About

I am a PhD candidate from the University of Notre Dame. My area’s of research include public economics, labor economics, and the economics of education. I use a blend of machine learning tools and traditional causal inference techniques to study public finance in the US education system. My other research looks at K-12 faculty labor markets and measuring teacher effectiveness.

I am on the job market for AY 2025/2026.

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Job Market Paper

Job Market Paper

Credit Crunch in the Classroom: School District Financing Under Liquidity Constraints

In this paper, I examine how access to bond market liquidity affects future funding and staffing decisions in the US education system. Using a novel and comprehensive dataset of all municipal bonds issued by U.S. public school districts since 1987, I apply machine learning techniques to identify districts near key credit rating thresholds. Leveraging an RD design, I then estimate the causal impact of diminished credit access across these thresholds. I find that reduced access to bond market credit results in approximately 5% lower spending in the fiscal year following a ratings update. I show that this is primarily driven by decreases in property tax revenue, capital expenditure spending and maintenance staff compensation with the largest effects observed for mid-sized school districts by total revenue.

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