Developing Spatial Inequality—The Case of Kenya

Authors: Michael White*, Brown University, Kevin Mwenda, Brown University, Guixing Wei, Brown University , Juanfang Lei, Brown University
Topics: Population Geography, Quantitative Methods, Third World
Keywords: Spatial Inequality, Segregation, Development, Kenya
Session Type: Virtual Paper
Day: 4/8/2021
Start / End Time: 3:05 PM / 4:20 PM
Room: Virtual 35
Presentation File: No File Uploaded

While the study of spatial segregation of socioeconomic traits is well-developed for high-income societies, we know much less about socio-spatial differentiation elsewhere. Spatial inequality of socioeconomic status and access to resources in these settings may increase as they experience urbanization and socioeconomic transformation. We examine spatial inequality by several means—both aspatial segregation measures and contemporary spatial statistical measures—for small geographic units in urban and rural territory of Kenya. We make use of geocoded Demographic and Health Survey (DHS) data and include characteristics measuring socioeconomic standing (DHS wealth index, possession of consumer durables), and indicators of health and infrastructure conditions (water source, electricity access, child stunting and wasting). We also address the methodological challenge of the fact that these data are collected and assembled for geographic clusters (versus a complete enumeration) and also are promulgated with slightly displaced coordinates. Preliminary results point to appreciable variation within and between urban and rural territory in the degree of spatial inequality by characteristic. Figure 1 maps the spatial unevenness of possession of a consumer durable (radio) across Kenya districts. Figure 2 exploits the lower-level geography of the clusters to indicate the appreciable unevenness of several characteristics overall in Kenya, and also separately within the universe of urban and rural clusters. Upcoming work will investigate these types of spatial inequality more systematically and the degree to which spatial clustering is further explained by selective socioeconomic traits and, of key importance, how much spatial clustering remains in the presence of such controls.

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