Robert Shiller, Nobel Laureate

Robert Shiller spent much of his career at Yale University.  He is a famous economist for his analysis of speculative bubbles and price overreaction to new information, first in stock markets and then later in real estate markets.  He has been a leading candidate for a Nobel Prize for some time now.

Here is Shiller’s home page.  Here is Shiller on Wikipedia.  Here are short columns by Shiller on Project Syndicate.  He also writes regularly for the Sunday New York Times, and some of his columns are here.  Here is a 2005 David Leonhardt profile of Shiller.

Shiller’s most famous piece is from 1981, “Do Stock Prices Move Too Much to be Justified by Subsequent Changes in Dividends?”  Here Shiller developed the very important “variance bounds test” for scrutinizing the rationality of stock prices.  The intuition runs like this.  Let’s say you were trying to forecast the result of Miami Heat vs. San Antonio Spurs.  The results of the actual games would show higher variance than your forecast, which would reflect your single best guess of which team is better.  But in reality sometimes Miami will win, sometimes the Spurs will win, by a little, by a lot, etc.   That is a basic principle of forecasting rationality, in other words that actual outcomes should show higher variance than forecasts.  But now consider stocks.  According to Shiller, the “actual results” — namely the realized returns — are the dividends.  The forecasts of the dividends are stock prices.  Yet dividends hardly vary, while stock prices move around a great deal.  It would appear that stock prices violate this variance bounds test because the forecast has a higher variance than the actual outcomes.  (For some push back on this, see the papers by Allan Kleidon from the 1980s.  For non-stationary time series for instance a variance bounds test may not hold because the population variance, as opposed to the sample variance, is infinite and thus undefined.  Another point is that stock prices may move because the stock is an option on the real assets of the firm, which have changing value, whether or not dividends ever vary and of course dividends are consciously smoothed.)

Shiller also extended his variance bounds test to the term structure of interest rates, for instance in his work with John Campbell.  Think of long rates as being forecasts of future short rates.  According to a variance bounds test, the long rates should be less volatile, but in market data we generally observe the opposite.  This again raises the possibility that markets are overreacting to new information rather than estimating values rationally.

You will note that some of Shiller’s models imply systematic returns to betting against the market and expecting some long-run mean reversion.  If the market is overreacting to new information right now, over some longer time horizon it will have to return closer to fundamental values.  So if you, as an investor, have enough patience, you should (on average) bet against short-term market movements.  Of course this hypothesis has received a good deal of empirical testing and perhaps there is some (slight) long run mean reversion, although it is not clear how much those gains can be captured after transactions costs are paid.  In any case, there may be some excess returns to buying right after prices have fallen, contrary to what a strict interpretation of efficient markets theory would suggest.

Shiller’s 1984 piece, “Stock Prices and Social Dynamics,” with Ben Friedman, started laying out a “trends” and “fads” approach to stock and also housing prices.  This integration of psychology and economics might help explain why markets appear to overreact to short-term information.

One intriguing side of Shiller is his advocacy of derivatives and prediction markets to help individuals better hedge risk.  On that see Shiller’s book Finance and the Good Society.  Shiller for instance would like to see explicit futures or forward markets in gdp, and individuals could hedge with those markets to bet against bad business prospects.  One also can imagine laborers insuring their future income by transacting in indicators of economic health.  Shiller has raised the idea of using housing price indices to help hedge against home price risk, whether for future sellers or future buyers.  This aspect of Shiller’s thought has perhaps disappointed some of his fans who have wanted him to take a more critical attitude toward finance.  Shiller instead thinks that a properly reconstituted financial sector could bring the world very significant gains, typically through superior risk hedging.  It remains a general puzzle why so many of these markets continue not to exist, and when they are sometimes started up, they fail to attract sufficient liquidity.

Shiller’s greatest practical contribution is the Case-Shiller housing price index, described by Wikipedia like this:

The Standard & Poor’s Case–Shiller Home Price Indices are repeat-sales house price indices for the United States. There are multiple Case–Shiller home price indices: A national home price index, a 20-city composite index, a 10-city composite index, and twenty individual metro area indices.

This index has become a staple of real world financial analysis and discussion and it is reported in the financial press on a regular basis.

Shiller is also famous for having predicted the housing price bubble which played an important role in America’s Great Recession.  Here is one of his early pieces on that issue.  One of his research innovations was the common sense idea of simply asking home buyers what kind of future price gains they were expecting and then analyzing whether those expectations were realistic (hint: they weren’t).

Here is an on-line course with Shiller, on finance.


Alex called this one last time. That's either ahead of the curve or terrible timing ;)

He deserves it.

Don't forget the Cyclically Adjusted Price Earnings Ratio, which is quite good at predicting returns over the long term.

That being said, I'm disappointed it went to asset pricing people. I think it's by far the weakest part of financial economics, and everything involving SDFs borders dangerously on pseudoscience.

You can take his finance class at Yale for free.

Here is the link:

Shiller's work is great, but I disagree with the ''predicted the housing bubble and crash'' point. If someone predicts an event every year and it eventually happens, how good a prediction is it? That is, in a forecast calibration sense, Shiller was lousy (as we all are).

So I strongly disagree with the idea Shiller was a better forecaster than anyone else. However, he *did* explain very well, and correctly, why he thought there was a bubble, what he meant by "bubble", and why it would crash. So his analysis was very good, even though his timing was no better than anyone else's.

Give him a little more love dude. Plenty of folks didn't even recognize there was a bubble. "Home prices never go down"

Well, that 'early piece' is from 2003 and it doesn't look like we ever really got below that level, so not sure we can give him much credit. He called a bubble when we were at a low. (Or is this still a bubble?)

If he were Ben Bernanke, we would just conclude that all that means is that it is THAT hard.

Also his new Coursera course on financial markets starts Feb 2014:

At the risk of getting in a little over my head in something which is not my main area of research, I would say this:
1. Shiller's variance bounds test was just wrong. The reasons are exactly the ones given by Tyler. The prices are not stationary and the dividends are not the only way to get money out of the firm.
2. Shiller's variance bounds test was still an immense contribution because it led the way to the studies that nailed the question Shiller asked. The question “Do Stock Prices Move Too Much to be Justified by Subsequent Changes in Dividends?” was the right question to ask (if you change dividends to cash flow or something), a variance bounds framework was the right way to frame it, and so the later scholars were kind of crossing the t's and dotting the i's - which was of course crucially necessary.

This is basically the same idea as in JackPQ's comment. Shiller is defining something very carefully and enabling you to test it - even if his particular test may not turn out to be the best one.

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