Measuring spatial polarization and inequality in cities using housing transaction big data

Authors: Jinhyung Lee*, The Ohio State University, Harvey J. Miller, The Ohio State University, Elena G. Irwin, The Ohio State University, Nicholas B. Irwin, The Ohio State University
Topics: Geographic Information Science and Systems, Spatial Analysis & Modeling, Urban Geography
Keywords: Urban geography, spatial polarization, spatial inequality, housing price, hedonic model
Session Type: Paper
Day: 4/14/2018
Start / End Time: 10:00 AM / 11:40 AM
Room: Grand Chenier, Sheraton, 5th Floor
Presentation File: No File Uploaded

Recent years have witnessed the economic recovery of the U.S. cities from the Great Recession. However, the benefits of the revitalization have not been equally distributed across space, resulting in the increased spatial polarization and inequality within the city. Although examining the spatiotemporal patterns of polarization and inequality is crucial for understanding socio-economical changes and formulating policies, there has not been many empirical studies using high-resolution geospatial data. This research investigates the spatial polarization and inequality trends in the three biggest cities in Ohio, Columbus, Cincinnati, and Cleveland using housing transaction big data spanning the period from 2000 to 2015. The boundaries utilized are the Urbanized Areas. We measure spatial polarization and inequality through spatial analysis of the housing location premium in all three cities. We measure location premium through the residuals from hedonic housing price models controlling housing features (e.g., the number of bedrooms). We visualize the spatial polarization patterns through Kriged surfaces of location premium for the time periods 2000-2003, 2004-2007, 2008-2011 and 2012-2015. We also calculate spatial autocorrelation indices and Gini coefficients for these patterns. The location premium surface maps and Moran’s I values during the study period suggest that the three Ohio cities have been spatially polarized over the time period 2000-2015. Also, the changes in Gini coefficients of residuals show that the inequalities of location premium within the three cities have increased. This research provides a data-driven framework for geovisualizing the changes in urban economic landscape and assessing the spatial polarization and inequality in cities.

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