Agent-Based Econometrics
This project leverages Monte Carlo simulations to evaluate and establish the statistical properties of estimators within an agent-based model.
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Comparing Human-Only, AI-Assisted, and AI-Led Teams in Quantitative Social Science
This study presents a field experiment conducted in collaboration with the Institute for Replication, comparing the effectiveness of human, AI-assisted, and AI-led teams in replicating published social science research.
Social Context Matters: How Large Language Model Agents Reproduce Real-World Segregation Patterns in the Schelling Model
We extend the classic Schelling segregation model by replacing its traditional, rule-based agents with Large Language Model (LLM) agents that make residential decisions using natural language reasoning grounded in social context.