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Working Paper 2003-015C

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"Estimation of Markov Regime-Switching Regression Models with Endogenous Switching"
by Chang-Jin Kim, Jeremy M. Piger, and Richard Startz

Following Hamilton (1989), estimation of Markov regime-switching regressions typically relies on the assumption that the latent state variable controlling regime change is exogenous. We relax this assumption and develop a parsimonious model of endogenous Markov regime-switching. Inference via maximum likelihood estimation is possible with relatively minor modifications to existing recursive filters. The model nests the exogenous switching model, yielding straightforward tests for endogeneity. In Monte Carlo experiments, maximum likelihood estimates of the endogenous switching model
parameters were quite accurate, even in the presence of certain model misspecifications. As an application, we extend the volatility feedback model of equity returns given in Turner, Startz and Nelson (1989) to allow for endogenous switching.

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