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. Lutz Kilian, 2008. "The Economic Effects of Energy Price Shocks," Journal of Economic Literature, American Economic Association, vol. 46(4), pages 871-909, December.
    3. 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.
    4. Ullrich Heilemann & Karsten Müller, 2018. "Wenig Unterschiede – Zur Treffsicherheit Internationaler Prognosen und Prognostiker [Few differences—on the accuracy of international forecasts and forecaster]," AStA Wirtschafts- und Sozialstatistisches Archiv, Springer;Deutsche Statistische Gesellschaft - German Statistical Society, vol. 12(3), pages 195-233, December.
    5. Olivier J. Blanchard & Jordi Galí, 2007. "The Macroeconomic Effects of Oil Price Shocks: Why Are the 2000s so Different from the 1970s?," NBER Chapters, in: International Dimensions of Monetary Policy, pages 373-421, National Bureau of Economic Research, Inc.
    6. Clark, Todd & McCracken, Michael, 2013. "Advances in Forecast Evaluation," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 1107-1201, Elsevier.
    7. John Elder & Apostolos Serletis, 2010. "Oil Price Uncertainty," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 42(6), pages 1137-1159, September.
    8. 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.
    9. John Baffes, 1997. "Explaining stationary variables with non-stationary regressors," Applied Economics Letters, Taylor & Francis Journals, vol. 4(1), pages 69-75.
    10. 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.
    11. Filip Keereman, 2003. "External assumptions, the international environment and the track record of the Commission Forecast," European Economy - Economic Papers 2008 - 2015 189, Directorate General Economic and Financial Affairs (DG ECFIN), European Commission.
    12. Heilemann, Ullrich, 2002. "Increasing the transparency of macroeconometric forecasts: a report from the trenches," International Journal of Forecasting, Elsevier, vol. 18(1), pages 85-105.
    13. 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.
    14. 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.
    15. Berge, Travis J. & Chang, Andrew C. & Sinha, Nitish R., 2019. "Evaluating the conditionality of judgmental forecasts," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1627-1635.
    16. G. Elliott & C. Granger & A. Timmermann (ed.), 2013. "Handbook of Economic Forecasting," Handbook of Economic Forecasting, Elsevier, edition 1, volume 2, number 2.
    17. Ulrich Fritsche & Ullrich Heilemann, 2010. "Too Many Cooks? The German Joint Diagnosis and Its Production," Macroeconomics and Finance Series 201001, University of Hamburg, Department of Socioeconomics.
    18. 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 027, Directorate General Economic and Financial Affairs (DG ECFIN), European Commission.
    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. Heinisch Katja & Behrens Christoph & Döpke Jörg & Foltas Alexander & Fritsche Ulrich & Köhler Tim & Müller Karsten & Puckelwald Johannes & Reichmayr Hannes, 2024. "The IWH Forecasting Dashboard: From Forecasts to Evaluation and Comparison," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 244(3), pages 277-288, June.

    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. Joëts, Marc & Mignon, Valérie & Razafindrabe, Tovonony, 2017. "Does the volatility of commodity prices reflect macroeconomic uncertainty?," Energy Economics, Elsevier, vol. 68(C), pages 313-326.
    2. Liu, Li & Ma, Feng & Wang, Yudong, 2015. "Forecasting excess stock returns with crude oil market data," Energy Economics, Elsevier, vol. 48(C), pages 316-324.
    3. Lang, Korbinian & Auer, Benjamin R., 2020. "The economic and financial properties of crude oil: A review," The North American Journal of Economics and Finance, Elsevier, vol. 52(C).
    4. Jo, Soojin & Karnizova, Lilia & Reza, Abeer, 2019. "Industry effects of oil price shocks: A re-examination," Energy Economics, Elsevier, vol. 82(C), pages 179-190.
    5. Francesca Rondina, 2017. "The Impact of Oil Price Changes in a New Keynesian Model of the U.S. Economy," Working Papers 1709E, University of Ottawa, Department of Economics.
    6. Degiannakis, Stavros & Filis, George & Floros, Christos, 2013. "Oil and stock returns: Evidence from European industrial sector indices in a time-varying environment," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 26(C), pages 175-191.
    7. John Baffes & M. Ayhan Kose & Franziska Ohnsorge & Marc Stocker, 2015. "The Great Plunge in Oil Prices: Causes, Consequences, and Policy Responses," Koç University-TUSIAD Economic Research Forum Working Papers 1504, Koc University-TUSIAD Economic Research Forum.
    8. Degiannakis, Stavros & Filis, George & Floros, Christos, 2013. "Oil and stock price returns: Evidence from European industrial sector indices in a time-varying environment," MPRA Paper 80495, University Library of Munich, Germany.
    9. 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.
    10. Matthew Klepacz, 2021. "Price Setting and Volatility: Evidence from Oil Price Volatility Shocks," International Finance Discussion Papers 1316, Board of Governors of the Federal Reserve System (U.S.).
    11. Díaz-Kovalenko, Igor E. & Torres, José L., 2022. "Oil price shocks, government revenues and public investment: The case of Ecuador," MPRA Paper 112268, University Library of Munich, Germany, revised 07 Mar 2022.
    12. Samya Beidas-Strom & Marco Lorusso, 2019. "Macroeconomic Effects of Reforms on Three Diverse Oil Exporters: Russia, Saudi Arabia, and the UK," IMF Working Papers 2019/214, International Monetary Fund.
    13. Vincent Brémond & Emmanuel Hache & Tovonony Razafindrabe, 2016. "The Oil Price and Exchange Rate Relationship Revisited: A time-varying VAR parameter approach," European Journal of Comparative Economics, Cattaneo University (LIUC), vol. 13(1), pages 97-131, June.
    14. Baumeister, Christiane & Kilian, Lutz & Lee, Thomas K., 2014. "Are there gains from pooling real-time oil price forecasts?," Energy Economics, Elsevier, vol. 46(S1), pages 33-43.
    15. Pham T. T. Trinh & Bui T. T. My, 2023. "The impact of world oil price shocks on macroeconomic variables in Vietnam: the transmission through domestic oil price," Asian-Pacific Economic Literature, The Crawford School, The Australian National University, vol. 37(1), pages 67-87, May.
    16. Lutz Kilian, 2010. "Oil Price Shocks, Monetary Policy and Stagflation," RBA Annual Conference Volume (Discontinued), in: Renée Fry & Callum Jones & Christopher Kent (ed.),Inflation in an Era of Relative Price Shocks, Reserve Bank of Australia.
    17. Ansgar Belke & Daniel Gros, 2014. "A simple model of an oil based global savings glut—the “China factor”and the OPEC cartel," International Economics and Economic Policy, Springer, vol. 11(3), pages 413-430, September.
    18. Alan S. Blinder & Jeremy B. Rudd, 2013. "The Supply-Shock Explanation of the Great Stagflation Revisited," NBER Chapters, in: The Great Inflation: The Rebirth of Modern Central Banking, pages 119-175, National Bureau of Economic Research, Inc.
    19. Fédéric Holm-Hadulla & Kirstin Hubrich, 2017. "Macroeconomic Implications of Oil Price Fluctuations : A Regime-Switching Framework for the Euro Area," Finance and Economics Discussion Series 2017-063, Board of Governors of the Federal Reserve System (U.S.).
    20. Andreopoulos Spyros, 2009. "Oil Matters: Real Input Prices and U.S. Unemployment Revisited," The B.E. Journal of Macroeconomics, De Gruyter, vol. 9(1), pages 1-31, March.

    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.

    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. RePEc uses bibliographic data supplied by the respective publishers.