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Title: MEASURING U.S. SPATIAL POVERTY CONCENTRATION: METHODOLOGICAL IMPLICATIONS FOR PUBLIC POLICY
Citation Type: Dissertation/Thesis
Publication Year: 2018
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Abstract: The available literature has shown a growing and a compelling interest amongst scholars and researchers to spatially measure neighborhood poverty concentration. Previous research has defined poverty measurement as an intricate process that involves analysis of the demographic and socioeconomic characteristics within a spatial environment (Rogers, 2015). Poverty measurement is, therefore, important for understanding the complexity of poverty and for assessing the effectiveness of poverty-mitigating policies (Rogers, 2015) Literature on measuring geographically concentrated poverty has focused on two main models: (1) the traditional global model that includes, for example, Ordinary Least Squares (OLS) classic regression, spatial autocorrelation (global Moran’s I); (2) the local geospatial model, mainly, Geographically Weighted Regression (GWR) (Anselin, 1995; Fotheringham & Brunsdon, 1999; Lloyd, 2010; Sandoval, 2015c). The global model measures the overall clustering of data and yields a single-value statistic for the whole study area. The local geospatial model, on the other hand, disaggregates global statistical data and yields multi-value statistics across different locations (Anselin, 1995; Lloyd, 2010; Sandoval, 2015c)...
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Authors: Mohamed, Abdalla A.
Institution: Saint Louis University
Department: Sociology
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Data Collections: IPUMS NHGIS
Topics: Population Mobility and Spatial Demography
Countries: United States