Combining Socioeconomic, Demographic, and Zoning Data to Explore Urban Inequality in Pittsburgh

Abstract

Historic injustices due to racial discrimination, redlining, and inequitable zoning practices have contributed to urban inequalities in the United States. These inequalities have been compounded by a lack of consideration for how infrastructure, industrial projects, and zoning impact nearby low-income and minority populations. To promote an equitable future, this paper investigates whether there are spatial patterns based on zoning variance data in the city of Pittsburgh. The authors used principal component analysis and regression analysis to study statistical correlations between socioeconomic and demographic characteristics and zoning variance application data. Several relationships reflect statistical significance, such as the average income of the residents and the percentage over the age of 25 who are college-educated , while the overall results highlight potential future research areas. Our work combining data sets with spatially explicit statistical analysis has the potential to equip decision makers with future tools necessary to account for inequalities and assess communities that may be unaware of the opportunities that variances present.