The scholars quoted in the original article sound like they are just engaging in a fancy form of technical analysis, which purports to capture in mathematics the psychology of the crowd, but in almost all cases turns out to be worthless numerology.
The fancy math doesn't explain bubbles any better than [Robert] Schiller's simple driving analogy: there is a big event at an obscure location (let's call it Burning Man, out in the middle of the desert somewhere). People driving to the event are very uncertain of the directions. At a certain intersection, on average 60% of them correctly believe they must turn right and 40% incorrectly believe they must turn left. But they can usually reduce their uncertainty by observing the behavior of others, who are somewhat more likely to be correct than wrong, and altering their [probability estimates] accordingly. Normally this works, but on rare occasions it goes wrong: for example, if the first three cars happen to turn left, the fourth, who had believed with 60% confidence that right was the proper direction, will rationally change his mind and go left. Thus a string of bad luck can make all the cars start going off in the wrong direction, except for those handful of drivers that are strongly confident in their knowledge that one should go right.
Where this analogy goes off the rails as public policy analysis is with the tacit hubris that certain academics from sufficiently elite schools are flying above the whole event in a helicopter and can direct traffic, if only their mathematical analysis is fancy enough. Rather academics and policy makers are in the traffic themselves, generally seeing information biased in ways similar to or even more extreme than the information investors see and act on. In many cases mispriced markets create arbitrage opportunities for truly knowledgeable investors, but analogs to such arbitrage opportunities, i.e. the ability to be rewarded for correcting actual misinformation, are much less prevalent in academic and political policy circles. We should thus expect political policy to be much more prone to biased political fads and herd-following than markets are. Both markets and governments may often take wrong directions, but for politics the inability to correct wrong directions may be endemic. Markets tend to correct themselves, usually in the short run and practically always in the long run, depending on the costs of arbitrage, but there is often no easy way to recognize or correct a political bubble.
Thus, applying the same rational uncertainty assumptions to politics as we do to markets, if we give political decisionmakers the power to "pop" bubbles they think they recognize, they will probably tend to make genuine market bubbles worse, will prevent markets from sending genuine supply and demand signals, and will introduce other extra transaction costs.
Saturday, May 17, 2008
In response to this Wall Street Journal article, describing a number of scholars developing mathematical models of market bubbles, I posted the following comment at Marginal Revolution which is worth reposting here: