Method Generalized Linear Model and Generalized Linear Mixed Model for Panel Data Human Development Index (HDI) in Indonesia

Abstract

The Generalized Linear Model method and the Generalized Linear Mixed Model method are methods that delete the assumption of data normality for the response variables. The two methods are compared and applied to the Human Development Index (HDI) panel data to see the best model and determine what factors affect HDI. The predictor variables used include: GRDP, ratio of elementary school teachers to elementary students, ratio of junior high school teachers to junior high school students, ratio of high school teachers to high school students, number of health workers, population and poverty ratio. The data source comes from BPS by taking three provinces classified into provinces with very high HDI represented by DKI Jakarta province, Province with high HDI represented by West Java province, and provinces with moderate HDI represented by NTB province. The results showed that neither the GLM method nor the GLMM method could be used to model HDI data. The factors that influence the HDI for the data for the provinces of Jakarta and NTB are the GRDP factor, the ratio of elementary school teachers to elementary students, the ratio of junior high school teachers to junior high school students, the number of health workers, and the total population. In the data for the province of Jakarta, an anomaly in economic theory is found which states that an increase in GRDP causes a decrease in the HDI value. This indicates that the GRDP factor for the DKI Jakarta province isnot sufficient to represent the economic dimension as one of the indicators in forming the HDI value. The factors that influence the HDI value in the province of West Java are the GRDP factor and the poverty ratio, while other factors have no significant effect on the HDI value.