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«DiscoVeriNg HomelessNess Volume 13, Number 1 • 2011 U.S. Department of Housing and Urban Development | Office of Policy Development and Research ...»

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The Office of Federal Housing Enterprise Oversight (OFHEO) was the original agency that created the HPI in 1996. This office was incorporated in the FHFA in 2008, based on the Housing and Economic Recovery Act of 2008.

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The FHFA HPI measures the average price change in the sales or refinancing of the same single-family homes with mortgages purchased or securitized by the Federal National Mortgage Association (Fannie Mae) and the Federal Home Loan Mortgage Corporation (Freddie Mac) in a particular geographical area (Calhoun, 1996). The HPI methodology is a modified version of the weighted-repeat sales methodology proposed by Case and Shiller (1989).

One advantage of the HPI is the control it provides for differences in the quality of the homes in its sample, given that the data come from repeated transactions on the same property (Calhoun, 1996). Further, the FHFA provides two types of HPI with large national samples: a purchase-only index (based only on sales prices) and an all-transactions index (based on sales prices and appraisal valuations for refinancing purposes) (FHFA, 2010b).

The all-transactions HPI (the HPI) has detailed temporal and spatial coverage at the metropolitan area level and it is available free of charge on the FHFA website. The FHFA estimates both the purchase-only HPI and the HPI for the United States, the 9 census divisions, the 50 states, and the District of Columbia. Only the HPI has full coverage of the 366 metropolitan areas in the United States, however, the purchase-only HPI is being calculated only for the largest 25 metropolitan areas. For 11 large metropolitan areas, the FHFA estimates the HPI for their metropolitan division components, going below the metropolitan area level.4 The HPI estimates at both the metropolitan area level and metropolitan division level are based on large samples, with at least 1,000 accumulated transactions (FHFA, 2010b).

The FHFA estimates quarterly the HPI at the metropolitan area level, not seasonally adjusted, and it reports it with a 2-month lag. The HPI equals 100 points for all the metropolitan areas in the first quarter of 1995. The HPI quarterly time series extends back to 1975 for most of the metropolitan areas, depending on the fulfillment of the 1,000 accumulated transactions criterion.

The FHFA revises the historical estimates each quarter, based on updated information provided by Fannie Mae and Freddie Mac and the revised definitions of the metropolitan statistical areas from the Office of Management and Budget (OMB) (FHFA, 2010b). This quarterly revision allows for the comparability of the HPI estimates for a metropolitan area for all the available quarters.

Two major weaknesses of the HPI during the latest housing bubble were the low price ceiling of its underlying data and the limitation to houses backed by Fannie Mae and Freddie Mac financing.

The FHFA calculates the HPI based on mortgage data from Fannie Mae and Freddie Mac, capped at relatively low ceilings during the boom years of 2004 to 2007. Although the Fannie Mae mortgage limit for a single unit home was $417,000 in 2007, the median sale price for an existing single-family home was more than $800,000 in the San Jose and San Francisco metropolitan areas (Fannie Mae, 2009; NAR, 2008).5 Consequently, the HPI did not capture the highest house prices The FHFA calculates the all transactions HPI by metropolitan division for the following metropolitan areas: BostonCambridge-Quincy, MA-NH; Chicago-Naperville-Joliet, IL-IN-WI; Dallas-Fort Worth-Arlington, TX; Detroit-WarrenLivonia, MI; Los Angeles-Long Beach-Santa Ana, CA; Miami-Fort Lauderdale-Miami Beach, FL; New York-Northern New Jersey-Long Island, NY-NJ-PA; Philadelphia-Camden-Wilmington, PA-NJ-DE-MD; San Francisco-Oakland-Fremont, CA;

Seattle-Tacoma-Bellevue, WA; and Washington-Arlington-Alexandria, DC-VA-MD-WV (FHFA, 2010b). For the definition of metropolitan division, see OMB (2009).

Beginning with 2008, the FHFA allows Fannie Mae and Freddie Mac to purchase or securitize mortgages up to $729,750 for one-unit properties in high-cost areas in the contiguous United States (Fannie Mae, 2009).

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during the latest housing boom and the spatial concentration of these high house prices. Further, an analysis of the differences between HPI and the S&P/Case-Shiller showed that the inclusion of houses with alternative financing diminished the HPI appreciation rates during the boom years (OFHEO, 2008a).

