Bayesian Inference for Censored Panel Regression Model

- Journal title : Communications for Statistical Applications and Methods
- Volume 21, Issue 2, 2014, pp.193-200
- Publisher : The Korean Statistical Society
- DOI : 10.5351/CSAM.2014.21.2.193

Title & Authors

Bayesian Inference for Censored Panel Regression Model

Lee, Seung-Chun; Choi, Byongsu;

Lee, Seung-Chun; Choi, Byongsu;

Abstract

It was recognized by some researchers that the disturbance variance in a censored regression model is frequently underestimated by the maximum likelihood method. This underestimation has implications for the estimation of marginal effects and asymptotic standard errors. For instance, the actual coverage probability of the confidence interval based on a maximum likelihood estimate can be significantly smaller than the nominal confidence level; consequently, a Bayesian estimation is considered to overcome this difficulty. The behaviors of the maximum likelihood and Bayesian estimators of disturbance variance are examined in a fixed effects panel regression model with a limited dependent variable, which is known to have the incidental parameter problem. Behavior under random effect assumption is also investigated.

Keywords

Censored panel regression;Gibbs sampling;incidental parameter problem;

Language

English

Cited by

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