IDEAS home Printed from https://ideas.repec.org/p/wfo/rbrief/y2020i13.html
   My bibliography  Save this paper

Hochfrequenzkonjunkturanalyse vom Juli 2020

Author

Listed:
  • Sandra Bilek-Steindl
  • Julia Bock-Schappelwein
  • Christian Glocker

    (WIFO)

  • Serguei Kaniovski

Abstract

Der neu entwickelte wöchentliche WIFO-Wirtschaftsindex (WWWI) zeigt auf der Basis hochfrequenter Daten bis Ende Juli 2020 (Kalenderwoche 31, 27. Juli bis 2. August) eine Verbesserung der Wirtschaftslage gegenüber dem Tiefstand während des Lockdown im März und April 2020 (–22%). Die Wirtschaftsleistung lag damit jedoch noch immer deutlich unter dem Vorjahreswert (–3,1%). Die auf dem WWWI aufbauende Einschätzung für das Gesamtjahreswachstum des BIP stabilisierte sich ab Ende April bei rund –7%. Die Lage auf dem Arbeitsmarkt entspannte sich im Juli weiter, jedoch schwächer als in den Monaten zuvor.

Suggested Citation

  • Sandra Bilek-Steindl & Julia Bock-Schappelwein & Christian Glocker & Serguei Kaniovski, 2020. "Hochfrequenzkonjunkturanalyse vom Juli 2020," WIFO Research Briefs 13, WIFO.
  • Handle: RePEc:wfo:rbrief:y:2020:i:13
    Note: With English abstract.
    as

    Download full text from publisher

    File URL: https://www.wifo.ac.at/wwa/pubid/66525
    File Function: abstract
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Aruoba, S. BoraÄŸan & Diebold, Francis X. & Scotti, Chiara, 2009. "Real-Time Measurement of Business Conditions," Journal of Business & Economic Statistics, American Statistical Association, vol. 27(4), pages 417-427.
    2. Josef Baumgartner & Serguei Kaniovski & Jürgen Bierbaumer & Christian Glocker & Ulrike Huemer & Simon Loretz & Helmut Mahringer & Hans Pitlik, 2020. "Die Wirtschaftsentwicklung in Österreich im Zeichen der COVID-19-Pandemie. Mittelfristige Prognose 2020 bis 2024," WIFO Monatsberichte (monthly reports), WIFO, vol. 93(4), pages 239-265, 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. Faria, Gonçalo & Verona, Fabio, 2023. "Forecast combination in the frequency domain," Bank of Finland Research Discussion Papers 1/2023, Bank of Finland.
    2. Máximo Camacho & Rafael Doménech, 2012. "MICA-BBVA: a factor model of economic and financial indicators for short-term GDP forecasting," SERIEs: Journal of the Spanish Economic Association, Springer;Spanish Economic Association, vol. 3(4), pages 475-497, December.
    3. Turan G. Bali & Robert F. Engle & Yi Tang, 2017. "Dynamic Conditional Beta Is Alive and Well in the Cross Section of Daily Stock Returns," Management Science, INFORMS, vol. 63(11), pages 3760-3779, November.
    4. Libero Monteforte & Valentina Raponi, 2019. "Short‐term forecasts of economic activity: Are fortnightly factors useful?," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 38(3), pages 207-221, April.
    5. 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.
    6. Büyükşahin, Bahattin & Robe, Michel A., 2014. "Speculators, commodities and cross-market linkages," Journal of International Money and Finance, Elsevier, vol. 42(C), pages 38-70.
    7. Armendáriz Villarreal Thelma & Ramírez Claudia, 2015. "Estimation of a Financial Conditions Index for Mexico," Working Papers 2015-17, Banco de México.
    8. Proietti, Tommaso, 2008. "Estimation of Common Factors under Cross-Sectional and Temporal Aggregation Constraints: Nowcasting Monthly GDP and its Main Components," MPRA Paper 6860, University Library of Munich, Germany.
    9. Christiane Baumeister & Danilo Leiva-León & Eric Sims, 2024. "Tracking Weekly State-Level Economic Conditions," The Review of Economics and Statistics, MIT Press, vol. 106(2), pages 483-504, March.
    10. Rozite, Kristiana & Bezemer, Dirk J. & Jacobs, Jan P.A.M., 2019. "Towards a financial cycle for the U.S., 1973–2014," The North American Journal of Economics and Finance, Elsevier, vol. 50(C).
    11. John W. Galbraith & Greg Tkacz, 2009. "A Note on Monitoring Daily Economic Activity Via Electronic Transaction Data," CIRANO Working Papers 2009s-23, CIRANO.
    12. Timotheos Angelidis & Nikolaos Tessaromatis, 2014. "Global portfolio management under state dependent multiple risk premia," Proceedings of Economics and Finance Conferences 0400966, International Institute of Social and Economic Sciences.
    13. Matthes, Christian & Wang, Mu-Chun, 2012. "What drives inflation in New Keynesian models?," Economics Letters, Elsevier, vol. 114(3), pages 338-342.
    14. Juan M. Londono & Mary Tian, 2014. "Bank Interventions and Options-based Systemic Risk: Evidence from the Global and Euro-area Crisis," International Finance Discussion Papers 1117, Board of Governors of the Federal Reserve System (U.S.).
    15. Sebastian Rondeau, 2012. "Sources of Fluctuations in Emerging Markets: Structural Estimation with Mixed Frequency Data," 2012 Meeting Papers 1156, Society for Economic Dynamics.
    16. Faust, Jon & Wright, Jonathan H., 2009. "Comparing Greenbook and Reduced Form Forecasts Using a Large Realtime Dataset," Journal of Business & Economic Statistics, American Statistical Association, vol. 27(4), pages 468-479.
    17. Baumeister, Christiane & Guérin, Pierre & Kilian, Lutz, 2015. "Do high-frequency financial data help forecast oil prices? The MIDAS touch at work," International Journal of Forecasting, Elsevier, vol. 31(2), pages 238-252.
    18. Valenti, Daniele & Bastianin, Andrea & Manera, Matteo, 2023. "A weekly structural VAR model of the US crude oil market," Energy Economics, Elsevier, vol. 121(C).
    19. Baruník, Jozef & Ellington, Michael, 2024. "Persistence in financial connectedness and systemic risk," European Journal of Operational Research, Elsevier, vol. 314(1), pages 393-407.
    20. Azar, Jose, 2009. "Electric Cars and Oil Prices," MPRA Paper 15538, University Library of Munich, Germany.

    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:wfo:rbrief:y:2020:i:13. 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: Florian Mayr (email available below). General contact details of provider: https://edirc.repec.org/data/wifooat.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.