The Trump administration stands on the cusp of something potentially transformative. If President Trump succeeds in unleashing a new era of energy abundance and securing America’s leadership in artificial intelligence, the economic gains will be profound. Lower energy costs, faster innovation and greater industrial dynamism would provide a powerful tailwind to American productivity and growth.
But if the president continues to treat disagreement as disloyalty — especially from vital, independent agencies such as the Bureau of Labor Statistics and the Congressional Budget Office — then Trump’s second term could leave a dark mark on the country. He has been bullying the chair of the Federal Reserve for months. The president and his proxies launched nonstop attacks on the CBO during the “One Big Beautiful Bill” debate. And now, Trump has fired the head of the statistics bureau in response to its latest jobs report.
It’s ugly business. Some of these agencies are not just recordkeepers of past economic activity; they are part of the infrastructure of a modern, data-driven economy. From job seekers and entrepreneurs to homeowners and policymakers, nearly every consequential decision in modern America depends on the credibility and quality of the numbers these agencies produce. In an era shaped by artificial intelligence, energy transformation and digitized commerce, the United States needs a statistical system that is modern, agile and protected from political interference.
To be sure, these agencies are far from perfect. I have been a strong critic of many of them. The CBO’s budget models rest on questionable assumptions and routinely underestimate the effects of rising debt on interest rates and investment. The office projected that the debt burden would reach 166% of GDP or higher, and yet its projection of annual inflation stays around 2% as if unaffected by the rising debt. Such projections would be laughable, if they weren’t so dangerously disconnected from fiscal reality.
The Bureau of Labor Statistics also deserves criticism. The headline unemployment rate masks labor-market weakness by overlooking discouraged workers and those stuck in part-time jobs. The agency has also been slow to adapt its methods to reflect the modern economy and has struggled to capture the rise of gig work, hybrid jobs and other emerging trends. It has resisted using real-time administrative and private data that could improve the speed and accuracy of its reporting. Add to this a bureaucratic culture defined by wariness of reform, overly rigid job classifications and methodological opacity, and it’s easy to see why critics on both sides of the aisle push for change.
The issue has drawn the administration’s ire, however, is the bureau’s increasingly erratic employment estimates followed by significant downward revisions — which the president and his allies see as evidence that the system is rigged. It’s not rigged, but there is no doubt that it’s broken. According to John Podhoretz at Commentary magazine, during the last 30 months “there have been 30 revisions. … Twenty-five of them have been downward revisions, and five of them have been upward revisions.” And some of these revisions have been extremely large. One reason the jobs reports have become less reliable is the sharp decline in the monthly employer survey response rates, which have fallen from around 60% pre-COVID to just 43% today. This drop has made it significantly harder to accurately measure employment.
Still, flaws are different from bad faith. While I am glad the administration is drawing attention to the need for reform at the bureau, it’s going about it the wrong way. First, firing the commissioner, as Trump did last week, won’t fix the system. Second, as Dominic Pino pointed out in National Review, Commerce Secretary Howard Lutnick recently disbanded the Federal Economic Statistics Advisory Committee, an expert advisory group that was actively working on this accuracy problem. Composed of unpaid professionals from academia and industry, the committee had been helping the bureau and other statistical agencies explore ways to improve data quality by boosting response rates — drawing on lessons from the U.K., Canada and Germany. Its elimination was not a cost-saving move but a decision that undercuts ongoing efforts to strengthen the integrity of federal economic data, even as the administration publicly expresses frustration with the quality of those same data.
Firing the head of the Bureau of Labor Statistics because the agency produced a revised — and hence more accurate — number that told an inconvenient truth won’t help the administration either. The administration’s political replacement may not be taken seriously, especially if employment numbers improve.
Trump wants to restore American economic dynamism. But he should begin by restoring confidence in the institutions that help measure and guide it. That means respecting their independence, even when their findings complicate his message. It also means pursuing real reform, not political retaliation, when they fall short.
Veronique de Rugy is a senior research fellow at the Mercatus Center at George Mason University. This article was produced in collaboration with Creators Syndicate.
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Ideas expressed in the piece
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The administration’s attacks on independent economic agencies like the Bureau of Labor Statistics and Congressional Budget Office represent a dangerous pattern of treating disagreement as disloyalty that threatens the foundation of America’s data-driven economy[1]. These agencies serve as critical infrastructure for modern economic decision-making, from job seekers and entrepreneurs to policymakers, making their credibility essential for the functioning of the American economy.
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While these statistical agencies have legitimate flaws that deserve criticism, including outdated methodologies and questionable assumptions in budget projections, these shortcomings reflect institutional problems rather than deliberate manipulation[2]. The Bureau of Labor Statistics struggles with declining response rates and has been slow to adapt to the modern gig economy, but data revisions are a normal feature of statistical reporting designed to improve accuracy over time rather than evidence of systemic bias.
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The administration’s approach of firing officials and eliminating advisory committees undermines genuine reform efforts and damages institutional credibility without addressing underlying problems[2]. Trump’s dismissal of the BLS commissioner and Commerce Secretary Lutnick’s disbanding of the Federal Economic Statistics Advisory Committee represents political retaliation that hinders ongoing efforts to improve data quality and response rates.
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Restoring American economic dynamism requires strengthening rather than attacking the institutions that measure and guide economic progress, meaning the administration should respect agency independence even when findings complicate political messaging. The focus should be on pursuing substantive reform rather than political interference, as undermining public trust in economic data threatens both the administration’s credibility and the broader economy’s foundation.
Different views on the topic
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The administration’s criticism of the Bureau of Labor Statistics reflects legitimate concerns about data integrity, particularly given the pattern of significant downward revisions that have occurred in recent employment reports[1]. Trump’s defenders point to Goldman Sachs findings that the two-month revisions on recent jobs reports were the largest since 1968 outside of a recession, suggesting genuine problems with the agency’s initial data collection and reporting processes.
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The White House maintains that its actions aim to ensure accurate data reporting rather than suppress unfavorable information, emphasizing the need for reliable economic statistics that reflect reality[1]. Trump’s aides argue that their fundamental focus centers on ensuring any data provides an accurate view of economic conditions, with the administration claiming to operate with complete transparency in its approach to government information.
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Economic experts acknowledge that the current statistical system faces real challenges that justify reform efforts, including significantly reduced employer survey response rates that have dropped from 60% pre-COVID to just 43% currently[2]. These declining participation rates make it substantially harder to accurately measure employment, contributing to the reliability issues that have drawn administrative attention to the need for systematic improvements in data collection methods.