A Bayesian Analysis of Unit Roots in Panel Data Models with Cross-Sectional Dependence
14 Pages Posted: 29 Jan 2009
Date Written: January 29, 2009
In this paper a Bayesian approach to unit root testing for panel data models is proposed based on the comparison of stationary autoregressive models with and without individual determinist trends, with their counterpart models with unit autoregressive roots. This is done under cross-sectional dependence among the units of the panel. Simulation experiments are conducted with the aim to assess the performance of the suggested inferential procedure, as well as to investigate if the Bayesian model comparison approach can distinguish unit root models from stationary autoregressive models under or without cross-section dependence. The approach is applied to real GDP data for a panel of G7.
Keywords: Autoregressive models, Bayesian inference, Cross-sectional dependence, Model comparison, Panel data, Unit root testing
JEL Classification: C11, C22, G10
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