Estimating Poverty Indicator with Small Area Estimation in Simulation Study of Different Population and Sample Size

Authors(3) :-Fera Kuraysia, Kusman Sadik, Anang Kurnia

The estimation of poverty indicators of the sub-district or village level can be calculated by small area estimation using direct estimation, empirical Bayes and fast empirical Bayes method. These three methods are evaluated through a simulation study. The usual simulation uses the same population size and sample for each area. This study compares three SAE methods with four population size scenarios with different samples for each area. Based on Bias and MSE values, direct predictions are well used in small populations. The EB method is capable of generating estimation with small bias and MSEs for all scenarios but take longer computation time. While the FEB method produces estimations with bias and MSE are small in large population conditions with faster computational time

Authors and Affiliations

Fera Kuraysia
Department of Statistics, Bogor Agricultural University, Bogor, Indonesia
Kusman Sadik
Department of Statistics, Bogor Agricultural University, Bogor, Indonesia
Anang Kurnia
Department of Statistics, Bogor Agricultural University, Bogor, Indonesia

direct estimation, empirical Bayes, fast empirical Bayes, poverty indicator, small area estimation

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Publication Details

Published in : Volume 4 | Issue 9 | July-August 2018
Date of Publication : 2018-07-30
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 208-212
Manuscript Number : IJSRSET184948
Publisher : Technoscience Academy

Print ISSN : 2395-1990, Online ISSN : 2394-4099

Cite This Article :

Fera Kuraysia, Kusman Sadik, Anang Kurnia, " Estimating Poverty Indicator with Small Area Estimation in Simulation Study of Different Population and Sample Size , International Journal of Scientific Research in Science, Engineering and Technology(IJSRSET), Print ISSN : 2395-1990, Online ISSN : 2394-4099, Volume 4, Issue 9, pp.208-212, July-August-2018.
Journal URL : http://ijsrset.com/IJSRSET184948

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