Using many moment conditions can improve efficiency but makes the usual GMM inferences inaccurate. Two step GMM is biased. Generalized empirical likelihood (GEL) has smaller bias but the usual standard errors are too small. In this paper we use alternative asymptotics, based on many weak moment...

<p><p>This paper studies nonparametric estimation of conditional moment models in which the residual functions could be nonsmooth with respect to the unknown functions of endogenous variables. It is a problem of nonparametric nonlinear instrumental variables (IV) estimation, and a difficult nonlinear...</p></p>

We develop inference tools in a semiparametric partially linear regression model with missing response data. A class of estimators is defined that includes as special cases: a semiparametric regression imputation estimator, a marginal average estimator and a (marginal) propensity score weighted...

Choosing among a number of available treatments the most suitable for a given subject is an issue of everyday concern. A physician has to choose an appropriate drug treatment or medical treatment for a given patient, based on a number of observed covariates <i> X </i> and prior experience. A case...

This paper considers structural nonparametric random utility models for continuous choice variables. It provides suffcient conditions on random preferences to yield reduced- form systems of nonparametric stochastic demand functions that allow global invertibility between demands and random...

The principal purpose of this paper is to adapt to the conditional moment context the GEL unconditional moment methods described in Smith(1997, 2001) and Newey and Smith(2004). In particular we develop GEL estimators which achieve the semiparametric efficiency lower bound. The requisite GEL...

This paper provides weak conditions under which there is nonparametric interval identification of local features of a structural function which depends on a discrete endogenous variable and is nonseparable in a latent variate. The function may deliver values of a discrete or continuous outcome...

The approximate effects of measurement error on a variety of measures of inequality and poverty are derived. They are shown to depend on the measurement error variance and functionals of the error contaminated income distribution, but not on the form of the measurement error distribution, and to...

This paper develops and implements semiparametric methods for estimating binary response (binary choice) models withcontinuous endogenous regressors. It extends the existing literature on semiparametric estimation in single index binary response models to the case of endogenous regressors. It...

I study inverse probability weighted M-estimation under a general missing data scheme. The cases covered that do not previously appear in the literature include M-estimation with missing data due to a censored survival time, propensity score estimation of the average treatment effect for linear...