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bibo:abstract "Spatial regression of panel data is an analytical approach used to model data\r\nwith spatial and temporal dimensions while accounting for spatial interdependencies.\r\nThis study uses panel data from districts and cities in West Java Province\r\nfor the period 2020-2024, provided by the BPS. The analysis was conducted using\r\nSAR and SEM with a Rook’s contiguity weighting matrix to capture spatial effects\r\nbetween regions. The results indicate the presence of spatial dependence in poverty\r\nlevels, suggesting that poverty conditions in a given region are influenced by conditions\r\nin neighboring regions. The SAR-REM model was selected as the best model\r\nbecause it accounts for both spatial effects and random effects in panel data. Model\r\nestimates indicate that the poverty line variable has a negative effect on poverty levels,\r\nwhile the Gini ratio and registered job seekers variables have a positive effect.\r\nOverall, poverty levels are influenced by socioeconomic factors as well as spatial\r\ninterdependence between regions, thus requiring policies that take regional aspects\r\ninto account."^^xsd:string;
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