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

Sibel Şahin; Süleyman Alpaykut

doi:10.19113/sdufbed.56119

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

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

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Details

Primary Language

Turkish

Subjects

-

Journal Section

-

Authors

Sibel Şahin

Süleyman Alpaykut

Publication Date

February 9, 2018

Submission Date

April 28, 2017

Acceptance Date

-

Published in Issue

Year 2018 Volume: 22 Number: 1

DOI

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

IZ

https://izlik.org/JA36WP34KY

Cite

RIS / Bibtex

APA

Şahin, S., & Alpaykut, S. (2018). Comparison of Sampling Methods for Annual Industry and Service Statistics Survey by TURKSTAT. Süleyman Demirel Üniversitesi Fen Bilimleri Enstitüsü Dergisi, 22(1), 81-87. https://doi.org/10.19113/sdufbed.56119

AMA

1.Şahin S, Alpaykut S. Comparison of Sampling Methods for Annual Industry and Service Statistics Survey by TURKSTAT. J. Nat. Appl. Sci. 2018;22(1):81-87. doi:10.19113/sdufbed.56119

Chicago

Şahin, Sibel, and Süleyman Alpaykut. 2018. “Comparison of Sampling Methods for Annual Industry and Service Statistics Survey by TURKSTAT”. Süleyman Demirel Üniversitesi Fen Bilimleri Enstitüsü Dergisi 22 (1): 81-87. https://doi.org/10.19113/sdufbed.56119.

EndNote

Şahin S, Alpaykut S (April 1, 2018) Comparison of Sampling Methods for Annual Industry and Service Statistics Survey by TURKSTAT. Süleyman Demirel Üniversitesi Fen Bilimleri Enstitüsü Dergisi 22 1 81–87.

IEEE

[1]S. Şahin and S. Alpaykut, “Comparison of Sampling Methods for Annual Industry and Service Statistics Survey by TURKSTAT”, J. Nat. Appl. Sci., vol. 22, no. 1, pp. 81–87, Apr. 2018, doi: 10.19113/sdufbed.56119.

ISNAD

Şahin, Sibel - Alpaykut, Süleyman. “Comparison of Sampling Methods for Annual Industry and Service Statistics Survey by TURKSTAT”. Süleyman Demirel Üniversitesi Fen Bilimleri Enstitüsü Dergisi 22/1 (April 1, 2018): 81-87. https://doi.org/10.19113/sdufbed.56119.

JAMA

1.Şahin S, Alpaykut S. Comparison of Sampling Methods for Annual Industry and Service Statistics Survey by TURKSTAT. J. Nat. Appl. Sci. 2018;22:81–87.

MLA

Şahin, Sibel, and Süleyman Alpaykut. “Comparison of Sampling Methods for Annual Industry and Service Statistics Survey by TURKSTAT”. Süleyman Demirel Üniversitesi Fen Bilimleri Enstitüsü Dergisi, vol. 22, no. 1, Apr. 2018, pp. 81-87, doi:10.19113/sdufbed.56119.

Vancouver

1.Sibel Şahin, Süleyman Alpaykut. Comparison of Sampling Methods for Annual Industry and Service Statistics Survey by TURKSTAT. J. Nat. Appl. Sci. 2018 Apr. 1;22(1):81-7. doi:10.19113/sdufbed.56119

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SSRN Electronic Journal

https://doi.org/10.2139/ssrn.2027407