Getting the full picture on education finance
Despite pledges to increase funding for SDG 4, many countries still don’t know how much they are currently spending on education. They don’t have the tools or data to track expenditure by their different levels of governments and the amounts households are contributing to their children’s education.
In response, a new report shows how countries can produce the accurate data needed to gain a complete picture of their education spending. Who Pays for What in Education: The Real Costs Revealed through National Education Accounts is the result of a joint project by the UNESCO Institute for Statistics (UIS), the UNESCO International Institute for Educational Planning (IIEP), and the IIEP Pôle de Dakar, with funding from the Global Partnership for Education (GPE).
Together they have developed a new methodology, referred to as the National Education Account (NEA), which was used to help eight countries gain a complete picture of their education spending: Côte d’Ivoire, Guinea, Lao PDR, Nepal, Senegal, Uganda, Viet Nam and Zimbabwe. Experience in the pilot countries show that NEAs can be complex to implement so a set of guidelines has been produced to help others apply them on a step-by-step basis.
One solution: The National Education Account
NEAs provide a framework for comprehensive data collection, processing and analysis that cover all education levels, and all sources of funding, as well as all types of education providers.
These exercises are new to the sphere of education but have proven results in other sectors. They originate in national accounts, which measure a country’s economic activities comprehensively to calculate GDP, and in ‘satellite’ accounts that use the same broad framework to produce detailed sub-accounts for specific sectors, such as health and tourism. National Health Accounts have been around for decades and have been implemented in more than 100 countries worldwide.
Through the NEA, data collected from those funding education and those providing education services are processed using common classifications of education level, type of provider and economic transactions.
While the data are not strictly comparable from one country to another, they can be compared when integrated within international categories. They are compatible, for example, with UIS data collection on education finance.
Perhaps most importantly, an accurate perspective on education spending can reveal some surprising results, as highlighted in the report.
1. Countries spend more on education than normally assumed
Before the NEA, Uganda and Nepal seemed to be spending less on education than Côte d’Ivoire and Viet Nam (around 2% and 4%, compared to 4.4% and 6% of GDP, respectively). When the NEA identified more funding sources, Nepal jumped into the lead: spending 9.3% of GDP, compared to 7.3% in Côte d’Ivoire and 7.9% in Viet Nam.
2. Households are major funders of education
Households fund a quarter of education expenditure in Viet Nam, a third in Côte d’Ivoire, half in Nepal and more than half in Uganda. As the report highlights, if the burden on family finances is too high, problems may arise with education access and equity.
3. Ministries of Education are not always the main government funders
The government is the main funder in most pilot countries (with the exceptions of Nepal and Uganda). Government funding also doesn’t mean funding from the Ministry of Education alone. In Côte d’Ivoire, for example, government expenditure on education jumped by 9% after taking into account the contribution of the President’s Emergency Programme and 17 other ministries. In Zimbabwe, previous data collection had overlooked the fact that the civil service commission pays the pensions of teachers and other education staff, which accounts for 11% of government expenditure on education. The report also found that In Viet Nam, the Ministry of Education is only responsible for tertiary institutions, and not even all of those. Every other level is decentralized to districts and provinces.
National reports and data tables: