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Forecasting Quarter-on-Quarter Changes of German GDP with Monthly Business Tendency Survey Results

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  • Klaus Abberger

Abstract

Results from business tendency surveys are often used to construct leading indicators. The indicators are then, for example, employed to forecast GDP growth. In this article more detailed results of business tendency surveys are used to forecast quarter-onquarter GDP growth. The target series is very challenging because this type of growth rate leads to quite volatile time series. The present study focuses on German GDP data and survey results provided by the Ifo Institute. Since numerous time series of possible indicators result from the surveys, methods that can handle this setting are applied. One candidate method is principal component analysis, which is used to reduce dimensionality. On the other hand, subset selection procedures are applied. For the present setting the latter method seems more successful than principal components. But this is not a statement about the two types of procedures in general. Which method should be favoured depends very much on the aims of the specific study.

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Bibliographic Info

Paper provided by Ifo Institute for Economic Research at the University of Munich in its series Ifo Working Paper Series with number Ifo Working Paper No. 40.

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Date of creation: 2007
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Handle: RePEc:ces:ifowps:_40

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Related research

Keywords: Business tendency surveys; business cycle analysis; principal component regression; subset selection.;

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References

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  1. repec:fth:inseep:9313 is not listed on IDEAS
  2. Entorf, Horst, 1993. "Constructing leading indicators from non-balanced sectoral business survey series," International Journal of Forecasting, Elsevier, vol. 9(2), pages 211-225, August.
  3. Stefan Mittnik & Peter A. Zadrozny, 2004. "Forecasting Quarterly German GDP at Monthly Intervals Using Monthly IFO Business Conditions Data," CESifo Working Paper Series 1203, CESifo Group Munich.
  4. Bair, Eric & Hastie, Trevor & Paul, Debashis & Tibshirani, Robert, 2006. "Prediction by Supervised Principal Components," Journal of the American Statistical Association, American Statistical Association, vol. 101, pages 119-137, March.
  5. Rünstler, Gerhard & Sédillot, Franck, 2003. "Short-term estimates of euro area real GDP by means of monthly data," Working Paper Series 0276, European Central Bank.
  6. Baffigi, Alberto & Golinelli, Roberto & Parigi, Giuseppe, 2004. "Bridge models to forecast the euro area GDP," International Journal of Forecasting, Elsevier, vol. 20(3), pages 447-460.
  7. Stock, James H. & Watson, Mark W., 2006. "Forecasting with Many Predictors," Handbook of Economic Forecasting, Elsevier.
  8. Stock J.H. & Watson M.W., 2002. "Forecasting Using Principal Components From a Large Number of Predictors," Journal of the American Statistical Association, American Statistical Association, vol. 97, pages 1167-1179, December.
  9. Klaus Abberger & Klaus Wohlrabe, 2006. "Einige Prognoseeigenschaften des ifo Geschäftsklimas - Ein Überblick über die neuere wissenschaftliche Literatur," Ifo Schnelldienst, Ifo Institute for Economic Research at the University of Munich, vol. 59(22), pages 19-26, November.
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Citations

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Cited by:
  1. Sascha O. Becker & Klaus Wohlrabe, 2007. "Micro Data at the Ifo Institute for Economic Research – The “Ifo Business Survey”, Usage and Access," Ifo Working Paper Series Ifo Working Paper No. 47, Ifo Institute for Economic Research at the University of Munich.
  2. Klaus Abberger & Sascha O. Becker & Barbara Hofmann & Klaus Wohlrabe, 2007. "Mikrodaten im ifo Institut für Wirtschaftsforschung: Bestand, Verwendung, Zugang," Ifo Working Paper Series Ifo Working Paper No. 44, Ifo Institute for Economic Research at the University of Munich.
  3. Boriss Siliverstovs, 2010. "Assessing Predictive Content of the KOF Barometer in Real Time," KOF Working papers 10-249, KOF Swiss Economic Institute, ETH Zurich.
  4. António Brandão Moniz, 2008. "Assessing scenarios on the future of work," Enterprise and Work Innovation Studies, Universidade Nova de Lisboa, IET/CESNOVA-Research on Enterprise and Work Innovation, Faculty of Science and Technology, vol. 4(4), pages 91-106, November.
  5. Antipa, P. & Barhoumi, K. & Brunhes-Lesage, V. & Darné, O., 2012. "Nowcasting German GDP: A comparison of bridge and factor models," Working papers 401, Banque de France.
  6. Sascha O. Becker & Klaus Wohlrabe, 2008. "European Data Watch: Micro Data at the Ifo Institute for Economic Research – The “Ifo Business Survey”, Usage and Access," Schmollers Jahrbuch : Journal of Applied Social Science Studies / Zeitschrift für Wirtschafts- und Sozialwissenschaften, Duncker & Humblot, Berlin, vol. 128(2), pages 307-319.

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