Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/56818 
Year of Publication: 
2012
Series/Report no.: 
Jena Economic Research Papers No. 2012,008
Publisher: 
Friedrich Schiller University Jena and Max Planck Institute of Economics, 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.
Subjects: 
differential evolution
dynamic programming
nonlinear optimization
optimal control
JEL: 
C54
C61
E27
E61
E62
Document Type: 
Working Paper

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