IDEAS home Printed from https://ideas.repec.org/p/zbw/ifwbox/20185.html
   My bibliography  Save this paper

Zur Kurzfristprognose mit Faktormodellen und Prognoseanpassungen

Author

Listed:
  • Hauber, Philipp

Abstract

Das Bruttoinlandsprodukt wird in Quartalsfrequenz veröffentlicht und dies mit einigem zeitlichen Abstand zum jeweiligen Quartalsende (üblicherweise 45 Tage). Zugleich ist eine Vielzahl an anderen Indikatoren in höherer Frequenz und mit geringeren Publikationsverzögerungen (z.B. Umfrage-Indikatoren oder Produk-tionsdaten) verfügbar, die Informationen über das Bruttoinlandsprodukt im laufenden Quartal enthalten dürften. Unter dem Begriff "Nowcasting" werden in der Literatur Ansätze diskutiert, die mit den Besonderheiten dieser Situation für die Kurzfristprognose umgehen können.

Suggested Citation

  • Hauber, Philipp, 2018. "Zur Kurzfristprognose mit Faktormodellen und Prognoseanpassungen," Kiel Insight 2018.5, Kiel Institute for the World Economy (IfW Kiel).
    • Handle: RePEc:zbw:ifwbox:20185
    as

    Download full text from publisher

    File URL: https://www.econstor.eu/bitstream/10419/201164/1/ifw-box-2018-05.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Schumacher, Christian & Breitung, Jörg, 2008. "Real-time forecasting of German GDP based on a large factor model with monthly and quarterly data," International Journal of Forecasting, Elsevier, vol. 24(3), pages 386-398.
    2. Vladimir Kuzin & Massimiliano Marcellino & Christian Schumacher, 2013. "Pooling Versus Model Selection For Nowcasting Gdp With Many Predictors: Empirical Evidence For Six Industrialized Countries," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 28(3), pages 392-411, April.
    3. Jansen, W. Jos & Jin, Xiaowen & de Winter, Jasper M., 2016. "Forecasting and nowcasting real GDP: Comparing statistical models and subjective forecasts," International Journal of Forecasting, Elsevier, vol. 32(2), pages 411-436.
    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. Boysen-Hogrefe, Jens & Groll, Dominik & Jannsen, Nils & Kooths, Stefan & Meuchelböck, Saskia & Sonnenberg, Nils, 2022. "German Economy Summer 2022 - Slowly progessing recovery," Kiel Institute Economic Outlook 92, Kiel Institute for the World Economy (IfW Kiel).
    2. Ademmer, Martin & Boysen-Hogrefe, Jens & Fiedler, Salomon & Groll, Dominik & Hauber, Philipp & Jannsen, Nils & Kooths, Stefan & Potjagailo, Galina & Wolters, Maik H., 2018. "Deutsche Konjunktur im Sommer 2018 - Deutsche Wirtschaft: Luftloch im konjunkturellen Höhenflug [German Economy Summer 2018 - German economy: Temporary slowdown, boom not over yet]," Kieler Konjunkturberichte 44, Kiel Institute for the World Economy (IfW Kiel).
