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Stochastic Optimization and Worst-Case Analysis in Monetary Policy Design

Abstract

In this paper we compare expected loss minimization to worst-case or minimax analysis in the design of simple Taylor-style rules for monetary policy. To this end we use a small model estimated for the euro area by Orphanides and Wieland (2000). We find that rules optimized under a minimax objective in the presence of general parameter and shock uncertainty do not imply extreme policy activism. Such rules also tend to obey the Brainard principle, which implies that policy responsiveness declines with increasing uncertainty about policy effectiveness. We find that rules derived by means of minimax analysis are effective insurance policies limiting maximum loss over ranges of parameter values to be set by the policy maker. In practice, we propose to set these ranges with an eye towards the cost of such insurance cover in terms of the implied increase in expected inflation variability.

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Correspondence to Volker Wieland.

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JEL Classifications System: E52, E58, E61

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Žaković, S., Wieland, V. & Rustem, B. Stochastic Optimization and Worst-Case Analysis in Monetary Policy Design. Comput Econ 30, 329–347 (2007). https://doi.org/10.1007/s10614-005-9012-4

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  • DOI: https://doi.org/10.1007/s10614-005-9012-4

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