Estimation of Markov regime-switching regression models with endogenous switching

被引:117
|
作者
Kim, Chang-Jin [1 ,2 ]
Piger, Jeremy [3 ]
Startz, Richard [1 ]
机构
[1] Univ Washington, Dept Econ, Seattle, WA 98195 USA
[2] Korea Univ, Seoul 136701, South Korea
[3] 1285 Univ Oregon, Dept Econ, Eugene, OR 97403 USA
关键词
endogeneity; regime-switching;
D O I
10.1016/j.jeconom.2007.10.002
中图分类号
F [经济];
学科分类号
02 ;
摘要
Following Hamilton [1989. A new approach to the economic analysis of nonstationary time series and the business cycle. Econometrica 57, 357-384], 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 et al. [1989. A Markov model of heteroskedasticity, risk, and learning in the stock market. Journal of Financial Economics 25, 3-22] to allow for endogenous switching. ((C) 2007 Elsevier B.V. All rights reserved.
引用
收藏
页码:263 / 273
页数:11
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