Non‐parametric testing for seasonally and periodically integrated processes
Non‐parametric testing for seasonally and periodically integrated processes
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季节性和定期集成过程的非参数测试
DOI：
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发表时间：
2012
期刊：
影响因子：
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通讯作者：
D. Osborn
中科院分区：
文献类型：
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作者：
Tomás del Barrio Castro;D. Osborn
本文给出了A.M.R. Taylor（2005，Journal of Econometrics 124，33），将这些检验应用于周期性整合过程[PI（1）]。与过程是季节性整合的情况相反[SI（1）]，PI（1）情况下的所有检验统计量都由单一随机趋势驱动，因此遵循Breitung（2002，Journal of Econometrics 108，343）为原始（非季节性）方差比检验获得的分布。Breitung（2002 Journal of Econometrics 108，343）的多元非参数协整检验也被用来区分PI和SI过程。蒙特卡洛分析表明，这些结果适用于有限样本的SI和PI过程和实证应用调查季节性未经调整的季度美国工业生产序列。
This article obtains the asymptotic distributions of the seasonal variance ratio tests proposed by A.M.R. Taylor (2005,Journal of Econometrics 124, 33) when these tests are applied to a periodically integrated process [PI(1)]. In contrast to the situation where the process is seasonally integrated [SI(1)], all test statistics in the PI(1) case are driven by a single stochastic trend and hence follow the distribution obtained by Breitung (2002, Journal of Econometrics 108, 343) for the original (non‐seasonal) variance ratio test. The multivariate non‐parametric cointegration test of Breitung (2002 Journal of Econometrics 108, 343) is also investigated to distinguish between PI and SI processes. A Monte Carlo analysis shows how these results apply in finite samples for both SI and PI processes and an empirical application investigates seasonally unadjusted quarterly US industrial production series.