Yves here. The decline in trust has been a pervasive issue in the United States, affecting not only government institutions but also interpersonal and commercial interactions. Strangely, the consequences of this waning confidence are often overlooked. For example, commercial agreements have grown increasingly complex, resulting in higher legal review costs and more intensive negotiations, ultimately raising contracting expenses. This article aims to quantify the impact of diminishing trust specifically in official statistics, revealing that the repercussions are significant.
This observation is quite logical. When you doubt the information related to an investment or project, you should apply a higher discount rate due to the increased uncertainty, or possibly decide against proceeding altogether.
By Nicholas Bloom, Department of Economics, Stanford University; William Eberle Professor of Economics Stanford University; Erica Groshen, Senior Economics Advisor, School of Industrial and Labor Relations Cornell University; Duncan Hobbs, Senior Research Associate American Enterprise Institute; and Michael R. Strain, Paul F. Oreffice Senior Fellow in Political Economy American Enterprise Institute; Professor of Practice Georgetown University. Originally published at VoxEU
Trust in official economic statistics has become a pressing policy concern, particularly in the U.S., where the Commissioner of the Bureau of Labor Statistics (BLS) was dismissed in August 2025 due to allegations of data manipulation. This incident led to a considerable rise in economic policy uncertainty, with existing estimates suggesting that this loss of trust may have resulted in a US GDP decline of about $20 billion. Although some economic activities postponed during periods of uncertainty may occur later, there are reasons to believe that at least a portion of this impact could be long-lasting.
Concerns over the reliability of official economic statistics have intensified across advanced economies, fueled by political pressures on statistical agencies, declining survey response rates, and the increasing challenge of measuring rapidly evolving economies. In the U.S., these discussions surged after August 2025, following the removal of BLS Commissioner Erika McEntarfer and public allegations of data manipulation.
Economists have long maintained that uncertainty can incur substantial economic costs. Research by Bernanke (1983) and Bloom (2009) has shown that heightened uncertainty hampers investment, hiring, and consumption as firms and households hesitate to make decisions. Increased uncertainty in international markets can adversely affect domestic investment, consumption, and economic growth (Bali et al. 2017, Biljanovska et al. 2021). Numerous VoxEU columns have discussed how uncertainty shocks weaken economic activity and complicate policymaking (Bloom 2014, Baker et al. 2020, Weber et al. 2021, Salish 2026). Yet, while uncertainty has been extensively studied by economists, much less focus has been placed on one of its key drivers: trust in official statistics.
Our recent research investigates whether a sudden loss of confidence in U.S. federal statistics resulted in measurable economic costs. The findings indicate that it indeed did. The events surrounding the dismissal of the BLS Commissioner in August 2025 caused a sharp rise in economic policy uncertainty. Based on existing estimates correlating uncertainty with macroeconomic outcomes, we conclude that this decline in trust may have reduced U.S. GDP by approximately $20 billion.
While this figure is necessarily an approximation, a broader implication emerges: reliable federal statistics constitute valuable economic infrastructure. This finding is particularly relevant for democracies, which typically maintain high-performing statistical agencies as a part of their economic framework (Di Gennaro 2024).
Why Statistical Credibility Matters
The BLS produces crucial indicators that inform economic decision-making in the U.S., including unemployment rates, monthly payroll employment estimates, wage metrics, and the Consumer Price Index. These data shape monetary policy, impact financial markets, guide public spending, influence wage negotiations, and affect private-sector investment decisions.
The significance of these statistics extends far beyond government use. A survey conducted by the National Association for Business Economics (Hughes-Cromwick and Coronado 2019) revealed that 95% of business economists consider government statistics vital for their work, with labor market indicators ranked as some of the most critical factors for forecasting and planning.
Reliable statistics create value primarily by reducing uncertainty. Companies can invest more confidently when inflation and labor market conditions are consistently and credibly measured. Households can make long-term decisions with greater assurance regarding wages, employment prospects, and prices. Policymakers can more effectively calibrate fiscal and monetary policy.
These advantages resemble other forms of public infrastructure: they are widespread, benefit the entire economy, and are challenging to quantify directly. However, one measurable avenue through which trustworthy statistics yield benefits—reducing uncertainty—can be assessed indirectly.
Measuring the Uncertainty Shock
To gauge the economic impacts of the events in August 2025, we leverage the Economic Policy Uncertainty (EPU) Index developed by Baker et al. (2016). This index tracks the frequency of newspaper articles addressing economic policy uncertainty and has become a widely recognized measure for uncertainty shocks. It surged dramatically during various episodes, including the 2008 Global Financial Crisis, the 2020 COVID-19 pandemic, and U.S. fiscal brinkmanship in 2011 and 2013.
