El presidente Donald Trump despidió a Erika McEntarfer, jefa del Bureau of Labor Statistics (BLS), el viernes 1 de agosto, después de la publicación del informe de empleos de agosto y la revisión de los números de los lanzamientos anteriores. Este despido es parte de una serie de movimientos de la administración que afectarán la recopilación y distribución de datos federales. Estas acciones han generado preocupaciones significativas sobre la integridad de los datos utilizados por investigadores y formuladores de políticas para informar decisiones de política críticas.
Los datos de inflación precisos son esenciales para garantizar que los beneficios del Programa de Asistencia Nutricional Suplementaria (SNAP) reflejen el costo real de la comida. Los beneficios del SNAP se calculan utilizando datos recopilados por el gobierno, específicamente el Plan de Alimentos Generosos (el Thrifty), que establece el costo de adquirir una dieta modesta y nutritiva en los Estados Unidos. El Thrifty se ajusta anualmente en función del Índice de Precios al Consumidor (CPI) para monitorear cómo los cambios en los costos de la compra afectan la adecuación de los beneficios del SNAP. Esta ajuste depende únicamente de información de inflación precisa producida por el Bureau of Labor Statistics (BLS). Si el BLS es obligado a manipular el CPI para hacer que la inflación parezca menor de lo que es, la ajuste anual de la inflación para el SNAP y otros programas producirá beneficios insuficientes.
Consecuencias de la eliminación de datos climáticos y meteorológicos
La eliminación de datos climáticos y meteorológicos ha hecho que los estadounidenses sean menos seguros durante la temporada de huracanes y incendios forestales. Las acciones del presidente Trump para despedir al comisionado del BLS son parte de una campaña más amplia para socavar la integridad de los datos federales. Esto incluye la eliminación de datos climáticos y meteorológicos, que son cruciales para la planificación federal, estatal y local. Los datos sobre el cambio climático son esenciales para que las comunidades urbanas y rurales se adapten a nuevas amenazas como los incendios forestales, las inundaciones, el aumento del nivel del mar y la desertificación. Los agricultores, los aseguradores, los planificadores locales y los gerentes de emergencias dependen de estos datos. Sin embargo, las acciones de la administración han colocado a los estadounidenses de a pie en mayor riesgo al socavar la precisión de los pronósticos meteorológicos y desvalorizar el conocimiento de los expertos. Esto hace que sea más probable que los desastres que de otro modo podrían ser manejables causen mayores pérdidas de vida o daños a la propiedad. Durante las emergencias, los datos meteorológicos locales precisos son cruciales para pronosticar amenazas y proporcionar advertencias oportunas para que los residentes evacúen. Sin embargo, las acciones de la administración han llevado a una escasez de pronosticadores, lo que hace que sea difícil manejar estas amenazas de manera efectiva.
Consecuencias de la disminución del IRS
La disminución del IRS tendrá efectos en cascada a lo largo del gobierno. El reciente despido del comisionado del BLS ha generado preocupaciones sobre la interferencia política en los datos producidos por las agencias estadísticas de EE. UU. El IRS, a través de su programa de estadísticas de ingresos (SOI), produce datos críticos que moldean la política tributaria, la planificación presupuestaria federal y la investigación económica. Estas estadísticas forman la base analítica para las agencias y economistas de todo el país. Los datos SOI se utilizan por el Office of Tax Analysis en el Departamento del Tesoro de EE. UU., el Comité Conjunto sobre Impuestos y el Congreso de Presupuesto para evaluar los efectos de la legislación propuesta, analizar los efectos distributivos del sistema tributario, predecir las recepciones fiscales federales y modelar el comportamiento del contribuyente. Casi cada análisis de política tributaria importante comienza con los datos SOI como su base. Los datos SOI también juegan un papel crucial en una amplia gama de instituciones federales, incluido el Bureau of Economic Analysis y el Consejo Federal de Reserva. Las reducciones de personal en curso en el IRS, particularmente como prescritas por el Departamento de Eficiencia del Gobierno, junto con los presupuestos en declive, plantean una amenaza seria a la capacidad del agencia para producir datos estadísticos precisos, oportunos y de alta calidad. Esto incluye la suspensión del Programa de Investigación Estadística Conjunta, que apoya la política tributaria basada en evidencia y las funciones estadísticas básicas a lo largo del gobierno federal.
