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Published July 2015 | public
Journal Article Open

Conformity in the lab


We use a revealed preference approach to disentangle conformity, an intrinsic taste to follow others, from information-driven herding. We provide observations from a series of sequential decision-making experiments in which subjects choose the type of information they observe before making their decision. Namely, subjects choose between observing a private (statistically informative) signal or the history of play of predecessors who have not chosen a private signal (i.e., a statistically uninformative word-of-mouth signal). In our setup, subjects choose the statistically uninformative social signal 34% of the time and, of those, 88% follow their observed predecessors' actions. When allowing for payoff externalities by paying subjects according to the collective action chosen by majority rule, the results are amplifed and the social signal is chosen in 51% of all cases, and 59% of those who pick the social signal follow the majority choice. The results from the majority treatment demonstrate that conformist behavior is not driven by inequality aversion, nor by strategic voting behavior in which voters balance others who are uninformed. Raising the stakes five-fold does not eliminate conformist behavior; in both treatments, the social signal is chosen nearly 50% of the time. Individual level analysis yields the identification of rules of thumb subjects use in making their decisions.

Additional Information

© 2015 Economic Science Association. Received: 31 October 2014; Revised: 22 December 2014; Accepted: 27 January 2015; First Online: 24 February 2015. We thank Tom Palfrey and Charlie Plott for several useful conversations as well as Nageeb Ali, Navin Kartik, Nikos Nikiforakis, and Robert Slonim for comments on an earlier draft. Roy Chen, Lauren Feiler, and Angelo Polydoro provided outstanding research assistance. We gratefully acknowledge financial support from the National Science Foundation (SES 0551014), the Gordon and Betty Moore Foundation (Grant 1158), and the European Research Council (ERC Advanced Investigator Grant, ESEI-249433).

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August 22, 2023
August 22, 2023