FAO/INFOODS Evaluation framework to assess the quality of published food composition tables and databases User guide

Year: 2023

Abstract: High-quality food composition data are crucial to obtain adequate results in research education, health claims and policy decisions. This publication targets compilers and users of food composition tables and databases working for example in ministries and government entities, academic and research institutions, and private and public sector institutions dealing with nutrition, agriculture or health. It will assist them in easily evaluating food composition tables and databases and advocate the importance of their high quality to decision makers. This user guide provides background information on the development of an evaluation framework, its objectives and underlying methodology, as well as an overview of the criteria and scoring system. Download the evaluation framework that accompanies this publication

Mapping of territorial markets Methodology and guidelines for participatory data collection

Year: 2022

Abstract: Malnutrition in all its forms (undernutrition, micronutrient deficiency, overweight and obesity) is a major global challenge, and improving nutrition is a key priority for global development, as recognized in the UN Decade of Action on Nutrition (2016–2025) and the 2030 Agenda for Sustainable Development. In this context, ensuring availability, physical accessibility and affordability of healthy and nutritious food at territorial level is crucial to ensure the achievement of the Sustainable Development Goals (SDGs). In many developing countries, territorial markets are key retail outlets for fruits and vegetables, but also for animal source foods and staple foods. Besides the relevance, data concerning the availability of the different food groups and characteristics of food retailers and consumers in territorial markets are seldom considered in national data collection systems. This publication presents a structured methodology and a series of guidelines for mapping territorial markets, as developed by the Food and Agriculture Organization of the United Nations (FAO), along with representatives of producer organizations and academics.

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Minimum Dietary Diversity for Women. An updated guide for measurement: from collection to action

Year: 2021

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

Guidelines on data disaggregation for SDG Indicators using survey data

Year: 2021

Abstract: The overarching principle of the 2030 Agenda for Sustainable Development – “leave no one behind” – calls for more granular and disaggregated data than are currently available in most countries, in order to inform the Sustainable Development Goal (SDG) monitoring process. Recognizing the fundamental role played by disaggregated data and information, the United Nations Statistical Commission (UNSC), at its Forty-seventh Session, requested the IAEG-SDG to form a working group on data disaggregation, with the objective of strengthening national capacities and developing the necessary statistical standards and tools to produce disaggregated data. As a member of the working group on data disaggregation, the Food and Agriculture Organization of the United Nations (FAO) has taken numerous steps towards supporting Member Countries in the production of disaggregated estimates. Within this framework, these Guidelines offer methodological and practical guidance for the production of direct and indirect disaggregated estimates of SDG indicators having surveys as their main or preferred data source. Furthermore, the publication provides tools to assess the accuracy of these estimates and presents strategies for the improvement of output quality, including Small Area Estimation methods.

Lead authoring unit/office: Office of Chief Statistician (OCS)

Metadata and microdata curation and dissemination protocol

Year: 2021

Abstract: Data collected through surveys, and administrative systems form the foundation of official statistics, and are an invaluable source for research. They are aggregated to generate national estimates by official statisticians, and analyzed by researchers and policy analysts to gain scientific insights which can be translated into policy. These data are commonly referred to as microdata defined as to unitlevel information on individual people or entities (such as individuals, households, business enterprises, farms, or even geographic areas). The power of microdata stems from its granularity. Because microdata contain individual level information, they allow an analyst to investigate the unique ways a certain phenomenon may effect sub-populations. For example, a particular agricultural policy may effect male and female agricultural holders differently. Likewise, a social protection scheme may benefit a particular demographic and disadvantage another. This type of analysis is impossible without highly granular datasets which allow for the analyst to stratify a dataset by a one or more variables. Itisimportantto note here thatthis protocol incorporatesthe FAO Personal Data Protection Principles (AC No. 2021/01) and it is in accordance with the principles.

Lead authoring unit/office: Office of Chief Statistician (OCS)

Statistical disclosure control protocol

Year: 2021

Abstract: Statisticians have long acknowledged the importance of securing this information in order to maintain the trust of the populations they serve. In this regard, the 6th principle of the Fundamental Principles of Official Statistics states “Individual data collected by statistical agencies for statistical compilation, whether they refer to natural or legal persons, are to be strictly confidential and used exclusively for statistical purposes.” Furthermore, FAO’s Statistical Quality Assurance defines Principle 10 as “All data subject to national confidentiality policies (e.g. concerning people and legal entities, or small aggregates) are kept strictly confidential, and are used exclusively for statistical purposes, or for purposes mandated by legislation.” However, while acknowledging the importance of securing individual data, the United Nations also advocates for the free dissemination of microdata. Disseminating microdata allows users to engage in research, increases the transparency and accountability of nationalstatistical institutions, and generate quality improvements through feedback from users (UNSD 2014). The competing principles of data security and microdata dissemination are arbitrated through a domain ofstatistics called Statistical Disclosure Control (SDC). SDC methods allow for protecting a dataset through the application of statistical tools, allowing the institution to safely disseminate the micro dataset. It is important to note here that this protocol incorporates the FAO Personal Data Protection Principles (AC No. 2021/01) and it is in accordance with the principles.

Lead authoring unit/office: Office of Chief Statistician (OCS)

System of Environmental-Economic Accounting for Agriculture, Forestry and Fisheries (SEEA-AFF)

Year: 2020

Abstract: The System of Environmental-Economic Accounting for Agriculture, Forestry and Fisheries (SEEA-AFF) is a statistical framework that facilitates description and analysis of agriculture, forestry and fisheries as economic activities and their relationship with the environment. It extends to these primary sectors the environmental-economic structure and principles of the System of Environmental-Economic Accounting Central Framework (SEEA-CF), an official UN statistical standard. The SEEA-AFF defines core national accounting tables, easily integrated into synthetic view tables, provided as a basis for the measurement and reporting of information on physical and monetary assets and flows accounts on natural resource use, production, trade and consumption of food and other agricultural products. It thus offers countries a robust statistical structure for the development of agri-environmental indicators, including SDGs, which can be monitored in a transparent, coherent and internationally comparable manner.

Lead authoring unit/office: United Nations Statistics Division (UNSD)

Food-based dietary guidelines

Year: 2020

Abstract: Food-based dietary guidelines (also known as dietary guidelines) are intended to establish a basis for public food and nutrition, health and agricultural policies and nutrition education programmes to foster healthy eating habits and lifestyles. They provide advice on foods, food groups and dietary patterns to provide the required nutrients to the general public to promote overall health and prevent chronic diseases.

Lead authoring unit/office: Statistics Division (ESS)

Guidelines for collecting data for sex-disaggregated and gender-specific indicators in national agricultural surveys (Second edition)

Year: 2018

Abstract: Prepared by the Global Strategy to Improve Agricultural and Rural Statistics (GSARS), these Guidelines aim to improve the availability of systematically integrated and comparable sex-disaggregated and gender-relevant data within agricultural surveys by bridging significant data gaps. Specifically, the Guidelines identify key indicators focusing on crop and livestock activities in developing countries where the agricultural sector is largely characterized by agricultural households, and propose adaptations to existing agriculture surveys based on the latest research in survey methods and gender analysis.

Lead authoring unit/office: Statistics Division (ESS)

Guidelines for the Integrated Survey Framework

Year: 2018

Abstract: The growing demand by policymakers and decision makers for statistics based on information that is interlinked in economic, social, and environmental aspects requires the large-scale expansion of national efforts to implement statistical surveys, in terms of organization and budget. Therefore, the collection of data by integrating information from different sources is becoming a crucial requirement for the production of statistics. The Guidelines are intended especially for use by the staff of national statistical offices and ministries or agencies that are involved in data collection on agriculture, and seek to provide basic information with a step-by-step approach, beginning with practical examples drawn from the experiences of certain countries. These Guidelines illustrate a statistical method that produces correct estimates with reduced time and costs; in particular, they demonstrate the application of indirect sampling to integrated household surveys for a wide range of topics on the basis of the correspondence between households and holdings, so that these may be observed in various scenarios within a single survey.These guidelines were prepared by the Global Strategy to Improve Agricultural and Rural Statistics (GSARS).

