Heteroscedasticity and Distributional Assumptions in the Censored Regression Model

DOI10.1080/03610918.2013.851217zbMath1328.62486OpenAlexW2078869916MaRDI QIDQ5265828

No author found.

Publication date: 29 July 2015

Published in: Communications in Statistics - Simulation and Computation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/03610918.2013.851217

zbMATH Keywords

censored regressionnonnormalitytobitpartially adaptive estimators

Mathematics Subject Classification ID

Linear inference, regression (62J99)

Cites Work

• Estimation of Relationships for Limited Dependent Variables
• A Monte Carlo comparison of estimators for censored regression models
• Tobit models: A survey
• Least absolute deviations estimation for the censored regression model
• Specification tests for distributional assumptions in the Tobit model
• A generalization of the beta distribution with applications
• A comparison of semi-parametric and partially adaptive estimators of the censored regression model with possibly skewed and leptokurtic error distributions
• Robust estimation based on grouped-adjusted data in censored regression models
• Financial Data and the Skewed Generalized T Distribution
• Symmetrically Trimmed Least Squares Estimation for Tobit Models
• On the Asymptotic Bias of the Ordinary Least Squares Estimator of the Tobit Model
• An Investigation of the Robustness of the Tobit Estimator to Non-Normality
• Sample Selection Bias as a Specification Error
• Autoregressive Conditional Density Estimation
• Regression Analysis when the Dependent Variable Is Truncated Normal
• Unnamed Item
• Unnamed Item