Model-selection tests for conditional moment restriction models

Yu-Chin Hsu; Xiaoxia Shi

doi:10.1111/ectj.12081

SEMIPARAMETRIC EFFICIENCY BOUNDS FOR CONDITIONAL MOMENT RESTRICTION MODELS WITH DIFFERENT CONDITIONING VARIABLES

Econometric Theory ◽

10.1017/s0266466615000080 ◽

2015 ◽

Vol 32 (4) ◽

pp. 917-946 ◽

Cited By ~ 4

Author(s):

Marian Hristache ◽

Valentin Patilea

Keyword(s):

Regression Models ◽

Supply And Demand ◽

Simultaneous Equations ◽

Conditional Moment ◽

Efficient Score ◽

Semiparametric Efficiency ◽

Regression Quantile ◽

New Applications ◽

Theoretical Results ◽

Moment Restriction

This paper addresses the problem of semiparametric efficiency bounds for conditional moment restriction models with different conditioning variables. We characterize such an efficiency bound, that in general is not explicit, as a limit of explicit efficiency bounds for a decreasing sequence of unconditional (marginal) moment restriction models. An iterative procedure for approximating the efficient score when this is not explicit is provided. Our theoretical results provide new insight for the theory of semiparametric efficiency bounds literature and open the door to new applications. In particular, we investigate a class of regression-like (mean regression, quantile regression,…) models with missing data, an example of a supply and demand simultaneous equations model and a generalized bivariate dichotomous model.

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A NOTE ON GENERALIZED EMPIRICAL LIKELIHOOD ESTIMATION OF SEMIPARAMETRIC CONDITIONAL MOMENT RESTRICTION MODELS

Econometric Theory ◽

10.1017/s0266466616000360 ◽

2016 ◽

Vol 33 (5) ◽

pp. 1242-1258 ◽

Cited By ~ 2

Author(s):

Naoya Sueishi

Keyword(s):

Empirical Likelihood ◽

Estimation Method ◽

Likelihood Estimation ◽

Unknown Parameters ◽

Conditional Moment ◽

Finite Dimensional ◽

Dimensional Parameters ◽

Image Position ◽

Asymptotically Efficient ◽

Moment Restriction

This paper proposes an empirical likelihood-based estimation method for semiparametric conditional moment restriction models, which contain finite dimensional unknown parameters and unknown functions. We extend the results of Donald, Imbens, and Newey (2003, Journal of Econometrics 117, 55–93) by allowing unknown functions to be included in the conditional moment restrictions. We approximate unknown functions by a sieve method and estimate the finite dimensional parameters and unknown functions jointly. We establish consistency and derive the convergence rate of the estimator. We also show that the estimator of the finite dimensional parameters is $\sqrt n$-consistent, asymptotically normally distributed, and asymptotically efficient.

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Constrained conditional moment restriction models

10.1920/wp.cem.2015.5915 ◽

2015 ◽

Cited By ~ 17

Author(s):

Victor Chernozhukov ◽

Whitney K. Newey ◽

Andres Santos

Keyword(s):

Conditional Moment ◽

Moment Restriction

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CONDITIONAL MOMENT RESTRICTIONS IN CENSORED AND TRUNCATED REGRESSION MODELS

Econometric Theory ◽

10.1017/s0266466601175018 ◽

2001 ◽

Vol 17 (5) ◽

pp. 863-888 ◽

Cited By ~ 14

Author(s):

Whitney K. Newey

Keyword(s):

Regression Models ◽

Efficient Estimation ◽

Truncated Regression ◽

Conditional Moment ◽

Weighted Version ◽

Unknown Distribution ◽

Consistent Estimators ◽

Semiparametric Efficiency Bound ◽

Moment Restrictions ◽

Moment Restriction

Censored and truncated regression models with unknown distribution are important in econometrics. This paper characterizes the class of all conditional moment restrictions that lead to √n-consistent estimators for these models. The semiparametric efficiency bound for each conditional moment restriction is derived. In the case of a nonzero bound it is shown how an estimator can be constructed and that an appropriately weighted version can attain the efficiency bound. These estimators also work when the disturbance is independent of the regressors. The paper discusses combining conditional moment restrictions for more efficient estimation in this case.

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