Analysis Of Factors Influencing The Poverty Rate In Central Java Province Using Panel Data Regression

Abstrak

The issue of poverty in Indonesia has become a severe problem, particularly in Central Java Province, the third most populous province in Indonesia. The population of Central Java Province is approximately 36.74 million people, and it ranks second in having the highest poverty rate in Indonesia after East Java. Over the years, there has been an increase in poverty, peaking in 2021 at 11.79%. This study aims to model the poverty rate in Central Java Province using five independent variables, including provincial minimum wage, school participation rate, open unemployment rate, population density, and dependency ratio, using panel data regression and to identify the factors influencing the poverty rate. Three approaches used in panel data regression consist of the Common Effect Model (CEM), Fixed Effect Model (FEM), and Random Effect Model (REM). Based on the parameter testing results with panel data regression, it can be concluded that the best model for analyzing the factors influencing the poverty rate in Central Java Province is the FEM approach. The testing results with the FEM approach obtained a regression model Yit=7,290131+7,72×10-7X1it -0,021603X2it+0,086597X3it+ 8,27×10-5X4it+ 0,065326X5it. Provincial minimum wage, open unemployment rate, and dependency ratio variables positively and significantly affect the poverty rate in Central Java Province. In contrast, the population density has a positive but not significant effect. Meanwhile, the school participation rate has a negative and not significant effect.