Working Papers

The "Fake News" Effect: Experimentally Identifying Motivated Reasoning Using Trust in News

Summary: I design a new experimental tool for portably identifying motivated reasoning from Bayesian updating, and use this tool to show that politics affects inference about factual questions on a broad range of topics: immigration, income mobility, crime, racial discrimination, gender, climate change, and gun laws. Politically-motivated reasoning is more severe for partisans and leads people to over-trust news more when it reinforces the biases in their beliefs.

Media: National Affairs

Gender Differences in Motivated Reasoning (Revise & Resubmit, Journal of Economic Behavior and Organiztion)

Summary: I show experimentally that there are statistically significant gender gaps in motivated reasoning about outperforming others, but that motivated reasoning about political issues is similar across genders. Motivated reasoning can help explain why there are gender gaps in overconfidence.

Do People Engage in Motivated Reasoning to Think the World Is a Good Place for Others?

Summary: I experimentally test whether people motivatedly reason towards believing the world is a good place for others, and find a well-powered null effect. Via a survey, I show that respondents anticipate that these types of "positive" beliefs make people happier but are not necessarily beliefs that they are motivated to hold.


Polarization and Public Health: Partisan Differences in Social Distancing during the Coronavirus Pandemic (with Hunt Allcott, Levi Boxell, Jacob Conway, Matthew Gentzkow, and David Yang). Journal of Public Economics, 2020.

Summary: Using GPS data, we show that areas with more Republicans have engaged in less social distancing during COVID-19 than areas with more Democrats, and using a new survey, we show that Republican individuals self-report less social distancing and believe that the risk of COVID-19 is lower.

Media: Wired, CNN (video), New York Times, Mother Jones, Economist, Reuters, Los Angeles Times, FiveThirtyEight, Newsweek, USA Today

Works in Progress

Overinference from Weak Signals, Underinference from Strong Signals, and the Psychophysics of Interpreting Information

Summary: I experimentally study how people make inferences from signals of varying strengths, and find that they behave as if they misperceive the strength S using a pyschophysics power function k*S^β. This misperception leads to both overinference from weak signals and underinference from strong ones. Consistent with the theory, subjects have excess demand for low-quality information sources, and experience and cognitive sophistication are associated with less severe misperceptions.

n ∈ [6,12] Angry Men: The Importance of Endogenizing Jury Size when Comparing Voting Rules

Summary: I present a model that compares the accuracy and efficiency of jury voting mechanisms when both jury size and voting rule can vary. The main result is that an (n+2)-person jury that allows for one dissenter is both more accurate and less likely to hang than an n-person jury under unanimity. (Slides available upon request.)

The Supply of Motivated Beliefs

And Now for Something Completely Different

Tribone Tilings of Triangular Regions that Cover All but Three Holes. Discrete & Computational Geometry, 2015.

Summary: I show that there are a lot of ways to tile triangular regions with tribones when you leave three spaces uncovered.