Showing 1 - 9 of 9
The goal of this paper is to develop techniques to simplify semiparametric inference. We do this by deriving a number of numerical equivalence results. These illustrate that in many cases, one can obtain estimates of semiparametric variances using standard formulas derived in the...
Persistent link: https://www.econbiz.de/10010288344
Persistent link: https://www.econbiz.de/10002131174
The central concern of the paper is with the formulation of tests of neglected parameter heterogeneity appropriate for model environments specified by a number of unconditional or conditional moment conditions. We initially consider the unconditional moment restrictions framework. Optimal...
Persistent link: https://www.econbiz.de/10010288363
We propose a generalization of the linear quantile regression model to accommodate possibilities afforded by panel data. Specifically, we extend the correlated random coefficients representation of linear quantile regression (e.g., Koenker, 2005; Section 2.6). We show that panel data allows the...
Persistent link: https://www.econbiz.de/10011594348
We propose a generalization of the linear quantile regression model to accommodate possibilities afforded by panel data. Specifically, we extend the correlated random coefficients representation of linear quantile regression (e.g., Koenker, 2005; Section 2.6). We show that panel data allows the...
Persistent link: https://www.econbiz.de/10011445722
Many structural economics models are semiparametric ones in which the unknown nuisance functions are identified via nonparametric conditional moment restrictions with possibly nonnested or overlapping conditioning sets, and the finite dimensional parameters of interest are over-identified via...
Persistent link: https://www.econbiz.de/10011282654
In this note, we characterize the semiparametric efficiency bound for a class of semi- parametric models in which the unknown nuisance functions are identified via nonparametric conditional moment restrictions with possibly non-nested or over-lapping conditioning sets, and the finite dimensional...
Persistent link: https://www.econbiz.de/10010318691
We study the asymptotic distribution of three-step estimators of a finite dimensional parameter vector where the second step consists of one or more nonparametric regressions on a regressor that is estimated in the first step. The first step estimator is either parametric or non-parametric....
Persistent link: https://www.econbiz.de/10010288379
Persistent link: https://www.econbiz.de/10001718757