Implementation of Multivariate Small Area Estimation on Socio-Economic Indicators - Firdaus, Firdaus; Nugroho, Sigit; Ayu Lestari, Wina; Pandu Winata, Aji (Enthusiastic : International Journal of Applied Statistics and Data Science, 2026)
The welfare of a region’s population is generally measured through socio-economic indicators such as per capita expenditure, access to education, and access to safe drinking water. This study aimed to estimate socio-economic indicators in Bengkulu Province at the small-area level using the multivariate small area estimation (SAE) approach under the empirical best linear unbiased prediction (EBLUP) framework. The analysis was based on secondary data obtained from BPS-Statistics Indonesia, covering the 2024 observation period, with indicators aggregated at the district level. Area-level auxiliary variables derived from the Village Potential Statistics (Potensi Desa, PODES) were incorporated to improve estimation accuracy by borrowing strength across correlated indicators and areas. Results showed that indirect estimation substantially improved the precision of direct estimates. The mean squared error (MSE) for the school participation rate decreased from 0.260 to 0.040, while the MSE for access to safe drinking water decreased from 0.00550 to 0.00098, indicating efficiency gains of approximately 85% for both indicators. Overall, the multivariate EBLUP approach yielded more stable and reliable estimates than direct estimation. Therefore, this approach is recommended for generating small area estimates of correlated welfare indicators when sample sizes are limited, thereby providing more accurate information for regional planning and policy formulation.