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The growing dissatisfaction with the performance of America's educational system has resulted in a reform movement that has shifted the focus of attention from the district level to the school site. Berne and Stiefel (1994) cite three reasons why the dominance of the school district as the unit in school finance analysis is being challenged. First, across school districts, states, and even countries, there is a growing belief that the most critical activities are closest to the child — at the school or program level. Second, there is increasing interest in measuring and focusing on processes, outputs, and outcomes, rather than simply financial inputs. Third, the rapid advancement of technology now makes it possible to collect and analyze information at a level of detail that more closely mirrors the education process at the school level.

The analysis of school-level finance data has enormous potential to answer important questions about the distribution of expenditures and resources in school districts and schools. More specifically, school-level expenditure data permit analysis of the following types of questions:

In addition to permitting analysis of differences in the use of school funds, school-level data can provide valuable information about the equity, or fairness, of the distribution of educational resources. Traditional equity analyses have focused on the school district as the unit of analysis, largely because school districts in most states have been empowered by state governments to raise revenues for education and provide school programs. However, these analyses assume that all students in a district receive the same level of resources. School-level finance data offer the potential to examine that assumption by conducting comparisons of schools within districts. They also offer the potential to conduct statewide analyses of expenditures and resources, using schools instead of districts as the unit of analysis. The following types of issues can be addressed using school-level finance data:

Still a third set of questions that can be addressed using school-level finance data deals with the relationship between school expenditures (and resources), on the one hand, and student outcomes, on the other. By linking school-level expenditures with school-level achievement data, the relationship between expenditures and outcomes can be explored more effectively than earlier studies that had to relate district-level expenditures to different outcome measures.

Although school-level finance data offer the potential to address a broad range of policy issues, several problems with school-level finance data must be addressed before rigorous analysis can be conducted (Berne and Stiefel 1994). One is that school-level data do not offer a complete picture of school expenditures. There are several functions or objects (e.g., transportation, utilities, supplies) that may be purchased more cost-efficiently at the district level through "bulk buying." To accurately portray school-level spending, expenditures for these services must be allocated to the school level. Second, expenditures for some personnel (e.g., music and art teachers, curriculum specialists) who provide services at more than one school may be accounted for at the district level, rather than the school site. To fully account for school spending, these expenditures must again be allocated from the district level to individual schools. Still another problem area is with fringe benefits, particularly retirement benefits, which may be administered at the state level. Again, these expenditures must be attributed to individual schools to provide a comprehensive picture of school expenditures. However, since these expenditures may not appear in school districts' financial accounts, attribution of these expenditures to districts and schools may make expenditures appear higher than in published district and state reports.

Another problem in developing analyses of school-level finance data involves accounting for non-district resources that are used at the school level. Monk and Roellke (1994) described three sources of non-district revenue that need to be incorporated into school-level analyses: (1) monies from business, foundations, and other organized groups; (2) user fees and off-budget fund raising; and (3) donated parent and community resources. Little is known about the size of these resources and how they are distributed among schools either within or across school districts.

Review of Studies Using School-Level Finance Data

Very few studies have been conducted to date using school-level finance data, since, until recently, only Florida collected and reported school-level expenditures on a statewide basis. The small number of studies have attempted to address the following types of questions:

The following discussion summarizes the methodologies used in these studies and their major findings. Although the methodological rigor of some of these studies have been debated by researchers, the discussion that follows does not include a critique of the studies, but instead highlights their major findings about the allocation of school expenditures.

Studies of the Distribution of Expenditures for Different Functions and Objects

One of the earliest studies to examine the distribution of expenditures between the central office and the schools was a study of the New York City Public Schools, conducted by Cooper and Sarrel (1991). The researchers used a "cascade" model to study expenditures for different functions in the New York City high schools. Subsequently, a revised model of school expenditures called the School Micro-Financial Allocations Study (SMAS) Model was developed under a grant from the Lilly Endowment to account for expenditures at the central office and each school site (Lilly Endowment 1993). The SMAS included five functional categories, with each function performed at both the central office and the school site level. The five functions in the model were: administration; operations and facilities; teacher support; pupil support; and instruction.

The SMAS Model was first used to examine the use of school funds for these functions at the central office and the school site in a sample of eight school districts, with enrollments ranging from just under 6,500 to around 75,000, and total expenditures ranging from about $20 million to about $340 million. The study developed several interesting findings about the use of school resources.

Contrary to popular belief that large amounts of money go into central office expenditures, the study found that central office expenditures ranged from a low of 6 percent to a high of 20 percent — or conversely that between 80 and 94 percent of total funds were distributed to the schools. The ranges in the shares of expenditures for both central administration and school administration were also lower than expected — between 2 percent and 10 percent of total spending for central administration and between 4.5 and 6 percent for school administration. On the other hand, the share of expenditures for classroom instruction at the school site averaged about 60 percent in the eight districts, with a range from about 55 percent to 63 percent across the districts.

After further refinement, the SMAS Model was used again to analyze expenditures in a sample of 38 school districts (Cooper et al 1994). An analysis of five of the 38 systems showed similar findings to the previous study: central office expenditures ranged from 7 to 16 percent, and expenditures reaching the school ranged from a low of 84 percent to a high of 93 percent. Expenditures for central administration ranged from 2.5 to 3.5 percent and the share of expenditures for school-level instruction ranged from 52 to 60 percent.

Cooper et al (1994) also developed "efficiency coefficients" to determine how much it would cost to deliver services to students. One coefficient, called the Student Instructional Ratio (SIR) divides classroom instructional expenditures per student by expenditures devoted to administration and operations at the central office and each school site. A second coefficient, the Student Services Ratio (SSR), divides expenditures for school-level instruction and support services by expenditures for central office administration, school administration, facilities, staff support and development. These coefficients were applied to schools in the five districts to determine the relative efficiency of their school operations.

