Clustering of Countries in the World Based on the Legatum Prosperity Index and Determining Iran's Position

Document Type : Research Paper

Authors

1 PhD student in health economic, Department of Economics, Khomeinishahr Branch, Islamic Azad University, Isfahan, Iran,

2 Assistant Professor, Department of Economics, Khomeinishahr Branch, Islamic Azad University, Isfahan, Iran,

3 Assistant Professor, Department of Mathematics & Statistics, Khomeinishahr Branch, Islamic Azad University, Isfahan, Iran,

Abstract

The main objective of the present research is to analyze the level of well-being of countries worldwide based on 12 components of the Legatum Prosperity Index and to determine Iran's position through clustering methods. In this research, using the K-Means algorithm in SPSS software, the clustering of countries worldwide based on 12 components of the Legatum Prosperity Index from 2007 to 2023 (for 167 countries) has been conducted to identify hidden patterns among countries and Iran's position within these clusters.
The research results indicate that, based on classifying countries into three clusters, Iran falls into a cluster with a medium level of welfare. Additionally, these results suggest that Iran is most similar to the countries of South Africa, Algeria, and Turkmenistan. The most essential variables in differentiating countries include "infrastructure and market access, education, and living conditions," the least important variables are assessed as "social capital and the natural environment."
Based on the research findings, it is necessary to consider the multidimensional aspects of welfare to increase the level of welfare in Iran. Therefore, economic policymakers should make greater efforts in open economy and inclusive societies.

Keywords

References

  1. Abonyi, J., & Feil, B. (2007). Cluster analysis for data mining and system identification. Springer Science & Business Media.‏
  2. Akar, H. (2015). Farklılaşan refah ölçüm yöntemleri ve eğitim açısından Türkiye’nin değerlendirilmesi. Finans Politik ve Ekonomik Yorumlar, (606), 23-40.‏
  3. Akar, S. (2014). TÜRKİYE’DE DAHA İYİ YAŞAM ENDEKSİ: OECD ÜLKELERİ İLE KARŞILAŞTIRMA. Journal of Life Economics, 1(1), 1-12.‏
  4. Aristei, D., & Perugini, C. (2010). Preferences for redistribution and inequality in well-being across Europe. Journal of Policy Modeling, 32(2), 176-195.‏
  5. Bakhtiari, S., Ranjbar, H., & Ghorbani, S. (2013). Composite Index of Economic Well Being and its Measurement for Selected Developing Countries. Economic Growth and Development Research, 3(9), 58-41 (In Persian).
  6. Bangoria Bhoomi, M. (2014). Enhanced K-Means clustering algorithm to reduce time complexity for numeric values. International Journal of Computer Science and Information Technologies, 5(1), 876-879.‏
  7. Bhatia, M. P. S., & Khurana, D. (2013). Experimental study of Data clustering using k-Means and modified algorithms. International Journal of Data Mining & Knowledge Management Process, 3(3), 17.‏
  8. Budsaratragoon, P., & Jitmaneeroj, B. (2021). Reform priorities for prosperity of nations: The Legatum Index. Journal of Policy Modeling, 43(3), 657-672.‏
  9. Büyüksarıkulak, A. M., & Kahramanoğlu, A. (2019). The prosperity index and its relationship with economic growth: Case of turkey. Journal of Entrepreneurship, Business and Economics, 7(2), 1-30.‏
  10. Cifuentes, M. P., Doogan, N. J., Fernandez, S. A., & Seiber, E. E. (2016). Factors shaping Americans’ objective well-being: A systems science approach with network analysis. Journal of Policy Modeling, 38(6), 1018-1039.‏
  11. Brian, E., Landau, S., Leese, M., & Stahl, D. (2011). Cluster analysis (> wiley series in probability and statistics).‏
  12. Faizan, M., Zuhairi, M. F., Ismail, S., & Sultan, S. (2020). Applications of clustering techniques in data mining: a comparative study. International Journal of Advanced Computer Science and Applications, 11(12).‏
  13. Graafland, J. (2020). When does economic freedom promote well being? On the moderating role of long-term orientation. Social Indicators Research, 149(1), 127-153.‏
  14. Hancock, G. R., Mueller, R. O., & Stapleton, L. M. (2010). The reviewer's guide to quantitative methods in the social sciences. Routledge.‏
  15. Kaufman, L., & Rousseeuw, P. J. (2009). Finding groups in data: an introduction to cluster analysis. John Wiley & Sons.‏
  16. Kulesza, M., & Ucıeklak-Jez, P. (2012). Poland and Selected Countries in the Light of OECD’s Better Life Index. Prace Naukowe Akademi im. Jana Dáugosza w Czstochowie, Pragmata tes Oikonomia, z. VI, ss, 183-191.‏
  17. Levy-Carciente, S., Phélan, C. M., & Perdomo, J. (2020). Prosperity in Spain and Latin America: myths and facts. International Journal of Advance Study and Research Work, 3(7), 2581-5997.‏
  18. Mohammadi, H., & Mahmoudi, M. (2018). Investigating the Role of Variables Affecting the Legatum Prosperity Index Using Ordered Logit Regression approach. Journal of economics and regional development, 25(16), 1-20. doi: 10.22067/erd.v25i15.64435 (In Persian).
  19. Mooi, E., & Sarstedt, M. (2011). A concise guide to market research: The process, data, and methods using IBM SPSS statistics. Springer.
  20. People E. 2023 Prosperity Index.
  21. Pilehvar, M., & Negintaji, Z. (2024). The Dynamic Effects of Demographic and Economic Variables on the Welfare Level of Iranian Households in the Horizon of 1420. Quarterly Journal of Applied Theories of Economics, 11(1), 241-278. doi: 10.22034/ecoj.2024.57542.3215 (In Persian).
  22. R, F., & A, S. (2014). Cluster analysis: a Tool for Analyzing Data in Quantitative and Mixed Method Studies. Psychological Models and Methods, 4(15), 13-36 (In Persian).
  23. Sargolzaie, A., Lotfalipour, M. R., & Salehnia, N. (2022). Investigating the Impact of Natural Resource Rents and Good Governance on the Welfare of Developing Countries: The Welfare Curse Phenomenon and the Quantile Regression Approach. Quarterly Journal of Applied Theories of Economics, 9(2), 1-34. doi: 10.22034/ecoj.2022.46618.2904 (In Persian).
  24. Shahab, A., Karimi, M. S., & Delangizan, S. (2024). The Effect of Economic and Social Factors on Housing Poverty in Iran. Quarterly Journal of Applied Theories of Economics, 10(4), 103-140. doi: 10.22034/ecoj.2024.59220.3254 (In Persian).
  25. Stiglitz, J. E., Sen, A., & Fitoussi, J. P. (2009). The measurement of economic performance and social progress revisited (Vol. 33, pp. 1-63). France: Ofce.‏
  26. Taheri S, Hosseinzadeh M. (2019). Analysis of the Welfare Situation in Iran Based on Global Standard Indicators. Iranian official statistics review magazine. 30 (1): 281-237 (In Persian).
  27. Yılmaz, Ş. K., & Şener, S. (2022). Analysis of the countries according to the prosperity level with data mining. Alphanumeric Journal, 10(2), 85-104.‏
  28. Zhong, Y. (2010). The economic theory of developing countries' rise: Explaining the myth of rapid economic growth in china. University Press of America.‏

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