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Time-Transformed Unit Root Tests for Models with Non-Stationary Volatility

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  • Giuseppe Cavaliere
  • A. M. Robert Taylor

Abstract

Conventional unit root tests are known to be unreliable in the presence of permanent volatility shifts. In this paper, we propose a new approach to unit root testing which is valid in the presence of a quite general class of permanent variance changes which includes single and multiple (abrupt and smooth transition) volatility change processes as special cases. The new tests are based on a time transformation of the series of interest which automatically corrects their form for the presence of non-stationary volatility without the need to specify any parametric model for the volatility process. Despite their generality, the new tests perform well even in small samples. We also propose a class of tests for the null hypothesis of stationary volatility in (near-) integrated time-series processes. Copyright 2007 The Authors

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File URL: http://www.blackwell-synergy.com/doi/abs/10.1111/j.1467-9892.2007.00557.x
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Bibliographic Info

Article provided by Wiley Blackwell in its journal Journal of Time Series Analysis.

Volume (Year): 29 (2008)
Issue (Month): 2 (03)
Pages: 300-330
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Handle: RePEc:bla:jtsera:v:29:y:2008:i:2:p:300-330

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Cited by:
  1. Giuseppe Cavaliere & Anders Rahbek & A. M. Robert Taylor, 2007. "Testing for co-integration in vector autoregressions with non-stationary volatility," Discussion Papers 07/02, University of Nottingham, Granger Centre for Time Series Econometrics.
  2. Brendan K. Beare, 2008. "Unit Root Testing with Unstable Volatility," Economics Papers 2008-W06, Economics Group, Nuffield College, University of Oxford.
  3. Cavaliere, Giuseppe & Rahbek, Anders & Taylor, Robert, 2010. "Determination of the Number of Common Stochastic Trends Under Conditional Heteroskedasticity/Determinación del número de tendencias estocásticas comunes bajo heteroscedasticidad condicional," Estudios de Economía Aplicada, Estudios de Economía Aplicada, vol. 28, pages 519-552, Diciembre.

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