Measuring the process of urban gentrification: A composite measure of the gentrification process in Toronto

Abstract

Gentrification is being experienced by cities around the world. Its drivers and characteristic features are complex and diverse, ranging from the displacement of low-income households to the redevelopment of commercial districts. This paper combines multiple data sources to explore the coevolution of gentrification in the residential market and developments in non-residential sectors in the Canadian city of Toronto. Analysis starts from a max-p-regions clustering based on a composite measure of the gentrification process, which includes measures of household income, educational attainment, building permits, and the composition of establishments. The variables that describe each region are examined for patterns of gentrification. We then develop a Bayesian hierarchical spatial (BHS) model to describe the change in residential property prices over the five-year period between 2011 and 2016. The results show that establishment entropy and composition are found to influence residential property prices, with significant spatial variation in its effect. The combination of endogenous region definitions and hierarchical modeling is strongly supported by model results.