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The topological structure of panel variance decomposition networks

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  • Celani, Alessandro
  • Cerchiello, Paola
  • Pagnottoni, Paolo

Abstract

In this paper we provide a framework to study the network topology of generalized forecast error variance decomposition (GFEVD) derived from multi-country, multi-variable time series models. Our dynamic variance decomposition network is based on a Bayesian Global Vector Autoregressive (GVAR) model, a suitable macroeconometric method to consider simultaneous multi-level interdependencies across variables. We demonstrate the usefulness of our methodology to analyze the network structure of shock propagation in longitudinal time series and, in particular: (a) the shortest paths of contagion; (b) the clusters of shock transmission; (c) the role of nodes in the risk transmission channels. We illustrate our method through an empirical application to a set of 12 European countries’ Industrial Production, Retail Trade and Economic Sentiment indices over the period 01/2000–11/2021.

Suggested Citation

  • Celani, Alessandro & Cerchiello, Paola & Pagnottoni, Paolo, 2024. "The topological structure of panel variance decomposition networks," Journal of Financial Stability, Elsevier, vol. 71(C).
    • Handle: RePEc:eee:finsta:v:71:y:2024:i:c:s157230892400007x
    DOI: 10.1016/j.jfs.2024.101222
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    More about this item

    Keywords

    Crisis; Global VAR; Network theory; Systemic risk; Variance decomposition;
    All these keywords.

    JEL classification:

    • C40 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - General
    • E44 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Financial Markets and the Macroeconomy
    • G01 - Financial Economics - - General - - - Financial Crises

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