ANALYSIS OF INCOME INEQUALITY AND CORRUPTION IN INDONESIA

Abstract

This research analyzes the relationship between income inequality and corruption in Indonesia, considering the influence of economic factors and the spatial dimensions between regions. Secondary panel data from 34 provinces for the 2017–2022 period were used, including government expenditure, per capita GDP, domestic direct investment (DDI), poverty ratio, Gini Ratio, and the Integrity Assessment Survey (IAS) as a proxy for the level of corruption. The methods used include the Granger causality test, spatial panel data regression, and spatial autocorrelation analysis with Moran's I and Local Indicator of Spatial Association (LISA). The research results show a two-way causal relationship between DDI and the poverty ratio, between corruption and per capita GDP, and between corruption and DDI. The Spatial Error Model (SEM) test reveals that per capita income, DDI, and the poverty ratio have a significant effect on income inequality, while in the corruption model, only DDI is significant. The Moran's I and LISA tests found that income inequality and corruption in Indonesia have a spatial pattern that tends to form clusters, both High-High and Low-Low, in certain regions. These findings indicate that policies for reducing inequality and eradicating corruption need to consider the spatial linkages between provinces to be more effective and equitable.