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Forecasting Short-Term Real GDP Growth in the Euro Area and Japan Using Unrestricted MIDAS Regressions

  • Maxime Leboeuf
  • Louis Morel
Registered author(s):

    In this paper, the authors develop a new tool to improve the short-term forecasting of real GDP growth in the euro area and Japan. This new tool, which uses unrestricted mixed-data sampling (U-MIDAS) regressions, allows an evaluation of the usefulness of a wide range of indicators in predicting short-term real GDP growth. In line with previous Bank studies, the results suggest that the purchasing managers’ index (PMI) is among the best-performing indicators to forecast real GDP growth in the euro area, while consumption indicators and business surveys (the PMI and the Economy Watchers Survey) have the most predictive power for Japan. Moreover, the results indicate that combining the predictions from a number of indicators improves forecast accuracy and can be an effective way to mitigate the volatility associated with monthly indicators. Overall, our preferred U-MIDAS model specification performs well relative to various benchmark models and forecasters.

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    File URL: http://www.bankofcanada.ca/wp-content/uploads/2014/06/dp2014-3.pdf
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    Paper provided by Bank of Canada in its series Discussion Papers with number 14-3.

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    Length: 32 pages
    Date of creation: 2014
    Date of revision:
    Handle: RePEc:bca:bocadp:14-3
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    1. Martha Banbura & Domenico Giannone & Michèle Modugno & Lucrezia Reichlin, 2012. "Now-Casting and the Real-Time Data Flow," Working Papers ECARES ECARES 2012-026, ULB -- Universite Libre de Bruxelles.
    2. Michael P. Clements & Ana Beatriz Galvao, 2009. "Forecasting US output growth using leading indicators: an appraisal using MIDAS models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 24(7), pages 1187-1206.
    3. Diebold, Francis X & Mariano, Roberto S, 1995. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 13(3), pages 253-63, July.
    4. Isabel Yi Zheng & James Rossiter, 2006. "Using Monthly Indicators to Predict Quarterly GDP," Working Papers 06-26, Bank of Canada.
    5. Elena Angelini & Gonzalo Camba‐Mendez & Domenico Giannone & Lucrezia Reichlin & Gerhard Rünstler, 2011. "Short‐term forecasts of euro area GDP growth," Econometrics Journal, Royal Economic Society, vol. 14, pages C25-C44, 02.
    6. repec:ecb:ecbwps:20111428 is not listed on IDEAS
    7. David Hendry & Michael Clements, 2001. "Pooling of Forecasts," Economics Series Working Papers 2002-W09, University of Oxford, Department of Economics.
    8. Godbout, Claudia & Lombardi, Marco J., 2012. "Short-term forecasting of the Japanese economy using factor models," Working Paper Series 1428, European Central Bank.
    9. Mark W. Watson & James H. Stock, 2004. "Combination forecasts of output growth in a seven-country data set," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 23(6), pages 405-430.
    10. Claudia Godbout & Jocelyn Jacob, 2010. "Le pouvoir de prévision des indices PMI," Discussion Papers 10-3, Bank of Canada.
    11. Foroni, Claudia & Marcellino, Massimiliano & Schumacher, Christian, 2012. "U-MIDAS: MIDAS regressions with unrestricted lag polynomials," CEPR Discussion Papers 8828, C.E.P.R. Discussion Papers.
    12. Eleonora Granziera & Corinne Luu & Pierre St-Amant, 2013. "The Accuracy of Short-Term Forecast Combinations," Bank of Canada Review, Bank of Canada, vol. 2013(Summer), pages 13-21.
    13. Vladimir Kuzin & Massimiliano Marcellino & Christian Schumacher, 2013. "Pooling Versus Model Selection For Nowcasting Gdp With Many Predictors: Empirical Evidence For Six Industrialized Countries," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 28(3), pages 392-411, 04.
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