Editor’s Note: This blog is one of a series on early childhood development, featuring experts from Brookings and elsewhere that have been discussing the topic as part of work being conducted by the Center for Universal Education.
There is a paucity of information available on costs of early childhood development (ECD) programs, as noted in earlier blogs in this series. Recent efforts to estimate costs of ECD programs in the context of impact evaluations are encouraging, but is there something to learn from related fields where costing has been undertaken more systematically, as in health? Here are four lessons learned from health that will be relevant for ECD program costing:
- Costing serves multiple purposes, leading to great diversity in methods and approaches used. In health, costing studies have served as input into advocacy for global investment in specific disease areas; budgeting and planning; modeling impact and financial scenarios; conducting economic evaluation; assessing efficiency of providers and facilities; and designing payment mechanisms. Each purpose has its own requirements for documentation, completeness and accuracy over time. For example, a global call for greater investment in “intervention X” at one point in time requires only rough estimates of average costs. However, greater accuracy and completeness would be necessary for a government to assure that payments to public providers cover their costs for a given set of services over a fiscal year. Costing methods must fit their purpose, and will therefore be different in terms of methods and approaches used.
- Costing tools are useful to set standards, but principles may be more practical. Many costing “tools” and efforts to standardize costing methods have been developed in health: OneHealth, Community Health Services Costing Tool, ABCE, to name a few. Further, there are multiple costing tools available on specific disease interventions or technologies, for a bottom-up or top-down perspective, based on normative standards for provision or based on actually observed costs. And in spite of these efforts, a recent systematic review found that “existing tools and studies don’t provide sufficient detail on methods and techniques [used when] conducting micro-costing analyses.” Even simple but important data descriptors, such as currency conversions used, are sometimes omitted in published studies. As a practical alternative, reference cases that establish principles for the planning, conduct and reporting of costing data and related economic evaluation may be a better way forward, in lieu of standardizing spreadsheets through tools.
- Focus on cost functions, not average unit costs. Most people acknowledge that the marginal costs of providing a given health service are usually less than average costs. Yet existing spending and services are often ignored and average costs are taken and simply summed up to determine program costs. This is not the way to go; the size of facilities, service delivery modalities, volumes, prices and quality all matter for average costs and matter along the cost function, and summing up average costs will likely lead to substantial over-budgeting. Further, we have to think of the future; for example, how will volumes and prices change with new technologies?
- Analyze and interpret cost data with care. Most empirical costing studies find enormous heterogeneity in costs across geographic areas and types of providers, which makes sense given that input costs and reference populations vary tremendously. Analysis needs to control for these variations if they are to make comparisons between providers on efficiency and effectiveness. High cost providers—outliers—may or may not be inefficient, for example, depending on the quality of care provided or other factors.
Costing is a complex but necessary undertaking in any field in order to make a convincing investment case; taking on lessons learned from efforts in the health sector may save time and aggravation for ECD.