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Testing for causality in variance in the presence of breaks

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  • van Dijk, Dick
  • Osborn, Denise R.
  • Sensier, Marianne

Abstract

We examine the size properties of tests for causality in variance in the presence of structural breaks in volatility. Extensive Monte Carlo simulations demonstrate that these tests suffer from severe size distortions when such breaks are not taken into account. Pre-testing the series for structural changes in volatility is shown to largely remedy the problem.
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Suggested Citation

  • van Dijk, Dick & Osborn, Denise R. & Sensier, Marianne, 2005. "Testing for causality in variance in the presence of breaks," Economics Letters, Elsevier, vol. 89(2), pages 193-199, November.
  • Handle: RePEc:eee:ecolet:v:89:y:2005:i:2:p:193-199
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    References listed on IDEAS

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    1. Cheung, Yin-Wong & Ng, Lilian K., 1996. "A causality-in-variance test and its application to financial market prices," Journal of Econometrics, Elsevier, vol. 72(1-2), pages 33-48.
    2. Marianne Sensier & Dick van Dijk, 2004. "Testing for Volatility Changes in U.S. Macroeconomic Time Series," The Review of Economics and Statistics, MIT Press, vol. 86(3), pages 833-839, August.
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    7. Pantelidis, Theologos & Pittis, Nikitas, 2004. "Testing for Granger causality in variance in the presence of causality in mean," Economics Letters, Elsevier, vol. 85(2), pages 201-207, November.
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    More about this item

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes

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