Education and Long Run Economic Growth in Selected Low Income Countries

This research will examine the education and long run economic growth in selected low-income countries. This study’s used panel data to analyse the test statics; the dependent variables that used for this research is gross national income per capital, while the independent variable included human development index, adult literacy rate, productivity capacity index, and gender parity index for gross secondary school enrolment for the period 2007 to 2021 which over a 15 year timeframe. The following panel data regression analyses are used in this study to evaluate the relationships between the variables: Pooled Ordinary Least Squares (POLS), Fixed Effect Model (FEM), Random Effect Model (REM), Hausman test, Likelihood Ratio (LR) test, and Breusch-Pagan Lagrange (LM). The empirical findings of the final model shows that the most appropriate panel regression model for selected low-income countries is Fixed Effect Model (FEM). As the results found that, the coefficients of all independent variables have the positive relationship with dependent variable. Meanwhile, if increasing of 1percent in independent variables will lead the increasing of 1percent in dependent variable. Besides that, there are two independent variables are significant impact on dependent variable and two independent variables are insignificant impact on dependent variable