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Semiparametric Generalized Least Squares in the Multivariate Nonlinear Regression Model

Published online by Cambridge University Press:  18 October 2010

Miguel A. Delgado
Miguel A. Delgado
Affiliation:
Indiana University
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Abstract

Asymptotically efficient estimates for the multiple equations nonlinear regression model are obtained in the presence of heteroskedasticity of unknown form. The proposed estimator is a generalized least squares based on nonparametric nearest neighbor estimates of the conditional variance matrices. Some Monte Carlo experiments are reported.

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Type
Articles
Information
Econometric Theory , Volume 8 , Issue 2 , June 1992, pp. 203 - 222
Copyright
Copyright © Cambridge University Press 1992

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