Statistical vs. identified lives in benefit-cost analysis

B-Tier
Journal: Journal of Risk and Uncertainty
Year: 2007
Volume: 35
Issue: 1
Pages: 45-66

Score contribution per author:

1.005 = (α=2.01 / 2 authors) × 1.0x B-tier

α: calibrated so average coauthorship-adjusted count equals average raw count

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

Technical Details

RePEc Handle
repec:kap:jrisku:v:35:y:2007:i:1:p:45-66
Journal Field
Theory
Author Count
2
Added to Database
2026-01-25