Semiparametric estimation of binary response models with endogenous regressors
Abstract: In this paper, we propose a two-step semiparametric maximum likelihood (SML) estimator for the coefficients of a single index binary choice model with endogenous regressors when identification is achieved via a control function approach. The first step consists of estimating a reduced form equation for the endogenous regressors and extracting the corresponding residuals. In the second step, the latter are added as control variates to the outcome equation, which is in turn estimated by SML. We establish the estimator’s n-consistency and asymptotic normality. In a simulation study, we compare the properties of our estimator with those of existing alternatives, highlighting the advantages of our approach
- Standort
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Deutsche Nationalbibliothek Frankfurt am Main
- Umfang
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Online-Ressource
- Sprache
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Englisch
- Anmerkungen
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Postprint
begutachtet (peer reviewed)
In: Journal of Econometrics ; 153 (2009) 1 ; 51-64
- Ereignis
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Veröffentlichung
- (wo)
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Mannheim
- (wann)
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2009
- Urheber
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Rothe, Christoph
- DOI
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10.1016/j.jeconom.2009.04.005
- URN
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urn:nbn:de:0168-ssoar-248602
- Rechteinformation
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Open Access unbekannt; Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Letzte Aktualisierung
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25.03.2025, 13:56 MEZ
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Beteiligte
- Rothe, Christoph
Entstanden
- 2009
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