Political Science and Political Economy Research Seminar
Biased Learning from Elections
Andrew Little (Berkeley)
Tuesday 27 September 2022 14:00 - 15:30
Many of our seminars and public events this year will continue as in person or as hybrid (online and in person) events. Please check our website listings and Twitter feed @STICERD_LSE for updates.
Unless otherwise specified, in-person seminars are open to the public.
Those unable to join the seminars in-person are welcome to participate via zoom if the event is hybrid.
About this event
A foundational premise in democratic theory is that political competition encourages parties to be responsive to voters. Parties have incentives to respond to the median voter’s preferences in order to win elections, and should learn from the results of elections where their platforms diverge from what the electorate wants. However, parties may be subject to motivated reasoning, wanting to believe that the electorate favors their own policy preferences. We develop a repeated model of elections with motivated beliefs to explore how this bias affects how parties compete with one another for popular support. Motivated beliefs lead to excessive platform divergence, and allow parties to infer from poor electoral outcomes that elections are unfair rather than that their platforms are unpopular. Disagreement about the fairness of the electoral system increases over time, even if platform divergence decreases. Our analysis reveals how motivated beliefs inhibit parties’ ability to learn what voters want while encouraging partisans to distrust the electoral process itself.
The Political Science and Political Economy (PSPE) research group at the LSE brings together faculty and PhD students who do quantitative and/or formal research on political institutions, political behaviour, public policy, and political economy.
The PSPE Research Seminar provides a venue for researchers (mostly from outside of the LSE) to present their work.
These seminars are held on Tuesdays in term time at 14.00-15.30, both ONLINE AND IN PERSON in room 32L 3.05, unless specified otherwise.
Seminar coordinator: Mathilde Emeriau
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