1Department of Economics, Indonesia
2Universitas Islam Indonesia, Indonesia
BibTex Citation Data :
@article{JDEP43919, author = {Aminuddin Anwar}, title = {SPATIAL ANALYSIS OF REGIONAL POVERTY IN CENTRAL JAVA INDONESIA}, journal = {JURNAL DINAMIKA EKONOMI PEMBANGUNAN}, volume = {5}, number = {1}, year = {2022}, keywords = {Spatial Autoregressive Model, Regional Poverty, Economic Growth, Population}, abstract = { This study analyzes the effect of the spatial interaction of poverty in districts/cities in Central Java for three periods, 2010, 2015, and 2019. The method used in this research is a spatial analysis using Global Moran's I Statistics, Local Indicator of Spatial Association (LISA), and spatial regression with Spatial Autoregressive Model (SAR). Spatial distribution analysis concluded that the high concentration of poverty for three periods occurred in the southern part of Central Java, accompanied by a high concentration of unemployment and population. The results of non-spatial regression analysis concluded that there was a negative effect of economic growth on poverty, a positive influence of population on poverty in Central Java for the three study periods, and a negative effect of education on poverty only in 2019. The estimation model uses SAR as the best model chosen to explain poverty conditions in Central Java, and it shows that poverty in neighboring areas has a positive value, so it can be concluded that there is a spatial effect of poverty in Central Java. The spatial influence of poverty implies that the government carries out an integrated poverty alleviation program to produce policies that have local impacts in one area but must have a spatial impact, which means reducing poverty between regions. }, issn = {2620-3049}, pages = {36--55} doi = {10.14710/jdep.5.1.36-55}, url = {https://ejournal.undip.ac.id/index.php/dinamika_pembangunan/article/view/43919} }
Refworks Citation Data :
This study analyzes the effect of the spatial interaction of poverty in districts/cities in Central Java for three periods, 2010, 2015, and 2019. The method used in this research is a spatial analysis using Global Moran's I Statistics, Local Indicator of Spatial Association (LISA), and spatial regression with Spatial Autoregressive Model (SAR). Spatial distribution analysis concluded that the high concentration of poverty for three periods occurred in the southern part of Central Java, accompanied by a high concentration of unemployment and population. The results of non-spatial regression analysis concluded that there was a negative effect of economic growth on poverty, a positive influence of population on poverty in Central Java for the three study periods, and a negative effect of education on poverty only in 2019. The estimation model uses SAR as the best model chosen to explain poverty conditions in Central Java, and it shows that poverty in neighboring areas has a positive value, so it can be concluded that there is a spatial effect of poverty in Central Java. The spatial influence of poverty implies that the government carries out an integrated poverty alleviation program to produce policies that have local impacts in one area but must have a spatial impact, which means reducing poverty between regions.
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