Analisis Regresi Data Panel pada Faktor-Faktor yang Mempengaruhi Tingkat Kemiskinan Provinsi Sumatera Utara Tahun 2016-2020

Abstract

This study aims to obtain the best model of poverty rate data in thirty-three districts/cities in North Sumatra Province from 2016 to 2020 and determine the effect of life expectancy, average length of schooling, per capita expenditure figures, Gross Regional Domestic Product (GRDP), income inequality and population density to poverty level using panel data regression method. In panel data regression, three estimation methods used are Common Effect Model (CEM), Fixed Effect Model (FEM) and Random Effect Model (REM). These three approaches will be selected through testing namely Chow test, Hausman test, and Lagrange Multiplier test. From the results of the model specification test, it can be seen that the best model is the Random Effect Model (REM). The results of the significance test show that the variables of the average length of schooling, the rate of expenditure per capita have a negative and significant effect on the poverty level in the province of North Sumatra. The population density variable has a positive and significant effect on the poverty level in North Sumatra Province.