Estimating Markov-switching regression models in Stata

Ashish Rajbhandari ()

2015 Stata Conference from Stata Users Group

Abstract: Many datasets are not well characterized by linear autoregressive moving-average (ARMA) models. In this presentation, I will describe the new mswitch command, which implements Markov-switching regression models, which characterize many of these datasets well. Markov-switching regression models allow the time series to switch between unobserved states according to a Markov process. mswitch can estimate the parameters of the Markov-switching dynamic regression (MSDR) model and Markov-switching autoregressive (MSAR) model. This talk outlines the models, discusses the relative advantages of MSDR and MSAR models, and discusses examples of how to intepret mswitch output and its postestimation features.

Date: 2015-08-02
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Persistent link: https://EconPapers.repec.org/RePEc:boc:scon15:24

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