Lead authoring unit/office: Statistics Division (ESS)

Guidelines on defining rural areas and compiling indicators for development policy

Year: 2018

Abstract: Prepared by the Global Strategy to Improve Agricultural and Rural Statistics (GSARS), these Guidelines aim to support decisions about rural development policy by offering concepts and methods to improve the quality, availability, and use of statistics. The Guidelines present and explain how to construct a rural definition that is useful for organizing statistical information about rural areas.

Lead authoring unit/office: Statistics Division (ESS)

Guidelines for measuring youth employment and decent work in agriculture within developing countries

Year: 2018

Abstract: These Guidelines, developed as part of the Global Strategy to improve Agricultural and Rural Statistics (GSARS), seek to measure dimensions of labour force performance and job quality that are not well captured in the Decent Work framework in this setting. More specifically, the Guidelines propose Decent Work indicators that focus on youth (ages 15–24 years) within developing countries where the majority of households depend on agriculture for their well-being and a large share of the population lives in poverty. 

Lead authoring unit/office: Statistics Division (ESS)

Guidelines for the compilation of food balance sheets

Year: 2017

Abstract: These Guidelines for the compilation of Food Balance Sheets have been developed under the Global Strategy to improve Agricultural and Rural Statistics (GSARS), with the intention to provide countries with a user-friendly handbook that can aid in the construction of country-level Food Balance Sheets (FBS) as a tool for policy analysis.

Lead authoring unit/office: Statistics Division (ESS)

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Handbook on agricultural cost of production statistics. Guidelines for data collection, compilation and dissemination

Year: 2016

Abstract: This version of the Handbook on Agricultural Cost of Production Statistics was prepared under the aegis of the Global Strategy to Improve Agricultural and Rural Statistics (Global Strategy), an initiative endorsed by the United Nations Statistical Commission in 2010. This Handbook presents guidelines and recommendations for designing and implementing a statistical program on cost of production (CoP) in agriculture at the country level.  This Handbook may serve as a useful reference tool for agricultural statisticians and economists to build on or to adapt existing programmes for estimating agricultural costs of production, and for analysts to understand the nature and limitations of data from which final indicators are derived. 

Lead authoring unit/office: Statistics Division (ESS)

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Guidelines on the Integrated Survey Framework

Year: 2015

Abstract: These Guidelines for the Integrated Survey Framework have been developed as a specific topic of the “Technical Report on the Integrated Survey Framework”, within the Research activity carried out by the Global Strategy to improve Agricultural and Rural Statistics. These Guidelines illustrate a statistical method that produces correct estimates with reduced time and costs; in particular, they demonstrate the application of indirect sampling to integrated household surveys for a wide range of topics on the basis of the correspondence between households and holdings, so that these may be observed in various scenarios within a single survey.

Lead authoring unit/office: Statistics Division (ESS)

System of Environmental-Economic Accounting 2012: Central Framework (SEEA-CF)

Year: 2014

Abstract: The System of Environmental-Economic Accounting 2012: Central Framework (SEEA-CF), was adopted as the first international standard for environmental-economic accounting by the United Nations Statistical Commission at its 43rd Session in 2012. It fits into the System of National Accounts (SNA), which is an integrated system of macroeconomic accounting that most countries in the world follow. SEEA integrates the impact of the environment into the economy. Adopting an accounting approach in agriculture leads to a set of standard classifications from which a consistent and comprehensive data are compiled and comparable across countries and regions.

