IDEAS home Printed from https://ideas.repec.org/p/kof/wpskof/09-215.html
   My bibliography  Save this paper

Do forecasters inform or reassure?

Author

Listed:
  • Konstantin A. Kholodilin
  • Boriss Siliverstovs

Abstract

The paper evaluates the quality of the German national accounting data (GDP and its use-side components) as measured by the magnitude and dispersion of the forecast/ revision errors. It is demonstrated that government consumption series are the least reliable, whereas real GDP and real private consumption data are the most reliable. In addition, early forecasts of GDP, private consumption, and investment growth rates are shown to be systematically upward biased. Finally, early forecasts of all the variables seem to be no more accurate than naive forecasts based on the historical mean of the final data.

Suggested Citation

  • Konstantin A. Kholodilin & Boriss Siliverstovs, 2009. "Do forecasters inform or reassure?," KOF Working papers 09-215, KOF Swiss Economic Institute, ETH Zurich.
  • Handle: RePEc:kof:wpskof:09-215
    DOI: 10.3929/ethz-a-005778341
    as

    Download full text from publisher

    File URL: http://dx.doi.org/10.3929/ethz-a-005778341
    Download Restriction: no

    File URL: https://libkey.io/10.3929/ethz-a-005778341?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. de Gooijer, Jan G. & Klein, Andre, 1992. "On the cumulated multi-step-ahead predictions of vector autoregressive moving average processes," International Journal of Forecasting, Elsevier, vol. 7(4), pages 501-513, March.
    2. Ashiya, Masahiro, 2007. "Forecast accuracy of the Japanese government: Its year-ahead GDP forecast is too optimistic," Japan and the World Economy, Elsevier, vol. 19(1), pages 68-85, January.
    3. Batchelor, Roy, 2007. "Bias in macroeconomic forecasts," International Journal of Forecasting, Elsevier, vol. 23(2), pages 189-203.
    4. Jan Jacobs & Jan-Egbert Sturm, 2005. "Do Ifo Indicators Help Explain Revisions in German Industrial Production?," Contributions to Economics, in: Jan-Egbert Sturm & Timo Wollmershäuser (ed.), Ifo Survey Data in Business Cycle and Monetary Policy Analysis, pages 93-114, Springer.
    5. Graham Elliott & Allan Timmermann & Ivana Komunjer, 2005. "Estimation and Testing of Forecast Rationality under Flexible Loss," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 72(4), pages 1107-1125.
    6. Loungani, Prakash, 2001. "How accurate are private sector forecasts? Cross-country evidence from consensus forecasts of output growth," International Journal of Forecasting, Elsevier, vol. 17(3), pages 419-432.
    7. Francis X. Diebold & Lutz Kilian, 2001. "Measuring predictability: theory and macroeconomic applications," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 16(6), pages 657-669.
    8. Faust, Jon & Rogers, John H & Wright, Jonathan H, 2005. "News and Noise in G-7 GDP Announcements," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 37(3), pages 403-419, June.
    9. Lahiri, Kajal & Sheng, Xuguang, 2010. "Learning and heterogeneity in GDP and inflation forecasts," International Journal of Forecasting, Elsevier, vol. 26(2), pages 265-292, April.
    10. Isiklar, Gultekin & Lahiri, Kajal, 2007. "How far ahead can we forecast? Evidence from cross-country surveys," International Journal of Forecasting, Elsevier, vol. 23(2), pages 167-187.
    11. N. Gregory Mankiw & Matthew D. Shapiro, 1986. "News or Noise? An Analysis of GNP Revisions," NBER Working Papers 1939, National Bureau of Economic Research, Inc.
    12. McNees, Stephen K., 1989. "Forecasts and actuals: The trade-off between timeliness and accuracy," International Journal of Forecasting, Elsevier, vol. 5(3), pages 409-416.
    13. Knetsch, Thomas A. & Reimers, Hans-Eggert, 2006. "How to treat benchmark revisions? The case of German production and orders statistics," Discussion Paper Series 1: Economic Studies 2006,38, Deutsche Bundesbank.
    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. Katharina Glass & Ulrich Fritsche, 2015. "Real-time Macroeconomic Data and Uncertainty," Macroeconomics and Finance Series 201406, University of Hamburg, Department of Socioeconomics.
    2. Jacopo Cimadomo, 2016. "Real-Time Data And Fiscal Policy Analysis: A Survey Of The Literature," Journal of Economic Surveys, Wiley Blackwell, vol. 30(2), pages 302-326, April.
    3. Heilemann Ullrich & Stekler Herman O., 2013. "Has The Accuracy of Macroeconomic Forecasts for Germany Improved?," German Economic Review, De Gruyter, vol. 14(2), pages 235-253, May.
    4. de Mendonça, Helder Ferreira & Baca, Adriana Cabrera, 2022. "Fiscal opacity and reduction of income inequality through taxation: Effects on economic growth," The Quarterly Review of Economics and Finance, Elsevier, vol. 83(C), pages 69-82.
    5. Helmut Herwartz & Konstantin A. Kholodilin, 2014. "In‐Sample and Out‐of‐Sample Prediction of stock Market Bubbles: Cross‐Sectional Evidence," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 33(1), pages 15-31, January.
    6. Gabriel C Montes & Caio F Ferreira, 2022. "Monetary policy opacity and disagreements in expectations about variables under central bank control," Economics Bulletin, AccessEcon, vol. 42(2), pages 703-721.
    7. Katharina Glass, 2018. "Predictability of Euro Area Revisions," Macroeconomics and Finance Series 201801, University of Hamburg, Department of Socioeconomics.
    8. Helder Ferreira de Mendonça & Vítor Ribeiro Laufer Calafate, 2021. "Lack of fiscal transparency and economic growth expectations: an empirical assessment from a large emerging economy," Empirical Economics, Springer, vol. 61(6), pages 2985-3027, December.
    9. de Mendonça, Helder Ferreira & Díaz, Raime Rolando Rodríguez, 2023. "Can ignorance about the interest rate and macroeconomic surprises affect the stock market return? Evidence from a large emerging economy," The North American Journal of Economics and Finance, Elsevier, vol. 64(C).
    10. António Rua & Carlos Melo Gouveia & Fátima Cardoso, 2023. "From first to last: the National Accounts revisions," Economic Bulletin and Financial Stability Report Articles and Banco de Portugal Economic Studies, Banco de Portugal, Economics and Research Department.
    11. Gabriel Caldas Montes & Paulo Henrique Lourenço Luna, 2022. "Do fiscal opacity, fiscal impulse, and fiscal credibility affect disagreement about economic growth forecasts? Empirical evidence from Brazil considering the period of political instability and presid," Review of Development Economics, Wiley Blackwell, vol. 26(4), pages 2356-2393, November.