La importancia de medir lo que importa
La antigua adagio de que lo que medimos es lo que importa es cierto. El PIB, por ejemplo, tiene defectos en lo que hace y no hace. Cuenta el petróleo derramado en el océano como una entrada positiva y no coloca un valor en el trabajo realizado por cuidadores de la casa. Estos defectos resultan en la sobrevaloración de la producción de bienes materiales y la subvaloración de las actividades no materiales esenciales para invertir en o mantener la salud y el bienestar de la población. Estas valoraciones influyen en cómo se ponderan respectivamente los aspectos de nuestro bienestar en las decisiones de política y presupuestarias. Más allá del PIB, nuestro sistema estadístico nacional produce una gama de medidas económicas y otras valiosas para las decisiones de política económica y otras. Con el tiempo, nuestro sistema estadístico federal ha crecido más sofisticado y ha hecho progresos en medir lo que importa más allá de la producción de bienes materiales, como aspectos de la salud física y mental, cómo los ciudadanos asignan su tiempo entre el trabajo, el cuidado, el ocio y el aprendizaje, y nuevos tipos de datos de salud y otros esenciales para las innovaciones médicas y científicas. El clima actual, en el que la recopilación y el informe de datos nacionales están siendo politizados, amenaza nuestra reputación nacional de excelencia científica y la salud de nuestra nación de manera inmediata y peligrosa. Los conjuntos de datos clave que rastrean la salud mental, las desigualdades de salud y el bienestar de la población están siendo eliminados o manipulados por la administración actual. Estos mecanismos de seguimiento son cruciales para identificar las vulnerabilidades emergentes, como el reciente descenso de la salud mental de la juventud y la resurgencia de enfermedades mortales. Eliminar estos datos hace que los riesgos de estas tendencias sean mayores, ya que nuestra capacidad para identificar su ocurrencia de manera oportuna se está erosionando.
Politicizing the BLS undermines the integrity of labor market data and the professionals who produce it. The dismissal of the BLS commissioner raises concerns around the potential politicization of one of the country’s oldest and most important federal statistical agencies. Reliable and unbiased labor market data are essential to policymakers, businesses, and many other users. Collecting, cleaning, and releasing quality and timely data are of utmost importance to the hundreds of economists and other civil servants at BLS. The multiple rounds of fact-checking and review were a constant during the preparation of a monthly statistical release, requiring a keen eye for detail, frequent collaboration, and extreme care before every public release. The integrity of labor market data is crucial for the ongoing operation and oversight of BLS, including impacts on future data releases. The data and policy ramifications of this dismissal, alongside a wave of other federal firings and resignations, could extend for years to come.
Political interference threatens data integrity and democracy
The firing of the BLS Commissioner can be interpreted as an attempt by the Trump administration to bury transparent and accountable data and undercut independent expertise and statistical agencies. Accurate and unmanipulated data are vital in managing the U.S. economy and essential to government transparency and accountability. State and local governments across the country rely significantly on federal data for everything from budgeting to public infrastructure. U.S. businesses, civil society, and academic and research institutions also rely on U.S. government data to conduct their activities. The BLS has faced debilitating budget cuts, hiring freezes, and the disbanding of expert advisory committees. All of this raises fresh concerns that the Trump administration’s economic policies may be performing poorly and that data and information will be manipulated to downplay a potentially faltering U.S. economy. With public trust in government institutions and expertise steadily declining, doctored data and information, if widespread across the administration, could decrease this trust further and have serious ramifications for our democracy and the economic well-being and security of Americans. The economy consistently ranks as a top issue for many Americans. Without trusted and accurate data, American voters will have less access to unbiased resources to help them make informed decisions and hold officials accountable.
High-quality data about the state of the economy is essential for bank regulation
Many banks fail because regulators do not have access to the most accurate data quickly enough. Cooking the books may help a bank avoid problems in the short term, but in the long run, those problems catch up to them, becoming worse over time. America’s financial regulatory system relies on high-quality data both within banks and throughout the broader economy. A reduction in the quality or integrity of key datasets, like the jobs report and GDP, will result in regulatory problems down the road. Bank regulators are used to dealing with facts that cause problems. The solution is never to ignore the data or turn uncomfortable facts into rosier lies. If American savers and businesses lose confidence in the accuracy of data around banks and the financial system, it could result in a financial crisis. Finance, at the end of the day, is about trust. Trust involves a shared commitment to truth, however uncomfortable that truth may be. Bank regulators who reject truth and embrace lies as facts will eventually find themselves in a much worse situation and risk taking much of the American economy with them.
