"Aligning School Finance with Academic Standards: A Weighted-Student Formula Based on a Survey of Practitioners"

March 2007

Adequacy was defined as meeting the state goal of an API (Academic Performance Index) of 800 for all schools in California, although, in the end, the study did not hold schools to this level in calculating the total costs. See note under “Calculated Additional Costs”

Total Costs:
Average: $9,912 per pupil

The study did not provide special needs weightings. The $9,912 per pupil average is the result of statistical modeling that took into account many demographic variables.

Over $17 billion, more than a 40 percent increase

Note: As explained in the methodology section, below, this additional cost does not represent the cost of adequacy, according to the definition used. The authors found that to reach an API of 800, many schools would have to exceed the highest maximum budget allowed to participants in the study’s online model. Not wanting to extrapolate the cost-achievement relationship outside the bounds they studied, they truncated estimated costs, resulting in a maximum per pupil cost for any school of about $11,500. This truncation, the authors note, leaves schools with a median API of 797. The $17 billion increase, therefore, is not the full cost of adequacy, but only an estimate of what is needed to start California’s climb towards adequacy.

Allocate revenue based on district need, but not in a way that prompts districts to game the system, for example by changing how it identifies children as ELL or Special Education. The formula should be based on regional salaries, poverty, population density, and enrollment.

The increase in funding should be implemented gradually

The study did not recommend educatinal strategies. The study’s estimates are based on statistical analyses of the relationship between expenditures and academic performance, as determined from the collective judgment of the educators surveyed.

Professional Judgment, modified:
This study used a new “professional judgment” methodology, . Instead of using panels of educators, as traditional PJ studies do, this study solicited individual responses from educators to online hypothetical schools and budgets. Participants were asked to allocate resources to a variety of areas based on a specific maximum budget and a list of resource costs. This study includes features designed to prevent overestimation, but its methodology is unique so far and therefore somewhat unproven.

568 randomly selected teachers, principals, and school district superintendents were selected for the study. Each worked independently.
Each participant was given a hypothetical school (each school was actually each participant’s school, but that information was withheld) and a hypothetical budget, in a manner intended to promote efficiency and economy on the part of participants.
Participants were asked to allocate funds for staffing (based on provided salaries) and estimate the API of a school with that level and distribution of resources
Features:

• Pre-kindergarten was not required, but was allowed
• Lengthening of the school day or school year was not required, but was allowed
• This part of the study did NOT include special education.

Based on the set of relationships between demographics, expenditures, and estimated academic performance determined by the study, the authors statistically extrapolated the cost of reaching an API of 800 for each school in the state.
School-level per pupil expenditures as determined by this statistical analysis were truncated at $3,000 to $7600 per pupil, the lower and upper limits of the budgets provided to educators. This was done because the authors did not want to extrapolate the cost-achievement relationship outside the bounds they studied. This significantly reduced the estimated funding of many schools.

Special education costs were added in later as a statistical adjustment that raised cost and lowered API based on special education enrollment
District-level costs were added in based on actual costs.
Three other statistical adjustments were made to total school costs:

• A population density adjustment
• A regional salary adjustment
• An adjustment for special education expenses incurred at the district level
  

No “public” input. However, the methodology involved input from 568 educators.

This study did not necessarily include the cost of preschool. Educators were free to allocate funds for preschool in their models, but this was not required. This study excluded capital costs for school facilities or costs for transportation and food service, which most cost studies exclude.

After the input was received from educators, the study team developed equations that best fit the trends found in the study. The following equations are not recommendations, but retrospective models of the data gathered.

• PPE (Per Pupil Expenditure) = $9533 + (58.6 x S) + (12.0 x P), where S is the “Regional Salary Index” and P is the “Poverty Index,” both expressed in terms of percent deviation from the state average



• Another close approximation was expressed as:
  PPE = $9608 + (51.4 x S) + (11.9 x P) + (0.87 x D) – (0.09 x E), where D is population density in people per square kilometer, and E is school enrollment

School-Level Costs:
School level costs were best modeled as follows. FRL = number of students eligible for free/reduced-price lunches. ELL = number of students receiving English language learner services

• - Elementary PPE = $2103 – (0.75 x E) + (111 x FRL) – (0.76 x ELL)
• Middle PPE = $1936 + (0.83 x E) + (91 x FRL) – (15 x ELL)
• High PPE = $6080 – (0.89 x E) + (49 x FRL) + (43 x ELL)
  

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Institute for Research on Education Policy & Practice, Stanford University, “Getting Down to Facts” Project, which was undertaken at the request of the Governor’s Committee on Education Excellence