Advice For A Career In Economics (Sort of)

Adam Ozimek is an economist at Moody's Analytics. Given the advice he provides students who want to pursue a career in economics, it is obvious he doesn't get, or never read, Friedrich Hayek's The Counter-Revolution of Science.

In the book, Hayek details the case that economists who attempt to mimic the physical sciences through empirical study and complex mathematical creations, fail to understand the true nature of economics as a science. For Hayek, economic theory is a qualitative science not an empirical science.

Thus, the below advice from Ozimek (written for Forbes) would be rejected by Hayek (and also Mises and Rothbard)

One theme that was reflected in every panelists’ comments was the importance of learning how to program. Statistical packages are one particular kind of programming language, and it’s important to learn more than one of these. Among these my personal preference is Stata, but I’ve also learned R and Fortran in the past, and have dabbled in others. But you never know which you’ll have to use at your first job. So more important than learning any particular language is learning how to learn one. Your first programming language will be hard. Your second one will be easier. By your third you’ll be learning how to learn and it will be much easier.

If you have a chance learning GIS can be a big advantage too. In a similar vein, taking a machine learning class will really open your eyes to techniques for working with Big Data that are becoming increasingly important but almost always neglected in econometrics classes.

I want to go into a little more detail about what it means to learn how to do statistical programming. I don’t mean take the dataset your professor gave with all the variables organized neatly, run some regressions, and then interpret the coefficients. In the classroom this is often the approach, but in the real world finding, assembling, and manipulating the data will be a big part of the work you do. Today many researchers provide code on their websites so you can go from the raw data to the results in their papers. You will learn a lot by trying to recreate the results of a paper you enjoy without the code, and then reading their code and seeing how they did it. Take your time with this. Start by trying to do the whole thing from scratch, and if your answer is wrong (it will be), steal their first few lines of code and then try again to do it on your own from that point. Who knows, you may even find an error in a superstar researcher’s paper and then get famous.

In my personal experience, it also helps you really learn econometrics to program estimators from scratch. And by scratch I mean without even using pre-packaged matrix multiplication. Maybe this is just my own learning deficit, but I didn’t really understand method of moments estiamtion until I had to program it.

Tragically, in one important sense, Ozimek is correct, in that currently almost all major university graduate programs focus on this type of faulty mathematical and programming work. If you hope to get a major university graduate degree in economics, this is what you will have to waste your time doing. An alternative is to study economic history. Also, I believe that it is possible to get a graduate degree in sociology and pretty much do Austrian economics---as long as you don't call the work you are doing Austrian economics.

I offer no insight into the job prospects for those with doctorate degrees in economic history or sociology, I just don't know. They probably aren't great. But if you are driven to become a sound economist, despite limited job prospects in academia, then economic history and sociology are sound options. But you are going to have to be very inner driven to make something out of your career long term. with the academic approach.  If you want a degree in economics, and want to avoid the mathematical programs, there are some schools out there, none in the Ivy league, where that is possible.

If you aren't hung up on getting a graduate degree, Gary North does make the case that you don't need one and this is probably true, but you will still have to be very driven to succeed.