IDEAS home Printed from https://ideas.repec.org/a/ces/ifosdt/v68y2015i05p27-32.html
   My bibliography  Save this article

ifo Konjunkturampel revisited

Author

Listed:
  • Wolfgang Nierhaus
  • Klaus Abberger

Abstract

Mit einem Markov-Switching-Modell können die monatlichen Veränderungen des ifo Geschäftsklimas in Wahrscheinlichkeiten für die beiden konjunkturellen Regime »Expansion« bzw. «Kontraktion« umgesetzt werden. Diese Wahrscheinlichkeiten – abgebildet in der ifo Konjunkturampel – liefern für die Früherkennung konjunktureller Wendepunkte wichtige Informationen. Die Umstellung der Saisonbereinigung des ifo Geschäftsklimas auf das Census- X-13ARIMA-SEATSVerfahren machte auch eine Neuberechnung der ifo Konjunkturampel erforderlich. Der Beitrag präsentiert Methodik und Ergebnisse.

Suggested Citation

  • Wolfgang Nierhaus & Klaus Abberger, 2015. "ifo Konjunkturampel revisited," ifo Schnelldienst, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 68(05), pages 27-32, March.
  • Handle: RePEc:ces:ifosdt:v:68:y:2015:i:05:p:27-32
    as

    Download full text from publisher

    File URL: https://www.ifo.de/DocDL/ifosd_2015_05_4.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Klaus Abberger & Wolfgang Nierhaus, 2010. "Markov-Switching and the Ifo Business Climate: the Ifo Business Cycle Traffic Lights," OECD Journal: Journal of Business Cycle Measurement and Analysis, OECD Publishing, Centre for International Research on Economic Tendency Surveys, vol. 2010(2), pages 1-13.
    2. Klaus Abberger & Wolfgang Nierhaus, 2008. "Markov-Switching und ifo Geschäftsklima," ifo Schnelldienst, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 61(10), pages 25-30, May.
    3. Klaus Abberger & Wolfgang Nierhaus, 2011. "Die aktuelle Wirtschaftsentwicklung im Lichte der ifo Konjunkturampel," ifo Schnelldienst, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 64(22), pages 36-38, November.
    4. Wolfgang Nierhaus & Klaus Abberger, 2014. "Zur Prognose von konjunkturellen Wendepunkten: Dreimal-Regelversus Markov-Switching," ifo Schnelldienst, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 67(16), pages 21-25, August.
    5. Steffen Henzel, 2015. "Prognosekraft des ifo Konjunkturtests – Einfluss der neuen Saisonbereinigung mit X-13ARIMA-SEATS," ifo Schnelldienst, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 68(01), pages 59-63, January.
    6. Stefan Sauer & Klaus Wohlrabe, 2015. "Die Saisonbereinigung im ifo Konjunkturtest – Umstellung auf das X-13ARIMA-SEATS-Verfahren," ifo Schnelldienst, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 68(01), pages 32-42, January.
    7. Gerhard Bry & Charlotte Boschan, 1971. "Cyclical Analysis of Time Series: Selected Procedures and Computer Programs," NBER Books, National Bureau of Economic Research, Inc, number bry_71-1, June.
    8. Gerhard Bry & Charlotte Boschan, 1971. "Foreword to "Cyclical Analysis of Time Series: Selected Procedures and Computer Programs"," NBER Chapters, in: Cyclical Analysis of Time Series: Selected Procedures and Computer Programs, pages -1, National Bureau of Economic Research, Inc.
    9. Hamilton, James D, 1989. "A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle," Econometrica, Econometric Society, vol. 57(2), pages 357-384, March.
    10. Kai Carstensen & Wolfgang Nierhaus & Tim Oliver Berg & Christian Breuer & Christian Grimme & Steffen Henzel & Atanas Hristov & Nikolay Hristov & Michael Kleemann & Wolfgang Meister & Johanna Garnitz &, 2013. "ifo Konjunkturprognose 2013/2014: Günstige Perspektiven für die deutsche Konjunktur," ifo Schnelldienst, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 66(13), pages 17-64, July.
    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. Christian Glocker & Philipp Wegmueller, 2020. "Business cycle dating and forecasting with real-time Swiss GDP data," Empirical Economics, Springer, vol. 58(1), pages 73-105, January.
    2. Timo Wollmershäuser & Wolfgang Nierhaus & Nikolay Hristov & Dorine Boumans & Johanna Garnitz & Marcell Göttert & Christian Grimme & Stefan Lauterbacher & Robert Lehmann & Wolfgang Meister & Magnus Rei, 2016. "ifo Konjunkturprognose 2016–2018: Robuste deutsche Konjunktur vor einem Jahr ungewisser internationaler Wirtschaftspolitik," ifo Schnelldienst, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 69(24), pages 28-73, December.
    3. Robert Lehmann, 2023. "The Forecasting Power of the ifo Business Survey," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 19(1), pages 43-94, March.
    4. Stefan Sauer & Klaus Wohlrabe, 2020. "ifo Handbuch der Konjunkturumfragen," ifo Beiträge zur Wirtschaftsforschung, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, number 88.
    5. Wolfgang Nierhaus, 2017. "Wirtschaftskonjunktur 2016: Prognose und Wirklichkeit," ifo Schnelldienst, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 70(02), pages 72-78, January.

