Eve is here. In the United States, trust has been declining for a very long time, not only in government institutions, but also on an interpersonal and commercial level. And strangely, too little attention has been paid to the costs of this kind of loss of faith. for example. Rising contract costs are a form of friction, as commercial contracts are almost always very long-term, increasing legal review costs and negotiation effort. This article attempts to measure the damage caused by one type of decline in trust in official statistics, but we find that it is not trivial.
It makes perfect sense. If you have reason to doubt the data you have about an investment or project, you should either assign a higher discount rate to reflect the greater uncertainty or not proceed at all.
Written by Nicholas Bloom, Department of Economics, Stanford University. William Eberle Professor of Economics at Stanford University. Erica Groshen, Senior Economics Advisor, Cornell University School of Industrial and Labor Relations; Duncan Hobbs, Senior Fellow, American Enterprise Institute. Michael R. Strain and Paul F. Orefice, Senior Fellows in Political Economy at the American Enterprise Institute. Professor of Practice at Georgetown University. Originally published on VoxEU
Trust in official economic statistics has become an increasingly prominent policy issue, including in the United States, where the head of the Bureau of Labor Statistics was fired in August 2025 following allegations that the agency’s data had been manipulated. This column shows that these events sharply increased economic policy uncertainty, and existing estimates link uncertainty to macroeconomic outcomes and suggest that the resulting loss of confidence could have reduced U.S. GDP by about $20 billion. Although some economic activities postponed during uncertain times may ultimately be implemented at a later date, there is reason to think that at least some impacts may be lasting.
Trust in official economic statistics has become an increasingly salient policy issue. Across the developed world, political pressure on statistical agencies, declining survey response rates, and concerns about the difficulty of measuring a rapidly changing economy are raising questions about the resilience of public data systems. In the United States, these debates intensified after the August 2025 firing of Bureau of Labor Statistics (BLS) Director Erica McEnterfer and accompanying public allegations that the agency’s data had been manipulated.
Economists have long argued that uncertainty can impose significant economic costs. Studies following Bernanke (1983) and Bloom (2009) have shown that firms and households delay decision-making and that increased uncertainty reduces investment, employment, and consumption. Increased uncertainty in foreign markets can negatively impact domestic investment, consumption, and economic growth (Bali et al. 2017, Biljanovska et al. 2021). VoxEU columns have repeatedly highlighted how uncertainty shocks weaken economic activity and complicate policy decisions (Bloom 2014, Baker et al. 2020, Weber et al. 2021, Salish 2026). However, while economists have studied uncertainty extensively, one of its underlying determinants, trust in official statistics, has received less attention.
Our recent research investigates whether the sudden decline in confidence in U.S. federal statistics has caused measurable economic costs. We found evidence that that happened. The events surrounding the firing of the BLS Director in August 2025 sharply increased economic policy uncertainty, and existing estimates linking uncertainty to macroeconomic outcomes suggest that the resulting loss of confidence could have reduced U.S. GDP by approximately $20 billion.
Although this estimate is necessarily imprecise, the broader implications are clear. Reliable federal statistics are valuable economic infrastructure. This finding is particularly relevant for democracies, which tend to maintain high-performance statistical institutions as part of their economic infrastructure (Di Gennaro 2024).
Why is statistical reliability important?
BLS produces many indicators that support U.S. economic decision-making, including the unemployment rate, monthly payroll employment estimates, wage indicators, and the consumer price index. These data influence monetary policy, financial markets, public spending, wage negotiations, and private sector investment decisions.
Its importance extends beyond government. A survey of business economists by the National Association for Business Economics (Hughes-Cromwick and Coronado, 2019) found that 95% consider government statistics important to their job, and labor market indicators rank among the most important inputs to forecasting and planning.
Reliable statistics also create value because they reduce uncertainty. When inflation and labor market conditions are measured consistently and reliably, businesses can invest with more confidence. Households can make more confident long-term decisions about wages, employment prospects and prices. Policymakers can more effectively coordinate fiscal and monetary policy.
These benefits are similar to other forms of public infrastructure: they are diffuse, spread across the economy, and difficult to put a price on directly. However, one of the channels through which reliable statistics create value (uncertainty reduction) can be measured indirectly.
Measuring uncertainty shocks
To estimate the economic impact of the August 2025 events, we use the Economic Policy Uncertainty (EPU) index developed by Baker et al. (2016). This index tracks the proportion of newspaper articles that discuss economic policy uncertainty and is widely used as a measure of uncertainty shocks. It rose sharply during the global financial crisis in 2008, the coronavirus pandemic in 2020, and the US fiscal brinkmanship policies in 2011 and 2013.
