# Applying to economics Ph.D. programs

Published:

Everything below is my opinion and does not necessarily reflect the view of the UCSD economics department. For some resources provided by UCSD economics, please see here.

An economics professor is one of the best jobs. You have plenty of free time to do fun things (research), but unlike other scientific fields, economics professors get paid reasonably well. (If you like money, then being a business school professor or working in the industry may be better, but then you might have to spend a lot of time doing unpleasant things.)

To become an economics professor, you need an economics Ph.D. There are already plenty of advices on applying to economics Ph.D. programs out there (see here or here), so I will be brief. In my opinion, the most important things are

1. Letter of recommendation,
2. Mathematics,
3. Relevant research experience.

Below, I discuss these points in a bit more detail. My advice is aimed at top 10-20 programs (since UCSD is one of them).

## Letter of recommendation

What you need are informative and credible letters of recommendation. Letters should be informative so that evaluators can tell how good you are. When I write recommendation letters (for Ph.D. programs), I write things like

• this student took such-and-such class (some course description) in 20XX and ranked $n$ among $N$ students,
• this student has taken this, this, and that mathematics courses and obtained A in all of them,
• among all students I have interacted with, this student compares to so-and-so who graduated in 20XX and went to such-and-such program,

etc. Since competitive programs receive hundreds of strong applications, evaluators need concrete information to make informed decisions. Letters that praise the applicant without concrete evidence just get ignored. Letters should also be credible. Glowing but dubious letters just get ignored. To get credible letters, ask professors that have taught you (and know you) and have good reputations and respectable publication records (you can check this by looking at their CVs). If you want me to write you a letter, read this instruction.

## Mathematics

You should take rigorous, proof-based courses, not the mechanical, Mickey Mouse stuff. Calculus and linear algebra are necessary but insufficient. I recommend Ph.D. applicants to take at least real analysis (the rigorous one offered at mathematics departments), and then add more courses such as ordinary differential equation, complex analysis, functional analysis, optimization, numerical analysis, probability theory, stochastic processes, etc., as much as you can handle. (One reason I got into Yale despite not being an economics major is because I took many advanced mathematics courses in undergrad.)

## Relevant research experience

It is not necessary, but better, if you have relevant research experience. This could be a research paper (properly typeset) that signals your creativity, or a research assistanceship at the Fed or other institutions. A research paper reveals a lot of information. What I mean by this is that attaching a research paper (writing sample) to your application package can atcually increase or decrease the probability of acceptance. When I evaluate admission files and see a sloppy term paper that just runs regressions, I would downgrade my evaluation. On the other hand, if I see something solid, I would upgrade my evaluation. So think carefully before submitting your application package.

## Other considerations

• Letters need to be (mostly) written by economics professors (to be credible). This means that you need to take some economics courses. If you are not an economics major, one option is to go to a master program first.
• GRE is used only for screening. A near-perfect score in GRE quantitative is necessary but otherwise irrelevant once you pass screening.
• Statement of Purpose and Diversity Statement are mostly irrelevant. If you have time writing these, study more mathematics instead.
• Programming skill becomes important once you get into grad school. Learn programming languages at an early stage.