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The complexity of simplicity

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  • Keuzenkamp, Hugo A.
  • McAleer, Michael

Abstract

This paper is concerned with the practical problems associated with understanding and defining the concept of simplicity. Different attempts that have been made to define simplicity and, in particular, definitions based on counting parameters, are discussed and analyzed. The limitations of these attempts, especially as applied to economics, are illustrated by means of several econometric examples, including single-equation models, systems of equations, alternative functional forms, and probability distributions.

Suggested Citation

  • Keuzenkamp, Hugo A. & McAleer, Michael, 1997. "The complexity of simplicity," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 43(3), pages 553-561.
    • Handle: RePEc:eee:matcom:v:43:y:1997:i:3:p:553-561
    DOI: 10.1016/S0378-4754(97)00044-X
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    References listed on IDEAS

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    1. Keuzenkamp, H.A. & McAleer, M., 1994. "Simplicity, scientific inference and econometric modelling," Other publications TiSEM dabcc476-15d7-4177-a2f5-b, Tilburg University, School of Economics and Management.
    2. Fiebig, Denzil G. & McAleer, Michael & Bartels, Robert, 1992. "Properties of ordinary least squares estimators in regression models with nonspherical disturbances," Journal of Econometrics, Elsevier, vol. 54(1-3), pages 321-334.
    3. McAleer, Michael & McKenzie, C R, 1991. "Keynesian and New Classical Models of Unemployment Revisited," Economic Journal, Royal Economic Society, vol. 101(406), pages 359-381, May.
    4. Bai, J. & Jakeman, A.J. & Mcaleer, M., 1990. "Estimation And Discrimination Of Alternative Air Pollution Models," Papers 209, Australian National University - Department of Economics.
    5. Sims, Christopher A, 1980. "Macroeconomics and Reality," Econometrica, Econometric Society, vol. 48(1), pages 1-48, January.
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    Cited by:

    1. Zellner, Arnold, 1999. "Keep It Sophisticatedly Simple," CUDARE Working Papers 198673, University of California, Berkeley, Department of Agricultural and Resource Economics.
    2. Ronald W. Butler & Marc S. Paolella, 2017. "Autoregressive Lag—Order Selection Using Conditional Saddlepoint Approximations," Econometrics, MDPI, vol. 5(3), pages 1-33, September.

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