A quantile estimation approach to identify income and age variation in the value of a statistical life

In theory, heterogeneity in individual characteristics translates into variation in the marginal willingness to pay for a mortality risk reduction. Two dimensions of heterogeneity, with respect to income and age, have recently received attention due to their policy relevance. We propose a quantile regression approach to simultaneously explore these two sources of heterogeneity and their interactions within the context of the hedonic wage model, the most common revealed preference approach for obtaining value of statistical life estimates. We illustrate the approach using data from the Health and Retirement Study (HRS). We find that the impact of age on the wage–risk tradeoff varies across the wage distribution. This result indicates important interactions between age and income heterogeneity. Thus, the conventional mean hedonic wage regression, even when the mean effect is allowed to vary with age, masks important heterogeneity.