One of the issues that statistical organizations face in disseminating micro data is confidentiality, which has made the data not easily available to the public.One way to solve this problem is Synthetic simulation. In this article we proposed a simulated method, which is called synthetic, generates data with high similarity to the original population while maintaining confidentiality. Thus, estimated parameters are more accurate. The labor force survey (LFS) is one of the important surveys of statistical center of Iran, which provides valuable information about Iran’s LFS situation, specially unemployment rate.In this article, an attempt is made to investigate the application of the synthetic method for simulation target population, using results of the Iran’s LFS, summer 2018, for whole 31 country provinces. Moreover, due to compare the accuracy of Horowitz-Thompson estimates from the simulated population and real population, we have used the asymptotic relative efficiency estimate, which shows that estimation from the synthetic population is more efficient than the estimation obtained from sample of original population. This paper also shows that the proposed method can be used to estimate the parameters of small areas and where the sample size is not sufficient

Author Name: Ashkan Shabbak, Hamed Lorvand, Ali Rahimi

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Keywords: Population Simulation Synthetic Method Unemployment Rate Estimated Asymptotic Relative Efficiency Small Area Estimation

ISSN: 2008-3742

EISSN: 2008-3742

EOI/DOI: 10.22034/jpai.2020.243911

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