Dr. Rui Sun

Assistant Professor of Economics


  • Ph.D. Economics, University of Connecticut, 2021
  • M.S., Quantitative Economics, University of Connecticut, 2021
  • M.S., Finance, Johns Hopkins University, 2015
  • M.S., Applied Economics, Johns Hopkins University, 2014
  • B.S., Finance, Chongqing University, China, 2012

Dr. Sun earned his Ph.D. in economics from the University of Connecticut. Prior to joining the graduate program at UConn, he obtained an M.S. in finance and M.S. in applied economics from Johns Hopkins University and a B.S. in finance from Chongqing University in China. During his Ph.D. study, he taught undergraduate courses in econometrics and time series forecasting. He was also an adjunct faculty member at Eastern Connecticut State University, where he taught a course in quantitative finance. His teaching interests are in quantitative methods for economics and business, as well as machine learning and open source programming (i.e. R/Python). His research has been published in Empirical Economics, etc.

Courses Taught

  • BUS 350: Business Quantitative Analysis
  • BUS 601: Global Managerial Economics
  • BUS 606: Decision Making and Decision Analytics
  • BDA 601: Foundations of Programming
  • BDA 602: Statistics for Business Analytics
  • BDA 610: Advanced Business Statistics


  • Econometrics
  • Machine Learning


  • American Economic Association
  • Econometric Society

Professional Interests

  • Econometrics
  • Applied Microeconomics
  • Applications of Machine Learning Methods for Causal Inference

Recent Publications

  • Krumel, T., Goodrich, C., Sun, R., and Fiala, N. (2022), Linking Employment and Death: Measuring the Structural Disparity in COVID-19 Deaths for Non-telework Essential Workers, The B.E. Journal of Economic Analysis & Policy
  • Kao, C., Liu, L., and Sun, R. (2021), A Bias-Corrected Fixed Effects Estimator in the Dynamic Panel Data Model, Empirical Economics

Contact Dr. Sun


3001 Mercer University Drive, Atlanta, Georgia 30341
Stetson-Hatcher School of Business, BE-226