Estimating censored regression models in the presence of nonparametric multiplicative heteroskedasticity

By Songnian Chen, Shakeeb Khan. 2000

50 citations recorded by the source corpus.

Abstract Powell's (1984, Journal of Econometrics 25, 303–325) censored least absolute deviations (CLAD) estimator for the censored linear regression model has been regarded as a desirable alternative to maximum likelihood estimation methods due to its robustness to conditional heteroskedasticity and distributional misspecification of the error term. However, the CLAD estimation procedure has failed in certain empirical applications due to the restrictive nature of the ‘full rank’ condition it requires. This condition can be especially problematic when the data are heavily censored. In this paper we introduce estimation procedures for heteroskedastic censored linear regression models with a much weaker identification restriction than that required for the LCAD, and which are flexible enough to allow for various degrees of censoring. The new estimators are shown to have desirable asymptotic properties and perform well in small-scale simulation studies, and can thus be considered as viable alternatives for estimating censored regression models, especially for applications in which the CLAD fails.

Subfields: Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/773bc3abdde17fa4858ddff08513de0784c084c8

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In Statistics and Probability

Citations in the corpus

Two-step estimation of semiparametric censored regression models (2001, background): “The second result for the local linear estimator has been proved in Lemma 2 in Chen and Khan (2000).”
Nonparametric Identification and Estimation of a Censored Location-Scale Regression Model (2005, methodology): “17) follows from the same arguments used in lemma 2 of Chen and Khan (2000). The only difference is in that lemma, the smoothness and bandwidth conditions implied that the bias term was op(n−1/2), whereas in this case, using Assumptions A6 and A7.”
Market Imperfections and Land Productivity in the Ethiopian Highlands (2008, background): “It is considered a desirable alternative due to its robustness to conditional heteroskedasticity and distributional misspecification of the error term (Chen and Khan 2000).”
Censored Data and Truncated Distributions (2005, methodology): “The authors suggest substituting Powell’s consistent estimator for β0, then using a bootstrapping procedure to sharpen the estimator of β. Chen and Khan (2000) further extend Powell’s approach to allow for unspecified heteroscedasticity.”
Land Redistribution, Tenure Insecurity, and Intensity of Production: A Study of Farm Households in Southern Ethiopia (2002, unknown): “It provides consistent parameter estimates and is considered a desirable alternative because of its robustness to conditional heteroskedasticity and distributional misspecification of the error term (Chen and Khan 2000).”