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Disaggregate: Income level


Whether individuals or households are considered low income, middle income, or high income

Why it matters

Disaggregating data by income level is important for identifying disparities caused by economic inequality and unequal access to certain supports. For example, in 2017, the national adjusted cohort graduation rate (ACGR) for economically disadvantaged students was 78 percent, compared to the overall ACGR of 85 percent. In addition, students who graduate from low-income high schools are more likely to leave college after the first year than those from higher income high schools. One study showed that just 14 percent of students classified as low socioeconomic status (SES) earned a bachelor’s degree or higher within eight years of high school completion, compared to 29 percent of middle-SES students and 60 percent of high-SES students. Measuring outcomes for students from low-income households is required for accountability in grades K–12 under the Every Student Succeeds Act (ESSA), and the Integrated Postsecondary Education Data System (IPEDS) collects and reports postsecondary enrollment and completion by Pell Grant status, as well as net price by income level.

What to know about measurement

E-W systems currently use various (and sometimes proxy) measures to determine income level, as the available data vary across sectors. For example, K–12 systems might measure low-income status based on whether students receive free or reduced-price lunch, whereas postsecondary systems might measure it based on Pell Grant receipt. These classifications are often imperfect proxies for income level. For example, schools eligible for the Community Eligibility Provision program do not collect individual-level data to determine eligibility for the National School Lunch Program (NSLP). Because of the limitations of data on NSLP eligibility, some districts are beginning to track alternative measures of economic disadvantage. For instance, Pittsburgh and Philadelphia schools determine whether students are directly certified for the NSLP through the Supplemental Nutrition Assistance Program (SNAP), Temporary Assistance for Needy Families (TANF), Medicaid, or other social service programs. However, not all low-income individuals may be eligible or participate, so program receipt (whether NSLP, Pell Grants, SNAP, or other programs) may undercount individuals in lower income categories.

We recommend that E-W systems collect data on household income directly and use that information to determine income groupings for disaggregation. One standard approach is to form income groupings in relation to the federal poverty level (FPL): for example, (1) up to 200 percent of FPL, (2) 200 to 399 percent of FPL, and (3) 400 percent or higher. In 2021, the 200 percent threshold for a family of a four was $53,000 and the 400 percent threshold was $106,000. (These values apply to the contiguous United States; FPL values are higher in Hawaii and Alaska.) Another approach, one the U.S. Department of Housing and Urban Development uses, is based on the area median income (AMI) rather than the FPL. Under this guidance, “low income” is defined as up to 80 percent of AMI and “moderate income” is defined as 80 to 120 percent of AMI. Because AMI definitions are based on local data, the thresholds can vary significantly across localities and better reflect differences in the cost of living. For instance, the “low-income” threshold for a family of four living in San Francisco, California in 2021 was $106,550. In Chattanooga, Tennessee, that threshold was $57,050.1250 We encourage E-W systems to converge on an approach to reporting income groups for data disaggregation.

Source frameworks

This disaggregate appeared in 20 source frameworks reviewed for this report, such as the National School Readiness Indicators Initiative, the Urban Institute Robust and Equitable Measures to Identify Quality Schools (REMIQS) framework, and the Postsecondary Value Commission Equitable Value framework.


The framework's recommendations are based on syntheses of existing research. Please see the framework report for a list of works cited.

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