Economic Spatial Patterns and Human Development Index Districts and Cities in Five Southern Sumatera Provinces

Ahmad Dhea Pratama, Ukhti Ciptawaty
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Abstract

The Spatial linkages between regions are an important part of a regional economy as an analysis of relations and interactions between regions. Regional economic studies tend to focus only on the independence of a region so that it does not consider the spatial effects that occur between one region and another. This study focuses on looking at spatial autocorrelation which will produce spatial patterns and spatial linkages between regions of the gross regional domestic product and the human development index, with the findings of seeing spatial interactions and patterns of similarities or differences in the formation of the two variables between regions. The research area focuses on 60 districts and cities in 5 provinces of Southern Sumatera with the 2015-2019 research year, the analysis method uses Geographic Information Systems with Geoda software, the results of the calculations will produce Moran’s I, LISA Significance and Clustered maps.  The outcomes show that there has been a spatial relationship as certain autocorrelation of GRDP and HDI, the formation of the economy and human capital has a spatial relationship, results of Moran'I show that the positive value of the two variables has a group pattern and has a level of formation of GRDP and HDI with the same characteristics, moran scatterplot shows the similarity with the resulting region divided into 4 quadrants. The LISA cluster map and the LISA marking are the similarities in the findings of the GRDP and HDI results, but both variables have no findings of Low-high patterns.
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南苏门答腊五省城市经济空间格局与人类发展指数
区域间空间联系是区域经济的重要组成部分,是对区域间关系和相互作用的分析。区域经济研究往往只关注区域的独立性,而没有考虑区域间的空间效应。本研究的重点是研究区域生产总值与人类发展指数的空间自相关性,这将产生区域之间的空间格局和空间联系,并发现两个变量在区域之间形成的空间相互作用和相似或不同的模式。研究区域以南苏门答腊省5个省60个区市为研究对象,以2015-2019年为研究年度,分析方法采用Geoda软件的地理信息系统,计算结果将生成Moran’s I、LISA Significance和Clustered地图。结果表明,GRDP与HDI之间存在一定的空间自相关关系,经济与人力资本的形成存在一定的空间关系,Moran’i结果表明,GRDP与HDI具有相同特征的两个变量的正值具有类群模式,具有一定的形成水平,Moran散点图显示了相似性,结果将区域划分为4个象位。LISA聚类图和LISA标记是GRDP和HDI结果的相似之处,但两个变量都没有发现低-高模式。
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审稿时长
12 weeks
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