Data is America's Foundation

Table of Contents

Data Infrastructure: America’s Foundation

The destruction of America’s data infrastructure is eliminating the credibility that has been the foundation of American global leadership—and without reliable information systems, recovery from mounting economic and democratic challenges becomes nearly impossible.

Markets Can’t Trust the Numbers

Walmart builds distribution centers based on Census Bureau population projections. JPMorgan Chase evaluates mortgage risk using Bureau of Labor Statistics employment data. Tesla plans manufacturing capacity with Department of Energy consumption forecasts. Every major business decision starts with federal data.

This information infrastructure has powered American economic leadership since World War II. While other nations struggled with unreliable statistics, American businesses made trillion-dollar decisions on data they could trust. International investors allocated capital based on American economic indicators. Global markets operated on the assumption that U.S. statistics were accurate and beyond political manipulation.

That foundation cracked on August 1, 2025.

The Bureau of Labor Statistics released employment data showing the economy added 73,000 jobs in July—half the expected 175,000. The report revealed that May and June figures had been revised downward by 258,000 positions. President Trump fired BLS Commissioner Erika McEntarfer that afternoon, accusing her of manipulating data “for political purposes” [1].

Financial markets reacted strongly, with the Dow falling 500 points by close [2]. The ongoing market turbulence was more than a reaction to the numbers themselves; it reflects a deeper issue as market participants grapple with working alongside an America that seems indifferent to institutional norms and data integrity.

McEntarfer had been confirmed by the Senate eighteen months earlier. She sees employment numbers Wednesday before publication and plays no role in data collection [3]. The revisions Trump criticized follow transparent procedures operating since 1979 [4].

Firing the statistician changes nothing about economic reality. The message to both domestic and international partners was unmistakable: American institutions now report what politicians want to hear.

Who Depends on Federal Data

Businesses depend on federal data across every sector. The Census Bureau provides demographic information for market analysis. Agricultural corporations trade futures based on Department of Agriculture crop reports. Energy companies invest billions using Department of Energy forecasts. Manufacturing firms plan workforce strategies with Bureau of Labor Statistics productivity data.

America is the sum of all its diverse populations. The country’s strength lies in the rich tapestry of its people: rural communities, working families, women, and the diverse populations who represent the true strength of America’s global power. We need to know who we are in order to maintain our national strength. When data quality falters, vital segments become “invisible” in the statistics that shape policy, resources, and opportunity. America is about all Americans having their experiences and needs accurately recognized and addressed.

This invisibility creates real harm. When underrepresented groups are left out of economic and social data, policies fail to meet their realities—leaving millions without adequate housing, healthcare, education, or jobs. That weakens the middle class that holds the nation together. A thriving America depends on the participation and well-being of all its people.

Our statistical credibility developed over eight decades. The Bureau of Labor Statistics, established in 1884, pioneered methodologies that other nations copied. Census Bureau surveys provide demographic foundations for congressional redistricting and retail expansion. Federal Reserve research guides monetary policy affecting global markets.

International investors trust American markets because they trust American data. Foreign pension funds allocate assets based on U.S. statistics. Multinational corporations choose facility locations using Census demographics and BLS employment trends. This trust creates capital flows, jobs, and economic growth.

America’s strength is found in its diversity—and that strength depends on seeing and supporting every part of its people. Federal data infrastructure enables this recognition while powering American economic leadership. Destroying it attacks the information foundation of that leadership.

How Data Creates Lasting Value

Federal research and data agencies generate substantial economic returns. NIH funding produces $2.46 in economic activity per dollar invested [5]. Federal R&D spending overall generates 5-15 times higher multipliers than generic government expenditures, with some programs like weather forecasting achieving 79:1 returns [6]. The Census Bureau supports $2.8 trillion in annual federal funding and guides trillions in business spending [7].

These impressive returns reflect deeper mechanisms that create lasting value beyond initial investments.

Carryover Effects: How Research and Data Compound

Federal research and statistical systems create returns that continue long after a budget year closes. Those returns accrue through four channels.

First, knowledge and platform spillovers. Once a dataset, method, or platform is built—GPS, weather observing networks, core surveys, health and energy registries—it gets reused across sectors for decades. Each subsequent user does not have to rebuild the foundation, which is why the benefits scale with time rather than stop at appropriations.

