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

D. Blueschke, V. Blueschke-Nikolaeva and Ivan Savin
Authors registered in the RePEc Author Service: Dmitri Blueschke

Journal of Economic Dynamics and Control, 2013, vol. 37, issue 4, 821-837

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: 2013
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (17)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:dyncon:v:37:y:2013:i:4:p:821-837

DOI: 10.1016/j.jedc.2012.12.003

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Journal of Economic Dynamics and Control is currently edited by J. Bullard, C. Chiarella, H. Dawid, C. H. Hommes, P. Klein and C. Otrok

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