IDEAS home Printed from https://ideas.repec.org/p/zbw/iwhdps/182019.html
   My bibliography  Save this paper

How forecast accuracy depends on conditioning assumptions

Author

Listed:
  • Engelke, Carola
  • Heinisch, Katja
  • Schult, Christoph

Abstract

This paper examines the extent to which errors in economic forecasts are driven by initial assumptions that prove to be incorrect ex post. Therefore, we construct a new data set comprising an unbalanced panel of annual forecasts from different institutions forecasting German GDP and the underlying assumptions. We explicitly control for different forecast horizons to proxy the information available at the release date. Over 75% of squared errors of the GDP forecast comove with the squared errors in their underlying assumptions. The root mean squared forecast error for GDP in our regression sample of 1.52% could be reduced to 1.13% by setting all assumption errors to zero. This implies that the accuracy of the assumptions is of great importance and that forecasters should reveal the framework of their assumptions in order to obtain useful policy recommendations based on economic forecasts.

Suggested Citation

  • Engelke, Carola & Heinisch, Katja & Schult, Christoph, 2019. "How forecast accuracy depends on conditioning assumptions," IWH Discussion Papers 18/2019, Halle Institute for Economic Research (IWH).
  • Handle: RePEc:zbw:iwhdps:182019
    as

    Download full text from publisher

    File URL: https://www.econstor.eu/bitstream/10419/201837/1/167161237X.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Fred Joutz & Michael P. Clements & Herman O. Stekler, 2007. "An evaluation of the forecasts of the federal reserve: a pooled approach," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 22(1), pages 121-136.
    2. Cohen, Gail & Jalles, Joao Tovar & Loungani, Prakash & Marto, Ricardo, 2018. "The long-run decoupling of emissions and output: Evidence from the largest emitters," Energy Policy, Elsevier, vol. 118(C), pages 58-68.
    3. Davies, Anthony & Lahiri, Kajal, 1995. "A new framework for analyzing survey forecasts using three-dimensional panel data," Journal of Econometrics, Elsevier, vol. 68(1), pages 205-227, July.
    4. Rachidi Kotchoni & Maxime Leroux & Dalibor Stevanovic, 2019. "Macroeconomic forecast accuracy in a data‐rich environment," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 34(7), pages 1050-1072, November.
    5. Heilemann, Ullrich & Stekler, H. O., 2003. "Has the accuracy of German macroeconomic forecasts improved?," Technical Reports 2003,31, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.
    6. Bergholt, Drago & Larsen, Vegard H. & Seneca, Martin, 2019. "Business cycles in an oil economy," Journal of International Money and Finance, Elsevier, vol. 96(C), pages 283-303.
    7. Marco Fioramanti, ISTAT & Laura González Cabanillas & Bjorn Roelstraete & Salvador Adrian Ferrandis Vallterra, 2016. "European Commission's Forecasts Accuracy Revisited: Statistical Properties and Possible Causes of Forecast Errors," European Economy - Discussion Papers 2015 - 027, Directorate General Economic and Financial Affairs (DG ECFIN), European Commission.
    Full references (including those not matched with items on IDEAS)

