I’m a PhD student in the Department of Economics at UC Berkeley. I’m generally interested in researching how insights from psychology and behavioral economics can inform how we design and understand the effects of public policies.
Abstract (click to expand) (–): Economists typically check the robustness of their results by comparing them across plausible ranges of parameter values and model structures. A preferable approach to robustness—for the purposes of policymaking and evaluation—is to design policy that takes these ranges into account. We modify the standard optimal income tax model to include the policymaker’s subjective uncertainty over parameter values, and we characterize robust optimal policy as that which maximizes expected social welfare. After calibrating uncertainty over the elasticity of taxable income from past empirical work and novel survey data on economists’ beliefs, we compare the implied robust optimal marginal tax rates to the alternative benchmark policy based on the best point estimates of relevant parameters. Our results suggest that robust optimal marginal tax rates are typically more progressive than in benchmark analyses, raising top marginal tax rates by between 5 and 7 percentage points, and generating modest expected welfare gains.
(with Hunt Allcott, Benjamin Lockwood, and Dmitry Taubinsky)
Current version: March 2022
Revise and Resubmit at The Review of Economic Studies
Abstract (click to expand) (–): We use natural experiments embedded in state-run lotteries and a new nationally representative survey to provide reduced-form and structural estimates of risk preferences and behavioral biases in lottery demand. We find that sales respond more to the expected value of the jackpot than to price, but are unresponsive to variation in the second prize—a pattern that implies probability weighting but is inconsistent with standard parameterizations. In the survey, we find that lottery spending decreases modestly with income and is strongly associated with measures of innumeracy, poor statistical reasoning, and other proxies for behavioral bias. These bias proxies decline with income and statistically account for 43 percent of lottery purchases, suggesting that at least some of lottery demand is due to behavioral bias, not just anticipatory utility or entertainment value. We use these empirical moments to estimate a model of socially optimal lottery design. In the model, current multi-state lottery designs increase welfare but may harm heavy spenders.
Abstract (click to expand) (–): Using data from a field experiment on exercise, we analyze the relationship between im- perfect memory and people’s awareness of their limited self-control. We find that people overestimate past gym attendance, and that larger overestimation of past attendance is as- sociated with (i) more overestimation of future attendance, (ii) a lower willingness to pay to motivate higher future gym attendance, and (iii) a smaller gap between goal and forecasted attendance. We organize these facts with a structural model of quasi-hyperbolic discount- ing and naivete, estimating that people with more biased memories are more naive about their time inconsistency, but not more time-inconsistent.
Selected Work in Progress
Ideology and Moral Hazard
(with Na’ama Shenhav and Dmitry Taubinsky)
I’m grateful to Gautam Rao for sharing the code for his website, created by Xinyue Lin, in his GitHub repository. I also thank Jonathan Old for the instructions provided in the GitHub repository for his website.
