The Value of Reliable Statistics

Nicholas Bloom (), Erica Groshen, Duncan Hobbs and Michael Strain ()
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Nicholas Bloom: Stanford University
Erica Groshen: Cornell University
Duncan Hobbs: American Enterprise Institute
Michael Strain: American Enterprise Institute

No 18631, IZA Discussion Papers from IZA Network @ LISER

Abstract: On August 1, 2025, President Trump fired the head of the U.S. Bureau of Labor Statistics (BLS) and claimed that the agency’s data were “rigged.†In the aftermath, measures of economic policy uncertainty rose sharply, consistent with the idea that reduced trust in official data increases uncertainty for investors, businesses, and households. We use an event-study design to estimate the effect of the firing on policy uncertainty, and then map that increase in uncertainty into implied macroeconomic outcomes. This yields a back-of-the-envelope estimate of the marginal value of public trust in official statistics. Our baseline estimate implies that preserving trust in the integrity and quality of official statistics generates economic benefits of about $25 for every $1 spent on the agency’s budget.

Keywords: statistics; uncertainty; policy uncertainty (search for similar items in EconPapers)
JEL-codes: D8 E01 J00 (search for similar items in EconPapers)
Date: 2026-05
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