Using job changes to evaluate the bias of value of a statistical life estimates

This paper presents a new approach to obtaining unbiased estimates of the value of a statistical life (VSL) with labor market data. Investigating job changes, we combine the advantages of recent panel studies, allowing us to control for unobserved heterogeneity of workers, and conventional cross-sectional estimations, which are less affected by measurement error. We find a VSL of 6.1 million euros from pooled cross-sectional estimation, 1.5 million euros from the first-differences panel model and 2.0 million euros from the job-changer specification. Thus, ignoring individual heterogeneity causes overestimates of the VSL, whereas the attenuation bias in panel data models leads to underestimates of the VSL. Our results are less biased than former results and can be used to perform cost-benefit analyses of public projects aimed at reducing fatality risks, e.g., in the domains of environmental, health, or traffic policy.