NSTC Subcommittee on Equitable Data
Office of Science and Technology Policy
Eisenhower Executive Office Building
1650 Pennsylvania Avenue, NW
Washington, DC 20504

Dear Subcommittee Members:

Thank you for the opportunity to share with you our input on how the Federal government can encourage equitable data collaboration across different levels of government, grassroots and community organizations, and the broader research community.

The Economic Policy Institute (EPI) is a nonprofit, nonpartisan think tank created in 1986 to include the needs of low- and middle-income workers in economic policy discussions. EPI conducts research and analysis on the economic status of working America, proposes public policies that protect and improve the economic conditions of low- and middle-income workers, and assesses policies with respect to how well they further those goals. In 2008, EPI launched the Program on Race, Ethnicity, and the Economy (PREE) to provide a more focused and integrated approach to exploring and explaining how race, ethnicity, gender and class intersect to affect economic outcomes in the United States. Over the last 14 years, PREE has become a leader among Washington, DC-based policy and research organizations providing data-driven analysis of large racial economic disparities in the United States that have persisted over generations, and at times have either been improved or exacerbated by public policy decisions.

The following comments are most relevant to the following questions posed by the White House’s Office of Science and Technology Policy:

• What resources, programs, training, or other tools can expand opportunities for historically underrepresented scholars and research institutions to access and use equitable data across levels of government (question #4)?
• What resources, programs, training, or tools can increase opportunities for community-based organizations to use equitable data to hold government accountable to the American public (question #5)?
• What resources, programs, training, or tools can make equitable data more accessible and useable for members of the public (question #6)?
• In which agencies, programs, regions, or communities are there unmet needs, broken processes, or problems related to participation and accountability that could be remedied through stronger collaborations and transparency around equitable data (question #7)?

Like many other research organizations, EPI often leverages federal data to document the economic conditions of workers and their families, assess the impact of economic policies on different demographic groups, and propose policy solutions that effectively support the needs and well-being of all communities across the country. Surveys such as the American Community Survey, Current Population Survey, and decennial census are critical to obtain an accurate and comprehensive understanding of different communities and their experiences across key areas of life, such as health, housing, employment, economic security, and public benefits use.

These surveys are the foundation of our national data infrastructure, providing critical information about individuals, families and households in the United States while also enabling researchers and policy analysts to evaluate state and federal policy impacts. However, each of these datasets has limitations with respect to coverage, response rates, timely processing and data availability. In turn, each of those data limitations affects our ability to understand the experiences of communities of color that are underrepresented in national statistics and to develop evidence-based policy solutions to improve outcomes, address disparities and effectively allocate billions of dollars in funding that can measurably improve lives with respect to health care, housing, employment, education, and government services and benefits.

Addressing the limitations of existing data sources requires a significant investment of federal resources to adequately staff the agencies responsible for developing the surveys, collecting the data, and processing the data for use by researchers, community-based organizations and the public. Through increased investment in our federal statistical infrastructure we can increase population coverage and survey sample sizes in a way that expands access to more disaggregated data on race, ethnicity, gender identity, geography and other key demographic variables1. This includes the development of new survey instruments and modes of data collection that acknowledge a more inclusive range of lived experiences, the historic systematic exclusion of different communities, and major changes in our society, economy and demography of the population over time. Investments in federal statistical infrastructure will also allow the federal government to expand its capacity to provide oversight and guidance related to consistent collection and documentation of data across federal, state and local agencies as the nation works to develop more inclusive systems of classifying the multiple and intersecting layers of identity that contribute to disparate social and economic outcomes. Uniformity in the definitions and concepts used to collect data is paramount to maximizing the efficiency of data collection efforts at all levels of government because it allows more data systems to “talk to each other” in a way that helps us to understand how different demographic groups access and utilize the expansive web of federal, state and local programs. 

In addition to building a more robust data collection infrastructure, expanding access to equitable data is critical to equal opportunity within the research community. Allowing a more diverse and representative group of researchers – including racial and ethnic identity, gender identity and research discipline – to have access to more robust data sources also helps to broaden the scope and perspective of research questions being asked to inform policy. Structural barriers faced by people of color and women within academia and other research institutions as well as inequities in institutional resources contribute to unequal access to data. While the practice of restricting access to detailed personal data is important to protecting the integrity of data collection efforts and the privacy of individuals, these practices can also be misused as a way of gatekeeping and restricting access to data in ways that favor better-resourced or more well-connected researchers. Careful consideration of practices and process that provide necessary security for survey respondents while expanding access to more robust data sources is essential to overcoming the particularly acute structural barriers faced by historically underrepresented scholars and research institutions, including historically Black Colleges and Universities (HBCUs) and other Minority Serving Institutions (MSIs). Agencies must prioritize engaging these underrepresented groups to facilitate more equal access to data networks, seminars, and tools so they may be better equipped to fully participate in the production of a knowledge base that helps to inform policy. Coupled with efforts to disaggregate data, these groups would have increased research capacity to examine intersections of race, ethnicity, gender, class and place that affect social and economic outcomes for underrepresented communities.

Finally, access to published research findings based on equitable data should be more readily available to the general public. Research and data with important implications for low- to moderate income households and marginalized or disadvantaged communities are often held behind paywalls that limit the access of those who may have an interest or personal stake in the research findings. Academic research journals should provide open access to research that uses government survey data as a way to improve accessibility and general utility. Through significant federal investments in a more robust national statistical data infrastructure and implementation of processes and practices that support expanded equitable data access, the efficacy of national, state and local data collection efforts can be improved while providing decision-makers with the information needed to develop policies that support more equitable outcomes.

Sincerely,

Adewale Maye
Policy and Research Analyst
Program on Race, Ethnicity, and the Economy
Economic Policy Institute

Valerie Wilson
Director
Program on Race, Ethnicity, and the Economy
Economic Policy Institute

1. Rhonda Vonshay Sharpe, “Disaggregating Data by Race Allows for More Accurate Research,” Nature Human Behaviour, 2019 3 (December 2019): 1240, https://doi.org/10.1038/s41562-019-0696-1