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Simplicity, Scientific Inference and Econometric Modelling

Bibliographic Data

ID9712977
AuthorsHugo A Keuzenkamp (Tilburg University), Michael McAleer (0000-0003-2707-3835, The University of Western Australia)
Year1995
Volume105
Issue428
Pages1
Publication date1995-01-01
Peer ReviewedYes
Open AccessNo
TypeARTICLE
VenueThe Economic Journal (JOURNAL)
Journal identifiersISSN: 0013-0133 • E-ISSN: 1468-0297
PublisherOxford University Press (OUP) (PUBLISHER)
DOI10.2307/2235317
OpenAlexW2023698897
LanguageEN
Citations received1

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

Bayesian inference · Bayesian probability · Epistemology · Inference · Mathematical economics · Simplicity · Artificial Intelligence · Complex Systems and Time Series Analysis · Computer Science · Mathematics · Philosophy

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Unique citing works1
Citations per year0,06
Citation span2010 - 2010 (1)
Citation velocityhistorical
Highly citedNo
Citation typesNeutral: 1
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