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Forecasting economic activity in Germany: how useful are sentiment indicators?

  • Schröder, Michael
  • Hüfner, Felix P.

We analyze four economic sentiment indicators for the German economy regarding their ability to forecast economic activity. Using cross correlations and Granger causality tests we find that the ifo business expectations (ifo), the Purchasing Managers Index (PMI) and the ZEW Indicator of Economic Sentiment (ZEW) lead the yearon-year growth rate of German industrial production by five months. Taking into account the publication lag of industrial production this lead is even larger. On the contrary, the European Commission?s Economic Sentiment Indicator (ESIN) does not exhibit a lead but rather seems to coincide or even lag economic activity. Analyzing lead/lag structures among the indicators we find that the ZEW indicator leads the ifo business expectations significantly by one month and that the latter has a onemonth lead over the PMI. Out-of-sample forecast evaluations suggest that both ifo and ZEW provide the best forecasts for industrial production among the three indicators ifo, PMI and ZEW. It is found that the ZEW indicator performs better than the ifo and PMI over the whole sample (Jan. 1994 – Mar. 2002) and especially over horizons from six to twelve months. The ifo expectations predict better at shorter horizons (up to three months) and is superior to the ZEW and PMI indicator when a shorter sample (Jan. 1998 – Mar. 2002) is regarded.

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Paper provided by ZEW - Zentrum für Europäische Wirtschaftsforschung / Center for European Economic Research in its series ZEW Discussion Papers with number 02-56.

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Date of creation: 2002
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Handle: RePEc:zbw:zewdip:566
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  1. Kwiatkowski, D. & Phillips, P.C.B. & Schmidt, P., 1990. "Testing the Null Hypothesis of Stationarity Against the Alternative of Unit Root : How Sure are we that Economic Time Series have a Unit Root?," Papers 8905, Michigan State - Econometrics and Economic Theory.
  2. Ulrich Fritsche & Sabine Stephan, 2000. "Leading Indicators of German Business Cycles: An Assessment of Properties," Macroeconomics 0004005, EconWPA.
  3. repec:att:wimass:9220 is not listed on IDEAS
  4. Newey, Whitney & West, Kenneth, 2014. "A simple, positive semi-definite, heteroscedasticity and autocorrelation consistent covariance matrix," Applied Econometrics, Publishing House "SINERGIA PRESS", vol. 33(1), pages 125-132.
  5. Granger, C W J, 1969. "Investigating Causal Relations by Econometric Models and Cross-Spectral Methods," Econometrica, Econometric Society, vol. 37(3), pages 424-38, July.
  6. Norbert Funke, 1997. "Predicting recessions: Some evidence for Germany," Review of World Economics (Weltwirtschaftliches Archiv), Springer, vol. 133(1), pages 90-102, March.
  7. Newey, Whitney K & West, Kenneth D, 1994. "Automatic Lag Selection in Covariance Matrix Estimation," Review of Economic Studies, Wiley Blackwell, vol. 61(4), pages 631-53, October.
  8. Ulrich Fritsche, 1999. "Vorlaufeigenschaften von Ifo-Indikatoren für Westdeutschland," Discussion Papers of DIW Berlin 179, DIW Berlin, German Institute for Economic Research.
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