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Type I Spurious Regression in Econometrics

In applied econometrics researchers often infer the relation among nonstationary time series by regression of their differences. The aim of this paper is to show that in some circumstances regression of differenced time series tends to reject the relation among their levels. This phenomenon is known as type I spurious regression. Time series are dynamic processes, and the ignored system dynamics will become the systematic errors in regression equations. Differencing does not preserve the underlying relation among time series in regression due to systematic errors. This paper will outline how regression of differenced time series tends to reject the relation between their levels, and so potentially to incur type I spurious regression.

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File URL: http://www.finance.uts.edu.au/research/wpapers/wp114.pdf
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Paper provided by Finance Discipline Group, UTS Business School, University of Technology, Sydney in its series Working Paper Series with number 114.

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Date of creation: 01 Apr 2002
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Handle: RePEc:uts:wpaper:114
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  1. Granger, C. W. J. & Newbold, P., 1974. "Spurious regressions in econometrics," Journal of Econometrics, Elsevier, vol. 2(2), pages 111-120, July.
  2. 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.
  3. Carl Chiarella & S. Gao, 2002. "Solving the Price-Earnings Puzzle," Working Paper Series 116, Finance Discipline Group, UTS Business School, University of Technology, Sydney.
  4. Harvey, Andrew, 1997. "Trends, Cycles and Autoregressions," Economic Journal, Royal Economic Society, vol. 107(440), pages 192-201, January.
  5. Engle, Robert F & Granger, Clive W J, 1987. "Co-integration and Error Correction: Representation, Estimation, and Testing," Econometrica, Econometric Society, vol. 55(2), pages 251-76, March.
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