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On the ethics of pollsters or journalists or political scientists betting on prediction markets

Andrew Gelman · published 2 February 2023

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Do we really believe the Democrats have an 88% chance of winning the presidential election? Read at the source ↗
statmodeling.stat.columbia.edu
https://www.stat.columbia.edu/~gelman/research/published/what_learned_in_2016_5.pdf
stat.columbia.edu
https://slate.com/news-and-politics/2016/12/19-lessons-for-political-scientists-from-the-2016-election.html
slate.com
https://arxiv.org/pdf/1703.06351.pdf
arxiv.org
Is it meaningful to talk about a probability of “65.7%” that Obama will win the election? Read at the source ↗
statmodeling.stat.columbia.edu
https://www.stat.columbia.edu/~gelman/research/published/swingers.pdf
stat.columbia.edu
Concerns with our Economist election forecast Read at the source ↗
statmodeling.stat.columbia.edu
No, Bayes does not like Mayor Pete. (Pitfalls of using implied betting market odds to estimate electability.) Read at the source ↗
statmodeling.stat.columbia.edu
Reverse-engineering the problematic tail behavior of the Fivethirtyeight presidential election forecast Read at the source ↗
statmodeling.stat.columbia.edu
How good are election prediction markets? Read at the source ↗
statmodeling.stat.columbia.edu
https://rajivsethi.substack.com/p/prediction-markets-in-a-polarized
rajivsethi.substack.com
https://rajivsethi.substack.com/p/predicting-rare-events
rajivsethi.substack.com