Considering the Case for the Case-Schiller Index

Posted by Donny Mak on Monday, July 30th, 2012 at 1:00am.



By: Alan Aptheker

Based on this title, you may think I’ll be discussing the excessive use of alliteration in the titles of articles about the housing industry.  No, it’s about Standard & Poor’s Case-Shiller Index, or S&P/Case–Shiller, or “CSI.” It’s a U.S. national home price set of indices that measures the average change in the total value of all existing single-family homes, in the aggregate, in the U.S. The first thing we can all agree upon: some studies just happen to end up with a very cool acronym.

Karl Case, Robert Shiller and Allan Weiss developed the CSI in the 1980s to come up with a more meaningful metric with respect to housing prices, that is, better than your basic monthly snapshot. 

We look to the CSI to gauge how the housing market is doing. But how does it do it, and in the end, what does it really say.  If you want to know every excruciating detail, go to the Standard & Poor’s CSI website page, bring some Excedrin, and that son or daughter who’s doing well in calculus. There’s a 39 page explanation of the methodology.  Good luck with that.

The CSI includes 23 “things” in its measurements: an analysis of 20 large metropolitan areas, and three composites – that’s data processed by a complex algorithm, or as let’s just say all melted together, to arrive at National, 10-city and 20 city numbers. Put all 23 things in a blender, and you get the S&P/Case–Shiller Index. Every month, you can see changes in the relative value of residential real estate represented by a single number. For example, at the end of January, 2012, it was down 1.3 percent. One can only “infer” from the data what’s really going on, but the CSI has its good points and its not-so-good points. 
 
  • Good: First of all, it’s better than just a monthly snapshot that compares one month to another. It’s based on a three month rolling average, that is, at the end of every month, you take the monthly averages from three months ago, two months ago and last month, average out the averages, and you get a three month rolling average. 
     
  • Not-so-good: the data is two-months old. The 1.3% reported in the news in January 2012 was the three month rolling average calculated at the end of November, 2011. These things take time.
     
  • Based on this title, you may think I’ll be discussing the excessive use of alliteration in the titles of articles about the housing industry.  No, it’s about Standard & Poor’s Case?Shiller Index, or S&P/Case–Shiller, or “CSI.”
     
  • Good: it’s based on real numbers, not projections or estimates. They go off of actual public filings. It only counts the actual sale of an actual house. Not what we think it might sell for, or when it might sell, but what the price was at closing. Solid.  So when you think about it, it’s not based on one price of a home. It’s based on two prices of the same home, or apples to apples. It compares the first sales price to the resale price.  (Let’s say you’re a house. You have to be sold twice for the CSI to count you).   
     
  • Not-so-good: using the actual, official sales data misses some things that could be important to the trending of home sales: It doesn’t count property transfers between family members. It skips over transactions where the property type changed, e.g., properties originally recorded as single-family homes that are later recorded as condominiums. CSI doesn’t include prices for new construction, co-ops or apartments and multi-family homes. What about when two parties agree on the price, sign a contract, and it doesn’t close for another three months? Not in there.
  • Good: A sales contract can implode before closing, and still, it will only be counted by the CSI when it actually closes – when the deal is really done.


Good, bad, not-so- good - no U.S. Housing Study is perfect, but kudos to Case, Shiller and Weiss for coming up with a better mousetrap. Conclusion: the Case-Shiller data is great to look at over long periods of time to see long term trends. It’s like those 3-D picture books.  You stare at it long enough, you start to see something.

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