CMStatistics 2020: Start Registration
View Submission - CFE
A0442
Title: Communicating data uncertainty: Experimental evidence for U.K. GDP Authors:  Ana Galvao - University of Warwick (United Kingdom)
James Mitchell - University of Warwick (United Kingdom) [presenting]
Johnny Runge - National Institute of Economic and Social Research (United Kingdom)
Abstract: Many economic statistics, like GDP and inflation, are measured with error. But estimates are commonly communicated without any direct quantitative indication of their uncertainty. To assess if and how the public interprets and understands UK GDP data uncertainty, we conduct two sets of a randomized controlled online experiment, one at a time of growth and one during a recession. The surveys are designed to assess: (1) perceptions of the uncertainty in single-valued GDP growth numbers; (2) the public's interpretation and understanding of uncertainty information communicated in different formats; and (3) how communicating uncertainty affects trust in the data and the producer of these data. We find that the majority of the public understands that there is uncertainty inherent in GDP numbers, but communicating uncertainty information improves the public's understanding of why data revisions happen. It encourages them not to take GDP point estimates at face-value but does not decrease trust in the data. We find that it is especially helpful to communicate uncertainty information quantitatively using intervals, density strips and bell curves.