In response to a growing demand for high-quality and internationally-comparable statistics, FAO develops, implements and promotes methods and standards to guide national data producers in generating and using sound statistics. In particular, the Organization is committed to provide national statistical systems with internationally recognized definitions, concepts and classifications as well as methodological guidance for the production of high quality statistics related to food and agriculture.
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You can access here all the statistical guidelines and handbooks, technical reports, working papers and methodological documents, and capacity development resources.
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Comments, suggestions and inquiries can be addressed to: [email protected].
Abstract: The global indicator on water stress tracks the level of pressure that human activities exert over natural freshwater resources, indicating the environmental sustainability of the use of water resources. A high level of water stress has negative effects on social and economic development, increasing competition and potential conflict among users. This calls for effective supply and demand management policies. Securing environmental flow requirements is essential to maintaining ecosystem health, resilient, and available for future generations. This indicator addresses the environmental component of target 6.4. In this report, you can learn more about the progress on the level of water stress globally, by country, and by major basin. More information and the methodological guidance can be found at: www.fao.org/sustainable-development-goals/ indicators/642 This report is part of a series that tracks progress towards the various targets set out in SDG 6 using the SDG global indicators. To learn more about water and sanitation in the 2030 Agenda for Sustainable Development, and the Integrated Monitoring Initiative for SDG 6, visit our website: www.sdg6monitoring.org
Lead authoring unit/office: Land and Water Division (NSL)
Abstract: The global indicator on water-use efficiency tracks to what extent a country’s economic growth is dependent on the use of water resources, and enables policy and decision-makers to target interventions at sectors with high water use and low levels of improved efficiency over time. This indicator addresses the economic component of target 6.4. In this report, you can learn more about the global and country progress on water-use efficiency. More information and methodological guidance can be found at: www.fao.org/sustainable-development-goals/ indicators/641 This report is part of a series that tracks progress towards the various targets set out in SDG 6 using the SDG global indicators. To learn more about water and sanitation in the 2030 Agenda for Sustainable Development, and the Integrated Monitoring Initiative for SDG 6, visit our website: www.sdg6monitoring.org
Lead authoring unit/office: Land and Water Division (NSL)
Abstract: Virtual Training Series conducted by the FAO Statistics Division (ESS) on SDG indicator 2.4.1, "Proportion of Agricultural Area under Productive and Sustainable Agriculture”.
Lead authoring unit/office: Statistics Division (ESS)
Abstract: This paper provides an overview of the endorsed methodology of the indicator by the Inter-Agency and Expert Group on SDG indicators (IAEG-SDG). Importantly, it provides a protocol for the collection of the required data via a dedicated survey questionnaire.
Lead authoring unit/office: Statistics Division (ESS)
Abstract: These guidelines illustrate recommendations for good practices on data collection in Eastern European inland fisheries, and in particular the Western Balkan region, based on the methodologies and approaches used in countries throughout Europe and from FAO experience of inland fisheries in other regions. They provide guidance on the options available to inland fishery managers based on particular circumstances i.e. commercial fishing or recreational use, and they are especially relevant for assisting the economies-in transition in Europe, Caucasus and Central Asia. These guidelines are not an overarching work on inland fisheries management, nor do they provide advice on the environmental aspects or competing uses of inland water bodies. They focus on issues of data collection to support fishery managers whether they be government agencies, fishers or angler associations co-responsible for the management of inland resources in European rivers and lakes.
Lead authoring unit/office: Fisheries Division (NFI)
Abstract: Since the launch of the Minimum Dietary Diversity for Women (MDD-W) indicator in 2015, new global developments and research conducted in three countries to further determine best practices in the data collection resulted in new information and guidelines. This research was supported by capacity-development activities on the assessment of individual food consumption. This publication is an update to the 2016 FAO/FHI 360 joint publication MDD-W: A Guide to Measurement. It includes guidance on the most accurate and valid methodologies on collecting, analyzing, interpreting, and presenting data on women’s dietary diversity, for use in research, impact assessment and large-scale, health and nutrition surveys such as the Demographic Health Survey (DHS), to generate nationally representative data, that are comparable over time and across countries. In addition to supporting the regular collection of high-quality dietary data following standardized methodologies, the publication also aims to promote dialogues on and appropriate application of the data towards informing policy and programming decisions and monitoring and evaluation of nutrition outcomes and progress at global, regional, and country levels.
