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: Developed by the Global Strategy to Improve Agricultural and Rural Statistics (GSARS), These guidelines are the result of the first comprehensive effort to develop a standard methodology to assess countries’ capacity to produce agricultural statistics. The presented methodology takes into account previous similar international efforts, particularly those led by the International Monetary Fund (IMF), the World Bank (WB), Paris 21, and more recently, the United Nations Statistical Commission (UNSC), for building a standard framework to assess statistical systems’ capacity and data quality. The assessment framework covers the institutional infrastructure, human and financial resources available, statistical methods and practices, and data availability at the country level. The guidelines also present a set of operational tools and methods for carrying out assessments in conformity with the proposed framework, which has been developed through an extensive consultative process and pilot testing in all regions. In addition to a standard questionnaire and guidelines on data collection, a set of indicators on different dimensions and capacity elements are also provided. These indicators will serve as a tool for monitoring progress at country level and for providing counterfactual information necessary for measuring impact in countries. At this stage it is expected that the methodology illustrated in these guidelines will be institutionalized for periodic assessment in all countries.
Lead authoring unit/office: Statistics Division (ESS)
Abstract: The development of these guidelines falls under the framework of the Global Strategy to Improve Agricultural and Rural Statistics. These guidelines are the result of a comprehensive effort to develop a standard methodology to design strategic plans for agricultural and rural statistics in line with the NSDS methodology developed by PARIS21. The guidelines present a set of operational tools, methods and good practices that have been developed through a long process, taking advantage of country experiences and existing material on statistics strategic planning developed over the last 10 years. Countries will be expected to use the SPARS as a platform for long-term sustainable development of agricultural and rural statistics, as a coordination platform for producers and data users and as a means to address immediate needs and direct priority assistance. The guidelines will be regularly updated thanks to the feedback and experiences of the countries that are implementing the SPARS
Lead authoring unit/office: Statistics Division (ESS)
Abstract: The development of these guidelines falls under the framework of the Global Strategy to Improve Agricultural and Rural Statistics and builds on the International Household Survey Network methods and practices. This Guide presents a set of operational tools, methods and good practices that are the result of a long process, taking advantage of knowledge from country experiences and existing material developed by the World Bank and PARIS21 on household survey microdata, within the International Household Survey Network.
Lead authoring unit/office: Statistics Division (ESS)
Abstract: Prepared in the framework of the Global Strategy to improve Agricultural and Rural Statistics (GSARS), this manual presents some contributions produced as part of a research project on data integration, and a proposal for a master sample frame for agriculture, based on FAO’s experience in the linkage of population and house censuses and agricultural censuses, and on the experience gathered by countries following the guidelines of the World Programme for the Census of Agriculture (2000).
Lead authoring unit/office: Statistics Division (ESS)
Abstract: Prepared in the framework of the Global Strategy to improve Agricultural and Rural Statistics (GSARS), this technical paper on identifying the most appropriate sampling frame for specific landscape types is the result of a comprehensive literature review on the subject, followed by a gap analysis and development of innovative methodological proposals for addressing any issues that emerged.
Lead authoring unit/office: Statistics Division (ESS)
Abstract: This paper, which is part of FAO Statistics Working Paper Series, presents the methodological framework used by FAO’s Statistics Division to now-cast consumer food inflation at regional level. Hybrid ARIMA-GARCH models are estimated for each region, with additional explanatory variables constructed from a large and high-frequency dataset.
Lead authoring unit/office: Statistics Division (ESS)
Abstract: This paper, which is part of FAO Statistics Working Paper Series, reports on refinements to the methodology for estimating the prevalence of undernourishment that were adopted during the preparation of the State of Food Insecurity in the World report 2014.
Lead authoring unit/office: Statistics Division (ESS)
Abstract: This paper, which is part of FAO Statistics Working Paper Series, elaborates on some of the methodological aspects linked to assessing food insecurity, with special reference to the practice that FAO has been following in monitoring the state of food insecurity in the world.
Lead authoring unit/office: Statistics Division (ESS)
Abstract: Following a review of developments in undernourishment in a population, this paper - which is part of FAO Statistics Working Paper Series - shows that the formulation of PU within the bivariate distribution framework is inappropriate. Subsequently, the relevance of the univariate approach is clarified.
Lead authoring unit/office: Statistics Division (ESS)
Abstract: This report, which is part of FAO Statistics Working Paper Series, discusses new knowledge on anthropogenic greenhouse gas (GHG) emissions from agriculture, forestry and other land use (AFOLU) activities made available through the new FAOSTAT Emission database.
Lead authoring unit/office: Statistics Division (ESS)
