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Unit root tests under time-varyng variances

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Author Info
Giuseppe Cavaliere

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Abstract

The paper provides a general framework for investigating the effects of permanent changes in the variance of the errors of an autoregressive process on unit root tests. Such a framework — which is based on a novel asymptotic theory for integrated and near integrated processes with heteroskedastic errors — allows to evaluate how the variance dynamics affect the size and the power function of unit root tests. Contrary to previous studies, it is shown that under permanent variance shifts, the conventional critical values can lead both to oversized and undersized tests. The paper concludes by showing that the power function of the unit root tests is affected by non-constant variances as well.

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File URL: http://amsacta.cib.unibo.it/archive/00002421/
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Publisher Info
Paper provided by Department of Statistics, University of Bologna in its series Quaderni di Dipartimento with number 2.

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Date of creation: 2003
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Handle: RePEc:bot:quadip:89

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  1. Giuseppe Cavaliere & Anders Rahbek & A.M.Robert Taylor, 2008. "Testing for Co-integration in Vector Autoregressions with Non-Stationary Volatility," CREATES Research Papers 2008-50, School of Economics and Management, University of Aarhus. [Downloadable!]
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  2. Ke-Li Xu & Peter C.B. Phillips, 2006. "Adaptive Estimation of Autoregressive Models with Time-Varying Variances," Cowles Foundation Discussion Papers 1585R, Cowles Foundation, Yale University, revised Nov 2006. [Downloadable!]
    Other versions:
  3. Xu Cheng & Peter C.B. Phillips, 2008. "Semiparametric Cointegrating Rank Selection," Cowles Foundation Discussion Papers 1658, Cowles Foundation, Yale University. [Downloadable!]
    Other versions:
  4. Brendan K. Beare, 2008. "Unit Root Testing with Unstable Volatility," Economics Papers 2008-W06, Economics Group, Nuffield College, University of Oxford. [Downloadable!]
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