Lead authoring unit/office: FAO
Abstract: At the end of each census round, FAO reviews and assesses national census practices, methodologies and results, and summarizes the findings in methodological publications, under the Statistical Development Series (SDS). For the WCA 2010 round (2006–2015), these assessments have been presented in two separate publications. The first one, titled “Main results and metadata by country” (SDS 17), published in 2019, presented a compendium of census metadata and main results for a record number of 127 countries and territories. The SDS 18, i.e. this publication, presents in its first part (Chapters 1 to 12) a methodological review of the national censuses. In its second part (Chapter 13), it illustrates global comparable data on key variables characterizing the structure of agriculture. The global review of census results includes key structural variables that are not available elsewhere. Some examples are number and area of holdings, land tenure and holder gender. Other variables are land size classes, average holding sizes, legal status of holders, household sizes, source of farm labour, land use and operated land.
Lead authoring unit/office: Statistics Division (ESS)
Abstract: A study was conducted in two Agriculture Development District (ADDs) of Malawi, Salima and Lilongwe, to pilot a new methodology for estimating on-farm harvest and post-harvest losses. The study was carried-out with technical support from the Global strategy to improve agricultural and rural statistics (GSARS) of the Food and Agricultural Organization of the United Nations (FAO). This pilot exercise principally aimed at strengthening the capacity of Malawi in generating reliable estimates on post-harvest losses. The data collection was carried out using a household questionnaire which was specifically developed for this exercise. The analysis of the results showed that a significant amount of farm produce is lost during harvesting, followed by threshing. The study also highlighted that on-time harvesting and use of chemicals are considered by farmers as the most effective strategies for preventing on-farm losses, even though farmers are not always in a position to implement these strategies. The authors recommend that a solid baseline on harvest and post-harvest losses be established by replicating on a larger scale this pilot survey for three consecutive years, to account for weather variation and other exogenous factors which may affect losses. The survey would benefit from the integration with existing country-wide data collection systems such as the Agricultural production estimates survey (APES) to ensure low operational costs and sustainability. It is also recommended that Computer assisted personal interviewing (CAPI) should be introduced for future exercises to improve on data quality and timeliness
Abstract: This report provides a summary and highlights from a technical meeting on “Dietary Data Collection, Analysis and Use: Taking Stock of Country Experiences and Promising Practices in Low- and Middle-Income Countries”, jointly convened by the Food and Agriculture Organization of the United Nations and the Intake Center for Dietary Assessment, on December 11–13, 2019 at FAO headquarters in Rome, Italy. The meeting, which brought together experts from 20 LMICs across different regions of the world, aimed overall to promote South–South learning, cross-regional networking, and the sharing of experiences with national (or large-scale), government-led, government-owned, quantitative 24-hour dietary recall surveys in LMICs.
Lead authoring unit/office: FAO
Abstract: This course has been developed to support countries in the analysis and reporting for Indicator 2.4.1 of the 2030 Sustainable Development Goals (Proportion of agricultural area under productive and sustainable agriculture), and to facilitate the understanding of the main concepts underpinning the methodology. Audience The course is primarily intended for those who play a role in data collection, analysis and reporting for SDG Indicator 2.4.1, including agronomists, statisticians, enumerators and data analysts, as well as policy makers and people with an interest in the process. You will learn about The concept of sustainable agriculture and the importance of SDG Indicator 2.4.1 The key features of the Indicator, with a focus on its 11 themes that span economic, social and environmental dimensions The use of the farm survey and alternative options for data collection The methodology for analyzing, computing and reporting this SDG Indicator Course structure The course consists of 4 lessons, ranging from approximately 25 to 40 minutes duration each: Lesson 1 – Introduction to SDG Indicator 2.4.1 Lesson 2 – Key features of SDG Indicator 2.4.1 Lesson 3 – Collecting the data Lesson 4 – Analysing and reporting
Lead authoring unit/office: Statistics Division (ESS)
