Research
My research examines how behavioral frictions, information environments, and institutional design affect economic outcomes, using causal inference and computational methods.
Empirical Research (Applied Microeconomics)
Salience, Attention, and Memory: Crime Capitalization in Housing Prices (Work in Progress)
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)
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)
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 & Simulation-Based Economics
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 (Working Paper)
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