I am a PhD Candidate in the Department of Economics at the University of Michigan. I am on the economics job market in the 2021-2022 academic year.

My research focuses on public economics, with a particular focus on the use of theory to inform the design of policy and the interpretation of empirical evidence. My work touches on topics in optimal taxation, bunching methodology, political economy, and behavio(u)ral economics.

Job Market Paper


Evaluating Tax Reforms without Elasticities: What Bunching Can Identify


Link to paper. Link to animated Twitter explainer.

Abstract

I present a new method for evaluating proposed reforms of progressive, piecewise linear tax schedules. Typically, estimates of the elasticity of taxable income (ETI) are used to predict taxpayer responses to changes in tax rates and/or tax bracket thresholds. I show that elasticities are not always needed for this task: the “bunching mass” at a bracket threshold (the share of taxpayers locating there) is a sufficient statistic for the revenue effect of behavioral responses to small changes of the threshold. Building on this finding, revenue forecasting and welfare analysis of threshold changes can be conducted using the pre-reform distribution of taxable income alone. I apply these results in an analysis of the Earned Income Tax Credit, an exercise which motivates extensions addressing optimization error, tax rate heterogeneity, and large reforms. This new use case for bunching complements existing bunching methods: it is robust to key limitations of bunching-based ETI estimation, but addresses a relatively narrow set of policy questions.