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Clustering Nuts Level 2 Regions By K-Means Method According To Household Consumption Expenditures

Year 2022, Volume 14, Issue 4, 375 - 386, 29.12.2022
https://doi.org/10.52791/aksarayiibd.1105051

Abstract

This paper attempts to determine similar regions in Turkey according to consumption expenditures. For this reason, the data used in the analysis was gathered from Turkish Statistical Instıtute, Household Consumption Expenditures research. In the data, there were 12 variables: food and non-alcoholic beverages, alcoholic beverages, cigarettes, clothing and foot wear, housing and rent, furniture, house appliances, health, transportation, communication, entertainment and culture, educational services, restaurants, food services and hotels, various goods and services. Moreover, NUTS Level 2 regions was analyzed. K-was used to determine similar regions, and Silhouette Index was used to determine the number of clusters. As a result of the analysis, it was determined that there are 3 clusters and there were 4, 4 and 18 regions in the clusters.

References

  • Aslam, A. L. (2017). Does consumption expenditure induce the ecomonic growth? An empirical evidence from Sri Lanka. World Scientific News, 81(2), 221-234.
  • Attanasio, O., E. Hurst, and L. Pistaferri.(2015). the evolution of income, consumption, and leisure inequality in the us, 1980–2010.C.D. Carroll, T.F. Crossley, and J. Sabelhaus (Eds). In Improving the Measurement of Consumer Expenditures (100–140). University of Chicago Press
  • Beer, C. and Wagner, K. (2017). Household's housing expenditure in Austria, Germany and Italy. Monetary Policy and the Economy (Q4/17). https://www.oenb.at/en/Publications/Economics/Monetary-Policy-and-the-Economy.html
  • Berry, Francien, Brian Graf, Michael Stanger, and Mari Ylä-Jarkko (2019). Price Statistics Compilation in 196 Economies: The Relevance for Policy Analysis.” International Monetary Fund Working Paper 19/163
  • Charlier, E., Melenberg, B., & van Soest, A. (2001).” An Analysis of Housing Expenditure Using Semiparametric Models and Panel Data”, Journal of Econometrics, 101, 71–107.
  • Charrad, M., Ghazzali, N., Boiteau, V., Niknafs, A., & Charrad, M. M. (2014). “Package ‘nbclust’”, Journal of Statistical Software”, 61, 1-36.
  • Çağlayan, E. ve Astar, M. (2012). A Microeconometric Analysis of Household Consumption Expenditure Determinants for Both Rural and Urban Areas in Turkey. American International Journal of Contemporary Research, 2(2), 27-34.
  • Dhanachandra, N., Manglem, K., & Chanu, Y. J. (2015). “Image Segmentation Using K -means Clustering Algorithm and Subtractive Clustering Algorithm”, Procedia Computer Science, 54, 764–771.
  • Eurostat (.2020). Household Budget Survey. (11.08.2020). https://ec.europa.eu/eurostat/web/microdata/household-budget-survey.
  • Ghosh, S., & Dubey, S.K. (2013). “Comparative Analysis of K-Means and Fuzzy C Means Algorithms”, International Journal of Advanced Computer Science and Applications, 4 (4), 35-39.
  • Huy, V.Q.(2012). “Determinants of Educational Expenditure in Vietnam”, International Journal of Applied Economics, 9(1), 59-72.
  • Hronova, S., Hindls, R. (2013), Czech households in the years of crises. Statistics and Economic Journal, 93(4), 4-23.
  • Jain, A. K. (2010).” Data clustering: 50 years beyond K-means”, Pattern Recognition Letters, 31(8), 651-666.
  • Kassambara, A., & Mundt, F. (2017). “Package ‘factoextra’”, Extract and Visualize the Results of Multivariate Data Analyses, 76.
  • Kotu, V., & Deshpande, B. (2018). Data Science: Concepts and Practice. Morgan Kaufmann.
  • Likas, A., Vlassis, N., & Verbeek, J. J. (2003).” The Global K-Means Clustering Algorithm”, Pattern recognition, 36(2), 451-461.
  • Madhulatha, T. S. (2012). An overview on clustering methods. arXiv preprint arXiv:1205.1117.
  • McLean, I. W. (1999). Consumer Prices and Expenditure Patterns in Australia 1850-1914. Australian Economic History Review, 39(1), 1–28.
  • Meyer, B. D., & Sullivan, J. X. (2011). Viewpoint: Further results on measuring the well-being of the poor using income and consumption. Canadian Journal of Economics/Revue Canadienne D’économique, 44(1), 52–87.
  • Mont, O., & Power, K. (2010). “The Role of Formal and Informal Forces in Shaping Consumption and Implications for a Sustainable Society. Part I”, Sustainability, 2(7), 2232–2252.
  • Noll, H.-H., & Weick, S. (2014). Consumption expenditures and subjective well-being: empirical evidence from Germany. International Review of Economics, 62(2), 101–119.
  • Obinna, o. (2020). Effect of Inflation on Household Final Consumption Expenditure in Nigeria. Journal of Economics and Development Studies, 8(1), 104-111
  • OECD, (2013). OECD Framework for Statistics on the Distribution of Household Income, Consumption and Wealth. Paris: OECD.
  • Schultze, C. L. (2003). The Consumer Price Index: Conceptual Issues and Practical Suggestions. Journal of Economic Perspectives, 17(1), 3–22.
  • Tapsin, G. ve Hepsag, A. (2014). An Analysis of Household Consumption Expenditures in EA-18. European Scientific Journal , 10(16), 1-12. Tokatlıoğlu, İ. ve Tokatlıoğlu,Y. (2013). “Türkiye’de 2002-2011 Yılları Arasında Katastrofik Sağlık Harcamalarının Yoksulluk Yaratma Kapasitesi”, Ekonomik Yaklaşım, 24(87), 1-36.
  • TÜİK (2019). Hanehalkı Tüketim Harcaması. (10.08.2020). http://www.tuik.gov.tr/PreHaberBultenleri.do?id=30584.
  • TÜİK (2020). Hanehalkı Tüketim Harcaması. https://data.tuik.gov.tr/Bulten/Index?p=Hanehalki-Tuketim-Harcamasi-(Bolgesel)-2019-33594
  • Uğurlar, A. ve Eceral, T.Ö.(2014). “Ankara’da Mevcut Konut (Mülk ve Kiralık) Piyasasına İlişkin bir Değerlendirme”, İdealkent, (12), 132-159.
  • Zalik, K.R. (2008). “An Efficient k’ -means Clustering Algorithm”, Pattern Recognition Letters, 29(9), 1385–1391.
  • Zeynalova Z., Mammadli M., (2020). Analysis of the Economic Factors Affectıng Household Consumption Expenditures in Azerbaijan. Journal of Critical Reviews, 7(7), 241-248.

