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. 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.
    3. 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.
    4. 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.
    5. 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.
    6. 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.
    7. 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.
    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. 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.
    10. 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.
    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. 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.
    2. 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.
    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. 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.
    5. 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, March.

    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, October.
    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, March.
    3. 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.
    4. 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.
    5. 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.
    6. 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.
    7. 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.
    8. Vitor Castro, 2015. "The Portuguese business cycle: chronology and duration dependence," Empirical Economics, Springer, vol. 49(1), pages 325-342, August.
    9. 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.
    10. 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.
    11. 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.
    12. Billio, Monica & Casarin, Roberto & Ravazzolo, Francesco & van Dijk, Herman K., 2012. "Combination schemes for turning point predictions," The Quarterly Review of Economics and Finance, Elsevier, vol. 52(4), pages 402-412.
    13. Castro, Vítor, 2010. "The duration of economic expansions and recessions: More than duration dependence," Journal of Macroeconomics, Elsevier, vol. 32(1), pages 347-365, March.
    14. Brandyn Bok & Daniele Caratelli & Domenico Giannone & Argia M. Sbordone & Andrea Tambalotti, 2018. "Macroeconomic Nowcasting and Forecasting with Big Data," Annual Review of Economics, Annual Reviews, vol. 10(1), pages 615-643, August.
    15. Marcelle Chauvet & Jeremy Piger, 2013. "Employment And The Business Cycle," Manchester School, University of Manchester, vol. 81, pages 16-42, October.
    16. Antonin Aviat & Frédérique Bec & Claude Diebolt & Catherine Doz & Denis Ferrand & Laurent Ferrara & Eric Heyer & Valérie Mignon & Pierre-Alain Pionnier, 2021. "Dating business cycles in France: a reference chronology," SciencePo Working papers Main hal-03373425, HAL.
    17. Dagum, Estela Bee, 2010. "Business Cycles and Current Economic Analysis/Los ciclos económicos y el análisis económico actual," Estudios de Economia Aplicada, Estudios de Economia Aplicada, vol. 28, pages 577-594, Diciembre.
    18. Marcus Scheiblecker, 2007. "Datierung von Konjunkturwendepunkten in Österreich," WIFO Monatsberichte (monthly reports), WIFO, vol. 80(9), pages 715-730, September.
    19. Soh, Ann-Ni, 2020. "A Review on the Leading Indicator Approach towards Economic Forecasting," MPRA Paper 103854, University Library of Munich, Germany.
    20. Olivier Darné & Laurent Ferrara, 2011. "Identification of Slowdowns and Accelerations for the Euro Area Economy," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 73(3), pages 335-364, June.

    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.