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The Performance of Forward-Looking Monetary Policy Rules under Model Uncertainty


  • Volker Wieland

    () (Federal Reserve Board)

  • Andrew Levin

    () (Federal Reserve Board)

  • John C. Williams

    () (Federal Reserve Board)


Recently, increasing attention is being devoted to interest rate rules that respond directly to economic forecasts rather than relying on current and past observations. Empirical studies suggest this 'forward-looking' rule provides a reasonable description of recent monetary policy in several industrial countries. Such rules are also advocated on analytical grounds including simplicity, transparency, and efficiency. But, such rules can fail to generate unique rational expectations equilibrium under various combinations of structural and policy parameters, raising concerns whether forward-looking rules are robust to model uncertainty. Here, we analyze the efficiency and robustness of forward-looking rules using four structural macroeconometric models of the U.S. economy: the Fuhrer-Moore model, Taylor's Multi-Country Model, the MSR model of Orphanides and Wieland, and the FRB staff model. All four incorporate assumptions of rational expectations, short-run nominal inertia, and long-run monetary neutrality, but differ in other respects such as real expenditures and the dynamics of prices. We assume a policy objective of minimizing a weighted sum of the unconditional variances of the inflation rate, the output gap, and federal funds rate changes. For given model and particular class of policy rules, we determine the region of the parameter space for which simple forward-looking and backward-looking rules generate unique equilibria. Within this region, we determine the performance of rules on the policy frontier -- the best obtainable outcomes for output, inflation, and funds-rate volatilities. Finally, we evaluate robustness to model uncertainty, taking rules that perform well in one model and assessing their performance in each of the other three. Our analysis yields three significant conclusions. First, the indeterminacy problem is not one of practical concern. All four models exhibit a relatively high degree of nominal and real inertia consistent with U.S. data. Second, in each model, we find that forward-looking rules provide negligible stabilization benefits compared with well-designed backward-looking rules. Finally, the forward-looking rules that perform well in one model often perform very poorly in the other three. By contrast, simple backward-looking rules taken from the policy frontier of one model are generally very close to the frontier in each of the other three. Thus, while small improvements in output and inflation variability can sometimes be obtained using forward-looking rules, we find them to be much less robust to model uncertainty than simple backward-looking rules.

Suggested Citation

  • Volker Wieland & Andrew Levin & John C. Williams, 1999. "The Performance of Forward-Looking Monetary Policy Rules under Model Uncertainty," Computing in Economics and Finance 1999 1153, Society for Computational Economics.
  • Handle: RePEc:sce:scecf9:1153

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    Cited by:

    1. 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.
    2. Roberts John M., 2005. "How Well Does the New Keynesian Sticky-Price Model Fit the Data?," The B.E. Journal of Macroeconomics, De Gruyter, vol. 5(1), pages 1-39, September.
    3. Tetlow, Robert J. & von zur Muehlen, Peter, 2009. "Robustifying learnability," Journal of Economic Dynamics and Control, Elsevier, vol. 33(2), pages 296-316, February.
    4. Amman, Hans M. & Kendrick, David A., 2003. "Mitigation of the Lucas critique with stochastic control methods," Journal of Economic Dynamics and Control, Elsevier, vol. 27(11-12), pages 2035-2057, September.
    5. Richard Dennis, 2003. "Exploring the Role of the Real Exchange Rate in Australian Monetary Policy," The Economic Record, The Economic Society of Australia, vol. 79(244), pages 20-38, March.
    6. Kendrick, David A., 2005. "Stochastic control for economic models: past, present and the paths ahead," Journal of Economic Dynamics and Control, Elsevier, vol. 29(1-2), pages 3-30, January.

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