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The biggest question in school funding today is: Are American schools meeting the oft-stated goal of pumping extra dollars to support students in low-income areas? In other words, are schools funded progressively, to boost disadvantaged students, or regressively, to spend money on schools where children have the advantages of wealth?
Using a new, more accurate dataset, I analyzed the Washington, D.C. metro area (locally known as DMV) and found that the area’s K-12 funding is regressive – but individual districts progressively provide more per student as the income bracket narrows. This is called Simpson’s paradox, a statistical phenomenon in which the combined numbers do not reflect the patterns of smaller groups.
The dataset was made possible by the Every Student Succeeds Act, which requires states to report actual funding per student in every public school in America. Previously, officials reported budgets for individual schools based on average teacher salaries for the entire district, not actual teacher salaries at those schools.
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This almost always underestimates expenses for high-income neighborhoods in a district, where teachers tend to be experienced and earn more on the standardized salary scale. And the reverse is true for schools in low-income areas that employ younger, lower-paid teachers.
The new data, first reported for the 2018-19 school year, accurately measures a school’s per-student allocation from federal and state/local sources. This allows comparisons between status lines.
In my analysis, I combined funding numbers with census data on per capita income for nearly 1,000 schools in DC, Maryland, and Virginia based on their ZIP codes and ranked those ZIP codes as ultra-rich, rich, middle and low-income.
When school expenditure is totaled by income group, the picture appears regressive. Rich and middle-income areas receive more than low-income and ultra-rich areas. Low-income schools receive about 6% less than wealthy schools. While the difference isn’t significant, it falls far short of the progressive ideal of low-income schools getting extra money for their students.
However, when broken down by jurisdiction, the picture is different. DC public schools spend 22% more in low-income areas than the ultra-rich, a classic progressive model.
Maryland is somewhat progressive. It allocates less to ultra-rich and affluent areas than to middle- or low-income areas. But low-income schools receive $270 less than middle-income schools, based on the Maryland ZIP codes in the sample.
In Virginia, spending is regressive. Rich and ultra-rich schools receive $2,400 more funding per student than those in low-income areas, a difference of 17%. Virginia’s low-income middle school gets less money per student than schools in wealthier ZIP codes in Maryland and DC
But that’s not the end of the story. Looking at the districts of Virginia, all seem progressive. In other words, the lowest income category in each section spends more than the groups above it.
So how come Virginia’s total spending is so regressive when all of its sample districts appear progressive?
The answer is at the bottom of the table. Prince William County and two small towns within its borders spend significantly less per student than other northern Virginia districts. In Prince William, schools in low-income postcodes spend 8% more per student than those in middle-income postcodes.
Yet Prince William’s spending per student in low-income schools is almost 50% lower than in low-income schools in neighboring Fairfax and Loudoun districts. They also have less per student than middle and wealthier schools in other districts.
These graphs show the paradox. Overall, funding appears regressive. For the States and DC, it’s a mixed bag. But even in the most regressive state, individual school districts seem progressive.
Two factors combine to create the regressive financing of the region, and both relate to the distribution of wealth within each jurisdiction.
As part of the analysis, I ranked the schools and their incomes relative to each state’s averages as progressive, progressive-leaning, status quo, regressive-leaning, and regressive. For example, progressive schools included ultra-rich and affluent schools with low spending and low-income schools with high spending levels. The regressive schools were the reverse.
Schools that were nearly progressive or regressive were about to spend the correct amount to be considered fully progressive or regressive. Because a graduated funding model provides all schools with spending levels commensurate with their income, some middle-spending schools have fallen in the wrong direction. If middle-income schools were above or below average, I classified them as regressive.
The status quo group included middle-income schools with average spending.
The charts below show that large districts in the county with affluent areas have the resources to distribute funding incrementally. In general, the higher the percentage of schools in high-income ZIP codes, the higher the rate of progressively funded schools.
In short, districts must have wealth to share wealth.
This is why 89 of the 91 Prince William County schools in the sample were regressive or leaned in that direction. Without any wealthy schools to generate revenue, the district did not have enough money to invest in its low-income areas or even provide its middle-income schools with average funding levels for northern Virginia.
By comparison, wealthier districts have generated enough revenue to gradually spend in some schools and ensure that most of their middle-income areas meet the average spending amount.
The unequal distribution of wealth is not the only factor contributing to the degree of progressiveness of neighborhoods. State financing formulas can play an even more important role.
Virginia”places a relatively high burden of all states on localities to pay the majority of K-12 costsaccording to the Commonwealth Institute for Fiscal Analysis. As in most other states, local property tax revenues provide the bulk of school funding. The formula aims for overall K-12 spending to come 45% from local sources and 55% from the state. Federal funding for Title I, special education, and other grant programs is allocated according to their formulas.
Although Virginia creates an index to determine the “ability to pay” of each school district, it does not correct for the imbalances in property tax revenue between wealthy inner suburban areas (Arlington, Alexandria, and Fairfax) and relatively higher income areas. weak. codes in Prince William County.
Without local funds to invest, Prince William County will not be able to increase spending in its low-income areas to create a progressive image for Northern Virginia.
By contrast, Maryland sets a minimum per-student funding amount for each district, distributing a greater share of state resources to lower-income communities. In addition, there are programs to meet the needs of children at risk, with limited English proficiency or with disabilities. As with the base grant, low-income districts receive a larger share of this funding per student.
In 2021, the Maryland Legislature passed a new approach to funding schools improve the one in place at the start of the 2018-2019 school year. The changes could tip the state towards a gradual distribution of school money.
Finally, Washington, D.C. school financial approach sets a per-student amount that forms the basis for each school, then adds money for each at-risk student, English learner, and child in multiple special education categories. Schools receive an additional 22% per pupil at risk and up to three times per pupil for the most severely disabled pupils.
The result is the most progressive school funding in the region.
When it comes to measuring school funding, there’s more to it than meets the eye. Digging deeper into the data helps understand the nuanced history and detailed policies that result in progressively or progressively funded schools.
The situation is better in some places than others, but it is clear: in the DMV, states and districts can do better and should strive to do so.
David J. Hoff is a writer and data analyst based in Arlington, Virginia.
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