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

  • Macdonald, Ryan

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.

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Paper provided by Statistics Canada, Analytical Studies Branch in its series Economic Analysis (EA) Research Paper Series with number 2007047e.

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Date of creation: 05 Dec 2007
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Handle: RePEc:stc:stcp5e:2007047e
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  1. Nelson, Charles R. & Plosser, Charles I., 1982. "Trends and random walks in macroeconmic time series : Some evidence and implications," Journal of Monetary Economics, Elsevier, vol. 10(2), pages 139-162.
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  3. Im, Kyung So & Pesaran, M. Hashem & Shin, Yongcheol, 2003. "Testing for unit roots in heterogeneous panels," Journal of Econometrics, Elsevier, vol. 115(1), pages 53-74, July.
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  5. Kaddour Hadri, 2000. "Testing for stationarity in heterogeneous panel data," Econometrics Journal, Royal Economic Society, vol. 3(2), pages 148-161.
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  8. 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.
  9. 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.
  10. Gu, Wulong & Baldwin, John R., 2007. "Multifactor Productivity in Canada: An Evaluation of Alternative Methods of Estimating Capital Services," The Canadian Productivity Review 2007009e, Statistics Canada, Economic Analysis.
  11. Granger, C. W. J. & Newbold, P., 1974. "Spurious regressions in econometrics," Journal of Econometrics, Elsevier, vol. 2(2), pages 111-120, July.
  12. Baldwin, John R. & Harchaoui, Tarek, 2002. "Productivity Growth in Canada," Productivity Growth in Canada, Statistics Canada, Economic Analysis, number stcb6e, December.
  13. Balke, Nathan S & Fomby, Thomas B, 1994. "Large Shocks, Small Shocks, and Economic Fluctuations: Outliers in Macroeconomic Time Series," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 9(2), pages 181-200, April-Jun.
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  15. Kevin J. Stiroh & Dale W. Jorgenson, 2000. "U.S. Economic Growth at the Industry Level," American Economic Review, American Economic Association, vol. 90(2), pages 161-167, May.
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