Robust and efficient specification tests in Markov-switching autoregressive models
Robust and efficient specification tests in Markov-switching autoregressive models
复制标题
马尔可夫切换自回归模型中稳健且高效的规范测试
DOI：
10.1007/s11203-022-09277-5
复制
发表时间：
2022
影响因子：
0.8
通讯作者：
Masaru Chiba
中科院分区：
文献类型：
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作者：
Keiji Nagai;Yoshihiko Nishiyama;Kohtaro Hitomi;and Junfan Tao;Masaru Chiba
本研究开发了两种适用于马尔可夫切换自回归模型的稳健检验统计量。检验统计量可以通过给定观测值来自特定状态的“平滑”概率的总和函数来构建，并且不需要估计附加参数。蒙特卡罗实验表明，该测试具有良好的有限样本量和功效特性。这些测试用于调查美国实际国民生产总值增长的波动。
This study develops two types of robust test statistics applicable to Markov-switching autoregressive models. The test statistics can be constructed by sum functionals of the “smoothed” probabilities that a given observation came from a particular regime and do not require the estimation of additional parameters. Monte Carlo experiments show that the tests have good finite-sample size and power properties. The tests are applied to investigate the fluctuations in real GNP growth in the U.S.