Insights into the accuracy of social scientists’ forecasts of societal change

Igor Grossmann*, Amanda Rotella, Cendri A. Hutcherson, Konstantyn Sharpinskyi, Michael E. W. Varnum, Sebastian Achter, Mandeep K. Dhami, Xinqi Evie Guo, Mane Kara-Yakoubian, David R. Mandel, Louis Raes, Louis Tay, Aymeric Vie, Lisa Wagner, Matus Adamkovic, Arash Arami, Patricia Arriaga, Kasun Bandara, Gabriel Banik, František BartošErnest Baskin, Christoph Bergmeir, Michal Bialek, Caroline K. Børsting, Dillon T. Browne, Eugene M. Caruso, Rong Chen, Bin-Tzong Chie, William J. Chopik, Robert N. Collins, Chin W. Cong, Lucian G. Conway, Matthew Davis, Martin V. Day, Nathan A. Dhaliwal, Justin D. Durham, Martyna Dziekan, Christian T. Elbaek, Eric Shuman, Marharyta Fabrykant, Mustafa Firat, Geoffrey T. Fong, Jeremy A. Frimer, Jonathan M. Gallegos, Simon B. Goldberg, Anton Gollwitzer, Julia Goyal, Lorenz Graf-Vlachy, Scott D. Gronlund, Sebastian Hafenbrädl, Andree Hartanto, Matthew J. Hirshberg, Matthew J. Hornsey, Piers D. L. Howe, Anoosha Izadi, Bastian Jaeger, Pavol Kacmár, Yeun Joon Kim, Ruslan Krenzler, Daniel G. Lannin, Hung-Wen Lin, Nigel Mantou Lou, Verity Y. Q. Lua, Aaron W. Lukaszewski, Albert L. Ly, Christopher R. Madan, Maximilian Maier, Nadyanna M. Majeed, David S. March, Abigail A. Marsh, Michal Misiak, Kristian Ove R. Myrseth, Jaime M. Napan, Jonathan Nicholas, Konstantinos Nikolopoulos, Jiaqing O, Tobias Otterbring, Mariola Paruzel-Czachura, Shiva Pauer, John Protzko, Quentin Raffaelli, Ivan Ropovik, Robert M. Ross, Yefim Roth, Espen Roysamb, Landon Schnabel, Astrid Schütz, Matthias Seifert, A. Timur Sevincer, Garrick T. Sherman, Otto Simonsson, Ming-Chien Sung, Chung-Ching Tai, Thomas Talhelm, Bethany A. Teachman, Philip E. Tetlock, Dimitrios Thomakos, Dwight C. K. Tse, Oliver J. Twardus, Joshua M. Tybur, Lyle Ungar, Daan Vandermeulen, Leighton Vaughan Williams, Hrag A. Vosgerichian, Qi Wang, Ke Wang, Mark E. Whiting, Conny E. Wollbrant, Tao Yang, Kumar Yogeeswaran, Sangsuk Yoon, Ventura r. Alves, Jessica R. Andrews-Hanna, Paul A. Bloom, Anthony Boyles, Loo Charis, Mingyeong Choi, Sean Darling-Hammond, Zoe E. Ferguson, Cheryl R. Kaiser, Simon T. Karg, Alberto López Ortega, Lori Mahoney, Melvin S. Marsh, Marcellin F. R. C. Martinie, Eli K. Michaels, Philip Millroth, Jeanean B. Naqvi, Weiting Ng, Robb B. Rutledge, Peter Slattery, Adam H. Smiley, Oliver Strijbis, Daniel Sznycer, Eli Tsukayama, Austin van Loon, Jan G. Voelkel, Margaux N. A. Wienk, Tom Wilkening, The Forecasting Collaborative

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

10 Citations (Scopus)
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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 the 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. After we provided them with historical trend data on the relevant domain, social scientists submitted pre-registered monthly forecasts for a year (Tournament 1; N = 86 teams and 359 forecasts), with an opportunity to update forecasts on the basis of new data six months later (Tournament 2; N = 120 teams and 546 forecasts). Benchmarking forecasting accuracy revealed that social scientists’ forecasts were on average no more accurate than those of simple statistical models (historical means, random walks 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.

Original languageEnglish
Pages (from-to)484-501
Number of pages18
JournalNature Human Behaviour
Volume7
Issue number4
Early online date9 Feb 2023
DOIs
Publication statusPublished - 1 Apr 2023

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