Spatial analysis of social capital and community heterogeneity at the United States county level
Bibliographic Data
| ID | 21449804 |
|---|---|
| Authors | Alina Peluso (0000-0003-2895-0406, Oak Ridge National Laboratory, corresponding author), Joseph V Tuccillo (0000-0002-5930-0943, Oak Ridge National Laboratory), K Sparks (0000-0002-0340-8090, Oak Ridge National Laboratory), Anuj Kapadia (0000-0003-2755-4495, Oak Ridge National Laboratory), Heidi A Hanson (0000-0003-0056-196X, Oak Ridge National Laboratory) |
| Year | 2024 |
| Volume | 162 |
| Pages | 103168 |
| Publication date | 2024-01-01 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Applied Geography (JOURNAL) |
| Journal identifiers | ISSN: 0143-6228 • E-ISSN: 1873-7730 |
| Publisher | Elsevier BV (PUBLISHER) |
| DOI | 10.1016/j.apgeog.2023.103168 |
| OpenAlex | W4389802962 |
| Language | EN |
| Citations received | 7 |
| References cited | 22 |
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
Capital (architecture) · Civic engagement · Econometrics · Economic geography · Economic growth · Economics · Geography · Index (typography) · Ordinary least squares · Political science · Politics · Population · Regional science · Social capital · Social engagement · Social mobility · Social science · Sociology · Demography · Health disparities and outcomes · Spatial and Panel Data Analysis · Urban, Neighborhood, and Segregation Studies
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| Unique citing works | 7 |
|---|---|
| Citations per year | 3.5 |
| Citation span | 2024 - 2026 (3) |
| Citation velocity | current |
| Highly cited | No |
| Citation types | Neutral: 7 |