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This study examines the dynamics of real housing price appreciation in 130 metropolitan areas across the United States. The study finds that real housing price appreciation is strongly influenced by the growth of population and real changes in income, construction costs and interest rates. The study also finds that stock market appreciation imparts a strong current and lagged wealth effect on housing prices. Housing appreciation rates also are found to vary across areas because of locationspecific fixed-effects; these fixed effects represent the residuals of housing price appreciation attributable to location. The magnitudes of the fixed-effects in particular cities are positively correlated with restrictive growth management policies and limitations on land availability. I n t r o d u c t i o n The factors that influence changes in housing prices are of interest to urban planners, developers, real estate professionals and financial executives as well as most American households. According to a 1998 Federal Reserve survey (Kennickell, Starr-McCluer and Surette, 2000), 66.2% of households in the United States are homeowners, and housing investment amounts to 33% of household net worth. Over the past two decades, stock market appreciation has markedly increased the total wealth of U.S. households, but the linkage between housing prices and stock market wealth has not been explored. A number of studies have examined housing price change by metropolitan area, but few studies have been able to estimate the separate the effects of both demandand supply-side variables. This study examines the factors that influence real housing price changes in a sample of 130 metropolitan areas during the 1984 to 1998 period. In comparison to prior research, this research offers a much broader sample of MSAs over a longer time period. The study shows that real housing price appreciation is 3 0 J u d a n d W i n k l e r significantly related to changes in population and real changes in income, construction costs, stock price appreciation and after-tax interest rates. The analysis employs a fixed-effects model to control for MSA-specific factors that may influence appreciation rates in particular areas. The magnitudes of the fixedeffect coefficients are positively correlated with restrictive growth management policies and limitations on land availability. P a s t S t u d i e s o f H o u s i n g P r i c e C h a n g e s There have been a number of studies of housing prices and housing price changes. The focus here is on those studies that have examined housing price changes, rather than the level of prices. A review of early work in this area can be found in Bartik (1991, Chapter 5), who introduces a lagged adjustment model and provides additional empirical results. The studies reveal that housing appreciation is directly influenced by population and employment growth, although the estimated impacts of these factors vary widely. A study by Poterba (1991) examines the effects of population and income changes as well as the impacts of construction and after-tax user costs. He finds that income and construction costs are important in explaining housing cost changes, but his results provide no support for the role of demographic factors or after-tax user costs. Abraham and Hendershott (1996) develop a model of housing price change that allows for a lagged adjustment process. Their model, which is estimated using the quality-adjusted Freddie Mac-Fannie Mae repeat transaction database for thirty metropolitan areas, reveals that that real housing price appreciation is directly related to increases in real construction costs, employment and real income. They find that appreciation rates are negatively related to rises in real interest rates. The prolonged rise in stock prices over the past two decades has dramatically increased household wealth, and stock holdings have grown as a fraction of total household wealth, rising from 8.5% in 1989 to 22.9% in 1998 (Kennickell, StarrMcCluer and Surette, 2000). Although the effect of wealth on consumption has been much debated (Ludvigson and Steindel, 1999; and Starr-McCluer, 1998), no work was found that focused specifically on the impact of wealth changes on housing expenditures or prices. A number of economic models have examined the ‘‘wealth effect’’ on total consumer spending. Most of these models estimate that a one-dollar increase in stock market wealth raises consumer spending by three to seven cents per year (Starr-McCluer, 1998), but the magnitude of the effect remains a subject of debate and research. For example, a recent paper by Poterba (2000) suggests the wealth effect might be less than three cents per dollar, while work by Ludvigson and Steindel (1999) finds evidence that the effect of wealth on durable goods spending is larger and more long lasting than its effect on total spending. T h e D y n a m i c s o f M e t r o p o l i t a n H o u s i n g P r i c e s 3 1 J R E R V o l . 2 3 N o s . 1 / 2 – 2 0 0 2 This study analyzes the determinants of real housing price change using a sample encompassing 130 metro areas from 1984 through 1998. The model introduces a wealth effect on housing prices, and an MSA fixed-effects model is utilized to account for changes in metropolitan-specific cost factors. The model is estimated with a maximum likelihood procedure that allows correction of the time-series, cross-sectional sample for heteroskedasticity and autocorrelation within metropolitan cross sections. The sample data of housing prices are derived from recently available qualityadjusted housing price indexes reported by the Office of Federal Housing Enterprise Oversight (OFHEO). OHHEO’s House Price Indexes are available at the MSA level. They track average house price changes in repeat sales or refinancings on the same single-family properties and are based on analysis of data obtained from over 11.9 million repeat transactions over the past twenty years (OFHEO, 1999). T h e M o d e l a n d E m p i r i c a l S p e c i f i c a t i o n The demand for housing in any metropolitan market (i) at time (t) is given by: D Q D(P ,Y ,W ,I ,Pop ,u ), (1) i,t i,t i,t i,t i,t i,t i,t