We propose a simple mixtures estimator for recovering the joint distribution of
parameter heterogeneity in economic models, such as the random coefficients
logit. The estimator is based on linear regression subject to linear inequality con-
straints, and is robust, easy to program, and computationally attractive compared
to alternative estimators for random coefficient models. For complex structural
models, one does not need to nest a solution to the economic model during op-
timization. We present a Monte Carlo study and an empirical application to dy-
namic programming discrete choice with a serially correlated unobserved state
variable.
Keywords. Random coefficients, mixtures, demand, logit, mixed logit, dynamic
programming, teacher labor supply.
JEL classification. C25, C14, L.