Tag Archives: spatial regression

Data and code for my columns

I would like to share the original data and code I use in all of the, well, software and code column.  I’m using Figshare to host all of this, and will try to keep it organized by column. Here is the data and original code for the first column, with the column found here and the  second column found here.  Thanks!


Poverty Segregation in Nonmetro Counties: A Spatial Exploration of Segregation Patterns in the US

By: Johnelle Sparks, Corey S. Sparks and Joseph J.A. Campbell

Abstract: Most research on segregation focuses on racial residential segregation in metropolitan statistical areas and typically uses a-spatial measures of segregation. What is less clear is if segregation measures operate in a similar fashion in nonmetropolitan areas and if spatial patterns exist for poverty segregation in nonmetro counties. The purpose of this research was to examine multiple dimensions of poverty segregation in the United States the period 2006-2010 for metropolitan and nonmetropolitan counties. Data for this analysis come from the 2006-2010 American Community Survey 5 year estimates, the 2000 U.S. Census of Population and Housing, Summary File 3 and the USDA Economic Research Service. Four different measures of poverty segregation were calculated, including both aspatial and spatial measures. A nonparametric Kruskal-Wallis test was used to test for variation in the segregation indices across metro and nonmetro areas and spatially autoregressive models were used to examine the socioeconomic correlates of poverty segregation. Results indicate significant variation in poverty segregation patterns in metro and nonmetro counties in the US, and nonmetro counties outside of the South have significantly lower levels of poverty segregation. This research adds to the literature by exploring patterns of metro and nonmetro poverty segregation and measuring different dimensions of segregation with an explicit spatial referent across counties in the contiguous United States in an effort to note differences in how segregation works across rural and urban places.

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A Study of County Child Poverty Rates in Puerto Rico: Does Space Matter?

By: Heidy Colon-Lugo and Corey S. Sparks

Abstract: Previous literature on childhood poverty in Puerto Rico is sparse. This is surprising since Puerto Rico exhibits very high poverty rates as compared to the rest of the United States. In this paper, we apply a structural perspective and consider how economic characteristics, household structure and migration patterns influence child poverty rates in Puerto Rico. Data for this paper come from the 2006-2010 Puerto Rico Community Survey (PRCS) summary files. We apply methods of exploratory spatial data analysis and spatial regression models to understand how municipio (county equivalents) level child poverty rates are influenced by these factors. A spatial modeling methodology was deemed appropriate since significant spatial structure is found for the child poverty rate and residuals from the Ordinary Least Squares model. Household composition, as measured by the percent of female headed households and the percent of grandparents caring for their own grandchildren consistently showed positive associations with child poverty. In terms of the economic sector variables, the proportion of the workforce in agriculture and proportion without a high school education showed significant positive effects on child poverty. With respect to migration, we find little to no impact, but we do find that child poverty is concentrated outside of the region adjacent to the capital of San Juan.

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