Modeling social heterogeneity, neighborhoods and local influences on urban real estate prices : spatial dynamic analyses in the Belo Horizonte metropolitan area, Brazil

Abstract

This study aims to bring together the insights of two strands of literature regarding urban development: urban economics – originally considered in a monocentric spatial-economic framework – and self-organizing systems and cellular automata (CA) modeling, which aim to explain multinodal and evolutionary urban development. We do so by examining urban real estate markets that reflect the complexity of urban development. Innovatively, socioeconomic heterogeneity and the notion of neighborhoods – viewed as essential in planning and urban studies – are introduced in our models. Herein, neighborhoods as identity communities and their local influence are hypothesized to be crucial elements for explaining urban economic and morphological development in a research framework applied to the metropolis of Belo Horizonte in Brazil. Geoprocessing techniques and principal component analysis (PCA) are used to aggregate the spatially distributed socio-economic data by neighbourhood. This produces a detailed description of the urban fabric at the neighbourhood level. The empirical analyses in this thesis extend models in both strands through the cross-fertilization of concepts and causal mechanisms. The first is an econometric model which is tested against its spatial component and that incorporates quantile regression analysis (IVQR). The second is a cellular automata model which extends the initial proposal of White and Engelen (1993) and explicitly considers disagglomerative effects influence on real estate urban prices. Both models include social heterogeneities and local influences as central explanatory elements. The application of the models provided insights into what factors contribute (and to what extent) to the formation of real estate prices, given its configuration; as well as the identification of which factors dynamically interact to determine the location of urban actors and urban land price formation. In both cases, the analyses of actors from different socioeconomic levels and its relative location within the neighborhoods proved to be relevant.