Thumbnail Image

An indirect estimation approach for disaggregating SDG indicators using survey data

Case study based on SDG Indicator 2.1.2










FAO. 2022­. An indirect estimation approach for disaggregating SDG indicators using survey data - Case study based on SDG Indicator 2.1.2. Rome. 





Also available in:
No results found.

Related items

Showing items related by metadata.

  • Thumbnail Image
    Book (stand-alone)
    Integrating surveys with geospatial data through small area estimation to disaggregate SDG indicators at subnational level
    Case study on SDG Indicators 2.3.1 and 2.3.2
    2023
    Also available in:
    No results found.

    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.
  • Thumbnail Image
    Book (series)
    Disaggregating data for development: a cost-effective approach to SDG Indicators 2.1.2, 2.3.1 and 2.3.2 in Latin America using small area estimation 2025
    Also available in:
    No results found.

    This paper presents the experience of the Food and Agriculture Organization of the United Nations (FAO) in providing technical assistance to four countries in Latin America – Brazil, Chile, Colombia and Ecuador – to produce small area estimates for three Sustainable Development Goal (SDG) indicators: SDG Indicator 2.1.2, on the prevalence of moderate and severe food insecurity in the population based on the Food Insecurity Experience Scale (FIES); SDG Indicator 2.3.1, measuring the average value of agricultural production per labour unit; and SDG Indicator 2.3.2, on the average income of small-scale food producers.The paper describes the methodological details and results of the case studies developed, showing how small area estimation can be used to increase the precision of estimates at the subnational level and produce predictions in estimation domains excluded from the sample. It discusses the policy implications of having SDG estimates at the subnational level, and how countries can use this information to formulate programmes and allocate funds. The paper concludes with recommendations on how small area estimation can be incorporated in the processes implemented at the national level to produce agriculture and food security statistics.
  • Thumbnail Image
    Book (stand-alone)
    Using small area estimation for data disaggregation of SDG indicators
    Case study based on SDG Indicator 5.a.1
    2022
    Also available in:
    No results found.

    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.

Users also downloaded

Showing related downloaded files

No results found.