Doctoral Dissertation Research in Political Science: Policy Tool Bundling: Predicting the Selection of Economic Development Policy Instruments Using a Multivariate Probit Analysis

政治学博士论文研究：政策工具捆绑：使用多元概率分析预测经济发展政策工具的选择

• 批准号: 0921538
• 负责人: Richard Feiock
• 金额: $ 1.05万
• 依托单位: Florida State University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-09-01 至 2011-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0921538&HistoricalAwards=false
• 关键词: Doctoral; Dissertation; Research; Political; Science

This award is funded under the American Recovery and Reinvestment Act of 2009 (Public Law 111-5).Modeling choices of economic development incentive tools requires integration of a complex system of political and economic considerations and accounting for relationships among specific instruments within a bundle of policy options. Previous studies of policy instrument choice focus almost exclusively on individual policy tools in isolation. This neglects the reality that multiple tools work in conjunction with one another. Relationships among economic development incentives can result from local officials' pursuit of efficiencies, such as scale economies, or their pursuit of political gains, from satisfying ideological or constituency demands. The selection of any policy alternative is not independent of the other policy options. Just as with economic goods, policy tools can operate as complements or substitutes. This dissertation develops a theory of policy tool bundling to explain the configurations of development policies cities adopt to promote their economic or political interests. The policy bundling approach builds on extant research from the tools of government and policy diffusion literatures by investigating how factors internal to local governments and external pressures from neighboring jurisdictions influence the set of policy instruments selected. Pooled, longitudinal data is employed to identify codependences among incentives policies for Georgia cities. The longitudinal nature of the study allows predictions of the influence of previous and current economic policies choices while avoiding spurious relationships. Focusing on one state facilitates the inclusion of diffusion variables capturing the actions of surrounding communities. The influences of political institutions, particularly the presence of professional managers and at-large council representation are expected to encourage policy bundling based on efficiency concerns. The presence of elected executives and district representation are expected to encourage bundling based on political interests. A Bayesian multivariate probit model is used to predict economic policy choice because it allows simultaneous estimation of multiple policy adoptions and identification substitutive and complementary effects. The intellectual merit of this dissertation is derived from the synthesizing of the policy tools and diffusion policy theoretical frameworks to explain policy bundling. Systematic investigation of policy interdependencies is absent from extant empirical research in both areas. The theory of policy bundling developed in this research seeks to fill this lacuna and can be extended to numerous policy areas including economic development, environmental regulation, tax policy, and numerous other government initiatives which utilize multiple instruments simultaneously. Thus, this research promises to benefit both academics and practitioners and expand our understanding of how political institutions influence policy outcomes.

该奖项根据 2009 年《美国复苏和再投资法案》（公法 111-5）提供资金。经济发展激励工具的建模选择需要整合政治和经济因素的复杂系统，并考虑一系列政策选项中特定工具之间的关系。先前对政策工具选择的研究几乎完全集中于孤立的个别政策工具。这忽略了多种工具相互协同工作的现实。 经济发展激励之间的关系可能源于地方官员对效率的追求，例如规模经济，或者他们对政治利益的追求，即满足意识形态或选民的需求。 任何政策选择的选择都不是独立于其他政策选择的。 正如经济产品一样，政策工具可以作为补充或替代。 本文发展了一种政策工具捆绑理论来解释城市为促进其经济或政治利益而采取的发展政策的配置。 政策捆绑方法建立在政府工具和政策扩散文献的现有研究的基础上，通过调查地方政府的内部因素和邻近司法管辖区的外部压力如何影响所选的政策工具集。利用汇总的纵向数据来确定佐治亚州城市激励政策之间的相互依赖性。该研究的纵向性质允许预测以前和当前经济政策选择的影响，同时避免虚假关系。关注一个州有助于纳入捕捉周围社区行为的扩散变量。 政治机构的影响，特别是职业经理人和广大议会代表的存在，预计将鼓励基于效率考虑的政策捆绑。 民选高管和地区代表的存在预计将鼓励基于政治利益的捆绑。 贝叶斯多元概率模型用于预测经济政策选择，因为它允许同时估计多种政策的采用并识别替代和互补效应。 本文的学术价值源于对政策工具和扩散政策理论框架的综合来解释政策捆绑。 这两个领域的现有实证研究都缺乏对政策相互依赖性的系统调查。 本研究中提出的政策捆绑理论旨在填补这一空白，并且可以扩展到许多政策领域，包括经济发展、环境监管、税收政策以及同时利用多种工具的许多其他政府举措。 因此，这项研究有望使学者和实践者受益，并扩大我们对政治制度如何影响政策结果的理解。