Altruistic observational learning

Christoph March and Anthony Ziegelmeyer

Journal of Economic Theory, 2020, vol. 190, issue C

Abstract: We report a laboratory experiment that tests the causal impact of altruism on observational learning behavior. Once endowed with a private signal, subjects submit their guess about the payoff-relevant state in two parallel sequences. In the observed sequence, guesses are revealed publicly so that subjects in both sequences can benefit from guesses that are informative. Unobserved guesses, on the other hand, never reveal any information to others as they remain private. We find that observed guesses are significantly more informative than unobserved guesses. The strong responses to private information benefit information aggregation as observational learning behavior is informationally more efficient in the observed sequence than in standard equilibrium outcomes. Once the incentives to make the empirically optimal guess are large enough, observed and unobserved behave quite similarly, and observed guesses are significantly less informative if fewer successors can benefit from the revelation of private signals. These findings are well in line with the qualitative predictions of an observational learning model where players have altruistic preferences.

Keywords: Altruism; Observational learning; Experiments; Herd behavior; Overconfidence (search for similar items in EconPapers)
JEL-codes: C72 C92 D83 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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Related works:
Working Paper: Altruistic Observational Learning (2016)
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Persistent link: https://EconPapers.repec.org/RePEc:eee:jetheo:v:190:y:2020:i:c:s0022053120301162

DOI: 10.1016/j.jet.2020.105123

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