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Dutch GDP Data Revisions: Are They Predictable and Where Do They Come from?

Author

Listed:
  • Olivier Roodenburg
  • Ard H.J. den Reijer

Abstract

This paper examines whether the preliminary releases of GDP incorporate efficiently all available information or the preliminary estimates contain information that can be useful in predicting forthcoming GDP revisions. Forecast rationality tests are applied to distinguish between these two characterisations. We analyse the revision over three horizons: the very short-term revision after one quarter, the short-term revision after two years, and the long-term revision. We find evidence of the predictability of all short- and long-term revisions of Dutch GDP data. Our evidence for the revisions of the seasonally adjusted quarter-on-quarter growth rates are in line with the findings on G7 countries. Moreover, we analyse the revisions of the six expenditure components and ten production components that constitute GDP. Only the preliminary releases of household consumption and the construction sector seem to explain the GDP data revisions. However, the general conclusion is that the forecast rationality hypothesis is rejected for almost all components separately, but that almost no individual component’s preliminary data release can forecast the revisions of GDP.

Suggested Citation

  • Olivier Roodenburg & Ard H.J. den Reijer, 2006. "Dutch GDP Data Revisions: Are They Predictable and Where Do They Come from?," Applied Economics Quarterly (formerly: Konjunkturpolitik), Duncker & Humblot, Berlin, vol. 52(4), pages 337-356.
    • Handle: RePEc:aeq:aeqaeq:v52_y2006_i4_q4_p337-356
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    Citations

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    Cited by:

    1. Amey Sapre & Rajeswari Sengupta, 2017. "Analysis of Revisions in Indian GDP Data," World Economics, World Economics, 1 Ivory Square, Plantation Wharf, London, United Kingdom, SW11 3UE, vol. 18(4), pages 129-172, October.
    2. Boysen-Hogrefe, Jens & Neuwirth, Stefan, 2012. "The impact of seasonal and price adjustments on the predictability of German GDP revisions," Kiel Working Papers 1753, Kiel Institute for the World Economy (IfW Kiel).
    3. Döhrn, Roland, 2018. "Revisionen der Volkswirtschaftlichen Gesamtrechnungen: Revisionspraxis des Statistischen Bundesamtes und ihre Auswirkungen auf Prognosen," RWI Materialien 127, RWI - Leibniz-Institut für Wirtschaftsforschung.
    4. Caroline Flodberg & Pär Österholm, 2017. "A Statistical Anaysis of Revisions in Swedish National Accounts Data," Finnish Economic Papers, Finnish Economic Association, vol. 28(1), pages 10-33, Autumn.
    5. Roland Döhrn, 2019. "Revisionen der Volkswirtschaftlichen Gesamtrechnungen und ihre Auswirkungen auf Prognosen [Revisions of national accounts data and their impact on forecasts]," AStA Wirtschafts- und Sozialstatistisches Archiv, Springer;Deutsche Statistische Gesellschaft - German Statistical Society, vol. 13(2), pages 99-123, September.

    More about this item

    Keywords

    Real-time data; GDP data revision; forecast efficiency;
    All these keywords.

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods

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