Marking Single–Family Property Values to Market

This paper is the text of the 2001 Presidential Address for the American Real Estate and Urban Economics Association. House price prediction accuracy is a function of: (1) the procedure used to identify within–metropolitan–area housing submarket boundaries, (2) the econometric technique used to estimate the parameters of the house price model and (3) the characteristics of the local housing market. This paper empirically examines several procedures for delineating within–metropolitan–area housing submarket boundaries. In addition, the paper examines the increase in prediction accuracy that can be achieved by employing spatial econometric techniques to spatially adjust ordinary least squares house price predictions. Finally, the paper examines the influence that local housing market characteristics have on house price prediction accuracy. Housing market characteristics examined here are: (1) structural characteristics of neighborhood properties, (2) heterogeneity of the neighborhood housing stock and (3) housing market liquidity. Prediction accuracy is examined using hedonic house price equations with over 40,000 single–family transactions for Dallas, Texas.     

Urban Housing Markets Modelling: Short-Run Equilibrium Implications

This paper tests for the existence of short-run equilibrium in the urban housing market in Metropolitan Toronto. The alternative hypothesis is the housing market segmented with respect to locational and structural attributes. We found insignificant differences in attribute prices across hypothesized submarkets. This implies that an unstratified hedonic price regressions model, based on the assumption of short-run equilibrium, is equally efficient in the analysis of housing prices as a model based on a number of subsamples stratified along lines of segmentation.     

House Search Duration in Hot and Cold Residential Markets

This study analyzes the determinants of house search duration of consumption‐driven buyers and individual investors in different housing market environments. We use data from surveys of recent house‐buyers in “hot” and “cold” housing markets in the 2000s housing bubble in California characterized by rising and declining residential house prices, respectively. The average house price and the surveyed geographical area are the same for both periods. Expected house ownership horizon is shown to be an important determinant of the realized search duration in addition to commonly considered housing and buyer characteristics. We find a statistically significant positive effect of it on the time until purchase in both housing price environments for consumption‐driven buyers. We also find that consumption‐driven house purchases were highly pronounced in coastal areas in the hot market and inland areas in the cold market. In contrast, long‐horizon investment activity leads that of consumption activity in those areas. Short‐horizon investors, on the other hand, concentrated their house search activity in inland areas in both housing market environments.     

Housing Attributes Associated with Capital Gain

Housing units are heterogeneous goods. Rates of change in housing prices are typically modelled as if they arise from factors unrelated to the housing unit itself. For example, housing price increases in the latter part of the 1970s and early 1980s are argued to have arisen primarily from demographic factors and the differential effects of inflation on the effective rate of taxation on income from corporate capital and on owner-occupied housing. Cross-sectional variation in price inflation is not addressed. Consumers who purchased housing units are not indifferent to their attributes. To the extent that expectations vary within regional housing markets as a consequence of variation in housing attributes, standard linear hedonic price regression may generate biased estimates of implicit prices. This paper identifies sufficient conditions for the estimates of implicit prices in linear hedonic price regressions to be unbiased and generate unbiased estimates of implied price changes. Finally, this paper identifies living space (house size) as a significant attribute related positively to the increase in individual housing prices in a regional market.     

Do House Price Levels Anticipate Subsequent Price Changes within Metropolitan Areas?

This research examines the relationship between hedonically controlled housing price levels and subsequent changes in those prices across locations within MSAs. Are areas with a high price relative to an “imputed rent” paying for higher appreciation? In an efficient market (e.g., Gordon Growth Model), as fundamentals (impute rent) differ across locations and change over time, anticipation of these should generate a positive correlation between (residual) price levels and subsequent price changes. We undertake these tests in four different MSAs using a panel of repeat‐sale house price indices that have been scaled to price levels with the hedonic attributes of the house and ZIP code. In three markets we find that identical houses in higher priced ZIP codes subsequently appreciate faster. In one market we find that there is little statistical difference.     

The Duration of Marketing Time of Residential Housing

The marketing of unique durable goods such as housing presents a good example for the application of search theory. An optimal stopping rule strategy is employed to model sellers' behavior. The primary hypothesis is that the greater the atypicality of a house, the greater the expected variance of offers. Because a maximizing seller will wish to entertain more offers the greater is the variance, the marketing time of atypical houses will be relatively longer than that of standard houses. Using a sample of resale houses, the empirical study uses a failure time model to confirm the hypothesis. Extensions are mentioned, including discussions of the role of the list price and the limitations of the standard hedonic regression approach when applied to housing.     

The independent submarkets model: an application to the Spanish retail banking market

The aim of this paper is to test the predictions of Sutton’s independent submarkets model with data on the Spanish retail banking market. The prediction of this model for aggregates of submarkets is that the form of equilibrium outcome must involve some minimal degree of size inequality. However, within each submarket, when three conditions hold, the only form of equilibrium outcome will be an extreme ‘fragmented’ structure. To test these predictions, firstly I propose methods to identify independent submarkets. Then I analyze the degree of inequality in bank sizes for markets with different levels of aggregation (submarkets, regions and national market). Using concentration by towns’ data, I find that in single submarket towns the degree of inequality of the size among banks is zero. Moreover, multimarket towns with a significant degree of concentration are shown to be formed by a different number of independent submarkets where each bank owns one branch. Nonetheless, when the regional and the national bank markets are considered, the degree of inequality in bank sizes becomes high. These results are consistent with the predictions of the theoretical model.     

