Penerapan Model Regresi Data Panel dalam Analisis Faktor-Faktor Penyebab Kemiskinan di Provinsi Papua (Jurnal EurekaMatika, 2024)
Poverty is when a person cannot adequately fulfill his daily needs. The data is taken from the official website of the Papua Province Central Statistics Agency (BPS). The panel data regression method was analyzed with the help of the EViews 12SV lite version for students and the IBM SPSS Statistics 24. This research aims to examine the most influential factors causing poverty in Papua and obtain the best regression model. Based on the Chow test, Hausman test, significance test, and classical assumption tests, the best model for panel data regression for modeling poverty in Papua is the fixed effect model (FEM). The results of the analysis show that 99.78% of the poor population has a life expectancy, human development index, gross regional domestic product, labor force participation rate, and open unemployment rate. Meanwhile, the remaining 0.22% is explained by other variables outside the model. Life expectancy and the human development index have a significant effect, while gross regional domestic product, labor force participation rate, and open unemployment rate are not significant on the poor population in Papua in 2017-2020.
Keywords: Fixed Effect Model; Poor Population; Regression Panel Data