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Revisiting data mining: 'hunting' with or without a license

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  • Aris Spanos

Abstract

The primary objective of this paper is to revisit a number of empirical modelling activities which are often characterized as data mining, in an attempt to distinguish between the problematic and the non-problematic cases. The key for this distinction is provided by the notion of error-statistical severity. It is argued that many unwarranted data mining activities often arise because of inherent weaknesses in the Traditional Textbook (TT) methodology. Using the Probabilistic Reduction (PR) approach to empirical modelling, it is argued that the unwarranted cases of data mining can often be avoided by dealing directly with the weaknesses of the TT approach. Moreover, certain empirical modelling activities, such as diagnostic testing and data snooping, constitute legitimate procedures in the context of the PR approach.

Suggested Citation

  • Aris Spanos, 2001. "Revisiting data mining: 'hunting' with or without a license," Journal of Economic Methodology, Taylor & Francis Journals, vol. 7(2), pages 231-264.
    • Handle: RePEc:taf:jecmet:v:7:y:2001:i:2:p:231-264
    DOI: 10.1080/13501780050045119
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    References listed on IDEAS

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    1. John B. Davis & D. W. Hands & Uskali Mäki (ed.), 1998. "The Handbook of Economic Methodology," Books, Edward Elgar Publishing, number 741, March.
    2. Spanos,Aris, 1986. "Statistical Foundations of Econometric Modelling," Cambridge Books, Cambridge University Press, number 9780521269124, January.
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    Cited by:

    1. Panos Pashardes & Soteroula Hajispyrou, 2002. "Consumer Demand and Welfare under Increasing Block Pricing," University of Cyprus Working Papers in Economics 0207, University of Cyprus Department of Economics.
    2. Panos Hatzipanayotou & Sajal Lahiri & Michael S. Michael, 2002. "Reforms of Environmental Policies in the Presence of Cross-border Pollution and two Stage Clean Up," University of Cyprus Working Papers in Economics 0203, University of Cyprus Department of Economics.
    3. Spanos, Aris, 2009. "The Pre-Eminence of Theory versus the European CVAR Perspective in Macroeconometric Modeling," Economics - The Open-Access, Open-Assessment E-Journal (2007-2020), Kiel Institute for the World Economy (IfW Kiel), vol. 3, pages 1-14.
    4. Michael Haliassos, 2003. "Stockholding: Recent Lessons from Theory and Computations," Palgrave Macmillan Books, in: Luigi Guiso & Michael Haliassos & Tullio Jappelli (ed.), Stockholding in Europe, chapter 2, pages 30-49, Palgrave Macmillan.
    5. Thomas Mayer, 2006. "The Empirical Significance of Econometric Models," Working Papers 620, University of California, Davis, Department of Economics.
    6. Spanos, Aris, 2008. "The 'Pre-Eminence of Theory' versus the 'General-to-Specific' Cointegrated VAR Perspectives in Macro-Econometric Modeling," Economics Discussion Papers 2008-25, Kiel Institute for the World Economy (IfW Kiel).
    7. Spanos, Aris, 2010. "Statistical adequacy and the trustworthiness of empirical evidence: Statistical vs. substantive information," Economic Modelling, Elsevier, vol. 27(6), pages 1436-1452, November.
    8. Spanos, Aris, 2010. "Akaike-type criteria and the reliability of inference: Model selection versus statistical model specification," Journal of Econometrics, Elsevier, vol. 158(2), pages 204-220, October.

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