Second, crowd-in of private R&D. Public research spending induces additional private investment when the scientific frontier and the measurement base are both visible and credible. Empirical work consistently finds that public R&D does not displace private activity; it attracts it, and the effect grows over multi-year horizons.

Third, human-capital accumulation. Grants, labs, and field operations train people who carry skills into firms and institutions that never received the original dollar. That diffusion raises long-run productivity and shows up in multipliers that are larger at five-year windows than at one-year windows.

Fourth, time-lagged compounding. Basic research typically takes about 20 years before measurable macro effects appear, with another 20 years to reach full impact. Applied research shows effects over 10 to 30 years. Those lags are not defects; they are the mechanism that turns one-year budgets into multi-decade gains.

These channels depend on credibility and continuity. If official statistics are politicized, the reuse chain breaks, private investment hesitates, and users move to inferior substitutes. Carryover effects are not automatic; they are a product of independence and professional standards that make the numbers trustworthy across administrations.

The Collision of Politics and Facts

These compounding benefits depend on the institutional independence that McEntarfer’s firing directly attacked. Her removal broke eight decades of statistical independence. No U.S. president had ever removed a statistical agency head for publishing unfavorable data.

McEntarfer spent twenty years in federal service. She worked at the Census Bureau, Treasury Department, and White House Council of Economic Advisers—the institutional expertise that makes American data globally respected [8]. Her predecessor, William Beach, whom Trump appointed in 2019, condemned the firing.

“The groundless firing of Dr. McEntarfer sets a dangerous precedent and undermines the statistical mission of the Bureau,” Beach wrote, calling it an “unprecedented attack on the independence and integrity of the federal statistical system” [9].

Statistical agencies worldwide maintain professional independence to avoid credibility problems that plague authoritarian systems. The July employment report showed exactly what indicators are supposed to show: early signs of economic weakness requiring policy attention. Attacking the messenger eliminates early warning systems that prevent small problems from becoming crises.

The crisis is deepening as the federal workforce contracts at speed. Roughly 154,000 employees have already exited this year via buyouts/deferred resignations [10]. The Center on Budget and Policy Priorities documents about 130,000 positions already eliminated and plans for roughly 150,000 additional reductions [11]. The Office of Personnel Management’s director has forecast total 2025 reductions near 300,000 through all mechanisms [12]. These losses include statisticians and domain researchers essential for maintaining and interpreting federal data systems; the attrition erodes institutional memory and degrades data quality going forward [13].

Once lost, this expertise is nearly impossible to rebuild. Rebuilding decades of accumulated knowledge and methodological development requires vastly more resources than preserving existing systems. The gradual erosion of federal data infrastructure jeopardizes the very foundation of America’s economic and democratic leadership.

Credibility Standards: The Rules That Keep Numbers Neutral

The firing violated specific institutional safeguards designed to prevent exactly this type of political interference. The U.S. system runs on formal guardrails. OMB Statistical Policy Directive No. 1 sets the fundamental responsibilities of federal statistical agencies: relevance, accuracy, objectivity, and professional autonomy [14]. Directive No. 3 governs compilation and policy-neutral, pre-announced release of principal economic indicators; in 2024 OMB updated it to modernize release-comment timing while keeping neutrality provisions intact [15]. These are not optional norms; they are the operating rules that keep markets from treating releases as political statements.

Internationally, the IMF’s SDDS Plus is the highest tier of data-transparency standards. The United States adheres to SDDS Plus, and adherence is monitored on the IMF’s Dissemination Standards Bulletin Board [16][17]. The European Statistics Code of Practice codifies professional independence and is reinforced by peer reviews across the EU [18]. These frameworks communicate reliability to investors and partners in a language they already understand.

McEntarfer’s firing represents the visible symbol of a much larger information-infrastructure destruction that violates these established standards.

Credible Data Is Infrastructure

Data-infrastructure destruction is a capstone crisis because reliable information systems are prerequisites for addressing any economic or social challenge. You cannot manage what you cannot measure. You cannot solve problems you cannot diagnose.

The employment situation illustrates the problem. BLS revisions showed May and June job growth was 258,000 positions lower than initially reported—the largest two-month downward revision since April 2020 [19]. This information guides Federal Reserve interest-rate decisions, business hiring plans, and economic forecasting. Attacking the agency for accurate revisions eliminates the early warning system preventing employment problems from becoming crises.

