Natalie Epstein

Natalie Epstein is a PhD Candidate in Technology and Operations Management at Harvard Business School. She received her B.S. in Industrial Engineering and M.S. in Operations Management from Universidad de Chile. Prior to Harvard, Natalie worked as a Business Analyst at McKinsey & Company and as a Research Associate at Universidad de Chile. Her research interests are in empirical operations in retail, e-commerce, logistics, and consumer behavior.

Journal Articles

• Correa, Jose, Natalie Epstein, Rafael Epstein, Juan Escobar, Ignacio Rios, Nicolas Aramayo, Bastian Bahamondes, Carlos Bonet, Martin Castillo, Andres Cristi, Boris Epstein, and Felipe Subiabre. "School Choice in Chile." Operations Research 70, no. 2 (March–April 2022): 1066–1087. View Details

Working Paper

• Balakrishnan, M., MoonSoo Choi, and Natalie Epstein. "An Empirical Study of Time Allotment and Delays in E-commerce Delivery." Working Paper, August 2022. View Details
• Epstein, Natalie, Santiago Gallino, and Antonio Moreno. "The Hidden Cost of Coordination: Evidence from Last-Mile Delivery Services." Working Paper, May 2023. View Details

Cases and Teaching Materials

• Toffel, Michael, and Natalie Epstein. Assessing Prediction Accuracy of Machine Learning Models. Harvard Business School Tutorial 621-706, February 2021. View Details
• Parzen, Michael, Natalie Epstein, Chiara Farronato, and Michael Toffel. T-tests: Theory and Practice. Harvard Business School Tutorial 621-707, February 2021. View Details
• Toffel, Michael W., Natalie Epstein, Kris Ferreira, and Yael Grushka-Cockayne. "Assessing Prediction Accuracy of Machine Learning Models." Harvard Business School Technical Note 621-045, August 2020. (Revised September 2020.) View Details

Area of Study

• Technology and Operations Management