Research

My research studies how local environments and institutional policies shape economic and social outcomes, using modern causal inference and computational methods.

Empirical Research (Applied Microeconomics)

Crime, Salience, and the Housing Market (Work in Progress)

How do housing markets respond over space and time to localized crime shocks?

Fields: Urban Economics, Behavioral Economics, Housing Markets
Methods: Spatial–Temporal Kernel Estimation, Repeat-Sales Models

Abstract Homebuyers observe crime infrequently, recall it imperfectly, and often overweight unusually salient incidents. This paper studies how these behavioral frictions shape the spatial and temporal pattern of crime capitalization in housing prices. Using detailed incident-level crime data linked to repeat-sales transactions, I develop a flexible space–time kernel estimator that recovers the distance-decay and time-decay of crime’s price impact.

The Effect of Diversity Statements in Faculty Hiring with David Slichter (Working Paper)

Do diversity statement requirements causally change faculty hiring composition and ideology?

Fields: Labor & Personnel Economics, Higher Education, Applied Microeconomics
Methods: Difference-in-Differences (csdid), Entropy Balancing, Text Classification

Abstract This project examines how mandatory diversity statements in faculty job applications influence hiring and student outcomes. Using comprehensive text from JOE and APSA postings linked to institution–year–discipline hiring records, we classify DEI-related requirements and estimate their effects using staggered-adoption DiD estimators with entropy-balancing weights.

Food Swamps, Obesity, and Metabolic Risks (Work in Progress)

Do dollar-store rollouts causally affect metabolic health risks?

Fields: Health Economics, Urban Economics, Public Economics
Methods: Event Studies / DiD

Abstract This project examines how the expansion of dollar stores and low-nutrition retail environments contributes to obesity and metabolic health risks. Using store rollouts and quasi-experimental variation in food environments, I study how changes in access to calorie-dense, nutrient-poor options affect chronic disease outcomes.

Computational Methods & Simulation

Monte Carlo Diagnostics for Agent-Based Models with Christopher Zosh, Yixin Ren, Andreas Pape (Working Paper)

Fields: Computational Economics, Econometrics, Simulation
Methods: Agent-Based Models, Monte Carlo Simulation, Simulation-Based Inference

Abstract We develop a statistical framework for diagnosing parameter identifiability and uncertainty in stochastic agent-based models (ABMs). The approach combines Monte Carlo experiments with simulation-based confidence intervals, providing generalizable tools for calibration, validation, and sensitivity analysis in complex ABMs.

Paper Link: PDF


Social Context in the Schelling Model Using LLMs with Andreas Pape, Srikanth Iyer, Carl Lipo, Yixin Ren, Christopher Zosh (Work in progress)

Fields: Computational Economics, Behavioral Economics, Social Dynamics
Methods: Agent-Based Models, Large Language Models, Experimental Simulation

Abstract This paper introduces large language models as agents in the classic Schelling segregation model to study how communication, narrative framing, and social context shape emergent spatial patterns.

Paper Link: PDF