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Optimal Control of Nonlinear Dynamic Econometric Models: An Algorithm and an Application

  • Viktoria Blüschke-Nikolaeva
  • Dmitri Blüschke
  • Reinhard Neck

In this paper, we present a new version of the OPTCON algorithm for the optimal control of nonlinear stochastic systems with special reference to econometric models. It delivers approximate numerical solutions of optimum control problems with a quadratic objective function for nonlinear econometric models with additive and multiplicative (parameter) uncertainties. The algorithm was programmed in C# and allows for deterministic and stochastic control, the latter with open-loop and passive learning (open-loop feedback) information patterns. We demonstrate the applicability of the algorithm by experiments with a small quarterly macroeconometric model for Slovenia. This shows the convergence and the practical usefulness of the algorithm and (in most cases) the superiority of open-loop feedback over open-loop controls.

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File URL: http://comisef.eu/files/wps032.pdf
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Paper provided by COMISEF in its series Working Papers with number 032.

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Length: 48 pages
Date of creation: 22 Feb 2010
Date of revision:
Handle: RePEc:com:wpaper:032
Contact details of provider: Web page: http://www.comisef.eu

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  1. Coomes, Paul A., 1987. "PLEM: A computer program for passive learning, stochastic control experiments," Journal of Economic Dynamics and Control, Elsevier, vol. 11(2), pages 223-227, June.
  2. Neck, Reinhard, 1984. "Stochastic control theory and operational research," European Journal of Operational Research, Elsevier, vol. 17(3), pages 283-301, September.
  3. Hans M. Amman & David A. Kendrick, 1997. "Should Macroeconomic Policy Makers Consider Parameter Covariances?," CARE Working Papers 9701, The University of Texas at Austin, Center for Applied Research in Economics.
  4. Marianna Lyra & Johannes Paha & Sandra Paterlini & Peter Winker, 2008. "Optimization Heuristics for Determining Internal Rating Grading Scales," Center for Economic Research (RECent) 023, University of Modena and Reggio E., Dept. of Economics "Marco Biagi".
  5. Hans M. Amman & David A. Kendrick, 2003. "A Classification System for Economic Stochastic Control Models," Computing in Economics and Finance 2003 114, Society for Computational Economics.
  6. Winker, Peter & Gilli, Manfred, 2004. "Applications of optimization heuristics to estimation and modelling problems," Computational Statistics & Data Analysis, Elsevier, vol. 47(2), pages 211-223, September.
  7. Chen, Baoline & Zadrozny, Peter A., 2009. "Multi-step perturbation solution of nonlinear differentiable equations applied to an econometric analysis of productivity," Computational Statistics & Data Analysis, Elsevier, vol. 53(6), pages 2061-2074, April.
  8. Hans M. Amman & David A. Kendrick, . "Computational Economics," Online economics textbooks, SUNY-Oswego, Department of Economics, number comp1, March.
  9. Amman, Hans, 1996. "Numerical methods for linear-quadratic models," Handbook of Computational Economics, in: H. M. Amman & D. A. Kendrick & J. Rust (ed.), Handbook of Computational Economics, edition 1, volume 1, chapter 13, pages 587-618 Elsevier.
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