GNAIOct 12, 2023

Belief formation and the persistence of biased beliefs

arXiv:2310.08466v1h-index: 3
Originality Incremental advance
AI Analysis

This addresses the problem of belief persistence for researchers in behavioral economics and psychology, but it is incremental as it builds on existing models of belief formation.

The paper tackles the problem of how biased beliefs persist by modeling belief formation where agents discriminate between theories, with asymmetry in evidence strength leading to one-sided evidence accumulation. The result shows that sophisticated agents avoid bias, while less sophisticated ones end up with biased beliefs.

We propose a belief-formation model where agents attempt to discriminate between two theories, and where the asymmetry in strength between confirming and disconfirming evidence tilts beliefs in favor of theories that generate strong (and possibly rare) confirming evidence and weak (and frequent) disconfirming evidence. In our model, limitations on information processing provide incentives to censor weak evidence, with the consequence that for some discrimination problems, evidence may become mostly one-sided, independently of the true underlying theory. Sophisticated agents who know the characteristics of the censored data-generating process are not lured by this accumulation of ``evidence'', but less sophisticated ones end up with biased beliefs.

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