How Does Moral Hazard Impact Critical Market Banking Performance?

Corey Williams

American Business Review2025https://doi.org/10.37625/abr.28.1.103-142article
ABDC B
Weight
0.37

What the paper says

The degree to which financial institutions form expectations of policy intervention despite their own risk appetites lies at the heart of macrofinancial regulations such as the Dodd-Frank and Consumer Protection Acts. The effectiveness of these policies hinge on the assumption that large banks are the only banks that are too-big-to-fail (TBTF). However, alternative perspectives posit that banks may be too-complex-to-fail, regardless of their size. To remedy competing TBTF definitions, we propose a new criterion to identify potential TBTF banks by their relative involvement in so-called critical markets, considerate of both bank size and complexity. We estimate a restricted translog semiparametric smooth coefficient seemingly unrelated regressions model (SPSC SUR) wherein model elasticities are functions of nonperforming assets, a proxy for moral hazard, to derive nonperformance-adjusted returns-to-scale estimates for critical market banks from 2001 through 2023. Over our full sample, the median critical market bank tends to operate under increasing returns-to-scale while most critical market banks exhibit decreasing or constant returns-to-scale. Results taken over the past two decades suggest that most TBTF banks have exhausted their economies of scale concurrently alongside the shrinking competitive landscape.

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https://doi.org/https://doi.org/10.37625/abr.28.1.103-142

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@article{corey2025,
  title        = {{How Does Moral Hazard Impact Critical Market Banking Performance?}},
  author       = {Corey Williams},
  journal      = {American Business Review},
  year         = {2025},
  doi          = {https://doi.org/https://doi.org/10.37625/abr.28.1.103-142},
}

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Evidence weight

0.37

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.16 × 0.4 = 0.06
M · momentum0.53 × 0.15 = 0.08
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

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