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: Calculated RiskS&P Concerned about Seasonal Adjustment for House Prices
By Anonymous
Economic data which are affected by the time of the year, or the seasons, are often adjusted to remove these effects to make it easier to identify underlying changes in the economy. Seasonal adjustment increases the unadjusted values in weak months and decreases the unadjusted values in strong months to eliminate regular seasonal patterns while leaving the underlying trend unaffected. For the S&P/Case-Shiller Home Price Indices, S&P reports two data sets ? before seasonal adjustment and seasonally-adjusted. In some recent reports the two series have given conflicting signals, with the seasonally-adjusted series rising month-over-month and the unadjusted series declining. After reviewing the data, the S&P/Case-Shiller Home Price Index Committee believes that, for the present, the unadjusted series is a more reliable indicator and, thus, reports should focus on the year-over-year changes where seasonal shifts are not a factor. Additionally, if monthly changes are considered, the unadjusted series should be used.
The Census X-12 program breaks down the unadjusted S&P/Case-Shiller Home Price index series into three components: trend, seasonal, and irregular. ?Trend? represents the underlying trend in the data, ?irregular? consists of changes with no apparent or regular pattern, and ?seasonal? are the seasonal factors. Chart 2 shows the three series for the S&P/Case-Shiller Home Price 20-City Composite. The seasonal component shows the same regular pattern as on the first chart, and the trend shows the peak and subsequent drop in home prices. Beginning in January 2008, the irregular component became steadily larger. The increase in the size of the irregular component appears to be the cause of the increase in the seasonal factors ...Diana Olick mentioned this today: Even Good Housing Numbers Aren't Adding Up Right and the S&P note credits a recent note by David Rosenberg, chief economist at Gluskin Sheff. I first raised this issue in July 2009. The irregular components are just too large - and are apparently leading to a huge increase in the seasonal factors.
Full post as published by Calculated Risk on April 22, 2010 (boomark / email).
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