Censored regression quantiles with endogenous regressors
نویسندگان
چکیده
منابع مشابه
Censored Regression Quantiles with Endogenous Regressors
This paper develops a semiparametric method for estimation of the censored regression model when some of the regressors are endogenous (and continuously distributed) and instrumental variables are available for them. A “distributional exclusion” restriction is imposed on the unobservable errors, whose conditional distribution is assumed to depend on the regressors and instruments only through a...
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In this paper we propose a method to robustly estimate linear regression quantiles with censored data. We adjust the estimator recently developed by Portnoy by replacing the Koenker-Bassett regression quantiles with the regression depth quantiles. The resulting optimization problem is solved iteratively over a set of grid points. We show on some examples that, contrary to the Koenker-Bassett ap...
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For censored data, it is very common for the tail of the survival function to be non-identifiable because of the abundance of censored observations in the tail. Thus, if bootstrap methods are needed, they may perform poorly near the point of non-identifiability because of the variability in bootstrap samples. Since jackknife methods provide much less variability, they should provide better cove...
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Quantile regression is a wide spread regression technique which allows to model the entire conditional distribution of the response variable. A natural extension to the case of censored observations was introduced by Portnoy (2003) using a reweighting scheme based on the Kaplan-Meier estimator. We apply the same ideas on the depth quantiles defined in Rousseeuw and Hubert (1999). This leads to ...
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ژورنال
عنوان ژورنال: Journal of Econometrics
سال: 2007
ISSN: 0304-4076
DOI: 10.1016/j.jeconom.2007.01.016