An alternative model for analyzing the distribution of school expenditures between the central office and schools and across different school functions was developed by Coopers & Lybrand (1994). The School District Budget Model (SDBM) organizes expenditures into six major functions: Instruction - Schools; Instructional Support - Schools; Operations - Schools; Operations - Central & District; Pass-Throughs; and Capital Formation. Using the model for the first time to analyze expenditures in the New York City Public Schools during the 1993-94 school year, Coopers and Lybrand found that 81.4 percent of budgeted funds was delivered to the school site.

The first statewide analysis of the distribution of school-level expenditures for different functions and objects was conducted recently by Nakib (1995) under the auspices of the Center for Research in Education Finance at the University of Southern California. Nakib analyzed expenditures in Florida's 67 school districts during the 1991-92 school year, focusing first on district-level expenditures and then on expenditures at the school site. Statewide, Nakib found that about 93 percent of districts' total budgets was spent on school site operations; only 7 percent was kept at the district office level. Excluding transportation and food services, about 65 percent of districts' expenditures was used to fund direct school instruction, while administration represented about 9 percent of the total.

Nakib also examined school-level expenditures by function and object. The functions used in the analysis included: instruction, instructional support, administration, maintenance, transportation, food, and capital outlay. Objects of expenditure included: salaries, fringe benefits, services, materials and supplies, instructional capital, and other. Statewide, he found that about 58 percent of school site expenditures (excluding food and transportation) were used to fund direct school instruction and an additional 8 percent provided support services to students; administration comprised about 7 percent of the total.

Schools in Florida were stratified into five quintiles based on several criteria to determine whether the share of expenditures for different functions and objects was systematically related to different school characteristics. These criteria were: per pupil expenditures; size; property wealth per pupil of the district; percent of pupils served free/reduced price lunches; and percent of minority pupils in the school. While the share of expenditures for most functions did not differ significantly across groups of schools, the share of expenditures for instruction tended to increase as per pupil expenditures increased. The lowest quintile in per pupil expenditures spent about 57 percent of expenditures on instruction, while the highest quintile spent just over 59 percent. In addition to spending more per pupil for instruction, high-expenditure schools spent a slightly higher share of expenditures on instruction.

Studies of Horizontal and Vertical Equity

A few studies using school-level data have recently begun to focus on issues of equity in the distribution of money and resources among schools (horizontal equity) and the relationship between funds, resources and different measures of student need (vertical equity). The studies by Cooper cited above (Cooper et al 1994, Lilly Endowment 1993) not only examined the overall share of expenditures for different functions district-wide, but also examined differences in expenditures across schools within districts. Both studies found that more money was spent per pupil in high schools than in elementary schools; they also found substantial variation in expenditures per pupil in each group of schools. Several factors were offered to explain the difference between high- and low-spending schools including differences in the percentage of teachers with more education and experience, the age and condition of school buildings, and the percentage of students receiving special education services — whether in mainstream classes or in separate programs.

Berne and Stiefel (1994) used subdistrict and school-level data to examine both horizontal and vertical equity in the New York City Public Schools during the 1991-92 school year. The first level of analysis focused on the 32 community school districts that operate elementary and middle/junior high schools, the second on the 800 plus elementary and middle/junior high schools administered by the community school districts. Both involved the use of regression analysis to assess the relationship between budgets and expenditures in the general education program and reimbursable programs, and the number of budgeted positions in the general education program, on the one hand, and poverty (measured by the percent of pupils who qualified for free lunch in the subdistrict or school), on the other. The basic regression statistics were then used to estimate the differences in the resources per pupil between a high-poverty and a low-poverty subdistrict or school.

The analysis of the 32 community school districts found the following relationships between resources and subdistrict poverty. Budgets per pupil were distributed such that high-poverty subdistricts received higher per pupil amounts, while expenditures per pupil showed the opposite relationship. However, neither relationship was large nor especially strong. Teachers' salaries showed a larger and negative relationship with poverty, while pupils per position showed a moderately negative relationship to poverty. The combination of relatively more positions, but lower salaries, in poor subdistricts resulted in the weak relationship between total budgets per pupil and poverty.

Separate analyses of the relationship between resources and poverty in elementary and middle/junior high schools, on the other hand, found different relationships. At the elementary school level, all variables except positions were distributed in higher per pupil amounts to low poverty subdistricts. In contrast, at the middle school level, all variables except average teacher's salary were distributed in higher per pupil amounts to high poverty schools. Overall, middle/junior high school budgets and expenditures tended to favor high-poverty schools, whereas elementary school budgets and expenditures did not.

Replication of the analysis using the school, rather than the subdistrict, as the unit of observation found similar results: elementary school budgets and expenditures per pupil were higher in low-poverty schools, while middle/junior high school budgets and expenditures were lower in low-poverty schools. However, the size and strength of the relationships were lower in the school-level analysis than in the subdistrict analysis.

Summary and Conclusions

This chapter presented several of the major rationales that support the collection and analysis of school-level expenditures and resources. Through the use of school-level data, school and public officials, parents, and researchers can obtain a much better picture of the allocation of resources for different functions and school programs, the efficiency of school operations, and how equitably funds and resources are distributed among schools. The chapter also identified a number of methodological problems that need to be addressed in analyzing school-level expenditure data and the findings of the few studies that have been conducted to date using these data. It should be recognized that this work has been done in a context in which the school district is still the primary local entity with fiscal authority in education. However, should school-based management become a more common feature of American education, school-level fiscal analysis will take on even more importance in the future.

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