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Estimating TFP in the Presence of Outliers and Leverage Points: An Examination of the KLEMS Dataset

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  • Macdonald, Ryan

Abstract

This paper examines the effect of aberrant observations in the Capital, Labour, Energy, Materials and Services (KLEMS) database and a method for dealing with them. The level of disaggregation, data construction and economic shocks all potentially lead to aberrant observations that can influence estimates and inference if care is not exercised. Commonly applied pre-tests, such as the augmented Dickey-Fuller and the Kwaitkowski, Phillips, Schmidt and Shin tests, need to be used with caution in this environment because they are sensitive to unusual data points. Moreover, widely known methods for generating statistical estimates, such as Ordinary Least Squares, may not work well when confronted with aberrant observations. To address this, a robust method for estimating statistical relationships is illustrated.

Suggested Citation

  • Macdonald, Ryan, 2007. "Estimating TFP in the Presence of Outliers and Leverage Points: An Examination of the KLEMS Dataset," Economic Analysis (EA) Research Paper Series 2007047e, Statistics Canada, Analytical Studies Branch.
  • Handle: RePEc:stc:stcp5e:2007047e
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    References listed on IDEAS

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    Cited by:

    1. Wulong Gu, 2012. "Estimating Capital Input for Measuring Business Sector Multifactor Productivity Growth in Canada: Response to Diewert and Yu," International Productivity Monitor, Centre for the Study of Living Standards, vol. 24, pages 49-62, Fall.
    2. Macdonald, Ryan, 2008. "An Examination of Public Capital's Role in Production," Economic Analysis (EA) Research Paper Series 2008050e, Statistics Canada, Analytical Studies Branch.

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    Keywords

    Data analysis; Economic accounts; Productivity accounts; Statistical methods; Time series;

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