National Science Foundation
April 15, 2017 – March 31, 2020
Collectively, federal regulations to improve human health, safety, and the environment avert many thousands of deaths, and reduce non-fatal harm by hundreds of thousands of cases, but also impose costs up to billions of dollars annually. To become legally binding, almost all high-cost regulations must pass a “cost-benefit test”: the monetized value of the harms averted by the rule exceeds costs to regulated industries and consumers. Cost-benefit analysis (CBA) has been controversial in its monetary translation of life-saving benefits and how to estimate risks with incomplete data, but ironically, the mechanics of how to quantify effects of both risk reduction and cost on human welfare has received less attention. This project presumes that two changes to current methods of benefit and cost valuation might change which regulations pass or fail the cost-benefit test, and alter the optimal level of stringency for a given regulation. First, typical estimates of the value of a statistical life deliberately exclude all consideration of altruism, using the estimated private value of reducing a small risk of one’s own death to value public programs benefiting the entire nation. Secondly, CBA implicitly dictates that the total benefit of a program is proportional to the number of lives saved, regardless of whether some people face much higher mortality risks, and CBA also considers only the regulation’s total cost, even if costs affect some businesses or consumers disproportionately.
Two large survey experiments probe these simplified assumptions and offer principled, quantitative alternatives. The researchers estimate the “value of a statistical life with shared purpose” by querying subjects on the perceived desirability of hypothetical regulations in which the scale of tradeoffs is billions of dollars imposed on everyone and thousands of randomly saved lives, not a personal tradeoff between a few dollars and a tiny fraction of one life. This survey also tests for (and isolates) the effects of: (1) “paternalistic” altruism (concern for others’ longevity even if those others would prefer greater risk at less regulatory cost) versus “non-paternalistic” altruism (considering others’ net benefits including their costs); and (2) posing tradeoffs as both a user-defined acceptable cost for a fixed number of lives saved and a user-defined minimum number of lives saved for a fixed regulatory cost. A second survey tests the assumption that individual levels of risk and cost can be summed over the population without being disaggregated (i.e., that individuals regard the welfare effects of risk or cost at any level as linear), using subjects’ ratings of how dire they view varying hypothetical individual probabilities of harm and varying personal costs. This experiment reveals whether there are de minimus levels of either risk or cost that can sensibly be rounded to zero, and/or intolerably high levels whose effects are not merely proportional to those at lower levels. The project also enlists practitioners and users of CBA in the federal government as a separate subject group for the two surveys, and culminates with two workshops for these officials to discuss research results and whether adding “shared purpose” and nonlinear valuation of risk and cost might have changed important prior decisions about which regulatory option in fact had the greatest net benefit to society.