Publication Type

Journal Article

Version

publishedVersion

Publication Date

5-2019

Abstract

A new posterior odds analysis is developed to test for a unit root in volatilitydynamics in the context of stochastic volatility models. Our analysis extendsthe Bayesian unit root test of So and Li (1999) in two important ways. First,a mixed informative prior distribution with a random weight is introducedfor the Bayesian unit root testing in volatility. Second, a numerically morestable algorithm is introduced to compute Bayes factor, taking into accountthe special structure of the competing models. It can be shown that theapproach introduced overcomes the problem of the diverging “size” in themarginal likelihood approach by So and Li (1999) and improves the “power”of the unit root test. A simulation study is used to investigate the finite sampleperformance of the improved method and an empirical study implements theproposed method and the unit root hypothesis in volatility is rejected.

Keywords

Bayes factor, Markov chain Monte Carlo, Posterior odds ratio, Stochastic volatility models, Unit root testing

Discipline

Econometrics

Research Areas

Econometrics

Publication

Annals of Economics and Finance

Volume

20

Issue

1

First Page

103

Last Page

122

ISSN

1529-7373

Publisher

Peking Univ. Press

Copyright Owner and License

Authors

Included in

Econometrics Commons

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