Transaction-Based Office Price Indexes: A Spatiotemporal Modeling Approach

This study examines the potential of a two-order spatiotemporal autoregressive model with a Bayesian heteroskedasticity robust procedure in modeling strata-titled Singapore office unit transaction prices and in constructing transaction-based disaggregate office price indexes. The model reduces the problems caused by the infrequent trading of individual commercial properties. However, for those office properties that are located outside the CBD and also for those less frequently transacted, the power of the model in capturing these particular office buildings' price dynamics is limited. The significant differences of the office prices across the various office buildings and submarkets show that the model can capture the variation in office prices and track the timing of capital gains and losses that investors may accrue on spatially distributed office properties more accurately than hedonic or weighted least squares estimates.     

Modeling Spatial Variation in Housing Prices: A Variable Interaction Approach

The absolute location of each real estate parcel in an urban housing market has a unique location-value signature. Accessibility indices, distant gradients and locational dummies cannot fully account for the influence of absolute location on the market price of housing because there are an indeterminable number of externalities (local and nonlocal) influencing a given property at a given location. Furthermore, the degree to which externalities affect real estate values is not only unique at each location but highly variable over space. Hence, absolute location must be viewed as interactive with other determinants of housing value. We present an interactive variables approach and test its ability to explain price variations in an urban residential housing market. The statistical evidence suggests that the value of location, as embodied in the selling price of housing units, may not be separable from other determinants of value. It is recommended that housing valuation models, therefore, be specified to allow site, structural and other independent attributes to interact with absolute location—{ x , y } coordinates—when accounting for intraurban variation in the market price of residential housing. This approach is especially useful when estimating the value of housing for geographic areas where very little is known a priori about the neighborhoods or submarkets.     

The Economics of Style: Measuring the Price Effect of Neo‐Traditional Architecture in Housing

Vintage effects have received considerable attention from economists in the context of house prices. Although strongly related, the impact of architectural building styles on prices has not been studied yet. Using a cross‐sectional hedonic price analysis including building styles of recently developed homes in the Netherlands we find a significant price premium for housing with neo‐traditional architecture. Extensive intervention by local authorities on the supply side of the housing market seems the most probable explanation of this effect. The decreasing price premium over time reflects the impact of supply restrictions on price, but also indicates that style does matter.     

Internet Search Behavior,Liquidity and Prices in the Housing Market

We employ detailed internet search data to examine price and liquidity dynamics of the Dutch housing market. We show that the number of clicks on properties listed online proxies demand and the number of listed properties proxies supply. From this internet search behavior, we create a market tightness indicator and we find that this indicator Granger causes changes in both house prices and housing market liquidity. The results of a panel VAR suggest that a demand shock results in a temporary increase in liquidity and a permanent increase in prices in urban areas. This is in accordance with search and matching models.     

Black and White Preferences for Neighborhood Racial Composition

The research investigates the existence, nature and magnitude of the preferences of races to voluntarily "self-segregate" into particular areas of urban housing markets. Housing market theory is employed to develop a model showing how housing price variations within a group can provide unambiguous evidence of their preferences for neighborhood racial composition. The model is operationalized in a multiple regression specification wherein the variations in a given racial group's housing prices become a function of the dwelling's attributes and the attributes of the neighborhood (including quality, status, stability and density) as well as housing submarket location and racial composition. The size and statistical significance of the coefficient of the last attribute provides the evidence sought.
The regressions are estimated using two micro-household data bases from St. Louis (1967) and Wooster, Ohio (1975), and results compared. Results show that St. Louis black owners had an aversion to larger black proportions within black submarket neighborhoods, with .7% lower housing prices associated with a 1% higher percentage black. Racial effects for black owners in preponderantly white areas and for black renters in all areas were statistically insignificant. St. Louis whites of both tenures did not demonstrate aversion to neighborhoods with higher percentages of blacks as long as they remained 25% black or less. In areas 25–50% black, however, white prices were 1.5% lower for owners and 3.2% lower for renters per 1% higher proportion black. Such associations continued in majority-black areas, although the magnitudes of the price effect became progressively smaller. Wooster whites showed an aversion to living in neighborhoods having even a few percent of blacks, with prices 11% lower for owners and 7% lower for renters in such areas compared to all-white ones.     

Repeat Sales as a Matching Estimator

The most common approaches for constructing house price indices—hedonic price functions and the repeat sales estimator—focus on changes over time in mean prices. Though the hedonic approach is less wasteful of data than the repeat sales estimator, it relies on an accurate specification of the underlying econometric model. I suggest using a matching estimator as an alternative to the hedonic and repeat sales approaches. Like the repeat sales approach, a matching estimator uses pairs of sales from different dates to estimate the mean difference in sales prices over time. The matching approach preserves much larger sample sizes than the repeat sales estimator while requiring less preimposed structure than the hedonic approach. The matching approach makes it easy to characterize changes in the full distribution of house prices.     

