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Real-time GDP forecasting in the euro area

Author

Listed:
  • Alberto Baffigi

    (Bank of Italy, Economic Research Department)

  • Roberto Golinelli

    (University of Bologna, Department of Economics)

  • Giuseppe Parigi

    (Bank of Italy, Economic Research Department)

Abstract

Quantitative information on the current state of the economy is crucial to economic policy-making, but the quarterly national accounts data for GDP in the euro area are released with a significant delay. This paper presents alternative models for the real-time forecasting of euro area GDP and assesses their performance. We estimate univariate/multivariate statistical models, bridge models (systems of autoregressive distributed lags equations with indicators) and a small structural model. The models are estimated for aggregate GDP and components both area-wide and for the three main countries. They are estimated and tested for the period 1980-1999. Data from 1999 to 2001 are used to compare the forecasting ability, gauged by rolling-origin one-step-ahead errors.

Suggested Citation

  • Alberto Baffigi & Roberto Golinelli & Giuseppe Parigi, 2002. "Real-time GDP forecasting in the euro area," Temi di discussione (Economic working papers) 456, Bank of Italy, Economic Research and International Relations Area.
  • Handle: RePEc:bdi:wptemi:td_456_02
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    Cited by:

    1. Bruno Giancarlo & Lupi Claudio, 2003. "Forecasting Euro-Area Industrial Production Using (Mostly) Business Surveys Data," ISAE Working Papers 33, ISTAT - Italian National Institute of Statistics - (Rome, ITALY).
    2. Stylianos Asimakopoulos & Joan Paredes & Thomas Warmedinger, 2020. "Real‐Time Fiscal Forecasting Using Mixed‐Frequency Data," Scandinavian Journal of Economics, Wiley Blackwell, vol. 122(1), pages 369-390, January.
    3. Doll, Jens & Rosenthal, Beatrice & Volkenand, Jonas & Hamella, Sandra, 2017. "Nowcasting des deutschen BIP," Weidener Diskussionspapiere 59, University of Applied Sciences Amberg-Weiden (OTH).
    4. Emilia Bonaccorsi di Patti & Giorgio Gobbi, 2003. "The effects of bank mergers on credit availability: evidence from corporate data," Temi di discussione (Economic working papers) 479, Bank of Italy, Economic Research and International Relations Area.
    5. Castilla, Adolfo, 2015. "Proyecto LINK y Econometría de Alta Frecuencia: Las últimas aportaciones econométricas de Lawrence R. Klein /LINK Project and High Frequency Econometrics: Recent Econometric Contributions of Lawrence ," Estudios de Economia Aplicada, Estudios de Economia Aplicada, vol. 33, pages 421-450, Mayo.
    6. Paolo Angelini & Paolo Del Giovane & Stefano Siviero & Daniele Terlizzese, 2002. "Monetary Policy Rules for the Euro Area: What Role for National Information?," Temi di discussione (Economic working papers) 457, Bank of Italy, Economic Research and International Relations Area.
    7. Warmedinger, Thomas & Paredes, Joan & Asimakopoulos, Stylianos, 2013. "Forecasting fiscal time series using mixed frequency data," Working Paper Series 1550, European Central Bank.
    8. Attar, Andrea & Campioni, Eloisa, 2003. "Costly state verification and debt contracts: a critical resume," Research in Economics, Elsevier, vol. 57(4), pages 315-343, December.
    9. Esteves, Paulo Soares, 2013. "Direct vs bottom–up approach when forecasting GDP: Reconciling literature results with institutional practice," Economic Modelling, Elsevier, vol. 33(C), pages 416-420.
    10. Giacomo Sbrana, 2007. "Testing for Model Selection in Predicting Aggregate Variables," Giornale degli Economisti, GDE (Giornale degli Economisti e Annali di Economia), Bocconi University, vol. 66(1), pages 3-28, March.
    11. Oliver Hülsewig & Johannes Mayr & Stéphane Sorbe, 2007. "Assessing the Forecast Properties of the CESifo World Economic Climate Indicator: Evidence for the Euro Area," ifo Working Paper Series 46, ifo Institute - Leibniz Institute for Economic Research at the University of Munich.
    12. Rünstler, Gerhard & Sédillot, Franck, 2003. "Short-term estimates of euro area real GDP by means of monthly data," Working Paper Series 276, European Central Bank.

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    More about this item

    Keywords

    short-term GDP forecast; bridge model; out-of-sample forecasting accuracy;
    All these keywords.

    JEL classification:

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

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