Matthew M. Chingos and Kristin Blagg May 2017 Funding elementary and secondary schools has always been a state and local affair in the United States. Local governments provided more than 80 percent of school funding in the 1920s, but they have been roughly equal partners with state governments since the 1970s. The federal government has never provided more than 13 percent of school funding, and today it is responsible for less than 10 percent (figure 1). School districts vary widely in their funding levels and sources. Essentially all districts receive at least some funds from local sources, usually property taxes. 1 Every state provides additional funds to school districts based on a formula, with the details varying widely across states. States have many goals when it comes to school funding, such as increasing funding statewide and providing targeted support for districts that face higher costs, such as small districts in remote areas or those that serve many students with special needs. Redistributing funding across districts is a natural role for states to play, as they have the capacity to collect taxes statewide and then apportion funding among local districts. One widely (but by no means universally) shared goal among states is to target districts that serve higher percentages of students from low-income families. By definition, these districts tend to have less wealth and thus less capacity to raise local funds. EDUCATION POLICY PROGRAM Do Poor Kids Get Their Fair Share of School Funding?
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Do Poor Kids Get Their Fair Share of School Funding?...DO POOR KIDS GET THEIR FAIR SHARE OF SCHOOL FUNDING? 3 A New Measure of Funding Progressivity We propose a new measure of school
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Matthew M. Chingos and Kristin Blagg
May 2017
Funding elementary and secondary schools has always been a state and local affair in the
United States. Local governments provided more than 80 percent of school funding in the
1920s, but they have been roughly equal partners with state governments since the 1970s.
The federal government has never provided more than 13 percent of school funding, and
today it is responsible for less than 10 percent (figure 1).
School districts vary widely in their funding levels and sources. Essentially all districts receive at least
some funds from local sources, usually property taxes.1 Every state provides additional funds to school
districts based on a formula, with the details varying widely across states. States have many goals when it
comes to school funding, such as increasing funding statewide and providing targeted support for districts
that face higher costs, such as small districts in remote areas or those that serve many students with special
needs.
Redistributing funding across districts is a natural role for states to play, as they have the capacity to
collect taxes statewide and then apportion funding among local districts. One widely (but by no means
universally) shared goal among states is to target districts that serve higher percentages of students from
low-income families. By definition, these districts tend to have less wealth and thus less capacity to raise
local funds.
E D U C A T I O N P O L I C Y P R O G R A M
Do Poor Kids Get Their Fair Share
of School Funding?
2 D O P O O R K I D S G E T T H E I R F A I R S H A R E O F S C H O O L F U N D I N G ?
FIGURE 1
K–12 School Funding per Student
1919–2013 in 2015–16 dollars
Source: Digest of Education Statistics, 2016, table 235.10, https://nces.ed.gov/programs/digest/d16/tables/dt16_235.10.asp.
Most states have enacted policies aimed at narrowing differences in spending across districts,
increasing the resources available to districts that serve disadvantaged students, or both. Such school
finance reforms have been promulgated by courts and legislatures in at least 27 states since the early 1990s
(Lafortune, Rothstein, and Schanzenbach 2016).2 Recent research indicates that these efforts led to
increased test scores, educational attainment, and wages, especially among children from low-income
families (Jackson, Johnson, and Persico 2016; Lafortune, Rothstein, and Schanzenbach 2016).
Currently, 35 states have a provision in their formula that provides additional funding to districts
serving more low-income students.3 In theory, these provisions should make school funding more
progressive by spending more money on students from low-income families. But this depends on how
successful are states at counteracting local funding, which tends to be regressive.
In this report, we present new data on the progressivity of school district funding, focusing on the
degree to which the average low-income student attends districts that are better funded than districts the
average nonpoor student attends. We find that many states that have progressive funding formulas on
paper do not achieve this goal in practice, and that, in some states, the potential progressivity of school
funding is constrained by patterns of student sorting (segregation) by income.
2. State court activity on school finance dates to at least the 1971 Serrano v. Priest decision in California. See Serrano v. Priest, 5 Cal. 3d 584 (1971).
3. “Funded: State Education Funding Policies for all 50 States,” EdBuild, accessed May 19, 2017, Funded.edbuild.org; Thirty-five states provide additional funding to districts based on enrollment or concentration of low-income students (or both).
4. We exclude Hawaii because the entire state is a single district. We exclude Washington, DC, for the same reason.
5. Beginning with the 2017–18 school year, states will be required to report school-level funding data to the federal
government. This will be valuable information but will be difficult to collect in a way that is comparable across jurisdictions.
