SMALL AREA ESTIMATION OF MEAN YEARS SCHOOL IN BOGOR DISTRICT USING SEMIPARAMETRIC P-SPLINE

Abstract

The Fay-Herriot model generally uses the EBLUP (Empirical Best Linear Unbiased Prediction) method, which is less flexible due to the assumption of linearity. The P-Spline semiparametric model is a modification of the Fay-Herriot model which can accommodate the presence of two components, linear and nonlinear predictors. This paper also deals with spatial dependence among the random area effects so that a model with spatially autocorrelated errors will be implemented, known as the SEBLUP (Spatial Empirical Best Linear Unbiased Prediction) method. Using data from SUSENAS, PODES, and some publications from BPS, the main objective of this study is to estimate the mean years school at the sub-district level in Bogor district using the EBLUP, Semiparametric P-Spline approach, and the SEBLUP method. The results show that based on the RRMSE value, the cubic P-Spline model with three knots predicts the mean years school better than EBLUP. Meanwhile, the addition of spatial effects into the small area estimation has not been able to improve the estimated value of the P-Spline semiparametric approach.