This article studies the problem of joint selection of the state dimension and lag order for a class of Markov-switching vector autoregressive models, in which all parameters are presumed to be regime-dependent. To this end, three complexity-penalized criteria are considered, and a new criterion is derived by minimizing the Kullback–Leibler divergence. The efficacy of the procedure is evaluated by means of Monte Carlo experiments. We illustrate the usefulness of the joint model selection procedure with empirical applications to the modeling of business cycles in the USA and Australia.

中文翻译：

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联合确定马尔可夫切换向量自回归模型的状态维数和滞后阶数

本文研究了一类马尔可夫切换向量自回归模型的状态维数和滞后阶数的联合选择问题，其中所有参数都被假定为状态相关。为此，考虑了三个复杂性惩罚标准，并通过最小化 Kullback-Leibler 散度导出了一个新标准。该程序的功效通过蒙特卡罗实验进行评估。我们通过实证应用来说明联合模型选择程序对美国和澳大利亚商业周期建模的有用性。