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Markov-switching models with endogenous explanatory variables II: A two-step MLE procedure

  • Kim, Chang-Jin

This paper proposes a two-step maximum likelihood estimation (MLE) procedure to deal with the problem of endogeneity in Markov-switching regression models. A joint estimation procedure provides us with an asymptotically most efficient estimator, but it is not always feasible, due to the 'curse of dimensionality' in the matrix of transition probabilities. A two-step estimation procedure, which ignores potential correlation between the latent state variables, suffers less from the 'curse of dimensionality', and it provides a reasonable alternative to the joint estimation procedure. In addition, our Monte Carlo experiments show that the two-step estimation procedure can be more efficient than the joint estimation procedure in finite samples, when there is zero or low correlation between the latent state variables.

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Article provided by Elsevier in its journal Journal of Econometrics.

Volume (Year): 148 (2009)
Issue (Month): 1 (January)
Pages: 46-55

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Handle: RePEc:eee:econom:v:148:y:2009:i:1:p:46-55
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  1. John Y. Campbell & N. Gregory Mankiw, 1989. "Consumption, Income and Interest Rates: Reinterpreting the Time Series Evidence," NBER Chapters, in: NBER Macroeconomics Annual 1989, Volume 4, pages 185-246 National Bureau of Economic Research, Inc.
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  10. Christopher A. Sims & Daniel F. Waggoner & Tao Zha, 2006. "Methods for inference in large multiple-equation Markov-switching models," FRB Atlanta Working Paper 2006-22, Federal Reserve Bank of Atlanta.
  11. Campbell, John Y. & Mankiw, N. Gregory, 1991. "The response of consumption to income : A cross-country investigation," European Economic Review, Elsevier, vol. 35(4), pages 723-756, May.
  12. Kim, C.-J.Chang-Jin, 2004. "Markov-switching models with endogenous explanatory variables," Journal of Econometrics, Elsevier, vol. 122(1), pages 127-136, September.
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