Generalized method of moments (GMM) estimation has become an important unifying framework for inference in econometrics in the last 20 years. It can be thought of as encompassing almost all of the common estimation methods, such as maximum likelihood, ordinary least squares, instrumental...

This article evaluates the usefulness of a nonparametric approach to Bayesian inference by presenting two applications. Our first application considers an educational choice problem. We focus on obtaining a predictive distribution for earnings corresponding to various levels of schooling. This...

We consider the implications of an alternative to the classical measurement-error model, in which the observed, mismeasured data are optimal predictions of the true values, given some information set. In this model, any measurement error is uncorrelated with the reported value and, by necessity,...

In this paper, a new estimator is proposed for discrete choice models with choice-based sampling. The estimator is efficient and can incorporate information on the marginal choice probabilities in a straightforward manner and for that case leads to a procedure that is computationally and...

Census reports can be interpreted as providing nearly exact knowledge of moments of the marginal distribution of economic variables. This information can be combined with cross-sectional or panel samples to improve accuracy of estimation. In this paper, the authors show how to do this...