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Methods for Robust Control

Author

Listed:
  • Richard Dennis

    (Economic Research Federal Reserve Bank of San Francisco)

  • Kai Leitemo
  • Ulf Soderstrom

Abstract

Robust control allows policymakers to formulate policies that guard against model misspecification. The principal tools used to solve robust control problems are state-space methods (see Hansen and Sargent, 2005, and Giordani and Soderlind, 2004). In this paper we show that the structural-form methods developed by Dennis (2005a) to solve control problems with rational expectations can also be applied to robust control problems, with the advantage that they bypass the task, often onerous, of having to express the reference model in a state-space form. Interestingly, state-space and structural-form methods do not necessarily return the same equilibria for robust control problems. We apply both state-space and structural solution methods to an empirical New Keynesian business cycle model and find that the differences between the methods are both qualitatively and quantitatively important. In particular, with the structural-form solution methods the specification errors generally involve changes to the conditional variances in addition to the conditional means of the shock processes

Suggested Citation

  • Richard Dennis & Kai Leitemo & Ulf Soderstrom, 2006. "Methods for Robust Control," 2006 Meeting Papers 493, Society for Economic Dynamics.
    • Handle: RePEc:red:sed006:493
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    JEL classification:

    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • E52 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Monetary Policy
    • E58 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Central Banks and Their Policies

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