As a second-term senior, I feel the need to leave my experiences at MIT somewhere permanently. Here’s edition 1 of that.
The Economics classes at MIT are very math-heavy in comparison to what I’ve heard about economics elsewhere, and it’s a good idea to take a few math classes concurrent with your economics curriculum, especially if you’re aiming to go to grad school. I’ll list a few here that I’ve taken with econ classes they’re useful in.
You should take these math classes:
18.01/.02: required for 14.01/.02, I think, and it’s a good idea to have basic calculus down pat before you take any economics classes at MIT. Especially get comfortable with Lagrange multipliers; they will be with you for the rest of your economics career.
18.03: You’ll need this in the macro sequence, to solve the Solow model and some other differential equation problems. Other than that, this stuff doesn’t appear until grad-level classes. I took a PhD labor class, and there were a good number of people in it that never took a diffeq class in undergrad.
6.041/18.440/14.30: A statistics/probability class is immensely useful in the higher level economics classes; this comes up over and over and over, in econometrics, in finance, in labor, etc. etc. The ostensible rank in difficulty, hardest to easiest, is 18.440>6.041>14.30, though I think the curve is worse in 6.041 because of the course 6 masters students. Take this and know it well; it’s a requirement anyway. If you like this stuff, I hear 14.381, the PhD econ stats class is pretty good, too.
18.06: A linear algebra class is a needed to understand econometrics past the very basics. I don’t think anyone actually enjoys 18.06, but it’ll teach you what you need to know and more. Take this with Strang if you can.
18.100A/B/C: Real Analysis comes into play if you want to think about theory and proofs. This class is necessary if you want to go do a PhD in economics. Which level of the class you take will depend on your comfort with proofs and reading math. 100B/C is taught out of an incredibly dense book (Rudin) that is written in all math, and at a speed that was too much for me. 100A has more guidance for intuition, and is generally easier. I haven’t had to do any proofs in my undergrad classes; I think this comes in useful if you want to take the PhD intro classes.
Some other math classes that I took that aren’t so related:
18.443: More statistics, somewhat useful as a reference for econometrics, but I haven’t used it
18.310C: CI-M for math majors, discrete math with random topics about compsci, signals, sorting, etc. Makes you do dumb things like fourier transforms in Excel.
18.311: No tests. Ever. Continuous version of .310
If you have taken any interesting math classes that are relevant, leave it in comments.