IDEAS home Printed from https://ideas.repec.org/a/ces/ifosdt/v71y2018i12p27-32.html

Das ifo Importklima – ein erster Frühindikator für die Prognose der deutschen Importe

Author

Listed:
  • Christian Grimme
  • Robert Lehmann
  • Marvin Nöller

Abstract

Typischerweise zählen die Importe zu jenen Größen in der Konjunkturprognose, die die größten Prognosefehler aufweisen. Neben der erheblichen Volatilität der Importwachstumsraten ist dies dem Umstand geschuldet, dass bis dato kein bewährter Vorlaufindikator für die Importe Deutschlands vorliegt. In diesem Artikel wird ein erster Frühindikator, basierend auf Unternehmens- und Konsumentenbefragungen – das ifo Importklima –, für die Prognose der deutschen Importe vorgeschlagen. Das Importklima nutzt die Exporterwartungen der wichtigsten Handelspartner Deutschlands, um die deutsche Importnachfrage abzubilden. Ein Prognoseexperiment für das laufende und das kommende Quartal unterstreicht die Prognosegüte des ifo Importklimas, da es geringere Prognosefehler als andere Indikatoren, wie bspw. der Spezialhandel oder die Auftragseingänge, verursacht. Damit ist das ifo Importklima ein vielversprechender Indikator für die praktische Prognosearbeit.

Suggested Citation

  • Christian Grimme & Robert Lehmann & Marvin Nöller, 2018. "Das ifo Importklima – ein erster Frühindikator für die Prognose der deutschen Importe," ifo Schnelldienst, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 71(12), pages 27-32, June.
  • Handle: RePEc:ces:ifosdt:v:71:y:2018:i:12:p:27-32
    as

    Download full text from publisher

    File URL: https://www.ifo.de/DocDL/sd-2018-12-grimme-lehmann-noeller-importklima-2018-06-28.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Carstensen, Kai & Heinrich, Markus & Reif, Magnus & Wolters, Maik H., 2020. "Predicting ordinary and severe recessions with a three-state Markov-switching dynamic factor model," International Journal of Forecasting, Elsevier, vol. 36(3), pages 829-850.
    2. Grimme, Christian & Lehmann, Robert & Noeller, Marvin, 2021. "Forecasting imports with information from abroad," Economic Modelling, Elsevier, vol. 98(C), pages 109-117.
    3. Diebold, Francis X & Mariano, Roberto S, 2002. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 134-144, January.
    4. Steffen Elstner & Christian Grimme & Ulrich Haskamp, 2013. "Das ifo Exportklima – ein Frühindikator für die deutsche Exportprognose," ifo Schnelldienst, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 66(04), pages 36-43, March.
    5. Harvey, David & Leybourne, Stephen & Newbold, Paul, 1997. "Testing the equality of prediction mean squared errors," International Journal of Forecasting, Elsevier, vol. 13(2), pages 281-291, June.
    6. Döhrn Roland & Schmidt Christoph M., 2011. "Information or Institution?: On the Determinants of Forecast Accuracy," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 231(1), pages 9-27, February.
    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 & Silvia Delrio & Marcell Göttert & Christian Grimme & Jochen Güntner & Carla Krolage & Stefan Lautenbacher & Robert Lehmann & Sebastian Link & Wolfgang Nierhaus & Magnus Reif & Ra, 2018. "ifo Konjunkturprognose Sommer 2018: Gewitterwolken am deutschen Konjunkturhimmel," ifo Schnelldienst, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 71(12), pages 33-87, June.
    2. 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.

    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. 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, April.
    2. Grimme, Christian & Lehmann, Robert & Noeller, Marvin, 2021. "Forecasting imports with information from abroad," Economic Modelling, Elsevier, vol. 98(C), pages 109-117.
    3. Magnus Reif, 2020. "Macroeconomics, Nonlinearities, and the Business Cycle," ifo Beiträge zur Wirtschaftsforschung, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, number 87, April.
    4. Robert Lehmann, 2021. "Forecasting exports across Europe: What are the superior survey indicators?," Empirical Economics, Springer, vol. 60(5), pages 2429-2453, May.
    5. Robert Lehmann & Magnus Reif, 2021. "Predicting the German Economy: Headline Survey Indices Under Test," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 17(2), pages 215-232, November.
    6. Robert Lehmann, 2016. "Economic Growth and Business Cycle Forecasting at the Regional Level," ifo Beiträge zur Wirtschaftsforschung, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, number 65, April.
    7. Behrens, Christoph, 2019. "Evaluating the Joint Efficiency of German Trade Forecasts. A nonparametric multivariate approach," Working Papers 9, German Research Foundation's Priority Programme 1859 "Experience and Expectation. Historical Foundations of Economic Behaviour", Humboldt University Berlin.
    8. Ulrich Fritsche & Artur Tarassow, 2017. "Vergleichende Evaluation der Konjunkturprognosen des Instituts für Makroökonomie und Konjunkturforschung an der Hans-Böckler-Stiftung für den Zeitraum 2005-2014," IMK Studies 54-2017, IMK at the Hans Boeckler Foundation, Macroeconomic Policy Institute.
    9. Tino Berger & Simon Wintter, 2025. "Economic Forecasting With German Newspaper Articles," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 44(2), pages 497-512, March.
    10. Christoph Behrens, 2019. "A Nonparametric Evaluation of the Optimality of German Export and Import Growth Forecasts under Flexible Loss," Economies, MDPI, vol. 7(3), pages 1-23, September.
    11. 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.
    12. 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.
    13. Karsten Müller, 2022. "German forecasters’ narratives: How informative are German business cycle forecast reports?," Empirical Economics, Springer, vol. 62(5), pages 2373-2415, May.
    14. Chuliá, Helena & Garrón, Ignacio & Uribe, Jorge M., 2024. "Daily growth at risk: Financial or real drivers? The answer is not always the same," International Journal of Forecasting, Elsevier, vol. 40(2), pages 762-776.
    15. Mehmet Balcilar & Rangan Gupta & Stephen M. Miller, 2015. "The out-of-sample forecasting performance of nonlinear models of regional housing prices in the US," Applied Economics, Taylor & Francis Journals, vol. 47(22), pages 2259-2277, May.
    16. Jonathan Berrisch & Florian Ziel, 2023. "Multivariate Probabilistic CRPS Learning with an Application to Day-Ahead Electricity Prices," Papers 2303.10019, arXiv.org, revised Feb 2024.
    17. Sucarrat, Genaro, 2009. "Forecast Evaluation of Explanatory Models of Financial Variability," Economics - The Open-Access, Open-Assessment E-Journal (2007-2020), Kiel Institute for the World Economy, vol. 3, pages 1-33.
    18. Massimiliano Marzo & Paolo Zagaglia, 2010. "Volatility forecasting for crude oil futures," Applied Economics Letters, Taylor & Francis Journals, vol. 17(16), pages 1587-1599.
    19. Mittnik, Stefan & Robinzonov, Nikolay & Spindler, Martin, 2015. "Stock market volatility: Identifying major drivers and the nature of their impact," Journal of Banking & Finance, Elsevier, vol. 58(C), pages 1-14.
    20. Lahiri, Kajal & Yang, Liu, 2013. "Forecasting Binary Outcomes," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 1025-1106, Elsevier.

    More about this item

    Keywords

    ;
    ;
    ;
    ;

    JEL classification:

    • O10 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - General
    • O12 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Microeconomic Analyses of Economic Development
    • F10 - International Economics - - Trade - - - General

    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:71:y:2018:i:12: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.