Publications
Journal of Economic Behavior and Organization, Vol. 214 (February 2024), pages 486-513. [SSRN Version]
Abstract: Homophily is typically measured using a single dimension to define groups. However, people generally display friendship preferences over multiple dimensions when forming social connections. We develop a simple model that characterizes agents both by a (discrete) "group type" and a (continuous) "personality trait" value. Agents have preferences-for-similarity over both dimensions, but homophily is only measured with respect to group type. We show that our model belongs to a more general class of models for which a strongly stable network exits, and identify an algorithm that constructs it. Via simulations, we demonstrate that our model's strongly stable network exhibits three key patterns previously documented in the homophily literature. The model provides new insights and interpretations of these patterns.
American Economic Review, Vol. 111, No. 2 (February 2021), pages 720-754. [Online appendix] [Unabridged Version]
Abstract: We propose and develop a dynamic theory of endogenous preference formation in which people adopt worldviews that shape their judgments about their experiences. The framework highlights the role of mindset flexibility, a trait that determines the relative weights the decision maker places on her current and anticipated worldviews when evaluating future outcomes. The theory generates rich behavioral dynamics, thereby illuminating a wide range of applications and providing potential explanations for a variety of observed phenomena.
Working Papers
Victim Preferences for Punishment (Under Review)
Abstract: We investigate the influence of victim preferences on third-party punishment decisions. In an online experiment, we find that third-party decisions are significantly more influenced by victim preferences than by those of bystanders, suggesting that third parties grant victims some degree of moral authority in determining the appropriate punishment. A second experiment examines individuals’ views on the role victim preferences ought to play in punishment decisions. Results reveal substantial heterogeneity: 54% of participants make choices aligning with the belief that third parties should consider victim preferences; 46% make choices aligning with the belief that third parties should not. These findings provide insight into the motives behind third-party punishment and the potential role of victim sentence recommendations in legal contexts.
Works-in-Progress
Leveraging Machine Learning to Manage Library Inventory (with Rice Majors) [overview slides]
Abstract: University libraries have limited capacity to store inventory on-campus and must relegate a substantial amount to off-site repositories, in a process known as “weeding.” This process ideally identifies materials least likely to be requested by future library patrons, but it traditionally relies on labor-intensive, case-by-case evaluations by librarians. This project introduces a machine learning-based approach to optimize the weeding process, reducing the time and resources required for decision-making. Using two decades of collection data from a large public California university, we leverage data on book characteristics—such as publication date and Library of Congress classification codes—and prior checkout history to predict future usage. Standard machine learning techniques, including random forests and boosting, are applied to generate predictions. We quantify the accuracy of these techniques using actual checkout data and compare their effectiveness to more basic decision rules, as well as manual decisions made by librarians.
Victim as Offender and Offender as Victim (with Jocelyn Cruz) [overview slides]
Motivated Reasoning and Present Focus (with Hunt Allcott, B. Douglas Bernheim, and Tingyan Jia)
Abstract: In this project, we explore the possibility that individuals use motivated reasoning to justify present-focused behavior. When facing an intertemporal choice involving the present and the future, we convince ourselves that enjoying today (less investment, more leisure, unhealthy food, etc.) is optimal because things will be easier in the future. This generates a specific set of predictions: when choosing today whether to exert effort today or tomorrow, we convince ourselves that we can do less today because the returns to effort will be higher tomorrow relative to today. But when we choose for tomorrow vs. the day after, we do not need to distort our beliefs as there are no immediate actions to be taken today. We develop and run an experiment where we find preliminary evidence of this type of belief distortion.
Papers Laid to Rest
Preferences for Compensatory and Retributive Justice
Abstract: I experimentally investigate third-party preferences for victim compensation and offender punishment when one party has harmed another. I find that preferences for both compensation and punishment extend beyond pure distributional concerns: they reflect preferences for (what I term) compensatory and retributive justice, respectively. Demands for the two forms of justice are positively correlated across individuals, suggesting that they offer compatible outlooks. Exploring situational factors, I find suggestive evidence that these demands are affected by whether the offender finds out about the victim's compensation and whether the victim learns about the offender's punishment. I then consider a setting where the offender's action only induces probabilistic harm on the victim. I find that whether or not the victim suffers harm affects demands for overall compensation and punishment, but does not affect demands for compensatory or retributive justice.