Partisan Sentiment and Returns From Online Political Betting Markets in the 2020 US Presidential Election
Year: 2025
Type: article
Abstract: ABSTRACT In this study, we estimate the role of daily partisan sentiment in predicting the returns from political betting markets on the PredictIt platform for 10 of the most competitive states in the 2020 US presidential election. We utilize a textual analysis approach (multinomial inverse regression method) to measure partisan sentiment for market participants through message board posts on each market's web page. Our results suggest that estimated partisan sentiment may play a role in the mispricing of political betting markets. Results are strongest for Republican assets and are robust to different specifications.
DOI: 10.1111/sjpe.70007
Authors: Mary Becker, Zachary McGurk, Marc LoGrasso
Institution: University of Akron
Language: English
Subfield: Economics and Econometrics
Domain: Social Sciences
Open Access status: green
OpenAlex ID: W4410129620