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Tracking and Predicting the German Economy: ifo vs. PMI

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  • Robert Lehmann
  • Magnus Reif

Abstract

This analysis investigates the predictive power of the most important leading indicators for the German economy, which are provided by the ifo Institute and IHS Markit. We conduct an out-of-sample, real-time forecast experiment for growth of gross domestic product and growth of gross value added in both the manufacturing and the service sector. We find that both survey providers produce valuable leading indicators to predict the current quarter of German GDP growth. Regarding forecasts for the next quarter, the ifo indicators are slightly better than the IHS Markit headline index. For the manufacturing sector, series provided by ifo are clearly superior to those of IHS Markit. For the service sector, the ifo indicators produce better nowcasts, whereas the indicators by IHS are more valuable for one-quarter-ahead predictions.

Suggested Citation

  • Robert Lehmann & Magnus Reif, 2020. "Tracking and Predicting the German Economy: ifo vs. PMI," CESifo Working Paper Series 8145, CESifo.
    • Handle: RePEc:ces:ceswps:_8145
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    16. repec:ces:ifofor:v::y:2018:i::p: is not listed on IDEAS
    17. John B. Broughton & Bento J. Lobo, 2018. "Herding and anchoring in macroeconomic forecasts: the case of the PMI," Empirical Economics, Springer, vol. 55(3), pages 1337-1355, November.
    18. Robert Lehmann, 2023. "The Forecasting Power of the ifo Business Survey," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 19(1), pages 43-94, March.
    19. Klaus Wohlrabe & Timo Wollmershäuser, 2017. "Über die richtige Interpretation des ifo Geschäftsklimas als konjunktureller Frühindikator," ifo Schnelldienst, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 70(15), pages 42-46, August.
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    Cited by:

    1. Liudmila Kitrar & Tamara Lipkind, 2021. "Development Of Composite Indicators Of Cyclical Response In Business Surveys Considering The Specifics Of The ‘Covid-19 Economy’," HSE Working papers WP BRP 121/STI/2021, National Research University Higher School of Economics.
    2. Eraslan, Sercan & Reif, Magnus, 2023. "A latent weekly GDP indicator for Germany," Technical Papers 08/2023, Deutsche Bundesbank.
    3. Robert Lehmann & Sascha Möhrle, 2024. "Forecasting regional industrial production with novel high‐frequency electricity consumption data," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(6), pages 1918-1935, September.
    4. Lehmann, Robert & Wikman, Ida, 2022. "Quarterly GDP Estimates for the German States," MPRA Paper 112642, University Library of Munich, Germany.
    5. Robert Lehmann, 2023. "The Forecasting Power of the ifo Business Survey," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 19(1), pages 43-94, March.

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    More about this item

    Keywords

    forecasting nowcasting; survey data; ifo Business Climate; PMI;
    All these keywords.

    JEL classification:

    • E17 - Macroeconomics and Monetary Economics - - General Aggregative Models - - - Forecasting and Simulation: Models and Applications
    • E27 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Forecasting and Simulation: Models and Applications
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications

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