Panel Data Regression Model on Factors Affecting Poverty Levels in East Java Province

Abstract

This research aims to analyze the factors that influence the level of poverty in East Java Province using a panel data regression model approach. Secondary data from 38 districts/cities in East Java during 2019–2023 were sourced from the Central Statistics Agency (BPS). The dependent variable is the poverty level, while the independent variables consist of GRDP per capita, average years of schooling, labor force participation rate (TPAK), population density, life expectancy (AHH), and economic growth rate. Model selection was performed through the Chow Test and Hausman Test. The estimation results show that the Fixed Effect Model (FEM) is the best model with a coefficient of determination (R²) of 0.669, meaning 66.9% of the variation in poverty levels can be explained by the six independent variables. Partial tests indicate that average years of schooling is the most significant factor influencing poverty levels in East Java Province. These findings emphasize the importance of improving education quality in poverty alleviation efforts.