6. We use data files from the 1994–95 school year (version 1d) and the 2013–14 school year (version 1a).
7. We use Model-based Small Area Income and Poverty Estimates data from 1995 and 2014, and we calculate district-level poverty rates by dividing the number of children ages 5–17 in poverty by the total number of children
ages 5–17. An important limitation of poverty rates is that they do not adjust for regional differences in cost of
living, and thus they show rural areas to be relatively more disadvantaged than urban areas, all else equal (Baker et al. 2013).
8. We also drop from the analysis school districts with missing revenue data or no students enrolled.
D O P O O R K I D S G E T T H E I R F A I R S H A R E O F S C H O O L F U N D I N G ? 1 9
9. National Center for Education Statistics Comparable Wage Index; see also Taylor et al. 2007. Specifically, we calculate adjusted per-student funding as actual per-student funding in 2013–14 divided by the American
Community Survey–based comparable wage index for 2012–14.
10. This adjustment implicitly uses the wage index as a proxy for all costs districts face, including labor and nonlabor costs. It therefore does not consider other variation in district costs, such as those that result from differences in district size and density (e.g., we might expect a larger district to require lower per-student funding because of efficiency gains, all else equal, and a sparser district to require more funding, because of increased transportation costs). We experimented with regression-based adjustment models along the lines of those used by Baker (2016) and Baker et al. (2017), but found the resulting state-level progressivity estimates to be sensitive to the model specification. We also decided against using a regression-based model because it reflects differences in district-specific cost functions (which we want to account for) and differences in policy decisions that are correlated with cost drivers (which we do not want to account for). For example, a regression-based model that includes district size reflects both possible economies to scale that larger districts enjoy as well as the fact that larger districts (which tend to be located in cities) may spend more or less, on average, than other districts for other reasons (such as political ones).
11. The mean progressivity measure is similar and the correlation between the measures based on raw and cost-adjusted data is 0.96.
12. The most notable exception is Virginia, where the raw data indicate that funding is regressive by $330 per student and the cost-adjusted measure shows that funding is progressive by $450 per student. Unadjusted metrics for each state are reported in appendix table A.2.
13. As a robustness check, we adjust downward the funding of relatively small districts (those with fewer than 1,500 students, or about 58 percent of districts). Specifically, we apply the following adjustment to log(funding) for these districts: exp(log(adj_revpp1)−((10.553*size^−0.014)−9.526)). This adjustment is based on the observed relationship between log(funding) and district size nationwide. We find that the cost- and size-adjusted estimates are highly correlated (r=0.99) with the cost-adjusted estimates (see appendix table A.2).
14. Lafortune, Rothstein, and Schanzenbach (2016) also estimate the within-state relationship between district-level spending and average family income, controlling for enrollment.
15. Earlier research has estimated national models with state-specific poverty-funding gradients (see, for example, Baker 2016), which estimate more precise funding-covariate relationships but assume that those relationships are constant across states and are still based on a small number of observations for estimating the poverty-funding gradient in some states.
16. Baker et al. (2017) do not report a value for Alaska, so the correlation excludes this data point. Weighted by the number of districts in each state, the correlation is r = 0.92, suggesting that the two measures diverge the most among states with fewer districts.
17. We identify quintiles weighted by student enrollment. We drop the handful of districts with high poverty rates and high average incomes. Income is measured as median income of families with children younger than 18 in the 2010–14 American Community Survey (five-year estimates).
18. See appendix table A.2. The most notable difference between the two measures is New York, which is one of the least progressive states based on our preferred measure, but it is one of the most progressive states when looking at the richest versus poorest districts. However, New York again appears to be regressive if we look at raw spending instead of cost-adjusted spending (even though the raw and cost-adjusted versions of our alternative measure are correlated r = 0.88). We caution readers against reading too much into any of the results for New York given their unusually high sensitivity to methodology.
19. The corresponding revenue (from all sources) and spending progressivity measures in the “School Funding Fairness Data System” data have the same level of correlation (r = 0.76); see Bruce D. Baker, Ajay Srikanth, and Mark Weber, “Rutgers Graduate School of Education/Education Law Center: School Funding Fairness Data System,” 2016, http://www.schoolfundingfairness.org/data-download.
20. Weighting the regression by total enrollment in each district reduces the change in funding predicted ($5,234 to $2,168) by a 30 percentage point change.
21. State and local funding can interact, in that districts that receive more state funding may reduce the amount of local funding that they provide. In other words, progressive systems of state funding can (at least in theory) cause the distribution of local funding to be more regressive.
2 0 D O P O O R K I D S G E T T H E I R F A I R S H A R E O F S C H O O L F U N D I N G ?
22. Our progressivity measures are based on cost-adjusted data, but federal and state funding formulas are generally not cost adjusted. However, as noted earlier, the cost adjustment does not have a large effect on our progressivity measures. For example, our raw and cost-adjusted estimates of the progressivity of federal funding are highly correlated (r = 0.98).
