Observations of a PhD Student: An Introduction to Graduate School
The first part of a new series chronicling the thoughts of an Austrian earning their Phd.
By CobPD.
This will be the first of several posts to come in this new series I’ll be calling “Observations of a PhD Student.” As the name suggests, this series will be a hodgepodge of my insights into mainstream academia from an Austrian perspective. Some posts may be short and light, while others may be longer and slightly technical. This first entry to the series will just be an introduction to myself, my general experience in my program thus far, and some tips I can offer to students who are interested in pursuing graduate-level education.
I am pursuing a PhD in Finance. That’s right, not economics. I will explain this choice later. I’ve been a very dedicated student of Austrian economics since 2016, having read at least 80+ specifically Austrian books ranging from Mises, Hayek, and Rothbard to Machlup, Strigl, and Lewin. I attended the Mises University summer program in 2019 and was the only undergraduate student to make it to the final round (top 6 students) of the Mündliche Prüfung competition. With this history, I consider myself pretty knowledgeable on Austrian economics, although, of course, there’s always more to read and learn.
I was a double-major, double-minor in undergrad, earning B.S.s in Economics and Finance and minors in Math and Philosophy. I’ve known since high school that I wanted to eventually pursue a PhD. For most of this time, I always thought I’d go into economics. However, after some time in my undergrad finance courses and getting into personal investments, I became more passionate about financial markets. Furthermore, it became apparent that Austrian economics has a large blind spot when it comes to financial markets. There is some work from Fritz Machlup, Dave Howden, Mark Spitznagel, and even Robert Murphy, but I think there’s still a lot more room for bringing Austrian insights into financial market analysis. Thus, I decided to jump into finance academia rather than the overpopulated economics field. It’s an added bonus that finance academics are paid much more than their economist counterparts.
However, finance programs are often more competitive than economics programs since there are fewer available and they typically accept fewer students per year. I recommend that one pays serious attention towards studying for the quantitative section of the GRE (or the GMAT equivalent) since it will be an important requirement for competitive applicants. However, don’t be too discouraged if your score is falling behind the school’s average. Strong letters of recommendations, CV’s, and expressing strong interest and competence in research may make up for it. My score did fall behind the average of many of the schools I applied to, yet I still ended up in a top finance program (ranked top 10 according to some rankings, but consistently at least top 25). Also, it’s worth noting that a lot of PhD application outcomes may simply be up to luck. Decisions are often made according to what type of research the faculty/school wants to see or sponsor.
I have now completed the first semester of my program. I took Statistics, Microeconomic Theory I, Math for Economists (constrained optimization problems), Advanced Topics in Capital Markets (financial asset pricing), and attended regular seminars in which senior finance students presented their working papers. As you can see, this semester was heavily focused on economics. Three of the four courses were taken with the economics students. Next semester will be a similar picture: Micro II, Macro II, Econometrics, and Corporate Finance.
What have I noticed so far? These classes are almost pure math courses. Of course, anyone well-versed in Austrian critiques of mainstream economics would expect this. Being a well-read Austrian since high school, of course I knew this. Yet I still underestimated how much even Microeconomic Theory would be pure math. All of the content in the course was focused on understanding compact and convex sets, upper- and lower-hemicontinuous correspondences, fixed point theorems, Hessian and Jacobian matrices, total differentiation, even differential equations, etc. It was very easy to forget that we were even studying economics.
My program is likely a little more mathematically rigorous than many others, and it may be largely due to how the professor presents the topics. However, the general experience is certainly the same no matter where one goes: you’re essentially just studying math. Having come straight from undergrad, and with only a minor in math, I felt like I was falling behind the rest of my cohort. Nearly everyone else had already taken similarly-rigorous courses in their masters programs or had several years of research experience in some other capacity.
I knew most of the math concepts that I had come across, but it was still difficult to work in a purely mathematical framework. Previously, I would often just glaze over portions of text which had heavy mathematical notation, expecting that the text would explain the concepts in a more easily-understandable way. However, I quickly learned that I would have to get used to the language of mathematical notation since that’s the only method of presentation in mainstream economics. Fortunately, most of the math language isn’t too difficult to catch on to, and you begin to learn what’s there for purely formal reasons and what’s there as actual content.
Nonetheless, starting out with more mathematical experience would definitely have been very helpful. I highly recommend majoring in math in undergrad and spending more time self-studying and practicing with math. Even algebra gets more tedious and can slow you down more than you’d expect. And although masters programs usually come with a hefty price tag, I would at least consider taking that stepping stone before jumping straight into a PhD program.
One last recommendation: learn some coding. I came into the program with absolutely no experience or knowledge in coding. But I quickly discovered from my introductory Data Camp that this is a must-have skill for doing any empirical work. And the Data Camp was in no way introductory. Much like a lot of the mathematical applications, it seemed like I was expected to already be an expert on coding and SQL data collection. I have a lot of catching up to do.
Despite how difficult this semester has been, I made it through. There were definitely times that I was worried about my grades falling behind and losing my stipends, but it turns out that grades don’t really matter for the most part. Graduate school does not have a traditional grading system even if the syllabus states that exams are worth 80% of the grade. Thus, even bombing that 80% of the class can still result in the B- that’s needed. What seems to really matter is the comprehensive exams that come at the end of year 1 or 2 (depending on the program) and then quality of research.
Again, this will be a somewhat regular series of posts in which I write about some observations that I make about mainstream economics and finance academia from an Austrian perspective. The next post will be diving into a typical dichotomy that’s often drawn by mainstream academics between intuition and theory.
Other Articles Like This One
How Economics Became a Mathematical Science
Discover New Opportunities
Click here for the Austrian Economics Discord Server.
Click here for the Austrian Economics Discord YouTube Channel.