The HPI faces other limitations. This house index focuses only on existing single-family houses, not reflecting price changes in the sales or refinancing of other types of housing properties and new houses. Further, due to its appraisal component from refinancing transactions, the HPI tends to lag, because the appraisals are based on historical data. The quarterly revisions of the historical estimates of the HPI limit the comparison of HPI changes to the same quarterly dataset. For example, the HPI estimate for the Denver metropolitan area for the first quarter of 2008 was 201.83, as released in May 2008, while the revised HPI estimate for the first quarter of 2008 was 199.83, in May 2010 for the same metropolitan area (FHFA, 2010c; OFHEO, 2008b). A recent analysis of the revisions of the HPI estimates shows that the updates tended to moderate the longer term changes in the index from the first quarter of 2005 through the third quarter of 2009 (FHFA, 2010a).

The S&P/Case-Schiller® Home Price Index (S&P/Case-Schiller®) measures the average price change in the sales of the same single-family homes in a particular geographical area (Standard & Poor’s, 2009). It employs a weighted-repeat sales methodology based on Case and Shiller (1989).

The S&P/Case-Schiller® has several advantages, given its design. Similar with the HPI, the S&P/ Case-Schiller® is a “constant quality” house price index, because it is based on paired sales transactions of the same property. Further, the S&P/Case-Schiller® reflects only house price changes resulting from sales, avoiding the appraisal lag affecting the HPI. Its underlying data is gathered from all publicly available information at local recording offices and accumulated in rolling 3-month periods. The S&P/Case-Schiller® is estimated based on a 3-month moving average that allows for the correcting of any delays in the collection of the paired sales transactions (Standard & Poor’s, 2009).

The S&P/Case-Schiller® has great temporal coverage and is available free of charge on the Standard & Poor’s website (Standard & Poor’s and Fiserv, Inc., 2010a). Fiserv, Inc., estimates the index monthly for 20 metropolitan areas and 2 metropolitan composite indices and quarterly reports for the United States. It releases both seasonally adjusted and not seasonally adjusted estimates of the index. The S&P/Case-Schiller® equals 100 points in January 2000 for its metropolitan area indices.

The base period for the U.S. index is the first quarter of 2000. The S&P/Case-Schiller® time series extends back to January 1987 for 14 of the metropolitan areas and 1 metropolitan composite index (Standard & Poor’s and Fiserv, Inc., 2010a).

The S&P/Case-Schiller® signaled the decline in house prices earlier than the HPI. As exhibit 1 illustrates, the S&P/Case-Schiller® showed an earlier and more abrupt shift in the national housing market than the HPI. This contrast between the two house indices was evident across large metropolitan areas, such as Miami and Las Vegas (see exhibits A-1 and A-2).

The S&P/Case-Schiller’s® major weakness is the limited amount of geographical detail and is available

for only 20 metropolitan areas. Fiserv, Inc., originally estimated the index for 10 metropolitan areas:

Boston, Chicago, Denver, Las Vegas, Los Angeles, Miami, New York, San Diego, San Francisco,

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Exhibit 1 Comparison of Four-Quarter Appreciation Rates of the HPI and the S&P/CaseSchiller® for the United States, First Quarter of 1987 Through First Quarter of 2010 20% 15% 10% 5% 0% – 5% – 10% – 15% – 20%

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1– 1– 1– 1– 1– 1– 1– 1– 1– 1– 1– 1– 1– 1– 1– 1– 1– 1– 1– 1– 1–

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and Washington, D.C. It later added another 10 metropolitan areas: Atlanta, Charlotte, Cleveland, Dallas, Detroit, Minneapolis, Phoenix, Portland (Oregon), Seattle, and Tampa. Although most of the indices follow the OMB’s definition of a metropolitan statistical area, the S&P/Case-Schiller® for the Chicago area is calculated for the Chicago-Naperville-Joliet, IL, metropolitan division and the index for New York is based on a customized metropolitan area, including select New York, New Jersey, and Connecticut counties (Standard & Poor’s, 2009). Further, the S&P/Case-Schiller® U.S. index does not include house price data from 13 states, and it has incomplete data from another 29 states (Leventis, 2007; Standard & Poor’s, 2009).6 The S&P/Case-Schiller index for the United States is a composite index of the nine census divisions, based on accumulated data from the states. Standard & Poor’s does not collect data from the following states: Alabama, Alaska, Idaho, Indiana, Maine, Mississippi, Montana, North Dakota, South Carolina, South Dakota, West Virginia, Wisconsin, and Wyoming. It has incomplete coverage for the following states, at different rates: Arizona, Arkansas, California, Colorado, Delaware, Florida, Georgia, Illinois, Iowa, Kansas, Kentucky, Louisiana, Michigan, Minnesota, Missouri, Nebraska, Nevada, New Mexico, New York, North Carolina, Ohio, Oklahoma, Oregon, Pennsylvania, Tennessee, Texas, Utah, Virginia, and Washington (Standard & Poor’s, 2009).

