On Joint Determination of the Number of States and the Number of Variables in Markov-Switching Models: A Monte Carlo Study
نویسندگان
چکیده
In this paper we examine the performance of two newly developed procedures that jointly select the number of states and variables in Markov-switching models by means of Monte Carlo simulations. They are Smith, Naik and Tsai (2006) and Psaradakis and Spagnolo (2006), respectively. The former develops Markov switching criterion (MSC) designed specifically for Markov-switching models, while the latter recommends the use of standard complexitypenalised information criteria (BIC, HQC, & AIC). The Monte Carlo evidence shows that BIC outperforms MSC while MSC and HQC are preferable over AIC. URL: http://mc.manuscriptcentral.com/lssp E-mail: [email protected] Communications in Statistics Simulation and Computation
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ورودعنوان ژورنال:
- Communications in Statistics - Simulation and Computation
دوره 38 شماره
صفحات -
تاریخ انتشار 2009