Einav and Levin write:
Hamermesh recently reviewed publications from 1963 to 2011 in top economics journals. Until the mid-1980s, the majority of papers were theoretical; the remainder relied mainly on “ready- made” data from government statistics or surveys. Since then, the share of empirical papers in top journals has climbed to more than 70%.
Isn’t that remarkable? I certainly was under the wrong impression when I was a Ph.D. student in Berkeley and Mannheim and thought that it’s all about theory and methods. Where does this come from? Maybe it was because one tends to see so much theory in the first year of a full-blown Ph.D. program, which is full of core courses in Micro, Macro and Econometrics, covering what is the foundation to doing good economic research. In any case, my advice to Ph.D. students would be to strongly consider working with real data, as soon as possible. There is certainly room for theoretical and methodological contributions, but this should not mean that one never touches data. At least in theory 😉 everybody should be able to do an empirical analysis. And for this, one has to practice early on. Even if one wants to do econometric theory in the end. But even then one should know what one is talking about. Or would you trust somebody who talks about cooking but never cooks himself? OK, I admit, this goes a bit too far.
After having said this let me speculate a bit. My personal feeling is that one of the next big things and maybe a good topic for a PhD could be to combine structual econometrics with some of the methods that are now used and developed in data science (see the Einav and Levin article along with Varian‘s nice piece). In Tilburg, for instance, we have a field course in big data, by the way, and another sequence in structural econometrics (empirical IO).
At the recent Netspar Pension Workshop I’ve been talking to Susann Rohwedder from the RAND Corporation. We talked about van Gogh and how he spent his youth in Brabant, not far away from Tilburg. The way he was painting at that time can be described as relatively dark and gloomy and not nearly as amazing as what he produced later in his life in the south of France, with the exception of the potato eaters, probably. Here, what dominates, arguably, is good craftsmanship. What I find remarkable is that he learned painting from scratch before moving on and developing something new.
Likewise, also Picasso first learned painting from scratch, producing paintings that were well done, but way more realistic that what he is known for now. Susann remarked that also for modern dancing people often say that one should first learn ballet dancing, in order to get a good grip on technical skills, before moving on. Interesting.
This discussion made me realize that there is a strong communality with my thinking about behavioral economics. There are many people who do research in behavioral economics without ever learning classical economics from scratch, and I always wondered why they do that. Standard economic theory is the simplest possible model we can think of, and it works just fine for many questions we may want to answer. There is of course lots to be gained by studying behavioral aspects of individual decision making, as recently demonstrated once more by Raj Chetty in his Ely lecture. But I think the best way to get there is to first fully understand classical economic theory and only then build on that. In passing, another thing that Chetty pointed out very nicely was that the best way to go about doing behavioral economics is probably not to point out where the classical theory is wrong—any model is wrong, because it abstracts from some aspects of economic behavior in order to focus on others—but to ask the question how we can use the insights from behavioral economics for policy making.