In finite samples, the use of a slightly endogenous but highly relevant instrument can reduce mean-squared error (MSE). Building on this observation, I propose a moment selection criterion for GMM in which moment conditions are chosen based on the MSE of their associated estimators rather than...

In finite samples, the use of a slightly endogenous but highly relevant instrument can reduce mean-squared error (MSE). Building on this observation, I propose a moment selection criterion for GMM in which moment conditions are chosen based on the MSE of their associated estimators rather than...

This paper investigates the problem of testing conditional independence of Y and Z given λθ(X) for some unknown θ ∈ Θ ⊂ Rd, for a parametric function λθ(•). For instance, such a problem is relevant in recent literatures of heterogeneous treatment effects and contract theory. First,...

This paper studies the averaging generalized method of moments (GMM) estimator that combines a conservative GMM estimator based on valid moment conditions and an aggressive GMM estimator based on both valid and possibly misspecified moment conditions, where the weight is the sample analog of an...

This paper discusses the use of discrete choice dynamic programming (DCDP) methods for evaluating policies of particular relevance to developing countries, such as policies to reduce child labor and increase school attendance, to improve school quality, to affect immigration flows, to expand old...

This paper discusses methods for evaluating the impacts of social programs prior to their implementation. Ex ante evaluation is useful for designing programs that achieve some optimality criteria, such as maximizing impact for a given cost. This paper illustrates through several examples the use...

We develop an empirical methodology to study markets for services. These markets are typically organized as multi-attribute auctions in which buyers take into account seller's price as well as various characteristics, including quality. Our identification and estimation strategies exploit...

We study the nonparametric identification and estimation of a structural model for committee decisions. Members of a committee share a common information set, but differ in ideological bias while processing multiple information sources and in individual tastes while weighing multiple objectives....

This paper studies the nonparametric identification and estimation of voters’ preferences when voters are ideological. We establish that voter preference distributions and other parameters of interest can be identified from aggregate electoral data. We also show that these objects can be...

We introduce an approach for semi-parametric inference in dynamic binary choice models that does not impose distributional assumptions on the state variables unobserved by the econometrician. The proposed framework combines Bayesian inference with partial identification results. The method is...