The MS in Quantitative Economics

How an ongoing initiative to refine our curriculum—in consultation with leading experts from Amazon, Google, Zillow, and other top technology and data companies—is helping us shape the economists of tomorrow.

By Eduardo Zambrano | MS Quantitative Economics Program Director

The MS in Quantitative Economics delivers structured thinking about empirical problems and incentives. The overarching goal of our program is to teach students to work with data in messy, real-world environments.

During their time here, students learn advanced econometrics for prediction and causal inference, computer programming, and receive training in the analysis of individual and group incentives. They also learn how to use basic economics principles and experimental designs to help individuals and organizations make decisions with the aim of improving people’s lives.

Our job placement is outstanding—from Booz Allen Hamilton, Hulu, Oracle, Uber and Visa to top Ph.D. programs offered by universities such as the University of Minnesota and UC Santa Barbara.

We’re also of course always striving to improve. Recently, we developed and refined our curriculum in consultation with an Advisory Task Force of leading economists, consultants and data scientists from Amazon, Google, OnPoint Analytics, Streamlit and Zillow.

These are some of the things we learned from this exercise: Our industry advisors are impressed with the heavily empirically oriented nature of our program, and they recommend for this to be kept this way. They also like that our students begin coding and doing empirical work from the start of the program, and that this work is solidly grounded in economic theory.

Our advisors also tell us that four topics, which we already cover, are vital within industry and could be emphasized even more: coding proficiency, data management skills, machine learning, and experimentation. Our plan is to address the first two items by revamping our computer programing class, GSE 524. We’ll address the second two by creating two new courses: a Machine Learning for Prediction and Causal Inference elective, and a Behavioral and Experimental Economics elective.

We are confident that the implementation of these changes will help us as we continue to equip our graduates with first-rate training, allowing them to succeed in any organization, anywhere in the world.

The applications cycle for the fall of 2020 is now open. We encourage you to forward this information to anyone you think might be interested in what the MS in Quantitative Economics has to offer, and to contact us with any questions.

Click here to learn more about the MS in Quantitative Economics.