The integrity of federal data about our job market and population is about more than just understanding the health of the country’s economy
Trillions of dollars in federal funding are at stake. Congress and federal agencies use public data every day to manage the flow of federally directed dollars to places with specific characteristics. Undermining confidence in these numbers by politicizing their credibility is also an attack on the legitimacy and fairness of the programs that are managed using these metrics. For example, the U.S. Economic Development Administration targets potentially up to $1 billion in funding over time for the Distressed Area Recompete Pilot Program to areas where prime age employment falls below the national rate—a mapping exercise that relies in part on data from the BLS. The accuracy of federal data collection across multiple statistical agencies is a much larger and longstanding problem, related to funding, that spans administrations led by both parties. Census Bureau data products, in particular, guide trillions in federal spending across transportation, community development, health, and other sectors. Federal funding isn’t limitless. If we want to manage our resources effectively and get them where they are needed, we must invest in and protect both the human and fiscal capital that can generate a shared set of publicly accessible facts. The political debate about what criteria to use and when, and the spin about why can come after, but not during, that process.
Government data are already inadequate for Native Americans. Politicizing statistical agencies will only make it worse. President Trump‘s decision to fire the commissioner of the BLS risks exacerbating already severe labor market data issues for Native Americans. Native Americans have always been excluded from the monthly jobs report and only recently had any monthly labor market data published about them.
Politicizing government data could undermine Tribal governance and harm the wellbeing of Native American people. High-quality data matters for Tribes as governing entities. While other levels of government can rely on tax revenue to fund government operations, taxes are frequently not an option for Tribes, many of which have small populations, a significant number of low-income citizens, and are trying to maintain competitiveness with off-reservation communities.
Because of this, federal funding accounts for a significant portion of Tribal government budgets. Without accurate data, federal funding can’t meet the real needs of Native communities. However, as we write in a forthcoming report assessing data challenges for Native Americans in Southern California, Tribes must govern their citizens and territories while relying on data that would be considered inadequate for nearly any other group in the United States.
Data about Tribes and Native American people suffer from a variety of shortcomings, including insufficient sample sizes, data that lags by years, misalignment with Tribal boundaries, misclassification of Native people into other racial or ethnic groups, and data sets and statistical publications that are designed without Tribal input.
As one example, the total U.S. population varies by a range of 1% across three common federal data sets: the 2020 decennial census, the 2023 ACS one-year estimates, and the 2023 ACS five-year estimates. In comparison, the total Native American population varies by over 24% across those same three data sets, a difference of up to 2.3 million people depending on which data set is used.
Recent data challenges for Tribes extend beyond just the BLS. Since the start of 2025, the federal government has removed a growing number of federal data sets and research reports from the public domain, including those assessing demographic information on minority groups and public health statistics, in the name of eliminating “DEI” from the federal government.
Restauración y depolitización de la recopilación de datos
Moving forward, it will be essential that the federal government not only restore and depoliticize data collection but also take steps to improve the quality of data for Tribes and Native American people. In the absence of federal action, now is the moment for states, regions, and municipalities to fill the gap by improving their data relationships with Tribes and Native American communities.
This can include developing state and regional Indigenous data strategies, investing in Tribal data capacity to help Tribes scale up their own data operations, expanding Tribal access to state and regional government-held data, and making state and local data about Native Americans more accurate by increasing sample sizes and updating practices around race and ethnicity data collection to meet emerging best practices.
By taking these steps, policymakers can help build a data ecosystem that better supports not only Native Americans but Americans of all backgrounds.
Federal economic statistics are an essential part of decision-making for policymakers, businesses, and households. Economic statistics covering topics like inflation, unemployment, income growth, and household wealth dominate news cycles with every data release. There are two types of threats to economic statistics. The first is political manipulation, meaning deliberate attempts to alter or prevent the release of key economic facts that decision-makers need. The second is a deterioration in the quality of economic statistics because of a failure to make the necessary investments in data infrastructure.
Political threats to economic statistics have never really been an issue in the United States. No one seriously questions that the key statistical agencies report honestly. Statistics evolve after an initial data release because they start as estimates based on samples from currently available data. The statistics are subject to revision as more and higher-quality data become available. Statistics are locked down only when all the relevant information is in hand.
One key protection against political interference is integrity within the statistical agencies. However, there are other safeguards against political manipulation as well because of the elaborate and evolving interconnections between various headline statistics and the availability of multiple measures for the same outcomes. If someone attempted to manipulate, for example, headline employment numbers from the BLS Current Employment Statistics, that would create glaring distortions in productivity and other downstream statistics that rely on job counts.
It would also introduce inexplicable gaps between the BLS reported job counts and those from other sources, including state-level Unemployment Insurance records and private sector payroll statistics. However, the same interconnections and alternative data sources that limit the risk of political manipulation draw our attention to the second risk. The reason we have interconnected statistics and alternative data sources is because researchers at the agencies responsible for economic statistics and their academic partners have done the necessary work.
