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Measuring Data Uncertainty : An Application using the Bank of England’s “Fan Charts” for Historical GDP Growth

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  • Galvao, Ana Beatriz

    (University of Warwick)

  • Mitchell, James

    (University of Warwick)

Abstract

Historical economic data are often uncertain due to sampling and non-sampling errors. But data uncertainty is rarely communicated quantitatively. An exception are the “fan charts” for historical GDP growth published at the Bank of England. We propose a generic loss function based approach to extract from these ex ante density forecasts a quantitative measure of unforecastable data uncertainty. We find GDP data uncertainty in the UK rose sharply at the onset of the 2008/9 recession; and that data uncertainty is positively correlated with popular estimates of macroeconomic uncertainty.

Suggested Citation

  • Galvao, Ana Beatriz & Mitchell, James, 2019. "Measuring Data Uncertainty : An Application using the Bank of England’s “Fan Charts” for Historical GDP Growth," EMF Research Papers 24, Economic Modelling and Forecasting Group.
  • Handle: RePEc:wrk:wrkemf:24
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    References listed on IDEAS

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    Cited by:

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    3. Joshy Easaw & Christian Grimme, 2021. "The Impact of Aggregate Uncertainty on Firm-Level Uncertainty," CESifo Working Paper Series 8934, CESifo.

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    More about this item

    Keywords

    data revisions ; macroeconomic uncertainty ; ex ante uncertainty ; ex post uncertainty ; density forecast calibration ; backcasts;
    All these keywords.

    JEL classification:

    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles

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