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Trump Terminates BLS Commissioner: Outcry and Consequences

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by Giorgi Kostiuk

2 hours ago


President Trump's decision to fire the head of the Bureau of Labor Statistics has sparked public debate, raising concerns about the impact on statistics and criticism from politicians and economists.

Official Justifications for the Firing

National Economic Council Director Kevin Hassett attempted to justify the firing but did not provide concrete evidence. On NBC News, he stated, "Revisions are hard evidence," yet did not disclose the nature of this evidence. Hassett focused on recent changes in job reports that served as the basis for the termination, failing to clarify whether the White House had previously inquired with the former commissioner about the reasons for these changes.

Reactions from Former Officials and Lawmakers

Criticism of Trump's decision came swiftly. William Beach, a former BLS commissioner appointed by Trump, called the firing "totally groundless," warning it sets a dangerous precedent. On CNN, he added, "If they get a new commissioner, and this person provides bad numbers, people will suspect political influence over the reliability of the data." Senate Minority Leader Chuck Schumer condemned Trump's actions, asserting it exacerbated the existing chaos.

Discussion on Data Collection Methods

In light of the criticisms about the firing itself, others began to question the methods used to collect employment data. Brian Moynihan, CEO of Bank of America, stated on CBS News, "The government still uses surveys that frankly aren't that effective anymore." He suggested updating the system to ensure more reliable data. Senator Rand Paul also expressed concerns, stating that firing those who provide statistics complicates the acquisition of objective data.

The termination of the head of the Bureau of Labor Statistics not only may influence data integrity but also poses a threat to trust in statistical information overall. Discussions about improving data collection methods could be a critical step in mitigating potential political influence over statistics.

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