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Numerical Steady State Solutions for Nonlinear Dynamic Optimization Models

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Author Info
Hans M. Amman () (University of Amsterdam)
David A. Kendrick () (University of Texas)
Heinz Neudecker (University of Amsterdam)

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Abstract

Nonlinear dynamic optimization models are widely used in theoretical and empirical economic modeling, especially in the field of optimal growth and intertemporal macroeconomic modeling. In this paper we present a sequential quadratic programming algorithm for computing directly the steady state solution for a wide class of nonlinear dynamic optimization problems in discrete time.

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Paper provided by Society for Computational Economics in its series Computing in Economics and Finance 1996 with number _003.

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Handle: RePEc:sce:scecf6:_003

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Postal: Department of Econometrics, University of Geneva, 102 Bd Carl-Vogt, 1211 Geneva 4, Switzerland
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  1. Hans M. Amman & David A. Kendrick, 1997. "Computing the Steady State of Linear Quadratic Optimization Models with Rational Expectations," Economics, University of Texas at Austin 9707, Center for Applied Research in Economics. [Downloadable!]
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  2. P. Mercado & David Kendrick, 2006. "Parameter Uncertainty and Policy Intensity: Some Extensions and Suggestions for Further Work," Computational Economics, Springer, vol. 27(4), pages 483-496, June. [Downloadable!] (restricted)
  3. Arnulfo Rodriguez, 2004. "Robust Control: A Note on the Timing of Model Uncertainty," Computational Economics, Springer, vol. 24(3), pages 209-221, July. [Downloadable!] (restricted)
  4. Arnulfo Rodriguez, 2004. "Robust Control: A Note on the Timing of Model Uncertainty," Computing in Economics and Finance 2004 147, Society for Computational Economics. [Downloadable!]
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