IDEAS home Printed from https://ideas.repec.org/p/ags/hwwadp/26253.html
   My bibliography  Save this paper

Prognoseleistung von Fruhindikatoren: Die Bedeutung von Fruhindikatoren fur Konjunk-turprognosen - Eine Analyse fur Deutschland

Author

Listed:
  • Hinze, Jorg

Abstract

Das Papier untersucht die Rolle von Frühindikatoren bei der Erstellung von Konjunkturprognosen. Gegenstand der Analyse sind die Fragen: Welche Kriterien sollten Frühindikatoren generell erfüllen bzw. was sollten Frühindikatoren leisten? Inwieweit erfüllen die gängigen Indikatoren diese Anforderungen? Wie ist die Prognosegüte der verschiedenen Frühindikatoren zu beurteilen? Die theoretischen Überlegungen und ökonometrischen Untersuchungen kommen zu dem Ergebnis, dass die gängigen Frühindikatoren die in sie gesetzten Erwartungen nur eingeschränkt erfüllen können. Der Verlauf einzelner Frühindikatoren lässt keine eindeutigen Schlußfolgerungen auf die reale Wirtschaftsentwicklung zu und der Vorlauf der Frühindikatoren vor der realen Entwicklung beträgt bestenfalls einige Monate. Für die Erstellung von Konjunkturprognosen, die in der Regel einen Zeitraum von mehr als einem Jahr bis zu zwei Jahren umfassen, bedeutet das, dass Frühindikatoren allenfalls einen kleinen Ausschnitt abdecken können. Sie sind vor allem wertvoll für die Diagnose am "aktuellen Rand" und für Kurzfristprognosen. Prognosen für die Zeit darüber hinaus müssen sich nach wie vor vor allem auf die Analyse der Rahmenbedingungen stützen.

Suggested Citation

  • Hinze, Jorg, 2003. "Prognoseleistung von Fruhindikatoren: Die Bedeutung von Fruhindikatoren fur Konjunk-turprognosen - Eine Analyse fur Deutschland," Discussion Paper Series 26253, Hamburg Institute of International Economics.
    • Handle: RePEc:ags:hwwadp:26253
    DOI: 10.22004/ag.econ.26253
    as

    Download full text from publisher

    File URL: https://ageconsearch.umn.edu/record/26253/files/dp030236.pdf
    Download Restriction: no
    File URL: https://libkey.io/10.22004/ag.econ.26253?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Ulrich Fritsche, 1999. "Vorlaufeigenschaften von Ifo-Indikatoren für Westdeutschland," Discussion Papers of DIW Berlin 179, DIW Berlin, German Institute for Economic Research.
    2. Langfeldt, Enno, 1994. "Die Zinsstruktur als Frühindikator für Konjunktur und Preisentwicklung in Deutschland," Kiel Working Papers 615, Kiel Institute for the World Economy (IfW Kiel).
    3. Norbert Funke, 1997. "Predicting recessions: Some evidence for Germany," Review of World Economics (Weltwirtschaftliches Archiv), Springer;Institut für Weltwirtschaft (Kiel Institute for the World Economy), vol. 133(1), pages 90-102, March.
    4. Georg Goldrian, 2001. "Early indicators derived from survey data: adequate construction design and forecasting quality," ifo Schnelldienst, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 54(22), pages 32-36, December.
    5. Ulrich Fritsche & Sabine Stephan, 2000. "Leading Indicators of German Business Cycles: An Assessment of Properties," Macroeconomics 0004005, University Library of Munich, Germany.
    6. Diebold, Francis X & Rudebusch, Glenn D, 1996. "Measuring Business Cycles: A Modern Perspective," The Review of Economics and Statistics, MIT Press, vol. 78(1), pages 67-77, February.
    7. Döpke, Jörg, 1999. "Predicting Germany's recessions with leading indicators: Evidence from probit models," Kiel Working Papers 944, Kiel Institute for the World Economy (IfW Kiel).
    8. Peter Grasmann & Filip Keereman, 2001. "An indicator-based short-term forecast for quarterly GDP in the euro area," European Economy - Economic Papers 2008 - 2015 154, Directorate General Economic and Financial Affairs (DG ECFIN), European Commission.
    9. G. Goldrian & J.D. Lindbauer & G. Nerb & B. Ulrich, 2001. "Evaluation and development of confidence indicators based on harmonised business and consumer surveys (Study contracted to IFO, Munich)," European Economy - Economic Papers 2008 - 2015 151, Directorate General Economic and Financial Affairs (DG ECFIN), European Commission.
    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. Kholodilin Konstantin Arkadievich & Siliverstovs Boriss, 2006. "On the Forecasting Properties of the Alternative Leading Indicators for the German GDP: Recent Evidence," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 226(3), pages 234-259, June.
    2. Konstantin Arkadievich Kholodilin & Boriss Siliverstovs & Stefan Kooths, 2008. "A Dynamic Panel Data Approach to the Forecasting of the GDP of German Länder," Spatial Economic Analysis, Taylor & Francis Journals, vol. 3(2), pages 195-207.
    3. Akalan, Rodi & Brink, Siegrun & Icks, Annette & Wolter, Hans-Jürgen, 2023. "Bedrohungen und Chancen frühzeitig erkennen: Entwicklung eines Früherkennungskonzepts," IfM-Materialien 303, Institut für Mittelstandsforschung (IfM) Bonn.
    4. Katja Rietzler & Sabine Stephan, 2012. "Monthly recession predictions in real time: A density forecast approach for German industrial production," IMK Working Paper 94-2012, IMK at the Hans Boeckler Foundation, Macroeconomic Policy Institute.

