Mitigation Of The Lucas Critique With Stochastic Control Methods
AbstractLucas (1976) pointed out, that when optimization is performed on a deterministic macro model, the resulting policy may not reflect the true optimal solution. Private agents may react to announced policies and consequently model parameters will start to drift. The aim of this paper is to develop a methodology for deriving an optimal policy in the presence of rational expectations and parameter drift. This drift is captured by a stochastic optimization framework with time varying parameters. The resulting optimal policy is capable of tracking changes in the parameters due to policy changes. A numerical example illustrates how the methodology provides a way to mitigate the effects of the Lucas critique.
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Bibliographic InfoPaper provided by Society for Computational Economics in its series Computing in Economics and Finance 2000 with number 182.
Date of creation: 05 Jul 2000
Date of revision:
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Other versions of this item:
- 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), pages 2035-2057.
- 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.
- C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
- E61 - Macroeconomics and Monetary Economics - - Macroeconomic Policy, Macroeconomic Aspects of Public Finance, and General Outlook - - - Policy Objectives; Policy Designs and Consistency; Policy Coordination
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