When making labor supply decisions, workers frequently trade off wages and non-wage job characteristics. The theory of compensating differentials offers a framework for explaining how workers make many of these decisions, but the generality of the framework combined with insufficient empirical evidence have provided researchers and policymakers with a poor understanding of how the prices of non-wage job characteristics are affected by workers' preferences through labor supply decisions. The purpose of this project is to use a new empirical approach to advance the understanding of compensating differentials for fatality risk. The empirical setting focuses on the commercial fishing and crabbing industry in the Bering Sea and Aleutian Islands region of Alaska, where the same crewmembers performing the same jobs face variation in both wages and fatality risk in different seasons of the year. This unique variation between job spells makes it possible to circumvent many of the chronic sources of bias in previous empirical estimates arising from unobserved static worker and firm characteristics, unjustified assumptions about perfect labor markets, and from common sources of measurement error.

In addition, this approach of using variation within the worker-firm level provides information on how the compensating differential varies as the level of fatality risk varies. The literature estimating the statistical value of life has relied heavily on the assumption that compensating differentials vary linearly with fatality risk; however, this assumption has not been tested. This project will formally test this linearity assumption over the observed range of fatality risk in order to assess its validity for extrapolating estimates beyond empirically observable risk levels, which is necessary for estimating the statistical value of life. Improving estimates of the compensating differential for fatality risk and the statistical value of human life will assist policymakers whose decisions affect life expectancies, as in the cases of workplace safety policies, health policies, and environmental policies. Understanding how individuals in the labor market make vital decisions can guide public policy decisions.

Agency
National Science Foundation (NSF)
Institute
Division of Social and Economic Sciences (SES)
Type
Standard Grant (Standard)
Application #
0851605
Program Officer
Robert E. O'Connor
Project Start
Project End
Budget Start
2009-03-01
Budget End
2011-02-28
Support Year
Fiscal Year
2008
Total Cost
$8,477
Indirect Cost
Name
Cornell University
Department
Type
DUNS #
City
Ithaca
State
NY
Country
United States
Zip Code
14850