Using small area estimation for data disaggregation of SDG indicators Case study based on SDG Indicator 5.a.1
Offered by
Food and Agriculture Organization of the United Nations

Topics
- Sustainable Development Goals
- 2030 Agenda
- Leave no one behind
- Gender equality
- Subject
- SDG indicators
- Language
- English
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.