Asymptotic Variance and Extensions of a Denisty-Weighted-Response Semiparametric Estimator
Building on some early works, Lewbel (2000) proposed estimators for binary and ordered discrete response models with endogenous regressors. These estimators have been extended for panel data and for truncated and censored models by later papers. The estimators are particularly innovative in that the...
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sg-smu-ink.soe_research-10732019-08-26T03:39:28Z Asymptotic Variance and Extensions of a Denisty-Weighted-Response Semiparametric Estimator LEE, Myoung-jae HUANG, Fali KIM, Young-sook Building on some early works, Lewbel (2000) proposed estimators for binary and ordered discrete response models with endogenous regressors. These estimators have been extended for panel data and for truncated and censored models by later papers. The estimators are particularly innovative in that the latent linear regression functions are pulled out of the nonlinear limited dependent variable models, which are then treated as if they were the usual linear models. But understanding the estimators and their applications have been “hampered” by less-than-ideal expositions and assumptions. For this problem, this short note reviews the estimators and makes the following three points. First, the derivation and proper insight of the asymptotic variances are provided. Second, the inefficiency of the ordered discrete response version is pointed out and corrected. Third, assumptions in the panel data extension by Honoré and Lewbel (2002) are relaxed. 2008-03-01T08:00:00Z text application/pdf https://ink.library.smu.edu.sg/soe_research/74 https://ink.library.smu.edu.sg/context/soe_research/article/1073/viewcontent/jetem19_1_3.pdf http://creativecommons.org/licenses/by-nc-nd/4.0/ Research Collection School Of Economics eng Institutional Knowledge at Singapore Management University semiparametrics two-stage estimation binary response ordered discrete response panel data Econometrics |
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Building on some early works, Lewbel (2000) proposed estimators for binary and ordered discrete response models with endogenous regressors. These estimators have been extended for panel data and for truncated and censored models by later papers. The estimators are particularly innovative in that the latent linear regression functions are pulled out of the nonlinear limited dependent variable models, which are then treated as if they were the usual linear models. But understanding the estimators and their applications have been “hampered” by less-than-ideal expositions and assumptions. For this problem, this short note reviews the estimators and makes the following three points. First, the derivation and proper insight of the asymptotic variances are provided. Second, the inefficiency of the ordered discrete response version is pointed out and corrected. Third, assumptions in the panel data extension by Honoré and Lewbel (2002) are relaxed. |
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text |
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LEE, Myoung-jae HUANG, Fali KIM, Young-sook |
author_facet |
LEE, Myoung-jae HUANG, Fali KIM, Young-sook |
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LEE, Myoung-jae |
title |
Asymptotic Variance and Extensions of a Denisty-Weighted-Response Semiparametric Estimator |
title_short |
Asymptotic Variance and Extensions of a Denisty-Weighted-Response Semiparametric Estimator |
title_full |
Asymptotic Variance and Extensions of a Denisty-Weighted-Response Semiparametric Estimator |
title_fullStr |
Asymptotic Variance and Extensions of a Denisty-Weighted-Response Semiparametric Estimator |
title_full_unstemmed |
Asymptotic Variance and Extensions of a Denisty-Weighted-Response Semiparametric Estimator |
title_sort |
asymptotic variance and extensions of a denisty-weighted-response semiparametric estimator |
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Institutional Knowledge at Singapore Management University |
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2008 |
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https://ink.library.smu.edu.sg/soe_research/74 https://ink.library.smu.edu.sg/context/soe_research/article/1073/viewcontent/jetem19_1_3.pdf |
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