This paper reviews methods for the estimation of dynamic discrete choice structural models
and discusses related econometric issues. We consider single-agent models, competitive …

Nonlinear panel data models arise naturally in economic applications, yet their analysis is
challenging. Here we provide a progress report on some recent advances in the area. We …

This paper introduces time‐varying grouped patterns of heterogeneity in linear panel data
models. A distinctive feature of our approach is that group membership is left unrestricted …

This paper provides a novel mechanism for identifying and estimating latent group structures
in panel data using penalized techniques. We consider both linear and nonlinear models …

This chapter overviews productivity research from an industrial organization perspective. We
focus on what is known and what still needs to be learned about the productivity levels and …

This paper develops an open economy model with heterogeneous final goods producers
who simultaneously choose whether to export their output and whether to use imported …

We study discrete panel data methods where unobserved heterogeneity is revealed in a first
step, in environments where population heterogeneity is not discrete. We focus on two‐step …

We adapt the expectation–maximization algorithm to incorporate unobserved heterogeneity
into conditional choice probability (CCP) estimators of dynamic discrete choice problems …

In this paper, we decompose city size wage premia into various components. We base these
decompositions on an estimated on-the-job search model that incorporates latent ability …

We estimate demand for residential broadband using high‐frequency data from subscribers
facing a three‐part tariff. The three‐part tariff makes data usage during the billing cycle a …