This study aims to analyze the effects of Gross Regional Domestic Product (GRDP) per Capita, Social Assistance, Open Unemployment Rate, Informal Sector Labor Wages, Women's Income Contribution, Protein Consumption, and Population Growth Rate on poverty in the regencies/cities of Lampung Province from 2010 to 2024. The study employs a quantitative approach using secondary data in the form of panel data, which are analyzed through panel data regression using the Random Effect Model (REM). The simultaneous test results indicate that all independent variables jointly have a significant effect on poverty. Partially, GRDP per Capita, Informal Sector Labor Wages, Protein Consumption, and Population Growth Rate have significant negative effects on poverty, while Social Assistance, Open Unemployment Rate, and Women's Income Contribution have significant positive effects. The findings indicate that increases in GRDP per capita, informal sector labor wages, protein consumption, and population growth accompanied by adequate economic opportunities can reduce poverty. Conversely, high unemployment, social assistance concentrated in poorer areas, and a high contribution of women's income among vulnerable households are associated with increased poverty. The results are expected to serve as a consideration in formulating poverty alleviation policies in Lampung Province.
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