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A Comparison of Semiparametric Tests for Fractional Cointegration

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  • Leschinski, Christian
  • Voges, Michelle
  • Sibbertsen, Philipp

Abstract

There are various competing procedures to determine whether fractional cointegration is present in a multivariate time series, but no standard approach has emerged. We provide a synthesis of this literature and conduct a detailed comparative Monte Carlo study to guide empirical researchers in their choice of appropriate methodologies. Special attention is paid on empirically relevant issues such as assumptions about the form of the underlying process and the ability of the procedures to distinguish between short-run correlation and long-run equilibria. It is found that several approaches are severely oversized in presence of correlated short-run components and that the methods show different performance in terms of power when applied to common-component models instead of triangular systems.

Suggested Citation

  • Leschinski, Christian & Voges, Michelle & Sibbertsen, Philipp, 2019. "A Comparison of Semiparametric Tests for Fractional Cointegration," Hannover Economic Papers (HEP) dp-651, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
  • Handle: RePEc:han:dpaper:dp-651
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    References listed on IDEAS

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    Cited by:

    1. Christian Leschinski & Michelle Voges & Philipp Sibbertsen, 2021. "Integration and Disintegration of EMU Government Bond Markets," Econometrics, MDPI, vol. 9(1), pages 1-17, March.
    2. Theoplasti Kolaiti & Mwasi Mboya & Philipp Sibbertsen, 2020. "Volatility Transmission across Financial Markets: A Semiparametric Analysis," JRFM, MDPI, vol. 13(8), pages 1-13, July.
    3. Dräger, Lena & Kolaiti, Theoplasti & Sibbertsen, Philipp, 2020. "Measuring Macroeconomic Convergence and Divergence within EMU Using Long Memory," Hannover Economic Papers (HEP) dp-675, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät, revised Feb 2021.

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    More about this item

    Keywords

    Long Memory; Fractional Cointegration; Semiparametric Estimation and Testing;
    All these keywords.

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models

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