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.
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
