LAUSR

Three issues impinging on the potential use of Civil Registration and Vital Statistics (CRVS) data for the Sustainable Development Goals (SDGs) are analysed in the paper. These include CRVS data relevance, content and data production capacity of CRVS systems. The paper adopts a ‘data type’ approach to relevance and capacity and proposes two metrics based on a graded qualitative evaluation (GQE) methodology. One is a data-relevance metric for evaluating the relevance of CRVS data types to the SDGs. The second is a National Statistical Systems (NSS) data type production capacity metric used for evaluating the data production capacity of CRVS systems. CRVS data instrument analysis and the CRVS data production capacity are exemplified with the Nigerian CRVS system. Relevance assessment results suggest that CRVS systems can provide data relevant to 25% of the SDGs. However the SDG data contribution of CRVS depends on the ‘data type’ capacity of National CRVS systems. As the capacity assessment shows, the Nigerian CRVS system has ‘nominal’ capacity to produce all CRVS data types (fertility, mortality, migration, nuptiality and socio-economic) and ‘active’ and ‘latent’ capacities to provide data for some 21 SDG targets. However, it currently lacks ‘effective’ capacity to produce any of the data types for the SDGs. The paper has implications for goal setting and prioritization in evolving strategies to enhance the development of CRVS/NSS systems’ data capacities, especially in developing countries.