基于残差的非参数方差比无协整检验

IF 1.2 4区 数学 Q3 MATHEMATICS, INTERDISCIPLINARY APPLICATIONS
Karsten Reichold
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引用次数: 0

摘要

有文献明确指出,局部渐近幂特性是有限样本中基于残差的无协整检验性能的有用指标。然而,本文得出了相反的结论。我们特别指出,Breitung(2002 年,《计量经济学杂志》108 期,343-363 页)应用于回归残差的非参数方差比单位根检验可作为无协整检验,但从局部渐近功率的角度来看,该检验不如其竞争对手。尽管如此,在有限样本中,方差比检验具有良好的规模特性、竞争能力和无调整参数的便利性。总的来说,我们发现误差过程的短期动态对基于残差的无协整检验在有限样本中的性能的不利影响,要比影响检验局部渐近功率的唯一干扰参数的变化大得多。这些结果为实践者敲响了警钟,也为未来的研究指明了方向。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

A residual-based nonparametric variance ratio no-cointegration test

A residual-based nonparametric variance ratio no-cointegration test

It is prominently stated in the literature that local asymptotic power properties serve as a useful indicator for the performance of residual-based no-cointegration tests in finite samples. However, this article comes to an opposing conclusion. In particular, we show that Breitung's (2002, Journal of Econometrics 108, 343–363) nonparameteric variance ratio unit root test applied to regression residuals serves as a no-cointegration test but is inferior to its competitors from a local asymptotic power perspective. Nevertheless, in finite samples, the variance ratio test has good size properties, competitive power, and the convenience of being tuning parameter free. In general, we find that short-run dynamics in the error process can have considerably larger detrimental effects on the performance of residual-based no-cointegration tests in finite samples than changes in the only nuisance parameter affecting local asymptotic power of the tests. The results serve as a warning for practitioners and lead to interesting directions for future research.

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来源期刊
Journal of Time Series Analysis
Journal of Time Series Analysis 数学-数学跨学科应用
CiteScore
2.00
自引率
0.00%
发文量
39
审稿时长
6-12 weeks
期刊介绍: During the last 30 years Time Series Analysis has become one of the most important and widely used branches of Mathematical Statistics. Its fields of application range from neurophysiology to astrophysics and it covers such well-known areas as economic forecasting, study of biological data, control systems, signal processing and communications and vibrations engineering. The Journal of Time Series Analysis started in 1980, has since become the leading journal in its field, publishing papers on both fundamental theory and applications, as well as review papers dealing with recent advances in major areas of the subject and short communications on theoretical developments. The editorial board consists of many of the world''s leading experts in Time Series Analysis.
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