Methods for inference in large multiple-equation Markov-switching models

作者：Sims Christopher A; Waggoner Daniel F; Zha Tao^*

来源：Journal of Econometrics, 2008, 146(2): 255-274.

DOI：10.1016/j.jeconom.2008.08.023

• Density overlap
• New MHM
• Incremental and discontinuous changes
• Composite Markov process
• Integrated-out likelihood

Inference for multiple-equation Markov-chain models raises a number of difficulties that are unlikely to appear in smaller models. Our framework allows for many regimes in the transition matrix, without letting the number of free parameters grow as the square as the number of regimes, but also without losing a convenient form for the posterior distribution. Calculation of marginal data densities is difficult in these high-dimensional models. This paper gives methods to overcome these difficulties, and explains why existing methods are unreliable. It makes suggestions for maximizing posterior density and initiating MCMC simulations that provide robustness against the complex likelihood shape.

• 出版日期2008-10