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Another potential drawback of the S&P/Case-Schiller® is its limited focus on existing single-family houses, not reflecting price changes in the sales of other types of housing properties and new houses.

The adjusted version of the FHFA House Price Index (so-called “adjusted HPI”) was created in July 2007 by the OFHEO to analyze the possible sources of divergence between the change rates of the HPI and the S&P/Case-Schiller® (Leventis, 2007). The adjustment methodology of the HPI to the S&P/Case-Schiller® was improved in 2008 (OFHEO, 2008a). The method is stepwise, resulting in an adjusted HPI that covers the same counties as the S&P/Case-Schiller® in 10 metropolitan areas, excludes appraisals, puts less weight on homes that have lengthy intervals between valuations than HPI, includes single-family homes with alternative financing, uses value weighting, excludes some of the HPI data that are not in the DataQuick data set, and uses the same data filters as the S&P/Case-Schiller® (OFHEO, 2008a).

The adjusted HPI allowed for the identification of the three main causes for the smaller change rates of the HPI in comparison with the S&P/Case-Schiller®: the appraisal component of the HPI, too much weight placed on the transactions of homes with lengthy intervals between valuations, and the omission of low and moderately priced homes with financing other than from Fannie Mae and Freddie Mac (OFHEO, 2008a).

Because the FHFA estimates the adjusted HPI only for the original 10 metropolitan areas of the S&P/Case-Schiller® and reports its four-quarter appreciation rate occasionally, the adjusted HPI is not an appropriate index to use in a spatio-temporal analysis of house price trends at the moment.7 This index was constructed by OFHEO (and later FHFA) to compare the HPI with the S&P/ Case-Schiller®.

The Zillow Home Value Index (Zillow index) is the median Zillow estimate (Zestimate) of prices of all the houses in a given geographical area. A “Zestimate” is Zillow’s estimate of the current market value for a home (Zillow.com, 2010a). Zillow generates Zestimates for more than 70 million homes and has data for an additional 20 million homes (Zillow.com, 2010b).

The main advantage of the Zillow index is the detailed and broad geographical coverage. As of July 2010, Zillow kept track of 200 metropolitan areas (as defined by OMB) and estimated the Zillow index for 126 metropolitan areas for May 2010, based on available public data (Zillow.com, 2010c). The Zillow index is calculated also at the ZIP Code, county, metropolitan area, state, and national levels for all homes, for single-family homes, and for condominiums in a specific area.

It estimates the market value of all houses in a geographical area, not only of sold houses (Zillow.com, 2010a).

A primary disadvantage of the Zillow index is that it does not stand up to academic scrutiny because Zillow estimates the market value of a house using a proprietary valuation model. Zillow uses public data on house attributes and actual sale prices to develop the model (Zillow, 2010b).

Although Zillow reports month-over-month change, quarter-over-quarter change, year-over-year change, and 5- and 10-year annualized changes together with its latest estimated monthly Zillow index, it does not publicly provide the historical time series of house prices.

The OFHEO reported a time series of the adjusted HPI (March 1991–March 2007) in July 2007, but this index does not use the improved adjustment methodology, employed currently by FHFA (OFHEO, 2007b).

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The NATIONAL ASSOCIATION OF REALTORS® Median Home Price (NAR median home price) is the median sales price for existing homes that are at least 1 year old, based on transactions conducted through a real estate agent and those made by the owner (Bishop, 2008). The NAR calculates an index for single-family homes and one for condominiums and co-ops, reporting on a quarterly basis for metropolitan area level data and on a monthly basis for both the United States and the census region levels of data (NAR, 2010a).

The NAR median home price has broad spatial coverage at the metropolitan area level; it is estimated for 160 metropolitan areas, as defined by OMB. Given that the NAR existing house sales database extends back to 1968, the NAR median home price might have also a long time series, at least for single-family homes.

The main limitation of the NAR median home price index is the lack of control for housing quality.

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