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Agent-based modeling of long-term bank credit: buffer policies vs. selective lending in stochastic growth and decline

Mitja Steinbacher

Journal of Economic Interaction and Coordination2025https://doi.org/10.1007/s11403-025-00454-2article
AJG 1ABDC B
Weight
0.37

Abstract

This paper reexamines bank-firm interactions through an agent-based model, focusing on how banks influence long-term capital reallocation in stochastic, cyclical economies. Using an agent-based model with firm demand modeled as Geometric Brownian Motion, the paper studies growth/decline epochs under varying volatility. Unlike prior work focused on liquidity, this paper emphasizes long-term capital stocks and introduces a radial matching mechanism to minimize spatial bias. It extends prior work by introducing preference alignment between banks and firms, modeling credit as a two-stage process: (1) firms signal capital needs, and (2) banks approve/deny requests based on top-down buffer policies or bottom-up firm performance selection. Simulations across growth/decline epochs with varying volatility reveal a policy trade-off: (1) top-down buffers dominate during long-term growth, stabilizing credit allocation and (2) bottom-up selection excels in declines, efficiently restricting capital to high-performing firms. Here, a hybrid approach, combining both strategies, might be most resilient across cycles, suggesting that optimal credit regulation is phase-dependent. These findings challenge one-size-fits-all regulatory approaches and advocate for cycle-sensitive credit policies.

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https://doi.org/https://doi.org/10.1007/s11403-025-00454-2

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@article{mitja2025,
  title        = {{Agent-based modeling of long-term bank credit: buffer policies vs. selective lending in stochastic growth and decline}},
  author       = {Mitja Steinbacher},
  journal      = {Journal of Economic Interaction and Coordination},
  year         = {2025},
  doi          = {https://doi.org/https://doi.org/10.1007/s11403-025-00454-2},
}

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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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