IDEAS home Printed from https://ideas.repec.org/p/diw/diwwpp/dp399.html
   My bibliography  Save this paper

Growth and Inflation Forecasts for Germany: An Assessment of Accuracy and Dispersion

Author

Listed:
  • Jörg Döpke
  • Ulrich Fritsche

Abstract

Based on a panel of German professional forecasts for 1970 to 2002 we find that growth and inflation forecasts are unbiased and weakly, but not strongly efficient. Besides the effect of diverging forecasting dates, no other substantial differences in forecasting quality are found among forecasters. We argue that is not always advisable to listen to the majority of forecast-ers. The dispersion of forecasts correlates positively with the volatility of macroeconomic variables. This suggests that forecasters do not behave predominately strategic, but share no common belief on the adequate model of the economy.

Suggested Citation

  • Jörg Döpke & Ulrich Fritsche, 2004. "Growth and Inflation Forecasts for Germany: An Assessment of Accuracy and Dispersion," Discussion Papers of DIW Berlin 399, DIW Berlin, German Institute for Economic Research.
  • Handle: RePEc:diw:diwwpp:dp399
    as

    Download full text from publisher

    File URL: https://www.diw.de/documents/publikationen/73/diw_01.c.41216.de/dp399.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Bomberger, William A, 1996. "Disagreement as a Measure of Uncertainty," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 28(3), pages 381-392, August.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Gern, Klaus-Jürgen & Oskamp, Frank & Sander, Birgit & Scheide, Joachim & Schweickert, Rainer & Boss, Alfred & Dovern, Jonas & Meier, Carsten-Patrick & Oskamp, Frank, 2006. "Weltkonjunktur und deutsche Konjunktur im Frühjahr 2006," Kiel Discussion Papers 424/425, Kiel Institute for the World Economy (IfW Kiel).
    2. Frank-Oliver Aldenhoff, 2007. "Are economic forecasts of the International Monetary Fund politically biased? A public choice analysis," The Review of International Organizations, Springer, vol. 2(3), pages 239-260, September.
    3. Katharina Glass, 2018. "Predictability of Euro Area Revisions," Macroeconomics and Finance Series 201801, University of Hamburg, Department of Socioeconomics.
    4. Boss, Alfred & Dovern, Jonas & Meier, Carsten-Patrick & Oskamp, Frank & Scheide, Joachim, 2006. "Kräftiger, aber nur kurzer Aufschwung in Deutschland," Open Access Publications from Kiel Institute for the World Economy 3930, Kiel Institute for the World Economy (IfW Kiel).
    5. Birger Antholz, 2006. "Geschichte der quantitativen Konjunkturprognose-Evaluation in Deutschland," Vierteljahrshefte zur Wirtschaftsforschung / Quarterly Journal of Economic Research, DIW Berlin, German Institute for Economic Research, vol. 75(2), pages 12-33.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Marfatia, Hardik A., 2015. "Monetary policy's time-varying impact on the US bond markets: Role of financial stress and risks," The North American Journal of Economics and Finance, Elsevier, vol. 34(C), pages 103-123.
    2. Engelberg, Joseph & Manski, Charles F. & Williams, Jared, 2009. "Comparing the Point Predictions and Subjective Probability Distributions of Professional Forecasters," Journal of Business & Economic Statistics, American Statistical Association, vol. 27, pages 30-41.
    3. Aleksejs Krecetovs & Pasquale Della Corte, 2016. "Macro uncertainty and currency premia," 2016 Meeting Papers 624, Society for Economic Dynamics.
    4. Hall, Stephen G. & Mitchell, James, 2007. "Combining density forecasts," International Journal of Forecasting, Elsevier, vol. 23(1), pages 1-13.
    5. Himounet, Nicolas, 2022. "Searching the nature of uncertainty: Macroeconomic and financial risks VS geopolitical and pandemic risks," International Economics, Elsevier, vol. 170(C), pages 1-31.
    6. Carlos Alberto Piscarreta Pinto Ferreira, 2022. "Revisiting The Determinants Of Sovereign Bond Yield Volatility," Working Papers REM 2022/0241, ISEG - Lisbon School of Economics and Management, REM, Universidade de Lisboa.
    7. Pesaran, M. Hashem & Weale, Martin, 2006. "Survey Expectations," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 1, chapter 14, pages 715-776, Elsevier.
    8. Timur Hulagu & Saygin Sahinoz, 2011. "Enflasyon Belirsizligi ve Beklentilerdeki Uyusmazlik," CBT Research Notes in Economics 1104, Research and Monetary Policy Department, Central Bank of the Republic of Turkey.
    9. Catherine Fuss & Philip Vermeulen, 2008. "Firms' investment decisions in response to demand and price uncertainty," Applied Economics, Taylor & Francis Journals, vol. 40(18), pages 2337-2351.
    10. R?diger Bachmann & Steffen Elstner & Eric R. Sims, 2013. "Uncertainty and Economic Activity: Evidence from Business Survey Data," American Economic Journal: Macroeconomics, American Economic Association, vol. 5(2), pages 217-249, April.
    11. ter Ellen, Saskia & Verschoor, Willem F.C. & Zwinkels, Remco C.J., 2019. "Agreeing on disagreement: Heterogeneity or uncertainty?," Journal of Financial Markets, Elsevier, vol. 44(C), pages 17-30.
    12. Fabian Krüger & Ingmar Nolte, 2011. "Disagreement, Uncertainty and the True Predictive Density," Working Paper Series of the Department of Economics, University of Konstanz 2011-43, Department of Economics, University of Konstanz.
    13. Clements, Michael P., 2006. "Internal consistency of survey respondentsíforecasts: Evidence based on the Survey of Professional Forecasters," Economic Research Papers 269742, University of Warwick - Department of Economics.
    14. Pfajfar, D. & Zakelj, B., 2012. "Uncertainty and Disagreement in Forecasting Inflation : Evidence from the Laboratory (Revised version of CentER DP 2011-053)," Discussion Paper 2012-072, Tilburg University, Center for Economic Research.
    15. Patrick Mcallister & Graeme Newell & George Matysiak, 2008. "Agreement and Accuracy in Consensus Forecasts of the UK Commercial Property Market," Journal of Property Research, Taylor & Francis Journals, vol. 25(1), pages 1-22, June.
    16. Clements, Michael P., 2021. "Do survey joiners and leavers differ from regular participants? The US SPF GDP growth and inflation forecasts," International Journal of Forecasting, Elsevier, vol. 37(2), pages 634-646.
    17. Krüger, Fabian & Nolte, Ingmar, 2016. "Disagreement versus uncertainty: Evidence from distribution forecasts," Journal of Banking & Finance, Elsevier, vol. 72(S), pages 172-186.
    18. Michael P. Clements, 2022. "Forecaster Efficiency, Accuracy, and Disagreement: Evidence Using Individual‐Level Survey Data," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 54(2-3), pages 537-568, March.
    19. Gieseck Arne & Largent Yannis, 2016. "The Impact of Macroeconomic Uncertainty on Activity in the Euro Area," Review of Economics, De Gruyter, vol. 67(1), pages 25-52, May.
    20. Constantin Burgi, 2016. "What Do We Lose When We Average Expectations?," Working Papers 2016-013, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting.

    More about this item

    Keywords

    Forecast error evaluation; Consensus forecast; Disagreement; Uncertainty; Germany;
    All these keywords.

    JEL classification:

    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:diw:diwwpp:dp399. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Bibliothek (email available below). General contact details of provider: https://edirc.repec.org/data/diwbede.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.