Roadmap to Better Data on Education Financing

To fill the gap, a new high-level commission will be finding ways to raise more funds and make better use of existing resources. But to do this, they need accurate data on the financing of education.

In response, the UIS is working closely with countries to strengthen their ability to produce the data while collaborating with partners to leverage wider initiatives in the field. To this end, a new UIS study compares five initiatives involving the collection and compilation of education finance data:

• National Education Accounts (NEAs)—a comprehensive framework to compile data on education expenditure from all sources;
• Public Expenditure Reviews (PERs)—a tool to assess the effectiveness of government expenditure on all sectors;
• BOOST—a more recent initiative on government expenditure data;
• Education Country Status Reports (CSRs or RESEN)—in-depth analysis of the education sector covering financing but also enrolment, teachers, outcomes, policy, etc.; and
• The UIS-UOE (UNESCO-OECD-Eurostat) annual data collection on education financing, through a survey sent to all countries.

Key findings

While each of the tools has a different scope and purpose, the study identifies several areas of similarities and overlaps. To reduce duplication, the study proposes a roadmap to leverage the different tools in order to produce the indicators needed for policymaking. This strategy will involve close coordination with all of the key partners, while the UIS retains its role as the main source of finance data at the international level.

The central aim is to improve the effectiveness with which education finance data are collected and the quality of the resulting indicators. Currently, the same data can be processed multiple times through various tools, sometimes in collaboration with the same (often overburdened) government units.

In addition, the different data processing methods can yield different results in the same country for the same year, which can potentially create confusion among data users.