Semiparametric Nonlinear Least Square Estimation of Truncated Regression Models

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Semiparametric Nonlinear Least Square Estimation of Truncated Regression Models

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1990-02

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Center for Economic Research, Department of Economics, University of Minnesota

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Working Paper

Abstract

This article provides a semi parametric method for the estimation of truncated regression models where the disturbances are independent with the regressors before truncation. This independency property provides useful information on the identification and estimation of the model. Our estimate is shown to be Vn-consistent and asymptotically normal. Consistent estimate of the asymptotic covariance matrix of the estimator is provided. Monte Carlo experiments are performed to investigate some finite sample properties of the estimator.

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Lee, L., (1990), "Semiparametric Nonlinear Least Square Estimation of Truncated Regression Models", Discussion Paper No. 254, Center for Economic Research, Department of Economics, University of Minnesota.

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Lee, Lung-Fei. (1990). Semiparametric Nonlinear Least Square Estimation of Truncated Regression Models. Retrieved from the University Digital Conservancy, https://hdl.handle.net/11299/55533.

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