    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. Paul Hubert, 2015. "Revisiting the Greenbook’s relative forecasting performance," Revue de l'OFCE, Presses de Sciences-Po, vol. 0(1), pages 151-179.
    2. Geoff Kenny & Thomas Kostka & Federico Masera, 2015. "Can Macroeconomists Forecast Risk? Event-Based Evidence from the Euro-Area SPF," International Journal of Central Banking, International Journal of Central Banking, vol. 11(4), pages 1-46, December.
    3. Ager, P. & Kappler, M. & Osterloh, S., 2009. "The accuracy and efficiency of the Consensus Forecasts: A further application and extension of the pooled approach," International Journal of Forecasting, Elsevier, vol. 25(1), pages 167-181.
    4. repec:spo:wpecon:info:hdl:2441/f4rshpf3v1umfa09lat09b1bg is not listed on IDEAS
    5. Dovern, Jonas & Weisser, Johannes, 2008. "Are they really rational? Assessing professional macro-economic forecasts from the G7-countries," Kiel Working Papers 1447, Kiel Institute for the World Economy (IfW Kiel).
    6. Deschamps, Bruno & Ioannidis, Christos, 2013. "Can rational stubbornness explain forecast biases?," Journal of Economic Behavior & Organization, Elsevier, vol. 92(C), pages 141-151.
    7. Dovern, Jonas & Weisser, Johannes, 2011. "Accuracy, unbiasedness and efficiency of professional macroeconomic forecasts: An empirical comparison for the G7," International Journal of Forecasting, Elsevier, vol. 27(2), pages 452-465.
    8. Kappler, Marcus, 2007. "Projecting the Medium-Term: Outcomes and Errors for GDP Growth," ZEW Discussion Papers 07-068, ZEW - Leibniz Centre for European Economic Research.
    9. Chen, Qiwei & Costantini, Mauro & Deschamps, Bruno, 2016. "How accurate are professional forecasts in Asia? Evidence from ten countries," International Journal of Forecasting, Elsevier, vol. 32(1), pages 154-167.
    10. repec:spo:wpmain:info:hdl:2441/3pot7260lh88lrfhrhvs85lh2f is not listed on IDEAS
    11. Ullrich Heilemann & Herman Stekler, 2010. "Perspectives on Evaluating Macroeconomic Forecasts," Working Papers 2010-002, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting.
    12. Sheng, Xuguang (Simon), 2015. "Evaluating the economic forecasts of FOMC members," International Journal of Forecasting, Elsevier, vol. 31(1), pages 165-175.
    13. Vereda, Luciano & Savignon, João & Gouveia da Silva, Tarciso, 2021. "A new method to assess the degree of information rigidity using fixed-event forecasts," International Journal of Forecasting, Elsevier, vol. 37(4), pages 1576-1589.
    14. Silvija Vlah Jerić & Mihovil Anđelinović, 2019. "Evaluating Croatian stock index forecasts," Empirical Economics, Springer, vol. 56(4), pages 1325-1339, April.
    15. Sun, Yuying & Wang, Shouyang & Zhang, Xun, 2018. "How efficient are China's macroeconomic forecasts? Evidences from a new forecasting evaluation approach," Economic Modelling, Elsevier, vol. 68(C), pages 506-513.
    16. Davies, Antony, 2006. "A framework for decomposing shocks and measuring volatilities derived from multi-dimensional panel data of survey forecasts," International Journal of Forecasting, Elsevier, vol. 22(2), pages 373-393.
    17. Paul Hubert, 2010. "Monetary Policy, Imperfect Information and the Expectations Channel," Sciences Po publications info:hdl:2441/f4rshpf3v1u, Sciences Po.
    18. Graham Elliott & Ivana Komunjer & Allan Timmermann, 2008. "Biases in Macroeconomic Forecasts: Irrationality or Asymmetric Loss?," Journal of the European Economic Association, MIT Press, vol. 6(1), pages 122-157, March.
    19. Agnes Benassy-Quere, 2016. "Euro-Area Fiscal Stance: From Theory to Practical Implementation," CESifo Working Paper Series 6040, CESifo.
    20. Isiklar, Gultekin, 2005. "On aggregation bias in fixed-event forecast efficiency tests," Economics Letters, Elsevier, vol. 89(3), pages 312-316, December.
    21. Andrea Ferrero & Martin Seneca, 2019. "Notes on the Underground: Monetary Policy in Resource‐Rich Economies," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 51(4), pages 953-976, June.
    22. Graham Elliott & Allan Timmermann, 2016. "Economic Forecasting," Economics Books, Princeton University Press, edition 1, number 10740.

    More about this item

    Keywords

    forecasts; accuracy; forecast errors; external assumptions; forecast efficiency; forecast horizon;
    All these keywords.

    JEL classification:

    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • E02 - Macroeconomics and Monetary Economics - - General - - - Institutions and the Macroeconomy
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles

    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:zbw:iwhdps:182019. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: . General contact details of provider: https://edirc.repec.org/data/iwhhhde.html .

    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: ZBW - Leibniz Information Centre for Economics (email available below). General contact details of provider: https://edirc.repec.org/data/iwhhhde.html .

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

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.