A family of nonparametric unit root tests for processes driven by infinite variance innovations

IF 0.7 4区 经济学 Q3 ECONOMICS
K. C. Gogebakan
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引用次数: 0

Abstract

Abstract This paper presents extensions to the family of nonparametric fractional variance ratio (FVR) unit root tests of Nielsen (2009. “A Powerful Test of the Autoregressive Unit Root Hypothesis Based on a Tuning Parameter Free Statistic.” Econometric Theory 25: 1515–44) under heavy tailed (infinite variance) innovations. In this regard, we first develop the asymptotic theory for these FVR tests under this setup. We show that the limiting distributions of the tests are free of serial correlation nuisance parameters, but depend on the tail index of the infinite variance process. Then, we compare the finite sample size and power performance of our FVR unit root tests with the well-known parametric ADF test under the impact of the heavy tailed shocks. Simulations demonstrate that under heavy tailed innovations, the nonparametric FVR tests have desirable size and power properties.
无穷方差创新驱动过程的一类非参数单位根检验
摘要本文对Nielsen(2009)的非参数分数方差比(FVR)单位根检验族进行了扩展。“基于无调整参数统计的自回归单位根假说的有力检验”,重尾(无限方差)创新下的计量经济学理论25:1515-44。在这方面,我们首先发展了在这种设置下这些FVR检验的渐近理论。我们证明了检验的极限分布不受序列相关干扰参数的影响,但取决于无穷方差过程的尾指数。然后,我们将我们的FVR单位根检验的有限样本量和功率性能与众所周知的参数ADF检验在重尾冲击的影响下进行了比较。仿真表明,在重尾创新下,非参数FVR检验具有理想的大小和幂性质。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
1.40
自引率
12.50%
发文量
34
期刊介绍: Studies in Nonlinear Dynamics & Econometrics (SNDE) recognizes that advances in statistics and dynamical systems theory may increase our understanding of economic and financial markets. The journal seeks both theoretical and applied papers that characterize and motivate nonlinear phenomena. Researchers are required to assist replication of empirical results by providing copies of data and programs online. Algorithms and rapid communications are also published.
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