IDEAS home Printed from https://ideas.repec.org/p/ems/eureir/1593.html
   My bibliography  Save this paper

Seasonal adjustment and the business cycle in unemployment

Author

Listed:
  • Franses, Ph.H.B.F.
  • de Bruin, P.

Abstract

Several recent studies show that seasonal variation and cyclical variation in unemployment are correlated. A common finding is that seasonality tends to differ across the business cycle stages of recessions and expansions. Since seasonal adjustment methods assume that the two sources of variation can somehow be separated, the present study examines the impact of seasonal adjustment on the analysis of cyclical patterns. Seasonally adjusted quarterly unemployment data for 5 G-7 countries are modeled by a Smooth Transition Autoregression [STAR] while the corresponding unadjusted data are modeled by a so-called Seasonal STAR [SEASTAR]. A comparison of the implied estimated peaks and troughs shows that there is substantial agreement on the business cycle chronologies, albeit that for seasonally adjusted data recessionary periods tend to last longer.

Suggested Citation

  • Franses, Ph.H.B.F. & de Bruin, P., 1999. "Seasonal adjustment and the business cycle in unemployment," Econometric Institute Research Papers EI 9923-/A, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    • Handle: RePEc:ems:eureir:1593
    as

    Download full text from publisher

    File URL: https://repub.eur.nl/pub/1593/feweco19990603115820.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. H. J. A. Schouten, 1982. "Measuring pairwise interobserver agreement when all subjects are judged by the same observers," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 36(2), pages 45-61, June.
    2. Canova, Fabio & Ghysels, Eric, 1994. "Changes in seasonal patterns : Are they cyclical?," Journal of Economic Dynamics and Control, Elsevier, vol. 18(6), pages 1143-1171, November.
    3. Jeffrey A. Miron, 1996. "The Economics of Seasonal Cycles," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262133237, April.
    4. Ooms, Marius & Franses, Philip Hans, 1997. "On Periodic Correlations between Estimated Seasonal and Nonseasonal Components in German and U.S. Unemployment," Journal of Business & Economic Statistics, American Statistical Association, vol. 15(4), pages 470-481, October.
    5. 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.
    6. Granger, Clive W. J. & Terasvirta, Timo, 1993. "Modelling Non-Linear Economic Relationships," OUP Catalogue, Oxford University Press, number 9780198773207.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Siem Jan Koopman & Kai Ming Lee, 2009. "Seasonality with trend and cycle interactions in unobserved components models," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 58(4), pages 427-448, September.
    2. He, Changli & Kang, Jian & Teräsvirta, Timo & Zhang, Shuhua, 2019. "The shifting seasonal mean autoregressive model and seasonality in the Central England monthly temperature series, 1772–2016," Econometrics and Statistics, Elsevier, vol. 12(C), pages 1-24.
    3. Ghassen El Montasser, 2015. "The Seasonal KPSS Test: Examining Possible Applications with Monthly Data and Additional Deterministic Terms," Econometrics, MDPI, vol. 3(2), pages 1-16, May.
    4. Dalibor Stevanovic & Stéphane Surprenant & Rachidi Kotchoni, 2019. "Identification des points de retournement du cycle économique au Canada," CIRANO Project Reports 2019rp-05, CIRANO.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Dick van Dijk 1 & Birgit Strikholm & Timo Teräsvirta, 2003. "The effects of institutional and technological change and business cycle fluctuations on seasonal patterns in quarterly industrial production series," Econometrics Journal, Royal Economic Society, vol. 6(1), pages 79-98, June.
    2. Ahdi Ajmi & Adnen Ben Nasr & Mohamed Boutahar, 2008. "Seasonal Nonlinear Long Memory Model for the US Inflation Rates," Computational Economics, Springer;Society for Computational Economics, vol. 31(3), pages 243-254, April.
    3. Pami Dua & Lokendra Kumawat, 2005. "Modelling and Forecasting Seasonality in Indian Macroeconomic Time Series," Working papers 136, Centre for Development Economics, Delhi School of Economics.
    4. Matas-Mir, Antonio & Osborn, Denise R., 2004. "Does seasonality change over the business cycle? An investigation using monthly industrial production series," European Economic Review, Elsevier, vol. 48(6), pages 1309-1332, December.
    5. Emara, Noha & Ma, Jinpeng, 2019. "An Analysis of the Seasonal Cycle and the Business Cycle," MPRA Paper 99310, University Library of Munich, Germany.
    6. Dalibor Stevanovic & Stéphane Surprenant & Rachidi Kotchoni, 2019. "Identification des points de retournement du cycle économique au Canada," CIRANO Project Reports 2019rp-05, CIRANO.
    7. Siem Jan Koopman & Marius Ooms & Irma Hindrayanto, 2009. "Periodic Unobserved Cycles in Seasonal Time Series with an Application to US Unemployment," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 71(5), pages 683-713, October.
    8. Siem Jan Koopman & Philip Hans Franses, 2002. "Constructing Seasonally Adjusted Data with Time‐varying Confidence Intervals," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 64(5), pages 509-526, December.
    9. 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.
    10. Ghassen El Montasser, 2015. "The Seasonal KPSS Test: Examining Possible Applications with Monthly Data and Additional Deterministic Terms," Econometrics, MDPI, vol. 3(2), pages 1-16, May.
    11. 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.
    12. Ghysels, Éric, 1994. "L’analyse économétrique et la saisonnalité," L'Actualité Economique, Société Canadienne de Science Economique, vol. 70(1), pages 43-62, mars.
    13. Franses,Philip Hans & Dijk,Dick van & Opschoor,Anne, 2014. "Time Series Models for Business and Economic Forecasting," Cambridge Books, Cambridge University Press, number 9780521520911, October.
    14. 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.
    15. Khémiri, Wafa & Noubbigh, Hédi, 2020. "Size-threshold effect in debt-firm performance nexus in the sub-Saharan region: A Panel Smooth Transition Regression approach," The Quarterly Review of Economics and Finance, Elsevier, vol. 76(C), pages 335-344.
    16. Alex Cukierman & Anton Muscatelli, 2001. "Do Central Banks have Precautionary Demands for Expansions and for Price Stability?," Working Papers 2002_4, Business School - Economics, University of Glasgow, revised Mar 2002.
    17. Anton Muscatelli & Patrizio Tirelli & Carmine Trecroci, 2001. "Monetary and Fiscal Policy Interactions over the Cycle: Some Empirical Evidence," Working Papers 2002_13, Business School - Economics, University of Glasgow, revised Oct 2002.
    18. repec:wyi:journl:002087 is not listed on IDEAS
    19. Mohamed CHIKHI & Claude DIEBOLT, 2022. "Testing the weak form efficiency of the French ETF market with the LSTAR-ANLSTGARCH approach using a semiparametric estimation," Eastern Journal of European Studies, Centre for European Studies, Alexandru Ioan Cuza University, vol. 13, pages 228-253, June.
    20. Magdalena Osińska & Tadeusz Kufel & Marcin Błażejowski & Paweł Kufel, 2020. "Modeling mechanism of economic growth using threshold autoregression models," Empirical Economics, Springer, vol. 58(3), pages 1381-1430, March.
    21. Ko Munakata & Takeshi Shinohara & Shigenori Shiratsuka & Nao Sudo & Tsutomu Watanabe, 2023. "On the Source of Seasonality in Price Changes: The Role of Seasonality in Menu Costs," Keio-IES Discussion Paper Series 2023-016, Institute for Economics Studies, Keio University.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:ems:eureir:1593. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: RePub (email available below). General contact details of provider: https://edirc.repec.org/data/feeurnl.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.