Courses

Graduate-Level Economics Courses

At the intersection of economic theory and data science, UConn Master of Science in Quantitative Economics offers a STEM-designated curriculum that drives careers. Our coursework balances 18 core credits in advanced theory with 12 technical electives — including Python, R, and Machine Learning — preparing you for high-impact analytical roles in just three semesters.

Core Corses

  • ECON 5201. Microeconomics (3 Credits): Beginning graduate microeconomics covering consumer and producer theory, price determination, economic efficiency, and welfare analysis.
  • ECON 5202. Macroeconomics (3 Credits): Survey of the field: its historical foundations and development, conceptual framework, and application to current macroeconomic problems.
  • ECON 5301. Mathematical Economics (3 Credits): Use of mathematical concepts such as matrix algebra, optimization, and comparative statics, to study economic problems.
  • ECON 5311. Applied Econometrics I (3 Credits): Statistical theory and linear regression.
  • ECON 5312. Applied Econometrics II (3 Credits): Large sample linear regression, time series analysis, maximum likelihood, GMM, and qualitative choice models.
  • ECON 5317. Machine Learning for Economists (3 Credits): Machine learning techniques and causal inference. Applications to economic data.
  • ECON 5318. Panel Data Econometrics (3 Credits): Standard panel-data models, which apply to datasets that follow cross-sections of individuals through time. Emphasis on determining when causal relationships can be inferred from panel data.
  • ECON 5321. Programming and Computation with R for Economists (3 Credits) Basics of R programming. Objects, data structures, logical design, and functions.

Elective Courses (choose six credits)

  • ECON 5314. Causal Program Evaluation (3 Credits): Survey of the statistical methods and tools commonly used to evaluate causal claims about the impact of public policies and programs. This course is a required Master of Public Policy course.
  • ECON 5315. Financial Econometrics (3 Credits): Introduction to the mathematics of finance. Theoretical reasoning (proofs), modeling, useful simplifying approximations, and computing. Students will write basic programs in R.
  • ECON 5322. Open Source Programming with Python for Economists (3 Credits): Introduction to Python. Code structure; control flow; data input/output in various formats; testing and debugging.
  • ECON 5323. Convex Optimization with Python (3 Credits): Methods of convex optimization, including linear, quadratic, and general constrained and unconstrained problems. Applications, using Python, in economics and finance.
  • ECON 5326. Operations Research for Economics (3 Credits): Use of mathematical programming for optimization of input-output mixes, delivery routes, communication networks and performance evaluation based on economic theory of producer behavior.

Optional Courses

  • ECON 5501. Writing and Communication for Economics and Business I (2 Credits): Practice in written and oral communication of economic ideas. Development of skills and techniques for success in business and professional environments.
  • ECON 5502. Writing and Communication for Economics and Business II (1 Credit): Application of skills from ECON 5501 to writing and presenting a research paper developed in a third-semester Master of Science in Quantitative Economics course.

Application Deadlines

Fall Semester
All Tracks, Storrs & Stamford

Preferred Admission: June 1
Deadline: July 29

Spring Semester
Accelerated 4+1 Track, Storrs & Stamford

Deadline: December 1

Applying early is strongly recommended to avoid last-minute processing delays.
The MSQE program does not offer graduate assistantships at this time.