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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

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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.

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Paper provided by Statistics Canada, Direction des études analytiques in its series Série de documents de recherche sur l'analyse économique (AE) with number 2007047f.

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Date of creation: 05 Dec 2007
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Handle: RePEc:stc:stcp5f:2007047f

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Related research
Keywords: Méthodes statistiques; Comptes économiques; Séries chronologiques; Analyse des données; Comptes de la productivité;

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  1. Hamilton, James D, 1989. "A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle," Econometrica, Econometric Society, vol. 57(2), pages 357-84, March. [Downloadable!] (restricted)
  2. Kaddour Hadri, 1999. "Testing For Stationarity In Heterogeneous Panel Data," Research Papers 1999_04, University of Liverpool Management School.
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  3. Galeano, Pedro & Pena, Daniel & Tsay, Ruey S., 2006. "Outlier Detection in Multivariate Time Series by Projection Pursuit," Journal of the American Statistical Association, American Statistical Association, vol. 101, pages 654-669, June. [Downloadable!] (restricted)
  4. Dale W. Jorgenson & Kevin J. Stiroh, 2000. "U.S. Economic Growth at the Industry Level," American Economic Review, American Economic Association, vol. 90(2), pages 161-167, May. [Downloadable!] (restricted)
  5. Sunil K. Sapra, 2003. "High-breakdown point estimation of some regression models," Applied Economics Letters, Taylor and Francis Journals, vol. 10(14), pages 875-878, November. [Downloadable!] (restricted)
  6. Kwiatkowski, Denis & Phillips, Peter C. B. & Schmidt, Peter & Shin, Yongcheol, 1992. "Testing the null hypothesis of stationarity against the alternative of a unit root : How sure are we that economic time series have a unit root?," Journal of Econometrics, Elsevier, vol. 54(1-3), pages 159-178. [Downloadable!] (restricted)
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  7. Baldwin, John R. & Gu, Wulong, 2007. "La productivité multifactorielle au Canada : une évaluation de diverses méthodes d'estimation des services de capital," La revue canadienne de productivité 2007009f, Statistics Canada, Division de l'analyse économique. [Downloadable!]
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