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Abstract

I analyse the "spurious regression problem" from the Classical Regression Model (CRM) point of view. Simulations show that the autocorrelation corrections suggested by the CRM, e.g., feasible generalised least squares, solve the problem. Estimators are unbiased, consistent, efficient and deliver correctly sized tests. Conversely, first differencing the data results in inefficiencies when the autoregressive parameter in the error process is less than one. I offer practical recommendations for handling cases suspected to be in the "spurious regression" class.

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File URL: http://www.accessecon.com/Pubs/EB/2011/Volume31/EB-11-V31-I1-P88.pdf
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Bibliographic Info

Article provided by AccessEcon in its journal Economics Bulletin.

Volume (Year): 31 (2011)
Issue (Month): 1 ()
Pages: 925-937

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Handle: RePEc:ebl:ecbull:eb-10-00191

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Related research

Keywords: spurious regression; classical regression model; generalised least squares; autocorrelation corrections;

Find related papers by JEL classification:

• C4 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics
• C2 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables

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1. McCallum, Bennett T., 2010. "Is the spurious regression problem spurious?," Economics Letters, Elsevier, vol. 107(3), pages 321-323, June.
   
   • Bennett T. McCallum, 2010. "Is the Spurious Regression Problem Spurious?," NBER Working Papers 15690, National Bureau of Economic Research, Inc.
2. Phillips, P.C.B., 1986. "Understanding spurious regressions in econometrics," Journal of Econometrics, Elsevier, vol. 33(3), pages 311-340, December.
   
   • Peter C.B. Phillips, 1985. "Understanding Spurious Regressions in Econometrics," Cowles Foundation Discussion Papers 757, Cowles Foundation for Research in Economics, Yale University.
3. Sun, Yixiao, 2004. "A CONVERGENT t-STATISTIC IN SPURIOUS REGRESSIONS," Econometric Theory, Cambridge University Press, vol. 20(05), pages 943-962, October.
   
   • Sun, Yixiao, 2003. "A Convergent t-statistic in Spurious Regressions," University of California at San Diego, Economics Working Paper Series qt150457tv, Department of Economics, UC San Diego.
4. Granger, C. W. J. & Newbold, P., 1974. "Spurious regressions in econometrics," Journal of Econometrics, Elsevier, vol. 2(2), pages 111-120, July.
5. Wooldridge, Jeffrey M., 1991. "On the application of robust, regression- based diagnostics to models of conditional means and conditional variances," Journal of Econometrics, Elsevier, vol. 47(1), pages 5-46, January.
6. 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.
   
   • 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.
   • 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.

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