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Seasonal Unit Roots in Aggregate U.S. Data

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  • J. Joseph Beaulieu
  • Jeffrey A. Miron

Abstract

In this paper we provide evidence on the presence of seasonal unit roots in aggregate U.S. data. The analysis is conducted using the approach developed by Hyllebcrg, Engle, Granger and Yoo (1990). We first derive the mechanics and asyrnptotics of the HEGY procedure for monthly data and use Monte Carlo methods to compute the finite sample critical values of the associated test statistics. We then apply quarterly and monthly HEGY procedures to aggregate U.S. data. The data reject the presence of unit roots at most seasonal frequencies in a large fraction of the series considered.

Suggested Citation

  • 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.
    • Handle: RePEc:nbr:nberte:0126
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    1. Beaulieu, J. Joseph & Miron, Jeffrey A., 1991. "The seasonal cycle in U.S. manufacturing," Economics Letters, Elsevier, vol. 37(2), pages 115-118, October.
    2. 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.
    3. Danny Quah & Jeffrey M. Wooldridge, 1988. "A Common Error in the Treatment of Trending Time Series," Working papers 483, Massachusetts Institute of Technology (MIT), Department of Economics.
    4. Osborn, Denise R., 1990. "A survey of seasonality in UK macroeconomic variables," International Journal of Forecasting, Elsevier, vol. 6(3), pages 327-336, October.
    5. Peter C.B. Phillips, 1986. "Weak Convergence to the Matrix Stochastic Integral BdB," Cowles Foundation Discussion Papers 796, Cowles Foundation for Research in Economics, Yale University.
    6. Beaulieu, J Joseph & Miron, Jeffrey A, 1992. "A Cross Country Comparison of Seasonal Cycles and Business Cycles," Economic Journal, Royal Economic Society, vol. 102(413), pages 772-788, July.
    7. Franses, P. H., 1990. "Testing For Seasonal Unit Roots In Monthly Data," Econometric Institute Archives 272393, Erasmus University Rotterdam.
    8. Park, Joon Y. & Phillips, Peter C.B., 1988. "Statistical Inference in Regressions with Integrated Processes: Part 1," Econometric Theory, Cambridge University Press, vol. 4(03), pages 468-497, December.
    9. Bhargava, Alok, 1990. "An Econometric Analysis of the U.S. Postwar G.N.P," Journal of Population Economics, Springer;European Society for Population Economics, vol. 3(2), pages 147-156, August.
    10. Phillips, P C B, 1987. "Time Series Regression with a Unit Root," Econometrica, Econometric Society, vol. 55(2), pages 277-301, March.
    11. Granger, C. W. J. & Newbold, Paul, 1986. "Forecasting Economic Time Series," Elsevier Monographs, Elsevier, edition 2, number 9780122951831 edited by Shell, Karl, August.
    12. Ghysels, Eric & Lee, Hahn S. & Noh, Jaesum, 1994. "Testing for unit roots in seasonal time series : Some theoretical extensions and a Monte Carlo investigation," Journal of Econometrics, Elsevier, vol. 62(2), pages 415-442, June.
    13. Phillips, P C B, 1987. "Time Series Regression with a Unit Root," Econometrica, Econometric Society, vol. 55(2), pages 277-301, March.
    14. Barsky, Robert B & Miron, Jeffrey A, 1989. "The Seasonal Cycle and the Business Cycle," Journal of Political Economy, University of Chicago Press, vol. 97(3), pages 503-534, June.
    15. Schwert, G. William, 1987. "Effects of model specification on tests for unit roots in macroeconomic data," Journal of Monetary Economics, Elsevier, vol. 20(1), pages 73-103, July.
    16. Engle, R. F. & Granger, C. W. J. & Hallman, J. J., 1989. "Merging short-and long-run forecasts : An application of seasonal cointegration to monthly electricity sales forecasting," Journal of Econometrics, Elsevier, vol. 40(1), pages 45-62, January.
    17. Ghysels, E., 1987. "Unit Root Tests and the Statistical Pitfalls of Seasonal Adjustment: the Case of U.S. Post-War Real Gnp," Cahiers de recherche 8723, Universite de Montreal, Departement de sciences economiques.
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