Spatial Scale of Agglomeration and Dispersion: Theoretical foundations and empirical implications
Spatial Scale of Agglomeration and Dispersion: Theoretical foundations and empirical implications
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发表时间：
2017-08
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通讯作者：
T. Akamatsu;Tomoya Mori;M. Osawa;Yuki Takayama
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作者：
T. Akamatsu;Tomoya Mori;M. Osawa;Yuki Takayama
本文重新审视了多区域设置中各种现有的经济地理模型。它研究了每个模型固有的集聚和分散的空间尺度。在我们的统一分析框架中，这些模型简化为两个典型类别：一类具有全局色散力，另一类具有局部色散力。它们的形式区别在于前者是相关的，而后者独立于模型的距离结构。这些类别表现出两个明显的差异。第一个区别涉及它们对运输成本的反应：全球和本地分散力分别由较高和较低的运输成本引发。因此，在具有两种分散力的现实模型中，运输成本的下降同时导致全球范围内的集聚和局部范围内的分散。第二个差异涉及集聚模式：前者出现了多种集聚，并在全球范围内扩散到各个区域，而后者的集聚总是采取移动代理的单峰区域分布的形式。内生集聚机制通常不会孤立运输成本给定变化时集聚增长或下降的地点。然而，它们提供了对集群的全球空间分布以及单个集群的局部空间范围的预测。这些知识为区域集聚的简化形式回归得出的一组看似无关的经验结果提供了一致的解释（例如，Baum-Snow，2007；Baum-Snow、Brandt、Henderson、Turner 和Zhang，2017；Duranton 和Turner，2012；Faber，2014）；它提供了一组新的可检验的假设。此外，我们的分析框架提供了基于结构模型的区域集聚方法中处理效果的正式预测。讨论了最标准公式的应用（例如，Allen 和 Arkolakis，2014 年；Redding 和 Sturm，2008 年）。
This paper revisits a wide variety of existing economic geography models in a many-region setup. It investigates the spatial scale of agglomeration and dispersion intrinsic to each model. In our unified analytical framework, these models reduce to two canonical classes: one with a global dispersion force and the other with a local dispersion force. Their formal distinction is that the former is dependent, whereas the latter is independent of the distance structure of the model. These classes exhibit two stark differences. The first difference concerns their response to transport costs: Global and local dispersion forces are triggered by higher and lower transport costs, respectively. Consequently, in a realistic model with both types of dispersion forces, a decrease in transport costs simultaneously causes both agglomeration at the global scale and dispersion at the local scale. The second difference concerns the agglomeration pattern: multiple agglomerations emerge and spread globally over the regions in the former, whereas agglomeration always takes the form of a unimodal regional distribution of mobile agents in the latter. Endogenous agglomeration mechanisms generally do not isolate the locations at which agglomerations grow or decline for a given change in transport costs. However, they offer predictions for the global spatial distribution of agglomerations as well as the local spatial extent of an individual agglomeration. This knowledge provides a consistent explanation for the set of seemingly unrelated empirical results from reduced-form regressions on regional agglomerations (e.g., Baum-Snow, 2007; Baum-Snow, Brandt, Henderson, Turner and Zhang, 2017; Duranton and Turner, 2012; Faber, 2014); it provides a new set of testable hypotheses. Moreover, our analytical framework provides formal predictions of treatment effects in the structural model-based approaches for regional agglomeration. Applications to the most standard formulations (e.g., Allen and Arkolakis, 2014; Redding and Sturm, 2008) are discussed.