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<p>Although the literature has made substantial progress in measuring financial spillovers, the time‑varying behavior of inward spillover exposure at the bank level remains underexplored. This study examines whether inward spillover exposure for major North American banks, defined as the extent to which a bank is affected by shocks originating elsewhere in the banking system, varies systematically with domestic macro-financial conditions, global risk sentiment, and evolving network position. Stock market data cover 2002–2024, while the spillover and centrality series used in estimation run from 2005 to 2024. Using a two-way fixed-effects framework, the paper shows that spillover exposure is strongly persistent and positively associated with network centrality in the preferred specification. Evidence on global risk sentiment is supportive, but it comes primarily from benchmark and machine learning diagnostics. The findings position inward spillover exposure as a useful market-implied indicator for systemic risk monitoring.</p>

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Spillover exposure in North American banks: persistence, macroeconomic conditions, and network structure

  • 期刊论文

  • 发表日期：

    2026年4月20日

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  • Adedayo Ogunsanya

摘要

Although the literature has made substantial progress in measuring financial spillovers, the time‑varying behavior of inward spillover exposure at the bank level remains underexplored. This study examines whether inward spillover exposure for major North American banks, defined as the extent to which a bank is affected by shocks originating elsewhere in the banking system, varies systematically with domestic macro-financial conditions, global risk sentiment, and evolving network position. Stock market data cover 2002–2024, while the spillover and centrality series used in estimation run from 2005 to 2024. Using a two-way fixed-effects framework, the paper shows that spillover exposure is strongly persistent and positively associated with network centrality in the preferred specification. Evidence on global risk sentiment is supportive, but it comes primarily from benchmark and machine learning diagnostics. The findings position inward spillover exposure as a useful market-implied indicator for systemic risk monitoring.