Month: February 2014

[M]y own experience is that preparing for an economics exam has more to do with preparing for a musical performance than with preparing for an exam in the humanities. You cannot expect to play a piece of music perfectly the first time you sight-read your way through it. Rather, you will have to do a number of very rough sight-readings of it before you can identify weaknesses in your playing. When you have identified those weaknesses, you will isolate those measures that are the most difficult and work on them until you can play them seamlessly at the right tempo. Once that’s done, you will play the whole piece so as to make sure you can integrate those difficult measures into the easier material to make the whole piece of music flow evenly.

It’s that time of the semester once again, when students are preparing for their first wave of midterm exams. In my own APEC3001 — Consumers, Producers, and Markets course, my students have their first of two midterm next week, on Thursday.

As such, I just sent them the handout I had written a while back about how to do well in econ your econ courses. I thought I would share it again with the world at large; you can find here (link opens a .pdf document).

This past weekend, New York Times columnist Nicholas Kristof caused an uproar among academic bloggers when he published an op-ed titled “Professors, We Need You!,” in which he decried a supposed generalized lack of public engagement among academics. The response from those academics who are on social media was “Just because you don’t read us doesn’t mean we’re not here.”

I don’t want to add to my publicly engaged colleagues’ outrage regarding this last Kristof crisis beyond the fact that in my job, my social media engagement (insofar as it relates to my research and teaching, of course) counts as “outreach,” which is a distinct portion of our annual review, so maybe Kristof should look to land grant institutions for solace: Just on my part of the University of Minnesota campus, my colleague Jonathan Foley finds time to be publicly engaged, even though I’m sure being director of the Institute on the Environment (on top of his own research, teaching, and other committee responsibilities) keeps him very busy.

I did want to comment, however, on how this should not have surprised anyone in light of past experience.

In econometrics, goodness-of-fit measures tell us what percentage of the variation in a dependent variable is explained by the explanatory variables. If you’ve ever taken a statistics class, you are almost surely familiar with the R-square measure. In a regression of, say the logarithm of wage on age, gender, and education level, the R-square is simply the fraction of the total variation in wage that is explained by variation in age, gender, and education level.

Given the foregoing, you’d think R-square is a great measure, right? I mean, it tells you how much of the variation in Y all of your X‘s explain! Yeah, no… R-square is actually not all that interesting, because you can thrown in any variable on the right-hand side — for example, the color of one’s underwear in the log wage regression above — and R-square can only increase, because there is bound to be a (spurious) correlation between the color of one’s underwear and one’s wage. Even the adjusted R-square, which corrects for how many variables there are in X, isn’t that great, since that correction is somewhat arbitrary.