Math Preparation for Graduate School
Although economics graduate programs have varying admissions requirements, graduate training in economics is highly mathematical. A 1991 report by the American Economic Association presented economics PhD students with the following list of mathematical topics:
- high school mathematics only
- basic calculus and linear algebra
- applied mathematics, differential equations, linear programming, and basic probability theory
- advanced calculus, advanced algebra and stochastic processes
- real and complex analysis, advanced probability theory, and topology
The average student reported that the level of mathematics used in her various graduate courses was slightly above level 3.
Since that time, there has been an upward trend in the level of mathematics used in graduate courses. For example, the website econphd.net website suggests that: "Two or three terms of calculus, and often linear algebra, are deemed minimum preparation; similarly a semester of mathematical statistics. First-year graduate courses draw heavily on real analysis. Background in real analysis is highly valued and indeed almost expected of a strong applicant. Real analysis is usually the first 'rigorous' mathematics course, where you have to work through all proofs and write some yourself. The course is supremely effective preparation for initial graduate courses."
Further reading on mathematical preparation
- Harvard Professor Greg Mankiw wrote a blog post on Why Aspiring Economists Need Math
- The Economics Department at The College of William and Mary has Advice on undergraduate mathematics preparation for a PhD in economics
- Professor Sita Slavov at George Mason University offers Tips for Applying to Ph.D. Programs in Economics