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Expert Elicitation of the Value per Statistical Life in an Air Pollution Context

Authors

  • Henry A. Roman,

    Corresponding author
      Henry A. Roman, 1Industrial Economics, Incorporated, 2067 Massachusetts Ave, Cambridge, MA 02140, USA; tel: 617–354-0074; fax: 617–354-0463; hroman@indecon.com
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    • Industrial Economics, Incorporated, 2067 Massachusetts Ave, Cambridge, MA, USA.

  • James K. Hammitt,

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    • Harvard University (Center for Risk Analysis), 718 Huntington Avenue, Boston, MA, USA.

    • Toulouse School of Economics (LERNA-INRA), 21, allée de Brienne, Toulouse, France.

  • Tyra L. Walsh,

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    • Industrial Economics, Incorporated, 2067 Massachusetts Ave, Cambridge, MA, USA.

  • David M. Stieb

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    • Health Canada, AIR HEALTH EFFECTS RESEARCH, 400 - 4595 Canada Way, Burnaby, British Columbia V5G 1J9, Canada.


Henry A. Roman, 1Industrial Economics, Incorporated, 2067 Massachusetts Ave, Cambridge, MA 02140, USA; tel: 617–354-0074; fax: 617–354-0463; hroman@indecon.com.

Abstract

The monetized value of avoided premature mortality typically dominates the calculated benefits of air pollution regulations; therefore, characterization of the uncertainty surrounding these estimates is key to good policymaking. Formal expert judgment elicitation methods are one means of characterizing this uncertainty. They have been applied to characterize uncertainty in the mortality concentration-response function, but have yet to be used to characterize uncertainty in the economic values placed on avoided mortality. We report the findings of a pilot expert judgment study for Health Canada designed to elicit quantitative probabilistic judgments of uncertainties in Value-per-Statistical-Life (VSL) estimates for use in an air pollution context. The two-stage elicitation addressed uncertainties in both a base case VSL for a reduction in mortality risk from traumatic accidents and in benefits transfer-related adjustments to the base case for an air quality application (e.g., adjustments for age, income, and health status). Results for each expert were integrated to develop example quantitative probabilistic uncertainty distributions for VSL that could be incorporated into air quality models.

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