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Seasonal Unit Root Testing Based on the Temporal Aggregation of Seasonal Cycles

  • Gabriel Pons Rotger


    (Department of Economics, University of Aarhus, Denmark)

The effects of systematic sampling and temporal aggregation on the seasonal cycle model (see Miron, 1993) and the seasonally integrated process (see Hylleberg et al., 1990) are discussed. The temporal aggregation theory is used to improve the sequential test for monthly seasonal unit roots of Rodrigues and Franses (2003). It is shown by simulation that the monthly sequential test has better finite sample properties than the BM test (see Beaulieu and Miron, 1993). The new test is applied to monthly US Industrial Production and, contrary to the BM test, rejects the presence of any seasonal unit root.

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Paper provided by School of Economics and Management, University of Aarhus in its series Economics Working Papers with number 2004-1.

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Length: 26
Date of creation: 02 Apr 2004
Date of revision:
Handle: RePEc:aah:aarhec:2004-1
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  1. Granger, C.W.J. & Siklos, P.L., 1993. "Systematic Sampling, Temporal Aggregation, Seasonal Adjustment, and Cointegration: Theory and Evidence," Working Papers 93001, Wilfrid Laurier University, Department of Economics.
  2. Caner, Mehmet, 1998. "A Locally Optimal Seaosnal Unit-Root Test," Journal of Business & Economic Statistics, American Statistical Association, vol. 16(3), pages 349-56, July.
  3. Franses, Philip Hans, 1994. "A multivariate approach to modeling univariate seasonal time series," Journal of Econometrics, Elsevier, vol. 63(1), pages 133-151, July.
  4. Taylor, A M Robert, 2003. "Robust Stationarity Tests in Seasonal Time Series Processes," Journal of Business & Economic Statistics, American Statistical Association, vol. 21(1), pages 156-63, January.
  5. Hansen, Bruce E., 1992. "Testing for parameter instability in linear models," Journal of Policy Modeling, Elsevier, vol. 14(4), pages 517-533, August.
  6. Franses, Philip Hans, 1996. "Periodicity and Stochastic Trends in Economic Time Series," OUP Catalogue, Oxford University Press, number 9780198774549, July.
  7. J. Joseph Beaulieu & Jeffrey A. Miron, 1992. "Seasonal Unit Roots in Aggregate U.S. Data," NBER Technical Working Papers 0126, National Bureau of Economic Research, Inc.
  8. Philip Hans Franses & Timothy J. Vogelsang, 1998. "On Seasonal Cycles, Unit Roots, And Mean Shifts," The Review of Economics and Statistics, MIT Press, vol. 80(2), pages 231-240, May.
  9. H. Niemi, 1984. "The invertibility of sampled and aggregated ARMA models," Metrika, Springer, vol. 31(1), pages 43-50, December.
  10. Paulo Rodrigues & Philip Hans Franses, 2005. "A sequential approach to testing seasonal unit roots in high frequency data," Journal of Applied Statistics, Taylor & Francis Journals, vol. 32(6), pages 555-569.
  11. Jeffrey A. Miron, 1996. "The Economics of Seasonal Cycles," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262133237, June.
  12. Hylleberg, S. & Engle, R. F. & Granger, C. W. J. & Yoo, B. S., 1990. "Seasonal integration and cointegration," Journal of Econometrics, Elsevier, vol. 44(1-2), pages 215-238.
  13. Philip Hans Franses & Bart Hobijn, 1997. "Critical values for unit root tests in seasonal time series," Journal of Applied Statistics, Taylor & Francis Journals, vol. 24(1), pages 25-48.
  14. Hannan, E J & Terrell, R D & Tuckwell, N E, 1970. "The Seasonal Adjustment of Economic Time Series," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 11(1), pages 24-52, February.
  15. Franses, Philip Hans, 1991. "Moving average filters and unit roots," Economics Letters, Elsevier, vol. 37(4), pages 399-403, December.
  16. Paulo Rodrigues & Denise Osborn, 1999. "Performance of seasonal unit root tests for monthly data," Journal of Applied Statistics, Taylor & Francis Journals, vol. 26(8), pages 985-1004.
  17. Canova, Fabio & Hansen, Bruce E, 1995. "Are Seasonal Patterns Constant over Time? A Test for Seasonal Stability," Journal of Business & Economic Statistics, American Statistical Association, vol. 13(3), pages 237-52, July.
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