    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. Jan Jacobs & Jan-Egbert Sturm, 2009. "The information content of KOF indicators on Swiss current account data revisions," OECD Journal: Journal of Business Cycle Measurement and Analysis, OECD Publishing, Centre for International Research on Economic Tendency Surveys, vol. 2008(2), pages 161-181.
    2. Isiklar, Gultekin & Lahiri, Kajal, 2007. "How far ahead can we forecast? Evidence from cross-country surveys," International Journal of Forecasting, Elsevier, vol. 23(2), pages 167-187.
    3. Kajal Lahiri & Gultekin Isiklar, 2010. "Estimating International Transmission of Shocks Using GDP Forecasts: India and Its Trading Partners," Discussion Papers 10-06, University at Albany, SUNY, Department of Economics.
    4. Oller, Lars-Erik & Teterukovsky, Alex, 2007. "Quantifying the quality of macroeconomic variables," International Journal of Forecasting, Elsevier, vol. 23(2), pages 205-217.
    5. Tsuchiya, Yoichi, 2016. "Assessing macroeconomic forecasts for Japan under an asymmetric loss function," International Journal of Forecasting, Elsevier, vol. 32(2), pages 233-242.
    6. 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.
    7. Capistrán, Carlos & López-Moctezuma, Gabriel, 2014. "Forecast revisions of Mexican inflation and GDP growth," International Journal of Forecasting, Elsevier, vol. 30(2), pages 177-191.
    8. Pascal Bührig & Klaus Wohlrabe, 2015. "Revisionen der deutschen Industrieproduktion und die ifo Indikatoren," ifo Schnelldienst, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 68(21), pages 27-31, November.
    9. Corradi, Valentina & Fernandez, Andres & Swanson, Norman R., 2009. "Information in the Revision Process of Real-Time Datasets," Journal of Business & Economic Statistics, American Statistical Association, vol. 27(4), pages 455-467.
    10. Sinclair, Tara M., 2019. "Characteristics and implications of Chinese macroeconomic data revisions," International Journal of Forecasting, Elsevier, vol. 35(3), pages 1108-1117.
    11. Frenkel, Michael & Rülke, Jan-Christoph & Zimmermann, Lilli, 2013. "Do private sector forecasters chase after IMF or OECD forecasts?," Journal of Macroeconomics, Elsevier, vol. 37(C), pages 217-229.
    12. Dovern, Jonas & Jannsen, Nils, 2017. "Systematic errors in growth expectations over the business cycle," International Journal of Forecasting, Elsevier, vol. 33(4), pages 760-769.
    13. Jalles, João Tovar, 2017. "On the rationality and efficiency of inflation forecasts: Evidence from advanced and emerging market economies," Research in International Business and Finance, Elsevier, vol. 40(C), pages 175-189.
    14. Lahiri, Kajal & Sheng, Xuguang, 2010. "Learning and heterogeneity in GDP and inflation forecasts," International Journal of Forecasting, Elsevier, vol. 26(2), pages 265-292, April.
    15. José Daniel Aromí, 2021. "Large Current Account Deficits and Neglected Vulnerabilities," IMF Economic Review, Palgrave Macmillan;International Monetary Fund, vol. 69(4), pages 597-623, December.
    16. Aruoba, S. Borağan & Diebold, Francis X. & Nalewaik, Jeremy & Schorfheide, Frank & Song, Dongho, 2016. "Improving GDP measurement: A measurement-error perspective," Journal of Econometrics, Elsevier, vol. 191(2), pages 384-397.
    17. Dovern, Jonas & Fritsche, Ulrich & Loungani, Prakash & Tamirisa, Natalia, 2015. "Information rigidities: Comparing average and individual forecasts for a large international panel," International Journal of Forecasting, Elsevier, vol. 31(1), pages 144-154.
    18. 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.
    19. Tsuchiya, Yoichi, 2023. "Assessing the World Bank’s growth forecasts," Economic Analysis and Policy, Elsevier, vol. 77(C), pages 64-84.
    20. Roland Döhrn, 2023. "Are German National Accounts informationally efficient?," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 19(1), pages 23-42, March.

    More about this item

    Keywords

    Quality of statistical data; real-time data; signal-to-noise ratio; forecasts; revisions;
    All these keywords.

    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:kof:wpskof:09-215. 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: the person in charge (email available below). General contact details of provider: https://edirc.repec.org/data/koethch.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.