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Bank Runs and Monetary Arrangements : A Computational Examination

What is the role of inter-bank markets and central banks in coping with banking crises? I answer this question by developing a sensitivity analysis to the model in Diamond and Dybvig (1983). I implement an agent-based economic model to analyze different modifications and extensions to the original. In 36 experiments based on three different versions of the one-bank model the frequency of bank runs dropped from 42% to 17%. This was due to changes in the payoffs structure and social network effects whereby depositors go to the bank if at least three of their proximate neighbors went previously. In other experiments with multiple banks interacting in an inter-bank market with banks having the same market share there are no runs escalating to systemic panics. If there is one bank with a market share twice as big as the other ones, a liquidity crisis spreads to more than one bank. On the other hand, when banks cannot interact runs in isolated banks occur with a higher frequency. Finally, adding a central bank unexpectedly increases the occurrence of bank runs. Institutional complexity helps to reduce the frequency of bank runs. Hence, decentralized institutional structures perform better than centralized ones. JEL Codes: G21, C63