Dollars for Disabilities? What do we know?

In this article, Jay Greene and Marcus Winters present a grossly oversimplified perspective of what we really know about the relationship between state school finance systems – special education aid formulas – and state special education classification rates.

This supposed problem plays out at two levels. First, it is assumed that states which allocate funding based on local school district rates of classifying special education students will see greater overall growth in special education student populations than states that a) provide flat funding per fixed share of students in each district, b) cap the number of students classified for which funding will be provided or c) use some other better measures of local district resident rates of children with “real” disabilities – a  measure outside the influence of local district classification procedures. Second, some go so far as to assume that not only are state average disability rates different solely because of local responses to differences in state fiscal incentives, but that local rates of disability classification within states also vary largely because of differences in the extent to which local school officials play the special education fiscal incentives game. Green and Winters seem to be speaking primarily on the first point – state average differences and headcount incentives.

There is a small body of research, some of which is pretty solid, that supports the notion that there is a relationship between fiscal incentives and classification rates. That is not to say, however, that such incentives explain most or all of the differences, as implied by Greene and Winters in their absurd Maine to California anecdote. Second, studies that show that classification rates are partially responsive to fiscal incentives do not address whether the incentivised classification rate may actually be closer to the true rate of disabilities than the non-incentivised rate. Without a measure of true prevalence it is difficult to make the leap that the incentive is necessarily a bad one – one that distorts inappropriately the classification rates and services for children with disabilities.

Further, removing the fiscal incentives entirely does not necessarily bring to a grinding halt the overall statewide growth in classification rates or the variations across districts – even if capitation or flat funding does create modest statistical differences in growth rates between states. Pennsylvania has provided flat, census based funding since the early 1990s, yet classification rates grew dramatically since that time and rates continue to vary widely across Pennsylvania districts, from about 5% to over 30%.

Further, as with most demographic characteristics, families of children with mental or physical disabilities are simply not uniformly distributed across neighborhoods, cities and towns within states or across states making it very difficult to say that the typical school district or state should have only X% of such children. Complicating the issue is that the uneven distribution of families of children with disabilities is endogenous to the quality of services available across communities within states and across states. So, for example, if a state provides generous funding based on actual needs of students and that funding leads to higher quality services for students, families of children with disabilities are more likely to consider relocating to those states. The same applies to more local moves where services vary across districts. And parents of children with disabilities may make these decisions based on more than the services provided by the school district alone. Large towns and small cities in otherwise rural areas tend to have elevated disability rates in part because of greater availability of social services and health-care services less available in surrounding areas.

So perhaps a state can export its children with disabilities to a neighboring state by adopting school finance policies that ensure low quality programming and limit district incentive to pursue diagnostic testing. And perhaps some of the differences we see across states – especially between neighboring states – are a function of these programming and service quality differences. This question is yet to be thoroughly addressed in the literature.

In any case, it is a huge unwarranted stretch to argue that state limitation of funding for special education necessarily leads to a more correct identification rate of children in need while holding constant (or even improving) the quality of programs and services and while not exporting children with disabilities.

The problem for state policymakers is to find the correct balance between sensitivity to the needs of individual children as identified by those charged with providing their educational services (local school districts, etc.), and measures of population differences across cities, towns and school districts within states that can serve as a guide in the distribution of resources while avoiding the wrong incentives.

I have written about this topic in the attached research article.