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Simplicity, Scientific Interference and Econometric Modelling

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  • Keuzenkamp, Hugo A
  • McAleer, Michael

Abstract

Two issues are discussed in this paper. The first is whether a formal definition and justification of simplicity (parsimony) in scientific inference can be found, and whether an optimal level of simplicity is obtainable. A definition of simplicity is possible, as are the optimum conditions for the desired degree of simplicity. The model of inference used here relates Bayesian inference to algorithmic information theory. Simplicity is examined in the light of induction, the Duhem-Quine thesis, and bounded rationality. The second issue relates to the role that simplicity might play in econometric modeling. This is elucidated with some remarks on the 'general to specific' approach to modeling and discussions on the purpose of a model. Copyright 1995 by Royal Economic Society.

Suggested Citation

  • Keuzenkamp, Hugo A & McAleer, Michael, 1995. "Simplicity, Scientific Interference and Econometric Modelling," Economic Journal, Royal Economic Society, vol. 105(428), pages 1-21, January.
  • Handle: RePEc:ecj:econjl:v:105:y:1995:i:428:p:1-21
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    Cited by:

    1. Thomas Mayer, 2006. "The Empirical Significance of Econometric Models," Working Papers 620, University of California, Davis, Department of Economics.
    2. Werner Ploberger, 2000. "Empirical Limits for Time Series Models," Econometric Society World Congress 2000 Contributed Papers 1909, Econometric Society.
    3. Kakarot-Handtke, Egmont, 2010. "Axiomatic Basics of e-Economics," MPRA Paper 24331, University Library of Munich, Germany.
    4. Kakarot-Handtke, Egmont, 2011. "Properties of an economy without human beings," MPRA Paper 31497, University Library of Munich, Germany.
    5. Kakarot-Handtke, Egmont, 2011. "Keynes’s missing axioms," MPRA Paper 32742, University Library of Munich, Germany, revised 11 Aug 2011.
    6. Kakarot-Handtke, Egmont, 2011. "Schumpeter and the essence of profit," MPRA Paper 31176, University Library of Munich, Germany.
    7. Werner Ploberger & Peter C. B. Phillips, 2003. "Empirical Limits for Time Series Econometric Models," Econometrica, Econometric Society, vol. 71(2), pages 627-673, March.

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