A Monte Carlo comparison of Bayesian testing for cointegration rank

Katsuhiro Sugita

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Monetary Policy and Economic Impact Statistical Methods and Bayesian Inference Markov Chains and Monte Carlo Methods

Abstract

This article considers a Bayesian testing for cointegration rank, using an approach developed by Strachan and van Dijk (2007), that is based on Koop, Leon-Gonzalez, and Strachan (2006). The Bayes factors are calculated for selecting cointegrating rank. We calculate the Bayes factors using two methods - the Schwarz BIC approximation and Chib's (1995) algorithm for calculating the marginal likelihood. We run Monte Carlo simulations to compare the two methods.

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2003Valid Bayesian Estimation of the Cointegrating Error Correction Model 2005BAYESIAN REFERENCE ANALYSIS OF COINTEGRATION 2005Bayesian point estimation of the cointegration space 2007Bayesian model averaging in vector autoregressive processes with an investigation of stability of the US great ratios and risk of a liquidity trap in the USA, UK and Japan

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