Childhood analysis

Obtain both cost and efficiency to improve decision making in education

Despite increasing access to education, we face a global learning crisis: in 2019, it was estimated that more than half of children in low- and middle-income countries (LMICs) could not read and understand a simple text by the age of 10. The COVID-19 crisis has only exacerbated this learning poverty, as school closures have resulted in an increase of about 70 percent of children in LMICs experience learning poverty today. For donors to successfully reverse the learning crisis, they will need explicit information on the costs and effectiveness of educational interventions to make informed decisions.

While there has been recently increasing attention To measure and ensure the effectiveness of an intervention, there is a lack of high quality cost data let alone how it relates to effectiveness. In a world of limited resources, not getting the big picture means that donors, policy makers and education organizations cannot make informed investment decisions. For example, with information on cost-effectiveness, a funder might view a slightly less effective intervention as a better investment if it is much cheaper, thereby allowing many more students to benefit from it. For program implementers, understanding the cost-effectiveness of different levers in their interventions can help them double the ones that generate the most value and abandon resource-intensive activities that make little difference to student outcomes. . In addition, an understanding of what cost-effective interventions should cost provides a good target for implementers when designing programs, and for benchmark donors when setting budgets and funding expectations. their beneficiaries.

Given the double burden of the learning crisis and the limited budgets of governments and donors, spending must be directed towards smart investments in future results. Now more than ever, it is essential to have quality cost data and evidence on profitability.

At the Brookings and Dalberg Center for Universal Education (CUE), we have worked independently to improve access to resources and evidence to contribute to the global knowledge base on costs and effectiveness and the combination of the two. . CUE, as part of a larger project focused on collecting, analyzing and using data to achieve learning outcomes in early childhood education and development (ECD), has launched research on costs and cost data in 2014. Dalberg Advisors, in partnership with the British Asian Trust, UBS Optimus Foundation and the Foreign, Commonwealth and Development Office (FCDO) recently assessed the cost-effectiveness of educational interventions in public schools in India and analyzed how results-based financing mechanisms and COVID-19 can change them.


At CUE, this effort has two components: the Center co-leads with the ECD Action Network (ECDAN) a working group on costs, the Global Education and ECD Costing Consortium (GEECC), aimed at improving awareness and ” access to costing resources and cost data. In addition, the CUE is in the process of finalizing the Childhood Cost Calculator (C3), intended to facilitate cost analysis exercises, often referred to simply as “costing” of ECD and basic education interventions and programs. C3 is an online costing tool, soon to be available to the public, that allows the user to enter cost data into a guided survey form that can provide a range of calculations, estimates or simulated costs. This calculator was based on the Standardized ECD Cost Assessment Tool (SECT), which was previously developed by the CUE with the aim of providing methodological consistency for the cost of the full range of ECD interventions and to generate cost data for policy makers, donors, program implementers and researchers. to make informed and efficient investment decisions.

C3 helps answer the following questions:

The tool includes a number of different cost classifications, such as: cost categories, resource types, capital costs versus recurring costs, and imputed resource costs (data). It also includes features like currency conversions and depreciation. The data collected during the C3 costing exercises will be available in the Cost Data Explorer, an interactive database available on the website where the tool is hosted. This will allow funders, implementers and policy makers to explore the range of costs by program type and context facilitating their decision-making processes. In Q1 2022, CUE will pilot C3 across multiple countries and plans to launch in Q2, so stay tuned for more information on using this resource very soon.


the profitability study in India by Dalberg and partners is a starting point for filling important knowledge gaps about effective ways to support student learning. It provides guidance on what costs to expect per learning outcome for effective educational interventions in India and what to invest in and how much. The impetus for the study was the availability of solid data on the costs and effectiveness of the Quality Education India Development Impact Bond (QEI DIB). Because payments are tied to results, an impact bond generates some of the purest cost and efficiency data in the education sector. One of the objectives of QEI DIB was to measure this data on a range of education delivery models to inform the allocation of future funding in the Indian education sector. This study supplemented the intervention data from the QEI DIB with high-quality evidence on approximately 20 additional programs.

The study found that it costs around $ 13-40 per student (or around 5-15% of annual expenditure per student) for high-quality in-person interventions in public schools in India to deliver a year of additional learning beyond what the average student learns. Repairer and Teach at the right level Interventions (TaRL) are among the most cost-effective measures that can be easily adopted, while education technology can be powerful when combined with the right infrastructure and the right human resources. Another key finding is that QEI interventions led to a 50 percent increase in results compared to similar grant-funded programs, even though the costs were not higher. * This finding indicates vast potential for results-based financing mechanisms to improve cost-effectiveness through increased transparency and accountability.

Although a good starting point, the study was only able to evaluate six types of interventions because data on the costs and effectiveness of other interventions were limited. It also leaves several important questions unanswered, such as how the cost-effectiveness of interventions differs across key demographic and contextual differences (e.g. gender, rural versus urban schools, and high or low capacity states) . Tools such as CUE’s C3 could be extremely useful in collecting better cost data in addition to efficiency data.

A results-driven future

Given the double burden of the learning crisis and the limited budgets of governments and donors, spending must be directed towards smart investments in future results. Now more than ever, it is essential to have quality cost data and evidence on profitability. In addition, as donors increasingly link funding to results, whether through traditional results-based funding or through impact bonds and results funds, the need to ‘more accurately evaluating the results will increase. We see it, for example, with the establishment of the Education Outcomes Fund, which will launch projects in Ghana and Sierra Leone, and a soon to be launched back-to-school fund in India. If prices are set too low, these initiatives may not attract enough implementing partners to participate, while if they are set too high, they will not provide enough value to funders. Profitability criteria help set smart output prices and ultimately encourage innovation by incentivizing implementers to deliver within those set prices.

* Note: This does not mean that program budgets should be reduced in the future. There are some fixed costs per child – although more results can be expected per child, the costs may not be reducible.

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