Model Averaging and its Use in Economics
Mark Steel ()
MPRA Paper from University Library of Munich, Germany
The method of model averaging has become an important tool to deal with model uncertainty, for example in situations where a large amount of different theories exist, as are common in economics. Model averaging is a natural and formal response to model uncertainty in a Bayesian framework, and most of the paper deals with Bayesian model averaging. The important role of the prior assumptions in these Bayesian procedures is highlighted. In addition, frequentist model averaging methods are also discussed. Numerical methods to implement these methods are explained, and I point the reader to some freely available computational resources. The main focus is on uncertainty regarding the choice of covariates in normal linear regression models, but the paper also covers other, more challenging, settings, with particular emphasis on sampling models commonly used in economics. Applications of model averaging in economics are reviewed and discussed in a wide range of areas, among which growth economics, production modelling, finance and forecasting macroeconomic quantities.
Keywords: Bayesian methods; Model uncertainty; Normal linear model; Prior specification; Robustness (search for similar items in EconPapers)
JEL-codes: C11 C15 C20 C52 O47 (search for similar items in EconPapers)
Date: 2017-09-19, Revised 2018-11-16
New Economics Papers: this item is included in nep-big, nep-cmp, nep-for, nep-ore and nep-rmg
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https://mpra.ub.uni-muenchen.de/90110/1/MPRA_paper_90110.pdf original version (application/pdf)
https://mpra.ub.uni-muenchen.de/91970/5/MPRA_paper_91970.pdf revised version (application/pdf)
Working Paper: Model Averaging and its Use in Economics (2017)
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Persistent link: https://EconPapers.repec.org/RePEc:pra:mprapa:90110
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