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Retour vers le futur. Une analyse rétrospective des prévisions de MOSAÏQUE

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  • Alexandre Mathis
  • Andrew Brociner

Abstract

[fre] L'utilisation, pendant près de dix ans, du modèle trimestriel du département d'économétrie de l'OFCE permet de faire une rétrospective des erreurs de prévisions passées. Il s'agit, par une analyse statistique des erreurs, d'essayer d'en décrire les principales caractéristiques. Les erreurs sont-elles systématiques, biaisées ou encore expliquées par les erreurs sur d'autres variables, exogènes notamment. A quel horizon prévoit-on le mieux ? Les prévisions faites à l'aide d'un modèle économétrique surclassent-elles celles produites par un modèle naïf ? Il apparaît que la qualité des prévisions s'améliore fortement lorsque l'horizon de prévision se rapproche. Pour l'horizon de prévision le plus court, quelques variables sont systématiquement sous- estimées ou sur-estimées. Les variables que l'on prévoit le plus mal le sont aussi par tous les autres prévisionnistes. Cette étude montre également que les erreurs sur l'environnement international affectent uniquement les prévisions des horizons les plus éloignés et ceci pour un nombre restreint de variables. [eng] Back to the Future : an analysis of the forecasts errors of the MOSAÏQUE model Alexandre Mathis, Andrew Brociner This study analyzes past errors of the quarterly model of the Econometrics Department of the OFCE. We conduct a statistical analysis of errors to describe its principal features. Are the errors biased, systematic, or explained by other errors, especially of exogenous variables ? For which time horizons do we forecast best ? Dees the model perform better than a forecast made by a simple model ? These are the questions we pose and try to answer. We find that the quality of the forecast improves with the shortening of the time horizon. In the shortest time horizon, some variables systematically underestimate or over-estimate the actual values. The variables which are the most difficult to predict are the ones other forecasters also find difficult to predict. We

(This abstract was borrowed from another version of this item.)

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Bibliographic Info

Article provided by Presses de Sciences-Po in its journal Revue de l'OFCE.

Volume (Year): n° 49 (1994)
Issue (Month): 2 ()
Pages: 207-228

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Handle: RePEc:cai:reofsp:reof_p1994_49n1_0207

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Web page: http://www.cairn.info/revue-de-l-ofce.htm

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