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The 50x2030 Initiative was conceived to fill critical gaps in the availability and use of agricultural data in 50 low- and lower middle-income countries by 2030. Every year, governments in these countries invest US$957 billion in agriculture, often without good evidence to inform those investments. This leads to suboptimal outcomes, losses in productivity, shortfalls in agricultural income and, ultimately, more hunger and poverty. It also makes it extremely difficult for policymakers to make sound decisions that drive economic growth and reduce poverty. Implemented through a partnership...

50x2030 occupies a very distinct place in the data for development landscape. The Initiative involves an inter-agency collaboration at both the global and country levels, employs a distinct methodology (i.e. a new set of questionnaires that yield comprehensive, quality, timely data, and cover important dimensions like productivity, gender, etc.), and it intervenes at every stage of the data cycle: from identification of priority data needs and data production to ensuring data use for policymaking. Sustainability – both financial and technical -- is embedded in the program model. Partner...

There are three ways. 1. It builds on existing agricultural and/or socioeconomic surveys The Initiative’s integrated survey program builds on existing agricultural and/or socioeconomic surveys in a country. The Initiative offers two survey models – the Agricultural Survey Program (Agricultural Model) and the Integrated Agricultural and Rural Survey Program (Integrated Model). A country may choose to implement the model that aligns with their needs and requirements. Figure 1 below provides an overview of the Initiative's two survey models. In the Agricultural Model, the survey will cover both...

The Initiative’s implementation is divided into three interdependent components – data production, methods and tools development and data use. Each participating agency has deep experience and thus a comparative advantage in each area of work. FAO will lead the data production component through technical assistance and capacity building activities. The World Bank’s Center for Development Data (C4D2) will develop critical methodological research for agricultural (including fisheries, forestry and livestock) and rural surveys to produce more efficient and cost-effective measurement tools. To...