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Book (series)Sampling and estimation guide for SDG Indicator 2.4.1: Version 1.0 2024
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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. -
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 (series)Multiple frame agricultural surveys. Volume 1. Current surveys based on area and list sampling methods 1996
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No results found.Much of the required information for the agricultural sector, such as crop production, livestock inventories, and basic social and economic data, is obtained through periodic national, multi-purpose agricultural data collection programmes called "Current Agricultural Surveys". This manual describes the sample design, organization and implementation procedures for these current agricultural surveys using multiple frame probability sampling methods, which is a new methodology currently being adopted by many countries around the world. Specific case studies will be presented in Volume II. This handbook introduces the subject and describes the practical aspects of list and area frame construction and sample selection methods while recognizing the resource and specialized staff constraints faced by developing countries.
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