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Les algorithmes de la modélisation : une analyse critique pour la modélisation économique

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  • Buda, Rodolphe

Abstract

L'objet de ce papier n'est pas tant de présenter les principaux algorithmes utilisés en modélisation économique - nombre de manuels font des présentations de meilleure qualité et plus exhaustives - que d'en proposer une vision critique. Les modèles économiques, et plus particulièrement les modèles macroéconométriques, sont des représentations numériques qui, de ce fait, ont opéré des choix de simplification voire de réduction de la réalité. Revenir sur les algorithmes existants peut donc, nous l'espérons, constituer une étape vers la reformulation d'algorithmiques plus féconds pour la modélisation. Le problème de la modélisation consiste à se poser la question de savoir, compte tenu de l'état observé de l'économie et sous certaines hypothèses, quelle sera en mode projection, quelle serait (en mode simulation), l'état futur (vs l'état alternatif) de cette économie ? Depuis la phase de gestion de la banque de données qui requiert divers algorithmes de tri, jusqu'aux algorithmes d'analyse numérique impliqués dans les calculs matriciels d'estimation économétrique - pour être bref -, le fonctionnement de la modélisation macroéconométrique s'explique par des algorithmes . Il implique l'emploi d'une syntaxe, l'algorithmique, et d'un langage, les mathématiques. L'algorithme est une séquence d'instructions ordonnées et formalisées, permettant d'aboutir à la résolution du problème étudié. Peu d'ouvrages sont consacrés aux phases algorithmiques de la modélisation . Si les algorithmes visent tous à assister la décision (analyses rétrospective et prospective), ils sont loin de former une librairie homogène de programmes. Nous aborderons des algorithmes directement liés à un traitement numérique (estimation statistique, simulation optimisation). Mais nous consacrerons également quelques lignes à des algorithmes de nature apparemment "moins numériques", mais intervenant dans des phases déterminantes de la modélisation. Il s'agira d'une part des algorithmes permettant de structurer et/ou d'analyse des données ainsi que des algorithmes graphiques et ceux de communication. Enfin nous aborderons brièvement le problème de précision des calculs lié à l'arithmétique des ordinateurs. Délibérément, nous n'avons développé les aspects relatifs au Génie logiciel , de même que dans un souci de clarté, nous avons regroupé les programmes en annexe, lorsque la compréhension n'exigeait pas qu'ils accompagnent le texte. Notre présentation sera jalonnée de travaux algorithmiques et de références à nos notes de travail, réalisés dans le cadre de notre thèse de Doctorat.

Suggested Citation

  • Buda, Rodolphe, 2001. "Les algorithmes de la modélisation : une analyse critique pour la modélisation économique," MPRA Paper 3926, University Library of Munich, Germany, revised Jul 2004.
    • Handle: RePEc:pra:mprapa:3926
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    References listed on IDEAS

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    1. Nicolaas J. Vriend, 2002. "Was Hayek an Ace?," Southern Economic Journal, John Wiley & Sons, vol. 68(4), pages 811-840, April.
    2. Kendrick, David A & Amman, Hans M, 1999. "Programming Languages in Economics," Computational Economics, Springer;Society for Computational Economics, vol. 14(1-2), pages 151-181, October.
    3. Hans M. Amman & David A. Kendrick, . "Computational Economics," Online economics textbooks, SUNY-Oswego, Department of Economics, number comp1, December.
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    Cited by:

    1. Buda, Rodolphe, 2005. "Relevance of an accuracy control module - implementation into an economic modelling software," MPRA Paper 36520, University Library of Munich, Germany.
    2. Buda, Rodolphe, 2005. "Numerical Analysis in Econom(etr)ic Softwares: the Data-Memory Shortage Management," MPRA Paper 9145, University Library of Munich, Germany, revised 2007.
    3. Rodolphe Buda, 2008. "Two Dimensional Aggregation Procedure: An Alternative to the Matrix Algebraic Algorithm," Computational Economics, Springer;Society for Computational Economics, vol. 31(4), pages 397-408, May.
    4. Rodolphe Buda, 2015. "Data Checking and Econometric Software Development: A Technique of Traceability by Fictive Data Encoding," Computational Economics, Springer;Society for Computational Economics, vol. 46(2), pages 325-357, August.

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    JEL classification:

    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • C88 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Other Computer Software
    • C5 - Mathematical and Quantitative Methods - - Econometric Modeling
    • C87 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Econometric Software
    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General
    • B41 - Schools of Economic Thought and Methodology - - Economic Methodology - - - Economic Methodology
    • C43 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Index Numbers and Aggregation
    • C65 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Miscellaneous Mathematical Tools

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