A comparative study of multivariate Fay-Herriot model for small area estimation in various sample sizes

5th International Seminar on Sciences

自然科学（总论）

Nurizza, W.A.^1 ; Ubaidillah, A.^1

Department of Statistics, STIS Polytechnic of Statistics, East Jakarta

13330, Indonesia^1

关键词: Auxiliary variables;    Comparative studies;    Household expenditure;    Root mean square errors;    Sample sizes;    Small area estimation;    Standard errors;    Univariate;   

Others  :  https://iopscience.iop.org/article/10.1088/1755-1315/299/1/012027/pdf
DOI  :  10.1088/1755-1315/299/1/012027

学科分类：自然科学（综合）

来源: IOP

【 摘 要 】

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.