IDEAS home Printed from
   My bibliography  Save this paper

A Worst--Case Approach to Inflation Zone Targeting


  • B. Rustem, V. W. Wieland and S. Zakovic


In this paper we present an algorithm for continuous minimax problem where a quasi--Newton direction conditional on appropriate maximizers is used. The direction involves a quadratic subproblem to compute the minimum norm subgradient. An application of the algorithm to a monetary policy design is given. A simple model, due to Orphanides and Wieland, is used for practice of inflation zone targeting. In this paper, however, the approach is different as we minimize the worst--case with respect to inflation and economic activity. Also a comparison with the $H^infinity approach is included.

Suggested Citation

  • B. Rustem, V. W. Wieland and S. Zakovic, 2001. "A Worst--Case Approach to Inflation Zone Targeting," Computing in Economics and Finance 2001 15, Society for Computational Economics.
  • Handle: RePEc:sce:scecf1:15

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a search for a similarly titled item that would be available.

    References listed on IDEAS

    1. Powell, Alan A., 2000. "From Dornbusch to Murphy: Stylized Monetary Dynamics of a Contemporary Macroeconometric Model," Journal of Policy Modeling, Elsevier, vol. 22(1), pages 99-116, January.
    2. Orphanides, Athanasios & Wieland, Volker, 2000. "Inflation zone targeting," European Economic Review, Elsevier, vol. 44(7), pages 1351-1387, June.
    3. Mercado, P. Ruben & Kendrick, David A., 2000. "Caution in macroeconomic policy: uncertainty and the relative intensity of policy," Economics Letters, Elsevier, vol. 68(1), pages 37-41, July.
    4. Neck, Reinhard & Matulka, Josef, 1994. "Stochastic optimum control of macroeconometric models using the algorithm OPTCON," European Journal of Operational Research, Elsevier, vol. 73(2), pages 384-405, March.
    Full references (including those not matched with items on IDEAS)

    More about this item


    minimax optimization; inflation targeting; uncertainty;

    JEL classification:

    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • E43 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Interest Rates: Determination, Term Structure, and Effects


    Access and download statistics


    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:sce:scecf1:15. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Christopher F. Baum). General contact details of provider: .

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.