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.     

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.     

A Spatial Autocorrelation Approach for Examining the Effects of Urban Greenspace on Residential Property Values

This paper presents spatially explicit analyses of the greenspace contribution to residential property values in a hedonic model. The paper utilizes data from the housing market near downtown Los Angeles. We first used a standard hedonic model to estimate greenspace effects. Because the residuals were spatially autocorrelated, we implemented a spatial lag model as indicated by specification tests. Our results show that neighborhood greenspace at the immediate vicinity of houses has a significant impact on house prices even after controlling for spatial autocorrelation. The different estimation results from non-spatial and spatial models provide useful bounds for the greenspace effect. Greening of inner city areas may provide a valuable policy instrument for elevating depressed housing markets in those areas.     

The Hierarchical Trend Model for Property Valuation and Local Price Indices

This paper presents a hierarchical trend model (HTM) for selling prices of houses, addressing three main problems: the spatial and temporal dependence of selling prices and the dependency of price index changes on housing quality. In this model the general price trend, cluster-level price trends, and specific characteristics play a role. Every cluster, a combination of district and house type, has its own price development. The HTM is used for property valuation and for determining local price indices. Two applications are provided, one for the Breda region, and one for the Amsterdam region, lying respectively south and north in The Netherlands. For houses in these regions the accuracy of the valuation results are presented together with the price index results. Price indices based on the HTM are compared to a standard hedonic index and an index based on weighted median selling prices published by national brokerage organization. It is shown that, especially for small housing market segments the HTM produces price indices which are more accurate, detailed, and up-to-date.     

The relationship between rents and prices of owner-occupied housing in Taiwan

This article analyzes the changes of equilibrium rent and equilibrium price of owner-occupied housing in Taiwan, and also computes the rent multiplier and its trend in the past ten years in Taiwan to show how the housing consumption and housing investment change. A hedonic rent equation and a hedonic housing price equation are built first. Then, we apply the Housing Survey Report data from 1979 to 1989, and employ ordinary-least squares method to estimate the two equations. Using estimated coefficients of the two equations, we compute the market rents for owner-occupied housing and the market prices for rental housing. Finally, the rent multipliers are calculated from the market rents and market prices. The article finds that (1) changes of housing prices in Taipei lead to price changes in Kaoshung, and the latter leads Taiwan province; (2) changes of rent are much smaller than the changes of housing price; and (3) housing prices in Taiwan increased drastically. We also find: (1) at the peak of the housing market cycle, the rent multiplier is extremely high; (2) the rent multiplier drops in the year after the peak year because the rent catches up; (3) the rent multiplier in Taipei is greater than that of Kaoshung, and the multiplier in Kaoshung is greater than that of Taiwan province; and (4) overall, the rent multiplier in Taiwan is much greater than that of the United States.     

Spatial Dependence and House Price Index Construction

Accurate estimation of prevailing metropolitan housing prices is important for both business and research investigations of housing and mortgage markets. This is typically done by constructing quality-adjusted house price indices from hedonic price regressions for given metropolitan areas. A major limitation of currently available indices is their insensitivity to the geographic location of dwellings within the metropolitan area. Indices are constructed based on models that do not incorporate the underlying spatial structure in housing data sets. In this article, we argue that spatial structure, especially spatial dependence latent in housing data sets, will affect the precision and accuracy of resulting price estimates. We illustrate the importance of spatial dependence in both the specification and estimation of hedonic price models. Assessments are made on the importance of spatial dependence both on parameter estimates and on the accuracy of resulting indices.     

Spatial Dependence,Housing Submarkets,and House Price Prediction

This paper compares alternative methods of controlling for the spatial dependence of house prices in a mass appraisal context. Explicit modeling of the error structure is characterized as a relatively fluid approach to defining housing submarkets. This approach allows the relevant submarket to vary from house to house and for transactions involving other dwellings in each submarket to have varying impacts depending on distance. We conclude that—for our Auckland, New Zealand, data—the gains in accuracy from including submarket variables in an ordinary least squares specification are greater than any benefits from using geostatistical or lattice methods. This conclusion is of practical importance, as a hedonic model with submarket dummy variables is substantially easier to implement than spatial statistical methods.

Coastal development moratoria and housing prices

This article draws upon event study methodology typically employed in the field of empirical finance to explore the impact of a development moratorium on housing prices in Los Angeles County. Time-series analysis is employed to examine hedonic price-series, return-series, and cumulative returns for prototypical housing units by geographic location and housing type based on ex ante hypotheses about the relative impact of a coastal development moratorium on the market segments that these price and return data represent. In particular, housing prices, returns, and cumulative returns inside and outside the impacted area are examined as are the same measures for housing segmented by age and density. Housing prices in the impacted area experience a significant sustained increase of 6.8 percent and a 10.9 percent spike as of the event date relative to housing prices outside the area. Perhaps more convincing is a cumulative increase in relative returns of over 26 percent in the impacted area versus the inland area during the 22 months prior to the event date. The difference in returns is not significant after the event date. Consistent results are found for properties segmented by age and density. Application of this approach depends on the availability of large volumes of transactions to permit the construction of price-series and return-series in the market segments suggested by the research design.     

