Application of Empirical Best Linear Unbiased Prediction (EBLUP) in Estimating Labor Force Participation Rate at the Regency/City Level in Kalimantan Island, 2016

Izumi Citra Amelia (Politeknik Statistika STIS, Indonesia)
Riski Tommi Mardoni (Politeknik Statistika STIS, Indonesia)
Syofmarlianisyah Putri (Politeknik Statistika STIS, Indonesia)
Debby Cynthia Ningrum (Politeknik Statistika STIS, Indonesia)
Iftina Ika Rahmawati (Politeknik Statistika STIS, Indonesia)
Cucu Sumarni (Politeknik Statistika STIS)

Jurnal Statistika Universitas Muhammadiyah Semarang
Vol 13, No 2 (2025): Jurnal Statistika Universitas Muhammadiyah Semarang

The Labor Force Participation Rate (LFPR) serves as a vital indicator for labor market planning, particularly in Kalimantan, a region experiencing sustained economic growth. In 2016, however, regency- and city-level LFPR data were unavailable due to a reduced sample size in the National Labor Force Survey. This study employs Small Area Estimation (SAE) using the Empirical Best Linear Unbiased Prediction (EBLUP) method to estimate LFPR at the sub-provincial level. Auxiliary variables include the number of vocational high schools (SMK), the proportion of villages receiving foreign aid, the share of trade-related enterprises, and the number of villages with migrant workers. Findings indicate that SAE-EBLUP produces estimates with lower relative standard errors (RSE) than direct estimation, offering improved precision for small-area LFPR estimates.