Please use this identifier to cite or link to this item: https://doi.org/10.1016/j.jeconom.2011.07.005
Title: Semiparametric estimation of a bivariate Tobit model
Authors: Chen, S. 
Zhou, X.
Issue Date: Dec-2011
Source: Chen, S., Zhou, X. (2011-12). Semiparametric estimation of a bivariate Tobit model. Journal of Econometrics 165 (2) : 266-274. ScholarBank@NUS Repository. https://doi.org/10.1016/j.jeconom.2011.07.005
Abstract: The existing semiparametric estimation literature has mainly focused on univariate Tobit models and no semiparametric estimation has been considered for bivariate Tobit models. In this paper, we consider semiparametric estimation of the bivariate Tobit model proposed by Amemiya (1974), under the independence condition without imposing any parametric restriction on the error distribution. Our estimator is shown to be consistent and asymptotically normal, and simulation results show that our estimator performs well in finite samples. It is also worth noting that while Amemiya's (1974) instrumental variables estimator (IV) requires the normality assumption, our semiparametric estimator actually outperforms his IV estimator even when normality holds. Our approach can be extended to higher dimensional multivariate Tobit models. © 2011 Elsevier B.V. All rights reserved.
Source Title: Journal of Econometrics
URI: http://scholarbank.nus.edu.sg/handle/10635/52125
ISSN: 03044076
DOI: 10.1016/j.jeconom.2011.07.005
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