Comparison of Sampling Methods for Annual Industry and Service Statistics Survey by TURKSTAT

Year 2018, Volume: 22 Issue: 1, 81 - 87, 09.02.2018

Sibel Şahin Süleyman Alpaykut

https://doi.org/10.19113/sdufbed.56119

Cited By: 1

Abstract

The Annual Industry and Service Statistics is one of the largest surveys, conducted by Turkish Statistical Institute, which aims to determine changes in economic structure in Turkey. Both full enumeration and sampling methods are used in this survey. Nevertheless, the percentage of full enumeration increases every year. Even though efforts have been made in order to be used administrative records in recent years, this could not satisfy all of the necessary information needed. Hence, it is believed that there is a requirement to decrease the size of the survey. In this study, it is aimed to propose a sampling method for part of the Annual Industry and Service Statistics Survey conducted with the enumeration and to compare the suggested methods. For that purpose, in the first phase, stratified sampling is used and then the comparison is made by using three different sampling methods within the strata, namely poisson, systematic and simple random sampling. The size of the survey is reduced by using sampling methods, but the economic activity classification together with the level of estimation to the regions increase. It is concluded that the best estimations and minimum variances are obtained when poisson and simple random sampling methods are applied together.

Keywords

Stratified sampling, Poisson sampling; Random sampling; Systematic sampling; Annual statistics estimations

References

• [1] Brick, J.M. 2011. The future of survey sampling. Public Opinion Quarterly 75(5), 872-888.
• [2] Giovannini, E. 2008. Understanding economic statistics:an OECD perspective (p. 195). Bologna: Societa Editriceil Mulino.
• [3] Scheaffer, R.L., Mendenhall, W., Ott, L. 1990. Elementary survey sampling, 5th ed. (p. 501). Belmont: Duxbury Press.
• [4] Chambers, R. 2003. An introduction to model-based survey sampling (p. 90). Southampton: EUROSTAT.
• [5] Yamane, T. 2010. Temel örnekleme yöntemleri. (A. Esin, C. Aydın, M. A. Bakır, E. Gürbüzsel, Trans.) (p. 509). İstanbul: Literatür Yayıncılık.
• [6] Mathew, O.O., Sola, A.F., Oladiran, B.H. Amos, A.A. 2013. Efficiency of Neyman allocation procedure over other allocation procedures in stratified random sampling. American Journal of Theoretical and Applied Statistics, 2(5), 122-127.
• [7] Barnabas, A.F. Sunday, A.O. 2014. Comparison of allocation procedures in a stratified random sampling of skewed populations under different distributions and sample sizes. International Journal of Innovative Science, Engineering & Technology, 1(8) , 218-225.
• [8] Winkler, W.E. 2009. Sample allocation and stratification. Research report series of U.S. Census Bureau (Statistics #2009-8).
• [9] Cochran, W.G. 1977. Sampling Techniques (p. 596). New York: John Wiley&Sons.
• [10] Lohr, S. 2010. Sampling: design and analysis (2nd ed.) (p. 596). Boston: Brooks/ Cole.
• [11] Ha ́jek, J. 1958. Some contributions to the theory of probability sampling. Bulletin of the institute of international statistics. 36(3): 127-134.
• [12] Ha ́jek, J. 1964. Asymptotic theory of rejective sampling with varying probabilities from a finite population. Annals of Mathematical Statistics, 35, 1491-1523.
• [13] Williams, M.S., Schreuder, H.T., Terrazas, G.H. 1998. Poisson sampling: the adjusted and unadjusted estimator revisited. Research Note of United States Department of Agriculture (RMRS-RN-4).
• [14] Aires, N. 1999. Algorithms to find exact inclusion probabilities for conditional poisson sampling and pareto πps sampling designs. Methodology and Computing in Applied Probability, 1 (4),457-469.
• [15] Grafström, A. 2010. On unequal probability sampling designs, Umea ̇ University, Doctoral dissertation, p. 31, Umea ̇:
• [16] Ghosh, D., Vogt, A. 1999. A modification of poisson sampling. Proceedings of the American Statistical Association, Survey Research Methods Section, 198-199.
• [17] Saavedra,P.J. 2000. Estimation strategies using variants of poisson sampling discussion. Proceedings of the American Statistical Association International Conference of Establishment Surveys, Session 4, 300-301.
• [18] Williams, M.S., Ebel, E.D., Wells, S.J. 2009. Poisson sampling: A sampling strategy for concurrently establishing freedom from disease and estimating population characteristics. Preventive Veterinary Medicine, 89, 34-42.
• [19] Brewer, K.R.W., Early, L.J., Hanif, M. 1984. Poisson, modified poisson and collocated sampling. Journal of Statistical Planning and Inference,10, 15-30.
• [20] Lundquist, A. 2009. Contributions to the theory of unequal probability sampling. Umea ̇ University, Doctoral dissertation, p.28, Umea ̇ .
• [21] Sa ̈rndal, C.E., Swenson, B. Wretman, J. 1992. Model assisted survey sampling. (p.695), New York: Springer-Verlag.
• [22] Ardilly, P. Tillé, Y. 2006. Sampling methods: exercises and solutions (p. 382), New York: Springer.
• [23] TUİK. 2016. Annual Industry and Service Statistics (n.d.) In TURKSTAT Central Dissemination System-MEDAS. https://biruni.tuik.gov.tr/medas (Erişim Tarihi: 17.12.2016)