Low participation is a problem because surveying citizens is about much more than just satisfying Uncle Sam’s curiosity. Bosses and investors rely on accurate data about GDP growth, unemployment, inflation and much more to manage businesses and allocate capital. When information becomes less reliable, it becomes more difficult to make investment decisions. Some may be delayed, creating potential pressure on the economy.
But how much stretch? A new working paper from Nicholas Bloom of Stanford University, Erica Groschen, former head of the Bureau of Labor Statistics (BLS), now at Cornell University, and Duncan Hobbs and Michael Strain of the think-tank American Enterprise Institute threatens one estimate. The authors claim, maintaining confidence in the “integrity and quality of official data” yields economic benefits of approximately $25 for every $1 spent on the BLS, the agency with an annual budget of $700m that is responsible for many of these data.
To reach their conclusions the Quartet analyzed a scandalous episode in the recent history of BLS. On August 1, 2025, Donald Trump fired Erica McEnterfer, appointed by his predecessor Joe Biden, as commissioner of the agency. The President alleged, without evidence, that the BLS’s massive decline in recent jobs numbers had been “rigged to make the Republicans and I look bad”.
In fact, it was the unprovoked dismissal that looked bad in the eyes of many observers. Over the next seven days, the average value of the Index of Economic Policy Uncertainty (EPU), which tracks the number of articles mentioning such uncertainty published daily in US newspapers, increased by 50% compared with the previous week. It was also a marked jump when comparing the chaos caused by Mr Trump’s trade war in April 2025 and his actual war in Iran over the past two months. Based on Mr. Bloom’s earlier study with other colleagues of the impact of the EPU on business investment, industrial production, and employment, the authors estimate that the boom would have reduced US GDP by $100 billion (0.33%) and non-farm payrolls by $168,000 (0.11%).
Some of these may not be a direct result of Ms. McEnterfer’s firing. Part of this was probably due to major jobs revisions. The unrelated resignation of a Federal Reserve governor on the same day may also have played a role. But even after controlling for those variables, researchers believe the McEntire case cut GDP by $20 billion and employment by 31,000 jobs.
A brazen presidential attack on the reliance of statisticians could, admittedly, do more harm than a slow-motion crisis caused by uncooperative respondents. But studies show that reliable data have real value. To abandon them would be an irreparable loss.
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