Lead authoring unit/office: United Nations Statistics Division (UNSD)

Guidelines for assessing country capacity to produce agricultural and rural statistics

Year: 2014

Abstract: 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.

Lead authoring unit/office: Statistics Division (ESS)

System of Environmental-Economic Accounts for Water (SEEA-Water)

Year: 2012

Abstract: SEEA-Water was developed with the objective of standardizing concepts and methods in water accounting. It provides a conceptual framework for organizing economic and hydrological information, enabling a consistent analysis of the contribution of water to the economy and of the impact of the economy on water resources. SEEA-Water further elaborates the framework presented in SEEA-2003 to cover in more detail all aspects related to water. FAO has also been involved in the preparation of the United Nations SEEA-Water led by the United Nations Statistics Division (UNSD) in collaboration with the London Group on Environmental Accounting (in particular its subgroup on Water Accounting). The Natural Resources Management and Environment Department was particularly engaged in the preparation of the International Recommendations for Water Statistics (IRWS) which were finalized in 2010 and adopted by UNSC.

Lead authoring unit/office: United Nations Statistics Division (UNSD)

Food balance sheets - A handbook

Year: 2001

Abstract: These Guidelines set out a methodology for the collection of data and information on various aspects of the fisheries and aquaculture sector, especially concerning small-scale operators.

Lead authoring unit/office: Statistics Division (ESS)

Access to food in 2022: Filling data gaps

Year: 2023

Abstract: This report presents the results of food insecurity assessments based on the food insecurity experience scale (FIES) data collected by FAO in seven countries facing food insecurity crises, between September 2022 and October 2022. The detailed results, presented at the subnational level, can support country-level decision-making and will also inform the monitoring of the Sustainable Development Goals (SDGs) and targets, specifically SDG Target 2.1

Lead authoring unit/office: Statistics Division (ESS)

West African and Monetary Union countries 2018/19 living standards and conditions survey

Year: 2023

Abstract: The Rural Livelihoods Information System (RuLIS) is a set of harmonized household- and individual-level data and indicators on different aspects of livelihoods, including crops and livestock production, off-farm and non-farm income generating activities, households’ composition and demographics, agricultural inputs, technology use, access to social protection, time use, shocks and migration. RuLIS currently includes information from 39 countries, with increasing data coverage in time and space as more micro-data becomes available. RuLIS aims to provide critical information for understanding medium- and long- term trends in the structural transformation of agriculture and rural economies; and for the design of policies that promote and accompany social and economic transformation and enhancement. RuLIS provides data on a wide set of indicators, cross-tabulated by rural vs urban areas, gender and other variables; and standardized variables at the household and individual level. This brief uses RuLIS data to analyze survey data from eight Member States of the West African Economic and Monetary Union (WAEMU) to highlight the results of some key indicators related to living standards and conditions.

Lead authoring unit/office: Statistics Division (ESS)

Report on off-farm post-harvest loss assessment survey in Ethiopia

Year: 2023

Abstract: A study on post-harvest losses was conducted in Amhara, Oromiya and the Southern nation nationality and peoples regions of Ethiopia to pilot a methodology to produce national statistics of off-farm losses. The study was conducted by the Ethiopian Statistics Service (ESS), with technical and financial support from the Office of the Chief Statistician and the Statistics Division of the Food and Agriculture Organization of the United Nations (FAO).

Lead authoring unit/office: Statistics Division (ESS)

Integrating surveys with geospatial data through small area estimation to disaggregate SDG indicators at subnational level Case study on SDG Indicators 2.3.1 and 2.3.2

Year: 2023

Abstract: The present technical report illustrates a case study on the adoption of small area estimation techniques to produce granular sub-national estimates of SDG Indicators 2.3.1 and 2.3.2, by integrating survey microdata with auxiliary information retrieved from various trustworthy geospatial information systems. The technical report provides practical guidance to national statistical offices and other institutions wanting to implement small area estimation techniques on SDG Indicators 2.3.1 and 2.3.2 or similar indicators based on surveys microdata.

