Related items
Showing items related by metadata.
-
Book (series)Sampling and estimation guide for SDG Indicator 2.4.1 under multiframe designs 2024
Also available in:
This guide describes the estimation process for Sustainable Development Goal (SDG) Indicator 2.4.1 on agricultural sustainability, considering its subindicators, across different levels of disaggregation within a country. It complements the 2021 Sampling guidance for SDG Indicator 2.4.1 published by FAO. While the former brings useful information concerning a general sampling and estimation perspective, this guide considers the use of dual-frame sampling designs in national agricultural surveys, which combine area frames with list frames. Although the focus is on dual-frame designs, the results described in this guide also apply to situations relevant to countries using agricultural surveys based on single area or list frames. Methodological documents and reports of practical experiences that reflect the realities of various countries, including Colombia, Costa Rica, Mexico and Peru, were used as the basis for developing the topics in this guide, as well as for providing examples of the fundamental concepts in this initial version. The paper was commissioned by FAO and prepared by FAO consultant Cristiano Ferraz under the supervision of the FAO Regional Office for Latin America and the Caribbean regional statistician. -
Book (stand-alone)An indirect estimation approach for disaggregating SDG indicators using survey data
Case study based on SDG Indicator 2.1.2
2022Also available in:
No results found.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. -
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
2023Also 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.
Users also downloaded
Showing related downloaded files
No results found.