Classes for the last semester

by Gilbert Keith

Reflections on the first day.

The semester began yesterday, and I hope it lasts for a loooong time. Mostly because of the classes I am taking. Yesterday’s classes portend a fun semester of things and projects I want to do (something I haven’t really felt in the last few semesters) and that’s a good thing. There are also a lot of people in my classes I know, which makes things way better!

Class #1:

Weight Training.

Every senior should have some slacker class, or so I’m told. Well, instead I chose a class which would be fun, but also a little challenging. I’ve always wanted to lift weights properly, so when the opportunity to take a course presented itself, I latched onto it. This is my earliest class on Tuesdays and Thursdays, and requires me to be warmed up and ready to lift by 9:05 AM. That’s not particularly bad, since it allows me to incorporate a varied exercise schedule which looks something like:

Sunday: 2 hrs exercise bike

Monday: 1 hr walk/elliptical/jog

Tuesday: Lifting

Wednesday: 30 minute

Thursday: Lifting

Friday: 2 hrs exercise bike

Saturday: rest

Class #2:

Quantitative Analysis of the Macroeconomy.

Suffice it to say that the instructor began the class saying: “this is the class I wish I had taken as an undergrad.” I have the syllabus in front of me right now, and here are the items that we will be covering in the course: Economic measurement (micro & macro,) Dynamic Programming, Numerical Methods, Log linearlization: Impulse Response functions/computations, applications in Endogenous labor supply, taxes, stochastic technology shocks, etc. Looks like a semester packed with a lot of interesting stuff, no? The course was designed by Ed Prescott, who won the Nobel in Econ in 2004. Pretty cool. Of course, this is all from the Minnesota school of Economics, so things must be taken with a grain of salt.


One of the first assignments in the course is to listen to Prescott’s Nobel lecture, which ought to be interesting. We also have a lot of group projects in this course, which means it’ll involve a lot more of making new friends and developing old friendships. I know 5 or 6 people in this class, which is pretty awesome. Need I mention, all the recommended reading for this class is available online. You know what that means? A $150 stimulus in my pocket. That’s right.


The required reading for this class is: The ABCs of RBCs by McCandless and George; Dynamic Economics: Quantitative Methods and Applications by Adda and Cooper; Dynamic General Equilibrium Modeling: Computational Methods and Applications by Heer and Maußner; Numerical Methods in Economics by Judd; and Applied Computational Economics and Finance by Miranda and Falcker.

Class #3:

Macroeconomic Policy.

This class is taught by Justin Barnette, whose intro macro class I took freshman year. I remember the class being kind of boring freshman year, most likely because it was really easy. This class promises to be pretty fun. It’s going to be very technical, but Justin has promised to incorporate some of the pressing topics of today into the coursework. Based on my memory from 3 years ago, I think he’ll do a quite excellent job.

The class is slated to cover the Neoclassical Growth Model, Ramsey Optimal Fiscal policy, Commodity taxation, Competitive equilibrium under taxation, optimal taxation in NGM, Capital taxes, consumption and labor taxes, Cash in advance models, Ramsey monetary policy, Cash-credit goods model, Utility functions with money, and the New Keynesian model. We also need to write a paper for this class, which I think I’m going to use as my final paper. There is no required reading for this class either, so that puts another $150 in my pocket. Awesome.

Class #4.

Computing in Biology.

This class is going to be a killer. It is taught by Chad Myers who’s a fairly young guy and seems very approachable and easy going. The class, as the name implies, focuses on the computational side of biotechnology. The goals for the course are to understand the current state of technologies/methods in genomics and proteomics, understanding the kind of analysis that can efficiently be performed algorithmically, write scripts to manipulate data and extract info, and learn some basics of programming in the process. This sounds pretty great, as it’ll give me some employable skills which I can extend to other classes as well. GOSH. Why didn’t I take this class before?!

Class #5.

Renewable Energy and the Environment:

This seems kind of like a career exploration course, but I took it because it was a lib-ed requirement. I probably should have gone with the Health informatics course or something. This one proceeded awfully slowly, and I don’t see myself being motivated enough to go to all the classes, especially since everything is going to be so easy. There are apparently tests with 120 available points but only 50 of which will be graded. I feel like I’ve done all of this before, can’t I just get out of it?!