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Semiparametric Estimation of Simultaneous-Equation Microeconometric Models with Index Restrictions

Semiparametric Estimation of Simultaneous-Equation Microeconometric Models with Index Restrictions Abstract This article introduces semiparametric methods for the estimation of simultaneous-equation microeconometric models with index restrictions. The methods are motivated by a semiparametric minimum-distance procedure, which unifies the estimation of both regression-type and linear or nonlinear simultaneous-equation models without emphasis on the construction of instrumental variables. Single-equation and systematic estimation methods and optimal weighting procedures are considered. The estimators are n-consistent and asymptotically normal. For the estimation of nonparametric regression and some sample selection models where the variances of disturbances are functions of the same indices, the optimal weighted estimator attains Chamberlain’s efficient bound for models with conditional moment restrictions. The weighted estimator is shown to be optimal within a class of semiparametric instrumental variables estimators. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png The Japanese Economic Review Springer Journals

Semiparametric Estimation of Simultaneous-Equation Microeconometric Models with Index Restrictions

The Japanese Economic Review , Volume 49 (4): 38 – Dec 1, 1998

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References (32)

Publisher
Springer Journals
Copyright
1998 Japanese Economic Association
ISSN
1352-4739
eISSN
1468-5876
DOI
10.1111/1468-5876.00090
Publisher site
See Article on Publisher Site

Abstract

Abstract This article introduces semiparametric methods for the estimation of simultaneous-equation microeconometric models with index restrictions. The methods are motivated by a semiparametric minimum-distance procedure, which unifies the estimation of both regression-type and linear or nonlinear simultaneous-equation models without emphasis on the construction of instrumental variables. Single-equation and systematic estimation methods and optimal weighting procedures are considered. The estimators are n-consistent and asymptotically normal. For the estimation of nonparametric regression and some sample selection models where the variances of disturbances are functions of the same indices, the optimal weighted estimator attains Chamberlain’s efficient bound for models with conditional moment restrictions. The weighted estimator is shown to be optimal within a class of semiparametric instrumental variables estimators.

Journal

The Japanese Economic ReviewSpringer Journals

Published: Dec 1, 1998

Keywords: economics, general; microeconomics; macroeconomics/monetary economics//financial economics; econometrics; development economics; economic history

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