A Toolkit for Optimizing Functions in Economics
AbstractOptimization algorithms must be among the most common numerical methods used by economists. Yet, there is surprisingly little guidance on choosing the appropriate one. This problem is most notable with regard to conventional versus global optimizers. Typically, a global optimizer is used when a conventional one fails after substantial ``fiddling'' with a conventional optimizer. This paper introduces three different, easy-to-use, tools (cross-sections, radius plots, and a measure of the non-quadratic behavior of a function) that are designed to indicate when a global optimizer is needed. With their use, researchers should spend less time fiddling and more time generating results.
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Bibliographic InfoPaper provided by EconWPA in its series Computational Economics with number 9707001.
Length: 14 pages
Date of creation: 16 Jul 1997
Date of revision:
Note: Type of Document - ; prepared on Linux/LaTeX; to print on PostScript; pages: 14; figures: included. none
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optimization; estimation; simulation; algorithm;
Other versions of this item:
- C8 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs
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- Goffe William L., 1996. "SIMANN: A Global Optimization Algorithm using Simulated Annealing," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 1(3), pages 1-9, October.
- Veall, Michael R, 1990. "Testing for a Global Maximum in an Econometric Context," Econometrica, Econometric Society, vol. 58(6), pages 1459-65, November.
- Goffe, William L. & Ferrier, Gary D. & Rogers, John, 1994. "Global optimization of statistical functions with simulated annealing," Journal of Econometrics, Elsevier, vol. 60(1-2), pages 65-99.
- Hoffman, Dennis L. & Schmidt, Peter, 1981. "Testing the restrictions implied by the rational expectations hypothesis," Journal of Econometrics, Elsevier, vol. 15(2), pages 265-287, February.
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