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Using Newspapers for Tracking the Business Cycle: A comparative study for Germany and Switzerland

On the basis of keyword searches in newspaper articles several versions of the Recession-word Index (RWI) are constructed for Germany and Switzerland. We use these indices in order to track the business cycle dynamics in these two countries. Our main findings are the following. First, we show that augmenting benchmark autoregressive models with the RWI generally leads to improvement in accuracy of one-step ahead forecasts of GDP growth compared to those obtained by the benchmark model. Second, the accuracy of out-of-sample forecasts obtained with models augmented with the RWI is comparable to that of models augmented with established economic indicators in both countries, such as the Ifo Business Climate Index and the ZEW Indicator of Economic Sentiment for Germany, and the KOF Economic Barometer and the Purchasing Managers Index in manufacturing for Switzerland. Third, we show that the RWI-based forecasts are more accurate than the consensus forecasts (published by Consensus Economics Inc.) for Switzerland, whereas we reach the opposite conclusion for Germany. In fact, the accuracy of the consensus forecasts of GDP growth for Germany appears to be superior to that of any other indicator considered in our study. These results are robust to changes in estimation/forecast samples, the use of rolling vs expanding estimation windows, and the inclusion of a web-based recession indicator extracted from Google Trends into a set of the competing models.

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Paper provided by KOF Swiss Economic Institute, ETH Zurich in its series KOF Working papers with number 13-337.

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Length: 36 pages
Date of creation: Jun 2013
Date of revision:
Handle: RePEc:kof:wpskof:13-337
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  1. Nikos Askitas & Klaus F. Zimmermann, 2009. "Google Econometrics and Unemployment Forecasting," Discussion Papers of DIW Berlin 899, DIW Berlin, German Institute for Economic Research.
  2. Drechsel, Katja & Scheufele, Rolf, 2012. "The performance of short-term forecasts of the German economy before and during the 2008/2009 recession," International Journal of Forecasting, Elsevier, vol. 28(2), pages 428-445.
  3. Kholodilin, Konstantin A. & Siliverstovs, Boriss, 2012. "Measuring regional inequality by internet car price advertisements: Evidence for Germany," Economics Letters, Elsevier, vol. 116(3), pages 414-417.
  4. Matthias W. Uhl, 2011. "Nowcasting Private Consumption with TV Sentiment," KOF Working papers 11-293, KOF Swiss Economic Institute, ETH Zurich.
  5. Jan Grossarth-Maticek & Johannes Mayr, 2008. "Medienberichte als Konjunkturindikator," Ifo Schnelldienst, Ifo Institute for Economic Research at the University of Munich, vol. 61(07), pages 17-29, 04.
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  7. David Iselin & Boriss Siliverstovs, 2013. "The R-word index for Switzerland," Applied Economics Letters, Taylor & Francis Journals, vol. 20(11), pages 1032-1035, July.
  8. Michael Funke & Harm Bandholz, 2003. "In search of leading indicators of economic activity in Germany," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 22(4), pages 277-297.
  9. Kenneth D. West & Todd Clark, 2006. "Approximately Normal Tests for Equal Predictive Accuracy in Nested Models," NBER Technical Working Papers 0326, National Bureau of Economic Research, Inc.
  10. Evan F. Koenig & Sheila Dolmas & Jeremy Piger, 2003. "The Use and Abuse of Real-Time Data in Economic Forecasting," The Review of Economics and Statistics, MIT Press, vol. 85(3), pages 618-628, August.
  11. McCracken, Michael W., 2007. "Asymptotics for out of sample tests of Granger causality," Journal of Econometrics, Elsevier, vol. 140(2), pages 719-752, October.
  12. Konstantin A. Kholodilin & Maximilian Podstawski & Boriss Siliverstovs, 2010. "Do Google Searches Help in Nowcasting Private Consumption? A Real-Time Evidence for the US," KOF Working papers 10-256, KOF Swiss Economic Institute, ETH Zurich.
  13. Paul C. Tetlock, 2007. "Giving Content to Investor Sentiment: The Role of Media in the Stock Market," Journal of Finance, American Finance Association, vol. 62(3), pages 1139-1168, 06.
  14. Ammann, Manuel & Frey, Roman & Verhofen, Michael, 2012. "Do Newspaper Articles Predict Aggregate Stock Returns?," Working Papers on Finance 1204, University of St. Gallen, School of Finance.
  15. Konstantin A. Kholodilin & Boriss Siliverstovs, 2005. "On the Forecasting Properties of the Alternative Leading Indicators for the German GDP: Recent Evidence," Discussion Papers of DIW Berlin 522, DIW Berlin, German Institute for Economic Research.
  16. Francesco D’Amuri & Juri Marcucci, 2010. "“Google it!”Forecasting the US Unemployment Rate with a Google Job Search index," Working Papers 2010.31, Fondazione Eni Enrico Mattei.
  17. Massimiliano Marcellino & Christian Schumacher, 2010. "Factor MIDAS for Nowcasting and Forecasting with Ragged-Edge Data: A Model Comparison for German GDP," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 72(4), pages 518-550, 08.
  18. Mark Doms & Norman Morin, 2004. "Consumer sentiment, the economy, and the news media," Finance and Economics Discussion Series 2004-51, Board of Governors of the Federal Reserve System (U.S.).
  19. Harvey, David & Leybourne, Stephen & Newbold, Paul, 1997. "Testing the equality of prediction mean squared errors," International Journal of Forecasting, Elsevier, vol. 13(2), pages 281-291, June.
  20. Harvey, David I & Leybourne, Stephen J & Newbold, Paul, 1998. "Tests for Forecast Encompassing," Journal of Business & Economic Statistics, American Statistical Association, vol. 16(2), pages 254-59, April.
  21. Mark Doms, 2004. "Consumer sentiment and the media," FRBSF Economic Letter, Federal Reserve Bank of San Francisco, issue oct22.
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