Journal of Risk and Uncertainty

, Volume 35, Issue 1, pp 45–66 | Cite as

Statistical vs. identified lives in benefit-cost analysis

  • James K. HammittEmail author
  • 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.


Benefit-cost analysis Value of statistical life Information Heterogeneity 

JEL Classification

D61 D81 H42 I18 



The authors thank Matthew Adler, Joanne Linnerooth-Bayer, John Graham, W. Kip Viscusi, an anonymous referee, and seminar participants at the universities of Montréal, Paris (Panthéon-Sorbonne), Ohio State, Kyoto, Lille, Mannheim, and Harvard for helpful comments. James K. Hammitt thanks the Université de Toulouse (LERNA-INRA, IDEI), Institut pour une Culture de Sécurité Industrielle (ICSI), and the Région Midi-Pyrénées for hospitality and support.


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Copyright information

© Springer Science+Business Media, LLC 2007

Authors and Affiliations

  1. 1.Center for Risk AnalysisHarvard UniversityBostonUSA
  2. 2.Toulouse School of Economics (LERNA-INRA)ToulouseFrance

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