Thomas G. Thibodeau

Analysis of Spatial Autocorrelation in House Prices

This article examines spatial autocorrelation in transaction prices of single-family properties in Dallas, Texas. The empirical analysis is conducted using a semilog hedonic house price equation and a spherical autocorrelation function with data for over 5000 transactions of homes sold between 1991:4 and 1993:1. Properties are geocoded and assigned to separate housing submarkets within metropolitan Dallas. Hedonic and spherical autocorrelation parameters are estimated separately for each submarket using estimated generalized least squares (EGLS). We find strong evidence of spatial autocorrelation in transaction prices within submarkets. Results for spatially autocorrelated residuals are mixed. In four of eight submarkets, there is evidence of spatial autocorrelation in the hedonic residuals for single-family properties located within a 1200 meter radius. In two submarkets, the hedonic residuals are spatially autocorrelated throughout the submarket, while the hedonic residuals are spatially uncorrelated in the remaining two submarkets. Finally, we compare OLS and kriged EGLS predicted values for properties sold during 1993:1. Kriged EGLS predictions are more accurate than OLS in six of eight submarkets, while OLS has smaller prediction errors in submarkets where the residuals are spatially uncorrelated and the estimated semivariogram has a large variance.

Real Estate Investment Funds: Performance and Portfolio Considerations

This paper presents the results of a study dealing with a number of issues regarding real estate investment. Utilizing a data set consisting of returns from two of the oldest, continuously operating commingled real estate funds (CREFs), questions relative to investment performance, inflation hedging attributes and diversification benefits are addressed. The methodology used in exploring these issues are variants of the traditional capital asset pricing model (CAPM), extended to consider uncertain inflation (CAPMUI) and an arbitrage pricing model in which real estate performance is judged relative to a more inclusive market index representing larger numbers of substitute investments. Finally, issues relative to portfolio performance are considered by constructing portfolios containing all possible combinations of real estate, stocks and bonds to assess the potential for diversification benefits and portfolio performance.

Spatial Autoregression Techniques for Real Estate Data

This paper describes how spatial techniques can be used to improve the accuracy of market value estimates obtained using multiple regression analysis. Rather than eliminating the problem of spatial residual dependencies through the inclusion of many independent variables, spatial statistical methods typically keep fewer independent variables and augment these with a simple model of the spatial error dependence. We discuss alternative spatial autoregression model specifications, estimation methods, and prediction procedures. An empirical example is provided in the appendix.

Explaining metropolitan housing price differences

Abstract Housing prices differ substantially among metropolitan areas. The rent and house price indexes used here measure this variation among 54 metropolitan areas. A model of metropolitan housing price determination is presented and used to identify the sources of intermetropolitan price variation. Reduced-form equations explain close to 90% of the variation in rental prices and close to 60% of the variation in house prices.

Anisotropic Autocorrelation in House Prices

This article examines anisotropic spatial autocorrelation in single-family house prices and in hedonic house-price equation residuals using a spherical semivariogram and transactions data for one county in the Philadelphia, Pennsylvania, MSA. Isotropic semivariograms model spatial relationships as a function of the distance separating properties in space. Anisotropic semivariograms model spatial relationships as a function of both the distance and the direction separating observations in space. The goals of this article are (1) to determine whether there is spatial autocorrelation in hedonic house-price equation residuals and (2) to empirically examine the validity of the isotropy assumption. We estimate the parameters of spherical semivariograms for house prices and for hedonic house-price equation residuals for 21 housing submarkets within Montgomery County, Pennsylvania. These housing submarkets are constructed by dividing the county into 21 groupings of economically similar adjacent census tracts. Census tracts are grouped according to 1990 census tract median house prices and according to characteristics of the housing stock. We fit the residuals of each submarket hedonic house price equation to both isotropic and anisotropic spherical semivariograms. We find evidence of spatial autocorrelation in the hedonic residuals in spite of a very elaborate hedonic specification. Additionally, we have determined that, in some submarkets, the spatial autocorrelation in the hedonic residuals is anisotropic rather than isotropic. The empirical results suggest that the spatial autocorrelation in Montgomery County single-family house-price equation residuals is anisotropic in submarkets where residents typically commute to a regional or local central business district.

The spatial proximity of metropolitan area housing submarkets

An important question related to housing submarket construction is whether geographic areas must be spatially adjacent in order to be considered the same submarket. Housing consumers do not necessarily limit their search to spatially concentrated areas and may search similarly priced neighborhoods located throughout a metropolitan area when making housing consumption decisions. This article examines two alternative procedures for delineating submarkets: one that combines adjacent census block groups into areas with enough transactions to estimate the parameters of a hedonic house price equation and a second that permits spatial discontinuities in submarkets. The criterion used to evaluate the alternative techniques is the accuracy of hedonic house price predictions.

Have the GSE affordable housing goals increased the supply of mortgage credit

Abstract In the 1980s, housing market analysts and policymakers were concerned that Freddie Mac and Fannie Mae were not adequately facilitating the financing of affordable housing for low- and moderate-income families. To address these concerns, the Department of Housing and Urban Development established quantitative Affordable Housing Goals requiring the Government Sponsored Enterprises (GSEs) to increase their purchases of mortgages originated by low- and moderate-income households and for homes located in low-income neighborhoods. Our analysis indicates that the goals increased the supply of mortgage credit available to low- and moderate-income households, after controlling for other mortgage market factors. Our analysis suggests that the increase in the supply of low-income mortgage credit occurred primarily in 1998.

Housing Price Indexes from the 1974-1983 SIMSA Annual Housing Surveys

This paper reports residential real estate price indexes computed from the Standard Metropolitan Statistical Area (SMSA) Annual Housing Survey (AHS) for the 1974 through 1983 period. During this ten-year period, the U.S. Bureau of the Census conducted detailed surveys of the housing stock in sixty metropolitan areas in a three to four year cycle. This information is used to compute tenure specific hedonic housing price indexes for: (1) the entire metropolitan housing market; (2) separately for properties located in the central city and in the suburbs (whenever central city locations are identified); and (3) for three points in the dwelling quality distribution-for substandard housing (using the definition employed by the U.S. Department of Housing and Urban Development), for new housing (housing less than three years old and not substandard), and for existing standard quality housing (everything else). In addition, the hedonic prices reported here are adjusted for the finite sample bias introduced when taking the exponential of a lognormally distributed random variable. Copyright American Real Estate and Urban Economics Association.

Dwelling age heteroskedasticity in repeat sales house price equations

Several authors have attributed the heteroskedasticity observed in repeat sales house price equations to the length of time between sales. Recently, Goodman and Thibodeau (1995) developed a theoretical model that relates heteroskedasticity in hedonic house price equations to dwelling age. Using data for nearly 2,000 repeat sales in Dallas, Texas, this research examines whether repeat sales heteroskedasticity is related to dwelling age, to the length of time between sales, or to both. An iterative generalized least squares procedure that explicitly models the residual variance is used to obtain robust parameter estimates and to increase the efficiency of the usual repeat sales price indices. Copyright American Real Estate and Urban Economics Association.

The Relationship between Median and Constant Quality House Prices: Implications for Setting FHA Loan Limits

This paper examines the relationship between the asset price of housing and median sales price. We demonstrate: (1) median house prices (as reported by the National Association of Realtors) overstate the increase in constant-quality house prices by about 2% per year over the 1976-1985 period; and (2) regional differences in median house prices and their rates of increase, respectively, are systematically related to regional differences in real incomes and their rates of increase. We use these results to evaluate the recent proposal to raise the FHA maximum loan limit ceiling from the current ceiling of