California Costing-Out 2007, PPIC
State Funding Context
California education is critical to the entire nation’s future because more than one in eight public school students in the U.S. attends school in California. According to the latest data available from NCES:
- California had 6.4 million preK-12 students in 2004-05, of whom:
- 49.1 percent were eligible for free/reduced lunch and
- 25.1 percent were in ELL programs.
Also per NCES, the state spent $49.2 billion on preK-12 public education in 2003-04. However, this study based its findings on the figure $43 billion, which was the 2003-04 expenditures for the 950 districts they studied that had complete data.
|Study Title:||“Aligning School Finance with Academic Standards: A Weighted-Student Formula Based on a Survey of Practitioners”|
|Date Completed:||March 2007|
|Definition of Adequacy:||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”|
|Calculated Per Pupil Costs, Including Base Costs and Special-Needs Weightings:||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.
|Calculated Additional Costs:||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.
|Major Recommendations:|| 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.
|Methodology:||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.
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.
Special education costs were added in later as a statistical adjustment that raised cost and lowered API based on special education enrollment
|Public Input:||No “public” input. However, the methodology involved input from 568 educators.|
|Special Features:|| 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.
|Prepared for:||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|
|Prepared by:||Jon Stonstelie et al., of the Public Policy Institute of California|
Fact Sheet prepared July 2007