Cornell University

This is a past event. Its details are archived for historical purposes.

The contact information may no longer be valid.

Please visit our current events listings to look for similar events by title, location, or venue.

Joint Behavioral Economics & Public Economics Workshop: David Yang

Tuesday, September 29, 2020 at 11:30am to 1:00pm

Virtual Event

David Yang, Harvard University

Stereotypes and Politics

Abstract: US voters exaggerate the differences in attitudes held by Republicans and Democrats on a range of socioeconomic and political issues. We examine the drivers and implications of such perceived partisan differences. We find that a model of stereotypes where distortions are stronger for issues that are more salient to voters captures important features of the data. First, perceived partisan differences are predictable from the actual differences across parties, in particular the relative prevalence of extreme attitudes. Second, perceived partisan differences are larger on issues that individuals consider more important. In particular, we show that the end of the Cold War in 1991, which shifted US voters’ attention away from external threats, led to an increase in perceived partisan differences in domestic issues, and more so for issues with more stereotypical partisan differences. The reverse pattern occurred after the terrorist attacks in 2001, when attention swung back towards external threats. Finally, the belief distortions we identify are quantitatively significant, and strongly predict voting turnout.

Dial-In Information

If you are interested in participating in this seminar, please register at:

Note: If you have previously registered for the Fall 2020 Behavioral Economics Workshop, there is no need to re-register.


Google Calendar iCal Outlook
Event Type

Seminar, Class/ Workshop




economics, EconSeminar, EconPublic, EconBehave

Contact E-Mail

Contact Name

Ulrike Kroeller


David Yang

Speaker Affiliation

Harvard University

Open To

Cornell Economics Community - List Serve Members