The Devil is in the Detail: Hints for Practical Optimisation
AbstractFinding the minimum of an objective function, such as a least squares or negative log-likelihood function, with respect to the unknown model parameters is a problem often encountered in econometrics. Consequently, students of econometrics and applied econometricians are usually well-grounded in the broad differences between the numerical procedures employed to solve these problems. Often, however, relatively little time is given to understanding the practical subtleties of implementing these schemes when faced with illbehaved problems. This paper addresses some of the details involved in practical optimisation, such as dealing with constraints on the parameters, specifying starting values, termination criteria and analytical gradients, and illustrates some of the general ideas with several instructive examples.
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Bibliographic InfoArticle provided by Queensland University of Technology (QUT), School of Economics and Finance in its journal Economic Analysis and Policy (EAP).
Volume (Year): 38 (2008)
Issue (Month): 2 (September)
gradient algorithms; unconstrained optimisation; generalised method of moments;
Other versions of this item:
- T M Christensen & A S Hurn & K A Lindsay, 2008. "The Devil is in the Detail: Hints for Practical Optimisation," NCER Working Paper Series 32, National Centre for Econometric Research.
- C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
- C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
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