House Price Index Construction in the Nascent Housing Market: The Case of China

Most existing house price index construction methods are developed mainly based on transaction data from the secondary housing market, and are not necessarily suitable for the nascent housing markets where a predominant portion of housing transactions are new units. Using the booming market in China as an example, we evaluate and compare the performances of three most common house price measurement methods in the newly-built housing sector, including the simple average method without quality adjustment, the matching approach with the repeat sales modeling framework, and the hedonic modeling approach. Our analyses suggest that the simple average method fails to account for the substantial complex-level quality changes over time of sales during our sample period, and the matching model fails to control for the effect of developers’ pricing behaviors when adopted in the newly-built sector, hence both are downward biased. Based on this finding, we apply a hedonic method, which allows us to control for both quality changes over time of sales and developers’ pricing behaviors, to 35 major newly-built housing markets and provide the first multi-city constant-quality house price index in China. The new index reveals that the current Chinese housing market is facing a greater risk of mispricing than reported by the existing official metrics.     

Selectivity,Quality Adjustment and Mean Reversion in the Measurement of House Values*

This paper develops a model of price formation in the housing market which accounts for the non-random selection of those dwellings sold on the market from the stock of existing houses. The model we develop also accounts for changes in the quality of dwellings themselves and tests for mean reversion in individual house prices. The model is applied to a unique body of data representing all dwellings sold in Sweden's largest metropolitan area during the period 1982–1999. The analysis compares house price indices that account for selectivity, quality change and mean reversion with the conventional repeat sales models used to describe the course of metropolitan housing prices. We find that the repeat sales method yields systematically large biased estimates of the value of the housing stock. Our comparison suggests that the more general approach to the estimation of housing prices or housing wealth yields substantially improved estimates of the course of housing prices and housing wealth.     

Implicit pricing across residential rental submarkets

This paper examines implicit price differences of rental housing characteristics across various property types to measure whether determinants of rents are valued in the aggregate or separately. The results show that hedonic price functions are not identical across property types, which suggests that ordinary least squares is not the appropriate estimation technique when modeling the implicit prices for an aggregate rental market. Generalized least squares estimation of a random coefficient model removes the restriction of fixed parameters imposed by OLS and allows estimation of implicit prices for rental markets containing multiple property types.     

The effect of land-use restrictions on market values of single-family homes in Houston

This paper analyzes the effects of zoning and restrictive covenants on single-family housing prices in and around Houston, Texas. The calculation of a hedonic price index reveals that higher prices are paid for homes in neighborhoods with either type of land-use control than for comparable houses in neighborhoods without these controls. The premiums paid for these restrictions are not statistically distinguishable, but institutional constraints on these controls may explain why both forms continue to exist and to command market premiums.     

Long-Term Co-Memories and Short-Run Adjustment: Securitized Real Estate and Stock Markets

This study considers whether securitized real estate and stock markets have long-term co-memories and implications for short-term adjustment. Our results offer reasonable support for fractional cointegration (characteristic of a long memory process) between securitized real estate price, stock market price and key macroeconomic factors in some economies. The implication is that where fractional cointegration prevails, securitized real estate and common stocks are substitutable assets over the long run and these assets may not be held together in a portfolio for diversification purpose. Furthermore, short-run analysis indicates that the speed of adjustment towards the long-run equilibrium is faster for fractional integrated vector error correction model (FIVECM) than VECM as the former incorporates a long history of past cointegration residuals. Additional comparisons of the two models’ forecasting accuracy show that incorporating fractional cointegration in a VECM model improves the forecasting performance over conventional VECM models. Our results reinforce the notion that cointegration, fractional cointegration and short-run adjustment dynamics are important in understanding market integration/segmentation.     

The Construction of Residential Housing Price Indices: A Comparison of Repeat-Sales,Hedonic-Regression,and Hybrid Approaches

This article examines a number of hypotheses that underpin the repeat-sales and hedonic approaches to the construction of housing price indices, as well as the practical problems associated with the implementation of either approach. We also examine a hybrid procedure that combines elements of both the repeat-sales and hedonic-regression techniques. For our sample of individual home sales in Oakland and Fremont California over an 18-year period, repeat-sales methods are subject to sample selection bias; the maintained assumption of time constancy of implicit prices of housing attributes is violated; the repeat-sales estimator is extremely sensitive to influential observations; and the usual method used to correct for heteroskedasticity in repeat-sale housing returns is inappropriate in our sample. Hedonic techniques are better suited to contend with index number problems per se, as they can accommodate changing attribute prices over time. They also appear to give rise to more reliable estimates of price indices, as unusual observations have less effect on estimated price indices. Drawbacks of the hedonic approach include the usual concern with omitted attributes, and their effect on the estimated price index.     

