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

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

*Corresponding author for this work

Research output: Contribution to journalArticleResearchpeer-review

10 Citations (Scopus)

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.

Original languageEnglish
Pages (from-to)821-837
Number of pages17
JournalJournal of Economic Dynamics and Control
Volume37
Issue number4
DOIs
Publication statusPublished - Apr 2013

Keywords

  • Differential evolution
  • Dynamic programming
  • Nonlinear optimization
  • Optimal control

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