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The role of survey data in nowcasting euro area GDP growth

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  • Alessandro Girardi
  • Andreas Reuter
  • Christian Gayer

Abstract

This paper evaluates the impact of new releases of financial, real activity and survey data on the nowcasting of euro area GDP growth. We show that financial data are only essential for improving nowcasting in the first two months of a nowcast quarter. This contrasts with survey and real data, which are indispensable components throughout the entire nowcasting exercise. When treating variables as if they were all published at the same time and without any time lag, financial series lose all their significance, while survey data remain important. This evidence suggests that survey data offer more than just timeliness for the purpose of nowcasting GDP growth. The latter holds true for financial data only when restricting the analysis to the 2008-09 financial crisis.

Suggested Citation

  • Alessandro Girardi & Andreas Reuter & Christian Gayer, 2014. "The role of survey data in nowcasting euro area GDP growth," European Economy - Economic Papers 2008 - 2015 538, Directorate General Economic and Financial Affairs (DG ECFIN), European Commission.
  • Handle: RePEc:euf:ecopap:0538
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    Cited by:

    1. repec:eee:ecmode:v:64:y:2017:i:c:p:26-39 is not listed on IDEAS
    2. Johanna Garnitz & Robert Lehmann & Klaus Wohlrabe, 2019. "Forecasting GDP all over the world using leading indicators based on comprehensive survey data," CESifo Working Paper Series 7691, CESifo Group Munich.
    3. Evzen Kocenda & Karen Poghosyan, 2018. "Nowcasting real GDP growth with business tendency surveys data: A cross country analysis," KIER Working Papers 1002, Kyoto University, Institute of Economic Research.
    4. Siliverstovs, Boriss, 2017. "Dissecting models' forecasting performance," Economic Modelling, Elsevier, vol. 67(C), pages 294-299.
    5. repec:taf:applec:v:50:y:2018:i:42:p:4540-4555 is not listed on IDEAS
    6. Werner Hölzl & Gerhard Schwarz, 2014. "Der WIFO-Konjunkturtest: Methodik und Prognoseeigenschaften," WIFO Monatsberichte (monthly reports), WIFO, vol. 87(12), pages 835-850, December.
    7. Garnitz, Johanna & Lehmann, Robert & Wohlrabe, Klaus, 2017. "Forecasting GDP all over the World: Evidence from Comprehensive Survey Data," MPRA Paper 81772, University Library of Munich, Germany.
    8. Mogliani, Matteo & Darné, Olivier & Pluyaud, Bertrand, 2017. "The new MIBA model: Real-time nowcasting of French GDP using the Banque de France's monthly business survey," Economic Modelling, Elsevier, vol. 64(C), pages 26-39.
    9. Simón Sosvilla-Rivero & María del Carmen Ramos-Herrera, 2018. "Inflation, real economic growth and unemployment expectations: an empirical analysis based on the ECB survey of professional forecasters," Applied Economics, Taylor & Francis Journals, vol. 50(42), pages 4540-4555, September.

    More about this item

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications

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