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Statistical vs. identified lives in benefit-cost analysis

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Author Info
James Hammitt ()
Nicolas Treich ()

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Abstract

Evaluation of projects that affect mortality risk usually assumes that risk changes are small and similar across individuals. In reality, risks differ among individuals and information about risk heterogeneity determines the extent to which affected lives are “statistical” or “identified” and influences the outcome of benefit-cost analysis (BCA). The effects of information about risk heterogeneity on BCA depend on, inter alia, whether information concerns heterogeneity of baseline or change in risk and whether valuation uses compensating or equivalent variation. BCA does not systematically favor identified over statistical lives. We suggest some political factors that may explain the apparent public bias. Copyright Springer Science+Business Media, LLC 2007

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File URL: http://hdl.handle.net/10.1007/s11166-007-9015-8
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Publisher Info
Article provided by Springer in its journal Journal of Risk and Uncertainty.

Volume (Year): 35 (2007)
Issue (Month): 1 (August)
Pages: 45-66
Download reference. The following formats are available: HTML (with abstract), plain text (with abstract), BibTeX, RIS (EndNote, RefMan, ProCite), ReDIF
Handle: RePEc:kap:jrisku:v:35:y:2007:i:1:p:45-66

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Web page: http://www.springerlink.com/link.asp?id=100299

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Related research
Keywords: Benefit-cost analysis; Value of statistical life; Information; Heterogeneity; D61; D81; H42; I18;

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  7. Jenni, Karen E & Loewenstein, George, 1997. "Explaining the "Identifiable Victim Effect."," Journal of Risk and Uncertainty, Springer, vol. 14(3), pages 235-57, May-June. [Downloadable!] (restricted)
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    Other versions:
  16. Buchanan, James M. & Faith, Roger L., 1979. "Trying again to value a life," Journal of Public Economics, Elsevier, vol. 12(2), pages 245-248, October. [Downloadable!] (restricted)
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