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The joint spillover index

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  • Lastrapes, William D.
  • Wiesen, Thomas F.P.

Abstract

We propose an alternative measure of system-wide connectedness to the popular generalized spillover index, based on generalized forecast error variance decompositions, of Diebold and Yilmaz (2012, 2014). Our measure relies on joint conditional forecasts to decompose variance, as opposed to the popular method's reliance on single-variable conditioning sets, and is a more precise measure of aggregate spillovers. We show in an application to US industry sector stock returns that the difference between the two measures can be substantial.

Suggested Citation

  • Lastrapes, William D. & Wiesen, Thomas F.P., 2021. "The joint spillover index," Economic Modelling, Elsevier, vol. 94(C), pages 681-691.
    • Handle: RePEc:eee:ecmode:v:94:y:2021:i:c:p:681-691
    DOI: 10.1016/j.econmod.2020.02.010
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    References listed on IDEAS

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    More about this item

    Keywords

    Connectedness; Industry sectors; Market integration; Variance decomposition;
    All these keywords.

    JEL classification:

    • C4 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics
    • 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
    • G1 - Financial Economics - - General Financial Markets

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