Many regulations fail to demonstrate a need for agency action.
Many debates over regulation focus only on the costs of new rules. Critics argue that the weight of regulatory costs depresses economic activity, reduces productivity, and discourages formation of new businesses. Estimates seeking to quantify the total federal regulatory burden range from hundreds of billions to well over a trillion dollars. Regulation advocates, in contrast, claim that many of those estimates exaggerate the costs of regulation. More importantly, they point out that regulation critics focus exclusively on the costs and overlook the benefits of regulation.
Costs are only half of the question, of course. I recently examined the benefit side of the equation. Using a dataset constructed from the Mercatus Center’s Regulatory Report Card, I examined the likelihood that regulations would realize the benefits that agencies claimed that new rules would provide. I focused on two aspects of the regulatory analysis: (1) whether the agencies’ analysis demonstrated the need for regulation, and (2) whether the analysis demonstrated that the regulatory action would address the problem.
This exercise had a straightforward logic. When agencies fail to demonstrate that the problem they are trying to solve 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. I did not check the accuracy of the agencies’ estimates; instead, I examined the logic of the regulatory analysis to determine whether the regulation would likely deliver the promised benefits.
In the study, I constructed a dataset made up of the Report Card scores for 94 regulatory impact analyses (RIA) for economically significant regulations issued between 2008 and 2011. Examining the dataset, I found that almost a third of RIAs failed either to demonstrate the need for regulation or to explain how the regulation would lead to the promised beneficial outcomes.
In 23 RIAs, agencies failed to demonstrate the need for regulation. Some RIAs failed to prove that the problem was widespread and systemic and therefore deserved the federal government’s attention. This failure often went hand in hand with agencies’ inability to quantify the regulation’s benefits. The agencies often provided a qualitative description of benefits instead. The practice of relying on qualitative benefits may be justified given that some social and environmental benefits are difficult to express in monetary terms. It becomes questionable, however, when agencies simply rely on their own supposition that the problem they address is widespread and substantial enough to justify significant costs. If the underlying problem is relatively minor or rare, the regulation’s actual benefits will probably be correspondingly small. Thus, when agencies failed to demonstrate that problems they addressed were systemic, they were less likely to realize the benefits that would justify the regulation’s costs.
In other cases, RIAs failed to account for the fact that the problem might be resolved through other means in the absence of regulation. In these cases, existing trends indicated that private actors would at least partially address the problem without regulation. Regulatory benefits in these cases would be improvements above and beyond those achieved without agency actions. The RIAs for these regulations, which attributed the results of both private behavior and agency action to the regulation’s impact alone, most likely overestimated the rule’s benefits.
In contrast, agencies less frequently failed to explain how their regulations would produce the expected beneficial outcomes (only 7 cases in the dataset). In these RIAs, agencies provided little evidence that their proposed actions would lead to the expected benefits. The problems targeted by these regulations were often real and substantial, yet there was little evidence that the regulation, as proposed, would actually have an impact. If there was logic behind agencies’ actions in these cases, the RIAs failed to communicate it. Without any causality theory or empirical evidence, it is hard to judge whether these regulations would lead to the expected beneficial results. Yet it is very possible that agencies would miss the mark.
Finally, in a few cases, RIAs addressed a systemic problem in a way that probably would produce the promised benefits but failed to communicate this in the analysis. These RIAs were likely to achieve the benefits that they claimed, but the analysis lacked transparency. In these cases, it would be difficult for the public to evaluate and comment on agency analysis because crucial components were missing.
My study suggests that many economically significant regulations may not fully realize the beneficial outcomes they claim. In some cases, agencies exaggerate the underlying problem or wrongly attribute the results of private actions to the regulation’s impact. Alternatively, agencies sometimes fail to show that regulation will actually lead to the beneficial outcomes. To determine whether the benefits of regulations justify their costs, we need to examine both sides of the equation.