23. For all combinations, see Alex Tilsley, “School Funding: Do Poor Kids Get Their Fair Share?” Urban Institute, June 2017, http://apps.urban.org/features/school-funding-do-poor-kids-get-fair-share.
24. We also calculate dissimilarity indices, which are 0.40 for Florida Census tracts, 0.46 for New York Census tracts, 0.11 for Florida school districts, and 0.30 for New York districts.
References
Baker, Bruce D. 2014. America’s Most Financially Disadvantaged School Districts and How They Got that Way: How State and Local Governance Causes School Funding Disparities. Washington, DC: Center for American Progress.
Baker, Bruce D. 2016. “School Finance and the Distribution of Equal Educational Opportunity in the Postrecession US.” Education Inequality: Opportunity and Mobility 72 (4) 629–55.
Baker, Bruce D., and Sean P. Corcoran. 2012. The Stealth of Inequities of School Funding: How State and Local School Finance Systems Perpetuate Inequitable Student Spending. Washington, DC: Center for American Progress.
Baker, Bruce D., Danielle Farrie, Monete Johnson, Theresa Luhm, and David G. Sciarra. 2017. “Is School Funding Fair? A National Report Card.” New Brunswick, New Jersey: Education Law Center, Rutgers Graduate School of Education.
Baker, Bruce D., Lori Taylor, Jesse Levin, Jay Chambers, and Charles Blankenship. 2013. “Adjusted Poverty Measures and the Distribution of Title I Aid: Does Title I Really Make the Rich States Richer?” Education Finance and Policy 8 (3): 394–417.
Chingos, Matthew M. 2013. “Class Size and Student Outcomes: Research and Policy Implications.” Journal of Policy Analysis and Management 32 (2): 411–38.
Chingos, Matthew M., and Paul E. Peterson. 2010. “It’s Easier to Pick a Good Teacher than to Train One: Familiar and New Results on the Correlates of Teacher Effectiveness.” Economics of Education Review 30 (3): 449–65.
Cook, Philip J., Kenneth Dodge, George Farkas, Roland G. Fryer Jr., Jonathan Guryan, Jens Ludwig, Susan Mayer, Harold Pollack, and Laurence Steinberg. 2015. “Not Too Late: Improving Academic Outcomes for Disadvantaged Youth.” Working Paper Series WP-15-01. Evanston, IL: Institute for Policy Research, Northwestern University.
Hyman, Joshua. Forthcoming. “Does Money Matter in the Long Run? Effects of School Spending on Educational Attainment.” American Economic Journal: Economic Policy.
Jackson, C. Kirabo, Rucker C. Johnson, and Claudia Persico. 2016. “The Effects of School Spending and Economic Outcomes: Evidence from School Finance Reforms.” Quarterly Journal of Economics 131 (1): 157–218.
Lafortune, Julien, Jesse Rothstein, and Diane Whitmore Schazenbach. 2016. “School Finance Reform and the Distribution of Student Achievement.” Working paper. University of California, Berkeley.
Taylor, Lori L., Mark C. Glander, William J. Fowler Jr., Frank Johnson. 2007. Documentation for the NCES Comparable Wage Index Data Files, 2005. Washington, DC: US Department of Education.
About the Authors
Matthew M. Chingos is director of the Urban Institute’s Education Policy Program, which
undertakes policy-relevant research on issues from prekindergarten through
postsecondary education. Current research projects examine universal prekindergarten
programs, school choice, student transportation, school funding, college affordability,
D O P O O R K I D S G E T T H E I R F A I R S H A R E O F S C H O O L F U N D I N G ? 2 1
Kristin Blagg is a research associate in the Education Policy Program at the Urban Institute.
Her research focuses on both K–12 and postsecondary education. Blagg has conducted
studies on student transportation and school choice, student loans, and the role of
information in higher education.
Acknowledgments
This brief was funded by Laura and John Arnold Foundation. We are grateful to them and to all our funders,
who make it possible for Urban to advance its mission.
The views expressed are those of the authors and should not be attributed to the Urban Institute, its
trustees, or its funders. Funders do not determine research findings or the insights and recommendations of
Urban experts. Further information on the Urban Institute’s funding principles is available at
www.urban.org/support.
We thank Bruce Baker and Nora Gordon for helpful feedback on earlier drafts of this report.
ABOUT THE URBAN INST IT UTE The nonprofit Urban Institute is dedicated to elevating the debate on social and economic policy. For nearly five decades, Urban scholars have conducted research and offered evidence-based solutions that improve lives and strengthen communities across a rapidly urbanizing world. Their objective research helps expand opportunities for all, reduce hardship among the most vulnerable, and strengthen the effectiveness of the public sector.