Analysis of Spatial Autocorrelation and Causality GRDP and Income Inequality in Java

Abstract

Research on the relationship between GRDP and income inequality shows that there is a spatial autocorrelation, however, empirical data shows that there is still income inequality that differs between regions, so it is necessary to re-examine the relationship. The island of Java is the main pillar of Indonesia's economic cycle, but the income inequality between the provinces is still high. This study aims to identify the magnitude of income inequality in Java. Identify the autocorrelation of GRDP and income inequality spatially, and in clusters and identify the causal relationship between GRDP and income inequality in Java. The analysis method uses the Williamson Index, Moran Index, Local Indicator of Spatial Autocorrelation (LISA) using the LISA Clustermap, and Granger Quality. This study is on the level of income inequality in each province in Java based on the Williamson Index value in the category of high inequality, having a negative autocorrelation value (the pattern tends to spread) and there is no spatial autocorrelation. Autocorrelation based on LISA Clustermap there is a pattern of cluster linkages (clustering and influencing each other) which has a High-Spot value so that there are areas that can be used as areas of cooperation for development.