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Simplicity, Scientific Inference and Econometric Modelling

Hugo A. Keuzenkamp and Michael McAleer
The Economic Journal
Vol. 105, No. 428 (Jan., 1995), pp. 1-21
Published by: Wiley on behalf of the Royal Economic Society
DOI: 10.2307/2235317
Stable URL: http://www.jstor.org/stable/2235317
Page Count: 21
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Simplicity, Scientific Inference and Econometric Modelling
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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 modelling. This is elucidated with some remarks on the `general to specific' approach to modelling and discussions on the purpose of a model.

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