I recall a movie where a guy asks his buddy if his girlfriend is intelligent. The buddy replies “she’s average.” And the other guy responds “average is dumb.” Most people agree. I don’t know if that’s fair overall (I doubt it), but it’s probably true of economics. And this has led lots of people to be skeptical of the Rational Expectations Hypothesis (ratex.)

Mile Kimball and Noah Smith have a nice Quartz column on freshwater vs. saltwater economics. I mostly agree, but take issue with this assertion:

The labels “Freshwater” and “Saltwater” go back to the arguments and new ideas generated by the double-digit inflation in the 1970s. The names refer to the geography of key combatants in that period, when economists at the University of Chicago, Carnegie Mellon University and the University of Minnesota spearheaded the “Rational Expectations Revolution.” They believed that people are very, very smart and sensible in their economic decisions.

And this assertion:

The idea of rationality is both a great strength and the greatest blind spot of economics. Economists routinely pretend in their models that everyone (with the possible exception of government officials) is infinitely intelligent–or at least smart enough to make excellent economic decisions, even in very complex environments. Although there is a touching humility to this pretense (not always matched by humility of economists in relation to the real flesh-and-blood people they interact with), it is not true.

I don’t believe this is the right way to think about ratex. I use the ratex assumption in all my work, and yet I also assume that people suffer from money illusion, and that people are not very smart, nor very good at forecasting. Bennett McCallum has suggested that the term “consistent expectations” better describes what economists are actually doing with the ratex assumption. We assume that if the model predicts X, the public does not predict “not X.” The public’s expectations should be consistent with the model.

To see this distinction more clearly consider the famous example that led to the concept of the “wisdom of crowds.” The statistician Francis Galton attended a country fair where there was a contest of guessing the weight of an ox. He looked at all the guesses, and not surprisingly found that many were very far from the actual weight. It’s not easy to guess the weight of an ox! But even though the individual members of the crowd were not very smart, the crowd was brilliant, as the median guess was within about 1% of the actual weight–even better than the “expert guesses.” In ratex we don’t even assume that much. We don’t even assume that the public is particularly good at predicting the weight of an ox, but rather that if the ox weighs 2200 pounds, the model should not assume that the public believes it weighs 1800 pounds. That the predictions are unbiased. That’s all.

I don’t think individual people are very good at forecasting inflation, but I believe the market is very, very good, better than any single individual in the universe. Thus when modeling the economy it makes sense to assume that the public predicts an inflation rate that is equal to the prediction of the model. Our models from the 1960s failed to do this, and the mistake was quite costly.

As an aside, I am not claiming that surveys of inflation (such as the Michigan survey) will be unbiased. First, they might be wrong on occasion because people make mistakes. But there is also a more subtle problem. The public defines inflation differently than the BLS. The BLS adjusts for quality improvements whereas the public does not. The public is interested in “how much more money you need to live the way we live today.” In the 1950s that was a black and white TV, in the 1980s a color TV, in the 2010 a flat panel HDTV. Thus the public sees TV prices falling less rapidly than the BLS does. So the fact that the Michigan survey of inflation expectations tends to run a bit above the BLS data is not surprising.

Here’s a second misconception about ratex. The models seem to assume that the public would need a deep understanding of concepts like monetary theory, QE, forward guidance, etc. This is not so. The public’s expectations regarding monetary policy are mediated by the financial markets. Thus if QE causes asset prices to rise, the public notices the market response and changes its expectations of economic growth partly on that basis. All we really need to assume is that the asset markets know what is going on (a much weaker assumption) and that the public pays attention to the asset markets–also highly plausible. The dollar fell 6 cents against the euro on the day QE1 was announced, and yet I doubt one person in 100,000 can explain Rudi Dornbusch’s overshooting model (which predicts that sort of effect.)

Financial markets are kind of like Consumer Reports magazine. The average shopper cannot tell that a Mercedes car is better than a Hyundai Sonata with leather seats, even by looking under the hood. They don’t look that different. But the consumer knows the Mercedes is the better car because he or she is aware that experts who have studied cars have reached that conclusion.

Of course none of this proves that ratex is correct, or even a useful assumption. But it should not be rejected merely because it seems to imply an implausibly high level of intelligence on the part of the public. It does not, just as the (similarly misunderstood) Efficient Markets Hypothesis does not assume that individual investors are smart.

And finally, The Kimball and Smith piece seems to suggest that ratex is the crucial difference between the freshwater and saltwater schools. I say, “seems” because in fairness they later note that ratex has worked its way into the saltwater school, and also that sticky wages and prices are a key difference (in my view the key difference.) But the average reader might not pick up those subtle distinctions.

I end up in the same place as Kimball and Smith, leaning toward the saltwater side. But not because there is anything wrong with ratex, rather because the freshwater people tend to underestimate the importance of sticky wages and prices.

HT: Stephen Silver