Spatial Variation in Housing Prices: Econometric Analyses of Regional Housing Markets

Abstract

This thesis consists of six empirically-based papers. Collectively, the papers contribute to theunderstanding of the spatial variation in housing prices within regional housing markets. Themain ambitions have been to identify what contributes significantly to explain the spatialvariation in housing prices within such markets, and to account for this variation ineconometric models. The thesis focuses primarily on macroscopical and general spatialstructural characteristics, rather than on characteristics relevant for a specific region or aspecific neighborhood. A summary of the theory underlying hedonic models and a review ofthe relevant literature are included, in addition to a chapter on various estimators from thespatial econometrics literature.According to the thesis there are two main global factors contributing significantly to explainthe intraregional spatial variation in housing prices. These are the urban attraction effectmeasured by distance from the central business district (cbd), and labor market accessibility.The gravity-based labor market accessibility measure used in the thesis represents a usefulapproximation towards being able to study how changes in accessibility may manifestthemselves and exert a spillover effect on housing prices throughout a region. Relevant kindsof experiments are performed in the thesis. As an example, these experiments show that anincrease in the number of jobs in an urban area only marginally influences the spatialdistribution of house prices. The impact on local housing prices is predicted to beconsiderably larger if the job growth is concentrated to the peripheral zones. Thedecentralization of jobs is hence found to contribute towards levelling out the differences inhousing prices between the urban and peripheral zones.Even though the two globally-defined measures of spatial structure characteristics explain amajor part of the spatial variation in housing prices, we also find that some locally-definedmeasures are relevant. The existence of subcenters, for instance, contributes significantlytowards explaining spatial variation in housing prices.A model that includes both the urban attraction effect and labor market accessibility is shownto be useful for predictive purposes, particularly in relation to changes in the spatialdistribution of jobs. In cases where one does not have detailed information on the spatialdistribution of jobs, the cbd gradient captures both the urban attraction and the labor marketaccessibility effect. As an example, such a parsimonious model-formulation is demonstratedto offer reliable predictions of the variation in housing prices between a centre and theperiphery. This conclusion might, however, be changed in a more polycentric area than theone studied here.