While scholars and practitioners frequently laud the potential of networks to address complex policy problems, empirical evidence of the effectiveness of networks is scarce. This study examines how changes in network structure (centralization and transitivity), network composition (sector diversity and geographic range), and tie properties (stability and strength) influence community-level outcomes. Relying on a statutory requirement in the state of Iowa requiring local governments to file all instances of intergovernmental and intersectoral collaboration, we measure collaboration networks in 81 counties over 17 years in the areas of crime and economic development. Using fixed effects models, we examine how changes in the structure and composition of these county-level networks affect substantive policy outcomes. Our findings indicate that network properties matter, but that the specific properties may be context dependent. We find network centralization and stability are stronger predictors of crime while network composition is more strongly associated with economic development.

中文翻译：

---

分析网络解决公共问题的有效性：来自纵向研究的证据

虽然学者和从业者经常称赞网络解决复杂政策问题的潜力，但关于网络有效性的经验证据却很少。本研究考察了网络结构（集中化和传递性）、网络组成（部门多样性和地理范围）和联系属性（稳定性和强度）的变化如何影响社区层面的结果。根据爱荷华州的一项法定要求，要求地方政府提交政府间和跨部门合作的所有实例，我们衡量 81 个县在犯罪和经济发展领域超过 17 年的合作网络。使用固定效应模型，我们研究了这些县级网络结构和组成的变化如何影响实质性政策结果。我们的发现表明网络属性很重要，但特定属性可能取决于上下文。我们发现网络中心化和稳定性更能预测犯罪，而网络组成与经济发展的关联性更强。