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Stochastic Optimisation and Worst Case Analysis in Monetary Policy Design

Author

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  • S. Zakovic
  • V. Wieland
  • B. Rustem

Abstract

In this paper, we show how stochastic optimisation and worst-case analysis can be used together in order to provide central banks with a straightforward tool for selecting a policy rule that limits worst-case outcomes while at the same time providing reasonably good performance on average. We conduct this analysis within a simple estimated model of the euro area with adaptive expectations. In particular, we consider not only uncertainty due to additive shocks but also uncertainty with respect to all the parameters of the model, including multiplicative parameters and potential nonlinearities in the inflation-output relationship. In terms of monetary policy we focus on the optimal choice of response coefficients in a Taylor-style interest rate rule that responds to inflation and the output gap and we evaluate the performance of this type of rule by means of a standard quadratic loss function in output and inflation. We then compare the rules obtained by the two different methods by comparing their respective performance in the worst-case scenario as well as the overall expected performance given the empirical probability distributions.

Suggested Citation

  • S. Zakovic & V. Wieland & B. Rustem, 2004. "Stochastic Optimisation and Worst Case Analysis in Monetary Policy Design," Computing in Economics and Finance 2004 213, Society for Computational Economics.
  • Handle: RePEc:sce:scecf4:213
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    References listed on IDEAS

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    1. Orphanides, Athanasios & Wieland, Volker, 2000. "Inflation zone targeting," European Economic Review, Elsevier, vol. 44(7), pages 1351-1387, June.
    2. Rustem, Berc, 1994. "Stochastic and robust control of nonlinear economic systems," European Journal of Operational Research, Elsevier, vol. 73(2), pages 304-318, March.
    3. Svensson, Lars E. O., 1997. "Inflation forecast targeting: Implementing and monitoring inflation targets," European Economic Review, Elsevier, pages 1111-1146.
    4. Laurence M. Ball, 1999. "Policy Rules for Open Economies," NBER Chapters,in: Monetary Policy Rules, pages 127-156 National Bureau of Economic Research, Inc.
    5. Andrew Levin & Volker Wieland & John C. Williams, 2003. "The Performance of Forecast-Based Monetary Policy Rules Under Model Uncertainty," American Economic Review, American Economic Association, pages 622-645.
    6. repec:cup:macdyn:v:6:y:2002:i:1:p:111-44 is not listed on IDEAS
    7. Andrew T.. Levin & Volker Wieland & John Williams, 1999. "Robustness of Simple Monetary Policy Rules under Model Uncertainty," NBER Chapters,in: Monetary Policy Rules, pages 263-318 National Bureau of Economic Research, Inc.
    8. Christopher A. Sims, 2001. "Pitfalls of a Minimax Approach to Model Uncertainty," American Economic Review, American Economic Association, vol. 91(2), pages 51-54, May.
    9. Lars Peter Hansen & Thomas J. Sargent & Thomas D. Tallarini, 1999. "Robust Permanent Income and Pricing," Review of Economic Studies, Oxford University Press, vol. 66(4), pages 873-907.
    10. J. Tetlow, Robert & von zur Muehlen, Peter, 2001. "Robust monetary policy with misspecified models: Does model uncertainty always call for attenuated policy?," Journal of Economic Dynamics and Control, Elsevier, vol. 25(6-7), pages 911-949, June.
    11. Peter Isard & Douglas Laxton & Ann-Charlotte Eliasson, 1999. "Simple Monetary Policy Rules Under Model Uncertainty," International Tax and Public Finance, Springer;International Institute of Public Finance, vol. 6(4), pages 537-577, November.
    12. Orphanides, Athanasios, 2003. "Monetary policy evaluation with noisy information," Journal of Monetary Economics, Elsevier, vol. 50(3), pages 605-631, April.
    13. Giannoni, Marc P., 2002. "Does Model Uncertainty Justify Caution? Robust Optimal Monetary Policy In A Forward-Looking Model," Macroeconomic Dynamics, Cambridge University Press, vol. 6(01), pages 111-144, February.
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    15. Peter von zur Muehlen, 2001. "Activist vs. non-activist monetary policy: optimal rules under extreme uncertainty," Finance and Economics Discussion Series 2001-02, Board of Governors of the Federal Reserve System (U.S.).
    16. Onatski, Alexei & Stock, James H., 2002. "Robust Monetary Policy Under Model Uncertainty In A Small Model Of The U.S. Economy," Macroeconomic Dynamics, Cambridge University Press, vol. 6(01), pages 85-110, February.
    17. Taylor, John B., 1993. "Discretion versus policy rules in practice," Carnegie-Rochester Conference Series on Public Policy, Elsevier, vol. 39(1), pages 195-214, December.
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    Citations

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    Cited by:

    1. Leitemo, Kai & Söderström, Ulf, 2008. "Robust monetary policy in a small open economy," Journal of Economic Dynamics and Control, Elsevier, pages 3218-3252.
    2. David Hudgins & Joon Na, 2016. "Entering H $$^{\infty }$$ ∞ -Optimal Control Robustness into a Macroeconomic LQ-Tracking Model," Computational Economics, Springer;Society for Computational Economics, vol. 47(2), pages 121-155, February.
    3. Keith Kuester & Volker Wieland, 2010. "Insurance Policies for Monetary Policy in the Euro Area," Journal of the European Economic Association, MIT Press, vol. 8(4), pages 872-912, June.
    4. Crowley, Patrick M. & Hudgins, David, 2015. "Fiscal policy tracking design in the time–frequency domain using wavelet analysis," Economic Modelling, Elsevier, vol. 51(C), pages 502-514.
    5. Arnulfo Rodriguez, 2004. "Robust Control: A Note on the Timing of Model Uncertainty," Computational Economics, Springer;Society for Computational Economics, vol. 24(3), pages 209-221, July.
    6. Lim, G.C. & McNelis, Paul D., 2007. "Inflation targeting, learning and Q volatility in small open economies," Journal of Economic Dynamics and Control, Elsevier, vol. 31(11), pages 3699-3722, November.
    7. Gadi Barlevy, 2009. "Policymaking under uncertainty: Gradualism and robustness," Economic Perspectives, Federal Reserve Bank of Chicago, issue Q II, pages 38-55.
    8. Q. Farooq Akram & Yakov Ben-Haim & Øyvind Eitrheim, 2006. "Managing uncertainty through robust-satisficing monetary policy," Working Paper 2006/10, Norges Bank.
    9. Esteban-Bravo, Mercedes & Vidal-Sanz, Jose M., 2007. "Worst-case estimation for econometric models with unobservable components," Computational Statistics & Data Analysis, Elsevier, vol. 51(7), pages 3330-3354, April.

    More about this item

    Keywords

    robust decisions; worst case analysis; expected value optimisation;

    JEL classification:

    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • E47 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Forecasting and Simulation: Models and Applications

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