Past approaches to this calculation have used classic hedonic regression techniques, whereas the researchers’ method adds a structural estimation of preferences for risky jobs that explicitly considers the matching of workers to jobs while estimating the equilibrium hedonic wage equation. While the proposed model can be used to solve a wide range of assignment problems in both the field of family economics (marriage market) and labour economics (labour market), the researchers have chosen to illustrate the usefulness of their methodology by applying it to the estimation of compensating wage differentials for the risk of fatal injury on the job. In a forthcoming paper in Quantitative Economics entitled “A Note on the Estimation of Job Amenities and Labor Productivity”, Arnaud Dupuy, Professor in Economics at the Faculty of Law, Economics and Finance at the University of Luxembourg and co-author Alfred Galichon (NYU, Sciences-Po), build on their previous research to introduce a maximum likelihood estimator of the value of job amenities and labor productivity in a single matching market based on the observation of equilibrium matches and wages. The figure that they estimate is used to help policymakers and regulators perform cost-benefit analyses in fields such as workplace health and safety regulations.

Can you put a number on the value of a human life? How much are we willing to spend to reduce the risk of fatality in a given population? Economists can answer this question by calculating the value of a statistical life as a measure of the local trade-off between fatality risk and money spent.

Classic hedonic regression article