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SEMIPARAMETRIC ESTIMATION OF A HETEROSKEDASTIC SAMPLE SELECTION MODEL

Published online by Cambridge University Press:  24 September 2003

Songnian Chen  and
Shakeeb Khan
Songnian Chen
Affiliation:
Hong Kong University of Science and Technology
Shakeeb Khan
Affiliation:
University of Rochester
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Abstract

This paper considers estimation of a sample selection model subject to conditional heteroskedasticity in both the selection and outcome equations. The form of heteroskedasticity allowed for in each equation is multiplicative, and each of the two scale functions is left unspecified. A three-step estimator for the parameters of interest in the outcome equation is proposed. The first two stages involve nonparametric estimation of the “propensity score” and the conditional interquartile range of the outcome equation, respectively. The third stage reweights the data so that the conditional expectation of the reweighted dependent variable is of a partially linear form, and the parameters of interest are estimated by an approach analogous to that adopted in Ahn and Powell (1993, Journal of Econometrics 58, 3–29). Under standard regularity conditions the proposed estimator is shown to be -consistent and asymptotically normal, and the form of its limiting covariance matrix is derived.We are grateful to B. Honoré, R. Klein, E. Kyriazidou, L.-F. Lee, J. Powell, two anonymous referees, and the co-editor D. Andrews and also to seminar participants at Princeton, Queens, UCLA, and the University of Toronto for helpful comments. Chen's research was supported by RGC grant HKUST 6070/01H from the Research Grants Council of Hong Kong.

Type
Research Article
Information
Econometric Theory , Volume 19 , Issue 6 , December 2003 , pp. 1040 - 1064
Copyright
© 2003 Cambridge University Press

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