Semiparametric Nonlinear Least Square Estimation of Truncated Regression Models
1990-02
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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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Discussion Paper
254
254
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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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