Model choice and size distribution: a Bayequentist approach
AbstractWe 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.
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Bibliographic InfoPaper provided by University of Lüneburg, Institute of Economics in its series Working Paper Series in Economics with number 265.
Length: 39 pages
Date of creation: Feb 2013
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Web page: http://leuphana.de/institute/ivwl.html
model choice; model selection; hypothesis testing; size distributions; Gibrat's Law; Pareto distribution; rank-size rule; environmental risk; semi-arid rangelands; cattle farming;
Find related papers by JEL classification:
- C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
- C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
- D30 - Microeconomics - - Distribution - - - General
- D31 - Microeconomics - - Distribution - - - Personal Income and Wealth Distribution
- O44 - Economic Development, Technological Change, and Growth - - Economic Growth and Aggregate Productivity - - - Environment and Growth
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