معرفی
Giovanni Compiani is an Associate Professor at the University of Chicago Booth School of Business, specializing in Marketing. His research bridges industrial organization and quantitative marketing, focusing on advanced econometric methods.
- PhD, MPhil, MA in Economics from Yale University
- BSc, MSc in Economics from Bocconi University
- Previous Assistant Professor at Haas School of Business
His work explores unstructured data integration in demand estimation, consumer search behavior on online platforms, risk preferences in cryptocurrency markets, and time perception in behavioral economics. He has published in top journals including Journal of Political Economy, Marketing Science, and Review of Economic Studies.
Recent publications emphasize machine learning applications in econometrics, equilibrium modeling of lotteries, and crypto mining's economic impact. His research portfolio spans demand analysis, structural modeling, and behavioral insights.
- Editor's Choice Award, The Review of Asset Pricing Studies (2024)
- Developed nonparametric demand estimation frameworks
- Advances dynamic model identification with instrumental variables
Compiani teaches Data Science for Marketing Decision Making at Booth and maintains active collaborations with researchers across econometrics, computer science, and behavioral disciplines.