A hedonic price model for private properties in Hong Kong

A hedonic model is used to explore the effects of locational, structural, and neighborhood attributes on the price structure of private condominiums in Hong Kong. The regression results and the elasticities of housing attributes obtained from the Box-Cox analysis indicate that the valuation of a property is sensitive to changes in housing traits. Home buyers are rational and are willing (unwilling) to pay for desirable (undesirable) housing attributes and that the valuation of a property is market-driven in Hong Kong.     

Appraisal Quality and Residential Mortgage Default: Evidence from Alaska

We empirically examine the effect of appraisal quality on subsequent mortgage loan performance using data from the high volatility housing market of Alaska in the 1980s. We develop measures of appraisal quality by computing the residual between a hedonic estimate of house value using available information from other appraisals compared to actual ex ante appraised value. We then estimate proportional hazard models of mortgage default and find that several measures of appraisal quality, particularly appraised value in excess of hedonic estimates, are significantly related to default risk. Using valuations subsequent to loan default, we are also able to evaluate how well house price indices perform in terms of estimating current loan-to-value and offer some additional evidence on the controversy over the role of net equity versus trigger events as determinants of mortgage default. We also show that defaults are related to ex ante measures of housing market conditions, with additional implications for underwriting policies and the current industry trend away from traditional appraisal and toward automated valuation.     

Pricing mortgage insurance contracts under housing price cycles with jump risk: evidence from the U.K. housing market

Previous studies have investigated the determinants of housing price cycles in the housing market; however, we observed the phenomenon of housing price jumps in the 2007 subprime crisis. This paper presents a discussion on the housing price cycle and abnormal price jumps to describe the behavior of housing prices in the United Kingdom. The empirical results show that the impact factors of housing cycles are market risk and the switching factor. Furthermore, the impact factors of jump risks include the bursting of the housing bubble and financial crises. Therefore, in this paper, we employ the Markov switching model with jump risks to value the MI contracts and analyze the influences of housing price cycles, jump risks, risks of market interest rate, and the prepayment risks on MI premiums. The results of sensitivity analysis show that more volatile housing price index returns, as well as longer periods of higher volatility in housing prices, raise MI premiums. Moreover, the MI premium is positively related to the absolute value of the average jump amplitude and the shock frequency of abnormal events. There is the tradeoff between the market interest rate and the prepayment risk. The influences of market interest rate are different on MI premium with/without prepayment risks.     

The Benefits of Visibility Improvement: New Evidence from the Los Angeles Metropolitan Area

This article examines the impact of a specific aspect of air quality—visibility, or the ability to clearly see distant objects—on housing values. Our analysis is based on a data set constructed by matching residential housing sales data from the Los Angeles Metropolitan Area for the period 1980 through 1995 with visibility and other air pollution data and other characteristics. We find that visibility differences are capitalized into housing values, producing a measurable hedonic price gradient. The time-series design facilitates an estimate of the demand for visibility that we use to calculate the benefits of changes in visual range.     

List price signaling and buyer behavior in the housing market

To determine whether list price contains useful information for anticipating trends in eventual transactions prices, we develop a model of buyer behavior from a search-theoretic perspective. Using data from the Baton Rouge, Louisiana, housing market between 1985 and 1992, we estimate separate price indexes with list price and selling price as the respective dependent variables in the hedonic regressions. Consistent with our theory, we find that the list price may lead the market when functioning as a signal of seller intent, but list price will probably lag a market driven by buyer willingness to purchase. Granger causality tests conducted on quarterly data for the eight-year study support listing price as a leading indicator of selling price. However, an examination of the indexes around the period of market reversal suggest otherwise. Indeed, listing prices appear to contain the least useful information at the times when information would be most valuable: at the peaks and troughs of the market cycle.     

The Housing Price Impact of Covenant Restrictions and Other Subdivision Characteristics

Private land-use restrictions at the subdivision level, commonly called covenant or deed restrictions, have the potential to reduce housing consumption and investment risk and existing empirical evidence has shown a positive marginal housing price for covenant restrictions. However, some commentators have charged that covenant restrictions are full of boilerplate and mostly unenforced, thus any positive marginal price measurement captures other unobserved aspects of the subdivision. Indeed newly published estimates report zero or negative marginal price for deed-restricted subdivisions (DRS). This paper reviews these claims using a hedonic model of housing and a unique dataset that includes covenant restrictions, by-laws, and club goods. Results show a positive marginal price of deed restrictions even when controlling for several subdivision characteristics; however, the marginal price of restrictions falls to zero if a covenant is not updated after 25 years.