A BAYESIAN INFERENCE OF MULTIPLE STRUCTURAL BREAKS IN MEAN AND ERROR VARIANCE IN PANEL AR (1) MODEL

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Statistics in Transition New Series

Polish Statistical Association

Central Statistical Office of Poland

Subject: Economics , Statistics & Probability

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ISSN: 1234-7655
eISSN: 2450-0291

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VOLUME 19 , ISSUE 1 (March 2018) > List of articles

A BAYESIAN INFERENCE OF MULTIPLE STRUCTURAL BREAKS IN MEAN AND ERROR VARIANCE IN PANEL AR (1) MODEL

Varun Agiwal / Jitendra Kumar / Dahud Kehinde Shangodoyin

Keywords : panel data model, autoregressive model, structural break, MCMC, posterior odds ratio

Citation Information : Statistics in Transition New Series. Volume 19, Issue 1, Pages 7-23, DOI: https://doi.org/10.21307/stattrans-2018-001

License : (CC BY-NC-ND 4.0)

Published Online: 25-May-2018

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ABSTRACT

This paper explores the effect of multiple structural breaks to estimate the parameters and test the unit root hypothesis in panel data time series model under Bayesian perspective. These breaks are present in both mean and error variance at the same time point. We obtain Bayes estimates for different loss function using conditional posterior distribution, which is not coming in a closed form, and this is approximately explained by Gibbs sampling. For hypothesis testing, posterior odds ratio is calculated and solved via Monte Carlo Integration. The proposed methodology is illustrated with numerical examples.

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