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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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    References listed on IDEAS

    as
    1. Espasa, Antoni & Senra, Eva & Albacete, Rebeca, 2000. "Forecasting monetary union inflation: a disaggregated approach by countries and by sectors," DES - Working Papers. Statistics and Econometrics. WS 10143, Universidad Carlos III de Madrid. Departamento de Estadística.
    2. Canova, Fabio & Ciccarelli, Matteo, 2004. "Forecasting and turning point predictions in a Bayesian panel VAR model," Journal of Econometrics, Elsevier, vol. 120(2), pages 327-359, June.
    3. Michael Ehrmann & Leonardo Gambacorta & Jorge Mart�nez-Pag�s & Patrick Sevestre & Andreas Worms, 2001. "Fynancial Systems and the Role of Banks in Monetary Policy Transmission in the Euro area," Temi di discussione (Economic working papers) 432, Bank of Italy, Economic Research and International Relations Area.
    4. Giuseppe Parigi & Roberto Golinelli & Giorgio Bodo, 2000. "Forecasting industrial production in the Euro area," Empirical Economics, Springer, vol. 25(4), pages 541-561.
    5. Christoffersen, Peter F & Diebold, Francis X, 1998. "Cointegration and Long-Horizon Forecasting," Journal of Business & Economic Statistics, American Statistical Association, vol. 16(4), pages 450-458, October.
    6. Stark, Tom & Croushore, Dean, 2002. "Forecasting with a real-time data set for macroeconomists," Journal of Macroeconomics, Elsevier, vol. 24(4), pages 507-531, December.
    7. Croushore, Dean & Stark, Tom, 2001. "A real-time data set for macroeconomists," Journal of Econometrics, Elsevier, vol. 105(1), pages 111-130, November.
    8. Harvey, David I & Leybourne, Stephen J & Newbold, Paul, 1998. "Tests for Forecast Encompassing," Journal of Business & Economic Statistics, American Statistical Association, vol. 16(2), pages 254-259, April.
    9. Luca Dedola & Eugenio Gaiotti & Luca Silipo, 2001. "Money demand in the euro area: do national differences matter?," Temi di discussione (Economic working papers) 405, Bank of Italy, Economic Research and International Relations Area.
    10. Franses, Philip Hans & Kleibergen, Frank, 1996. "Unit roots in the Nelson-Plosser data: Do they matter for forecasting?," International Journal of Forecasting, Elsevier, vol. 12(2), pages 283-288, June.
    11. Fabio Bagliano & Roberto Golinelli & Claudio Morana, 2002. "Core inflation in the Euro area," Applied Economics Letters, Taylor & Francis Journals, vol. 9(6), pages 353-357.
    12. Kwiatkowski, Denis & Phillips, Peter C. B. & Schmidt, Peter & Shin, Yongcheol, 1992. "Testing the null hypothesis of stationarity against the alternative of a unit root : How sure are we that economic time series have a unit root?," Journal of Econometrics, Elsevier, vol. 54(1-3), pages 159-178.
    13. Filippo Altissimo & Domenico J. Marchetti & Gian Paolo Oneto, 2000. "The Italian Business Cycle: Coincident and Leading Indicators and Some Stylized Facts," Giornale degli Economisti, GDE (Giornale degli Economisti e Annali di Economia), Bocconi University, vol. 59(2), pages 147-220, September.
    14. Lutkepohl, Helmut, 1982. "Non-causality due to omitted variables," Journal of Econometrics, Elsevier, vol. 19(2-3), pages 367-378, August.
    15. Diebold, Francis X & Mariano, Roberto S, 2002. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 134-144, January.
    16. Tashman, Leonard J., 2000. "Out-of-sample tests of forecasting accuracy: an analysis and review," International Journal of Forecasting, Elsevier, vol. 16(4), pages 437-450.
    17. Irac, D. & Sédillot, F., 2002. "Short-Run Assessment of French Economic Activity Using OPTIM," Working papers 88, Banque de France.
    18. Norman R. Swanson & Jeffery D. Amato, 2000. "The real-time predictive content of money for output," BIS Working Papers 96, Bank for International Settlements.
    19. Maximo Camacho & Gabriel Perez-Quiros, 2002. "This is what the leading indicators lead," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 17(1), pages 61-80.
    20. Fabio Busetti, 2001. "The use of preliminary data in econometric forecasting: an application with the Bank of Italy Quarterly Model," Temi di discussione (Economic working papers) 437, Bank of Italy, Economic Research and International Relations Area.
