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New insights into optimal control of nonlinear dynamic econometric models: Application of a heuristic approach

  • Blueschke, D.
  • Blueschke-Nikolaeva, V.
  • Savin, I.

Optimal control of dynamic econometric models has a wide variety of applications including economic policy relevant issues. There are several algorithms extending the basic case of a linear-quadratic optimization and taking nonlinearity and stochastics into account, but being still limited in a variety of ways, e.g., symmetry of the objective function and identical data frequencies of control variables. To overcome these problems, an alternative approach based on heuristics is suggested. To this end, we apply a ‘classical’ algorithm (OPTCON) and a heuristic approach (Differential Evolution) to three different econometric models and compare their performance. In this paper we consider scenarios of symmetric and asymmetric quadratic objective functions. Results provide a strong support for the heuristic approach encouraging its further application to optimum control problems.

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Article provided by Elsevier in its journal Journal of Economic Dynamics and Control.

Volume (Year): 37 (2013)
Issue (Month): 4 ()
Pages: 821-837

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Handle: RePEc:eee:dyncon:v:37:y:2013:i:4:p:821-837
Contact details of provider: Web page: http://www.elsevier.com/locate/jedc

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  1. 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".
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  9. Reinhard Neck & Dmitri Blueschke & Klaus Weyerstrass, 2011. "Optimal macroeconomic policies in a financial and economic crisis: a case study for Slovenia," Empirica, Springer, vol. 38(3), pages 435-459, July.
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