title: Valuing Reductions in Fatal Illness Risks: Implications of Recent Research.
abstract: The value of mortality risk reductions, conventionally expressed as the value per statistical life, is an important determinant of the net benefits of many government policies. US regulators currently rely primarily on studies of fatal injuries, raising questions about whether different values might be appropriate for risks associated with fatal illnesses. Our review suggests that, despite the substantial expansion of the research base in recent years, few US studies of illness-related risks meet criteria for quality, and those that do yield similar values to studies of injury-related risks. Given this result, combining the findings of these few studies with the findings of the more robust literature on injury-related risks appears to provide a reasonable range of estimates for application in regulatory analysis. Our review yields estimates ranging from about $4.2 million to $13.7 million with a mid-point of $9.0 million (2013 dollars). Although the studies we identify differ from those that underlie the values currently used by Federal agencies, the resulting estimates are remarkably similar, suggesting that there is substantial consensus emerging on the values applicable to the general US population. Copyright © 2015 John Wiley & Sons, Ltd.
authors.affiliation: Harvard University (Center for Risk Analysis), Boston, MA, USA.
authors.forename: Lisa A
authors.initials: LA
authors.lastname: Robinson
authors.affiliation: Harvard University (Center for Risk Analysis), Boston, MA, USA.|Toulouse School of Economics (LERNA), Toulouse, France.|U.S. Department of Health and Human Services, Washington, D.C., USA.
authors.forename: James K
authors.initials: JK
authors.lastname: Hammitt
mesh_terms: D000206:Actuarial Analysis / Q000191:economics; D035843:Biomedical Research; D003362:Cost-Benefit Analysis / Q000191:economics; D006801:Humans; D040242:Risk Reduction Behavior; D014481:United States; D026712:Value of Life / Q000191:economics*
keywords: benefit-cost analysis; regulation; value per statistical life