We measure economic outcomes using different data sources and methods because we want to know if the alternatives give different answers, and if so, why? We worry that one method of collecting information—knocking on doors or making phone calls—that worked in the past may not work well today. We have embraced the availability of administrative data sources, such as the Unemployment Insurance records from states and private payroll employment mentioned above, to test for better (or cheaper) answers to key questions about economic performance.
We need to think about how to measure economic success in a world where intangible capital (ideas) has come to dominate the world of machines and physical goods. If we stop investing in economic measurement, the usefulness of economic statistics becomes questionable, and decision-makers will no longer have the tools they need. The environment also becomes ripe for political manipulation. Although political manipulation is a potential threat, the second threat to economic statistics is already becoming a reality.
Budgetary pressures and antagonism towards federal employees are weighing heavily on statistical agencies, who were already struggling with the challenges of measuring outcomes in a rapidly evolving economy. There are no simple answers to producing high-quality economic statistics. There are, thankfully, many government researchers and their academic partners who want to keep doing the work that needs to be done. If we are worried about political manipulation of economic statistics, we need to make sure we will know it when we see it.
La importancia de los datos federales
Federal data matter for a myriad of government activities. Many people don’t realize the essential role this agency information plays in grant distributions, school aid, and poverty alleviation, among other things. Without accurate information and public trust in public sector data, it will be impossible to have fair and unbiased distributions of federal money to state and local areas. Some places will get more than they deserve while others would receive less, and that would compromise public sector performance.
One of the reasons we need trustworthy government data is that grant distributions are based, in part, on demographic and other kinds of data at the state and local levels. Around $2.8 trillion in federal money is provided using U.S. Census Bureau numbers. This material enables hundreds of agencies to determine need through established aid formulas and allocate government grants based on population, income levels, and the like.
Census “undercounts” may deprive cities of millions of dollars and even lead to the loss of a congressional seat. School aid also is dependent on accurate, trustworthy numbers. Many states have grant formulas for school assistance that depend on factors such as community need, property valuations, and local tax levels. If the underlying numbers are not accurate or people do not have confidence in the integrity of the information, then this lack of confidence compromises the distribution of school funding and imperils education-related opportunities across the country.
Finally, having high-quality data is important for poverty alleviation. Programs such as food stamps, public aid, and housing assistance are partially based on income levels, nutrition needs, and community costs. These programs require reliable data sets to ensure fairness in the money distributions. Small differences in the quality of this underlying information could have a substantial impact on how much support people and communities receive.
La administración de Trump despidió al comisionado del BLS, lo que no solo perjudica a la economía estadounidense, sino que erosiona aún más la democracia estadounidense. Sin datos confiables, los formuladores de políticas, los periodistas y los ciudadanos no pueden evaluar las consecuencias de la política pública. Por extensión, los estadounidenses encontrarán más difícil atribuir crédito y culpa el día de las elecciones. El despido es la última en una larga línea de ataques contra el servicio civil independiente y no partidista del país, otro señal de que la seguridad de su trabajo depende no de la calidad de su trabajo, sino de que se ajusten a las vagas de los políticos. La administración ha socavado repetidamente la recopilación de datos del gobierno en una amplia gama de temas, desde el cambio climático hasta el rendimiento de los estudiantes. El despido del comisionado del BLS es parte de esta desmantelamiento sistemático de las instituciones que promueven la rendición de cuentas en nuestra democracia.
Un patrón global de ataques a la democracia
En todo el mundo, los líderes antidemocráticos intentan consolidar su poder controlando la información sobre el rendimiento de sus gobiernos. El gobierno chino respondió a niveles desfavorables de desempleo juvenil suspendiendo la publicación de datos sobre desempleo juvenil. En Turquía, el presidente Recep Tayyip Erdogan despidió al jefe de la agencia de estadísticas del gobierno después de que la agencia publicara datos de inflación poco halagadores. La India ha visto una serie de controversias, incluidas instituciones estatales presionando a los productores de datos para que cambien o intentando retrasar la publicación de datos que reflejan mal al partido gobernante. Estos no son ejemplos aislados; los datos muestran que los autócratas exageran sistemáticamente su crecimiento del PIB. Cuando no están encumbrados por un servicio civil independiente, los líderes autoritarios tienen los medios, la motivación y la oportunidad para socavar la publicación de datos precisos.
Un patrón peligroso
Despedir a funcionarios por informar datos precisos que resultan poco halagadores para la administración actual es una táctica directa de los libros de los autoritarios. Es un intento de engañar a la gente, evitar ser responsabilizado por fracasos de política y reescribir la historia. Desafortunadamente, podemos esperar mucho más de esto en los meses y años venideros.
