Applied Economics and Data Science, MEDS
Penn's Master of Applied Economics and Data Science is designed for students who want to combine a foundation in economic modeling with data science techniques to give them an edge in their career track. Much of data science is intended to inform decision makers about actions they should take. An action could be, for example, a firm's investment in a new production facility, or a central bank's choice of a target inflation rate. To evaluate the impact of particular actions on relevant outcomes and to identify actions that meet some optimality criteria, we need: (a) an economic model that allows us to measure costs associated with actions; (b) an economic model that allows us to measure the benefit of actions and forces us to think about static versus dynamic effects; (c) an empirical framework to measure, simulate, and forecast the effects of action on outcomes; (d) finally, an approach that lets us choose optimally among a set of potential actions (where we will have uncertainty in the above), for example Bayesian decision theory and/or game theory to capture strategic interactions. To meet these needs the program will develop students' knowledge and skills in three primary areas: using economic models for decision making, extracting information from data, and proficiency in the use and development of software.
The degree and major requirements displayed are intended as a guide for students entering in the Fall of 2026 and later. Students should consult with their academic program regarding final certifications and requirements for graduation.
Curriculum
| Code | Title | Course Units |
|---|---|---|
| Required Courses | ||
| AEDS 6100 | Applied Microeconomics I | 1 |
| AEDS 6110 | Applied Microeconomics II | 1 |
| AEDS 6200 | Applied Macroeconomics I | 1 |
| AEDS 6210 | Applied Macroeconomics II | 1 |
| AEDS 6300 | Econometrics I | 1 |
| AEDS 6310 | Econometrics II | 1 |
| AEDS 6400 | Computational Methods | 1 |
| AEDS 6410 | Machine Learning for Economists | 1 |
| Electives | ||
| Select 3 CU from the following: | 3 | |
| Topics in Industrial Organization, Market Design, and the Digital Economy | ||
| Topics in Macroeconomic Policy Analysis | ||
| Empirical Economics of Climate Change | ||
| Topics in Causal Inference | ||
| Topics in Forecasting and Big Data Analysis | ||
| Required Capstone Course | ||
| AEDS 7000 | Capstone Research Course | 1 |
| Total Course Units | 12 | |
- 1
Minimum 3.0 GPA is required for graduation.
- 2
Up to 2 course units of transfer credit is allowed.
The program requires 12CU's including a capstone research project to fulfill degree requirements. The course sequence is as follows:
| First Year | ||
|---|---|---|
| Fall | Course Units | |
| AEDS 6100 | Applied Microeconomics I | 1 |
| AEDS 6200 | Applied Macroeconomics I | 1 |
| AEDS 6300 | Econometrics I | 1 |
| AEDS 6400 | Computational Methods | 1 |
| Course Units | 4.00 | |
| Spring | ||
| AEDS 6110 | Applied Microeconomics II | 1 |
| AEDS 6210 | Applied Macroeconomics II | 1 |
| AEDS 6310 | Econometrics II | 1 |
| AEDS 6410 | Machine Learning for Economists | 1 |
| Course Units | 4.00 | |
| Second Year | ||
| Fall | ||
| Choose 3 electives | 3 | |
| Topics in Industrial Organization, Market Design, and the Digital Economy | ||
| Topics in Macroeconomic Policy Analysis | ||
| Empirical Economics of Climate Change | ||
| Topics in Causal Inference | ||
| Topics in Forecasting and Big Data Analysis | ||
| Required Capstone Course (1cu) | ||
| AEDS 7000 | Capstone Research Course | 1 |
| Course Units | 4.00 | |
| Total Course Units | 12.00 | |
Submatriculation
Exceptional Penn undergraduates may apply to the program in their junior year for submatriculation beginning in their senior year. Submatriculants must apply through the application system and will be considered alongside other applicants to the program. If submatriculants are admitted, the Executive Director will work with the student’s undergraduate major adviser to identify courses that may be double-counted (apply toward both the bachelor’s and undergraduate degrees). Submatriculants may take a maximum of two cu’s in the master’s program while they are undergraduates; they will take the remaining ten cu’s after they complete their undergraduate degree. The two courses (cu's) must form a two-course sequence (AEDS 6100 & AEDS 6110; AEDS 6200 & AEDS 6210; AEDS 6300 & AEDS 6310; or AEDS 6400 & AEDS 6410).