Lead authoring unit/office: Office of Chief Statistician (OCS)

Alternative methods for disaggregating Sustainable Development Goal indicators using survey data

Year: 2022

Abstract: Samples used in most surveys are either not large enough to guarantee reliable direct estimates for all relevant sub-populations, or do not cover all possible disaggregation domains. After having described a holistic strategy for producing disaggregated estimates of Sustainable Development Goal (SDG) indicators, this paper discusses alternative sampling and estimation methods that can be applied when sample surveys are the primary data source. In particular, the paper focuses on strategies that can be implemented at different stages of the statistical production process. At the design stage, the paper describes a series of sampling approaches that ensure a “sufficient” sampling size for each disaggregation domain. In this context, the article highlights the main limitations of traditional sampling approaches and shows how ad-hoc techniques could overcome some of their key constraints. At the analysis stage, it discusses an indirect model-assisted estimation approach to integrate data from independent surveys and censuses, eliminating costs deriving from redesigning data collection instruments, and ensuring a greater accuracy of the final disaggregated estimates. A case study applying the abovementioned method on the production of disaggregated estimates of SDG Indicator 2.1.2 (Prevalence of Moderate and Severe Food Insecurity) is then presented along with its main results.

Lead authoring unit/office: Office of Chief Statistician (OCS)

Estimating the prevalence of nutrient inadequacy from household consumption and expenditure surveys

Year: 2022

Abstract: Malnutrition is pervasive in both low- and middle-income countries. Yet, there is a scarcity of food intake data collected at the individual level to describe diets, determine the prevalence of inadequate nutrient consumption in populations, and shed light on how diets contribute to the malnutrition burden. In the absence of nationally representative individual-level food intake surveys, particularly in low- and middle-income countries, dietary data collected in household consumption and expenditure surveys (HCES) are being used as a second-best option to make inferences on the food and nutrient consumption of populations. This paper proposes an innovative approach to estimate variability in nutrient intake that uses food data collected in HCES to estimate the prevalence of nutrient inadequacy in a country. This method builds on the approach developed by FAO to estimate the indicator of inequality used in the Prevalence of Undernourishment used in the global monitoring of food insecurity.

Lead authoring unit/office: Statistics Division (ESS)

Using small area estimation for data disaggregation of SDG indicators – Case study based on SDG Indicator 5.a.1.

Year: 2022

Abstract: This technical report presents a case study based on the use of a small area estimation (SAE) approach to produce disaggregated estimates of SDG Indicator 5.a.1 by sex and at granular sub-national level. In particular, after introducing the framework for using SAE techniques, the report discusses a possible model-based technique to integrate a household or agricultural survey measuring the indicator of interest with census microdata, in order to borrow strength from a more comprehensive data source and produce estimates of higher quality. The discussed estimation approach could also be extended or customized for the integration of survey data with alternative data sources, such as administrative records, and/or geospatial information, and for the disaggregation of other (SDG) indicators based on survey microdata.

Lead authoring unit/office: Office of Chief Statistician (OCS)

An indirect estimation approach for disaggregating SDG indicators using survey data - Case study based on SDG Indicator 2.1.2

Year: 2022

Abstract: 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). It complements the 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.

Lead authoring unit/office: Office of Chief Statistician (OCS)

Methods for estimating greenhouse gas emissions from food systems. Part III: energy use in fertilizer manufacturing, food processing, packaging, retail and household consumption. FAO Statistics Working Paper Series / 21-29

Year: 2021

Abstract: This paper is part of a series detailing new methodologies for estimating key components of agri-food systems emissions, with a view to disseminate the information in FAOSTAT. It describes methods for estimating greenhouse gas (GHG) emissions from fossil fuel-based energy use in agri-food systems processes outside agricultural land, i.e. those associated with pre- and post-production activities – in an effort to inform countries of the environmental impacts of agri-food systems and the possible options to reduce them.

