IDEAS home Printed from https://ideas.repec.org/p/zbw/uhhwps/63.html
   My bibliography  Save this paper

Economics in Action – die Erstellung von Wirtschaftsprognosen in der (Corona-)Krise

Author

Listed:
  • Emme, Verena
  • Henze, Justus
  • Reichmann, Werner
  • Weinig, Max

Abstract

Das Papier geht der Frage nach, wie sich die Herstellung von Wirtschaftsprognosen im Kontext der radikalen Ungewissheit während der Corona-Pandemie verändert. Etablierte soziologische Forschungsarbeiten zu Wirtschaftsprognosen haben gezeigt, dass soziale Interaktionsprozesse zwischen den Akteur*innen der Prognostik innerhalb eines Netzwerks konstitutiv für die Herstellung von Prognosewissen sind. Dieses Papier aktualisiert und erweitert diese Erkenntnisse für die besonderen Bedingungen während der Corona-Pandemie. Mittels einer sozialen Netzwerkanalyse und der Auswertung von qualitativen Interviews mit führenden Prognostiker*innen im deutschsprachigen Raum wird gezeigt, dass die Bedeutung von sozialen Interaktionsprozessen innerhalb eines erweiterten Netzwerks zwischen Akteur*innen der Wirtschaftsforschung und -politik während der Corona-Pandemie stark zunimmt. Epistemische Interaktionen stellen sicher, dass in dieser weitreichenden gesellschaftlichen Krisensituation überhaupt plausible und glaubhafte Prognosen über die ökonomische Zukunft produziert werden können.

Suggested Citation

  • Emme, Verena & Henze, Justus & Reichmann, Werner & Weinig, Max, 2021. "Economics in Action – die Erstellung von Wirtschaftsprognosen in der (Corona-)Krise," WiSo-HH Working Paper Series 63, University of Hamburg, Faculty of Business, Economics and Social Sciences, WISO Research Laboratory.
  • Handle: RePEc:zbw:uhhwps:63
    as

    Download full text from publisher

    File URL: https://www.econstor.eu/bitstream/10419/260466/1/wp63.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Negro, Marco Del & Schorfheide, Frank, 2013. "DSGE Model-Based Forecasting," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 57-140, Elsevier.
    2. Döpke Jörg & Fritsche Ulrich & Waldhof Gabi, 2019. "Theories, Techniques and the Formation of German Business Cycle Forecasts : Evidence from a survey of professional forecasters," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 239(2), pages 203-241, April.
    3. Wolfgang Nierhaus, 2002. "Die Gemeinschaftsdiagnose der Wirtschaftsforschungsinstitute," ifo Schnelldienst, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 55(08), pages 40-42, April.
    Full references (including those not matched with items on IDEAS)

    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. Döpke Jörg & Fritsche Ulrich & Waldhof Gabi, 2019. "Theories, Techniques and the Formation of German Business Cycle Forecasts : Evidence from a survey of professional forecasters," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 239(2), pages 203-241, April.
    2. Shirai, Daichi, 2016. "Persistence and Amplification of Financial Frictions," MPRA Paper 72187, University Library of Munich, Germany.
    3. Esteban Prieto & Sandra Eickmeier & Massimiliano Marcellino, 2016. "Time Variation in Macro‐Financial Linkages," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 31(7), pages 1215-1233, November.
    4. Lindé, Jesper & Smets, Frank & Wouters, Rafael, 2016. "Challenges for Central Banks´ Macro Models," Working Paper Series 323, Sveriges Riksbank (Central Bank of Sweden).
    5. Barde, Sylvain, 2020. "Macroeconomic simulation comparison with a multivariate extension of the Markov information criterion," Journal of Economic Dynamics and Control, Elsevier, vol. 111(C).
    6. Carlo Altavilla & Domenico Giannone, 2017. "The Effectiveness of Non‐Standard Monetary Policy Measures: Evidence from Survey Data," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 32(5), pages 952-964, August.
    7. Marina Riem, 2017. "Essays on the Behavior of Firms and Politicians," ifo Beiträge zur Wirtschaftsforschung, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, number 73, May.
    8. Giannone, Domenico & Monti, Francesca & Reichlin, Lucrezia, 2016. "Exploiting the monthly data flow in structural forecasting," Journal of Monetary Economics, Elsevier, vol. 84(C), pages 201-215.
    9. Lars Winkelmann & Wenying Yao, 2024. "Tests for Jumps in Yield Spreads," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 42(3), pages 946-957, July.
    10. Elias, Christopher J., 2022. "Adaptive learning with heterogeneous expectations in an estimated medium-scale New Keynesian model," Journal of Macroeconomics, Elsevier, vol. 71(C).
    11. Patrick C. Higgins, 2014. "GDPNow: A Model for GDP \"Nowcasting\"," FRB Atlanta Working Paper 2014-7, Federal Reserve Bank of Atlanta.
    12. Bluwstein, Kristina, 2017. "Asymmetric Macro-Financial Spillovers," Working Paper Series 337, Sveriges Riksbank (Central Bank of Sweden).
    13. Wieland, Volker & Wolters, Maik, 2013. "Forecasting and Policy Making," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 239-325, Elsevier.
    14. Smets, Frank & Warne, Anders & Wouters, Raf, 2013. "Professional forecasters and the real-time forecasting performance of an estimated new keynesian model for the euro area," Working Paper Series 1571, European Central Bank.
    15. Pablo Guerróon‐Quintana & Molin Zhong, 2023. "Macroeconomic forecasting in times of crises," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 38(3), pages 295-320, April.
    16. Ganics, Gergely & Odendahl, Florens, 2021. "Bayesian VAR forecasts, survey information, and structural change in the euro area," International Journal of Forecasting, Elsevier, vol. 37(2), pages 971-999.
    17. Ilut, Cosmin & Saijo, Hikaru, 2021. "Learning, confidence, and business cycles," Journal of Monetary Economics, Elsevier, vol. 117(C), pages 354-376.
    18. Ángel Estrada & Luis Guirola & Iván Kataryniuk & Jaime Martínez-Martín, 2020. "The use of BVARs in the analysis of emerging economies," Occasional Papers 2001, Banco de España.
    19. repec:zbw:bofrdp:2018_022 is not listed on IDEAS
    20. Francesco Furlanetto & Paolo Gelain & Marzie Taheri Sanjani, 2021. "Output Gap, Monetary Policy Trade-offs, and Financial Frictions," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 41, pages 52-70, July.
    21. Michael Cai & Marco Del Negro & Edward Herbst & Ethan Matlin & Reca Sarfati & Frank Schorfheide, 2021. "Online estimation of DSGE models," The Econometrics Journal, Royal Economic Society, vol. 24(1), pages 33-58.

    More about this item

    Keywords

    Wirtschaftsprognosen; Corona; Pandemie; Covid-19; Wissensproduktion; Unsicherheit; Erwartungsbildung; Epistemische Interaktion;
    All these keywords.

    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:uhhwps:63. 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/fwhamde.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.