    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. Wolfgang Nierhaus & Timo Wollmershäuser, 2016. "ifo Konjunkturumfragen und Konjunkturanalyse: Band II," ifo Forschungsberichte, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, number 72, July.
    2. Stefan Sauer & Klaus Wohlrabe, 2020. "ifo Handbuch der Konjunkturumfragen," ifo Beiträge zur Wirtschaftsforschung, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, number 88.
    3. Mariam Camarero & María Dolores Gadea-Rivas & Ana Gómez-Loscos & Cecilio Tamarit, 2019. "External imbalances and recoveries," Working Papers 1912, Department of Applied Economics II, Universidad de Valencia.
    4. Ana Rodríguez-Santiago, 2019. "What has Changed After the Great Recession on the European Cyclical Patterns?," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 15(2), pages 121-146, December.
    5. Aastveit, Knut Are & Jore, Anne Sofie & Ravazzolo, Francesco, 2016. "Identification and real-time forecasting of Norwegian business cycles," International Journal of Forecasting, Elsevier, vol. 32(2), pages 283-292.
    6. Chun-Chang Lee & Chih-Min Liang & Hsing-Jung Chou, 2013. "Identifying Taiwan real estate cycle turning points- An application of the multivariate Markov-switching autoregressive Model," Advances in Management and Applied Economics, SCIENPRESS Ltd, vol. 3(2), pages 1-1.
    7. Theobald, Thomas, 2013. "Markov Switching with Endogenous Number of Regimes and Leading Indicators in a Real-Time Business Cycle Forecast," VfS Annual Conference 2013 (Duesseldorf): Competition Policy and Regulation in a Global Economic Order 79911, Verein für Socialpolitik / German Economic Association.
    8. Sergey V. Smirnov & Nikolay V. Kondrashov & Anna V. Petronevich, 2017. "Dating Cyclical Turning Points for Russia: Formal Methods and Informal Choices," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 13(1), pages 53-73, May.
    9. Grigoraş, Veaceslav & Stanciu, Irina Eusignia, 2016. "New evidence on the (de)synchronisation of business cycles: Reshaping the European business cycle," International Economics, Elsevier, vol. 147(C), pages 27-52.
    10. Vitor Castro, 2015. "The Portuguese business cycle: chronology and duration dependence," Empirical Economics, Springer, vol. 49(1), pages 325-342, August.
    11. Calderón, César & Fuentes, J. Rodrigo, 2014. "Have business cycles changed over the last two decades? An empirical investigation," Journal of Development Economics, Elsevier, vol. 109(C), pages 98-123.
    12. Michael T. Owyang & Jeremy Piger & Howard J. Wall, 2005. "Business Cycle Phases in U.S. States," The Review of Economics and Statistics, MIT Press, vol. 87(4), pages 604-616, November.
    13. Chris Birchenhall & Denise Osborn & Marianne Sensier, 2001. "Predicting UK Business Cycle Regimes," Scottish Journal of Political Economy, Scottish Economic Society, vol. 48(2), pages 179-195, May.
    14. Penelope A. Smith & Peter M. Summers, 2005. "How well do Markov switching models describe actual business cycles? The case of synchronization," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 20(2), pages 253-274.
    15. Bracke, Philippe, 2013. "How long do housing cycles last? A duration analysis for 19 OECD countries," Journal of Housing Economics, Elsevier, vol. 22(3), pages 213-230.
    16. Peter Martey Addo & Monica Billio & Dominique Guegan, 2013. "Turning point chronology for the Euro-Zone: A Distance Plot Approach," Documents de travail du Centre d'Economie de la Sorbonne 13025, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
    17. Fukuda, Kosei, 2012. "Illustrating extraordinary shocks causing trend breaks," Economic Modelling, Elsevier, vol. 29(4), pages 1045-1052.
    18. João Victor Issler & Hilton Hostalacio Notini & Claudia Fontoura Rodrigues, 2013. "Constructing coincident and leading indices of economic activity for the Brazilian economy," OECD Journal: Journal of Business Cycle Measurement and Analysis, OECD Publishing, Centre for International Research on Economic Tendency Surveys, vol. 2012(2), pages 43-65.
    19. Nathan S. Balke & Mark A. Wynne, 1993. "Recessions and recoveries in real business cycle models: do real business cycle models generate cyclical behavior?," Working Papers 9322, Federal Reserve Bank of Dallas.
    20. Giancarlo Bruno & Edoardo Otranto, 2003. "Dating the Italian Business Cycle: A Comparison of Procedures," Econometrics 0312003, University Library of Munich, Germany.

    More about this item

    Keywords

    Wirtschaftsindikator; Prognoseverfahren; Saisonbereinigung; Markov-Kette; Konjunktur;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles

    Statistics

    Access and download statistics

    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:ces:ifosdt:v:68:y:2015:i:05:p:27-32. 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: Klaus Wohlrabe (email available below). General contact details of provider: https://edirc.repec.org/data/ifooode.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.