Summary: I run two experiments to study the role that motivated reasoning plays in the supply of false information. Experiment 1, conducted using a large online sample of social media users, shows that incentivizing senders to be perceived as truthful causes them to send less truthful messages. Instead, these incentives lead senders to strategically misreport in order to appeal to receivers' current beliefs and their politically-motivated beliefs. However, receivers do not anticipate the adverse effects of senders' incentives. Experiment 2 breaks the interaction between senders and receivers, showing more directly that beliefs about motivated reasoning are a driver of these effects.
(Study materials here)
The Fake News Effect: Experimentally Identifying Motivated Reasoning Using Trust in News (Revise & Resubmit, AEJ: Microeconomics)
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.
(Study materials here)
Summary: I experimentally show that people systematically overinfer from weak signals despite underinferring from strong signals. Overinference is especially prominent for very weak signals, which have often been neglected in the literature. Greater task experience and cognitive sophistication are each associated with less overweighting of weak signals and less underweighting of strong signals. Results are consistent with a theory in which agents are cognitively imprecise about the strength of signals.
Good News Is Not a Sufficient Condition for Motivated Reasoning (New Draft: September 2022)
Summary: I experimentally test whether people engage in motivated reasoning towards believing "good news" or "bad news" about the world around them, and find a precisely-estimated and homogeneous null effect. Via a complementary survey, I show that respondents anticipate that good news makes people happier but are not necessarily beliefs that they are motivated to hold, suggesting that motivated reasoning is not primarily driven by belief-based happiness.
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.
Gender Differences in Motivated Reasoning. Journal of Economic Behavior and Organization, 2021.
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.
Works in Progress
N Angry Men: The Importance of Endogenizing Jury Size when Comparing Voting Rules
Using Negative Feedback to Debias Motivated Reasoning
Dynamic Information Acquisition in the Lab (with Alessandro Lizzeri and Leeat Yariv)
And Now for Something Completely Different
Tribone Tilings of Triangular Regions that Cover All but Three Holes. Discrete & Computational Geometry, 2015.
Summary: In my undergrad math thesis, I showed that there are a lot of ways to tile triangular regions with tribones when you leave three spaces uncovered.