CONJUGATE BAYESIAN PANEL DATA MODEL

The main thrust of the paper is the description of techniques devoted perform Bayesian inference based on Markov Chain Monte Carlo. This paper investigates panel data model which has fixed and random effects as well as the experimental error term. Then, a Bayesian approach based on conjugate prior is employed to make inferences on the model coefficients. We investigate the posterior density and identify the analytic form of the Bayes factor.