Publication Type

Journal Article

Version

submittedVersion

Publication Date

4-2023

Abstract

How well can social scientists predict societal change, and what processes underlie their predictions? To answer these questions, we ran two forecasting tournaments testing accuracy of predictions of societal change in domains commonly studied in the social sciences: ideological preferences, political polarization, life satisfaction, sentiment on social media, and gender-career and racial bias. Following provision of historical trend data on the domain, social scientists submitted pre-registered monthly forecasts for a year (Tournament 1; N=86 teams/359 forecasts), with an opportunity to update forecasts based on new data six months later (Tournament 2; N=120 teams/546 forecasts). Benchmarking forecasting accuracy revealed that social scientists’ forecasts were on average no more accurate than simple statistical models (historical means, random walk, or linear regressions) or the aggregate forecasts of a sample from the general public (N=802). However, scientists were more accurate if they had scientific expertise in a prediction domain, were interdisciplinary, used simpler models, and based predictions on prior data.

Keywords

Forecasting, Expert judgment, Well-being, Political polarization, Prejudice, Meta-science

Discipline

Experimental Analysis of Behavior | Social Psychology

Research Areas

Psychology

Publication

Nature Human Behaviour

Volume

7

First Page

484

Last Page

501

ISSN

2397-3374

Identifier

10.1038/s41562-022-01517-1

Publisher

Nature Research

Embargo Period

3-16-2023

Copyright Owner and License

Authors

Creative Commons License

Creative Commons Attribution 4.0 International License
This work is licensed under a Creative Commons Attribution 4.0 International License.

Additional URL

https://doi.org/10.1038/s41562-022-01517-1

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