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Seasonal Adjustment and the Detection of Business Cycle Phases

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  • A Matas-Mir
  • D R Osborn
Abstract
To date, there has been little investigation of the impact of seasonal adjustment on the detection of business cycle expansion and recession regimes. We study this question both analytically and through Monte Carlo simulations. Analytically, we view the occurrence of a single business cycle regime as a structural break that is later reversed, showing that the effect of the linear symmetric X-11 filter differs with the duration of the regime. Through the use of Markov switching models for regime identification, the simulation analysis shows that seasonal adjustment has desirable properties in clarifying the true regime when this is well underway, but it distorts regime inference around turning points, with this being especially marked after the end of recessions and when the one-sided X-11 filter is employed. JEL Classification: E32, C22, C80
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  • A Matas-Mir & D R Osborn, 2003. "Seasonal Adjustment and the Detection of Business Cycle Phases," Economics Discussion Paper Series 0304, Economics, The University of Manchester.
    • Handle: RePEc:man:sespap:0304
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    1. Ghysels, Eric & Perron, Pierre, 1996. "The effect of linear filters on dynamic time series with structural change," Journal of Econometrics, Elsevier, vol. 70(1), pages 69-97, January.
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    4. Findley, David F, et al, 1998. "New Capabilities and Methods of the X-12-ARIMA Seasonal-Adjustment Program: Reply," Journal of Business & Economic Statistics, American Statistical Association, vol. 16(2), pages 169-177, April.
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    6. Bell, William R & Hillmer, Steven C, 1984. "Issues Involved with the Seasonal Adjustment of Time Series: Reply," Journal of Business & Economic Statistics, American Statistical Association, vol. 2(4), pages 343-349, October.
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    11. Garcia, Rene, 1998. "Asymptotic Null Distribution of the Likelihood Ratio Test in Markov Switching Models," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 39(3), pages 763-788, August.
    12. Krane, Spencer & Wascher, William, 1999. "The cyclical sensitivity of seasonality in U.S. employment," Journal of Monetary Economics, Elsevier, vol. 44(3), pages 523-553, December.
    13. Franses, Philip Hans & Paap, Richard, 1999. "Does Seasonality Influence the Dating of Business Cycle Turning Points?," Journal of Macroeconomics, Elsevier, vol. 21(1), pages 79-92, January.
    14. Christiano, Lawrence J. & Todd, Richard M., 2002. "The conventional treatment of seasonality in business cycle analysis: does it create distortions?," Journal of Monetary Economics, Elsevier, vol. 49(2), pages 335-364, March.
    15. Findley, David F, et al, 1998. "New Capabilities and Methods of the X-12-ARIMA Seasonal-Adjustment Program," Journal of Business & Economic Statistics, American Statistical Association, vol. 16(2), pages 127-152, April.
    16. Ghysels,Eric & Osborn,Denise R., 2001. "The Econometric Analysis of Seasonal Time Series," Cambridge Books, Cambridge University Press, number 9780521565882.
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    Cited by:

    1. Giovanni Lombardo & Peter McAdam, 2010. "Incorporating financial frictions into new-generation macro models," Research Bulletin, European Central Bank, vol. 9, pages 13-16.
    2. Jani Beko & Timotej Jagric, 2009. "Demand models for direct mail and periodicals delivery services: results for a transition economy," Applied Economics, Taylor & Francis Journals, vol. 43(9), pages 1125-1138.
    3. Antonio Matas-Mir & Denise R. Osborn & Marco J. Lombardi, 2008. "The effect of seasonal adjustment on the properties of business cycle regimes," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 23(2), pages 257-278.
    4. D R Osborn & A Matas-Mir, 2003. "The Extent of Seasonal/Business Cycle Interactions in European Industrial Production," Centre for Growth and Business Cycle Research Discussion Paper Series 38, Economics, The University of Manchester.
    5. Fiorella De Fiore & Oreste Tristani, 2010. "Financial conditions and monetary policy," Research Bulletin, European Central Bank, vol. 9, pages 10-12.
    6. Crowley, Patrick M. & Lee, Jim, 2005. "Decomposing the co-movement of the business cycle: a time-frequency analysis of growth cycles in the euro area," Bank of Finland Research Discussion Papers 12/2005, Bank of Finland.
    7. Cornelia Holthausen & Huw Pill, 2010. "The forgotten markets: How understanding money markets helps us to understand the financial crisis," Research Bulletin, European Central Bank, vol. 9, pages 2-5.
    8. Crowley, Patrick M. & Lee, Jim, 2005. "Decomposing the co-movement of the business cycle : a time-frequency analysis of growth cycles in the euro area," Research Discussion Papers 12/2005, Bank of Finland.
    9. Lacroix, R., 2008. "Analyse conjoncturelle de données brutes et estimation de cycles Partie 2 : mise en oeuvre empirique," Working papers 210, Banque de France.
    10. Angela Maddaloni & José-Luis Peydró, 2010. "Bank lending standards and the origins and implications of the current banking crisis," Research Bulletin, European Central Bank, vol. 9, pages 6-9.
    11. Fok, D. & Franses, Ph.H.B.F. & Paap, R., 2005. "Performance of Seasonal Adjustment Procedures: Simulation and Empirical Results," Econometric Institute Research Papers EI 2005-30, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    12. repec:zbw:bofrdp:2005_012 is not listed on IDEAS
    13. Tomas del Barrio Castro & Denise R. Osborn, 2006. "A Random Walk through Seasonal Adjustment: Noninvertible Moving Averages and Unit Root Tests," Economics Discussion Paper Series 0612, Economics, The University of Manchester.

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    More about this item

    JEL classification:

    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C80 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - General

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