深陷信任危机！特朗普“政治清洗”正引发数据质量崩溃？

Core Insights - The report highlights the urgent need for support from the Trump administration and Congress to ensure U.S. statistical agencies can fulfill their essential duties and restore public confidence amid a deepening crisis [1] Group 1: Challenges Faced by Statistical Agencies - U.S. statistical agencies are struggling with weakened capabilities and damaged trust, requiring more funding and personnel [1] - Long-standing issues such as budget cuts and declining survey response rates, along with recent threats to their independence and integrity, have made their work increasingly difficult [1] - The report emphasizes the necessity for immediate action to prevent a severe decline in the ability of federal statistical agencies to meet growing information demands and address uncertainties regarding the credibility of federal statistical data [1] Group 2: Impact of Political Actions - Trump's administration has intensified pressure on federal statistical work, with actions that have left significant gaps in many agencies, leading to data issues as collateral damage from workforce reductions [1] - In August, Trump dismissed the head of the Bureau of Labor Statistics (BLS) following a weak non-farm payroll report, accusing her of manipulating data without evidence, which was refuted by economists and statisticians [2] - The report indicates that Trump's actions have forced the BLS to reconsider its approach, as his accusations have undermined future trust in statistical agencies [2] Group 3: Public Trust and Recommendations - A survey cited in the report shows public trust in federal data has declined from 57% in June to 52% in September [3] - The report identifies other actions taken by the government this year that have undermined official statistics, such as disbanding advisory committees and failing to fill leadership vacancies [3] - Recommendations include exempting key data agency positions from federal hiring freezes and urging Congress to fund upgrades for research and IT infrastructure to improve statistical quality [3]