Policy & Practice | Winter 2023

research corner

By Robin Clausen

Assessing Disadvantage: Trends in Alternative Poverty Measures in Montana

E ducation research and policy have been guided by an insuf ficient framework for economic disadvantage. One component involves poverty measures as seen in the use of free and reduced-price meal data—National School Lunch Program (NSLP) eligibility. Montana Title 1 allocations are determined by eligibility data. In many more states, districts use the NSLP to allocate resources to schools. Since the incor poration of eligibility data into public policy, there have been questions as to which poverty measure to choose in what context. NSLP eligibility data have many emerging insufficien cies, including over-identification of students, inaccurate income infor mation, and inaccurate accounting of students from families with low pandemic, issues regarding eligibility data became acute as the school meals program expanded and participation became decoupled from economic dis advantage. To face these challenges, alternative poverty measures have been proposed. Our study addresses three levels: state, locale (city, town, rural), and within rural communities using 2019 data. At various levels, some alterna tive poverty measures are sensitive and consistent, meanwhile, at other levels, these measures are less so. At the state level, differences between poverty measures are mixed and it is difficult to find a single solution to supple ment NSLP. There are eight poverty measures under consideration in this research. Our analysis highlights the incomes in Community Eligible Provision districts. 1 During the

of Education are also highly corre lated. The SAIPE (Small Area Income and Poverty Estimates) and direct certification data are moderately correlated. The SAIPE is a census estimate of the count of students whose families live below the poverty line. It is commonly used in federal formulas for district allocation. Direct certification is the count of identi fied students whose families receive federal benefits (SNAP and TANF). When regressing student outcome measures (attendance, graduation, dropout, achievement measures) by

impact of NSLP, allows an analysis of the relative strength of a poverty measure, and enables comparisons between measures. Overall, the most highly correlated poverty measures are NSLP par ticipation and longevity. Eligibility is based on the number of students eligible, a policy marker, rather than the actual enrollment in NSLP. Longevity is an average of the number of years a student has participated in NSLP by grade level. The SIDE (Spatially Interpolated Demographic Estimates) from the U.S. Department

Illustration by Chris Campbell

Policy & Practice Winter 2023 32