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Nested models and model uncertainty

Author

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  • Alexander Kriwoluzky
  • Christian A. Stoltenberg

Abstract

Uncertainty about the appropriate choice among nested models is a central concern for optimal policy when policy prescriptions from those models differ. The standard procedure is to specify a prior over the parameter space ignoring the special status of some sub-models, e.g. those resulting from zero restrictions. This is especially problematic if a model's generalization could be either true progress or the latest fad found to fit the data. We propose a procedure that ensures that the specified set of sub-models is not discarded too easily and thus receives no weight in determining optimal policy. We find that optimal policy based on our procedure leads to substantial welfare gains compared to the standard practice.

Suggested Citation

  • Alexander Kriwoluzky & Christian A. Stoltenberg, 2009. "Nested models and model uncertainty," Economics Working Papers ECO2009/37, European University Institute.
  • Handle: RePEc:eui:euiwps:eco2009/37
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    References listed on IDEAS

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    Cited by:

    1. Sienknecht, Sebastian, 2016. "Reassessing price adjustment costs in DSGE models," MPRA Paper 73763, University Library of Munich, Germany.

    More about this item

    Keywords

    Optimal monetary policy; model uncertainty; Bayesian model estimation;

    JEL classification:

    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • E52 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Monetary Policy

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