Recommended Math Courses for Economics Graduate Students

Disclaimer: The opinions expressed on this page are my own and do not represent the policy or opinions of the economics department. The recommendations here are based primarily on the success of past students who have taken the path I describe.

Remark: Distinguished Stanford graduates such as David Kreps and Darrell Duffie contributed important new ideas in economics from the beginning of their careers partly because they are creative and partly because they were extraordinarily well equipped in mathematical and statistical tools.

I recommend that graduate students in economics at Stanford take or audit a stream of math and statistics classes while they are here. If you take one course a quarter from the second year on, you will have at least nine quarters under your belt by the time you graduate. While it may be painful at first, like jogging, after a while the pain will vanish and you will acquire a facility in writing and reading economics. My experience has been that students who pay the price of learning adequate mathematical and statistical tools have much easier times writing their theses and acquiring jobs. This is certainly true in applied fields like macroeconomics.

You are very lucky because at Stanford there are wonderful courses taught by some of the most distinguished people in the world. Here are some courses I recommend.

Math Department:

• Math 103, 104, Linear algebra
• Math 113, 114 Linear algebra and matrix theory
• Math 106, Introduction to functions of a complex variable (especially useful for econometrics and time series analysis)
• Math 124, Introduction to stochastic processes
• Math 130, Ordinary differential equations
• Math 131, Partial differential equations
• Math 175, Functional analysis
• Math 205A, B, C, Real analysis and functional analysis
• Math 230A, B, C, Theory of Probability
• Math 236, Introduction to stochastic differential equations

Engineering Economic Systems and Operations Research

• EESOR 313, Vector Space Optimization. This course is taught from `the Bible' by the author (Luenberger). The book is wonderful and widely cited by economists.
• EESOR 322, Stochastic calculus and control

Statistics

• Stat 215-217, Stochastic processes (Cover)
• Stat 218, Modern Markov chains (Diaconis)
• Stat 310 A, B, Theory of probability (Dembo)

These are very useful courses for applied work in econometrics, macroeconomic theory, and applied industrial organization. They describe the foundations of methods used to specify and estimate dynamic competitive models.

Just as in jogging, I recommend not overdoing it. Rather, find a pace that you can sustain throughout your years here. You will find that taking these courses doesn't really cost time, because of your improved efficiency in doing economics.

There are many other courses that are interesting and useful. The most important thing is just to get started acquiring the tools and habits these courses will convey.