Despite modest gains in recent years, many developing countries, especially low-income countries and fragile states, continue to lack foundational data and statistics for effective policymaking. This lack of data and statistics is evident across all statistical domains: baselines for the measurement of the size and structure of the economy are often outdated, poverty surveys are lacking or conducted infrequently, births and deaths are not registered, data on land and the environment are incomplete.
A large number of international development actors actively engage in strengthening statistical capacity and the availability and use of data and statistics in low- and middle-income countries with allocations of official development assistance (ODA) of about USD 700 million per year, equivalent to 0.3% of total ODA. Actors include most members of the OECD’s Development Assistance Committee (DAC), international financial institutions, UN agencies, private foundations and civil society organisations. They provide different types of support, from funding for statistical operations or reforms to training and technical assistance, in line with their mandate and overarching development co-operation strategies. And they target different actors within national data ecosystems, different government entities but also data users outside of government. All of these actors are also users of development data and statistics, investing in data to guide their planning and help them monitor results.
This diversity in the international co-operation landscape raises challenges around co-ordination and coherence, especially in partner countries with low capacity to absorb different types of support and in which domestic demand for data and statistics can be low. Yet coherence is critical in an area where production requires different government entities to work together and in which the same data and statistics can generate value for many different stakeholders. The risk of fragmentation and duplication of efforts is thus substantial and their costs high. In addition, the rapid pace of innovation in the way official data are sourced, shared and used in the context of digitalisation will often mean that support to data and statistical systems will have to adapt.