Lead authoring unit/office: Statistics Division (ESS)

Gender and age dimensions in rural agricultural employment: analysis using Rural Livelihoods Information System (RuLIS)

Year: 2021

Abstract: RuLIS is a tool to support policies for reducing rural poverty, jointly developed by the Food and Agriculture Organization of the United Nations (FAO) Statistics Division, the World Bank and the International Fund for Agricultural Development (IFAD). RuLIS brings together harmonized indicators and comparable data across countries and over time on rural incomes, livelihoods and rural development. Using the surveys that are processed as part of the RuLIS database project, this brief explores patterns and trends in rural employment for women and youth with a focus on agriculture in 16 low-income and lower-middle-income countries around the world: 11 from sub-Saharan Africa, two from East Asia and the Pacific, two from Latin America and the Caribbean, and one from Central Asia.

Lead authoring unit/office: Statistics Division (ESS)

What is the share of income from crop and livestock production in total income in rural sub-Saharan Africa?

Year: 2021

Abstract: RuLIS is a tool to support policies for reducing rural poverty, jointly developed by the Food and Agriculture Organization of the United Nations (FAO) Statistics Division, the World Bank and the International Fund for Agricultural Development (IFAD). RuLIS brings together harmonized indicators and comparable data across countries and over time on rural incomes, livelihoods and rural development. This brief uses data from RuLIS to estimate the contribution of income from crop and livestock production to households’ total annual income. The shares in total income are also analysed across expenditure quintiles. The brief aims at exploring the importance of income from on-farm agricultural sources in rural livelihoods.

Lead authoring unit/office: Statistics Division (ESS)

Adoption of farm inputs, mechanization, irrigation and gender gaps in sub-Saharan Africa: insights from the Rural Livelihoods Information System (RuLIS)

Year: 2021

Abstract: RuLIS is a tool to support policies for reducing rural poverty, jointly developed by the Food and Agriculture Organization of the United Nations (FAO) Statistics Division, the World Bank and the International Fund for Agricultural Development (IFAD). RuLIS brings together harmonized indicators and comparable data across countries and over time on rural incomes, livelihoods and rural development. Using the RuLIS data, this brief focuses on the observations made in the adoption of agricultural inputs, along with improved technology such as irrigation, and mechanised tools among crop farm households in sub-Saharan Africa.

Lead authoring unit/office: Statistics Division (ESS)

Weather- and disease-related shocks in agriculture using data from the Rural Livelihoods Information System (RuLIS)

Year: 2021

Abstract: RuLIS is a tool to support policies for reducing rural poverty, jointly developed by the Food and Agriculture Organization of the United Nations (FAO) Statistics Division, the World Bank and the International Fund for Agricultural Development (IFAD). RuLIS brings together harmonized indicators and comparable data across countries and over time on rural incomes, livelihoods and rural development. Using the RuLIS data, this brief focuses on weather and geophysical shocks, and crop or livestock disease-related shocks, along with the coping strategies used by the affected households.

Lead authoring unit/office: Statistics Division (ESS)

Measuring SDG indicator 5.a.1: Individual’s land ownership over agricultural land using data from the Rural Livelihoods Information System (RuLIS)

Year: 2021

Abstract: RuLIS is a tool to support policies for reducing rural poverty, jointly developed by the Food and Agriculture Organization of the United Nations (FAO) Statistics Division, the World Bank and the International Fund for Agricultural Development (IFAD). RuLIS brings together harmonized indicators and comparable data across countries and over time on rural incomes, livelihoods and rural development and allows monitoring the status and progressr of Sustainable Development Goals (SDG) indicators. SDG 5.a1 measures women’s ownership rights and control over agricultural land. