Testing for mean reversion in heteroskedastic data based on Gibbs-sampling-augmented randomization

Privious work reported that heteroskedasticity did not affect the sampling distribution of the variance ratio, or had assumed that the investigator know a priori the pattern of heteroskedasticity. This paper uses the Gibbs sampling approach in the context of a three state Markov-switching model to show heteroskedasticity affects inference and suggest two strategies for valid inference.

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