On the age of empiricism

May 1, 2009 in Economics,Finance,Math

Caught this on Rortybomb - Barry Eichengreen has penned an excellent piece on the role of models in academia and finance, as well as the growing importance of empiricism (a point with which I particularly empathize).  An excerpt:

Maybe so. But amid the pervading sense of gloom and doom, there is at least one reason for hope. The last ten years have seen a quiet revolution in the practice of economics. For years theorists held the intellectual high ground. With their mastery of sophisticated mathematics, they were the high-prestige members of the profession. The methods of empirical economists seeking to analyze real data were rudimentary by comparison. As recently as the 1970s, doing a statistical analysis meant entering data on punch cards, submitting them at the university computing center, going out for dinner and returning some hours later to see if the program had successfully run. (I speak from experience.) The typical empirical analysis in economics utilized a few dozen, or at most a few hundred, observations transcribed by hand. It is not surprising that the theoretically inclined looked down, fondly if a bit condescendingly, on their more empirically oriented colleagues or that the theorists ruled the intellectual roost.

But the IT revolution has altered the lay of the intellectual land. Now every graduate student has a laptop computer with more memory than that decades-old university computing center. And she knows what to do with it. Just like the typical twelve-year-old knows more than her parents about how to download data from the internet, for graduate students in economics, unlike their instructors, importing data from cyberspace is second nature. They can grab data on grocery-store spending generated by the club cards issued by supermarket chains and combine it with information on temperature by zip code to see how the weather affects sales of beer. Their next step, of course, is to download securities prices from Bloomberg and see how blue skies and rain affect the behavior of financial markets. Finding that stock markets are more likely to rise on sunny days is not exactly reassuring for believers in the efficient-markets hypothesis.

The data sets used in empirical economics today are enormous, with observations running into the millions. Some of this work is admittedly self-indulgent, with researchers seeking to top one another in applying the largest data set to the smallest problem. But now it is on the empirical side where the capacity to do high-quality research is expanding most dramatically, be the topic beer sales or asset pricing. And, revealingly, it is now empirically oriented graduate students who are the hot property when top doctoral programs seek to hire new faculty.

Not surprisingly, the best students have responded. The top young economists are, increasingly, empirically oriented. They are concerned not with theoretical flights of fancy but with the facts on the ground. To the extent that their work is rooted concretely in observation of the real world, it is less likely to sway with the latest fad and fashion. Or so one hopes.

The late twentieth century was the heyday of deductive economics. Talented and facile theorists set the intellectual agenda. Their very facility enabled them to build models with virtually any implication, which meant that policy makers could pick and choose at their convenience. Theory turned out to be too malleable, in other words, to provide reliable guidance for policy.

In contrast, the twenty-first century will be the age of inductive economics, when empiricists hold sway and advice is grounded in concrete observation of markets and their inhabitants. Work in economics, including the abstract model building in which theorists engage, will be guided more powerfully by this real-world observation. It is about time.

Rortybomb does have one point with which I disagree, that being that VaR is a statistical (i.e. empirical) rather than theoretical figure. This is true only inasfar as the VaR is a historical VaR calculated from past returns; estimating a probable future VaR (as banks do in their financial disclosures) is a highly theoretical exercise in estimating the copula of portfolio returns - both the marginal distributions of each asset as well as the dependence structure.  A minor point but, I think, an important distinction.  Anyway, check out the full piece, it really is one of the best essays I've read in a while.

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