Graduate Program Minor Fields

Students must take four courses, each earning three or more credits. The rules concerning these four courses are:

1. Two of the courses must either be:

(a) A two-course sequence in one of the Economics Department’s seven major fields (excluding the student’s own major field); or
(b) Mathematics Department or Statistics Department courses at the 700 level or above.

2. The remaining two courses must be

(a) Economics Department or Statistics Department courses at the 700 level or above
(b) Mathematics Department courses at the 500 level or above.

Students are also welcome to propose four-course sequences that do not satisfy items 1 and 2 above. Approval of such proposals is at the discretion of the Director of Graduate Studies.

A GPA of 3.0 must be maintained in the minor. In addition, grades of B or better must be received in courses used to fulfill the minor field requirement. Workshop courses and independent study courses may not be used for the minor. Courses which are part of the student's major field may not be included. The beginning Micro and Macro sequence (Econ 711, 712, 713, & 714) and the beginning Econometrics sequence (Econ 709, 710) may also not be used as part of the minor. Courses taken more that 10 years ago may not be utilized for the minor.

Minor form

Minor course requirements for students in other departments

Graduate students in other departments who seek a minor in Economics as part of their Ph.D. program should obtain the appropriate minor agreement forms from their department. As a rule, a set of four courses in Economics (12 credits) taken as a graduate student will be approved. At least one course should be in the theory sequence (711-714), along with three appropriate doctoral level courses at the 600-900 level. Not more than one course may be a reading course, workshop, or seminar. The minor field must be approved by the Director of Graduate Studies. Grades of B or better are required for each of the four courses in the minor.

Suggested Minor Field Courses in Mathematics and Statistics

Mathematics (Course Descriptions)

Analysis:

521 Advanced Calculus I

522 Advanced Calculus II

629 Introduction to Measure and Integration

721 Real Analysis I

725 Real Analysis II

821 Advanced Topics in Real Analysis

Probability:

632 Introduction to Stochastic Processes

635 Introduction to Brownian Motion and Stochastic Calculus

735 Stochastic Analysis

831 Theory of Probability I

832 Theory of Probability II

833 Topics in the Theory of Probability

Optimization:

525 Linear Programming Methods

726 Nonlinear Programming Theory and Applications

Dynamical Systems:

716 Ordinary Differential Equations

777 Nonlinear Dynamics, Bifurcations, and Chaos

807 Dynamical Systems

Statistics (Course Descriptions)

Time Series:

701 Applied Time Series Analysis, Forecasting, & Control I

702 Applied Time Series Analysis, Forecasting, & Control II

Classical Statistics:

709 Mathematical Statistics I

710 Mathematical Statistics II

732 Large Sample Theory of Statistical Inference

Bayesian Statistics:

775 Introduction to Bayesian Decision and Control

853 Bayesian Inference