Last summer, Environmental Protection Agency (EPA) began one of the more important, and less understood, rulemakings in recent years in “Increasing Consistency and Transparency in Considering Benefits and Cost in the Clean Air Act Rulemaking Process,” Docket ID No. EPA-HQ-OAR-2020-00044. The rulemaking has generated hundreds of comments, and has been controversial. A list of commenting parties and their affiliation can be found here. The rulemaking is expected to become final this year, possibly by mid-November. It will likely be appealed to the D.C. Circuit, or revisited depending on the results of the presidential election.
This proposal is particularly important because it will codify use of best scientific and economic analyses practices, which are used to balance benefits in public health and the economic consequences of Agency rules. Cost Benefit Analysis (CBA) has been used for years in many EPA rulemakings in differing ways, from predicting the cost of a regulation to more elaborate exercises in balancing theoretical risks against those costs. CBA is entirely dependent on algorithms and the quality data inputs and the data used to drive hundreds of thousands of computations. Once the dollar impact and risk calculations are generated, the ultimate questions about how much risk and how much cost are determined by the policy makers. Judicial review of CBA is tricky, to say the least, given the Chevron deference standard, the aversion of most judges to math, and statistics. A clear and logical explanation of CBA techniques, assumptions, and disclosure of data are critical elements in conducting a “searching inquiry” on the record.
Recently, The Wall Street Journal published an article noting some of the limits and benefits of the scientific method. See, “What the Pandemic Has Taught Us About Science.” Matt Ridley. The Wall Street Journal, October 11, 12, 2020: “The scientific method remains the best way to solve many problems, but bias, overconfidence, and politics can sometimes lead scientists astray”. Using the pandemic as a crisis, Ridley cites this anecdote to demonstrate the suboptimal effect of predictive models. “An epidemiological model developed last March at Imperial College London…[predicted] the pandemic could kill 2.2 million Americans, 510,000 Britons, and 96,000 Swedes. The Swedes tested the model against the real world and found it wanting: They decided to forgo a lockdown, and fewer than 6,000 have died there.”
Errors, such as these can derive from poor data, inadequate data, confirmation bias, unrealistic modeling assumptions, inherent variance, and statistical uncertainties. While these factors could never be eliminated, EPA’s CBA proposal ameliorates these effects by emphasizing consistency and transparency in future rulemakings. See, “Increasing Consistency and Transparency in Considering Benefits and Cost in the Clean Air Act Rulemaking Process,” Docket ID No. EPA-HQ-OAR-2020-00044.
Increasing consistency isn’t synonymous “with sameness.” EPA will apply CBA in particular cases in the manner allowed by the statute. In some instances, the Clean Air Act allows for cost considerations in technology determinations. In others, the statute may require balance of cost and health risk. In all regulatory actions, the case law and the particular statutory provision should guide just how costs and/or benefits will be used and analyzed. Without jeopardizing consistency, the Agency needs to be open to new data or advances in modelling. Risk analysis is not a static science. More is known every day on relative risks, assessment methods, and the representativeness of assumptions.
By requiring greater transparency, the Agency will go a long way in taking the veil off the “magic” of CBA. By open discussion of the statistical uncertainty, CBA results would eliminate the illusion of certainty. It should be a standard protocol for EPA to publish clear and understandable summaries of the uncertainties inherent in all “benefit” and “risk” calculations and what that means to the public. Likewise, economic cost models suffer from the same problem of inherent inaccuracies or whether any given model is applicable to the economic and industrial status. Economies change rapidly, and industry impacts are often influenced by unforeseen circumstances. EPA can also improve its position as an authority on regulations by being clearer about key assumptions that drive these analyses, as well as a frank disclosure of uncertainty or risk in the models used and how that may influence decision making. Under the Administrative Procedure Act and the Clean Air Act provisions on rulemaking, the Agency is already required to provide a basis and purpose for its rules. By codifying its intent to increase transparency, the agency will improve the quality of its rules, the comment process, and judicial review.
EPA’s CBA proposal represents a strong step in incorporating CBA into Clean Air Act decision making. When finalized, the result will be better rules, better public acceptance of rules, and rules which balance competing public interests. All the public comments are available at
Docket ID No. EPA-HQ-OAR-2020-00044, and a summary of some the industrial and business interest comments can be found here.
