Communicating Uncertainty in Official Economic Statistics (WP-14-08)


Charles F. Manski

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 urges agencies 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 nonsampling error. The researcher finds it useful to distinguish transitory statistical uncertainty, permanent statistical uncertainty, and conceptual uncertainty. The paper illustrates how each arises as the Bureau of Economic Analysis periodically revises GDP estimates, the Census Bureau generates household income statistics from surveys with nonresponse, and the Bureau of Labor Statistics seasonally adjusts employment statistics.

Charles F. Manski, Board of Trustees Professor in Economics, Faculty Fellow, Institute for Policy Research, Northwestern University

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