Modeling Expected Years of Schooling Based on Socioeconomic Factors in Banten Province Using the Gamma Regression Model

Resti Oktaviani

Abstract


Despite rapid economic growth in Banten Province, the disparity in Expected Years of Schooling (HLS) between districts/cities remains significant due to socioeconomic factors. This study aims to analyze the effect of Poverty Percentage, Gender Development Index (IPG), and Beneficiary Families (KPM) on HLS using Gamma Regression. A quantitative approach using secondary data from BPS Banten (2020-2024), the population of all districts/cities (n=42 total sampling observations), was analyzed through GLM R Studio with the link log function. The results show that IPG has a significant positive effect on HLS (p=0.007), while Poverty Percentage and KPM have a non-significant negative effect. The model has a high fit (AIC=79.05, MAPE=3.62%, RMSE=0.581) without heteroscedasticity, autocorrelation, or multicollinearity. Gender equality has been shown to be crucial for increasing access to education, although poverty remains a structural barrier.


Keywords


Banten Province, Gamma Regression, Gender Development Index, Expected Years of Schooling, Socioeconomic Factors

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References


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DOI: https://doi.org/10.31004/jele.v11i2.2020

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