  In dynamic discrete choice (DDC) analysis, it is common to use mixture models
to control for unobserved heterogeneity. However, consistent estimation
typically requires both restrictions on the support of unobserved heterogeneity
and a high-level injectivity condition that is difficult to verify. This paper
provides primitive conditions for point identification of a broad class of DDC
models with multivariate continuous permanent unobserved heterogeneity. The
results apply to both finite- and infinite-horizon DDC models, do not require a
full support assumption, nor a long panel, and place no parametric restriction
on the distribution of unobserved heterogeneity. In addition, I propose a
seminonparametric estimator that is computationally attractive and can be
implemented using familiar parametric methods.
