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Inference on the long-memory properties of time series with non-stationary volatility

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  • Demetrescu, Matei
  • Sibbertsen, Philipp

Abstract

Time-varying volatility is often present in time series data and can have adverse effects when inferring about the persistence properties of examined series. This note analyzes the effects of such nonstationarity on periodogram-based inference for the fractional integration parameter. Based on asymptotic arguments and Monte Carlo simulations, we show that the log-periodogram regression estimator remains consistent, but has asymptotic distribution whose variance depends on the variation of the volatility of the series.

Suggested Citation

  • Demetrescu, Matei & Sibbertsen, Philipp, 2016. "Inference on the long-memory properties of time series with non-stationary volatility," Economics Letters, Elsevier, vol. 144(C), pages 80-84.
  • Handle: RePEc:eee:ecolet:v:144:y:2016:i:c:p:80-84
    DOI: 10.1016/j.econlet.2016.04.034
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    References listed on IDEAS

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    1. Cavaliere, Giuseppe & Nielsen, Morten Ørregaard & Taylor, A.M. Robert, 2015. "Bootstrap score tests for fractional integration in heteroskedastic ARFIMA models, with an application to price dynamics in commodity spot and futures markets," Journal of Econometrics, Elsevier, vol. 187(2), pages 557-579.
    2. Cavaliere, Giuseppe & Rahbek, Anders & Taylor, A.M. Robert, 2010. "Testing for co-integration in vector autoregressions with non-stationary volatility," Journal of Econometrics, Elsevier, vol. 158(1), pages 7-24, September.
    3. Clifford M. Hurvich & Rohit Deo & Julia Brodsky, 1998. "The mean squared error of Geweke and Porter‐Hudak's estimator of the memory parameter of a long‐memory time series," Journal of Time Series Analysis, Wiley Blackwell, vol. 19(1), pages 19-46, January.
    4. Giuseppe Cavaliere & A. M. Robert Taylor, 2008. "Time‐Transformed Unit Root Tests for Models with Non‐Stationary Volatility," Journal of Time Series Analysis, Wiley Blackwell, vol. 29(2), pages 300-330, March.
    5. Velasco, Carlos, 2000. "Non-Gaussian Log-Periodogram Regression," Econometric Theory, Cambridge University Press, vol. 16(1), pages 44-79, February.
    6. Cavaliere, Giuseppe & Taylor, A.M. Robert, 2005. "Stationarity Tests Under Time-Varying Second Moments," Econometric Theory, Cambridge University Press, vol. 21(6), pages 1112-1129, December.
    7. Kew, Hsein & Harris, David, 2009. "Heteroskedasticity-Robust Testing For A Fractional Unit Root," Econometric Theory, Cambridge University Press, vol. 25(6), pages 1734-1753, December.
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    Cited by:

    1. Hanck, Christoph & Demetrescu, Matei & Kruse, Robinson, 2015. "Fixed-b Asymptotics for t-Statistics in the Presence of Time-Varying Volatility," VfS Annual Conference 2015 (Muenster): Economic Development - Theory and Policy 112916, Verein für Socialpolitik / German Economic Association.
    2. Matei Demetrescu & Christoph Hanck & Robinson Kruse, 2016. "Fixed-b Inference in the Presence of Time-Varying Volatility," CREATES Research Papers 2016-01, Department of Economics and Business Economics, Aarhus University.
    3. Eroğlu, Burak Alparslan & Yiğit, Taner, 2016. "A nonparametric unit root test under nonstationary volatility," Economics Letters, Elsevier, vol. 140(C), pages 6-10.

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    More about this item

    Keywords

    Time-varying variance; Heteroskedasticity; Persistence; Fractional integration; Modulated process;
    All these keywords.

    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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