After the BLS Commissioner was fired on August 1, 2025, the EPU index rose sharply (Figure 1). Comparing the week before the announcement (July 25th to 31st) and the following week (August 1st to 7th), the index rose by about 127 points, an increase of more than 50%.
Figure 1 Economic policy uncertainty index before and after launch on August 1, 2025
Note: This figure shows the daily Economic Policy Uncertainty Index for the week before and after August 1st. The solid black line is the raw daily index, and the dashed lines on either side of August 1st represent the average EPU index for the weeks before and after August 1st, respectively.
Source: https://policyuncertainty.com/media/All_Daily_Policy_Data.csv, retrieved October 27, 2025.
This increase is not entirely due to concerns about statistical reliability due to layoffs. On the same day, there were also significant downward revisions to employment statistics and the announcement of the resignation of Federal Reserve Board President Adriana Kugler. We adjust our estimates using media references specifically related to BLS controversies and employment reviews to isolate what is thought to be related to declining trust in federal statistics.
Using this more conservative approach, we estimate that the EPU index would have increased by approximately 22 points, or approximately 9%, due to decreased confidence in BLS independence and data integrity.
Converting uncertainty into economic costs
A large body of literature shows that increased uncertainty suppresses economic activity. Bernanke (1983) argued that uncertainty causes firms to postpone irrevocable investment decisions. Bloom (2009) found that uncertainty shocks reduce employment and investment, while subsequent studies showed that policy uncertainty is associated with lower output, employment, and productivity growth.
Applying estimates from this literature to the observed increase in uncertainty suggests that the decline in confidence associated with the August 2025 event could have reduced GDP by approximately $20 billion.
This estimate should be interpreted with caution. It captures only one channel for which reliable statistics are important: effects operating through increased uncertainty. This does not include other important benefits of federal statistics, such as improving labor market matching, informing productivity measurements, facilitating accurate inflation adjustments, and enabling evidence-based policymaking.
Still, the comparison with agency budgets is striking. FY 2025 spending on the BLS was approximately $704 million. Therefore, our estimates suggest that the small decline in trust associated with the events of August 2025 could have imposed economic costs many times the agency’s annual budget.
Importantly, the public has not completely lost confidence in BLS data. Financial markets, businesses, and policy makers continued to rely heavily on official statistics. Therefore, the estimated losses reflect only a partial decline in trust over a short period of time.
Temporary disruption or permanent damage?
One important question is whether such uncertainty shocks simply slow down activity, or rather create more persistent economic losses.
Some economic activities postponed during uncertain times may eventually be implemented at a later date. But there is reason to believe that at least some of its effects may last.
First, reputational damage to statistical institutions can persist beyond the immediate news cycle. Trust in official statistics is cumulative and varies from institution to institution. Once trust is questioned, it can take a significant amount of time to rebuild trust.
Second, many forms of investment are not simply deferred. Decisions regarding research and development, employee training, organizational restructuring, new business creation, etc. may be canceled entirely rather than postponed. Intangible investments in particular appear to be particularly sensitive to uncertainty.
These concerns come at a time when many statistical agencies are already facing operational strain. Low survey response rates, staffing constraints, aging technical systems, and funding pressures are making it difficult to produce high-quality economic statistics across the developed world.
In the United States, a recent report by the American Statistical Association (Auerbach et al. 2024) warned that federal statistical agencies remain vulnerable to political interference due to insufficient protections for professional autonomy. Meanwhile, BLS’s budget has declined significantly in real terms since 2010, limiting its ability to modernize its research and invest in new statistical methods.
Statistical institutions as economic infrastructure
Policy discussions about infrastructure typically focus on roads, ports, energy systems, and broadband networks. But statistical institutions also provide the basic infrastructure of modern economies.
In the United States, the BLS, Census Bureau, Bureau of Economic Analysis, and related agencies produce information that enables markets and government to function more effectively. Their results guide monetary policy, shape fiscal decision-making, support private sector planning, and improve public accountability.
Because these institutions are integrated into the overall economic decision-making process, their benefits are difficult to observe precisely. But the events of August 2025 suggest that the costs of eroding trust in official statistics can be immediate and significant.
Protecting the reliability, independence, and technical competence of federal statistical agencies is therefore not just an administrative concern. It’s a consequential economic thing.
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