Estimating the Distribution of Welfare Effects Using Quantiles

This paper proposes a framework to model empirically welfare effects that are associated with a price change in a population of heterogeneous consumers which is similar to Hausman and Newey (1995), but allows for more general forms of heterogeneity. Individual demands are characterized by a general model which is nonparametric in the regressors, as well as monotonic in unobserved heterogeneity. In this setup, we first provide and discuss conditions under which the heterogeneous welfare effects are identified, and establish constructive identification. We then propose a sample counterpart estimator, and analyze its large sample properties. For both identification and estimation, we distinguish between the cases when regressors are exogenous and when they are endogenous. Finally, we apply all concepts to measuring the heterogeneous effect of a chance of gasoline price using US consumer data and find very substantial differences in individual effects across quantiles.