Title: Why President Trump's "Fake" Economic Data Claims Pose a Threat
"Data is the lifeblood of our economy, just as crucial as roads and bridges," stated the speaker.
Governments, corporations, and various entities heavily rely on ample data and historical trends to make judicious investments and decisions that significantly impact individuals' livelihoods. However, this vital information infrastructure, already grappling with funding, trust issues, and low response rates, now faces an increased likelihood of collapse, according to experts like Groshen.
The risks of changes to data under President Trump's administration, combined with concerns about potential cuts, are escalating. With world leaders, regulators, economists, and executives relying on statistical data for decades, these fears, amplified and in some instances realized, are justified.
Surveying people, a traditional data-gathering method, is undergoing a challenging phase. The falling response rates, acknowledges ex-BLS commissioner Beach, represent a terminal disease. This trend significantly impacts statistical data's volatility and accuracy.
Controversy surrounding data integrity has increased in recent months, worsened by political accusations and shut-downs of federal programs that serve underserved communities. As a response, some take "pot shots" at data, harming its credibility.
An instance of this exploitation occurred during August 2024, with the preliminary benchmark revisions of employment data for March 2024. The revision led to criticism, even accusations of fraud, of job statistics by the then-President Trump.
Yet, trust remains vital to statistical agencies. Without it, data becomes irrelevant, making it impossible for people to rely on reliable information.
In addition to dwindling response rates, statistical agencies face long-term funding challenges. These constraints have forced them to become more efficient, but with trade-offs in other areas. The survey Modernization of the Current Population Survey, for example, has been a five-year goal, but with no financial support.
The possibility of streamlining government presents risks to federal data. As the statistical agencies fall under discretionary funding, potential budget cuts could lead to funding cuts, threatening their ability to measure economic conditions.
However, some suggest that a consolidation of statistical agencies could benefit the data collection process. This consolidation, done right, could boost the agencies' efficiency and improve their performance.
Universities could even partner with federal agencies to run surveys and programs, offering an alternative solution. Nevertheless, some fear that lack of funding could lead to data being erased from relevant communities, impacting underrepresented groups and hindering efforts to address inequality.
Such consequences could have far-reaching chilling effects on marginalized communities, especially within the LGBTQ+ community. It is essential to maintain comprehensive data to support policies that address health, employment, and equity issues in these communities.
Businesses and economic analysts heavily rely on this data to make informed decisions and predictions, which can impact their profits and growth strategies. Without reliable data, the stability of the entire economy could be compromised, as informed decisions become more challenging to make.
