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Probability models and robust policy rules

  • Levine, Paul
  • McAdam, Peter
  • Pearlman, Joseph

We consider Sims's (2008) argument that robust policy making requires that policy models be treated as “probability models”. In a welfare-based setting, we estimate by Bayesian methods a number of variants of a New Keynesian macroeconomic model and use both the model odds and posterior densities to design robust interest rate rules consisting of an inflation-forecast-based rule and a wage-targeting one. Each are shown to have distinct robustness qualities and distinct implications for the probability-models approach. To ensure feasible policy, we further impose that rules are stable, determinate and lower-bound compatible. Our results have important implications for the design, evaluation and analysis of the probability models approach to robust monetary policy making.

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Article provided by Elsevier in its journal European Economic Review.

Volume (Year): 56 (2012)
Issue (Month): 2 ()
Pages: 246-262

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Handle: RePEc:eee:eecrev:v:56:y:2012:i:2:p:246-262
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