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Assessing Predictive Content of the KOF Barometer in Real Time

We investigate whether the KOF Barometer–a leading indicator regularly released by the KOF Swiss Economic Institute–can be useful for short-term out-of-sample prediction of year-on-year quarterly real GDP growth rates in Switzerland. We find that the KOF Barometer appears to be useful for prediction of GDP growth rates. Even the earliest forecasts, made seven months ahead of the first official GDP estimate, allow us to predict GDP growth rates more accurately than forecasts based on an univariate autoregressive model. At every subsequent forecast round as new monthly releases of the KOF Barometer become available we observe a steady increase in forecast accuracy.

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Paper provided by KOF Swiss Economic Institute, ETH Zurich in its series KOF Working papers with number 10-249.

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Length: 27 pages
Date of creation: Jan 2010
Date of revision:
Handle: RePEc:kof:wpskof:10-249
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  1. Lemmens, Aurelie & Croux, Christophe & Dekimpe, Marnik G., 2005. "On the predictive content of production surveys: A pan-European study," International Journal of Forecasting, Elsevier, vol. 21(2), pages 363-375.
  2. Jan Jacobs & Jan-Egbert Sturm, 2008. "The information content of KOF indicators on Swiss current account data revisions," OECD Journal: Journal of Business Cycle Measurement and Analysis, OECD Publishing,Centre for International Research on Economic Tendency Surveys, vol. 2008(2), pages 161-181.
  3. Victor Zarnowitz, 1973. "A Review of Cyclical Indicators for the United States: Preliminary Results," NBER Working Papers 0006, National Bureau of Economic Research, Inc.
  4. Sarah M. Rupprecht, 2007. "When Do Firms Adjust Prices? Evidence from Micro Panel Data," KOF Working papers 07-160, KOF Swiss Economic Institute, ETH Zurich.
  5. Richard Etter & Michael Graff, 2003. "Estimating and Forecasting Production and Orders in Manufacturing Industry from Business Survey Data: Evidence from Switzerland, 1990-2003," Swiss Journal of Economics and Statistics (SJES), Swiss Society of Economics and Statistics (SSES), vol. 139(IV), pages 507-533, December.
  6. Christian Müller & Aniela Wirz & Nora Sydow, 2007. "A Note on the Carlson-Parkin Method of Quantifying Qualitative Data Evidence Based on a New Data Set," KOF Working papers 07-168, KOF Swiss Economic Institute, ETH Zurich, revised May 2007.
  7. Oller, Lars-Erik, 1990. "Forecasting the business cycle using survey data," International Journal of Forecasting, Elsevier, vol. 6(4), pages 453-461, December.
  8. Hansson, Jesper & Jansson, Per & Lof, Marten, 2005. "Business survey data: Do they help in forecasting GDP growth?," International Journal of Forecasting, Elsevier, vol. 21(2), pages 377-389.
  9. Croushore, Dean, 2005. "Do consumer-confidence indexes help forecast consumer spending in real time?," The North American Journal of Economics and Finance, Elsevier, vol. 16(3), pages 435-450, December.
  10. Stock, James H & Watson, Mark W, 2002. "Macroeconomic Forecasting Using Diffusion Indexes," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(2), pages 147-62, April.
  11. Balke, Nathan S & Petersen, D'Ann, 2002. "How Well Does the Beige Book Reflect Economic Activity? Evaluating Qualitative Information Quantitatively," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 34(1), pages 114-36, February.
  12. Oller, Lars-Erik & Tallbom, Christer, 1996. "Smooth and timely business cycle indicators for noisy Swedish data," International Journal of Forecasting, Elsevier, vol. 12(3), pages 389-402, September.
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  14. Michael Graff, 2005. "Ein multisektoraler Sammelindikator für die Schweizer Konjunktur," KOF Working papers 05-107, KOF Swiss Economic Institute, ETH Zurich.
  15. Golinelli, Roberto & Parigi, Giuseppe, 2008. "Real-time squared: A real-time data set for real-time GDP forecasting," International Journal of Forecasting, Elsevier, vol. 24(3), pages 368-385.
  16. Lemmens, A. & Croux, C. & Dekimpe, M.G., 2005. "On the Predictive Content of Production Surveys : a Pan-European Study," Other publications TiSEM adab9f0e-7dfd-4dc4-bd92-b, Tilburg University, School of Economics and Management.
  17. Richard Etter & Michael Graff, 2004. "Coincident and Leading Indicators of Manufacturing Industry," Journal of Business Cycle Measurement and Analysis, OECD Publishing,Centre for International Research on Economic Tendency Surveys, vol. 2004(1), pages 109-131.
  18. Francis X. Diebold & Glenn D. Rudebusch, 1989. "Forecasting output with the composite leading index: an ex ante analysis," Finance and Economics Discussion Series 90, Board of Governors of the Federal Reserve System (U.S.).
  19. Klaus Abberger, 2007. "Forecasting Quarter-on-Quarter Changes of German GDP with Monthly Business Tendency Survey Results," Ifo Working Paper Series Ifo Working Paper No. 40, Ifo Institute for Economic Research at the University of Munich.
  20. James H. Stock & Mark W. Watson, 1988. "A Probability Model of The Coincident Economic Indicators," NBER Working Papers 2772, National Bureau of Economic Research, Inc.
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