Eakinomics: Benefits, Costs, and Doing Arithmetic at the EPA

Policy analysts are fond of the benefit-cost framework for evaluating regulatory decisions. To the extent that benefits and costs can be quantified, the framework allows alternative regulations to be ranked in order of their (net) desirability and contributes important information to the decision over whether to impose a regulation or not. But how does one quantify the benefits and costs?

On January 5, the Environmental Protection Agency (EPA) addressed this issue by finalizing its rule on “Strengthening Transparency in Pivotal Science Underlying Significant Regulatory Actions and Influential Scientific Information,” aka the Transparency Rule. This meaty issue is fully dissected by AAF’s Dan Goldbeck in his most recent analysis. As he notes, “the proposal focuses primarily on ‘dose response data and models’ (essentially what effect a particular level of pollutant can have on a population) used in determining the ‘pivotal regulatory science’ (the scientific data EPA uses determine costs and benefits) behind a potential rulemaking.”

The basic goal of the rule was to make sure that scientific justification for regulatory actions was available to be replicated and validated. That makes sense. Opponents, however, were concerned that the original rule was subject to overreach that would exclude certain studies that had merit but could not feasibly meet this standard. To deal with these concerns, the EPA issued a “supplementary rule” regarding this situation, received over a million comments on both the original and supplementary rule, and used these as inputs to the final rule.

The final rule settles on a scope that includes “those studies that describe the quantitative relationship between the dose or exposure of a pollutant, contaminant, or substance and an effect,” or in Goldbeck’s words, “studies or data that directly apply to a specific, measurable issue.” As for those materials that might not fully meet the criteria, EPA is given a series of instructions on how to determine “the degree of consideration to afford pivotal science for which the dose response data are not available for independent validation.”

The Transparency Rule is an exercise in the delicate balancing of objectives in the regulatory process. It is not, as critics on both sides have asserted, either an attempt to exclude science from the regulatory process or a means to allow bureaucrats to insert their desired analysis without scrutiny.