Implementasi Small Area Estimation Hierarchical Bayes - Beta Difference Benchmark dalam Estimasi NEET Lulusan Perguruan Tinggi - Salis, Dian Rahmawati; Japany, Adham Malay; Rodliyah, Ratih; Ibad, Syaikhul; Pulungan, Ridson Al farizal; Ramadhan, Yogi (Seminar Nasional Official Statistics, 2024)
The survey data generated by BPS serves as the primary data source for calculating various SDGs indicators. However, not all indicators can be reliably estimated, particularly at detailed disaggregation levels. Some indicators face issues due to sample inadequacy, resulting in high Relative Standard Errors (RSEs) if estimated directly. One such indicator is the percentage of young college graduates who are neither in education, employment, nor training (NEET). This indicator is only available at the provincial level, with disaggregation based on other characteristics only available at national level. Therefore, this study aims to estimate NEET among college graduates at the regency/city level in Sumatra Island for the year 2023 using the SAE HB Beta model. To maintain consistency with direct estimates at the provincial level, which have shown sufficiently low RSEs, a benchmarking process will be conducted using the difference benchmark method. Based on the findings, the difference benchmark method enhances the validity of the estimation results using the SAE HB Beta model.