An efficiency Bayesian unit root test in Unobserved-ARCH models |
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Authors: | Fazlolah Lak Mahmood Afshari |
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Affiliation: | Department of Statistics, Persian Gulf University, Boushehr, Iran |
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Abstract: | This paper investigates the new prior distribution on the Unobserved-Autoregressive Conditional Heteroscedasticity (ARCH) unit root test. Monte Carlo simulations show that the sample size is seriously effective in efficiency of Bayesian test. To improve the performance of Bayesian test for unit root, we propose a new Bayesian test that is robust in the presence of stationary and nonstationary Unobserved-ARCH. The finite sample property of the proposed test statistic is evaluated using Monte Carlo studies. Applying the developed method, we test the policy of daily exchange rate of the German Marc with respect to the Greek Drachma. |
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Keywords: | Bayes factor Gibbs sampling Monte Carlo Markov Chain Unit root Unobserved-ARCH models |
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