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Data revisions to German national accounts: Are initial releases good nowcasts?

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  • Strohsal, Till
  • Wolf, Elias

Abstract

Data revisions to national accounts pose a serious challenge to policy decision making. Well-behaved revisions should be unbiased, small and unpredictable. This paper shows that revisions to German national accounts are biased, large and predictable. Moreover, using filtering techniques designed to process data subject to revisions, the real-time forecasting performance of initial releases can be increased by up to 17%. For total real GDP growth, however, the initial release is an optimal forecast. Yet, given the results for disaggregated variables, the averaging-out of biases and inefficiencies at the aggregate GDP level appears to be good luck rather than good forecasting.

Suggested Citation

  • Strohsal, Till & Wolf, Elias, 2019. "Data revisions to German national accounts: Are initial releases good nowcasts?," Discussion Papers 2019/11, Free University Berlin, School of Business & Economics.
    • Handle: RePEc:zbw:fubsbe:201911
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    References listed on IDEAS

    as
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    More about this item

    Keywords

    Revisions; Real-Time Data; German National Accounts; Nowcasting;
    All these keywords.

    JEL classification:

    • 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
    • C82 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Macroeconomic Data; Data Access
    • E66 - Macroeconomics and Monetary Economics - - Macroeconomic Policy, Macroeconomic Aspects of Public Finance, and General Outlook - - - General Outlook and Conditions

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