Regional inequality analysis in Indonesia multinomial logistic regression approach

This study aims to analyze the typology of regional inequality in Indonesia and the opportunity for regional inequality shifts due to changes in independent variables. The analysis method is carried out using the Williamson index and the Theil index. Furthermore, multinomial logit regression analysis was carried out to see the influence of the independent variable on the dependent variable. The results showed four classifications of regional inequality based on the value of the Williamson and Theil indexes. Thirty-seven per cent of provinces fall under the severe inequality classification, and 46 per cent of provinces fall under the low inequality classification. Significant variables in areas with severe inequality classification are Infrastructure, Human Resources, Investment, Fiscal Decentralization, Regional Expansion, Population, and Spending on Pro-Poor Growth Function. Significant variables in areas with high inequality classification are Openness, Fiscal Decentralization, Regional Expansion, and Population. Infrastructure, Investment, and Population are significant variables in regions with moderate inequality classification. Significant variables in areas with low inequality classification are Economic Growth, Human Resources, Fiscal Decentralization, Regional Expansion, and Spending on Pro-Poor Growth Functions.