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.

社会资本被定义为通过与他人的联系获得的资源或利益，有助于经济效率、社区发展和人口健康。 2006 年，Rupasingha 等人。 [1] 根据个人对社团活动、信任和公民参与的参与情况制定了高质量的美国县级社会资本指数，该指数可在 1990 年、1997 年、2005 年、2009 年和 2014 年使用。自推出以来，这些措施已用于多种用途，特别是用于调查社会资本与社区异质性之间的关联。然而，这种关系的非平稳空间性质很少被考虑。这项研究的目的有两个。 (1) 根据 Rupasingha 等人概述的定义，并通过使用免费、公开且可靠的数据，我们生成了 2019 年美国县级社会资本衡量标准，可用于当代研究。 (2) 我们通过地理加权回归评估具有非平稳变量的社会资本的局部空间变化，该回归显示出模型性能比普通最小二乘模型有显着改进。我们的研究结果有助于将社会资本与社区经济增长联系起来，这对于为企业、社区和整个社会创造可持续的未来至关重要。