Data that took decades to gather has been the basis of our growing economy and world leadership. Restoring even some of the lost information that we bought and paid for will require decades, and trillions of dollars. Restoration economics are brutal. Rebuilding data infrastructure costs exponentially more than preserving it. These datasets represent decades of methodological development and institutional relationships. When the Census Bureau removes 3,000 research pages, it destroys the documented knowledge base enabling accurate data collection [20].

Bad policy becomes worse without reliable information for course correction. If inflation data becomes politically manipulated, monetary policy loses empirical foundation. If employment statistics become unreliable, labor-market interventions become guesswork. If business-formation data disappears, economic development strategies operate blind.

International implications compound domestic damage. American competitive advantage came from being the most trusted source of global decision-making data. Multinational corporations turned to the U.S. Census Bureau for demographic information. Central banks relied on Federal Reserve research for policy coordination. International organizations depended on CDC surveillance for health tracking.

This trust created concrete economic advantages. The dollar’s reserve-currency status rests partly on confidence in American institutional reliability. International trade agreements work because partners trust American statistics. Foreign investment flows because investors believe U.S. market data.

American competitive advantage evaporates as data credibility collapses.

The Global Stakes When America Becomes Unreliable

The destruction of American data infrastructure creates opportunities for competitors who recognize the strategic value of reliable information systems. While American agencies face political interference and budget cuts, other nations invest in data infrastructure and position themselves as trustworthy alternatives.

The European Union expanded Eurostat’s capabilities and international partnerships, offering research services that corporations increasingly prefer over uncertain American sources [21]. China built comprehensive data partnerships with developing nations through the Belt and Road Initiative, creating alternative information networks reducing global dependence on American statistics [22].

Multinational corporations adjust research processes. When Unilever needs demographic data, Samsung requires economic indicators, or Nestlé analyzes agricultural trends—they build relationships with non-American sources to hedge against the risk that critical information might disappear from U.S. websites.

Academic research communities follow similar patterns. Universities worldwide that collaborated with American researchers through federal datasets develop alternative partnerships. When NIH databases become unreliable or access gets restricted for political reasons, international networks work around American institutions.

Financial markets reflect credibility concerns. International investors increasingly discount American statistics or seek independent verification through private sources. The premium American assets enjoyed because of trusted government information diminishes as institutional reliability declines.

Credibility Premium in Capital Markets

Transparency earns a measurable financing premium. IMF event studies find that countries joining the IMF’s data-standards regimes experience lower sovereign spreads in the year after reform—on the order of a 15% reduction—with older work estimating approximately 75 basis points on new bond issues following SDDS subscription [23][24]. Newer IMF research confirms that stronger data dissemination improves sovereign financing conditions by reducing uncertainty and risk premia [25]. These are direct market signals that statistical credibility is economic power.

The dollar’s reserve-currency status depends significantly on international confidence in American institutional stability. When the world’s largest economy cannot be trusted to report accurate employment data without political interference, fundamental questions arise about American economic commitments.

These changes create self-reinforcing dynamics. As international partners develop alternative information sources, their dependence on American data decreases. As American data becomes less central to global decision-making, incentives to maintain American data quality decrease further. The result is accelerating American isolation from global information networks enabling economic leadership.

Data Credibility Has Been Our Foundation

American global leadership since World War II rested on institutional credibility more than military force or natural resources. Other nations trusted American data, research, and analysis enough to base their policies on American information. This trust created enormous soft-power advantages and enabled international economic architecture benefiting American businesses and workers.

The Marshall Plan succeeded because European nations trusted American economic analysis of reconstruction needs. The Bretton Woods system worked because international partners believed American monetary statistics and Federal Reserve research. NATO coordination depends on shared intelligence assuming American institutional reliability.

This credibility developed through decades of consistent professional performance. American statistical agencies earned international respect by maintaining independence from political pressure, publishing unfavorable information when accuracy required it, and developing methodologies other nations adopted as global standards.

The current destruction dismantles institutional advantages that took generations to build. When other nations cannot trust American economic data, when businesses cannot rely on government information for strategic planning, when researchers flee because their work might disappear overnight—America loses the information infrastructure that enabled global leadership.

