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The performance of short-term forecasts of the German economy before and during the 2008/2009 recession

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  • Drechsel, Katja
  • Scheufele, Rolf

Abstract

The paper analyzes the forecasting performance of leading indicators for industrial production in Germany. We focus on single and pooled leading indicator models both before and during the financial crisis. Pairwise and joint significant tests are used to evaluate single indicator models, as well as forecast combination methods. In addition, we investigate the stability of forecasting models during the most recent financial crisis. We find that only a small number of single indicator models were performing well before the crisis. Pooling can substantially increase the reliability of leading indicator forecasts. During the crisis, the relative performances of many leading indicator models (e.g. using surveys, term and risk spreads) improved.

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Article provided by Elsevier in its journal International Journal of Forecasting.

Volume (Year): 28 (2012)
Issue (Month): 2 ()
Pages: 428-445

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Handle: RePEc:eee:intfor:v:28:y:2012:i:2:p:428-445
Contact details of provider: Web page: http://www.elsevier.com/locate/ijforecast

Keywords: Macroeconomic forecasting; Evaluating forecasts; Combining forecasts; Structural change;

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Cited by:

  1. David Iselin & Boriss Siliverstovs, 2013. "Using Newspapers for Tracking the Business Cycle: A comparative study for Germany and Switzerland," KOF Working papers 13-337, KOF Swiss Economic Institute, ETH Zurich.
  2. Jörg Döpke & Ulrich Fritsche & Christian Pierdzioch, 2015. "Predicting Recessions in Germany With Boosted Regression Trees," Macroeconomics and Finance Series 201505, Hamburg University, Department Wirtschaft und Politik.
  3. repec:zbw:iwhdps:7-13 is not listed on IDEAS
  4. Christian Seiler, 2014. "Mode Preferences in Business Surveys: Evidence from Germany," Ifo Working Paper Series Ifo Working Paper No. 193, Ifo Institute - Leibniz Institute for Economic Research at the University of Munich.
  5. Katja Drechsel & Rolf Scheufele, 2012. "Bottom-up or Direct? Forecasting German GDP in a Data-rich Environment," Working Papers 2012-16, Swiss National Bank.
  6. Boriss Siliverstovs, 2013. "Do business tendency surveys help in forecasting employment?: A real-time evidence for Switzerland," OECD Journal: Journal of Business Cycle Measurement and Analysis, OECD Publishing,Centre for International Research on Economic Tendency Surveys, vol. 2013(2), pages 129-151.
  7. Lehmann, Robert & Wohlrabe, Klaus, 2013. "Sectoral gross value-added forecasts at the regional level: Is there any information gain?," MPRA Paper 46765, University Library of Munich, Germany.
  8. Christian Seiler & Klaus Wohlrabe, 2013. "Das ifo Geschäftsklima und die deutsche Konjunktur," Ifo Schnelldienst, Ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 66(18), pages 17-21, October.
  9. Schumacher, Christian, 2016. "A comparison of MIDAS and bridge equations," International Journal of Forecasting, Elsevier, vol. 32(2), pages 257-270.
  10. Kitlinski, Tobias & an de Meulen, Philipp, 2015. "The role of targeted predictors for nowcasting GDP with bridge models: Application to the Euro area," Ruhr Economic Papers 559, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
  11. Katja Rietzler & Sabine Stephan, 2012. "Monthly recession predictions in real time: A density forecast approach for German industrial production," IMK Working Paper 94-2012, IMK at the Hans Boeckler Foundation, Macroeconomic Policy Institute.
  12. Katja Drechsel & R. Scheufele, 2013. "Bottom-up or Direct? Forecasting German GDP in a Data-rich Environment," IWH Discussion Papers 7, Halle Institute for Economic Research.
  13. Jens Boysen-Hogrefe, 2012. "A note on predicting recessions in the euro area using real M1," Economics Bulletin, AccessEcon, vol. 32(2), pages 1291-1301.
  14. Christian Seiler, 2014. "On the robustness of balance statistics with respect to nonresponse," OECD Journal: Journal of Business Cycle Measurement and Analysis, OECD Publishing,Centre for International Research on Economic Tendency Surveys, vol. 2014(2), pages 45-62.
  15. Schwarzmüller, Tim, 2015. "Model pooling and changes in the informational content of predictors: An empirical investigation for the euro area," Kiel Working Papers 1982, Kiel Institute for the World Economy (IfW).
  16. Anna Scharschmidt & Klaus Wohlrabe, 2011. "Sektorale Prognosen im Verarbeitenden Gewerbe," Ifo Schnelldienst, Ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 64(22), pages 27-35, November.
  17. Kitlinski, Tobias, 2015. "With or without you: Do financial data help to forecast industrial production?," Ruhr Economic Papers 558, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
  18. Tim Schwarzmüller, 2015. "Model Pooling and Changes in the Informational Content of Predictors: an Empirical Investigation for the Euro Area," Kiel Working Papers 1982, Kiel Institute for the World Economy.
  19. Christian Seiler, 2014. "The determinants of unit non-response in the Ifo Business Survey," AStA Wirtschafts- und Sozialstatistisches Archiv, Springer;Deutsche Statistische Gesellschaft - German Statistical Society, vol. 8(3), pages 161-177, September.
  20. Steffen Henzel & Sebastian Rast, 2013. "Prognoseeigenschaften von Indikatoren zur Vorhersage des Bruttoinlandsprodukts in Deutschland," Ifo Schnelldienst, Ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 66(17), pages 39-46, 09.

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