    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. Hinze, Jörg, 2003. "Prognoseleistung von Frühindikatoren: Die Bedeutung von Frühindikatoren für Konjunkturprognosen - Eine Analyse für Deutschland," HWWA Discussion Papers 236, Hamburg Institute of International Economics (HWWA).
    2. Benner, Joachim & Meier, Carsten-Patrick, 2005. "Was leisten Stimmungsindikatoren für die Prognose des realen Bruttoinlandsprodukts in Deutschland? Eine Echtzeit-Analyse," Open Access Publications from Kiel Institute for the World Economy 3725, Kiel Institute for the World Economy (IfW Kiel).
    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. Schröder, Michael & Hüfner, Felix P., 2002. "Forecasting economic activity in Germany: how useful are sentiment indicators?," ZEW Discussion Papers 02-56, ZEW - Leibniz Centre for European Economic Research.
    6. Benner Joachim & Meier Carsten-Patrick, 2004. "Prognosegüte alternativer Früh Indikatoren für die Konjunktur in Deutschland / Forecasting Performance of Alternative Indicators for the German Economy," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 224(6), pages 639-652, December.
    7. Hüfner, Felix P. & Schröder, Michael, 2001. "Unternehmens- versus Analystenbefragungen: Zum Prognosegehalt von ifo-Geschäftserwartungen und ZEW-Konjunkturerwartungen," ZEW Discussion Papers 01-04, ZEW - Leibniz Centre for European Economic Research.
    8. Ulrich Fritsche & Felix Marklein, 2001. "Leading Indicators of Euroland Business Cycles," Discussion Papers of DIW Berlin 238, DIW Berlin, German Institute for Economic Research.
    9. Benner, Joachim & Meier, Carsten-Patrick, 2003. "Prognosegüte alternativer Frühindikatoren für die Konjunktur in Deutschland," Kiel Working Papers 1139, Kiel Institute for the World Economy (IfW Kiel).
    10. 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.
    11. Ulrich Fritsche, 2001. "Do probit models help in forecasting turning points of German business cycles?," Macroeconomics 0012022, University Library of Munich, Germany.
    12. Weinert, Günter, 2003. "Zwischen Hoffen und Bangen - Konjunktur 2003," HWWA Reports 224, Hamburg Institute of International Economics (HWWA).
    13. Hüfner, Felix P. & Lahl, David, 2003. "What Determines the ZEW Indicator?," ZEW Discussion Papers 03-48, ZEW - Leibniz Centre for European Economic Research.
    14. Michael Funke & Harm Bandholz, 2003. "In search of leading indicators of economic activity in Germany," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 22(4), pages 277-297.
    15. Kholodilin Konstantin A., 2005. "Forecasting the German Cyclical Turning Points: Dynamic Bi-Factor Model with Markov Switching," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 225(6), pages 653-674, December.
    16. Konstantin A. Kholodilin, 2005. "Forecasting the Turns of German Business Cycle: Dynamic Bi-factor Model with Markov Switching," Discussion Papers of DIW Berlin 494, DIW Berlin, German Institute for Economic Research.
    17. Klaus Abberger & Sascha Becker & Barbara Hofmann & Klaus Wohlrabe, 2007. "Mikrodaten im ifo Institut für Wirtschaftsforschung – Bestand, Verwendung und Zugang," AStA Wirtschafts- und Sozialstatistisches Archiv, Springer;Deutsche Statistische Gesellschaft - German Statistical Society, vol. 1(1), pages 27-42, June.
    18. Agne Reklaite, 2011. "Coincident, leading and recession indexes for the Lithuanian economy," Baltic Journal of Economics, Baltic International Centre for Economic Policy Studies, vol. 11(1), pages 91-108, July.
    19. Heinrich, Markus & Carstensen, Kai & Reif, Magnus & Wolters, Maik, 2017. "Predicting Ordinary and Severe Recessions with a Three-State Markov-Switching Dynamic Factor Model. An Application to the German Business Cycle," VfS Annual Conference 2017 (Vienna): Alternative Structures for Money and Banking 168206, Verein für Socialpolitik / German Economic Association.
    20. Ulrich FRITSCHE & Vladimir KOUZINE, 2010. "Prediction of Business Cycle Turning Points in Germany," EcoMod2004 330600054, EcoMod.

    More about this item

    Keywords

    Agricultural and Food Policy;

    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:ags:hwwadp:26253. 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: AgEcon Search (email available below). General contact details of provider: https://edirc.repec.org/data/hwwaade.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.