Spatial pattern of housing prices in polycentric cities

This article analyses the formation of urban and suburban employment centralities and their impact on local housing values. Urban sprawl combined with the formation of suburban employment poles have produced complex spatial patterns, characterized by polycentric cities. This paper assumes that these changes in urban forms have influenced residential dynamics and have thus influenced housing prices. Suburban centralities are expected to improve local attractiveness and thus to be capitalized in housing prices.We use hedonic regressions to estimate the impact of the polycentric structure of the city on housing values, among other traditional factors. These estimations are completed by semi-parametric regressions in order to analyse sharply the form of the price gradients in a polycentric city. Data on residential transactions come from the PERVAL database recorded by French notary offices. The precise geolocation of transactions is used, in addition to a rich set of intrinsic characteristics of the buildings, to estimation sharply the spatial pattern of real estate prices. It is completed by a rich set of locational attributes coming from several data sources recorded at a fine spatial scale and covering accessibility, socio-economic attributes, local amenities and equipments, distance to the main subcenters. The study is conducted within the Lyon and Bordeaux metropolitan areas in France, allowing a comparison of two different urban patterns and urban sizes. The various scales of urban polycentrism are explored by taking into account two types of subcenters (emerging centralities in the suburban area and integration of satellite towns) and by estimating semi-parametric hedonic models. The first contribution of the paper is to estimate the impact of the polycentric form of the city on housing prices. The spatial pattern of housing prices is mainly explained by the increasing influence of urban amenities, at the expect of employment accessibility. The second contribution of this paper is to provide a precise estimation of the form of the hedonic gradients for residential and commercial real estate values through the use of semi-parametric regressions.