Topological Data Analysis in an Economic Context: Property Tax Maps
David B. Damiano, Anbo Wu · 2021 IEEE International Conference on Big Data (Big Data) · 2021
Property tax is a significant index which reflects housing quality and even the community structure of a neighborhood. Historically, economics has offered various methods to analyze living standards and policy effectiveness using property tax. In this paper we introduce a topological approach to explore local housing patterns. We use methods from topological data analysis (TDA) to analyze 210 property tax maps sampled from 21 cities. We then utilize clustering and dimension reduction methods to classify samples and identify features of the local tax patterns. By evaluating the topological features, we are able to identify the property tax value structure within each sample, and provide an efficient general classification. The clustering that results is distinct from past measures, and we also evaluate its relationship between local land use and indicators of regional demographic heterogeneity.