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The first major assumption in associated with price anomaly. The   methodology for the S&P/Case-Shiller Home Price Indices applies  smaller weights to home prices that see a large change relative to  the statistical distribution of all price changes in that  metropolitan area. Behind this premise is the assumption that price anomaly is due to changes in home quality. However, when home prices in one region start to quickly depreciate due to the large inventory of foreclosed homes (e.g. in an area with high unemployment), the full effect of foreclosed home prices change is not captured.

The price change of the foreclosed home is far from the statistical distribution of the price change for that region, and therefore is weighted down. Similarly, in hot housing market the quick uptick in home prices is weighted down in the S&P/Case-Shiller Home Price Indices methodology. This assumption smoothes rapid large price changes or artificially inflates the prices in high foreclosure areas. It produces the false belief that prices have stabilized when the actual price changes converge to the statistical distribution. We should not forget that home prices are driven by comparable sale in vicinity of the home in addition to buyer sentiment. price changes. As a result, the sale pair may become subject of being weighed down due to repeat sale high price differentiation. This assumption also smoothes rapid large price changes, artificially deflating home prices in overheated markets.

The second major assumption is associated with high turnover. The methodology for the S&P/Case-Shiller Home Price Indices discards prices for homes that sell more than once within six months (non-arm's-length). There is an assumption that home prices from non-arm- length sales are not market-driven. On the contrary, non-arm- length sale of home that incurred improvements are driven by the market. Excluding sales less than six months after a previous sale results in not accounting for gradual price changes. As a result, the sale pair may become subject of being weighed down due to repeat sale high price differentiation. This assumption also smoothes rapid large price changes, artificially deflating home prices in overheated markets.

The third major assumption is associated with time interval adjustments. The methodology for the S&P/Case-Shiller Home Price Indices also weights home sales pair prices based on the interval between the sales. Behind this notion is the assumption that for a long interval between the same house sales, the home prices changes may be caused my non-market conditions (e.g. house may have experience physical damage, etc.).Home prices are driven by supply and demand, buyer sentiment and other factors (e.g. primary residents, investment or vacation homes; new development regions with high employment; technological, cultural, social, or health benefits; improved property condition, etc.). Applying a time interval adjustment weighting scheme is not justified. Some regions see more dynamic sales; sales are more static in other areas.

The fourth and last major assumption is associated with initial home value. The methodology for the S&P/Case-Shiller Home Price Indices assigns weight equal to the first sale price. To utilize the initial home value weight distorts home prices index for markets that are subject to rapid home price changes and redistribution on both overheated and depressed markets.

The accuracy of a performance analysis for a specific system and conditions depends on the quality of the input data and assumptions that defines the system to be analyzed and its boundaries.  The S&P/Case-Shiller Home Price Indices methodology and its assumptions limit the system in measuring the performance of house price movement. The S&P/Case-Shiller Home Price Indices methodology weights down or eliminates data points that are market driven.

The S&P/Case-Shiller Home Price Indices are more designed to measure the growth in value of residential real estate more towards where the market should be rather than where the market actually is. However, using the S&P/Case-Shiller Home Price Indices with other new indices that capture complete repeat sales of single-family homes could be beneficial. Measuring divergence or convergence between these indices can determine when home prices are overheating or stabilizing.


Housing values skewed

Index can misdirect consumer mood, behavior

The S&P/Case-Shiller Home Price Indices   

Expectation can affect in a positive or negative way the economic reality.  Keynes refers to this “naive” confidence as the “animal spirits”.  False expectations that appear real can misdirect consumer mood and behavior.

Home values are a component of the personal wealth and greatly affect the economy’s consumer and housing sectors. When the price of houses increase, consumer sentiment increases and also the consumers' ability to draw from a much improved home equity.  This boosts spending, creating new demand for goods and services.

Housing prices increase also boost homebuilder confidence and encourage new construction starts, creating new demand for labor and goods. On the other hand, weakness in house prices have a reverse effect on consumer and housing sectors overall.

As a result, an accurate home price index that has a significant impact on the consumer or homebuilder sentiment is much needed. The S&P/Case-Shiller Home Price Indices self-portrait is a reliable and consistent benchmark of housing prices in 10 to 20 major metropolitan areas. It measures the average home price change between arm-lengths repeat sales of single-family home in a particular metropolitan area.

The S&P/Case-Shiller Home Price Indices for May showed continual strength during spring. The unadjusted composite 10-index surged 1.2 percent in May, following a healthy 0.7 percent increase for the previous month.  However, RealtyTrac reported Bank repossessions (REOs) hit a record monthly high for the second month in a row in May, with a total of 93,777 U.S. properties repossessed by lenders during the month—an increase of 1% from the previous month and an increase of 44% from May 2009. All 50 states posted year-over-year increases in REO activity.

Distressed real estate properties will keep prices down. Foreclosures count for almost 30 percent of the all home sales. This is in contrast with the S&P/Case-Shiller Home Price indicators that show price increases or at most price stabilization. These home price indicators are distorted because the index methodology, in this case, weighs down or eliminates data points associated with distressed property sales.

Distorted home price indicators can adversely affect the consumer by increasing expectations of a stabilized housing market. If these false expectations do not become reality, the result will be consumer fear. Managing expectations is an important factor in macroeconomics.

S&P/Case-Shiller indicates that the indices accuracy depends only on the accuracy of its data. However, in addition to the input data, initial assumptions are a very important factor in representing systems' performance and reflecting conditions that need analysis.

Once assumptions are established, the system boundaries and state are confined and the output performance data represent that system-state performance. Therefore, selecting different assumptions can provide different results. When assumptions are far from real market condition, even with accurate input data, the results will misrepresent the analysis intend.


The S&P/Case-Shiller Home Price Indices methodology introduces assumptions to control data quality for the collected sale prices.  The intent is to avoid introducing in the analysis of home prices anomalous prices or idiosyncratic price changes