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Economic Freedom Index Calculation Using FCM

Year 2018, Volume 6, Issue 1, 2018, 93 - 116, 26.06.2018
https://doi.org/10.17093/alphanumeric.337322

Abstract

The Index of Economic Freedom is an annual index and ranking created by The Heritage Foundation and The Wall Street Journal in 1995 to measure the degree of economic freedom in the world's nations. There are many kinds of Economic Freedom Indices depending on variables which many institute or company determine for their research. The aim is to predict countries or regions according to economic parameters. In this study, fuzzy clustering algorithm is proposed for economic freedom ındex calculation. By using degree of memberships founded by FCM, Economic Freedom index will be calculated for regions. Results compared with indices calculated by The Heritage Foundation for the year 2013, 2014, 2015 and 2016. It is showed that FCM is an alternative method for index calculating systems.

References

  • Ayal, E. B. and Karras, G., (1998), Components of Economic Freedom and Growth: An Empirical Study, The Journal of Developing Areas, Spring, 32, 327-338.
  • Balasko, B., Abonyi J. and Feil B., (2005), Fuzzy Clustering and Data Analysis Toolbox. Univ. Of Veszprem, Hungary.
  • Bengoa, M. and Robles, B. S., (2003), Foreign direct investment, economic freedom and growth: new evidence from Latin America, European Journal of Political Economy, volume 19, Issue 3, September, pages 529–545.
  • Berggren, N., (2003), The Benefits of Economic Freedom: A Survey, Independent Review, 8, no. 2, pp: 193–211.
  • Bezdek, J.C. (1974a), Cluster validity with fuzzy sets, J. Cybernetics 3, 58-73
  • Bezdek, J.C. (1974b), Numerical Taxonomy with Fuzzy Sets, J.Math Biol. 1, 57-71
  • Bezdek, J.C. (1981), Pattern Recognition with Fuzzy Objective Function Algorithms. NY Plenum Press. Carlsson F. and Lundström S., (2002), Economic Freedom and Growth: Decomposing the Effects, Public Choice, 112, pp. 335-344.
  • Dollar, D. (1992), Outward-oriented developing economies really do grow more rapidly: Evidence from 95 LDCs, 1976-1985, Economic Development and Cultural Change, 40: 523-544.
  • Erilli, N.A., Yolcu, U., Eğrioğlu, E., Aladağ, Ç.H. and Öner, Y. (2011), Determining the Most Proper Number of Cluster in Fuzzy Clustering by Artificial Neural Networks, Expert Systems with Applications, 38, pp. 2248-2252
  • Esposto A.G. and Zaleski P. A., (1999), Economic Freedom and the Quality of Life: An Empirical Analysis, Constitutional Political Economy, 10, 185–197.
  • Gwartney, J.G. and Lawson R.A., (2002), Economic Freedom of the World: 2002 Annual Report. Vancouver: Fraser Institute.
  • Gwartney, J.G., Lawson R.A. and Holcombe R.G., (1999), Economic Freedom and the Environment for Economic Growth, Journal of Institutional and Theoretical Economics, vol. 155, No. 4 , pp. 643-663.
  • Haan J. and Sturm J. E., (2000), On the relationship between economic freedom and economic growth, European Journal of Political Economy, Volume 16, Issue 2, June, Pages 215–241.
  • Halkidi, M., Batistakis, Y. and Vazirgiannis M. (2001), On Clustering Validation Techniques, Journal of Intelligent Systems, K.A. Publishes, Holland, pp. 107-145
  • Heckelman, J. C., (2000), Economic freedom and economic growth: A short-run causal investigation, Journal of Applied Economics, Vol. III, No. 1, May, 71-91.
  • Johnson, J. P. and Lenartowicz T., (1998), Culture, Freedom and Economic Growth: Do Cultural Values Explain Economic Growth?. Journal of World Business, 33(4), pp.332-356.
  • Kwon, S.H. (1998), Cluster Validity Index for Fuzzy Clustering, Elec. Lett, 34, 22, pp. 2176-2178.
  • Miller, T. and Kim, A. B., (2015a), Chapter 2: Why Economic Freedom Matters?, http://www.heritage.org/index/pdf/2015/book/chapter2.pdf.
  • Miller, T. and Kim, A. B., (2015b), Chapter 1: Principles of Economic Freedom, http://www.heritage.org/index/pdf/2015/book/chapter1.pdf
  • Naes T., and Mevik T.H., (1999), The Flexibility of Fuzzy Clustering Illustred By Examples, Journal Of Chemo Metrics.
  • Oliveira, J.V., and Pedrycz, W. (2007), Advances In Fuzzy Clustering And Its Applications, John Wiley &Sons Inc. Pub.,West Sussex, England
  • Rezaee, M.R., Lelieveldt, B.P.F. and Reiber, J.H.C. (1998). A New Cluster Validity Index for the FCM, Pattern Recognition Letters, 19, pp. 237-246
  • Sachs, J., and Warner, A. (1995), Economic reform and the process of global integration, Brookings Papers on Economic Activity, I: l-95.
  • Shen, C. and Williamson J. B., (2005), Corruption, Democracy, Economic Freedom, and State Strength A Cross-national Analysis, Int. Journal of comparative socıology, 46(4), p. 327-345.
  • Sintas, A.F., Cadenas, J.M. and Martin, F. (1999), Membership functions in the Fuzzy c-Means Algorithm, Fuzzy Sets and Systems, 101. Stroup, M. D., (2006), Economic Freedom, Democracy, and the Quality of Life, World Development Vol. 35, No. 1, pp. 52–66.
  • Xie, L. and Beni, G. (1991), A Validity Measure for Fuzzy Clustering, IEEE Transactions on Pattern Analysis and Machine Intelligence, 13(4), pp. 841-846
Year 2018, Volume 6, Issue 1, 2018, 93 - 116, 26.06.2018
https://doi.org/10.17093/alphanumeric.337322

