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Statistical vs. identified lives in benefit-cost analysis

  • James Hammitt

    ()

  • Nicolas Treich

    ()

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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Article provided by Springer in its journal Journal of Risk and Uncertainty.

Volume (Year): 35 (2007)
Issue (Month): 1 (August)
Pages: 45-66

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Handle: RePEc:kap:jrisku:v:35:y:2007:i:1:p:45-66
Contact details of provider: Web page: http://www.springerlink.com/link.asp?id=100299

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