Department of Economics
Departmental Honors
Students on Summer 2025, Fall 2025, or Spring 2026 requirements ECON-HON
Students pursuing the Bachelor of Arts in Economics have two options for earning departmental honors and should choose either the requirements for Option I or Option II below. Depending upon availability, students seeking an honors diploma are encouraged to take additional 300–400 level courses designated as honors sections.
Requirements
- GPA Requirements.
- College GPA. A College grade point average (GPA) of at least 3.500 is required.
- Major GPA. An Economics major grade point average (GPA) of at least 3.700 is required.
- Advanced Courses*. Six (6) credit hours:
- ECON-E 390 Undergraduate Seminar in Economics
- ECON-E 392 Seminar in Computational Methods and Econometrics
- ECON-E 401 Machine Learning for Economic Data
- ECON-E 402 Computational Methods In Macroeconomics
- ECON-E 411 Economics of Networks and Market Design
- ECON-E 425
- ECON-E 427
- ECON-E 471 Econometric Theory and Practice I
- ECON-E 472 Econometric Theory and Practice II
- ECON-E 490 Advanced Undergraduate Seminar in Economics
ECON-E 390 Undergraduate Seminar in Economics
- Credits
- 3
- Prerequisites
- ECON-E 321 or ECON-S 321
- Notes
- Additional prerequisites may be required depending on the seminar topic
- Description
- Intensive study of a topic area in economics. Topics will vary.
- Repeatability
- May be repeated with a different topic for a maximum of 9 credit hours.
ECON-E 392 Seminar in Computational Methods and Econometrics
- Credits
- 3
- Prerequisites
- ECON-E 321 or ECON-S 321; Additional prerequisites may be required depending on the seminar topic
- Description
- Intensive study of a topic area in computational methods or econometrics. Topics will vary.
- Repeatability
- May be repeated with a different topic for a maximum of 9 credit hours.
ECON-E 401 Machine Learning for Economic Data
- Credits
- 3
- Prerequisites
- ECON-E 321 or ECON-S 321; and ECON-E 371 or ECON-S 371
- Description
- What is machine learning and how can we use it to help us explore economic data? This course develops exploratory data analysis skills and provides training in a variety of machine learning techniques used to analyze economic data while using the R programming language.
ECON-E 402 Computational Methods In Macroeconomics
- Credits
- 3
- Prerequisites
- ECON-E 252 or ECON-B 252; and ECON-E 321 or ECON-S 321
- Description
- Macroeconomic data are increasingly available and used by economists and data scientists to help decision-makers. This course provides opportunities to develop tools to explore macroeconomic data, build and simulate macroeconomic models, perform experiments, and solve dynamic models using numeric methods. Also provides experience in the Python programming language.
ECON-E 411 Economics of Networks and Market Design
- Credits
- 3
- Prerequisites
- ECON-E 321 or ECON-S 321
- Description
- Combines tools of economics, computer science, and mathematics to study real-world problems like information diffusion, production networks, school choice, kidney exchange, and combinatorial auctions. Examines how economic models have a practical value in solving relevant practical problems.
ECON-E 471 Econometric Theory and Practice I
- Credits
- 3
- Prerequisites
- ECON-E 370, ECON-S 370, or MATH-M 365; and MATH-M 301, MATH-M 303, or MATH-S 303; and MATH-M 311 or MATH-S 311
- Notes
- Only 9 credit hours from ECON-E 371, ECON-S 371, ECON-E 471, and ECON-E 472 may be counted toward a major in economics
- Description
- Emphasis is on the classical linear regression model and its applications. Special topics include finite and asymptotic properties of least squares, hypothesis testing, model specification, dummy variables, proxies, multicollinearity and heteroscedasticity.
ECON-E 472 Econometric Theory and Practice II
- Credits
- 3
- Prerequisites
- ECON-E 471
- Notes
- Only 9 credit hours from ECON-E 371, ECON-S 371, ECON-E 471, and ECON-E 472 may be counted toward a major in economics
- Description
- Emphasizes extensions of the classical linear-regression model such as: limited dependent variables, instrumental variables, stationary and nonstationary data, fixed-effect and random-effect models, multiple-equation models, censored regression, and sample selection.
ECON-E 490 Advanced Undergraduate Seminar in Economics
- Credits
- 3
- Prerequisites
- ECON-E 321 or ECON-S 321
- Notes
- Additional prerequisites may be required depending on the seminar topic
- Description
- Advanced intensive study of a topic area in economics. Topics will vary.
- Repeatability
- May be repeated with different topics for a maximum of 9 credit hours.
- Thesis.
- Course Requirement. Six (6) credit hours over two (2) consecutive semesters:
- ECON-E 499 Honors Thesis
ECON-E 499 Honors Thesis
- Credits
- 3
- Prerequisites
- ECON-E 322 or ECON-S 322; and ECON-E 370 or ECON-S 370; Economics majors or interdepartmental major (ECON/POLS or ECON/MATH); minimum 3.300 economics GPA
- Notes
- Additional prerequisites may be required by the faculty mentor. Honors course; A maximum of 3 credit hours in ECON-E 499 may count toward the major in economics
- Description
- Honors thesis research by special arrangement with an economics faculty mentor and the director of undergraduate studies.
- Repeatability
- May be repeated up to 2 times for a maximum of 6 credit hours.
- Topic Approval. Research topic must be approved by an economics faculty mentor and the department’s Director of Undergraduate Studies prior to the beginning of the first semester in which student is enrolled in ECON-E 499.
- Course Requirement. Six (6) credit hours over two (2) consecutive semesters:
Exceptions to and substitutions for honors requirements may be made with the approval of the unit's Director of Undergraduate Studies, subject to final approval by the College of Arts and Sciences.