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Prognosegehalt von ifo-Geschäftserwartungen und ZEW-Konjunkturerwartungen: Ein ökonometrischer Vergleich / Forecasting German industrial Production: An Econometric Comparison of ifo- and ZEW-Business Expectations

Author

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  • Hüfner Felix P.

    (Dipl.-Volkw., Zentrum für Europäische Wirtschaftsforschung, (ZEW), Forschungsbereich „Internationale Finanzmärkte und Finanzmanagement”, Postfach 103443, D-68034 Mannheim)

  • Schröder Michael

    (Zentrum für Europäische Wirtschaftsforschung, (ZEW), Forschungsbereich „Internationale Finanzmärkte und Finanzmanagement”, Postfach 103443, D-68034 Mannheim)

Abstract

We compare the forecasting ability of the ifo-business expectations and ZEW-business expectations for the German industrial production in detail. Both are qualitative monthly surveys. While the ifo indicator is based on surveys of enterprises, the ZEW polls financial analysts from banks, insurances and large industrial companies. Using Granger causality tests we find a significant one-month lead of the ZEW-expectations over the ifo-expectations. Furthermore we find that the use of ZEW-expectations allows for longer term forecasts of German industrial production. For a forecast period of three to twelve months the ZEW-expectations significantly outperform a naive forecast (which is simply based upon its own lagged values) of German industrial production as well as the forecasts based on the ifo-expectations. The ifo-expectations provide slightly better forecasts for short term periods (one month). We suggest that this difference in forecast ability is due to the different participants of the surveys: the financial analysts from the ZEW survey might incorporate more macroeconomic factors when building their expectations, thereby allowing longer term forecasts than the enterprises that take part in the ifo survey. However, the latter are supposed to forecast the immediate future better than the analysts as they have a better knowledge of the present situation of their business. Finally, using encompassing tests we show that a combination of both indicators results in better medium-term forecasts (three to six months) of the German industrial production than using both indicators alone.

Suggested Citation

  • Hüfner Felix P. & Schröder Michael, 2002. "Prognosegehalt von ifo-Geschäftserwartungen und ZEW-Konjunkturerwartungen: Ein ökonometrischer Vergleich / Forecasting German industrial Production: An Econometric Comparison of ifo- and ZEW-Business ," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 222(3), pages 316-336, June.
    • Handle: RePEc:jns:jbstat:v:222:y:2002:i:3:p:316-336
    DOI: 10.1515/jbnst-2002-0303
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    1. Werner H. Strigel, 1997. "Seit 25 Jahren: das ifo Geschäftsklima als Konjunkturindikator," ifo Schnelldienst, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 50(27), pages 3-4, October.
    2. Norbert Funke, 1997. "Predicting recessions: Some evidence for Germany," Review of World Economics (Weltwirtschaftliches Archiv), Springer;Institut für Weltwirtschaft (Kiel Institute for the World Economy), vol. 133(1), pages 90-102, March.
    3. Whitney K. Newey & Kenneth D. West, 1994. "Automatic Lag Selection in Covariance Matrix Estimation," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 61(4), pages 631-653.
    4. Kwiatkowski, Denis & Phillips, Peter C. B. & Schmidt, Peter & Shin, Yongcheol, 1992. "Testing the null hypothesis of stationarity against the alternative of a unit root : How sure are we that economic time series have a unit root?," Journal of Econometrics, Elsevier, vol. 54(1-3), pages 159-178.
    5. Ulrich Fritsche & Sabine Stephan, 2000. "Leading Indicators of German Business Cycles: An Assessment of Properties," Macroeconomics 0004005, University Library of Munich, Germany.
    6. Diebold, Francis X & Mariano, Roberto S, 2002. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 134-144, January.
    7. Yock Y. Chong & David F. Hendry, 1986. "Econometric Evaluation of Linear Macro-Economic Models," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 53(4), pages 671-690.
    8. Erich Langmantel, 1999. "Das ifo Geschäftsklima als Indikator für die Prognose des Bruttoinlandsprodukts," ifo Schnelldienst, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 52(16-17), pages 16-21, October.
    9. West, Kenneth D, 2001. "Tests for Forecast Encompassing When Forecasts Depend on Estimated Regression Parameters," Journal of Business & Economic Statistics, American Statistical Association, vol. 19(1), pages 29-33, January.
    10. 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 254-259, April.
    11. Francis X. Diebold & Jose A. Lopez, 1995. "Forecast evaluation and combination," Research Paper 9525, Federal Reserve Bank of New York.
    12. Newey, Whitney & West, Kenneth, 2014. "A simple, positive semi-definite, heteroscedasticity and autocorrelation consistent covariance matrix," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 33(1), pages 125-132.
    13. 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.
    14. Granger, C W J, 1969. "Investigating Causal Relations by Econometric Models and Cross-Spectral Methods," Econometrica, Econometric Society, vol. 37(3), pages 424-438, July.
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    Cited by:

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    2. Lux, Thomas, 2009. "Rational forecasts or social opinion dynamics? Identification of interaction effects in a business climate survey," Journal of Economic Behavior & Organization, Elsevier, vol. 72(2), pages 638-655, November.
    3. Goldrian Georg, 2003. "Prognosegehalt von ifo-Geschäftserwartungen und ZEW-Konjunkturerwartungen. Eine Anmerkung," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 223(2), pages 223-226, April.
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    5. Nikolay Robinzonov & Klaus Wohlrabe, 2010. "Freedom of Choice in Macroeconomic Forecasting ," CESifo Economic Studies, CESifo Group, vol. 56(2), pages 192-220, June.
    6. Klaus Abberger & Sascha Becker & Barbara Hofmann & Klaus Wohlrabe, 2007. "Mikrodaten im ifo Institut für Wirtschaftsforschung – Bestand, Verwendung und Zugang," AStA Wirtschafts- und Sozialstatistisches Archiv, Springer;Deutsche Statistische Gesellschaft - German Statistical Society, vol. 1(1), pages 27-42, June.
    7. Benner, Joachim & Meier, Carsten-Patrick, 2005. "Was leisten Stimmungsindikatoren für die Prognose des realen Bruttoinlandsprodukts in Deutschland? Eine Echtzeit-Analyse," Open Access Publications from Kiel Institute for the World Economy 3725, Kiel Institute for the World Economy (IfW Kiel).
    8. Kai Carstensen & Steffen Henzel & Johannes Mayr & Klaus Wohlrabe, 2009. "IFOCAST: Methods of the Ifo short-term forecast," ifo Schnelldienst, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 62(23), pages 15-28, December.
    9. 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.
    10. 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.
    11. Anna Wolf, 2007. "Identical results of the ZEW Index of Business Expectations and the results for Germany of Ifo's World Economic Survey," ifo Schnelldienst, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 60(03), pages 55-56, February.
    12. Benner, Joachim & Meier, Carsten-Patrick, 2003. "Prognosegüte alternativer Frühindikatoren für die Konjunktur in Deutschland," Kiel Working Papers 1139, Kiel Institute for the World Economy (IfW Kiel).

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