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: Offered by the European Commission, the Degree of Urbanisation is a method to delineate cities, towns, suburbs and rural areas for international statistical comparison. It has been adopted by the 51st Statistical Commission of the United Nations. This training provides the necessary background to apply independently the Degree of Urbanisation method. We offer a multi-level learning experience across the various aspects of the Degree of Urbanisation, to help understanding what it is and how it can be applied to your own data. Applications include Sustainable Development Goals monitoring and breakdown by urbanisation class, disaster risk management, environmental and climate investigations, demography, development and cooperation.
Abstract: Monitoring public spending devoted to food and agriculture is a critical policy analysis tool to better understand agricultural public expenditure and how it affects agricultural development, food security and economic growth. This course will equip you with the skills to carry out your public expenditure analysis, looking at total amounts and breakdown of spending. This will allow you to better monitor areas that are underinvested or those that have higher returns on investment, identify budget bottlenecks and prioritize spending, in line with national development objectives. The analysis and results can then be used to shape and influence policymaking on food and agriculture expenditure and investments.
Lead authoring unit/office: FAO
Abstract: This e-learning course is part of a series which introduce the FAO Damage and Loss (D&L) methodology, developed to support countries to generate precise and holistic data for the agricultural sector, in response to climate- and weather-related disasters. This course introduces the formulae which are used to compute damage and loss in the agricultural sectors (crops, livestock, forestry, aquaculture and fisheries). It then considers the data requirements and possible sources, and how the data can be used both to report on Sendai and SDG targets, and at national level. (Released in: December 2020; 2 h of learning)
Lead authoring unit/office: FAO
Abstract: In recent decades, the occurrence of climate- and weather-related disasters has increased, and globally, a vast number of agricultural livelihoods are compromised each year, with far-reaching effects on food security and ecosystems. This course is part of a series which aim to introduce the FAO Damage and Loss (D&L) methodology, developed by FAO to support countries to generate precise and holistic data for the agricultural sector. This can be used for national Disaster Risk Reduction/Management, resilience and to help monitor the achievement of global targets. (Released in: September 2020; 55 min of learning)
Lead authoring unit/office: Statistics Division (ESS)
Abstract: Sustainable Development Goal 12.3 is defined as the goal that “by 2030, halve per capita global food waste at the retail and consumer levels and reduce food losses along production and supply chains, including post-harvest losses”. The e-learning course covers the sub-indicator 12.3.1. a Food Loss Index (FLI) which will aid countries in reducing food losses along production and supply chains. The lessons cover the index and its components, along with strategies and guidelines for collecting, integrating and modelling the necessary data from a variety of sources.
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)
Abstract: This course focuses on SDG Indicator 14.4.1 - Fish stocks sustainability: “Proportion of fish stocks within biologically sustainable levels”. It introduces basic fisheries concepts and definitions, illustrates some technical aspects of classical and data-limited stock assessment and provides detailed guidance on process and tools for the analysis and reporting of the Indicator.
Lead authoring unit/office: FAO
Abstract: This course has been developed to support countries in computing and monitoring Indicators 2.3.1 and 2.3.2 of the 2030 Sustainable Development Goals (Labour Productivity and Income of Small-scale Food Producers), and to facilitate the understanding of the main concepts underpinning the methodology.
Lead authoring unit/office: FAO
Abstract: The course provides guidance on the rationale and the main characteristics of Indicator 6.4.1, and on how to compute the two dimensions constituting the indicator: the hydrologic and the economic component. It also highlights possible challenges related to data availability, and the impact that monitoring results may have on national decision-making and identification of development policies.
Lead authoring unit/office: FAO
Abstract: This course has been developed to guide countries in reporting on Indicators 15.1.1 and 15.2.1. It illustrates the rationale of the indicators, the definitions and methodologies on which monitoring activities are based, and explains the process and the tools available for compiling data related to the two indicators through the Global Forest Resources Assessment (FRA) Programme.
Lead authoring unit/office: FAO