Hanehalkı Tüketim Harcamalarına Göre İibs Düzey 2 Bölgelerin Kümelenmesi

Year 2022, Volume 14, Issue 4, 375 - 386, 29.12.2022
https://doi.org/10.52791/aksarayiibd.1105051

Abstract

Mevcut çalışmada, Türkiye’de, tüketim harcamalarına göre benzer bölgelerin belirlenmesi amaçlanmıştır. Bu bağlamda, Türkiye İstatistik Kurumu’nun (TÜİK) yayınlamış olduğu Hanehalkı Tüketim Harcamasının verileri kullanılmıştır. İlgili veride gıda ve alkolsüz içecekler, alkollü içecekler, sigara ve tütün, giyim ve ayakkabı, konut ve kira, mobilya, ev aletleri ve bakım hizmetleri, sağlık, ulaştırma, haberleşme, eğlence ve kültür, eğitim hizmetleri, lokanta ve oteller, çeşitli mal ve hizmetler olmak üzere toplamda 12 harcama mevcuttur. Ayrıca veride, TÜİK’in belirlediği Türkiye İstatistiki Bölge Birimleri Sınıflandırması Düzey 2 bölgeleri yer almaktadır. Benzer bölgelerin belirlenmesi için kümeleme yöntemlerinden k-ortalamalar, küme sayısının belirlenmesi için ise Silhouette İndeksinden yararlanılmıştır. Analiz sonucunda 3 küme olduğu tespit edilmiş ve sırasıyla kümelerde 4, 4 ve 18 bölge yer almıştır.

References

  • Aslam, A. L. (2017). Does consumption expenditure induce the ecomonic growth? An empirical evidence from Sri Lanka. World Scientific News, 81(2), 221-234.
  • Attanasio, O., E. Hurst, and L. Pistaferri.(2015). the evolution of income, consumption, and leisure inequality in the us, 1980–2010.C.D. Carroll, T.F. Crossley, and J. Sabelhaus (Eds). In Improving the Measurement of Consumer Expenditures (100–140). University of Chicago Press
  • Beer, C. and Wagner, K. (2017). Household's housing expenditure in Austria, Germany and Italy. Monetary Policy and the Economy (Q4/17). https://www.oenb.at/en/Publications/Economics/Monetary-Policy-and-the-Economy.html
  • Berry, Francien, Brian Graf, Michael Stanger, and Mari Ylä-Jarkko (2019). Price Statistics Compilation in 196 Economies: The Relevance for Policy Analysis.” International Monetary Fund Working Paper 19/163
  • Charlier, E., Melenberg, B., & van Soest, A. (2001).” An Analysis of Housing Expenditure Using Semiparametric Models and Panel Data”, Journal of Econometrics, 101, 71–107.
  • Charrad, M., Ghazzali, N., Boiteau, V., Niknafs, A., & Charrad, M. M. (2014). “Package ‘nbclust’”, Journal of Statistical Software”, 61, 1-36.
  • Çağlayan, E. ve Astar, M. (2012). A Microeconometric Analysis of Household Consumption Expenditure Determinants for Both Rural and Urban Areas in Turkey. American International Journal of Contemporary Research, 2(2), 27-34.
  • Dhanachandra, N., Manglem, K., & Chanu, Y. J. (2015). “Image Segmentation Using K -means Clustering Algorithm and Subtractive Clustering Algorithm”, Procedia Computer Science, 54, 764–771.
  • Eurostat (.2020). Household Budget Survey. (11.08.2020). https://ec.europa.eu/eurostat/web/microdata/household-budget-survey.
  • Ghosh, S., & Dubey, S.K. (2013). “Comparative Analysis of K-Means and Fuzzy C Means Algorithms”, International Journal of Advanced Computer Science and Applications, 4 (4), 35-39.
  • Huy, V.Q.(2012). “Determinants of Educational Expenditure in Vietnam”, International Journal of Applied Economics, 9(1), 59-72.
  • Hronova, S., Hindls, R. (2013), Czech households in the years of crises. Statistics and Economic Journal, 93(4), 4-23.
  • Jain, A. K. (2010).” Data clustering: 50 years beyond K-means”, Pattern Recognition Letters, 31(8), 651-666.
  • Kassambara, A., & Mundt, F. (2017). “Package ‘factoextra’”, Extract and Visualize the Results of Multivariate Data Analyses, 76.
  • Kotu, V., & Deshpande, B. (2018). Data Science: Concepts and Practice. Morgan Kaufmann.
  • Likas, A., Vlassis, N., & Verbeek, J. J. (2003).” The Global K-Means Clustering Algorithm”, Pattern recognition, 36(2), 451-461.
  • Madhulatha, T. S. (2012). An overview on clustering methods. arXiv preprint arXiv:1205.1117.
  • McLean, I. W. (1999). Consumer Prices and Expenditure Patterns in Australia 1850-1914. Australian Economic History Review, 39(1), 1–28.
  • Meyer, B. D., & Sullivan, J. X. (2011). Viewpoint: Further results on measuring the well-being of the poor using income and consumption. Canadian Journal of Economics/Revue Canadienne D’économique, 44(1), 52–87.
  • Mont, O., & Power, K. (2010). “The Role of Formal and Informal Forces in Shaping Consumption and Implications for a Sustainable Society. Part I”, Sustainability, 2(7), 2232–2252.
  • Noll, H.-H., & Weick, S. (2014). Consumption expenditures and subjective well-being: empirical evidence from Germany. International Review of Economics, 62(2), 101–119.
  • Obinna, o. (2020). Effect of Inflation on Household Final Consumption Expenditure in Nigeria. Journal of Economics and Development Studies, 8(1), 104-111
  • OECD, (2013). OECD Framework for Statistics on the Distribution of Household Income, Consumption and Wealth. Paris: OECD.
  • Schultze, C. L. (2003). The Consumer Price Index: Conceptual Issues and Practical Suggestions. Journal of Economic Perspectives, 17(1), 3–22.
  • Tapsin, G. ve Hepsag, A. (2014). An Analysis of Household Consumption Expenditures in EA-18. European Scientific Journal , 10(16), 1-12. Tokatlıoğlu, İ. ve Tokatlıoğlu,Y. (2013). “Türkiye’de 2002-2011 Yılları Arasında Katastrofik Sağlık Harcamalarının Yoksulluk Yaratma Kapasitesi”, Ekonomik Yaklaşım, 24(87), 1-36.
  • TÜİK (2019). Hanehalkı Tüketim Harcaması. (10.08.2020). http://www.tuik.gov.tr/PreHaberBultenleri.do?id=30584.
  • TÜİK (2020). Hanehalkı Tüketim Harcaması. https://data.tuik.gov.tr/Bulten/Index?p=Hanehalki-Tuketim-Harcamasi-(Bolgesel)-2019-33594
  • Uğurlar, A. ve Eceral, T.Ö.(2014). “Ankara’da Mevcut Konut (Mülk ve Kiralık) Piyasasına İlişkin bir Değerlendirme”, İdealkent, (12), 132-159.
  • Zalik, K.R. (2008). “An Efficient k’ -means Clustering Algorithm”, Pattern Recognition Letters, 29(9), 1385–1391.
  • Zeynalova Z., Mammadli M., (2020). Analysis of the Economic Factors Affectıng Household Consumption Expenditures in Azerbaijan. Journal of Critical Reviews, 7(7), 241-248.

