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.
This interface allows you to search for statistical classifications, guidelines and handbooks, technical reports, working papers and methodological documents, and capacity development resources. You can search by SUBJECT (general, agriculture, forestry, fishery and aquaculture, and natural resources) or use the ADVANCED SEARCH to search by keyword, country, language and lead authoring unit/office. Comments, suggestions and inquiries can be addressed to: [email protected].
You can access here all the statistical guidelines and handbooks, technical reports, working papers and methodological documents, and capacity development resources.
Type a keyword in the free text search box or refine your search by keyword, country, language and lead authoring unit/office.
Comments, suggestions and inquiries can be addressed to: [email protected].
Abstract: Prepared by the Global Strategy to improve Agricultural and Rural Statistics (GSARS), this technical report presents different dimensions of employment and underemployment within agricultural households in three communities in Kenya.
Lead authoring unit/office: Statistics Division (ESS)
Abstract: This publication provides guidance for a statistical office to use when forming an MSF. The goals of this document are to (1) describe a process for building, maintaining and using MSFs; (2) discuss interrelations among survey objectives, core data elements, construction of sampling frames, estimation, and archival of results; and (3) offer guidance for using multiple sources of information. The statistical office will need to consider how the directives presented in this document apply to a particular situation. When deciding on an MSF approach, the statistical office should consider the ultimate uses of the collected data and the desired estimates.
Lead authoring unit/office: Statistics Division (ESS)
Abstract: Prepared by the Global Strategy to Improve Agricultural and Rural Statistics (GSARS), this document presents two case-studies, to illustrate the process of compilation of productivity indicators: i) the calculation of labour productivity based on data collected at farm-level, that is based on a pilot survey in Zambia, and ii) the construction of aggregate and country-level information on agricultural productivity from aggregate time-series.
Lead authoring unit/office: Statistics Division (ESS)
Abstract: Prepared by the Global Strategy to Improve Agricultural and Rural Statistics (GSARS), this Technical Report aims to develop an international definition of rural areas and indicators of rural development. Countries participating in the pilots are the following: Brazil, Colombia, Ethiopia, France, Malaysia, Pakistan and United States of America (USA).
Lead authoring unit/office: Statistics Division (ESS)
Abstract: Prepared by the Global Strategy to Improve Agricultural and Rural Statistics (GSARS), this Technical Report aims to present the methodology implemented for the spatial delimitation and production of statistics of rural areas and the results obtained.
Lead authoring unit/office: Statistics Division (ESS)
Abstract: Prepared by the Global Strategy to Improve Agricultural and Rural Statistics (GSARS), this technical report presents the results of a field test implemented in Costa Rica as part of the research activities planned within the frame of GSARS research line “SUST-3: Data collection methods for agri-environmental indicators”.
Lead authoring unit/office: Statistics Division (ESS)
Abstract: This supplement on selected country experiences to the Handbook on Master Sampling Frames for Agriculture has been prepared within the framework of the Global Strategy to Improve Agricultural and Rural Statistics (GSARS). It is intended to provide practical examples on how sampling frames can be developed and used as master sampling frames in different country contexts given the diversity of country situations and resources. The selected country experiences include: Brazil, Bulgaria, China, Ethiopia, Georgia, Guatemala, Nepal, Rwanda, USA and USDA experiences in Nicaragua, Nigeria and Tanzania.
Lead authoring unit/office: Statistics Division (ESS)
Abstract: Prepared by the Global Strategy to improve agricultural and rural statistics (GSARS), this material for in-classroom training on the measurement of harvest and post-harvest losses for food grain targets decision makers, survey managers, questionnaire designers, trainers of field staff and data analysts interested or involved in the measurement of food losses. The course package includes: This user guide, which can be used as a course syllabus; A set of six PowerPoint presentations on the following topics: 1) Conceptual framework and definitions 2) Measuring grain losses on the farm 3) Analyses of losses at the lab 4) Sampling design 5) Loss assessment through experimental design or field trials 6) Loss assessment through modelling.
Lead authoring unit/office: Statistics Division (ESS)
Abstract: Prepared by the Global Strategy to improve agricultural and rural statistics (GSARS), this module aims to introduce the concepts used in food loss measurement, and inform the audience about the benefits of and need to assess losses through the value chain of a chosen crop. Outline of the session: a) Introduction; b) Concepts and definitions; c) Identifying loss “hotspots” or critical loss points; d) Example of other loss assessments.
Lead authoring unit/office: Statistics Division (ESS)
Abstract: Prepared by the Global Strategy to improve agricultural and rural statistics (GSARS), this session tackles the different methods and approaches to measure grain losses on the farm occurring during the different stages and operations executed by the farmer. It also briefly discusses the approaches to measuring losses after the grains leave the farm (that is, off-farm losses). Outline of the session: a) Introduction; b) Overview of measurement methods; c) Measuring losses based on farmer declarations; d) Measuring losses based on objective measurements; e) Measuring losses based on visual scales; f) Overview of approaches to off-farm loss measurement.
Lead authoring unit/office: Statistics Division (ESS)
