Choosing information variables for transition probabilities in a time-varying transition probability Markov switching model
AbstractThis paper discusses a practical estimation issue for time-varying transition probability (TVTP) Markov switching models. Time-varying transition probabilities allow researchers to capture important economic behavior that may be missed using constant (or fixed) transition probabilities. Despite its use, Hamilton’s (1989) filtering method for estimating fixed transition probability Markov switching models may not apply to TVTP models. This paper provides a set of sufficient conditions to justify the use of Hamilton’s method for TVTP models. In general, the information variables that govern time-variation in the transition probabilities must be conditionally uncorrelated with the state of the Markov process.
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Bibliographic InfoPaper provided by Federal Reserve Bank of Kansas City in its series Research Working Paper with number 98-09.
Date of creation: 1998
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