Details

Primary Language Turkish
Subjects Social
Journal Section Research Article
Authors

Neslihan AKIN ÖZDEMİR> (Primary Author)
Zonguldak Bülent Ecevit Üniversitesi
0000-0002-6577-2525
Türkiye


Cem GÜRLER>
YALOVA ÜNİVERSİTESİ, YALOVA İKTİSADİ VE İDARİ BİLİMLER FAKÜLTESİ
0000-0001-5127-6726
Türkiye

Publication Date December 29, 2022
Published in Issue Year 2022, Volume 14, Issue 4

Cite

Bibtex @research article { aksarayiibd1105051, journal = {Aksaray Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi}, eissn = {2687-3427}, address = {Aksaray Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergi Editörlüğü Kampus 68100 AKSARAY}, publisher = {Aksaray University}, year = {2022}, volume = {14}, number = {4}, pages = {375 - 386}, doi = {10.52791/aksarayiibd.1105051}, title = {Hanehalkı Tüketim Harcamalarına Göre İibs Düzey 2 Bölgelerin Kümelenmesi}, key = {cite}, author = {Akın Özdemir, Neslihan and Gürler, Cem} }
APA Akın Özdemir, N. & Gürler, C. (2022). Hanehalkı Tüketim Harcamalarına Göre İibs Düzey 2 Bölgelerin Kümelenmesi . Aksaray Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi , 14 (4) , 375-386 . DOI: 10.52791/aksarayiibd.1105051
MLA Akın Özdemir, N. , Gürler, C. "Hanehalkı Tüketim Harcamalarına Göre İibs Düzey 2 Bölgelerin Kümelenmesi" . Aksaray Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi 14 (2022 ): 375-386 <http://aksarayiibd.aksaray.edu.tr/en/pub/issue/74487/1105051>
Chicago Akın Özdemir, N. , Gürler, C. "Hanehalkı Tüketim Harcamalarına Göre İibs Düzey 2 Bölgelerin Kümelenmesi". Aksaray Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi 14 (2022 ): 375-386
RIS TY - JOUR T1 - Clustering Nuts Level 2 Regions By K-Means Method According To Household Consumption Expenditures AU - NeslihanAkın Özdemir, CemGürler Y1 - 2022 PY - 2022 N1 - doi: 10.52791/aksarayiibd.1105051 DO - 10.52791/aksarayiibd.1105051 T2 - Aksaray Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi JF - Journal JO - JOR SP - 375 EP - 386 VL - 14 IS - 4 SN - -2687-3427 M3 - doi: 10.52791/aksarayiibd.1105051 UR - https://doi.org/10.52791/aksarayiibd.1105051 Y2 - 2022 ER -
EndNote %0 Journal of Aksaray University Faculty of Economics and Administrative Sciences Hanehalkı Tüketim Harcamalarına Göre İibs Düzey 2 Bölgelerin Kümelenmesi %A Neslihan Akın Özdemir , Cem Gürler %T Hanehalkı Tüketim Harcamalarına Göre İibs Düzey 2 Bölgelerin Kümelenmesi %D 2022 %J Aksaray Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi %P -2687-3427 %V 14 %N 4 %R doi: 10.52791/aksarayiibd.1105051 %U 10.52791/aksarayiibd.1105051
ISNAD Akın Özdemir, Neslihan , Gürler, Cem . "Hanehalkı Tüketim Harcamalarına Göre İibs Düzey 2 Bölgelerin Kümelenmesi". Aksaray Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi 14 / 4 (December 2022): 375-386 . https://doi.org/10.52791/aksarayiibd.1105051
AMA Akın Özdemir N. , Gürler C. Hanehalkı Tüketim Harcamalarına Göre İibs Düzey 2 Bölgelerin Kümelenmesi. Journal of ASU FEAS. 2022; 14(4): 375-386.
Vancouver Akın Özdemir N. , Gürler C. Hanehalkı Tüketim Harcamalarına Göre İibs Düzey 2 Bölgelerin Kümelenmesi. Aksaray Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi. 2022; 14(4): 375-386.
IEEE N. Akın Özdemir and C. Gürler , "Hanehalkı Tüketim Harcamalarına Göre İibs Düzey 2 Bölgelerin Kümelenmesi", Aksaray Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, vol. 14, no. 4, pp. 375-386, Dec. 2022, doi:10.52791/aksarayiibd.1105051