On Causal Networks of Financial Firms: Structural Identification via Non-parametric Heteroskedasticity
Staff Working Papers from Bank of Canada
We investigate the causal structure of financial systems by accounting for contemporaneous relationships. To identify structural parameters, we introduce a novel non-parametric approach that exploits the fact that most financial data empirically exhibit heteroskedasticity. The identification works locally and, thus, allows structural matrices to vary smoothly with time. With this causality in hand, we derive a new measure for systemic relevance. An application on volatility spillovers in the US financial market demonstrates the importance of structural parameters in spillover analyses. Finally, we highlight that the COVID-19 period is mostly an aggregate crisis, with financial firms’ spillovers edging slightly higher.
Keywords: Econometric and statistical methods; Financial markets; Financial stability (search for similar items in EconPapers)
JEL-codes: C32 C58 L14 (search for similar items in EconPapers)
Pages: 43 pages
New Economics Papers: this item is included in nep-cfn, nep-ecm, nep-net and nep-ore
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Persistent link: https://EconPapers.repec.org/RePEc:bca:bocawp:20-42
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