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Communicating Uncertainty in Official Economic Statistics

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  • Charles F. Manski

Abstract

Federal statistical agencies in the United States and analogous agencies elsewhere commonly report official economic statistics as point estimates, without accompanying measures of error. Users of the statistics may incorrectly view them as error-free or may incorrectly conjecture error magnitudes. This paper discusses strategies to mitigate misinterpretation of official statistics by communicating uncertainty to the public. Sampling error can be measured using established statistical principles. The challenge is to satisfactorily measure the various forms of non-sampling error. I find it useful to distinguish transitory statistical uncertainty, permanent statistical uncertainty, and conceptual uncertainty. I illustrate how each arises as the Bureau of Economic Analysis periodically revises GDP estimates, the Census Bureau generates household income statistics from surveys with non-response, and the Bureau of Labor Statistics seasonally adjusts employment statistics.

Suggested Citation

  • Charles F. Manski, 2014. "Communicating Uncertainty in Official Economic Statistics," NBER Working Papers 20098, National Bureau of Economic Research, Inc.
    • Handle: RePEc:nbr:nberwo:20098
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    References listed on IDEAS

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    Cited by:

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    2. Philip J. Cook & Jens Ludwig, 2014. "Elusive Facts About Gun Violence: Where Good Surveys Go Bad," SADO - Working Papers 166, Small Arms Data Observatory.
    3. David J. Hand, 2018. "Statistical challenges of administrative and transaction data," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 181(3), pages 555-605, June.

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    More about this item

    JEL classification:

    • C82 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Macroeconomic Data; Data Access
    • E01 - Macroeconomics and Monetary Economics - - General - - - Measurement and Data on National Income and Product Accounts and Wealth; Environmental Accounts
    • I32 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty - - - Measurement and Analysis of Poverty

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