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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. 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.
    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. Warmedinger, Thomas & Paredes, Joan & Asimakopoulos, Stylianos, 2013. "Forecasting fiscal time series using mixed frequency data," Working Paper Series 1550, European Central Bank.
    5. 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.
    6. 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 Economía Aplicada, Estudios de Economía Aplicada, vol. 33, pages 421-450, Mayo.
    7. 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.
    8. 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.
    9. 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.
    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.

    More about this item

    Keywords

    short-term GDP forecast; bridge model; out-of-sample forecasting accuracy;

    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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