A quick look at various news sites as well as the press release say essentially the same thing:
Home Prices Continue to Rise in May 2012
According to the S&P/Case-Shiller Home Price Indices
New York, July 31, 2012 – Data through May 2012, released today by S&P Dow Jones Indices for its S&P/Case-Shiller Home Price Indices, the leading measure of U.S. home prices, showed that average home prices increased by 2.2% in May over April for both the 10- and 20-City Composites.
Which makes the whole thing slightly funny, because the statements are so easy to verify.
With these kinds of data, you get two series: Seasonally adjusted and not seasonally adjusted. Seasonal adjustments are supposed to control the regular month by month ebb and flow of activity through the year.
When using data, it is important to always compare apples to apples. Which means, if you are going to compare May sales to April sales, you must seasonally adjusted values.
If you don't use the seasonally adjusted data, you can only compare May 2012 to May 2011 to May 2010, and compare April 2012 to April 2011 to April 2010 etc.
So, what was the change in the seasonally adjusted composite-20 index value between April 2012 to May 2012? Easy: (139.93 - 138.67) / 138.67 = 0.91%.
How did they come up with the 2.2% value? Well, they committed the cardinal sin of using the not-seasonally adjusted data to compare month-to-month changes.
Comparing the May 2012 value of 138.96 of the not-seasonally adjusted composite-20 index to its May 2011 value of paints a different picture: Home prices fell by 0.66% between May 2011 and May 2012.
And, the unadjusted value in May 2012 is the same as the unadjusted value in May 2009 (and they are down 31% compared to May 2007).
I find this rather odd: The people at S&P surely know the point of seasonal adjustments and they are capable of putting together some charts. Heck, even the enemy of algebra ought to be able to understand this.
So, I must ask, why?