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Nonparametric Estimation of Triangular Simultaneous Equations Models

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  • Whitney Newey
  • James Powell
  • Francis Vella

Abstract

This paper presents a simple two-step nonparametric estimator for a triangular simultaneous equation model. The authors use series approximations that exploit the additive structure of the model. The first step comprises the nonparametric estimation of the reduced form and the corresponding residuals. The second step is the estimation of the primary equation via nonparametric regression with the reduced form residuals included as a regressor. The authors derive consistency and asymptotic normality results for their estimator, including optimal convergence rates. An empirical example, on the relationship between the hourly wage rate and hours worked, illustrates the utility of the authors' approach.

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Bibliographic Info

Paper provided by Massachusetts Institute of Technology (MIT), Department of Economics in its series Working papers with number 98-16.

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Date of creation: Oct 1998
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Handle: RePEc:mit:worpap:98-16

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Postal: MASSACHUSETTS INSTITUTE OF TECHNOLOGY (MIT), DEPARTMENT OF ECONOMICS, 50 MEMORIAL DRIVE CAMBRIDGE MASSACHUSETTS 02142 USA
Phone: (617) 253-3361
Fax: (617) 253-1330
Web page: http://econ-www.mit.edu/
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Postal: MASSACHUSETTS INSTITUTE OF TECHNOLOGY (MIT), DEPARTMENT OF ECONOMICS, 50 MEMORIAL DRIVE CAMBRIDGE MASSACHUSETTS 02142 USA
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