Estimating the Effects of Economic Interactions in a Hierarchically Organized Space: Possibilities of the Balance Method

IF 1.6 3区工程技术 Q3 OPERATIONS RESEARCH & MANAGEMENT SCIENCE Networks & Spatial Economics Pub Date : 2022-01-01 DOI:10.14530/se.2022.4.009-035

N. Dzhurka

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Abstract

In this paper we discuss the capabilities of input-output tables for obtaining the estimates of system effects generated by interregional interactions in the hierarchically organized space. Two options of integrating the concepts of interregional interactions and central place are presented, one of which implies the a priori, the other – the a posteriori solution to the problem of identifying (constructing) a market hierarchy. While the first one is used only in situations when the system effects are reduced to the spill-over of economic activity from the periphery to the center, the second one is used in more general situations when the system effects include not only spill-over effects but also the feedback effects. We consider the feedback loop input-output analysis, which allows us to get a posteriori estimates of regions distribution by the levels of spatial hierarchy. And determine that it had varying effectiveness for the cases of Japan and Russia. In accordance with the existing methods of decomposition of spatial multipliers the system effects of interregional interactions are determined, on the one hand, as a residual multiplier effect obtained after identifying the effects of intra-regional interactions, on the other hand, as a result of superposition of the effects of interregional interactions within the framework of dyads, triads, tetrads, etc. composed of regions. In order to obtain estimates of the system effects generated by interactions on markets of different levels (provided that these levels are identified), we propose the method of localizable partition, organizing the calculation of the structural blocks of spatial multipliers in the ‘from the general to the particular’ logic (from the system effects of interactions on the national market to the effects of interactions on local markets). On the basis of this method, we estimate the size and structure of the system effects absorbed by the economies of the three central regions of Japan (Kanto, Chubu, Kinki), which form the core of the national economic space

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等级组织空间中经济相互作用的影响评估:平衡方法的可能性

在本文中，我们讨论了投入产出表的能力，以获得在层次组织空间中由区域间相互作用产生的系统效应的估计。提出了整合区域间相互作用和中心位置概念的两种选择，其中一种暗示了识别(构建)市场等级问题的先验解决方案，另一种-后验解决方案。前者仅用于系统效应减少为经济活动从外围向中心的溢出效应的情况，而后者则用于更一般的情况，即系统效应不仅包括溢出效应，还包括反馈效应。我们考虑了反馈回路的输入-输出分析，这使我们能够通过空间层次水平获得区域分布的后验估计。并确定它在日本和俄罗斯的案例中有不同的效果。根据现有的空间乘数分解方法，确定区域间相互作用的系统效应，一方面是识别区域内相互作用效应后得到的剩余乘数效应，另一方面是在由区域组成的二分体、三分体、四分体等框架内叠加区域间相互作用效应的结果。为了获得由不同层次的市场相互作用产生的系统效应的估计(前提是这些层次是确定的)，我们提出了可局部划分的方法，以“从一般到特殊”的逻辑组织空间乘数的结构块的计算(从相互作用对国家市场的系统效应到相互作用对地方市场的影响)。在此基础上，我们对构成日本国民经济空间核心的关东、中部、近畿三个中部地区经济吸收的制度效应的规模和结构进行了估算

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来源期刊

Networks & Spatial Economics 社会科学-运筹学与管理科学

CiteScore

4.00

自引率

4.20%

发文量

审稿时长

>12 weeks

期刊介绍： Networks and Spatial Economics (NETS) is devoted to the mathematical and numerical study of economic activities facilitated by human infrastructure, broadly defined to include technologies pertinent to information, telecommunications, the Internet, transportation, energy storage and transmission, and water resources. Because the spatial organization of infrastructure most generally takes the form of networks, the journal encourages submissions that employ a network perspective. However, non-network continuum models are also recognized as an important tradition that has provided great insight into spatial economic phenomena; consequently, the journal welcomes with equal enthusiasm submissions based on continuum models. The journal welcomes the full spectrum of high quality work in networks and spatial economics including theoretical studies, case studies and algorithmic investigations, as well as manuscripts that combine these aspects. Although not devoted exclusively to theoretical studies, the journal is "theory-friendly". That is, well thought out theoretical analyses of important network and spatial economic problems will be considered without bias even if they do not include case studies or numerical examples.