Do Districts Fund Schools Fairly? State and federal school accountability programs hold schools to specific standards of academic performance and assume each school is given a fair shake at accomplishing the task of educating its students.
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But are schools, in fact, treated fairly, at least with respect to funding? Over the past 3. 5 years, reforms adopted in most states have dramatically improved the equity of funding from one school district to another. But in recent years a new concern has surfaced: What if it’s not the district but rather the specific school a child attends within a district that matters most for accessing educational resources? Mounting evidence suggests that districts commonly distribute different amounts of funding, even when schools serve the same types of students.
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Our research and that of others indicate that schools with predominantly junior teachers receive fewer salary dollars than do schools staffed with veterans. Further, districts often compound these inequities by distributing a smaller share of unrestricted funds to the same schools that are shortchanged in salary dollars.
What we don’t yet know about school funding inequalities is whether and how these discrepancies have changed in recent years. Nor is there much information available about how spending differences within districts compare to differences between districts in the same state. In this study, we address these questions by taking an in- depth look at funding differences between and within Texas school districts over the course of a decade, from the 1. Within Texas, we focus our attention on large school districts, those with more than 2. In 1. 99. 4, the state had 2. These districts serve about half of all Texas public school students.
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Texas’s large districts are useful cases for two reasons. First, other studies of school funding equity have suggested that funding discrepancies are greatest in the largest and most urban school districts. By focusing on large districts, we are more confident that we are identifying the full extent of inequality that exists between schools. At the same time, we recognize that we may not be able to generalize our findings beyond such districts. Second, the state of Texas has in recent years aggressively addressed funding inequalities between districts.
In 1. 99. 3, following a state supreme court order to equalize public school spending, the state’s school finance system adopted a provision known as the “Robin Hood” law that requires property- rich districts to subsidize poorer districts within the state. Studying Texas districts and schools allows us to assess whether and how policies designed to reduce inequities between districts affected inequalities between schools within districts. Our findings demonstrate that, at least in Texas, funding decisions within districts currently have a greater impact on a school’s resources than inequalities in access to revenues across school districts. Although reforms have been successful in reducing inequalities between Texas districts, variation in funding within districts remains high. As a result, examining only data aggregated to the district level, still the standard practice in equity studies, misses much of the inequality in funding across schools.
Data and Methodology. We obtained financial and descriptive information about Texas districts with more than 2. Texas Education Agency.
The database reports financial allocations to schools by district. For each school, we know the nontargeted, or noncategorical, allocations made for each student who attends the school as well as how much the school received for five targeted groups of students: students eligible for free or reduced- price lunch, students eligible for bilingual education programs, students with disabilities, gifted students, and students in vocational education programs. We exclude charter schools from our analysis, as their funding levels are not determined by the same policies that affect traditional public schools. We first examine the differences between schools in noncategorical resources by comparing each school’s per- pupil funding to the average per- pupil funding in the district. We make this comparison by calculating the ratio of each school’s per- pupil noncategorical expenditure to the district’s average per- pupil noncategorical expenditure.
For example, if School A receives $4,0. School A is 0. 8 (or 8.
Since the ratio compares individual school funding to the average for the district, we know that any funding differences we see are entirely the product of intradistrict rather than interdistrict variation. Next, we compare total spending, including funds allocated specifically for students eligible for free or reduced- price lunch and bilingual, vocational, or gifted education. We exclude special education funds from this analysis because of large variations in funding depending on disability type. For each district, we compute the district’s average expenditure for each student- need group. For example, one district may allocate an average of $5. This average is effectively an implicit spending weight unique to each district, determined by dividing the sum of all allocations made on behalf of each student type by the number of students in that category.
We then calculate a ratio, called a Weighted Student Index (WSI), of the actual funding received by each school to the funding we would expect if schools received the district’s average allocation for its particular mix of students. The WSI allows us to compare per- pupil funding in schools while accounting for the types of students a school serves. A school with a WSI of 0. We follow standard practice among school finance researchers who are interested in studying potential inequality at both ends of the spectrum, and calculate for each school year in our study the coefficient of variation for the differences in funding within districts. We define the coefficient of variation as the standard deviation of the population divided by its mean. Since the mean value of our two spending indexes is 1. The value of 0 indicates perfect equity, with larger values signaling greater disparities in the allocation of funds.
Researchers studying spending differences between districts have established 0. As an additional point of comparison, we also examine spending inequalities between districts. In this analysis, we adjust spending figures to reflect differences in district size and in the costs of providing education before calculating the coefficient of variation. For both the between- schools and between- districts analyses, the dollars analyzed include total operating funds from federal, state, and local governments, and use real- dollar teacher salaries. The Funding Picture Throughout the decade we study, the 1. Texas districts was considerably less equal than between districts. The coefficient of variation calculated in the between- school analysis was consistently higher than that calculated in the between- district analysis.
We removed the state’s four largest urban districts from the sample and found between- school inequities were still much higher than inequities between districts. There has been modest progress toward equity of noncategorical funds across districts and schools in Texas over the last decade (see Figure 1a). At the district level, the coefficient of variation in 1. The coefficient of variation among schools for the 1. The good news is that in 2.
Texas’s 3. 9 largest school districts was less than 0. The average coefficient of variation across schools, however, exceeded this benchmark in each year. When we examined noncategorical per- pupil funding in the state’s four largest school districts—Austin, Dallas, Fort Worth, and Houston—the levels of inequity were even higher and each district was remarkably different from the others. In Dallas, Fort Worth, and Houston, the coefficients of variation were nearly always more than 0. In contrast, Austin had a coefficient of variation near 0. Houston ranged between 0.
Dallas had the highest levels of inequality, hovering around 0. During the decade we studied, Fort Worth made steady improvements toward equity in noncategorical funding across its schools, while Austin’s allocations became less evenly distributed over the last five years in our study. And while there appear to be some equity gains in these four districts over the last two years of this analysis, there is no clear long- term trend toward improvement. Figure 1b shows the equity picture for total funding over the period.
While inequities both between and within districts have decreased over the past 1. Taking into account resources expended for particular student types, then, does not change the patterns in noncategorical spending described above in any meaningful way. The Impact of School Characteristics. Of course, we should not assume that all inequalities in spending between schools are necessarily perverse.
District officials in Texas might point out that there are reasons aside from special student needs that could legitimately prompt uneven funding among schools. School level, school size, and academic performance are often cited as factors that shape strategic funding allocations to schools. Districts might, for example, allocate a relatively larger share of resources to high schools because they are expected to provide a diverse curriculum. Similarly, a district could be spending more on its lowest- performing schools to support improvement efforts. As discussed above, though, previous research documents spending differences resulting from less intentional factors, primarily differences in teacher salary costs due to different levels of teacher experience.
In order to investigate the role of both the intentional and unintentional factors, we explore the extent to which various school characteristics explain variation in the allocation of resources within a school district.