Extrapolating the Value Per Statistical Life Between Populations: Theoretical Implications

Abstract

Extrapolation of estimates of the value per statistical life (VSL) from high- to low- or middle-income populations requires attention to the possible effects of differences in income, current mortality risk, health, life expectancy, and many other factors. The standard theoretical model of VSL implies that VSL increases with income and decreases with current mortality risk. The effect of mortality risk is likely to be negligible while the effect of income is large and poorly quantified. Effects of differences in life expectancy and health are theoretically ambiguous. Effects of other factors, including differences in health care, formal and informal support networks, and cultural or religious factors that affect preferences for spending on oneself or others may be important but are unknown. Practical issues include choice of the most appropriate measure of income and possible differences in the patterns of age dependence between populations.