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 Society for Computational Economics in its series Computing in Economics and Finance 1997 with number 65.
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- 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.
- 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.
- 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.
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