Assembling an Open-Access School-by-School Spending Data Archive

Statistical/Methodological Product: This project built an asset for policy, practice, research, and advocacy that has the power to impact schooling and advance resource allocation for students nationwide. It has laid the groundwork for a permanent, massive all-state school-level finance data archive that can be updated year over year to enable spending and outcomes to be linked across all schools in the nation. All files are available via NERD$: National Education Resource Database on Schools website and preserved for future archive growth.

As part of building out the dataset, researchers created a rigorous, replicable norming methodology to reliably define and account for total per-pupil expenditures broken out by the unit of the school, using adjustments as warranted in the data. As part of the process, the team established common definitions of per-pupil expenditures by school, norming reported figures to standardized district expenditures and the appropriate variable inputs and included in the final dataset. The project also established an approach to apportion or impute expenditures that are insufficiently accounted for by school.

Statistical/Methodological Contribution: This robust, cross-state dataset where variables have common definitions and data are comparable within districts, across districts, and across states—fills a void in existing research data, enabling broad use to evaluate the actual costs and cost effectiveness of numerous programs, initiatives, and policies intended to boost student learning across the nation.

Development/Refinement Process: The project team convened an advisory board that represents the full life cycle of these data: from collection and publication, to use in policymaking, practice and research, and finally, continuous improvement of the data systems themselves. This diverse group of researchers, advocates, and education leaders at the federal, state, and district levels ensured that all relevant perspectives and expertise were represented to inform all phases of product development and dissemination and maximize the data’s reach and usefulness.

The team created a system where the cleaning, validation, and norming were largely automated and replicable, and a norming methodology that facilitates data mapping onto other large-scale datasets. Through multiple iterations we designed a user-friendly interface for easy data download/access.

User Testing: The team launched a mini-grant competition to produce early demonstration studies and build researcher awareness of the archive. This gave us the opportunity to test a first draft of the interactive online interface and explore options for expansion or integration with other datasets.

Use in Applied Education Research: Using this dataset, researchers can explore critical topics such as costs and benefits analyses, resource allocation, productivity and innovation, state finance formulas, and leadership training. They can begin to generate much-needed evidence about how current funding is allocated and the resulting patterns that are created, the nature of the policies that help create those allocation patterns, and the interplay between allocations and student outcomes. Toward this end, future research using the dataset can help clarify what financial policies and spending choices are most effective at increasing educational opportunity with different student populations and in different schooling contexts, and inform policy and practice around many of education’s most pressing issues.