ESTIMATION OF GEOGRAPHICALLY WEIGHTED PANEL REGRESSION MODEL WITH BISQUARE KERNEL WEIGHTING FUNCTION ON PERCENTAGE OF STUNTING TODDLERS IN INDONESIA

Abstract

Stunting is a condition of failure to thrive in children under five years old due to chronic malnutrition. Efforts that can be made to reduce the incidence of stunting in Indonesia are to identify factors that are thought to affect the incidence of stunting in Indonesia. The analysis methods used in this study are the global Fixed Effect Model (FEM) and the local Geographically Weighted Panel Regression (GWPR) model. FEM is a global regression model that assumes that each individual's model has a different intercept value. While GWPR is a local regression model from FEM that considers aspects of geographic location, by repeating data at each observation location, different times, and using spatial data. The weighting function used in this study is fixed bisquare and adaptive bisquare. This study aims to obtain a GWPR model on the percentage of stunting toddlers in Indonesia in 2019 until 2022 with independent variables, namely the percentage of children receiving exclusive breastfeeding, the percentage of households that have access to proper sanitation, the average per capita health expenditure of the population for a month, the average length of schooling for women, and the number of poor people. The variables are obtained from Statistics Indonesia (BPS) and Study of Indonesia’s Nutritional Status (SSGI). The results showed that the best weighting function, namely adaptive bisquare with a CV value of 264.80.