A Review of Heuristic Optimization Methods in Econometrics

47 Pages Posted: 5 Jun 2008  

Manfred Gilli

Geneva School of Economics and Management (GSEM); Swiss Finance Institute

Peter Winker

University of Giessen - Department of Economics

Date Written: June 2008

Abstract

Estimation and modelling problems as they arise in many fields often turn out to be intractable by standard numerical methods. One way to deal with such a situation consists in simplifying models and procedures. However, the solutions to these simplified problems might not be satisfying. A different approach consists in applying optimization heuristics such as evolutionary algorithms (Simulated Annealing, Threshold Accepting), Neural Networks, Genetic Algorithms, Tabu Search, hybrid methods and many others, which have been developed over the last two decades. Although the use of these methods became more standard in several fields of sciences, their use in estimation and modelling in econometrics appears to be still limited. We present an introduction to heuristic optimization methods and provide some examples for which these methods are found to work efficiently.

Keywords: Optimization heuristics, Estimation, Modelling

JEL Classification: C61, C63, C13

Suggested Citation

Gilli, Manfred and Winker, Peter, A Review of Heuristic Optimization Methods in Econometrics (June 2008). Swiss Finance Institute Research Paper No. 08-12. Available at SSRN: https://ssrn.com/abstract=1140655

Manfred Gilli (Contact Author)

Geneva School of Economics and Management (GSEM) ( email )

Bd du Pont d'Arve 46
Geneva 4, 1211
Switzerland
+41223798222 (Phone)
+41223798299 (Fax)

HOME PAGE: http://www.unige.ch/ses/metri/gilli/

Swiss Finance Institute ( email )

c/o University of Geneva
40, Bd du Pont-d'Arve
CH-1211 Geneva 4
Switzerland

Peter Winker

University of Giessen - Department of Economics ( email )

Licher Str. 62
D-35394 Giessen, DE
Germany

HOME PAGE: http://wiwi.uni-giessen.de/home/oekonometrie/

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