agencies are likely to be achieved. In contrast to other validation studies, the study focuses on the agencies’ benefit claims rather than the actually measured benefits. Since agencies justify their regulatory decisions based on expected benefits, examining the quality of these claims is important.

This study attempts to shed some light on whether the benefits claimed by the federal agencies are likely to be achieved. In contrast to other validation studies, the study focuses on the agencies’ benefit claims rather than the actually measured benefits. Since agencies justify their regulatory decisions based on expected benefits, examining the quality of these claims is important. To do that, the study focuses on two aspects of the agencies’ regulatory impact analysis: (1) whether the analysis demonstrates the existence of a systemic failure, and (2) whether the analysis provides a program theory that explains how the regulation would lead to beneficial outcomes. The study uses the Mercatus Center’s Regulatory Report Card to construct its dataset.

Many debates over regulation focus mainly on costs. Critics argue that, among other things, the weight of regulations depresses economic activity,[1] reduces productivity,[2] and discourages new businesses formation.[3] Additionally, regulations confer special privileges on incumbents4 and disproportionately impact smaller businesses.[5] All this results in diminished prosperity and foregone opportunities for the public. Numerous attempts to quantify the regulatory burden resulted in estimates ranging from hundreds of billions6 to well over a trillion dollars.[7]

In contrast, regulation advocates claim that many regulatory burden estimates exaggerate the costs.[8] More importantly, they point out that regulation critics focus exclusively on the costs and overlook the benefits of regulation.[9] These benefits can be substantial. For example, the Environmental Protection Agency (EPA) estimated that Clean Air Act regulations generated $22 trillion in net benefits during the period from 1970 to 1990.[10] The Office of Management and Budget (OMB) summed up agencies’ benefit estimates and found that aggregate benefits of major regulations issued in 2001–2011 ranged between $141 billion and $700 billion,[11] while aggregate costs within the same period ranged between $43 billion and $67 billion.[12] While conceding the critics’ point that regulations may be costly, advocates claim that regulations’ benefits justify their costs.

The OMB report, however, has major shortcomings. It only includes regulations with monetized cost and benefit estimates. Since only a fraction of regulations monetize benefits, the OMB report leaves out the majority of significant regulations. In addition, the estimate’s validity is uncertain. The OMB report acknowledges that it depends on the federal agencies for its overall estimate, yet the analysis quality varies widely between agencies.[13] The few studies that have examined the accuracy of agencies’ cost and benefit estimates using retrospective analysis yielded mixed evidence.[14] These studies suggested that agencies tended to overestimate both benefits and costs. However, they disagreed on whether agencies were more likely to overestimate benefits than costs.

In this paper, I take a different approach. Using a dataset constructed from the Mercatus Center’s Regulatory Report Card, I examine the likelihood that agencies realize the benefits they claim for regulations. To do that, I ask two questions:

  1. Does a regulation address a systemic problem such as market or government failure? 
  2. Does a regulation explain how it would solve the problem? 

The logic behind this exercise is straightforward. In their analysis, federal agencies have to clearly identify and demonstrate the existence of the problem they are trying to solve through regulation. Only significant problems that are unlikely to be solved without a government action warrant federal regulation. When agencies fail to demonstrate that the problem exists and is systemic, they are less likely to achieve the beneficial outcomes that they seek through regulation. Similarly, if agencies fail to explain how their regulation will fix the problem, the regulation may not deliver the intended results.

The goal of the paper is twofold. First, I attempt to shed some light on the validity of regulatory benefits claimed by the federal agencies. Second, using case studies, I point out the shortcomings in agencies’ regulatory analysis practices when it comes to estimating benefits. In contrast to traditional validation studies, I do not check the accuracy of the agencies’ estimates. Instead, I examine the logic of the regulatory analysis to determine whether the regulation will likely deliver the promised benefits. The advantage of this approach is that it is not limited to regulations with monetized benefits. Rather, it exposes the overall trends in the federal agencies’ regulatory analysis practices.

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