The irreversible nature of institutional trust makes this destruction particularly dangerous. Credibility requires decades of consistent performance to rebuild. International partners who develop alternative data sources and research relationships during American institutional collapse will not automatically return when American systems are eventually restored.

America faces a fundamental choice. Restore data integrity and institutional independence, or accept diminished global standing as other nations fill the credibility vacuum that American political interference has created. Without reliable information systems, recovery from mounting economic challenges becomes nearly impossible. Without institutional credibility, America’s role as a trusted global partner disappears.

Without trustworthy data, the invisible remain invisible, opportunities shrink, and prosperity slips away from the hands that built it. Safeguarding data integrity is a foundational issue—it’s the foundation of a stable, fair, and thriving America.

Note: By “data infrastructure,” this piece refers to the federal statistical system and adjacent information functions: the agencies, methods, legal safeguards, and professional independence that produce official statistics and make them publicly available [26][27].

Citations

[1] NBC News, “Trump fires labor statistics boss hours after the release of weak jobs report,” August 1, 2025

[2] CNN, “July jobs report: Just 73,000 US jobs added, with ‘stunning’ downward revisions,” August 1, 2025

[3] CNN, “How the Bureau of Labor Statistics jobs report really works and why revisions happen,” August 4, 2025

[4] BLS, “Nonfarm Payroll Employment: Revisions between over-the-month estimates, 1979-present”

[5] National Institutes of Health, “Direct Economic Contributions,” December 2024. https://www.nih.gov/about-nih/what-we-do/impact-nih-research/serving-society/direct-economic-contributions

[6] Congressional Budget Office, “Estimating the Long-Term Effects of Federal R&D Spending,” 2018

[7] U.S. Census Bureau, “Census Bureau Data Guide More Than $2.8 Trillion in Federal,” June 14, 2023

[8] AP News, “Who is Erika McEntarfer, the BLS commissioner fired by Trump?,” August 1, 2025

[9] William Beach, “Statement on Firing of Erika McEntarfer,” August 1, 2025

[10] Reuters, “About 154,000 federal workers took Trump administration’s buyout offers, source says,” July 31, 2025

[11] Center on Budget and Policy Priorities, “Trump Administration’s Mass Layoffs of Federal Workers Are Illegal,” May 2, 2025

[12] Reuters, “US government to shed 300,000 workers this year, Trump’s HR chief forecasts,” August 14–15, 2025

[13] American Statistical Association, The Nation’s Data at a Crossroads — Year Two Status Report, August 2025

[14] Office of Management and Budget, Statistical Policy Directive No. 1: Fundamental Responsibilities of Federal Statistical Agencies and Recognized Statistical Units, Federal Register, Dec. 2, 2014

[15] Office of Management and Budget, Statistical Policy Directive No. 3: Compilation, Release, and Evaluation of Principal Federal Economic Indicators — revised adoption, Feb. 15, 2024

[16] IMF Factsheet: Standards for Data Dissemination (SDDS / SDDS Plus overview), 2023

[17] IMF Press Release: The United States Adheres to SDDS Plus, Feb. 18, 2015

[18] Eurostat: European Statistics Code of Practice (professional independence; 2025 features/updates)

[19] BLS, “Employment Situation Summary — 2025 M07 Results,” August 1, 2025

[20] Wikipedia, “2025 United States government online resource removals,” accessed August 2025

[21] Eurostat, “Key figures on Europe: 2025 edition,” July 9, 2025

[22] ScienceDirect, “The Belt and Road Initiative and Partnership for Global Infrastructure,” 2025

[23] IMF Working Paper: The Effects of Data Transparency Policy Reforms on Emerging-Market Sovereign Bond Spreads, 2017

[24] IMF Working Paper: Does SDDS Subscription Reduce Borrowing Costs?, 2004

[25] IMF Working Paper: Improving Sovereign Financing Conditions Through Data Transparency, 2022

[26] National Academies of Sciences, Engineering, and Medicine, Principles and Practices for a Federal Statistical Agency (7th ed.), 2021

[27] Office of Management and Budget, Statistical Policy Directive No. 1: Fundamental Responsibilities of Federal Statistical Agencies and Recognized Statistical Units, Federal Register, Dec. 2, 2014

Eight Decades of Trust: How America Built and Lost Statistical Credibility