Many investigators have requested new methods to determine expenditures as a means for better understanding priorities, organizational investments, proposed strategies, and as a tool to quantify the deployment of resources across subunits. Completely new expenditure models have been pioneered by manufacturing theorists that include costs that are activity and program-based, and which assist in forming fiscal data to further broaden its comparability to strategic decision-making. In education, several reports have demanded new methods of expenditure recordkeeping as a means to modify district strategy; mostly toward ensuring the real expenditure involved in individual schools, programs, or services is duly identified.
Though the models demonstrate some differences regarding the terms of the categories used, all of them propose assigning a larger percentage of costs to specific types of students and schools. For those having an interest in resource data in relation to the context of educating students, it makes sense to review central and indirect costs that are associated with joint district resources, as well as resources that are typically school-based. Costs that have less relevance are associated with district leadership, other operations, and services of a non-educational category: e.g., transportation, food services, school facilities, and maintenance systems.
Reforms relating to accountability have placed a focus not only on performance inequalities between white students and students from minority group backgrounds, but also between students having differing determinable needs that result from disability, poverty, or limitation in English proficiency. Many policymakers stress that the first stage in tackling these achievement gaps is to align fiscal policy with student needs. But as policymakers refurbish their established funding formulas to fulfill the needs of different students, they do so without evidence. In the first instance, there is little explanation of the way resources are currently aligned to different subgroups.
Basically, for a state policymaker attempting to assign an allocation to particular student types, no baseline data exist on current expenditure in regard to each type of student within their own districts or other schools within other districts. School districts in most states do not fully track costs by student type or to the school level. Even where these data are tracked, they are not accessible from published works for policymakers attempting to pin answers down.
Equally challenging is the difficulty in accessing comparisons from other states regarding spending. Accurate ways of defining or reporting expenditures influenced by student needs are not available, which makes it impossible to compare data between states. Furthermore, policymakers have not yet determined how to flow funds from one level of government to the next. For example, funds may be designated by the federal government for students living in poverty, with the goal of enhancing expenditures at schools having high concentrations of poverty.
However, by the time funds are dispersed through state and local allocation streams, they may not reach their intended target. Finally, only limited documentation exists on different decisions for structuring assigned allocations and the way those decisions relate to policy aims. Put in other terms, allocations meant for students having limited English proficiency (LEP) might be realized as a fixed dollar amount per LEP student, reimbursements for the spending on bilingual education services, apportionment of staff full-time equivalents (FTEs) to high-needs schools, or as funds for other areas. Research has not yet delineated the ways these different decisions influence either what is finally spent per pupil or how efficiently that funding reaches the intended students.
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