<![CDATA[This study comparatively analyzes the spatial patterns and determinants of inter-provincial income inequality in Indonesia using the Theil Index for the years 2016 and 2023. Based on the Theil Index calculations, the level of inequality increased in 2023 compared to 2016. The Global Moran’s I test results reveal a significant positive spatial autocorrelation in both observation periods, confirming the existence of spatial dependence. The analysis proceeds with the Local Indicator of Spatial Association (LISA) and the Spatial Error Model (SEM). Specifically, the LISA mapping identifies regional polarization, wherein provinces with high inequality cluster together (High-High cluster) and are concentrated in Eastern Indonesia. Furthermore, the SEM estimations indicate that per capita GRDP and economic structure have a positive and significant effect on widening inequality. Conversely, formal labor exhibits a negative and significant effect in reducing inequality, while the Human Development Index (HDI) shows a negative but insignificant effect. Additionally, the significant spatial error coefficient (λ) confirms the presence of spatial dependence within the error component, indicating that unobserved shocks in one province generate spatial spillover effects on the inequality levels of its neighboring regions.]]>
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