Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/301789 
Year of Publication: 
2024
Publisher: 
ZBW - Leibniz Information Centre for Economics, Kiel, Hamburg
Abstract: 
In rural development research, social capital (SC) complements the causal gap between the endowment of resources and other capital in a community and the performance of collective actions, such as common-pool resource management. However, the concept of SC is ambiguous and its measurement is controversial. This study focuses on rural SC and attempts to measure it inductively using data (994 communities) related to various collective actions (22 types), rather than deductively piling up the detailed components of SC, as several studies have done. Hierarchical latent variable models are used to understand the hierarchical structure of SC. We used spatial regression models to examine the policy’s causal impacts on SC accumulation while considering spatial heterogeneity. The results show that SC has spatial heterogeneity and a hierarchical structure, depending on the internal (bonding-type) and external (bridging-type) components, as well as on the difference between general activities and collective agricultural actions. The SC accumulation is strongly correlated with traditional and agriculture-related activities. Furthermore, policies increase comprehensive SC by approximately 20% but are more effective for internal SC than for external SC. These results suggest the need for policy options such as agglomeration bonuses when expanding the range of collective actions. Other findings indicate that the reinforcement of agricultural corporations and educational facilities are also effective in accumulating SC.
Subjects: 
social capital
inductive measurement
heterogeneity
policy impact
hierarchical structure
spatial regression
Document Type: 
Preprint

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