Application of Spatial Empirical Best Linear Unbiased Prediction (SEBLUP) of Open Unemployment Rate on Sub-District Level Estimation in Banten Province

Abstract

The open unemployement rate is an indicator for measuring unemployment. Banten Province recorded as the highest on open unemployment rate number in Indonesia on 2018. A high open unemployment rates indicate serious problems in society. This problem must be resolved synergistically from the national level to the level of small areas such as sub-districts. However, data for the small area level has not been fulfilled due to the insufficient number of samples. We apply spatial EBLUP to estimate the open unemployment rates in the districs of Banten. Such a method of small area estimation is essential because some districts have small labor forces and direct estimation for them is not reliable. SEBLUP takes advantage of the correlation of the neighboring districts. Data that used for direct estimation is from National Labor Survey (Sakernas) and Village Potential (Podes) 2018. This research showed that SEBLUP model can increased the precision from direct estimation method or EBLUP. There are two districts that have highest category of open unemployment rate which are Curugbitung, and Koroncong