CMU’s Economics PhD unites rigorous microfoundations with frontier data methods. Students model strategic AI competition, quantify climate-risk pricing in bond markets, and run large-scale RCTs via online platforms. Interdisciplinary electives in computer science, public policy, and behavioral science position graduates for academia, central banks, and tech-economics leadership roles.
Difference-in-differences analysis of carbon tax impacts on wage growth
Machine-learning approach to estimating heterogeneous treatment effects in micro-loans
Game-theoretic model of data-broker market equilibria under privacy regulation
Structural estimation of strategic pricing in ride-hailing duopolies
Predictive model of sovereign-bond spreads under climate-vulnerability indices
RCT evaluating default-green-investment nudges in retirement funds
Synthetic-control study of gig-economy regulation on labor supply
Network analysis of global supply-chain contagion in semiconductor shortages
Econometric test of speculative bubbles in cryptocurrency markets
Field experiment on algorithmic pricing transparency and consumer trust
Macro-agent simulation of CBDC adoption and banking disintermediation
Event-study on ESG disclosure mandates and firm valuation dynamics
Policy memo on antitrust frameworks for AI-powered platforms
Computational replication of famous market-design experiments in VR
Time-varying parameter VAR linking geopolitical risk and energy prices
Craft data-driven economic insight and policy at CMU.
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