|
|
|
|
||||
|
||||
New Insights into Optimal Control of Nonlinear Dynamic Econometric Models: Application of a Heuristic ApproachIvan SavinDFG Research Training Program "The Economics of Innovative Change", Friedrich Schiller University and the Max Planck Institute of Economics V. Blueschke-Nikolaevaaffiliation not provided to SSRN D. Blueschkeaffiliation not provided to SSRN 2012 Jena Economic Research Papers 2012-008 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.
Number of Pages in PDF File: 32 Keywords: differential evolution, dynamic programming, nonlinear optimization, optimal control JEL Classification: C54, C61, E27, E61, E62 working papers seriesDate posted: July 13, 2012Suggested CitationContact Information
|
|
||||||||||||||||||
© 2013 Social Science Electronic Publishing, Inc. All Rights Reserved.
FAQ
Terms of Use
Privacy Policy
Copyright
This page was processed by apollo1 in 0.515 seconds
