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

  • Maxime Leboeuf
  • Louis Morel
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    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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    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. Angelini, Elena & Camba-Mendez, Gonzalo & Giannone, Domenico & Reichlin, Lucrezia & Rünstler, Gerhard, 2008. "Short-term Forecasts of Euro Area GDP Growth," CEPR Discussion Papers 6746, C.E.P.R. Discussion Papers.
    2. Diebold, Francis X & Mariano, Roberto S, 2002. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 134-44, January.
    3. 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.
    4. Godbout, Claudia & Lombardi, Marco J., 2012. "Short-term forecasting of the Japanese economy using factor models," Working Paper Series 1428, European Central Bank.
    5. repec:ecb:ecbwps:20111428 is not listed on IDEAS
    6. Banbura, Marta & Giannone, Domenico & Modugno, Michele & Reichlin, Lucrezia, 2012. "Now-casting and the real-time data flow," CEPR Discussion Papers 9112, C.E.P.R. Discussion Papers.
    7. David Hendry & Michael P. Clements, 2001. "Pooling of Forecasts," Economics Papers 2002-W9, Economics Group, Nuffield College, University of Oxford.
    8. 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.
    9. 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.
    10. Foroni, Claudia & Marcellino, Massimiliano & Schumacher, Christian, 2011. "U-MIDAS: MIDAS regressions with unrestricted lag polynomials," Discussion Paper Series 1: Economic Studies 2011,35, Deutsche Bundesbank, Research Centre.
    11. Claudia Godbout & Jocelyn Jacob, 2010. "Le pouvoir de prévision des indices PMI," Discussion Papers 10-3, Bank of Canada.
    12. Isabel Yi Zheng & James Rossiter, 2006. "Using Monthly Indicators to Predict Quarterly GDP," Working Papers 06-26, Bank of Canada.
    13. James Rossiter, 2010. "Nowcasting the Global Economy," Discussion Papers 10-12, Bank of Canada.
    14. 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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