Summary
Evan Munro is an econometrician and statistician who blends economic theory, machine learning, and rigorous statistical methods to tackle measurement and inference problems. With eight years of experience spanning academic research at Stanford, visiting positions at Berkeley, and a faculty appointment at Chicago Booth beginning 2025, he translates cutting‑edge theory into applied tools. His background includes industry research stints at Google and Microsoft Research and data‑driven consulting for central banks, reflecting a rare ability to move between policy, research, and production environments. Earlier roles in finance and engineering give him practical experience in risk modeling, structured products, and complex data systems. Evan often combines unconventional data sources—satellite imagery, transaction records—and computational methods to generate timely economic indicators. He is based in Palo Alto and is known for bridging disciplinary boundaries to produce work with both theoretical depth and real‑world impact.
8 years of coding experience
4 years of employment as a software developer
Master of Philosophy - MPhil Economics, Master of Philosophy - MPhil Economics at University of Oxford
Lisgar Collegiate Institute
Bachelor of Arts Economics Computer Science-Mathematics, Bachelor of Arts Economics Computer Science-Mathematics at Columbia University
Doctor of Philosophy - PhD Economic Analysis and Policy, Doctor of Philosophy - PhD Economic Analysis and Policy at Stanford University
French