Abstract
In general, surveys are designed for large areas with sufficient sample size. If the survey is used for small areas in which the sample sizes are not sufficient, the results of estimates may not be reliable due to the large standard error. Therefore, a Small Area Estimation (SAE) method was developed, to increase the effectiveness of the sample size by borrowing the strength of the neighboring region and information from the auxiliary variables that have a strong relationship with the observational variable. This study aims to analyze the SAE using Multivariate Fay-Herriot (MFH) model and Univariate Fay-Herriot (UFH) model for a variety of sample sizes. Simulations were conducted by using household expenditure per capita of food group and non-food group data from Susenas on March 2017. The simulation results showed that the average Root Mean Square Errors (RMSEs) using the MFH models in various sample size are smaller than the UFH model and the direct estimation.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: IOP Conference Series: Earth and Environmental Science
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