After the dismissal of the BLS Commissioner on August 1, 2025, the EPU Index experienced a steep rise (Figure 1). Comparing the week before the announcement (July 25–31) with the subsequent week (August 1–7), the index increased by approximately 127 points, marking a more than 50% rise.
Figure 1 Economic Policy Uncertainty Index around August 1, 2025 firing
Note: This figure illustrates the daily Economic Policy Uncertainty Index in the week leading up to and following August 1. The solid black line represents the raw daily index, while the dashed lines around August 1 indicate the average EPU index for the week before and after.
Source: https://policyuncertainty.com/media/All_Daily_Policy_Data.csv, retrieved October 27, 2025.
Not all of this increase can be solely linked to concerns over statistical credibility triggered by the dismissal. The same day also included significant downward revisions to payroll employment estimates and the resignation announcement of Federal Reserve Governor Adriana Kugler. To isolate the part of this increase plausibly associated with reduced trust in federal statistics, we adjust the estimate using media references specifically related to the BLS controversy and employment revisions.
By taking a more conservative approach, we estimate that the erosion of trust in the independence and integrity of the BLS data raised the EPU Index by about 22 points, or approximately 9%.
Translating Uncertainty into Economic Costs
A substantial body of research indicates that increases in uncertainty hinder economic activity. Bernanke (1983) argued that uncertainty leads businesses to delay irreversible investment decisions. Bloom (2009) demonstrated that uncertainty shocks diminish hiring and investment, while subsequent studies have linked policy uncertainty to declines in output, employment, and productivity growth.
Applying insights from this research to the observed rise in uncertainty suggests that the trust decline associated with the August 2025 events may have resulted in a GDP reduction of approximately $20 billion.
This estimate must be interpreted with caution. It reflects only one channel through which trustworthy statistics hold value: the effect realized through increased uncertainty. It does not account for other important advantages of federal statistics, such as enhancing labor market matching, informing productivity assessments, facilitating precise inflation adjustments, or enabling evidence-based policymaking.
Despite this, the comparison with agency budgets is telling. The fiscal year 2025 budget for the BLS was around $704 million. This implies that the marginal erosion of trust linked to the August 2025 events could lead to economic costs far exceeding the agency’s annual budget.
Importantly, the public did not entirely relinquish confidence in BLS data. Financial markets, businesses, and policymakers continued to depend heavily on official statistics. Consequently, the estimated losses reflect only a partial decline in trust over a brief time frame.
Temporary Disruption or Lasting Damage?
A crucial question is whether these uncertainty shocks merely postpone economic activity or inflict longer-lasting losses.
Some economic activities delayed during periods of uncertainty may eventually proceed later. However, there are valid reasons to believe that a portion of this impact may persist.
First, reputational harm to statistical agencies can linger beyond the immediate news cycle. Trust in official statistics is cumulative and institution-specific; once credibility is called into question publicly, restoring confidence can require considerable time.
Second, not all investment decisions can simply be deferred. Choices related to research and development, workforce training, organizational restructuring, or new business formation may be permanently canceled rather than just postponed. Intangible investments, in particular, appear to be particularly sensitive to uncertainty.
These concerns arise at a time when many statistical agencies are already facing operational challenges. Declining survey response rates, staffing limitations, outdated technology, and budget constraints have complicated the accurate production of economic statistics across advanced economies.
In the U.S., a recent report by the American Statistical Association (Auerbach et al. 2024) cautioned that federal statistical agencies remain susceptible to political interference due to inadequate protections for professional autonomy. Simultaneously, the BLS budget has decreased significantly in real terms since 2010, restricting its capacity to modernize surveys and invest in advanced statistical methods.
Statistical Agencies as Economic Infrastructure
Discussions about infrastructure often center on roads, ports, energy systems, or broadband networks. However, statistical agencies also represent fundamental infrastructure for contemporary economies.
In the U.S., the BLS, the Census Bureau, the Bureau of Economic Analysis, and related agencies generate crucial information that enables markets and governments to operate more efficiently. Their outputs guide monetary policies, shape fiscal decisions, support private-sector planning, and enhance public accountability.
The advantages provided by these institutions are challenging to observe precisely because they are embedded within economic decision-making. Nonetheless, the events of August 2025 indicate that undermining trust in official statistics can lead to significant and immediate costs.
As such, safeguarding the credibility, independence, and technical capacity of federal statistical agencies is not merely an administrative matter; it is a critical economic concern.
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