Baltagi, Badi H. and Bresson, Georges and Chaturvedi, Anoop and Lacroix, Guy (2014): Robust linear static panel data models using epsiloncontamination.

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Abstract
The paper develops a general Bayesian framework for robust linear static panel data models using epsiloncontamination. A twostep approach is employed to derive the conditional type II maximum likelihood (MLII) posterior distribution of the coefficients and individual effects. The MLII posterior densities are weighted averages of the Bayes estimator under a base prior and the datadependent empirical Bayes estimator. Twostage and three stage hierarchy estimators are developed and their finite sample performance is investigated through a series of Monte Carlo experiments. These include standard random effects as well as Mundlaktype, Chamberlaintype and HausmanTaylortype models. The simulation results underscore the relatively good performance of the threestage hierarchy estimator. Within a single theoretical framework, our Bayesian approach encompasses a variety of specifications while conventional methods require separate estimators for each case. We illustrate the performance of our estimator relative to classic panel estimators using data on earnings and crime.
Item Type:  MPRA Paper 

Original Title:  Robust linear static panel data models using epsiloncontamination 
English Title:  Robust linear static panel data models using epsiloncontamination 
Language:  English 
Keywords:  epsiloncontamination, hyper gpriors, type II maximum likelihood posterior density, panel data, robust Bayesian estimator, threestage hierarchy. 
Subjects:  C  Mathematical and Quantitative Methods > C1  Econometric and Statistical Methods and Methodology: General > C11  Bayesian Analysis: General C  Mathematical and Quantitative Methods > C2  Single Equation Models ; Single Variables > C23  Panel Data Models ; Spatiotemporal Models C  Mathematical and Quantitative Methods > C2  Single Equation Models ; Single Variables > C26  Instrumental Variables (IV) Estimation 
Item ID:  59896 
Depositing User:  Professor Georges BRESSON 
Date Deposited:  14 Nov 2014 20:11 
Last Modified:  27 Sep 2019 03:30 
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URI:  https://mpra.ub.unimuenchen.de/id/eprint/59896 