Virtual Training on Data Disaggregation and Small Area Estimation for the SDGs (20-28 September 2022)

From 20 to 28 September 2022, the FAO Regional Office for Asia and the Pacific and the Office of Chief Statistician organized a virtual training on Data Disaggregation and Small Area Estimation (SAE) for the SDGs. The main objective of the training was to introduce SAE methods and techniques to statisticians and data analysts from the agriculture statistics divisions of the National Statistical Office (BPS) and the Ministry of National Development Planning (BAPPENAS) of Indonesia, and the Central Bureau of Statistics (CBS) of Nepal.

With the adoption of the Leave No One Behind (LNOB) principle as central pledge of the 2030 Agenda for Sustainable Development, the United Nations member states have committed to eradicate poverty in all its forms, eliminate hunger, end discrimination and reduce inequalities and vulnerabilities. In this framework, the production of high quality disaggregated estimates of SDG indicators - needed to monitor the Agenda’s goals and targets for all relevant groups and geographical areas - imposes significant challenges to National Statistical Offices (NSOs), both in terms of data requirements and operational complexity. In particular, when SDG indicators are produced using microdata from household and/or agricultural surveys, the limited sample size of these data collection systems usually does not allow producing reliable direct estimates for all relevant sub-populations and disaggregation domains.

Issues of this kind can be addressed at different stages of the statistical production process. They can be tackled at the design stage, by adopting sampling strategies guaranteeing an observed set of sampling units for every disaggregation domain. Although potentially optimal, this approach normally results in an exponential increase of the sampling size and survey costs and complexity. Alternatively, data disaggregation can be addressed at the data analysis stage, by adopting indirect estimation approaches – such as Small Area Estimation (SAE) - borrowing strength from related disaggregation domains and/or time periods, thus resulting in an increase of the effective sample size.

With this in mind, a Virtual Training on Data Disaggregation and Small Area Estimation (SAE) for the SDGs has been organized by the FAO Regional Office for Asia and the Pacific (FAO RAP) and the Office of the Chief Statistician (OCS), with the objective of providing an introduction to SAE techniques to statisticians and data analysts from the agriculture statistics divisions of the National Statistical Office (BPS) and the Ministry of National Development Planning (BAPPENAS) of Indonesia, and the Central Bureau of Statistics (CBS) of Nepal.

For more information, detailed agenda and key resources, read the summary report.