What I learned in econ grad school

I always find it interesting that criticisms of economics education focus more on the graduate side than the undergrad. Consider this broadside by Brad DeLong and Larry Summers:

For Summers, the problem is that there is so much that is “distracting, confusing, and problem-denying in…the first year course in most PhD programs.” As a result, even though “economics knows a fair amount,” it “has forgotten a fair amount that is relevant, and it has been distracted by an enormous amount.”...

The fact is that we need fewer efficient-markets theorists and more people who work on microstructure, limits to arbitrage, and cognitive biases. We need fewer equilibrium business-cycle theorists and more old-fashioned Keynesians and monetarists. We need more monetary historians and historians of economic thought and fewer model-builders. We need more Eichengreens, Shillers, Akerlofs, Reinharts, and Rogoffs – not to mention a Kindleberger, Minsky, or Bagehot.

Yet that is not what economics departments are saying nowadays.

This is interesting because, as someone who never studied econ as an undergrad (I was a physics major), I learned everything I know about macro from my grad courses. If there is an aspiring economist out there whose understanding of macro has been hurt by an overly narrow graduate curriculum, it would be me.

So, what did I learn in my first-year graduate macro course at the University of Michigan?

My first semester was on business cycle theory. (the second semester was all growth theory). We spent a day covering the basic history of the field - the neoclassicals, Keynes, Friedman, Lucas and the RBC people, and finally the neo-Keynesian movement. I recall reading the Summers vs. Prescott debate but not really getting what it was about. From then on it was all DSGE. We did the Ramsey model and learned about Friedman's Permanent Income Hypothesis. We spent a lot of time on RBC. We took a big break to learn value function iteration and how to numerically solve DSGE models by fixed-point convergence. Then we did Barro's model of Ricardian Equivalence, learned a basic labor search model, briefly sketched a couple of ideas about heterogeneity, touched on menu costs, and spent a good bit of time on Q-theory and investment costs. Finally, at the very end of the semester, we squeezed in a one-week whirlwind overview of Calvo Models and the New Keynesian Phillips Curve...but we weren't tested on it.

This course would probably have given Brad DeLong the following reasons for complaint:

1. It contained very little economic history. Everything was math, mostly DSGE math.

2. It was heavily weighted toward theories driven by supply shocks; demand-based theories were given extremely short shrift.

3. The theories we learned had almost no frictions whatsoever (the two frictions we learned, labor search and menu costs, were not presented as part of a full model of the business cycle). Other than Q-theory, there was nothing whatsoever about finance* (Though we did have one midterm problem, based on the professor's own research, involving an asset price shock! That one really stuck with me.).

At the time I took the course, I didn't yet know enough to have any of these objections. But coming as I did from a physics background, I found several things that annoyed me about the course (besides the fact that I got a B). One was that, in spite of all the mathematical precision of these theories, very few of them offered any way to calculate any economic quantity. In physics, theories are tools for turning quantitative observations into quantitative predictions. In macroeconomics, there was plenty of math, but it seemed to be used primarily as a descriptive tool for explicating ideas about how the world might work. At the end of the course, I realized that if someone asked me to tell them what unemployment would be next month, I would have no idea how to answer them.

As Richard Feynman once said about a theory he didn't like: "I don’t like that they’re not calculating anything. I don’t like that they don’t check their ideas. I don’t like that for anything that disagrees with an experiment, they cook up an explanation - a fix-up to say, 'Well, it might be true.'"

That was the second problem I had with the course: it didn't discuss how we knew if these theories were right or wrong. We did learn Bob Hall's test of the PIH. That was good. But when it came to all the other theories, empirics were only briefly mentioned, if at all, and never explained in detail. When we learned RBC, we were told that the measure of its success in explaining the data was - get this - that if you tweaked the parameters just right, you could get the theory to produce economic fluctuations of about the same size as the ones we see in real life. When I heard this, I thought "You have got to be kidding me!" Actually, what I thought was a bit more...um...colorful. 

(This absurdly un-scientific approach, which goes by the euphemistic name of "moment matching," gave me my bitter and enduring hatred of Real Business Cycle theory, about which Niklas Blanchard and others have teased me. I keep waiting for the ghost of Francis Bacon or Isaac Newton to appear and smite Ed Prescott for putting theory ahead of measurement. It hasn't happened.)

Now keep in mind, this was back before the financial crisis, at the tail end of the unfortunately named "Great Moderation." When the big crisis happened, I quickly realized that nothing I had learned in my first-year course could help me explain what I was seeing on the news. Given my dim view of the standards of verification and usefulness to which the theories I knew had been subjected, I was not surprised.

Around that time, I started teaching undergrad macro (under Miles Kimball and others), and was instantly struck by the disconnect between what I was teaching and what I had learned. Intro macro had a lot of history. Explication was done with simple graphs rather than calculus of variations. And undergrad macro was all about demand - never once did I utter the words "technology shock" in class. We taught Keynes and Friedman. Minsky got a shout-out, and we spent a whole week on the fragility of the financial sector, in addition to the week we spent analyzing the 2008 crisis.

In other words, Brad DeLong would probably have approved of the macro course I taught. He would probably think that the bankers, consultants, managers, executives, accountants, and policy researchers who even now are going through life looking at the economy through the lens of that intro macro class have been reasonably well-served by their education.

But all the same, I absolutely don't blame the grad-level professor for teaching what he taught. Our curriculum was considered to be the state of the art by everyone who mattered. Without a thorough understanding of DSGE models and the like, a macroeconomist is severely disadvantaged in today's academic job market; if he had spent that semester teaching us Kindleberger and Bagehot and Minsky, our professor might have given us better ways to think about history, but he would have been effectively driving us out of the macroeconomics profession.

Thus, DeLong and Summers are right to point the finger at the economics field itself. Senior professors at economics departments around the country are the ones who give the nod to job candidates steeped in neoclassical models and DSGE math. The editors of Econometrica, the American Economic Review, the Quarterly Journal of Economics, and the other top journals are the ones who publish paper after paper on these subjects, who accept "moment matching" as a standard of empirical verification, who approve of pages upon pages of math that tells "stories" instead of making quantitative predictions, etc. And the Nobel Prize committee is responsible for giving a (pseudo-)Nobel Prize to Ed Prescott for the RBC model, another to Robert Lucas for the Rational Expectations Hypothesis, and another to Friedrich Hayek for being a cranky econ blogger before it was popular. 

If you want to change economics education, it is to these people that you must appeal. The ghost of Francis Bacon, unfortunately, is not available for comment.

*Update:  I now recall that we also learned the Consumption Capital Asset Pricing Model (CCAPM). So that was about finance too.

Update 2: In my second year I took a macro field sequence, which taught me all about demand-based models, frictions, heterogeneity, and other interesting stuff. I don't want to make it sound like graduate school taught me nothing about how to understand the recession...it taught me plenty. It just all came in the field course...

Update 3: I've decided to remove the professor's name from this post. Although I tried to make it clear (and it should be obvious anyway) that one teacher is in no way responsible for the problems in the field of macroeconomics, I am still worried that some readers might interpret the post to reflect negatively on him, which is the last thing I want.

Update 4: I added a sequel to this post, describing what I learned in my second year.