The changing housing market: a bang or a whimper?

The U.S. housing market has had an extraordinary 15-year run in terms of prices, sales of existing homes, and new construction, especially on the East and West Coasts. Beginning in the spring of 2006, however, the housing market began to turn distinctly downward. We know that 2005 was a good year and that 2006 has not been such a good year, and we see indications that 2007 could be tough. To help understand why the market has shifted from hot to, at a minimum, cool, this paper, which is the first in a series of NEPPC policy briefs on housing, recaps some of the factors that contributed to this housing run and discusses some of the factors that will determine just how long and steep this reversal of housing fortune might be.Housing - Prices

Home price appreciation in low- and moderate-income markets

Do homes in low- and moderate- income areas of a city appreciate like homes in high income areas? Do owners of those lower-priced homes accumulate as much equity as owners of higher-priced homes? Karl Case and Maryna Marynchenko share their results, some of which are quite surprising.Housing - Boston ; Housing - Chicago ; Housing - Los Angeles

Housing risk and return: Evidence from a housing asset-pricing model

This paper investigates the risk-return relationship in determination of housing asset pricing. In so doing, the paper evaluates behavioral hypotheses advanced by Case and Shiller (1988, 2002, 2009) in studies of boom and post-boom housing markets. The paper specifies and tests a multi-factor housing asset pricing model. In that model, we evaluate whether the market factor as well as other measures of risk, including idiosyncratic risk, momentum, and MSA size effects, have explanatory power for metropolitan-specific housing returns. Further, we test the robustness of the asset pricing results to inclusion of controls for socioeconomic variables commonly represented in the house price literature, including changes in employment, affordability, and foreclosure incidence. We find a sizable and statistically significant influence of the market factor on MSA house price returns. Moreover we show that market betas have varied substantially over time. Also, results are largely robust to the inclusion of other explanatory variables, including standard measures of risk and other housing market fundamentals. Additional tests of model validity using the Fama-MacBeth framework offer further strong support of a positive risk and return relationship in housing. Our findings are supportive of the application of a housing investment risk-return framework in explanation of variation in metro-area cross-section and time-series US house price returns. Further, results strongly corroborate Case-Shiller survey research indicating the importance of speculative forces in the determination of U.S. housing returns

The Central Role of Home Prices in the Current Financial Crisis: How Will the Market Clear?

macroeconomics, financial crisis, subprime, house, home, market, household

Prices of Single Family Homes Since 1970: New Indexes for Four Cities

This paper uses data on nearly a million homes sold in four metropolitan areas -- Atlanta, Chicago, Dallas and San Francisco -- to construct quarterly indexes of existing home prices between 1970 and 1986. We propose and apply a new method of constructing such indexes which we call the weighted repeat sales method (WRS). We believe the results give an accurate picture of the actual rate of appreciation in home prices in the four cities. The paper explains the construction of the index, discusses the results and compares them with the National Association of Realtors data on the median price of existing single family homes for the period 1981 - 1986.

The Behavior of Home Buyers in Boom and Post-Boom Markets

A questionnaire survey looked at home buyers in May 1988 in two "boom" cities currently experiencing rapid price increases (Anaheim and San Francisco), a "post-boom" city whose home prices are stable or falling a couple years after rapid price increase (Boston) and a "control" city where home prices had been very stable (Milwaukee). Home buyers in the boom cities had much higher expectations for future price increases, and were more influenced by investment motives. The interpretations that people place on the boom are not usually related to any concrete news event; there are instead oft-repeated cliches about home prices. This suggests that sudden real estate booms have, at least in part, a social, rather than rational or economic, basis. There is evidence for excess demand in boom markets and excess supply in the post-boom market; there appear to be various reasons for this: notions of fairness, intrinsic worth, popular theories about prices, coordination problems, and simple mistakes.

The Efficiency of the Market for Single-Family Homes

Tests of weak-form efficiency of the market for single family homes are performed using data on repeat sales prices of 39,210 individual homes, each for two sales dates. Tests were done for Atlanta, Chicago, Dallas, and San Francisco/Oakland for 1970-86. While evidence for seasonality in real housing prices is weak, we do find some evidence of inertia in housing prices. A city-wide real log price index change in a given year tends to be followed by a city-wide real log price index change in the same direction (and between a quarter to a half as large in magnitude) in the subsequent year. However, the inertia cannot account for much of the variation in individual housing real price changes. There is so much noise in individual housing prices relative to city-wide price index changes that the R[squared] in forecasting regressions for annual real price change in individual homes is never more than .04.

Housing Price Dynamics Within a Metropolitan Area

This paper analyzes the pattern of cross-sectional house price appreciation in the Boston metropolitan area from 1982 to 1994. The empirical results are consistent with many of the predictions of a standard urban model in which towns have a fixed set of locational attributes and amenities. In particular, the evidence suggests that house prices in towns with a large share of residents working in the manufacturing sector in 1980 grew less quickly in the ensuing years when aggregate manufacturing employment fell. As baby boomers moved into middle age, house values appreciated faster in towns with a larger initial percentage of middle-aged residents. Housing values rose more slowly in towns that allowed additional construction, and values rose faster in towns closer to Boston. Finally, as fewer families had children who attended public schools statewide, the price premium associated with housing in towns with good schools fell. All of these findings support the view that town amenities and public services are not easily replicated or quickly adaptable to shifts in demand, even within a metropolitan area.

Forecasting Prices and Excess Returns in the Housing Market

The U. S. market for homes appears not to be efficient. A number of information variables predict housing price changes and excess returns of housing relative to debt over the succeeding year. Price changes observed over one year tend to continue for one more year in the same direction. Construction cost divided by price, the change in per capita real income, the change in adult population are all positively related to price changes or excess returns over the subsequent year. The results are based on time-series cross section regressions with quarterly data 1970-1 to 1987-3 and for cities Atlanta, Chicago, Dallas, and San Francisco.