This is a question that Professor, and Nobel Prize winner, Alvin Roth
was asked by a reporter from Brazil. The questions and Roth's answers follow:
1) Should the content of economics degrees change? Why? Why not?
I guess you mean should we change what we teach young economists, and of course the only answer is “of course!” What we teach young physicists and biologists and doctors and civil engineers changes as we learn more about those things, and economics is no different.
2) Has the criticism of economics been exaggerated after the 2008 crisis? To what extent is the current debate on content useful?
I think the 2008 crisis has been useful for pointing out that economics is, in many of its parts, still a very young science. For an analogy, think of medicine, which is the part of biology that we most often look to for advice, and is also a young science in many of its parts. Each year we worry that there might be an influenza epidemic due to whatever new strain of flu is observed in Asia that year, and each year vaccines are prepared, in an attempt to avert a disaster like the influenza pandemic of 1918. So far we've been lucky, but it’s not because we have a deep understanding of what could cause another epidemic or how to prevent it. But if another epidemic occurs, we’ll need to rely more on doctors and medicine, not less. So, while we need to understand epidemics better, that’s not a deep criticism of medicine, just an acknowledgement of some of its current limitations. Similarly for economic crises, and economics.
3) What changes should be made?
One of the things we’re devoting more attention to at Stanford is the kind of economic engineering called market design, which pays attention to the detailed rules by which particular marketplaces operate, and to experimental economics, which gives us a tool to better understand how people behave in economic environments.
4) Has economics teaching become too wedded to scientific pretension? Was excessive faith invested in abstract mathematical models?
Abstract mathematical models are very useful, in combination with other kinds of investigation. A lot of my work is devoted to market design, and my colleagues and I build a lot of marketplaces that have some of their ancestry in abstract mathematical models (including some of those explored by the famous Brazilian economist Marilda Sotomayor, in whose honor there is a conference next week). Mathematical models are becoming increasingly important as we start to explore really big data sets, since not only do you need mathematical tools to test hypotheses on data, you need models to even suggest what hypotheses you should be testing. Theory and observation work best in combination…
On this last point one of the top economic theorists in the area of the theory of the firm and contract theory, Oliver Hart,
has noted (and this would be my answer to Matt Nolan's recent
Discussion Tuesday question),
Although theory may not be as prominent as it once was, it remains essential for understanding the (increasingly) complex world we live in. One cannot analyze the bewildering amount of data now available without the organizing framework that theory provides. I would also suggest that one cannot understand the extraordinary events that we have recently witnessed, such as the financial crisis, or make sensible policy recommendations in response to these events, without the organizing framework of theory.
So for those who seem to think data can do everything, and we should therefore stop teaching theory, I don't think so. Empirical work is only as good as the theory underlying it. So, no, running a million regressions and picking the one that confirms your prejudices isn't how you do good economics.
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