Estimating TFP in the Presence of Outliers and Leverage Points: An Examination of the KLEMS Dataset
AbstractThis 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 InfoIf 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.
Bibliographic InfoPaper provided by Statistics Canada, Analytical Studies Branch in its series Economic Analysis (EA) Research Paper Series with number 2007047e.
Date of creation: 05 Dec 2007
Date of revision:
Statistical methods; Economic accounts; Time series; Data analysis; Productivity accounts;
This paper has been announced in the following NEP Reports:
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.:
- Kaddour Hadri, 1999.
"Testing For Stationarity In Heterogeneous Panel Data,"
1999_04, University of Liverpool Management School.
- Kaddour Hadri, 2000. "Testing for stationarity in heterogeneous panel data," Econometrics Journal, Royal Economic Society, vol. 3(2), pages 148-161.
- Perron, Pierre, 1989.
"The Great Crash, the Oil Price Shock, and the Unit Root Hypothesis,"
Econometric Society, vol. 57(6), pages 1361-1401, November.
- Perron, P, 1988. "The Great Crash, The Oil Price Shock And The Unit Root Hypothesis," Papers 338, Princeton, Department of Economics - Econometric Research Program.
- 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.
- 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.
- Baldwin, John R. Gu, Wulong, 2007. "Multifactor Productivity in Canada: An Evaluation of Alternative Methods of Estimating Capital Services," The Canadian Productivity Review 2007009e, Statistics Canada, Economic Analysis Division.
- Franses,Philip Hans, 1998. "Time Series Models for Business and Economic Forecasting," Cambridge Books, Cambridge University Press, number 9780521586412, November.
- 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.
- Kwiatkowski, D. & Phillips, P.C.B. & Schmidt, P., 1990. "Testing the Null Hypothesis of Stationarity Against the Alternative of Unit Root : How Sure are we that Economic Time Series have a Unit Root?," Papers 8905, Michigan State - Econometrics and Economic Theory.
- 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.
- 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.
- Pasaran, M.H. & Im, K.S. & Shin, Y., 1995.
"Testing for Unit Roots in Heterogeneous Panels,"
Cambridge Working Papers in Economics
9526, Faculty of Economics, University of Cambridge.
- 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.
- Baldwin, John R. Harchaoui, Tarek, 2002. "Productivity Growth in Canada," Productivity Growth in Canada, Statistics Canada, Economic Analysis Division, number stcb6e, May.
- 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.
- Granger, C. W. J. & Newbold, P., 1974. "Spurious regressions in econometrics," Journal of Econometrics, Elsevier, vol. 2(2), pages 111-120, July.
- 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.
- Sunil Sapra, 2003. "High-breakdown point estimation of some regression models," Applied Economics Letters, Taylor & Francis Journals, vol. 10(14), pages 875-878.
- 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.
- 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.
- Macdonald, Ryan, 2008. "An Examination of Public Capital's Role in Production," Economic Analysis (EA) Research Paper Series 2008050e, Statistics Canada, Analytical Studies Branch.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Mark Brown).
If references are entirely missing, you can add them using this form.