Missing values are a major problem in all econometric applications based on survey data. A standard approach assumes data are missing-at-random and uses imputation methods, or even listwise deletion. This approach is justified if item non-response does not depend on the potentially missing...

This paper shows how to construct locally robust semiparametric GMM estimators, meaning equivalently moment conditions have zero derivative with respect to the first step and the first step does not affect the asymptotic variance. They are constructed by adding to the moment functions the...

We give a general construction of debiased/locally robust/orthogonal (LR) moment functions for GMM, where the derivative with respect to first step nonparametric estimation is zero and equivalently first step estimation has no effect on the influence function. This construction consists of...

From an empirical perspective, this paper critically examines the concepts of returns to scale (RTS) and economies of scale (EOS), and argues that the concept of EOS is more relevant and broader enough to exhibit proper scale economies behavior of firms. Two approaches, i.e., production function...

We study a general class of semiparametric estimators when the infinite-dimensional nuisance parameters include a conditional expectation function that has been estimated nonparametrically using generated covariates. Such estimators are used frequently to e.g. estimate nonlinear models with...

We propose instrumental variable(IV) estimators for quantile marginal effects and the parameters upon which they depend in a semiparametric outcome model with endogenous discrete treatment variables. We prove identification, consistency, and asymptotic normality of the estimators. We also show...

There are many economic parameters that depend on nonparametric first steps. Examples include games, dynamic discrete choice, average consumer surplus, and treatment effects. Often estimators of these parameters are asymptotically equivalent to a sample average of an object referred to as the...

Often semiparametric estimators are asymptotically equivalent to a sample average. The object being averaged is referred to as the influence function. The influence function is useful in formulating primitive regularity conditions for asymptotic normality, in efficiency comparions, for bias...

This paper presents identification and estimation results for a flexible state space model. Our modification of the canonical model allows the permanent component to follow a unit root process and the transitory component to follow a semiparametric model of a higher‐order...

Triangular systems with nonadditively separable unobserved heterogeneity provide a theoretically appealing framework for the modeling of complex structural relationships. However, they are not commonly used in practice due to the need for exogenous variables with large support for...