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dc.contributor.authorManski, Charles F.
dc.date.accessioned2015-09-08T20:47:02Z
dc.date.available2015-09-08T20:47:02Z
dc.date.issued2014-10
dc.identifier.urihttps://hdl.handle.net/1813/40830
dc.description.abstractFederal 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 nonsampling 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 nonresponse, and the Bureau of Labor Statistics seasonally adjusts employment statistics. I anchor my discussion of communication of uncertainty in the contribution of Morgenstern (1963), who argued forcefully for agency publication of error estimates for official economic statistics.en_US
dc.language.isoen_USen_US
dc.relation.hasversionhttp://www.ncrn.info/bibliography/communicating-uncertainty-official-economic-statisticsen_US
dc.titleCommunicating Uncertainty in Official Economic Statistics: An Appraisal Fifty Years after Morgensternen_US
dc.typepreprinten_US


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Statistics