Guidelines On Data Disaggregation For Sdg Indicators Using Survey Data

As a member of the working group on data disaggregation, the Food and Agriculture Organization of the United Nations (FAO) has taken numerous steps towards supporting Member Countries in the production of disaggregated estimates. Within this framework, these Guidelines offer methodological and practical guidance for the production of direct and indirect disaggregated estimates of SDG indicators having surveys as their main or preferred data source. Furthermore, the publication provides tools to assess the accuracy of these estimates and presents strategies for the improvement of output quality, including Small Area Estimation methods.

As the custodian United Nations (UN) agency of 21 Sustainable Development Goal (SDG) indicators, and a member of the Inter-Agency and Expert Group on SDG Indicators (IAEG-SDGs) and the Working Group on data disaggregation, the Food and Agriculture Organization of the United Nations (FAO) has been working to support countries in reporting SDG indicators at the required disaggregation level. To this end, FAO Office of Chief Statistician (OCS) has developed Guidelines on data disaggregation for SDG Indicators using survey data (FAO, 2021), which offer methodological and practical guidance for the production of direct and indirect estimates of SDG indicators having surveys as their main or preferred data source. This technical report presents a case study based on the so-called “projection estimator”, allowing the integration of two independent surveys for the production of synthetic disaggregated estimates. In particular, the publication presents a practical exercise focused on the production of disaggregated estimates for SDG Indicator 2.1.2, on the Prevalence of Moderate or Severe Food Insecurity in the population based on the Food Insecurity Experience Scale (FIES). This application – based on survey microdata from Malawi – expands and enriches the brief practical exercise presented in the Guidelines.

This technical report presents a case study based on the use of a small area estimation (SAE) approach to produce disaggregated estimates of SDG Indicator 5.a.1 by sex and at granular sub-national level. In particular, after introducing the framework for using SAE techniques, the report discusses a possible model-based technique to integrate a household or agricultural survey measuring the indicator of interest with census microdata, in order to borrow strength from a more comprehensive data source and produce estimates of higher quality. The discussed estimation approach could also be extended or customized for the integration of survey data with alternative data sources, such as administrative records, and/or geospatial information, and for the disaggregation of other (SDG) indicators based on survey microdata.

The "leave no one behind" principle espoused by the 2030 Agenda for Sustainable Development requires measures of progress for different segments of the population. This entails detailed disaggregated data to identify subgroups that might be falling behind, to ensure progress toward achieving the Sustainable Development Goals (SDGs). The Asian Development Bank and the Statistics Division of the United Nations Department of Economic and Social Affairs developed this practical guidebook with tools to collect, compile, analyze, and disseminate disaggregated data. It also provides materials on issues and experiences of countries regarding data disaggregation for the SDGs. This guidebook is for statisticians and analysts from planning and sector ministries involved in the production, analysis, and communication of disaggregated data.

The present technical report illustrates a case study on the adoption of small area estimation techniques to produce granular sub-national estimates of SDG Indicators 2.3.1 and 2.3.2, by integrating survey microdata with auxiliary information retrieved from various trustworthy geospatial information systems. The technical report provides practical guidance to national statistical offices and other institutions wanting to implement small area estimation techniques on SDG Indicators 2.3.1 and 2.3.2 or similar indicators based on surveys microdata.

This catalogue aims to improve the dissemination and outreach of FAO’s knowledge products and overall publishing programme. By providing information on its key publications in every area of FAO’s work, and catering to a range of audiences, it thereby contributes to all organizational outcomes. From statistical analysis to specialized manuals to children’s books, FAO publications cater to a diverse range of audiences. This catalogue presents a selection of FAO’s main publications, produced in 2021 or earlier, ranging from its global reports and general interest publications to numerous specialized titles. In addition to the major themes of agriculture, forestry and fisheries, it also includes thematic sections on climate change, economic and social development, and food safety and nutrition.

Agrifood systems generate significant benefits to society, including the food that nourishes us and jobs and livelihoods for over a billion people. However, their negative impacts due to unsustainable business-as-usual activities and practices are contributing to climate change, natural resource degradation and the unaffordability of healthy diets. Addressing these negative impacts is challenging, because people, businesses, governments and other stakeholders lack a complete picture of how their activities affect economic, social and environmental sustainability when they make decisions on a day-to-day basis. The State of Food and Agriculture 2023 looks into the true cost of food for sustainable agrifood systems. The report introduces the concept of hidden environmental, health and social costs and benefits of agrifood systems and proposes an approach – true cost accounting (TCA) – to assess them. To operationalize the TCA approach, the report proposes a two-phase assessment process, first relying on national-level TCA assessments to raise awareness and then moving towards in-depth and targeted evaluations to prioritize solutions and guide transformative actions. It provides a first attempt at national-level assessments for 154 countries, suggesting that global hidden costs from agrifood systems amount to at least to 10 trillion 2020 PPP dollars. The estimates indicate that low-income countries bear the highest burden of the hidden costs of agrifood systems relative to national income. Despite the preliminary nature of these estimates, the analysis reveals the urgent need to factor hidden costs into decision-making for the transformation of agrifood systems. Innovations in research and data, alongside investments in data collection and capacity building, are needed to scale the application of TCA, especially in low- and middle-income countries, so that it can become a viable tool to inform decision- and policymaking in a transparent and consistent way.

The Flexible Voluntary Contribution (FVC) 2022 annual progress report captures the key achievements of the FVC, both in terms of its role as a pooled fund for non-earmarked and softly earmarked contributions from resource partners and the implementation of development initiatives through FVC subprogrammes. The report provides a comprehensive understanding of the FVC's role within the Organization, the contribution of FVC-funded work to the achievements of FAO's four betters and their respective Programme Priority Areas (PPAs), and the future direction of the FVC based on experiences in 2022. The report comprises six sections: (1) Introduction, (2) Achievements of the FVC as a fund, (3) Achievements of FVC programmes (the four betters), (4) Key FVC principles, (5) Challenges and lessons learned, and (6) Conclusions and future actions.