Perbandingan Regresi Robust dengan M, S, dan MM-Estimator untuk Menganalisis Faktor-Faktor yang Memengaruhi Indeks Pemberdayaan Gender di Nusa Tenggara Barat Tahun 2023

Abstrak

The government has targeted gender issues in the fifth sustainable development goal, one of which is to achieve gender empowerment. The indicator used to measure gender empowerment in Indonesia is the Gender Empowerment Measure (GEM). NTB has been the province with the lowest GEM in Indonesia for five consecutive years, from 2019 to 2023. In addition, in 2023, NTB experienced a decrease in GEM of 0.19 points from 2022. This research aims to analyze factors that influence GEM in NTB in 2023. However, outliers are often found in the data which makes estimates using OLS biased. Therefore, this research uses a robust regression analysis method to overcome outliers in the data by comparing parameter estimates between M, S, and MM-estimator. The analysis results show that the best estimation method is the S-estimator because it produces the highest  and the lowest residual standard error (RSE) between the M and MM-estimator. All predictor variables have a positive and significant effect on GEM, namely women's involvement in parliament , women as professionals , and women's income contribution . The S-estimator produces a  of 0,999, which means that all predictor variables used can explain a proportion of GEM diversity of 99,9%, while the remainder can be explained by other variables that are not included in the model.