Gög Ebakan Kemal Çag Lar, Eroglu Burak Alparslan
Cancer Early Detection Advanced Research Center, Knight Cancer Institute, Oregon Health and Science University, Portland, USA.
Knight Cancer Institute, Oregon Health and Science University, Portland, USA.
Comput Stat. 2022;37(5):2581-2636. doi: 10.1007/s00180-022-01211-w. Epub 2022 Mar 7.
This paper presents a new non-parametric seasonal unit root testing framework that is robust to periodic non-stationary volatility in innovation variance by making an extension to the fractional seasonal variance ratio unit root tests of Eroğlu et al. (Econ Lett 167:75-80, 2018). The setup allows for both periodic heteroskedasticity structure of Burridge and Taylar (J Econ 104(1):91-117, 2001) and non-stationary volatility structure of Cavaliere and Taylor (Econ Theory 24(1):43-71, 2008). We show that the limiting null distributions of the variance ratio tests depend on nuisance parameters derived from the underlying volatility process. Monte Carlo simulations show that the standard variance ratio tests can be substantially oversized in the presence of such effects. Consequently, we propose wild bootstrap implementations of the variance ratio tests. Wild bootstrap resampling schemes are shown to deliver asymptotically pivotal inference. The simulation evidence depicts that the proposed bootstrap tests perform well in practice and essentially correct the size problems observed in the standard fractional seasonal variance ratio tests, even under extreme patterns of heteroskedasticity.
The online version contains supplementary material available at 10.1007/s00180-022-01211-w.
本文提出了一种新的非参数季节性单位根检验框架，该框架通过扩展埃罗卢等人（《经济学通讯》167:75 - 80，2018年）的分数季节性方差比单位根检验，对创新方差中的周期性非平稳波动具有稳健性。该设置允许同时存在伯里奇和泰勒（《经济学杂志》104(1):91 - 117，2001年）的周期性异方差结构以及卡瓦列雷和泰勒（《经济理论》24(1):43 - 71，2008年）的非平稳波动结构。我们表明方差比检验的极限零分布取决于从潜在波动过程中导出的干扰参数。蒙特卡罗模拟表明，在存在此类效应的情况下，标准方差比检验可能会出现严重的规模过大问题。因此，我们提出了方差比检验的野生自举实现方法。野生自举重采样方案被证明能提供渐近枢轴推断。模拟证据表明，所提出的自举检验在实际中表现良好，并且即使在异方差的极端模式下，也能基本纠正标准分数季节性方差比检验中观察到的规模问题。
在线版本包含可在10.1007/s00180 - 022 - 01211 - w获取的补充材料。
