On the Long-Run Variance Ratio Test for a Unit Root

Ye Cai () and Mototsugu Shintani
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Ye Cai: Graduate Student, Department of Economics, Vanderbilt University

No 506, Vanderbilt University Department of Economics Working Papers from Vanderbilt University Department of Economics

Abstract: This paper investigates the effects of consistent and inconsistent long-run variance estimation on a unit root test based on the generalization of the von Neumann ratio. The results from the Monte Carlo experiments suggest that the tests based on an inconsistent estimator have less size distortion and more stability of size across different autocorrelation specifications as compared to the tests based on a consistent estimator. This improvement in size property, however, comes at the cost of a loss in power. The finite sample power, as well as the local asymptotic power, of the tests with an inconsistent estimator is shown to be much lower than that of conventional tests. This finding resembles the case of the autocorrelation robust test in the standard regression context. The paper also points out that combining consistent and inconsistent estimators in the long-run variance ratio test for a unit root is one possibility of balancing the size and power.

Keywords: Bandwidth; local asymptotic power; von Neumann ratio (search for similar items in EconPapers)
JEL-codes: C12 C22 (search for similar items in EconPapers)
Date: 2005-03
New Economics Papers: this item is included in nep-ecm and nep-ets
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http://www.accessecon.com/pubs/VUECON/vu05-w06.pdf First version, 2005 (application/pdf)

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Persistent link: https://EconPapers.repec.org/RePEc:van:wpaper:0506

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