What they have in common is the “second moment.” In statistics, the first moment of a distribution is the mean, a measure of central tendency. The second moment is the variance, or spread. Politically, their views have a high second moment. If they are asked policy questions during interviews, the differences should be wide.
Shiller is known for looking at “variance bounds” for asset prices. Previously, economists had tested the efficient market hypothesis by looking at mean returns on stocks or bonds. Shiller suggested comparing the variance of stock prices with the variance of discounted dividends. Thus, the second moment. He found that the variance of stock prices was much higher than that of discounted dividends, and this led him to view stock markets as inefficient. This in turn made him a major figure in behavioral finance.
Fama was the original advocate for efficient markets. However, he was an empiricist. He verified an important implication of Shiller’s work: if stock prices vary too much, stock returns should exhibit long-run “mean reversion.” Basically, when the ratio of stock prices to a smoothed path of dividends is high, you should sell. Conversely, when the ratio is low, you should buy. Mean reversion also says something about the properties of the second moment.
Finally, Hansen is the developer of the “generalized method-of-moments” estimator. This is a technique that is most useful if you have a theory that has implications for more than one moment of the distribution. For example, Shiller’s work shows that the efficient markets hypothesis has implications for both the first and second moment (mean and variance) of stock market returns.
Although Tyler and Alex are posting about this Nobel, I think that John Cochrane is likely to offer the best coverage. As of now, Cochrane has written two posts about Fama.
In one post, Cochrane writes,
“efficient markets” became the organizing principle for 30 years of empirical work in financial economics. That empirical work taught us much about the world, and in turn affected the world deeply.
In another post, Cochrane quotes himself
empirical finance is no longer really devoted to “debating efficient markets,” any more than modern biology debates evolution. We have moved on to other things. I think of most current research as exploring the amazing variety and subtle economics of risk premiums – focusing on the “joint hypothesis” rather than the “informational efficiency” part of Gene’s 1970 essay.
Cochrane’s point that efficient market theory is to finance what evolution is to ecology is worth pondering. I do not think that all economists would agree. Would Shiller?
Some personal notes about Shiller, who I encountered a few times early in my career.
1. His variance-bounds idea was simultaneously discovered by Stephen LeRoy and Dick Porter of the Fed. The reference for their work is 1981, “The Present-value Relation: Tests Based on Implied Variance Bound,”’ Econometrica, Vol. 49, May, pp. 555-574. Some of the initial follow-up work on the topic cited LeRoy and Porter along with Shiller, but over time their contribution has been largely forgotten.
2. When Shiller’s Journal of Political Economy paper appeared (eventually his American Economic Review paper became more famous), I sent in a criticism. I argued that his variance bound was based on actual, realized dividends (or short-term interest rates, because I think that the JPE paper was on long-term bond prices) and that in fact ex ante forecasted dividends did not have such a bound. Remember, this was about 1980, and his test was showing inefficiency of bond prices because short-term interest rates in the 1970s were far, far higher than would have been implied by long-term bond prices in the late 1960s. I thought that was a swindle.
He had the JPE reject my criticism on the grounds that all I was doing was arguing that the distribution of dividends (or short-term interest rates) is unstable, and that if you use a long enough data series, that takes care of such instability. I did not agree with his view, and I still don’t, but there was nothing I could do about it.
3. When I was at Freddie Mac, we wanted to use the Case-Shiller-Weiss repeat-sales house price index as a check against fraudulent appraisals. (The index measures house price inflation in an area by looking at the prices recorded when the same house is sold in two different years.) I contacted Shiller, who referred me to Weiss. Weiss was arrogant and unpleasant during negotiations, and we gave up and decided to create our own index using the same methodology and our loan database. Weiss was so difficult, that we actually had an easier time co-operating with Fannie on pooling our data, even though they had much more data at the time because they bought more loans than we did. Eventually, our regulator took over the process of maintaining our repeat-sales price index.
4. Here is my review of Shiller’s book on the sub-prime crisis. Here is my review of Animal Spirits, which Shiller co-wrote with George Akerlof.
Finally, note that Russ Roberts had podcasts with Fama on finance and Shiller on housing.
While forecasted dividends don’t have such a bound, the question is why, since by efficiency they should, and ex post do. It is one thing to claim uncertainty as the cause, even as uncertainty diminishes to insignificance over time, vanishing ex post, but it does highlight the inefficiency of our expectations of uncertainty.
Somewhat similar to how we can define efficient as what happens, like evolution, or we can define it as what we believe should happen only to be forced to reject it when it doesn’t, the former being a definition incapable of being false and the latter a testable hypothesis.
“I contacted Shiller, who referred me to Weiss. Weiss was arrogant and unpleasant during negotiations, and we gave up and decided to create our own index using the same methodology and our loan database. ” – lol, as somebody who negotiates for a living all the time, this is rather common. But, from an economics point of view, isn’t this progress? The availability and drive for substitutes drives down the price of comparable goods. So you should thank Weiss for doing you a favor, indirectly. GDP may have even gone up, though total factor productivity went down.
“In statistics, the first moment of a distribution is the mean, a measure of central tendency. The second moment is the variance, or spread. ”
To clarify, the second moment minus the square of the first moment is the variance.
E(X^2) – [E(X)]^2 = V(X)