SPATIAL MODELING IN DATA PANELS WITH LEAST SQUARE DUMMY VARIABLE TO IDENTIFY FACTORS AFFECTING UNEMPLOYMENT IN INDONESIA

Abstract

Unemployment is a serious issue that must be addressed. Unemployment has a negative impact on the national economy, making economic growth unpredictable. In 2015, Indonesia was ranked third with the highest unemployment rate in ASEAN. It is estimated that the unemployment rate in each province of Indonesia is influenced by the surrounding provinces. Therefore, spatial modelling on panel data with Least Square Dummy Variable (LSDV) is needed to identify factors that influence unemployment in Indonesia. The data used is Open Unemployment Rate (OUR) data and influencing factors are population, average length of schooling, Gross Regional Domestic Product (GRDP) rate, and Human Development Index (HDI) in 34 provinces of Indonesia from 2015 to 2020. Spatial model on panel data with appropriate LSDV for OUR data are Spatial Autoregressive Model (SAR) and Spatial Error Model (SEM). The SAR model with fixed effects has an value of 90.289%, which is greater than the SEM model with fixed effects (82.708%) and LSDV model (87.864%). The root mean square error value for SAR model with fixed effects is 0.58951, less than SEM model with fixed effects (0.78669) and LSDV model (0.65903). The best model is the SAR model with fixed effects. Based on this model, the factors that influence OUR in Indonesia from 2015-2020 are obtained, namely the rate of GRDP and HDI.