Summary
Yifeng Deng is an applied microeconomist and research assistant with eight years of quantitative research experience across top institutions, now entering a PhD program at UNC-Chapel Hill after completing an MA in Economics at Columbia. His work spans development, labor, and industrial organization with a strong empirical toolkit—data collection, cleaning, text-clustering, and visualization—applied to projects at the Federal Reserve Bank of New York, Columbia, Chicago Booth, and Cheung Kong Graduate School. He has scaled novel data pipelines (e.g., deduplicating over 1.2 billion job postings) and constructed industry proximity matrices from labor-flow and NLS data to reduce misclassification in applied analyses. Comfortable translating theory into implementable empirical strategies, he has extended structural models (à la Berry et al.) and clarified derivations for optimal trade-policy work. Based in New York, he combines careful coding (full-stack interests on GitHub) with policy-oriented research aimed at improving innovation and labor outcomes in developing countries.
8 years of coding experience
3 years of employment as a software developer
Bachelor of Science - BS Economics/Mathematics, Bachelor of Science - BS Economics/Mathematics at University of Southern California
Bachelor of Arts - BA Statistics, Bachelor of Arts - BA Statistics at University of Wisconsin-Madison
Master of Arts - MA Economics, Master of Arts - MA Economics at Columbia University
Doctor of Philosophy - PhD Economics, Doctor of Philosophy - PhD Economics at University of North Carolina at Chapel Hill