One area of school finance about which I’ve written quite a bit is what I refer to as the “tricks of the trade” in state aid allocation formulas. Most people who study or observe state school funding policies, including popular media outlets like Education Week tend to make the automatic assumption that increased state effort toward financing local schools necessarily leads to more equitable distribution of resources. After all, the initial goals of state intervention and aid allocation were to (a) encourage towns to create public schooling systems for their children and (b) to equalize towns’ ability to pay for schools, because substantial disparities in taxable property wealth across towns made it more difficult for some than others to pay for quality schools.
However, as state aid formulas have become increasingly complex over time, so too have the various ways in which state legislatures may craft allocations of aid in ways that actually send fewer dollars to those who need them more. Here is my short list of some of the more common Tricks of the Trade that shift state aid away from poorer, higher minority concentration school districts and quite often toward neighboring affluent suburban districts. Many of these policies lead to sharp racial differences in funding across school districts. And at least some of these policies are built on historical racial disparities within public education systems and in housing and residential segregation.
1. Aid allocated based on Average Daily Attendance rather than based on enrollment or membership. This one is relatively straight forward. Higher poverty and higher minority concentration school districts tend to have lower average daily attendance rates. As such, providing per pupil financing on the basis of average daily attendance systematically reduces aid to high poverty, high minority districts. Preston Green and I show this effect in an article titled “Urban Legends, Desegregation and School Finance: Did Kansas City Really Prove that Money Doesn’t Matter.”
Missouri is among a handful of states that continues to provide aid to local public school districts on the basis of their average daily attendance (ADA) rather than by enrolled pupil count or membership. From 2000 to 2004, poverty rates and black student population share alone explain 59% of variations in attendance rates across Missouri school districts enrolling over 2,000 students. Both black population share and poverty rate are strongly associated with lower attendance rates, leading to systematically lower funding per eligible or enrolled pupil in districts with higher shares of either population. Table 9 shows that, in 1999, while districts on average (excluding KCMSD) lost 5.6% of state aid due to differences between enrollment and ADA, KCMSD lost nearly 13%. That margin has decreased after KCMSD had improved its attendance rates. Nonetheless, KCMSD continues to receive a lower share of state aid due to ADA based funding, than other districts with lower poverty rates and smaller black populations.
2. Incorrectly estimated or wrongly conceived geographic cost (wage variation) adjustments. Geographic cost adjustments seem to be the new, hip and cool way to manipulate state aid formulas in order to drive more funding to affluent suburban districts, or in the case of Wyoming, very affluent tourist locations (Jackson Hole). Because estimating a well conceived and appropriate factor to compensate for variations in employment costs can be a complicated endeavor, Legislatures in some states have latched on to “plain common sense” solutions to twist state aid in their favor. I write about the worst of these in a recent article in the journal of education finance titled Doing more harm than good. The two most offensive examples of which I am presently aware are the Wyoming legislature’s choice to retain an index that provides 40% additional resources to Jackson Wyoming simply because the average housing value in Jackson (for tourist properties of the rich) is much higher than the rest of the state. Equally offensive is the Kansas policy that allows additional revenues to be raised in the 17 districts with housing values over 25% above state average. Most problematic about this Kansas policy is that those receiving the adjustment are districts in the Kansas City metropolitan area where the majority of residential housing was developed with racial restrictions in deeds – restrictions that were introduced as late as 1962 (years after prohibited by the U.S. Supreme Court) and were only symbolically stricken from deeds in 2006 (after some Kansas legislators resisted when the issue was raised the previous year). For a fun article on this topic, see: http://www.pitch.com/2005-04-14/news/funny-math/
More on this topic at a later point.
3. Allocating or adjusting aid based on existing patterns of teacher degree levels or teacher experience. An alternative to creating a complex wage index for adjusting aid is simply to include a factor that reinforces directly the existing patterns of disparities in teacher qualifications across wealthier and poorer school districts. Preston Green and I, in an article in the American Journal of Education titled “Tricks of the Trade” explain how Alabama, which at one time funded its highly segregated public schooling system on teacher units, assigning white teacher units twice the dollar value of black teachers, managed to accomplish roughly the same pattern of disparity across black and white schools by retaining their teacher unit funding model but allocating more money to schools having teachers with advanced degrees (the whiter, less poor schools). The Arizona alternative is to provide more funding to districts where the average teacher experience level is above the state average (whiter, less poor schools) – the Teacher Experience Index.
Like funding on attendance (why should we pay for kids who aren’t there?), funding on teacher experience and degree level can be argued to pass that “plain common sense” test, at least in some states. “Let’s fund ’em for the teachers they dun-did-got… not them ones they wish they dun-did-got or for cryin’ out loud, the ones they actually need.”
4. Allocating substantially higher levels of aid per high school student than per elementary school student in a district (student grade level weighting within K-12 unified school districts).
This one is a little trickier and more subtle, and thankfully the average effect of this “trick” seems to be somewhat smaller than the others on this list. But, I have found in some recent work that when a state puts a big enough differential in place on the cost of high school students relative to elementary school students, poorer, higher minority unified K-12 school districts end up receiving systematically less funding than more affluent districts. There appears to be a relationship between the percentage of children who are in elementary versus high school grades and district poverty rates. Higher poverty districts have more children in elementary grades and fewer in upper grades, and there may be any number of logical explanations for this pattern. First, dropouts may affect the pattern. Second, as children grow up beyond elementary grades, their parents may become more professionaly stable and have the opportunity to move up and out. Also, those same parents may have had the option while the child was in the elementary grades, but when faced with the prospect of poor urban middle or secondary schools they finally exercised that option. Or, they perhaps exercised the private schooling option (urban Catholic high school).
5. Census-based financing of special education programs. I used to strongly favor the “flat” or census based special education funding approach because of the increased flexibility and reduced incentive to identify children with marginal disabilities. For those not familiar, census based funding for special education involves setting a statewide average (or some other arbitrary) rate of assumed children with disabilities that exist in all school districts and then funding on that arbitrarily set assumed rate. Okay… those of you working in the field of special education can see the problem with this already… but that hasn’t slowed the policy momentum in this direction, has it?
After evaluating a handful of state special education finance programs, I’ve changed my mind… quite strongly. Hey… we don’t provide the same amout of poverty based funding across districts – because the concentration of children in poverty varies by neighborhood and town. We don’t provide the same level of funding for bilingual education programs – because the concentrations of children with limited English speaking skills varies by neighborhood and town. And, as I’ve come to learn, the concentrations of children with various forms of disabilities vary by neighborhood and town… and in some cases in logical and explanable ways. Large town and small city hubs that are otherwise distant from major urban centers and surrounded by rural areas often have much higher rates of children with disabilities than their surrounding rural districts. These patterns show up in both school enrollment data and in U.S. Census data based on resident responses (not school identification practices). It seems logical that parents having children identified with a disability might choose to relocate to the nearest population hub where a wider array of social and medical services are available. Whatever the reasons, disability population concentrations, like poverty, vary widely from one location to the next across states. And quite often, disability concentrations vary in relation to poverty and even minority student concentrations. In two states where I have conducted recent analyses, higher poverty school districts are systematically disadvantaged by this flat approach to special education funding.
I will continue to update this list over time.