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Data Mining: A Reconsideration

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  • Thomas Mayer

Abstract

Before condemning data mining one should distinguish between objective and biased data mining. The former is commendable. Even biased data mining is appropriate when used to illustrate and not to test hypotheses. In the context of testing, the problem with biased data mining arises not from the fitting of many regression, but from inadequate reporting of results. The trend towards reporting the results of more alternative specifications, and thus addressing the fragility problem, should be encouraged. To do that the incentives that economists face should be changed.

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Bibliographic Info

Paper provided by California Davis - Department of Economics in its series Department of Economics with number 97-15.

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Handle: RePEc:fth:caldec:97-15

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Postal: University of California Davis - Department of Economics. One Shields Ave., California 95616-8578
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Cited by:
  1. Gérard Charreaux, 2008. "La recherche en finance d’entreprise:quel positionnement méthodologique?," Working Papers CREGO 1080501, Université de Bourgogne - CREGO EA7317 Centre de recherches en gestion des organisations.
  2. David Colander, 2000. "New Millennium Economics: How Did It Get This Way, and What Way Is It?," Journal of Economic Perspectives, American Economic Association, vol. 14(1), pages 121-132, Winter.
  3. Amavilah, Voxi Heinrich, 2012. "The Caldwellian Methodological Pluralism: Wishful Thoughts and Personal Tendencies," MPRA Paper 44656, University Library of Munich, Germany, revised 28 Feb 2013.

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