Intraurban Industrial Location under Institutional and Accessibility Constraints: An Empirical Approach

对特定部门的城市内部工业区位的理解是城市空间结构理论的核心，并为一系列重要的政策问题提供知识基础。在理论方法方面，仍然有积极的研究扩展新古典经济学的投标-租金框架，人们对马绍尔工业区和集聚经济的作用普遍感兴趣，在地理学领域，人们对地点依赖(特别是机构)在塑造城市经济空间演变中的作用越来越感兴趣。尽管了解城市内部规模的企业区位选择很重要，但经验建模严重落后于当前的理论。开发相关模型的一个重大障碍是难以获得适用于城市内部分析的公司区位数据。理论和政策的形成都迫切需要新的经验性工作，以共同提高产业和空间分辨率，并纳入真实城市景观的重要制度特征。这项研究将开发和评估一种基于分层空间Cox回归的建模方法，该方法允许协变量与上述三种主要理论方法中的每一种方法一致。特定行业的位置数据将来自美国劳工统计局的地址地理编码和纵向匹配的机构记录。制度影响，以分区的形式，将直接纳入估计器，使用抽样函数来考虑城市经济空间的脱节性质。将对美国几个大都会地区的模型进行拟合和评估，这些地区被选为提供一套不同的机构背景。这项研究的首要目标不是坚持单一的理论观点，而是开发和验证一种建模方法，该方法将提供一个共同点，允许进行更广泛的理论测试，从而连接经济学和地理学。几个城市政策和公共投资决策直接受到城市内部产业区位理论的影响。其中一个重要的子集将包括：(1)交通规划-新建筑的选址决策和公共交通的方案设计，(2)试图缓解空间和技能不匹配问题的工作福利计划，(3)通过工业目标实现社区发展(无论是当地税收政策还是激励措施)，(4)与污染行业选址有关的环境正义问题，以及(5)与减轻工业和人口郊区化的影响有关的智能增长政策。这项研究将开发和测试一种统计建模方法，该方法将允许城市内部工业区位决策的更现实的规范。模型的结果将为城市政策分析提供更有力的依据，有助于完善城市产业结构和城镇内部就业动态的理论。

An understanding of sector-specific intraurban industrial location lies at the core of urban spatial structure theories and provides the knowledge-base that informs a range of important policy issues. In terms of theoretical approaches, there is still active research extending the bid-rent framework of neo-classical economics, there is widespread interest in the role of Marshallian industrial districts and agglomeration economies, and, there is, within geography, increasing interest in the role of place-dependence (especially for institutions) in shaping the evolution of urban economic space. Despite the importance of understanding firm location choices at the intraurban scale, empirical modeling has seriously lagged behind current theorizing. A significant obstacle to developing relevant models has been the accessibility of firm location data at scales suitable for intraurban analysis. Both theoretical and policy formation are starved for new empirical work that would jointly increase industry and spatial resolution and incorporate important institutional features of the real urban landscape. This research will develop and evaluate a modeling approach, based on hierarchical spatial Cox regression, that admits covariates consistent with each of the three major theoretical approaches mentioned above. Industry-specific location data will come from address geo-coded and longitudinally matched establishment records from the U.S. Bureau of Labor Statistics. Institutional influences, in the form of zoning, will be incorporated directly into the estimator using a sampling function to account for the disjoint nature of urban economic space. Models will be fitted and evaluated for several U.S. metropolitan areas that are selected to provide a diverse set of institutional contexts. Rather than adhering to a single theoretical perspective, the overarching goal of the research is to develop and validate a modeling approach that will provide a common ground allowing for a broader range of theory testing that bridges economics and geography.Several urban policy and public investment decisions are directly informed by theories of intraurban industry location. An important subset of these would include: (1) transportation planning - siting decisions for new construction and program designs for mass transit, (2) welfare-to-work programs which attempt to alleviate spatial- and skills- mismatch issues, (3) community development through industrial targeting (either local tax policy or incentives), (4) environmental justice issues related to the location of dirty industries, and (5) smart growth policies concerned with mitigating effects stemming from the suburbanization of both industry and population. This research will develop and test a statistical modeling approach that will admit more realistic specifications of intraurban industrial location decision-making. The results of the models will provide a stronger basis for urban policy analysis and will help to refine theories of urban industrial structure and intraurban employment dynamics.