The M-Estimator and S-Estimator in Robust Improved Geographically and Temporally Weighted Regression for Modelling GRDP in West Java, Indonesia - Tiya Wulandari; Anang Kurnia; Muhammad Nur Aidi (International Journal of Scientific Research in Science, Engineering and Technology, 2024)
The success of development in a region in Indonesia can be measured by economic growth, especially in the financial sector using the Gross Regional Domestic Product (GRDP) growth rate. The GRDP figure at the Regency and City level in West Java is one of Indonesia's highest and most diverse. This is due to various factors, including the geographical location of West Java, which is directly adjacent to DKI Jakarta, which is the center of the national economy. Although classified as high, the diversity of GRDP values between regions in West Java needs attention to equalize economic growth. The diversity of GRDP values can be modeled by the Improved Geographically and Temporally Weighted Regression (I-GTWR) method by taking samples in 2018-2022. The I-GTWR modeling method considers the influence of spatial heterogeneity and spatial-temporal interaction, which has been proven to produce better results than the GTWR method in modeling GRDP in Central Java in 2011-2015. This study also adds M-estimators and S-estimators to improve the model's performance and make it robust to outliers. The explanatory variables we use are Regional Original Revenue, General Allocation Fund, Foreign Investment, Regional Minimum Wage, Domestic Investment, Poverty, Per-Capita Expenditure, and Number of Job Vacancies. The analysis shows that the Robust I-GTWR model, especially the M-estimator, produces better model performance than the I-GTWR model in modeling West Java GRDP. The coefficient of determination made by the Robust I-GTWR method using the M-estimator is 94.62% with a mean absolute deviation value of 0.1491 and an Akaike Information Criterion value of 110.4899.
Keywords: Spatial Heterogeneity; GTWR; Improved GTWR; Outlier; GDRB