    3. Boysen-Hogrefe, Jens & Groll, Dominik & Jannsen, Nils & Kooths, Stefan & Meuchelböck, Saskia & Sonnenberg, Nils, 2022. "Deutsche Wirtschaft im Sommer 2022 - Erholung kommt mühsam voran [German Economy Summer 2022 - Slowly progessing recovery]," Kieler Konjunkturberichte 92, Kiel Institute for the World Economy (IfW Kiel).
    4. Boysen-Hogrefe, Jens & Groll, Dominik & Jannsen, Nils & Kooths, Stefan & Meuchelböck, Saskia & Sonnenberg, Nils, 2022. "German Economy Summer 2022 - Slowly progessing recovery," Kiel Institute Economic Outlook 92, Kiel Institute for the World Economy (IfW Kiel).
    5. Ademmer, Martin & Boysen-Hogrefe, Jens & Fiedler, Salomon & Groll, Dominik & Jannsen, Nils & Kooths, Stefan & Meuchelböck, Saskia, 2020. "Deutsche Wirtschaft im Winter 2020 - Zweite Corona-Welle unterbricht Erholung [German Economy Winter 2020 - Second Covid wave interrupts recovery]," Kieler Konjunkturberichte 74, Kiel Institute for the World Economy (IfW Kiel).
    6. Hauber, Philipp & Jannsen, Nils & Wolters, Maik H., 2018. "Schwacher Jahresauftakt 2018: Delle oder Beginn eines Abschwungs?," Kiel Insight 2018.10, Kiel Institute for the World Economy (IfW Kiel).
    7. Boysen-Hogrefe, Jens & Groll, Dominik & Hoffmann, Timo & Jannsen, Nils & Kooths, Stefan & Sonnenberg, Nils & Stamer, Vincent, 2023. "Deutsche Wirtschaft im Frühjahr 2023: Konjunktur fängt sich, Auftriebskräfte eher gering [German economy in spring 2023: Economy is stabilizing but little momentum going forward]," Kieler Konjunkturberichte 101, Kiel Institute for the World Economy (IfW Kiel).
    8. Boysen-Hogrefe, Jens & Groll, Dominik & Hoffmann, Timo & Jannsen, Nils & Kooths, Stefan & Sonnenberg, Nils & Stamer, Vincent, 2023. "Deutsche Wirtschaft im Winter 2023: Finanzpolitik in Turbulenzen - Gegenwind für die Erholung [German Economy in Winter 2023: Public budget under stress - Recovery faces headwinds]," Kieler Konjunkturberichte 110, Kiel Institute for the World Economy (IfW Kiel).
    9. Boysen-Hogrefe, Jens & Groll, Dominik & Hoffmann, Timo & Jannsen, Nils & Kooths, Stefan & Meuchelböck, Saskia & Sonnenberg, Nils, 2022. "Deutsche Wirtschaft im Herbst 2022 - Konjunktur auf Entzug [German Economy Autumn 2022 - Consumption-driven recession]," Kieler Konjunkturberichte 95, Kiel Institute for the World Economy (IfW Kiel).
    10. Boysen-Hogrefe, Jens & Groll, Dominik & Hoffmann, Timo & Jannsen, Nils & Kooths, Stefan & Sonnenberg, Nils & Stamer, Vincent, 2022. "Deutsche Wirtschaft im Winter 2022 - Im Kriechgang durch die Energiekrise [German Economy Winter 2022 - Inching through the energy crisis]," Kieler Konjunkturberichte 98, Kiel Institute for the World Economy (IfW Kiel).
    11. Boysen-Hogrefe, Jens & Groll, Dominik & Jannsen, Nils & Kooths, Stefan & Meuchelböck, Saskia & Sonnenberg, Nils, 2022. "Deutsche Wirtschaft im Sommer 2022 - Erholung kommt mühsam voran [German Economy Summer 2022 - Slowly progessing recovery]," Kieler Konjunkturberichte 92, Kiel Institute for the World Economy (IfW Kiel).

