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Information or Institution?: On the Determinants of Forecast Accuracy

Author

Listed:
  • Döhrn Roland

    () (RWI, Hohenzollernstr. 1-3, 45128 Essen, Germany, und Universität Duisburg-Essen, Germany)

  • Schmidt Christoph M.

    () (RWI, Hohenzollernstr. 1-3, 45128 Essen, Germany, und Ruhr- Universität Bochum, Germany)

Abstract

The accuracy of macroeconomic forecast depends on various factors, most importantly the mix of analytical methods used by the individual forecasters, the way that their personal experience is shaping their identification strategies, but also their efficiency in translating new information into revised forecasts. In this paper we use a broad sample of forecasts of German GDP and its components to analyze the impact of institutions and information on forecast accuracy. We find that forecast errors are a linear function of the forecast horizon, which serves as an indicator of the information available at the time a forecast is produced. This result is robust over a variety of different specifications. As better information seems to be the key to achieving better forecasts, approaches for acquiring reliable information early seem to be a good investment. By contrast, the institutional factors tend to be small and statistically insignificant. It has to remain open, whether this is the consequence of the efficiency-enhancing competition among German research institutions or rather the reflection of an abundance of forecast suppliers.

Suggested Citation

  • Döhrn Roland & Schmidt Christoph M., 2011. "Information or Institution?: On the Determinants of Forecast Accuracy," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 231(1), pages 9-27, February.
  • Handle: RePEc:jns:jbstat:v:231:y:2011:i:1:p:9-27
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    References listed on IDEAS

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    1. John P. Haisken-DeNew & Christoph M. Schmidt, 2000. "Interindustry and Interregion Differentials: Mechanics and Interpretation," The Review of Economics and Statistics, MIT Press, vol. 79(3), pages 516-521, August.
    2. Klinger, Sabine & Heilemann, Ullrich, 2005. "Zu wenig Wettbewerb? Zu Stand und Entwicklung der Genauigkeit makroökonomischer Prognosen," Technical Reports 2005,16, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.
    3. Kajal Lahiri & Gultekin Isiklar & Prakash Loungani, 2006. "How quickly do forecasters incorporate news? Evidence from cross-country surveys," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(6), pages 703-725.
    4. Lamont, Owen A., 2002. "Macroeconomic forecasts and microeconomic forecasters," Journal of Economic Behavior & Organization, Elsevier, vol. 48(3), pages 265-280, July.
    5. Simeon Vosen & Torsten Schmidt, 2011. "Forecasting private consumption: survey‐based indicators vs. Google trends," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 30(6), pages 565-578, September.
    6. 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.
    7. Dopke, Jorg & Fritsche, Ulrich, 2006. "When do forecasters disagree? An assessment of German growth and inflation forecast dispersion," International Journal of Forecasting, Elsevier, vol. 22(1), pages 125-135.
    8. Jörg Döpke & Ulrich Fritsche, 2006. "Growth and inflation forecasts for Germany a panel-based assessment of accuracy and efficiency," Empirical Economics, Springer, vol. 31(3), pages 777-798, September.
    9. Wolfgang Nierhaus & Jan-Egbert Sturm, 2003. "Methoden der Konjunkturprognose," ifo Schnelldienst, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 56(04), pages 7-23, February.
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    Cited by:

    1. Ulrich Fritsche & Artur Tarassow, 2017. "Vergleichende Evaluation der Konjunkturprognosen des Instituts für Makroökonomie und Konjunkturforschung an der Hans-Böckler-Stiftung für den Zeitraum 2005-2014," IMK Studies 54-2017, IMK at the Hans Boeckler Foundation, Macroeconomic Policy Institute.
    2. Ullrich Heilemann & Herman O. Stekler, 2013. "Has The Accuracy of Macroeconomic Forecasts for Germany Improved?," German Economic Review, Verein für Socialpolitik, vol. 14(2), pages 235-253, May.
    3. an de Meulen, Philipp, 2015. "Das RWI-Kurzfristprognosemodell," RWI Konjunkturberichte, RWI - Leibniz-Institut für Wirtschaftsforschung, vol. 66(2), pages 25-46.
    4. Jörg Döpke & Ulrich Fritsche & Karsten Müller, 2018. "Has Macroeconomic Forecasting changed after the Great Recession? - Panel-based Evidence on Accuracy and Forecaster Behaviour from Germany," Macroeconomics and Finance Series 201803, Hamburg University, Department Wirtschaft und Politik.
    5. Rülke Jan-Christoph, 2012. "Do Private Sector Forecasters Desire to Deviate From the German Council of Economic Experts?," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 232(4), pages 414-428, August.

    More about this item

    Keywords

    Forecast accuracy; forecast revisions; forecast horizon; economic activity;

    JEL classification:

    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • E27 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Forecasting and Simulation: Models and Applications
    • E01 - Macroeconomics and Monetary Economics - - General - - - Measurement and Data on National Income and Product Accounts and Wealth; Environmental Accounts

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