Community Enforcement of Trust with Bounded Memory
V Bhaskar and
Caroline Thomas ()
Review of Economic Studies, 2019, vol. 86, issue 3, 1010-1032
We examine how trust is sustained in large societies with random matching, when records of past transgressions are retained for a finite length of time. To incentivize trustworthiness, defaulters should be punished by temporary exclusion. However, it is profitable to trust defaulters who are on the verge of rehabilitation. With perfect bounded information, defaulter exclusion unravels and trust cannot be sustained, in any purifiable equilibrium. A coarse information structure, that pools recent defaulters with those nearing rehabilitation, endogenously generates adverse selection, sustaining punishments. Equilibria where defaulters are trusted with positive probability improve efficiency, by raising the proportion of likely re-offenders in the pool of defaulters.
Keywords: Trust game; Repeated games with community enforcement; Imperfect monitoring; Bounded memory; Credit markets; Information design (search for similar items in EconPapers)
JEL-codes: C73 D82 G20 L14 L15 (search for similar items in EconPapers)
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Persistent link: https://EconPapers.repec.org/RePEc:oup:restud:v:86:y:2019:i:3:p:1010-1032.
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