    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. Dennis Kant & Andreas Pick & Jasper de Winter, 2022. "Nowcasting GDP using machine learning methods," Working Papers 754, DNB.
    2. Hindrayanto, Irma & Koopman, Siem Jan & de Winter, Jasper, 2016. "Forecasting and nowcasting economic growth in the euro area using factor models," International Journal of Forecasting, Elsevier, vol. 32(4), pages 1284-1305.
    3. Cristea, R. G., 2020. "Can Alternative Data Improve the Accuracy of Dynamic Factor Model Nowcasts?," Cambridge Working Papers in Economics 20108, Faculty of Economics, University of Cambridge.
    4. Ademmer, Martin & Boysen-Hogrefe, Jens & Fiedler, Salomon & Groll, Dominik & Hauber, Philipp & Jannsen, Nils & Kooths, Stefan & Potjagailo, Galina, 2018. "Deutsche Konjunktur im Frühjahr 2018 - Deutsche Wirtschaft näher am Limit [German Economy Spring 2018 - German economy closer to its limit]," Kieler Konjunkturberichte 41, Kiel Institute for the World Economy (IfW Kiel).
    5. Jos Jansen & Jasper de Winter, 2016. "Improving model-based near-term GDP forecasts by subjective forecasts: A real-time exercise for the G7 countries," DNB Working Papers 507, Netherlands Central Bank, Research Department.
    6. Stavros Degiannakis, 2023. "The D-model for GDP nowcasting," Swiss Journal of Economics and Statistics, Springer;Swiss Society of Economics and Statistics, vol. 159(1), pages 1-33, December.
    7. Poncela, Pilar & Ruiz, Esther & Miranda, Karen, 2021. "Factor extraction using Kalman filter and smoothing: This is not just another survey," International Journal of Forecasting, Elsevier, vol. 37(4), pages 1399-1425.
    8. Kaufmann, Daniel & Scheufele, Rolf, 2017. "Business tendency surveys and macroeconomic fluctuations," International Journal of Forecasting, Elsevier, vol. 33(4), pages 878-893.
    9. Lehmann Robert & Wohlrabe Klaus, 2015. "Forecasting GDP at the Regional Level with Many Predictors," German Economic Review, De Gruyter, vol. 16(2), pages 226-254, May.
    10. Schumacher, Christian, 2016. "A comparison of MIDAS and bridge equations," International Journal of Forecasting, Elsevier, vol. 32(2), pages 257-270.
    11. Jansen, W. Jos & Jin, Xiaowen & de Winter, Jasper M., 2016. "Forecasting and nowcasting real GDP: Comparing statistical models and subjective forecasts," International Journal of Forecasting, Elsevier, vol. 32(2), pages 411-436.
    12. Christian Glocker & Serguei Kaniovski, 2022. "Macroeconometric forecasting using a cluster of dynamic factor models," Empirical Economics, Springer, vol. 63(1), pages 43-91, July.
    13. Konstantin Kuck & Karsten Schweikert, 2021. "Forecasting Baden‐Württemberg's GDP growth: MIDAS regressions versus dynamic mixed‐frequency factor models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(5), pages 861-882, August.
    14. Alessandro Girardi & Roberto Golinelli & Carmine Pappalardo, 2017. "The role of indicator selection in nowcasting euro-area GDP in pseudo-real time," Empirical Economics, Springer, vol. 53(1), pages 79-99, August.
    15. Rusnák, Marek, 2016. "Nowcasting Czech GDP in real time," Economic Modelling, Elsevier, vol. 54(C), pages 26-39.
    16. Pinkwart, Nicolas, 2018. "Short-term forecasting economic activity in Germany: A supply and demand side system of bridge equations," Discussion Papers 36/2018, Deutsche Bundesbank.
    17. Ryan T. Ball & Eric Ghysels, 2018. "Automated Earnings Forecasts: Beat Analysts or Combine and Conquer?," Management Science, INFORMS, vol. 64(10), pages 4936-4952, October.
    18. Mahmut Gunay, 2020. "Nowcasting Turkish GDP with MIDAS: Role of Functional Form of the Lag Polynomial," Working Papers 2002, Research and Monetary Policy Department, Central Bank of the Republic of Turkey.
    19. Dorinth van Dijk & Jasper de Winter, 2023. "Nowcasting GDP using tone-adjusted time varying news topics: Evidence from the financial press," Working Papers 766, DNB.
    20. Irma Hindrayanto & Siem Jan Koopman & Jasper de Winter, 2014. "Nowcasting and Forecasting Economic Growth in the Euro Area using Principal Components," Tinbergen Institute Discussion Papers 14-113/III, Tinbergen Institute.

    More about this item

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:zbw:ifwbox:20185. 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: ZBW - Leibniz Information Centre for Economics (email available below). General contact details of provider: https://edirc.repec.org/data/iwkiede.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.