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Statistical vs. Identified Lives in Benefit-Cost Analysis

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  • HAMMITT James K
  • TREICH Nicolas

    (LERNA, University of Toulouse)

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
(This abstract was borrowed from another version of this item.)

Suggested Citation

  • HAMMITT James K & TREICH Nicolas, 2006. "Statistical vs. Identified Lives in Benefit-Cost Analysis," LERNA Working Papers 06.11.204, LERNA, University of Toulouse.
    • Handle: RePEc:ler:wpaper:06.11.204
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    References listed on IDEAS

    as
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    More about this item

    JEL classification:

    • D61 - Microeconomics - - Welfare Economics - - - Allocative Efficiency; Cost-Benefit Analysis
    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty
    • H42 - Public Economics - - Publicly Provided Goods - - - Publicly Provided Private Goods
    • I18 - Health, Education, and Welfare - - Health - - - Government Policy; Regulation; Public Health

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