The topological structure of panel variance decomposition networks

Alessandro Celani, Paola Cerchiello and Paolo Pagnottoni

Journal of Financial Stability, 2024, vol. 71, issue C

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.

Keywords: Crisis; Global VAR; Network theory; Systemic risk; Variance decomposition (search for similar items in EconPapers)
JEL-codes: C40 E44 G01 (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:finsta:v:71:y:2024:i:c:s157230892400007x

DOI: 10.1016/j.jfs.2024.101222

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