IDEAS home Printed from https://ideas.repec.org/p/vic/vicewp/0101.html
   My bibliography  Save this paper

Econometric Modelling based on Pattern recognition via the Fuzzy c-Means Clustering Algorithm

Author

Listed:
  • David E. A. Giles

    ()

  • Robert Draeseke

Abstract

In this paper we consider the use of fuzzy modelling in the context of econometric analysis of both time-series and cross-section data. We discuss and demonstrate a semi-parametric methodology for model identification and estimation that is based on the Fuzzy c-Means algorithm that is widely used in the context of pattern recognition, and the Takagi-Sugeno approach to modelling fuzzy systems. This methodology is exceptionally flexible and provides a computationally tractable method of dealing with non-linear models in high dimensions. In this respect it has distinct theoretical advantages over non-parametric kernel regression, and we find that these advantages also hold empirically in terms of goodness-of-fit in a selection of economic applications.

Suggested Citation

  • David E. A. Giles & Robert Draeseke, 2001. "Econometric Modelling based on Pattern recognition via the Fuzzy c-Means Clustering Algorithm," Econometrics Working Papers 0101, Department of Economics, University of Victoria.
  • Handle: RePEc:vic:vicewp:0101
    Note: ISSN 1485-6441
    as

    Download full text from publisher

    File URL: http://www.uvic.ca/socialsciences/economics/assets/docs/econometrics/ewp0101.pdf
    Download Restriction: no

    References listed on IDEAS

    as
    1. Pagan,Adrian & Ullah,Aman, 1999. "Nonparametric Econometrics," Cambridge Books, Cambridge University Press, number 9780521355643, May.
    2. Murphy, Kevin M & Welch, Finis, 1990. "Empirical Age-Earnings Profiles," Journal of Labor Economics, University of Chicago Press, vol. 8(2), pages 202-229, April.
    3. Yu Hsing & David Smyth, 1994. "Kuznets's inverted-U hypothesis revisited," Applied Economics Letters, Taylor & Francis Journals, vol. 1(7), pages 111-113.
    4. Gregory Richardson, 1998. "The structure of fuzzy preferences: Social choice implications," Social Choice and Welfare, Springer;The Society for Social Choice and Welfare, vol. 15(3), pages 359-369.
    5. Mark Coppejans, 2000. "Breaking the Curse of Dimensionality," Econometric Society World Congress 2000 Contributed Papers 0830, Econometric Society.
    6. Jozsef, Sandor & Korosi, Gabor & Matyas, Laszlo, 1992. "A possible new approach of panel modelling," Structural Change and Economic Dynamics, Elsevier, vol. 3(2), pages 357-374, December.
    7. Coppejans, Mark, 2000. "Breaking the Curse of Dimensionality," Working Papers 00-13, Duke University, Department of Economics.
    8. Lindstrom, Tomas, 1998. "A fuzzy design of the willingness to invest in Sweden," Journal of Economic Behavior & Organization, Elsevier, vol. 36(1), pages 1-17, July.
    9. Peter Jacobsen & David Giles, 1998. "Income distribution in the United States: Kuznets' inverted-U hypothesis and data non-stationarity," The Journal of International Trade & Economic Development, Taylor & Francis Journals, vol. 7(4), pages 405-423.
    10. Finn E. Kydland & Edward C. Prescott, 1990. "Business cycles: real facts and a monetary myth," Quarterly Review, Federal Reserve Bank of Minneapolis, issue Spr, pages 3-18.
    11. Robert Draeseke & David E. A. Giles, 1999. "A Fuzzy Logic Approach to Modelling the Underground Economy," Econometrics Working Papers 9909, Department of Economics, University of Victoria.
    12. Kunal Sengupta, 1999. "Choice rules with fuzzy preferences: Some characterizations," Social Choice and Welfare, Springer;The Society for Social Choice and Welfare, vol. 16(2), pages 259-272.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Chad Stroomer & David E.A. Giles, 2003. "Income Convergence and trade Openness: Fuzzy Clustering and Time Series Evidence," Econometrics Working Papers 0304, Department of Economics, University of Victoria.
    2. David Giles & Chad Stroomer, 2006. "Does Trade Openness Affect the Speed of Output Convergence? Some Empirical Evidence," Empirical Economics, Springer, vol. 31(4), pages 883-903, November.
    3. Hui Feng & David E. Giles, 2007. "Bayesian Fuzzy Regression Analysis and Model Selection: Theory and Evidence," Econometrics Working Papers 0710, Department of Economics, University of Victoria.
    4. Morillas, Antonio & Díaz, Bárbara, 2007. "Qualitative Answering Surveys And Soft Computing," Fuzzy Economic Review, International Association for Fuzzy-set Management and Economy (SIGEF), vol. 0(1), pages 3-19, May.
    5. David E.A. Giles & Hui Feng, 2003. "Testing For Convergence in Output and in 'Well-Being' in Industrialized Countries," Econometrics Working Papers 0302, Department of Economics, University of Victoria.
    6. David E. A. Giles & Carl Mosk, 2003. "Ruminant Eructation and a Long-Run Environmental Kuznets' Curve for Enteric Methane in New Zealand: Conventional and Fuzzy Regression Analysis," Econometrics Working Papers 0306, Department of Economics, University of Victoria.
    7. David E. Giles & Chad N. Stroomer, 2004. "Identifying the Cycle of a Macroeconomic Time-Series Using Fuzzy Filtering," Econometrics Working Papers 0406, Department of Economics, University of Victoria.
    8. Giacomo Degli Antoni, 2007. "Do Social Relations Affect Economic Welfare? A Microeconomic Empirical Analysis," Working Papers 2007.32, Fondazione Eni Enrico Mattei.

    More about this item

    Keywords

    Fuzzy logic; fuzzy sets; fuzzy c-means algorithm; pattern recognition; semi-parametric modelling; curse of dimensionality.;

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C49 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Other
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:vic:vicewp:0101. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Graham Voss). General contact details of provider: http://edirc.repec.org/data/devicca.html .

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.