Predicting social tipping and norm change in controlled experiments

James Andreoni, Nikos Nikiforakis, Simon Siegenthaler

Research output: Contribution to journalArticlepeer-review


The ability to predict when societies will replace one social norm for another can have significant implications for welfare, especially when norms are detrimental. A popular theory poses that the pressure to conform to social norms creates tipping thresholds which, once passed, propel societies toward an alternative state. Predicting when societies will reach a tipping threshold, however, has been a major challenge because of the lack of experimental data for evaluating competing models. We present evidence from a large-scale laboratory experiment designed to test the theoretical predictions of a threshold model for social tipping and norm change. In our setting, societal preferences change gradually, forcing individuals to weigh the benefit from deviating from the norm against the cost from not conforming to the behavior of others. We show that the model correctly predicts in 96% of instances when a society will succeed or fail to abandon a detrimental norm. Strikingly, we observe widespread persistence of detrimental norms even when individuals determine the cost for nonconformity themselves as they set the latter too high. Interventions that facilitate a common understanding of the benefits from change help most societies abandon detrimental norms. We also show that instigators of change tend to be more risk tolerant and to dislike conformity more. Our findings demonstrate the value of threshold models for understanding social tipping in a broad range of social settings and for designing policies to promote welfare.

Original languageEnglish (US)
Article numbere2014893118
JournalProceedings of the National Academy of Sciences of the United States of America
Issue number16
StatePublished - Apr 20 2021


  • Conformity trap
  • Laboratory experiment
  • Social norms
  • Threshold models
  • Tipping points

ASJC Scopus subject areas

  • General


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