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Prognoseeigenschaften von Indikatoren zur Vorhersage des Bruttoinlandsprodukts in Deutschland

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  • Steffen Henzel
  • Sebastian Rast

Abstract

Die Güte der Prognose der Veränderungsrate des BIP für das laufende und das kommende Quartal bestimmt entscheidend die Treffsicherheit jeder Konjunkturprognose. Am aktuellen Rand lassen sich dafür die Informationen aus monatlich veröffentlichten Konjunkturindikatoren nutzen. Für Deutschland gibt es eine Vielzahl solcher Indikatoren, und es stellt sich die Frage, welcher die besten Prognoseeigenschaften aufweist und damit das verlässlichste Signal zur aktuellen konjunkturellen Situation bereitstellt. In dem Artikel werden die gängigsten weichen Indikatoren für Deutschland bezüglich ihrer Prognosekraft für die Quartalswachstumsrate des BIP verglichen. Zudem wird der Informationsvorsprung dieser Indikatoren gegenüber dem Produktionsindex evaluiert.

Suggested Citation

  • Steffen Henzel & Sebastian Rast, 2013. "Prognoseeigenschaften von Indikatoren zur Vorhersage des Bruttoinlandsprodukts in Deutschland," ifo Schnelldienst, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 66(17), pages 39-46, September.
    • Handle: RePEc:ces:ifosdt:v:66:y:2013:i:17:p:39-46
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    References listed on IDEAS

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    Citations

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    Cited by:

    1. Henzel Steffen R. & Lehmann Robert & Wohlrabe Klaus, 2015. "Nowcasting Regional GDP: The Case of the Free State of Saxony," Review of Economics, De Gruyter, vol. 66(1), pages 71-98, April.
    2. Steffen Henzel & Wolfgang Nierhaus & Tim Oliver Berg & Christian Breuer & Kai Carstensen & Christian Grimme & Oliver Hülsewig & Atanas Hristov & Nikolay Hristov & Michael Kleemann & Wolfgang Meister &, 2013. "ifo Konjunkturprognose 2013/2014: Deutsche Konjunkturlokomotive kommt unter Dampf," ifo Schnelldienst, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 66(24), pages 20-67, December.
    3. Inske Pirschel & Maik H. Wolters, 2018. "Forecasting with large datasets: compressing information before, during or after the estimation?," Empirical Economics, Springer, vol. 55(2), pages 573-596, September.
    4. 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.
    5. Christian Seiler & Klaus Wohlrabe, 2013. "Das ifo Geschäftsklima und die deutsche Konjunktur," ifo Schnelldienst, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 66(18), pages 17-21, October.
    6. 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.
    7. Timo Wollmershäuser, 2015. "Evaluation der ifo Konjunkturprognosen – ein Vergleich mit den Prognosen von Consensus Economics," ifo Schnelldienst, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 68(22), pages 26-28, November.
    8. Zeno Enders & Franziska Hünnekes & Gernot Müller, 2022. "Firm Expectations and Economic Activity," Journal of the European Economic Association, European Economic Association, vol. 20(6), pages 2396-2439.
    9. 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.
    10. Robert Lehmann & Andreas Sharik & Michael Weber, 2014. "Der Erklärungsgehalt der regionalen ifo-Indikatoren am Beispiel der Industrie- und Bauumsätze," ifo Dresden berichtet, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 21(04), pages 18-24, August.
    11. Pirschel, Inske & Wolters, Maik H., 2014. "Forecasting German key macroeconomic variables using large dataset methods," Kiel Working Papers 1925, Kiel Institute for the World Economy (IfW Kiel).
    12. 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.
    13. Timo Wollmershäuser & Wolfgang Nierhaus & Nikolay Hristov & Tim Oliver Berg & Christian Breuer & Johanna Garnitz & Christian Grimme & Atanas Hristov & Robert Lehmann & Wolfgang Meister & Magnus Reif &, 2016. "ifo Konjunkturprognose 2016/2017: Aufschwung in Deutschland geht in die zweite Halbzeit," ifo Schnelldienst, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 69(12), pages 21-57, June.
    14. Steffen Henzel & Robert Lehmann & Klaus Wohlrabe, 2015. "Die Machbarkeit von Kurzfristprognosen für den Freistaat Sachsen," ifo Dresden berichtet, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 22(04), pages 21-25, August.

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    More about this item

    Keywords

    Sozialprodukt; Konjunkturprognose; Volkswirtschaftliche Gesamtrechnung; Deutschland;
    All these keywords.

    JEL classification:

    • H61 - Public Economics - - National Budget, Deficit, and Debt - - - Budget; Budget Systems
    • O10 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - General

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