If the US Environmental Protection Agency doesn’t count the monetary benefits of regulations, Then federal actions are likely to lead to worse policy outcomes for public health and welfare.
A critical part of the rulemaking process for the US Environmental Protection Agency (EPA) is the preparation of regulatory impact analyses that assess the costs, benefits, and economic and equity impacts of proposed and final regulations. These analyses are important to help ensure that the public is aware of how regulations may affect their health and economic well-being. In a rule published on January 15, however, the Trump administration decided not to quantify human health benefits in its economic impact analysis, focusing solely on the costs to the regulated industry. Such an approach tilts the analysis in favor of less stringent regulation, resulting in forgone health and economic benefits. If this approach becomes the norm, analyses like this could lead to suboptimal decisions that would harm the American people.
Excluding the health benefits of regulation would go against accepted economic and scientific methodology, run counter to long-standing practice by the federal government under both political parties, and violate EPA’s own formal guidance for conducting such analyses. In this blog post, we assess each of EPA’s arguments for making such a drastic change to its proposed analytical process, finding that its arguments don’t hold up to even the most cursory scrutiny.
Excluding the health benefits of regulation would go against accepted economic and scientific methodology, run counter to long-standing practice by the federal government under both political parties, and violate EPA’s own formal guidance for conducting such analyses.
EPA first excluded the health benefits of air pollution regulation in several rules issued during the first Trump administration. Under the Biden administration, EPA undid those rules and returned to regulatory impact analyses that were consistent with best practices and their own peer-reviewed methods.
Now, EPA is returning to the discredited methods of the first Trump administration with a vengeance. In the economic impact analysis for the mid-January rule—which reviews the performance standards for stationary combustion turbines, a source of air pollutants that form ground-level ozone and particulate matter—EPA advances multiple angles of attack. The agency makes the following arguments:
- EPA’s past analytical practice did not adequately characterize uncertainties in benefits.
- Providing point estimates (expected monetary values of benefits) is inappropriate in the presence of uncertainties.
- EPA does not have sufficient confidence to monetize health benefits; for example, by using the value of a statistical life.
- Benefits from reducing particulate matter below the level of the national ambient air quality standards are so uncertain that they should not be included.
- Estimating fine particulate matter and ozone “co-benefits” for air regulations that target other pollutants is inappropriate.
These arguments are unsupported and out of step with the best available science and established practice.
Uncertainty Has Always Been a Part of Regulatory Analyses
EPA has quantified the human health benefits of regulations for decades and under both Republican and Democratic administrations. EPA’s methods for quantifying and monetizing the health benefits of air pollution, including how uncertainties are characterized, have been the subject of intense peer reviews, including by the National Academies of Sciences, Engineering, and Medicine; the EPA Science Advisory Board Council on Clean Air Act Compliance Analysis; the EPA Clean Air Scientific Advisory Committee; the EPA Environmental Economics Advisory Committee; and the EPA Science Advisory Board. These scientific review bodies have consistently supported EPA’s approaches for quantifying and monetizing human health benefits, including EPA’s approaches to characterizing uncertainty, which includes providing distributions of benefits as well as point estimates. EPA also quantifies uncertainties in its peer-reviewed, open-source benefits estimation software, the Environmental Benefits Mapping Analysis Program (which Bryan Hubbell led the development of while at EPA).
In addition, substantial uncertainties (and biases) plague cost estimates, such as an inability to predict future innovations and the results of human ingenuity in finding the cheapest mitigation strategies. But EPA, while arguing that uncertainties prevent it from monetizing health benefits, makes no mention of the equivalent concerns about presenting point estimates or distributions of costs. The regulatory impact analysis for the combustion turbines rule does not quantify cost uncertainties, devoting only six lines to cost uncertainties (on pages 26 and 63), ending with the conclusion, “costs presented in this [regulatory impact analysis] may be overestimates.”
Benefits Gained by Reducing Particulate Matter Concentrations Below National Standards
EPA sets standards that it decides are “requisite” to protect public health, including for vulnerable populations, with an “adequate margin of safety.” What defines an “adequate margin of safety” is a policy decision—not an absolute determined by the science. EPA has interpreted “requisite” to mean that standards should be set where the confidence is strongest in the associations between health effects and concentrations of particulate matter (known broadly as PM2.5, or particulate matter that’s less than 2.5 micrometers in diameter). In the 2024 National Ambient Air Quality Standards rule, EPA states that the relationship between PM2.5 and mortality is linear and without a threshold; in other words, the less PM2.5 in the air, the better for public health.
A facility likely covered by the new rule.
All of this is to say that the standards are a public health policy instrument, not a level below which no health risks occur. Consistent with guidance from EPA and the Office of Management and Budget, it is fully appropriate to include the expected benefits of reductions in PM2.5 concentrations below the National Ambient Air Quality Standards, with appropriate characterization of uncertainties.
The Value of a Statistical Life Is the Best Method for Monetizing Mortality Benefits
The value of a statistical life quantifies people’s willingness to pay to reduce their risk of death by a small amount. The value of a statistical life can be based on decisions made in everyday life; for example, people making decisions to pursue less lucrative but safer occupations or buying more expensive but safer cars. Economists also can determine the value of a statistical life by analyzing responses to highly structured surveys that can reveal willingness to pay for a risk reduction.
The value of a statistical life is emphatically not the value of a human life. But this value of statistical life can be useful for regulatory impact analyses. The monetized mortality benefits of a regulation are calculated by multiplying the value of a statistical life by premature deaths avoided due to the regulation. These calculations also involve statistical representations of uncertainty, such as confidence intervals and sensitivity analysis.
Environmental economists have published hundreds of studies on the value of a statistical life over the past few decades. Because of their importance in regulatory impact analyses, these values are reviewed and heavily scrutinized and endorsed by EPA’s Science Advisory Boards, the National Academies of Sciences, and similar bodies in other countries.
No Co-benefits—Only Benefits
The scientific and economic consensus is that benefit-cost analysis should include all the positive and negative effects of an air-quality regulation, not just those related to the targeted pollutant. Resources for the Future researchers addressed the issue of co-benefits in a 2021 peer-reviewed article, noting that “co-benefits are simply a semantic category of benefits that should be included in benefit-cost analyses.” They find that excluding co-benefits could lead to inappropriate conclusions about whether policies are economically efficient or provide net benefits to society.
More generally, the inclusion of co-benefits (or costs) improves regulatory analyses. Failing to include all benefits and costs of a regulation in such analyses, whether with direct intent or not, will bias estimates of net benefits, which could lead to worse policy outcomes.
Conclusion
EPA’s arguments against best practices for benefit-cost analysis are likely to be applied across the federal bureaucracy. By failing to include quantified and monetized benefits in economic impact analysis—for the recent rule on combustion turbines and likely for many upcoming deregulatory actions—EPA has chosen to abandon adherence to economic principles, decades of guidance from experts, its own economic analysis guidelines, and guidance from the Office of Management and Budget. EPA’s arguments for abandoning health benefits in the recent rule are neither persuasive nor well founded in science. The whole idea of a regulatory impact analysis becomes irrelevant without the assessment of economic benefits. Without applying the important tool of benefit-cost analysis, air-quality regulators cannot evaluate clearly whether rules have positive net benefits for society, and this lack of clarity will likely lead to worse policy outcomes for public health.
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