Thursday, May 14, 2009

Next top model

Why do economists all end up advocating the same positions, free trade, free markets, and all the other sorts of things that have been shown to have flaws that stunned those very economists when they were confronted with a real economy?

John Kay discusses the limitations of economic models here:

Since the 1970s economists have been engaged in a grand project. The project’s objective is that macroeconomics should have microeconomic foundations. In everyday language, that means that what we say about big policy issues – growth and inflation, boom and bust – should be grounded in the study of individual behaviour. Put like that, the project sounds obviously desirable, even essential. I confess I was long seduced by it.

Most economists would claim that the project has been a success. But the criteria are the self-referential criteria of modern academic life. The greatest compliment you can now pay an economic argument is to say it is rigorous. Today’s macroeconomic models are certainly that.

But policymakers and the public at large are, rightly, not interested in whether models are rigorous. They are interested in whether the models are useful and illuminating – and these rigorous models do not score well here.

Mark Thoma quotes Barry Eichengreen:
What got us into this mess, in other words, were not the limits of scholarly imagination. It was not the failure or inability of economists to model conflicts of interest, incentives to take excessive risk and information problems that can give rise to bubbles, panics and crises. It was not that economists failed to recognize the role of social and psychological factors in decision making or that they lacked the tools needed to draw out the implications. In fact, these observations and others had been imaginatively elaborated by contributors to the literatures on agency theory, information economics and behavioral finance. Rather, the problem was a partial and blinkered reading of that literature. The consumers of economic theory, not surprisingly, tended to pick and choose those elements of that rich literature that best supported their self-serving actions. ... It is in this light that we must understand how it was that the vast majority of the economics profession remained so blissfully silent and indeed unaware of the risk of financial disaster. ...
And from Thoma himself:
There are two uses of economic and econometric models, one is to use the models to understand how the world works, the other is to use the models to forecast. And while, of course, one of the goals of understanding the economy is to be able to predict it, it is simply not something most academic economists do (and the best models for forecasting are not necessarily the same as the best models for learning about how the economy works). Business economists do lots of prediction and forecasting, but academic economists? Not so much. We come along long after events have occurred - e.g. we're still analyzing the Great Depression to some extent - and try to use those events (as well as data from normal times) to try to understand how the economic world works, how policy can improve performance, etc.
[The preceding doesn't explain why academic economists take checks to do just the sorts of things Thoma says they can't do well - I'm sure there's a model to explain that.]

In a nutshell, here's the problem. Economists model what is most tractable to model, and a large economy with small players who can as a group be predicted is reasonably easy to model. It's not perfect; occasionally real people do crazy things like bid up the price of real estate beyond all historical precedent or reason, and as we saw, the models weren't able to cope with the implications of that.

If we look at the assumptions that undergird economic models, we have a roster of somewhat abstracted but perfectly logical ideas, each of which is imperfect if you want to describe real reality, but seem close enough. And, for the middle ground that is usually inhabited by the real world, they seem to work well enough.

Then along comes something extreme, something unprecedented, and the models fall apart - they simply weren't built to take into account things that have never before happened. That the extreme events are well within possibility is something the model builders prefer to ignore.

But there's something else, a feedback effect that is less noted. Once you have built your model, staked your professional flag on it, you're stuck with it and the vision of the world it encompasses. If you model free trade, and it demonstrates that free trade offers magical value-added effects, you then have to buy into a world in which free trade is always good, always right. (That's why even reputable economists refuse to refute a trade flack who makes profoundly misleading statements.)

And with that belief comes a series of subsequent conditioning. Any basic model of free trade only shows that there are gains to the two nations engaging in that trade. It doesn't demonstrate anything at all about the internal distribution of those gains, or some of the obnoxious utility effects. But your whole academic life now depends on free trade, so you have to ignore those things that are unpopular or inconvenient (and, if pressed, you fall back on the "my model doesn't include political effects" or some such hedge).

The real mistake is that we listen to these ivory tower dwellers, these folks who make amazing math while forgetting that it's supposed to model something the rest of us call reality. We shouldn't be amazed that the models failed us in the current crisis; we should be amazed when they tell us anything useful at all.

[For a somewhat more technical explication of models and assumptions, see this from Willem Buiter.]

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