Green Noise or Green Value? Measuring the Effects of Environmental Certification on Office Values

This study investigates the price effects of environmental certification on commercial real estate assets. It is argued that there are likely to be three main drivers of price differences between certified and noncertified buildings. These are additional occupier benefits, lower holding costs for investors and a lower risk premium. Drawing upon the CoStar database of U.S. commercial real estate assets, hedonic regression analysis is used to measure the effect of certification on both rent and price. The results suggest that, compared to buildings in the same submarkets, eco‐certified buildings have both a rental and sale price premium.     

Deed Types, House Prices and Mortgage Interest Rates

When houses are sold they come with a deed attached that spells out the legal guarantees on good title. Some deeds give clues about the characteristics of the seller or the house. Using a 37,043-observation house price hedonic with a Bayesian spatial error model, we find the type of deed attached to a housing sale can have a dramatic correlation with the sale price. Ten deed types command a discount, and one commands a premium relative to warranty deeds. Mortgage rates for sheriff's deeds and foreclosure deeds are lower than for warranty deeds, indicating more sophisticated buyers.     

Risk and Return in the U.S. Housing Market: A Cross-Sectional Asset-Pricing Approach

This article carries out an asset-pricing analysis of the U.S. metropolitan housing market. We use ZIP code–level housing data to study the cross-sectional role of volatility, price level, stock market risk and idiosyncratic volatility in explaining housing returns. While the related literature tends to focus on the dynamic role of volatility and housing returns within submarkets over time, our risk–return analysis is cross-sectional and covers the national U.S. metropolitan housing market. The study provides a number of important findings on the asset-pricing features of the U.S. housing market. Specifically, we find (i) a positive relation between housing returns and volatility, with returns rising by 2.48% annually for a 10% rise in volatility, (ii) a positive but diminishing price effect on returns and (iii) that stock market risk is priced directionally in the housing market. Our results on the return-volatility-price relation are robust to (i) metropolitan statistical area clustering effects and (ii) differences in socioeconomic characteristics among submarkets related to income, employment rate, managerial employment, owner-occupied housing, gross rent and population density.     

Explaining Intermetropolitan Variation in Housing Prices, Rents and Land Prices

In attempting to explain why housing prices, rents and urban land prices vary so dramatically between U.S. metropolitan areas, a simple model of a metropolitan housing market is presented identifying three interrelated submarkets. Estimating equations for rent, housing prices and urban land prices are identified and estimated using two-stage least squares. The empirical results provide strong support for the theoretical model concerning how these three submarkets interact. The results also suggest that household income and construction costs are the most important factors causing housing prices, rents and land prices to vary between metropolitan areas.     

Valuing the Redevelopment Option Component of Urban Land Values

This study draws from the redevelopment, real option, and urban spatial growth literatures to explore the spatial dynamics of the components of house prices. More specifically, the paper proposes that the capitalized value of the option to redevelop housing at the property level can be estimated by incorporating the likelihood of exercising the redevelopment option (the probability of redevelopment) into spatial and nonspatial hedonic house price models. Accordingly, option values are estimated for properties across the spectrum of the housing life cycle. Results from the study reveal a substantial level of spatial variation and clustering in the predicted option values, indicating that location is a major determinant of redevelopment and real option values. Furthermore, the results provide new evidence in support of the theoretical construct that properties purchased for immediate redevelopment are only valued for the underlying land.     

Explaining the Variability of Apartment Rents

The research reported here uses regression analysis to analyze rent variations in a sample of apartment data from the Phoenix metropolitan area. Many of the variables used in hedonic price studies of houses are found to be significant in explaining variations in apartment rent. There are differences between hedonic studies of houses and apartments particularly with respect to common area features or amenities. The analysis of various submarkets also produced interesting results. Various uses can be made of the results of this and similar studies by appraisers (market-derived adjustments), property managers (setting rents) and feasibility analysts (the design of apartment projects).     

Clientele Effects on the Demand For Housing Price Appreciation

If house buyers are segmented by income, one might expect to observe buyers in such markets valuing the benefits of expected capital gain differently. Presumably, individuals experiencing higher marginal tax rates should be inclined to pay relatively more for anticipated capital gain since the opportunities of sheltering such income from taxation are greater. This paper attempts to identify a proxy for expected capital gain by using the hedonic price methodology to predict a recent price series for each housing unit in a sample of sales. That proxy is then used to determine an individual buyer's marginal willingness to pay for anticipated price appreciation. The results indicate that one cannot reject the joint hypothesis that homebuyers naively extrapolate from prior implied price performance to establish future price expectations and the variation in willingness to pay for that expectation may be a function of the buyer's income. This suggests the existence in housing markets of a phenomenon termed the clientele effect. This effect has been the subject of considerable examination in the finance literature.