We show how to nonparametrically identify and estimate the distribution of random coefficients
that characterizes the heterogeneity among agents in a general class of economic choice
models. We introduce an axiom that we term separability and prove that separability of a
structural model ensures identification. Identification naturally gives rise to a nonparametric
minimum distance estimator. We prove identification of distributions of utility functions in
multinomial choice, distributions of labor supply responses to tax changes, and distributions
of wage functions in the Roy selection model. We also reconsider the problem of endogeneity
in economic choice models, leading to new results on the two-stage least squares model.