This study explores the contrasting racialized geographies of St. Louis County and factors of local college accessibility by re-framing the concepts of college deserts and oases post the Ferguson uprising. Through a Geographic Information Systems (GIS) analysis of educational divides, capital accumulation, and policing, we found dual spatial landscapes: a geography of Whiteness and higher education capital accumulation in southern St. Louis and a predominantly Black working-class geography of Ferguson in northern St. Louis. These dual landscapes capture the social, economic, and racial contexts of St. Louis as it informs the discourse of college-going.
In a world where one's future is heavily impacted by having postsecondary education, access to college is a pertinent research topic. Access is a widely researched topic, but only recently has college access been studied specifically. This study proposes a geographic information systems based methodology for quantifying college access at multiple spatial scales. This methodology was implemented with the Python programming language and ArcGIS. A sample of six metropolitan statistical areas were identified and analyzed using the developed methodology. Within this sample, college access varied primarily by socio-economic status although some variation between race/ethnicity was identified. Further research is needed to assess whether these trends are generalizable. Quantification of college access will aid policy-makers to prepare reforms to reduce the inequity of college access.
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Ruhr Economic Papers #509
In this study, we set up a dynamic stochastic general equilibrium (DSGE) model with upward looking consumption comparison and show that consumption externalities are an important driver of consumer credit dynamics. Our model economy is populated by two different household types. Investors, who hold the economy's capital stock, own the firms and supply credit, and workers, who supply labor and demand credit to finance consumption. Furthermore, workers condition their consumption choice on the investors' level of consumption. We estimate the model and find a significant keeping up mechanism by matching business cycle statistics. In reproducing credit moments, our proposed model significantly outperforms a model version in which we abstract from consumption externalities.
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