A Monte Carlo comparison of estimators for censored regression models

DOI10.1016/0304-4076(84)90079-4zbMath0527.62100OpenAlexW2073209353MaRDI QIDQ595313

Harry J. Paarsch

Publication date: 1984

Published in: Journal of Econometrics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/0304-4076(84)90079-4

zbMATH Keywords

tablesrobust estimatorsordinary least squarestwo-step methodcensored regression modelsleast absolute deviation estimatorsMonte Carlo comparison of estimatorsTobit maximum likelihood estimatortruncated regression models

Mathematics Subject Classification ID

Applications of statistics to economics (62P20) Robustness and adaptive procedures (parametric inference) (62F35) Monte Carlo methods (65C05)

Related Items (26)

Estimation of sample selection bias models by the maximum likelihood estimator and Heckman's two-step estimator ⋮ Non-parametric maximum likelihood estimation of censored regression models ⋮ A comparison of semi-parametric and partially adaptive estimators of the censored regression model with possibly skewed and leptokurtic error distributions ⋮ Recent contributions to censored regression models ⋮ Estimation and inference with censored and ordered multinomial response data ⋮ Asymptotic misspecification biases for heckman's two step estimator ⋮ Partially Adaptive Estimation of the Censored Regression Model ⋮ On the choice between sample selection and two-part models ⋮ Birnbaum–Saunders sample selection model ⋮ When does Heckman's two-step procedure for censored data work and when does it not? ⋮ Bounded-influence estimators for the Tobit model ⋮ Bias-corrected quantile regression estimation of censored regression models ⋮ Estimation of sample selection bias models ⋮ A genetic method of LAD estimation for models with censored data ⋮ Statistical models for exposure-biomarker relationships with measurement error and censoring ⋮ Two-step estimation of semiparametric censored regression models ⋮ SIZE CHARACTERISTICS OF TESTS FOR SAMPLE SELECTION BIAS: A MONTE CARLO COMPARISON AND EMPIRICAL EXAMPLE ⋮ Software for the computation of Tobit model estimates ⋮ A Mixture Model for Occupational Exposure Mean Testing with a Limit of Detection ⋮ Discrete factor approximations in simultaneous equation models: Estimating the impact of a dummy endogenous variable on a continuous outcome ⋮ Distributional specification tests against semiparametric alternatives ⋮ Tobit models: A survey ⋮ Estimation of Censored Quantile Regression for Panel Data With Fixed Effects ⋮ Bivariate symmetric Heckman models and their characterization ⋮ A note on the estimation of models with sample-selection biases ⋮ Heteroscedasticity and Distributional Assumptions in the Censored Regression Model

Cites Work

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• Estimation of Relationships for Limited Dependent Variables
• Tobit models: A survey
• Estimation in truncated samples when there is heteroscedasticity
• An Investigation of the Robustness of the Tobit Estimator to Non-Normality
• Sample Selection Bias as a Specification Error
• Regression Analysis when the Dependent Variable Is Truncated Normal

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