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Related Experiment Video

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Constructing and Visualizing Models using Mime-based Machine-learning Framework

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Published on: July 22, 2025

Connectionist agent-based learning in bank-run decision making.

Weihong Huang¹, Qiao Huang¹

¹Division of Economics, Nanyang Technological University, Singapore 637332.

Chaos (Woodbury, N.Y.)

|June 3, 2018

Summary

This summary is machine-generated.

Understanding bank runs is crucial. This study reveals that even in good economies, cognitive-affective networks can trigger bank runs, but higher late payoffs help prevent them.

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Area of Science:

Behavioral Economics
Agent-Based Computational Economics
Financial Stability

Background:

Classical models often neglect the probability of bank runs (PBR).
Bank runs stem from various factors beyond miscoordination or asset deterioration.
Heterogeneous agents with correlated beliefs influence financial stability.

Purpose of the Study:

To simulate nonlinear dynamic probabilities of bank runs using a global games approach.
To investigate the impact of cognitive-affective networks on agent behavior and PBR.
To explore the effects of payoff structures and risk sharing on bank run dynamics.

Main Methods:

Agent-based computational economics simulation.
Global games approach with heterogeneous, correlated beliefs.
Modeling agents with an integrated cognitive-affective network.

Main Results:

Cognitive-affective networks significantly influence agent reactions to bad news, even in positive economic conditions, potentially leading to bank runs.
Increased late payoffs (R) and early payoffs (r) reduce the impact of the affective process.
The effect of increased risk sharing on PBR is ambiguous; higher late payoffs are beneficial for bank run prevention.

Conclusions:

This research pioneers the integration of agent-based computational economics and behavioral economics to study bank runs.
Cognitive-affective dynamics play a critical role in financial instability, necessitating their inclusion in policy considerations.
Policy interventions focusing on increasing late payoffs can effectively mitigate the probability of bank runs.