Date of Award

Spring 2016

Degree Name

Bachelor of Science



First Advisor

Nicholas Woolley


In financial markets, banks play a key role in transforming illiquid assets into more liquid assets. However, their ability to spread the risk of liquidity shocks over a body of agents generates a positive probability for non-efficient bank runs. Building off of the classic Diamond-Dybvig framework, this paper uses an agent based model to observe the two equilibria, efficient risk sharing and the bank run. While previous literature has looked at under what conditions could a bank run equilibrium occur, this proximity based learning model (PBLM) focuses on the development of a panic driven bank run in light of limited information, proximity based learning, and localized interactions among heterogeneous agents. This simulation approach is novel in that it allows for the inclusion of more realistic conditions (e.g. heterogeneity and learning) that would make such a model difficult to solve, if not mathematically intractable. This paper finds proximity based learning to be an effective method of communication and a panic transmission mechanism when consumers only have limited information.


Senior thesis completed at Trinity College, Hartford, Connecticut for the degree of Bachelor of Science in Economics.

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