Abstract
Model uncertainty is a condition of analysis when the specification of the model of analysed process is open to doubt. A failure to account for model uncertainty may result in poor decisions. This article reviews various approaches to representing model uncertainty. The approaches depend on the research context, differ in their degree of generality, and may be classified as deterministic versus stochastic, Bayesian versus frequentist, and treating model uncertainty as static versus viewing model uncertainty as evolving over time.
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Onatski, A. (2018). Model Uncertainty. In: The New Palgrave Dictionary of Economics. Palgrave Macmillan, London. https://doi.org/10.1057/978-1-349-95189-5_2293
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DOI: https://doi.org/10.1057/978-1-349-95189-5_2293
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