UNC’s STEM MS in Economics delivers rigorous econometrics, machine learning, and structural-modeling training for careers in finance, tech, and government. Students scrape high-frequency data with Python, estimate DSGE models on cluster computing, and publish policy briefs through the Kenan Institute. Practitioner seminars with the Fed, IMF, and BlackRock ensure theory meets real-world complexity.
High-frequency trading strategy back-tested with limit-order-book data
Difference-in-differences study of broadband rollout and labor markets
Machine-learning model predicting sovereign-debt crises
Structural estimation of consumer demand for EV charging stations
Natural-language processing of central-bank speeches for sentiment indices
Agent-based simulation of housing-market bubbles under rate shocks
Policy memo on carbon-border adjustment and industry competitiveness
Open-source package implementing causal forests for panel data
Dashboard visualizing municipal bond risk under climate scenarios
Grant proposal studying cash-transfer impacts on food security
White paper on crypto-asset volatility contagion
Survey experiment on behavioral nudges for retirement savings
Workshop on reproducible research with Stata and Git
Apply cutting-edge econometrics to guide markets and public policy.
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