Model choice and size distribution: a Bayequentist approach

John-Oliver Engler () and Stefan Baumgaertner
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John-Oliver Engler: Department of Sustainability Sciences and Department of Economics Leuphana University of Lueneburg, Germany
Stefan Baumgaertner: Department of Sustainability Sciences and Department of Economics Leuphana University of Lueneburg, Germany
Authors registered in the RePEc Author Service: Stefan Baumgärtner

No 265, Working Paper Series in Economics from University of Lüneburg, Institute of Economics

Abstract: We propose a new three-step model-selection framework for size distributions in empirical data. It generalizes a recent frequentist plausibility-of-fit analysis (Step 1) and combines it with a relative ranking based on the Bayesian Akaike Information Criterion (Step 2). We enhance these statistical criteria with the additional criterion of microfoundation (Step 3) which is to select the size distribution that comes with a dynamic micro model of size dynamics. A numerical performance test of Step 1 shows that our generalization is able to correctly rule out the distribution hypotheses unjustified by the data at hand. We then illustrate our approach, and demonstrate its usefulness, with a sample of commercial cattle farms in Namibia. In conclusion, the framework proposed here has the potential to reconcile the ongoing debate about size distribution models in empirical data, the two most prominent of which are the Pareto and the lognormal distribution.

Keywords: model choice; model selection; hypothesis testing; size distributions; Gibrat's Law; Pareto distribution; rank-size rule; environmental risk; semi-arid rangelands; cattle farming (search for similar items in EconPapers)
JEL-codes: C12 C52 D30 D31 O44 (search for similar items in EconPapers)
Pages: 39 pages
Date: 2013-02
New Economics Papers: this item is included in nep-ecm
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Journal Article: Model Choice and Size Distribution: A Bayequentist Approach (2015)
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