    21. David F. Hendry & Michael P. Clements, 2004. "Pooling of forecasts," Econometrics Journal, Royal Economic Society, vol. 7(1), pages 1-31, June.
    22. Michael P. Clements & David F.Hendry, 2001. "Forecasting with difference-stationary and trend-stationary models," Econometrics Journal, Royal Economic Society, vol. 4(1), pages 1-19.
    23. Newbold, Paul & Leybourne, Stephen & Wohar, Mark E., 2001. "Trend-stationarity, difference-stationarity, or neither: further diagnostic tests with an application to U.S. Real GNP, 1875-1993," Journal of Economics and Business, Elsevier, vol. 53(1), pages 85-102.
    24. Gabriel Fagan & JÊrÆme Henry, 1998. "Long run money demand in the EU: Evidence for area-wide aggregates," Empirical Economics, Springer, vol. 23(3), pages 483-506.
    25. Harvey, David & Leybourne, Stephen & Newbold, Paul, 1997. "Testing the equality of prediction mean squared errors," International Journal of Forecasting, Elsevier, vol. 13(2), pages 281-291, June.
    26. Granger, Clive W.J. & YOON, GAWON, 2001. "Self-Generating Variables in a Cointegrated VAR Framework," University of California at San Diego, Economics Working Paper Series qt6010k0xn, Department of Economics, UC San Diego.
    27. Diebold, Francis X & Kilian, Lutz, 2000. "Unit-Root Tests Are Useful for Selecting Forecasting Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 18(3), pages 265-273, July.
    28. Marcellino, Massimiliano & Stock, James H. & Watson, Mark W., 2003. "Macroeconomic forecasting in the Euro area: Country specific versus area-wide information," European Economic Review, Elsevier, vol. 47(1), pages 1-18, February.
    29. Faust, Jon & Rogers, John H & Wright, Jonathan H, 2005. "News and Noise in G-7 GDP Announcements," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 37(3), pages 403-419, June.
    30. Eitrheim, Oyvind & Husebo, Tore Anders & Nymoen, Ragnar, 1999. "Equilibrium-correction vs. differencing in macroeconometric forecasting," Economic Modelling, Elsevier, vol. 16(4), pages 515-544, December.
    31. Roberta Zizza, 2002. "Forecasting the industrial production index for the euro area through forecasts for the main countries," Temi di discussione (Economic working papers) 441, Bank of Italy, Economic Research and International Relations Area.
    32. Johansen, Soren, 1995. "Likelihood-Based Inference in Cointegrated Vector Autoregressive Models," OUP Catalogue, Oxford University Press, number 9780198774501.
    33. Giacomini, Raffaella & Granger, Clive W. J., 2004. "Aggregation of space-time processes," Journal of Econometrics, Elsevier, vol. 118(1-2), pages 7-26.
    34. Sharon Kozicki, 2001. "Implications of real-time data for forecasting and modeling expectations," Research Working Paper RWP 01-12, Federal Reserve Bank of Kansas City.
    35. Roberto Golinelli & Sergio Pastorello, 2002. "Modelling the demand for M3 in the Euro area," The European Journal of Finance, Taylor & Francis Journals, vol. 8(4), pages 371-401.
    36. Paolo carnazza & Giuseppe Parigi, 2001. "The Evolution of Confidence for European Consumers and Businesses in France, Germany and Italy," Temi di discussione (Economic working papers) 406, Bank of Italy, Economic Research and International Relations Area.
    37. Michael P. Clements & David F. Hendry, 2001. "Forecasting Non-Stationary Economic Time Series," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262531895, December.
    38. James H. Stock & Mark W. Watson, 1998. "A Comparison of Linear and Nonlinear Univariate Models for Forecasting Macroeconomic Time Series," NBER Working Papers 6607, National Bureau of Economic Research, Inc.
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    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. 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.
    4. 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.
    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. 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.
    7. 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.
    8. Doll, Jens & Rosenthal, Beatrice & Volkenand, Jonas & Hamella, Sandra, 2017. "Nowcasting des deutschen BIP," Weidener Diskussionspapiere 59, University of Applied Sciences Amberg-Weiden (OTH).
    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. Warmedinger, Thomas & Paredes, Joan & Asimakopoulos, Stylianos, 2013. "Forecasting fiscal time series using mixed frequency data," Working Paper Series 1550, European Central Bank.
    11. 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.
    12. 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.

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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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