Some Thoughts on the Importance of Learning for the Working Econ PhD

Disclaimer: I’m writing these comments as someone working in a PhD-granting department at an R1 university. My guess, based on conversations with others, is that my experiences are the same for econ PhDs working in lots of other types of employment.

When I started grad school, I had no idea how important the ability to learn was to success as a PhD economist. The core PhD coursework I had to take in my first three semesters was seriously challenging. I didn’t understand the purpose of making the core courses so hard. In my first semester, I was required to take four courses: two math-heavy theory courses in macroeconomics and microeconomics, a math econ course that was in practice “real analysis for micro theorists”, and a mathematical statistics class that was 100% proofs of a wide range of propositions that had little relationship to economics.

I’ve now been out of grad school for twenty years. Even though I’ve never found the specifics of mathematical micro theory to be very helpful, I do understand the importance of being a good student. Here are four observations in no particular order on the place of learning in my career.

All the important research methods are things I learned after grad school. The classes I took in grad school provided a useful foundation for my research. Even when I was writing my dissertation, I had to learn a substantial proportion of the methods I used as I was doing research. Now, 20 years later, all the methods I use in my research have been self-taught. There is literally nothing I learned in grad school that can serve as the foundation of a paper I publish in a good journal in 2022.

There have been major changes in the tools used in research. The obvious change for empirical macroeconomists is the adoption of Bayesian methods for estimation. Although Bayesian inference certainly existed when I was taking classes in the late 1990s, it was seldom used, and there were few classes available for learning them, to say nothing about the computational limitations we faced back then. More generally, simulation methods are all the time today.

The term “macro model” usually means “DSGE model”, and in a lot of cases, “nonlinear DSGE model”. Most of the tools in existence today were not around in the late 1990s. A great example of this is models allowing for a zero lower bound.

Another example is the tools we have today for studying causality. By around 2010 I concluded I was no longer the best fit to teach the core econometrics class, as I was not keeping up with the latest developments in those methods, because I was not an empirical microeconomist. The days of “finding good instruments” were behind us. I would give that class to a colleague in 2013.

I’ve learned how to learn. I can pick up new methods much, much faster now than I could when I was younger. That’s a good thing because I don’t have the large blocks of time to devote to learning that I used to have. The only solution that would allow me to avoid becoming a dinosaur was to get better at learning.

Teaching grad courses makes you really efficient at learning. You need to constantly update your course with new material to reflect the trends in the profession. But you don’t have hundreds of hours to spend mastering each new topic.

I’ve learned while teaching that writing everything out clearly for others is an incredibly effective way to learn. Taking good notes is a superpower for learning. Another advantage of teaching is that you focus on what is important. After a while, you get better at determining what you should study in depth, and what you can ignore or that only requires superficial knowledge.

Editing requires learning. When you handle a large number of papers for a journal, especially one that accepts submissions from many different areas, you need to familiarize yourself with a lot of different approaches to research.

Your learning doesn’t have to be deep. That’s what the reviewers are for. You need to understand the topic and the contribution in order to make a decision on a paper. You can’t spend a week going down a rabbit hole to make a decision on a paper. You have to learn quickly to be an editor in a field like economics.