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The Devil is in the Detail: Hints for Practical Optimisation

T.M. Christensen, Stan Hurn and K.A. Lindsay
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T.M. Christensen: School of Economics and Finance, Queensland University of Technology
K.A. Lindsay: Department of Mathematics, University of Glasgow

Economic Analysis and Policy, 2008, vol. 38, issue 2, 345-368

Abstract: Finding 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.

Keywords: gradient algorithms; unconstrained optimisation; generalised method of moments (search for similar items in EconPapers)
JEL-codes: C13 C63 (search for similar items in EconPapers)
Date: 2008
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Citations: View citations in EconPapers (7)

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