Advanced Search
MyIDEAS: Login to save this paper or follow this series

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

Contents:

Author Info

  • 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.

Download Info

If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
File URL: http://www5.statcan.gc.ca/olc-cel/olc.action?ObjId=11F0027M2007047&ObjType=46&lang=en&limit=0
Download Restriction: no

Bibliographic Info

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

as in new window
Length:
Date of creation: 05 Dec 2007
Date of revision:
Handle: RePEc:stc:stcp5e:2007047e

Contact details of provider:
Postal: Tunney's Pasture, Ottawa, Ontario, K1A 0T6
Web page: http://www.statcan.gc.ca
More information through EDIRC

Related research

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

This paper has been announced in the following NEP Reports:

References

References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
as in new window
  1. Franses,Philip Hans, 1998. "Time Series Models for Business and Economic Forecasting," Cambridge Books, Cambridge University Press, number 9780521586412, Fall.
  2. Perron, Pierre, 1989. "The Great Crash, the Oil Price Shock, and the Unit Root Hypothesis," Econometrica, Econometric Society, vol. 57(6), pages 1361-1401, November.
  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.
  4. Kaddour Hadri, 2000. "Testing for stationarity in heterogeneous panel data," Econometrics Journal, Royal Economic Society, vol. 3(2), pages 148-161.
  5. Denis Kwiatkowski & Peter C.B. Phillips & Peter Schmidt, 1991. "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?," Cowles Foundation Discussion Papers 979, Cowles Foundation for Research in Economics, Yale University.
  6. Baldwin, John R. & Harchaoui, Tarek, 2002. "Productivity Growth in Canada," Productivity Growth in Canada, Statistics Canada, Economic Analysis, number stcb6e, December.
  7. Pena, Daniel, 1990. "Influential Observations in Time Series," Journal of Business & Economic Statistics, American Statistical Association, vol. 8(2), pages 235-41, April.
  8. 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.
  9. 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.
  10. 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.
  11. Maddala, G S & Wu, Shaowen, 1999. " A Comparative Study of Unit Root Tests with Panel Data and a New Simple Test," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 61(0), pages 631-52, Special I.
  12. 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.
  13. Granger, C. W. J. & Newbold, P., 1974. "Spurious regressions in econometrics," Journal of Econometrics, Elsevier, vol. 2(2), pages 111-120, July.
  14. 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.
  15. Sunil Sapra, 2003. "High-breakdown point estimation of some regression models," Applied Economics Letters, Taylor & Francis Journals, vol. 10(14), pages 875-878.
  16. Nathan S. Balke & Thomas B. Fomby, 1991. "Large shocks, small shocks, and economic fluctuations: outliers in macroeconomic times series," Research Paper 9101, Federal Reserve Bank of Dallas.
Full references (including those not matched with items on IDEAS)

Citations

Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
as in new window

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.

Lists

This item is not listed on Wikipedia, on a reading list or among the top items on IDEAS.

Statistics

Access and download statistics

Corrections

When requesting a correction, please mention this item's handle: RePEc:stc:stcp5e:2007047e. See general information about how to correct material in RePEc.

For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Mark Brown).

If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

If references are entirely missing, you can add them using this form.

If the full references list an item that is present in RePEc, but the system did not link to it, you can help with this form.

If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your profile, as there may be some citations waiting for confirmation.

Please note that corrections may take a couple of weeks to filter through the various RePEc services.