Doug Kass is on a mission! He has posted the same chart four times in the last ten days and mentioned it even more often. He has also cited it on CNBC appearances and probably other places. Here is the key point, drawn from his column today (subscription required), entitled "The Worst Is Yet to Come: A Second Downleg in Housing":
I have tried to document the clear relationship of mortgage availability to personal consumption expenditures, which occurs in every cycle (up and down). You simply can't deny this relationship.
He sees the following chart as powerful evidence of some forthcoming bad news. [click on all charts to enlarge.]
At "A Dash" we shall take the other side of Doug's mission -- since he is so powerful, let's call it Mission Impossible. We are going to show that the evidence he presents should not persuade one of his conclusion.
Doug Kass is the highly influential writer of The Edge on Street Insight, theStreet.com's useful product aimed at market professionals. Doug also gets plenty of exposure on CNBC, in Barron's, and other places. He modestly states that this is because there are so few bears left. In fact, he has an appealing delivery both on television and in writing. He is not just another loud, arguing voice and is quite persuasive. Personally, I read everything he writes, but I use his information carefully. Somehow he has been successful in managing his fund while being on the wrong side with his economic and market forecasts for several years. How does he do it? He does a lot of trading against his overall short position, makes some great calls, and takes profits on shorts when he is right.
The Chart -- A First Impression
When one wishes to make a convincing argument, adjusting the scales of a chart to fit the most visible features makes a powerful impression. The Kass chart is scaled to emphasize the two "V" troughs and the current plunge in mortgage availability. Whoever did this chart was familiar with Tufte's classic work (featured in our reading list).
An Objective Look
An expert view of the Kass chart would include looking for areas of no fit as well as the "V" troughs and also choosing a scale level that reflected the overall patterns, without undue emphasis on any feature. With the supporting help of Renae, we found the underlying data and produced the alternative views.
This is exactly the same chart with a different visual emphasis. The emphasized areas of "no fit" show that there is often no "relationship".
Another approach is to allow the Excel defaults to choose the scales, instead of trying to emphasize the two troughs. Here is what one finds.
While the general shapes are similar, the discrepancies are very obvious.
Regression and Correlation
In his Kudlow appearance, Doug claimed a very high correlation for this relationship. (My TIVO window scrolled off before I could replay it, but it sounded like he said .9). Let us examine the regression equation, the correlation, and the corresponding scatter plot.
The overall regression equation has an r-squared of .19, meaning that one variable "explains" about 20% of the variation of the other. Nearly all of the explanatory power comes from the handful of data points on the left -- the outliers. Without these points there is little relationship -- a data cloud. This suggests the need for examining the influential cases.
Looking at the Data
At "A Dash" we have maintained the importance of considering the variables in a relationship. We insist on asking what is being measured, how good the measures are, and specifying a causal model. We also have argued that it is important to select the right time frames for analysis, seeking enough similar cases from history, while not reaching back too far. Let us apply these tests to the Kass bivariate relationship hypothesis.
The alleged dependent variable is personal consumption, taken from the Department of Commerce. The causal variable is availability of mortgage credit, taken from a survey conducted by the Fed.
The Fed survey included 55 banks, so a shift of ten banks to "somewhat tightened" created the 18% decline showed in the chart. No bank officer reported a "substantial tightening". Moreover, it does not indicate whether standards were already tight or loose -- something that relates to size of mortgages as well as applicant qualifications. Here is the key part of the question asked:
If your bank's credit standards have not changed over the relevant period, please report them as unchanged even if the standards are either restrictive or accommodative relative to longer-term norms. If your bank's credit standards have tightened or eased over the relevant period, please so report them regardless of how they stand relative to longer-term norms.
The result is that we know little about whether the current standards are high, medium, or low by historic norms. We know that ten banks somewhat tightened mortgage standards, none substantially, and forty-five did not.
The Time Period
Kass asserts a relationship that occurs in "every cycle". The problem is that his data reports only one "cycle". The reason is that the Fed survey only goes back to 1990, so this is all of the available data. We do not know about any history before 1990.
Instead of a powerful chart showing many cycles, the proposition is much simpler. In the early nineties banks became somewhat more restrictive in mortgage lending at the same time personal consumption was declining. The question confronting those examining the data is whether the current situation is similar to exactly one prior case. That is all we have.
The Causal Model
When asserting causation, it is important to specify the causal model and to explain the relationship. We are mystified by Doug Kass's assertion. If a bank is more reluctant to grant a fresh mortgage, how does that affect consumption? The potential buyer remains a renter, or continues to live in an existing home.
If the argument is that refinancing is more difficult, we have a different problem. There are no data on that subject. It also does not speak to existing lines of credit, or how those might be used.
Most importantly, the mortgage variable does not lead the consumption variable. The Kass chart shows a simultaneous change. As we have pointed out in a typical example, this is often the case when there is a spurious relationship. Simply put, this means that some third (unspecified) variable is the underlying cause of two different effects. If one merely looks at the effects, there is some apparent correlation. In 1990, a weakening economy probably caused both effects.
Briefly put, the relationship in the one relevant prior case (a few points in the early nineties) shows two variables that are a result of something else.
The current mortgage market is much different from that of 1990. Nearly everyone -- especially Doug Kass -- believes that recent standards have become quite loose. Some tightening is a logical reaction. There is nothing in the data he presents that shows that this should result in a decline in consumer spending.
Such a decline might occur, of course. There may be other reasons to link housing and the economy. That is beyond the scope of Doug Kass's argument and this response. The point here is that the data in the original Kass chart do not support his conclusion.