Abstract

References

  • Ayal, E. B. and Karras, G., (1998), Components of Economic Freedom and Growth: An Empirical Study, The Journal of Developing Areas, Spring, 32, 327-338.
  • Balasko, B., Abonyi J. and Feil B., (2005), Fuzzy Clustering and Data Analysis Toolbox. Univ. Of Veszprem, Hungary.
  • Bengoa, M. and Robles, B. S., (2003), Foreign direct investment, economic freedom and growth: new evidence from Latin America, European Journal of Political Economy, volume 19, Issue 3, September, pages 529–545.
  • Berggren, N., (2003), The Benefits of Economic Freedom: A Survey, Independent Review, 8, no. 2, pp: 193–211.
  • Bezdek, J.C. (1974a), Cluster validity with fuzzy sets, J. Cybernetics 3, 58-73
  • Bezdek, J.C. (1974b), Numerical Taxonomy with Fuzzy Sets, J.Math Biol. 1, 57-71
  • Bezdek, J.C. (1981), Pattern Recognition with Fuzzy Objective Function Algorithms. NY Plenum Press. Carlsson F. and Lundström S., (2002), Economic Freedom and Growth: Decomposing the Effects, Public Choice, 112, pp. 335-344.
  • Dollar, D. (1992), Outward-oriented developing economies really do grow more rapidly: Evidence from 95 LDCs, 1976-1985, Economic Development and Cultural Change, 40: 523-544.
  • Erilli, N.A., Yolcu, U., Eğrioğlu, E., Aladağ, Ç.H. and Öner, Y. (2011), Determining the Most Proper Number of Cluster in Fuzzy Clustering by Artificial Neural Networks, Expert Systems with Applications, 38, pp. 2248-2252
  • Esposto A.G. and Zaleski P. A., (1999), Economic Freedom and the Quality of Life: An Empirical Analysis, Constitutional Political Economy, 10, 185–197.
  • Gwartney, J.G. and Lawson R.A., (2002), Economic Freedom of the World: 2002 Annual Report. Vancouver: Fraser Institute.
  • Gwartney, J.G., Lawson R.A. and Holcombe R.G., (1999), Economic Freedom and the Environment for Economic Growth, Journal of Institutional and Theoretical Economics, vol. 155, No. 4 , pp. 643-663.
  • Haan J. and Sturm J. E., (2000), On the relationship between economic freedom and economic growth, European Journal of Political Economy, Volume 16, Issue 2, June, Pages 215–241.
  • Halkidi, M., Batistakis, Y. and Vazirgiannis M. (2001), On Clustering Validation Techniques, Journal of Intelligent Systems, K.A. Publishes, Holland, pp. 107-145
  • Heckelman, J. C., (2000), Economic freedom and economic growth: A short-run causal investigation, Journal of Applied Economics, Vol. III, No. 1, May, 71-91.
  • Johnson, J. P. and Lenartowicz T., (1998), Culture, Freedom and Economic Growth: Do Cultural Values Explain Economic Growth?. Journal of World Business, 33(4), pp.332-356.
  • Kwon, S.H. (1998), Cluster Validity Index for Fuzzy Clustering, Elec. Lett, 34, 22, pp. 2176-2178.
  • Miller, T. and Kim, A. B., (2015a), Chapter 2: Why Economic Freedom Matters?, http://www.heritage.org/index/pdf/2015/book/chapter2.pdf.
  • Miller, T. and Kim, A. B., (2015b), Chapter 1: Principles of Economic Freedom, http://www.heritage.org/index/pdf/2015/book/chapter1.pdf
  • Naes T., and Mevik T.H., (1999), The Flexibility of Fuzzy Clustering Illustred By Examples, Journal Of Chemo Metrics.
  • Oliveira, J.V., and Pedrycz, W. (2007), Advances In Fuzzy Clustering And Its Applications, John Wiley &Sons Inc. Pub.,West Sussex, England
  • Rezaee, M.R., Lelieveldt, B.P.F. and Reiber, J.H.C. (1998). A New Cluster Validity Index for the FCM, Pattern Recognition Letters, 19, pp. 237-246
  • Sachs, J., and Warner, A. (1995), Economic reform and the process of global integration, Brookings Papers on Economic Activity, I: l-95.
  • Shen, C. and Williamson J. B., (2005), Corruption, Democracy, Economic Freedom, and State Strength A Cross-national Analysis, Int. Journal of comparative socıology, 46(4), p. 327-345.
  • Sintas, A.F., Cadenas, J.M. and Martin, F. (1999), Membership functions in the Fuzzy c-Means Algorithm, Fuzzy Sets and Systems, 101. Stroup, M. D., (2006), Economic Freedom, Democracy, and the Quality of Life, World Development Vol. 35, No. 1, pp. 52–66.
  • Xie, L. and Beni, G. (1991), A Validity Measure for Fuzzy Clustering, IEEE Transactions on Pattern Analysis and Machine Intelligence, 13(4), pp. 841-846
There are 26 citations in total.

Details

Primary Language English
Journal Section Articles
Authors

Necati Alp Erilli 0000-0001-6948-0880

Publication Date June 26, 2018
Submission Date September 8, 2017
Published in Issue Year 2018 Volume 6, Issue 1, 2018

Cite

APA Erilli, N. A. (2018). Economic Freedom Index Calculation Using FCM. Alphanumeric Journal, 6(1), 93-116. https://doi.org/10.17093/alphanumeric.337322

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