Spatial analysis of social capital and community heterogeneity at the United States county level

Social capital, defined as the resources or benefits received through one's connections with others, contributes to economic efficiency, growth of communities, and population health. In 2006, Rupasingha et al. [1] developed a high-quality, US county-level social capital index based on individua...

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Veröffentlicht in:Applied geography (Sevenoaks) 2023-12, Vol.162
Hauptverfasser: Peluso, Alina, Tuccillo, Joseph, Sparks, Kevin, Kapadia, Anuj, Hanson, Heidi A.
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Kapadia, Anuj
Hanson, Heidi A.
description Social capital, defined as the resources or benefits received through one's connections with others, contributes to economic efficiency, growth of communities, and population health. In 2006, Rupasingha et al. [1] developed a high-quality, US county-level social capital index based on individuals' participation in associational activities, trust, and civic engagement which is available for years 1990, 1997, 2005, 2009, and 2014. Since their introduction, such measures have been used in many ways, especially to investigate the association between social capital and community heterogeneity. Nevertheless, the non-stationary spatial nature of this relationship has rarely been considered. The purpose of this study was two-fold. (1) Based on the definition outlined by Rupasingha et al., and by using free, publicly available, and reliable data, we generated a 2019 US county-level measure of social capital that can be employed in contemporary studies. (2) We assess local spatial variations of social capital with non-stationary variables via a Geographically Weighted Regression which exhibited substantial improvements in model performance over the Ordinary Least-Squares model. Our findings contribute to literature linking social capital to economic growth of communities, which is essential for creating a sustainable future for business enterprises, communities, and society at large.
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(2) We assess local spatial variations of social capital with non-stationary variables via a Geographically Weighted Regression which exhibited substantial improvements in model performance over the Ordinary Least-Squares model. 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(2) We assess local spatial variations of social capital with non-stationary variables via a Geographically Weighted Regression which exhibited substantial improvements in model performance over the Ordinary Least-Squares model. 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subjects GENERAL AND MISCELLANEOUS
income inequality
racial diversity
social capital index
US county-level
title Spatial analysis of social capital and community heterogeneity at the United States county level
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