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Estimation de la PTF en présence de points aberrants et de points leviers : examen de l'ensemble de données KLEMS

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  • Macdonald, Ryan

Abstract

Le présent document porte sur l'effet des observations atypiques présentes dans la base de données KLEMS (capital, travail, énergie, matières et services) et propose une méthode pour le contrer. Le niveau de désagrégation, la construction des données et les chocs économiques peuvent se traduire par des observations atypiques susceptibles d'influer sur les estimations et sur l'inférence si des précautions ne sont pas prises. Les prétests couramment utilisés, tels que les tests DFA (Dickey-Fuller amélioré) et KPSS (Kwaitkowski, Phillips, Schmidt et Shin), doivent être appliqués avec prudence dans ce contexte parce qu'ils sont sensibles aux points de données inhabituels. En outre, les méthodes les plus connues qui sont employées pour établir des estimations statistiques, comme la méthode des moindres carrés ordinaires, peuvent ne pas fonctionner correctement en présence d'observations atypiques. Afin de pallier ce problème, le document illustre une méthode robuste d'estimation des relations statistiques.

Suggested Citation

  • Macdonald, Ryan, 2007. "Estimation de la PTF en présence de points aberrants et de points leviers : examen de l'ensemble de données KLEMS," Série de documents de recherche sur l'analyse économique (AE) 2007047f, Statistics Canada, Direction des études analytiques.
    • Handle: RePEc:stc:stcp5f:2007047f
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    References listed on IDEAS

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