This study aims to analyse the influence of inflation, labour, and the Human Development Index (HDI) on the economic growth of provinces in Java Island in the period 2015-2024 using a spatial econometric approach. Java Island is the centre of national economic activity; each province has a different development capacity, economic structure, and growth dynamics. The study uses balanced panel data consisting of six provinces and ten years of observation. Spatial relationships between regions are represented by a neighbourhood-based spatial weight matrix, while testing is carried out using Moran's I, the Spatial Autoregressive Model (SAR), the Spatial Error Model (SEM), and the Spatial Durbin Model (SDM). Descriptive results indicate an average economic growth of 4.407 percent, with the deepest contraction occurring during the pandemic period. Moran's I test indicates that most years do not exhibit significant spatial autocorrelation, but 2019 and 2020 showed indications of spatial autocorrelation at the 5% level, with a strong global spatial clustering pattern not yet detected. The spatial model estimation results show that after controlling for the economic shock caused by the pandemic, all key variables become statistically insignificant. A comparison of the SAR, SEM, and SDM models based on spatial parameters, AIC, and BIC provides no strong evidence of spatial dependence. Based on AIC and BIC, SAR is relatively more efficient, but its spatial parameters are insignificant; interpretation of spatial effects requires proportional analysis.
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