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On Causal Networks of Financial Firms: Structural Identification via Non-parametric Heteroskedasticity

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  • Ruben Hipp

Abstract

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.

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  • Ruben Hipp, 2020. "On Causal Networks of Financial Firms: Structural Identification via Non-parametric Heteroskedasticity," Staff Working Papers 20-42, Bank of Canada.
    • Handle: RePEc:bca:bocawp:20-42
    DOI: 10.34989/swp-2020-42
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    Cited by:

    1. Felix Brunner & Ruben Hipp, 2023. "Estimating large‐dimensional connectedness tables: The great moderation through the lens of sectoral spillovers," Quantitative Economics, Econometric Society, vol. 14(3), pages 1021-1058, July.
    2. Grzegorz Halaj & Ruben Hipp, 2024. "Decomposing Systemic Risk: The Roles of Contagion and Common Exposures," Staff Working Papers 24-19, Bank of Canada.
    3. Marko Mlikota, 2022. "Cross-Sectional Dynamics Under Network Structure: Theory and Macroeconomic Applications," Papers 2211.13610, arXiv.org, revised Sep 2025.
    4. Robin Braun & George Kapetanios & Massimiliano Marcellino, 2025. "Nonparametric Time Varying IV-SVARs: Estimation and Inference," Finance and Economics Discussion Series 2025-004, Board of Governors of the Federal Reserve System (U.S.).
    5. Hałaj, Grzegorz & Hipp, Ruben, 2024. "Decomposing systemic risk: the roles of contagion and common exposures," Working Paper Series 2929, European Central Bank.

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    JEL classification:

    • 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
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • L14 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - Transactional Relationships; Contracts and Reputation

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