New Insights Into Optimal Control of Nonlinear Dynamic Econometric Models: Application of a Heuristic Approach

D. Blueschke (dmitri.blueschke@aau.at), V. Blueschke-Nikolaeva (vbluesch@aau.at) and Ivan Savin
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D. Blueschke: University of Klagenfurt, Austria
V. Blueschke-Nikolaeva: University of Klagenfurt, Austria
Authors registered in the RePEc Author Service: Dmitri Blueschke

No 2012-008, Jena Economics Research Papers from Friedrich-Schiller-University Jena

Abstract: 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.

Keywords: Differential evolution; dynamic programming; nonlinear optimization; optimal control (search for similar items in EconPapers)
JEL-codes: C54 C61 E27 E61 E62 (search for similar items in EconPapers)
Date: 2012-03-07
New Economics Papers: this item is included in nep-cmp
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Journal Article: New insights into optimal control of nonlinear dynamic econometric models: Application of a heuristic approach (2013)
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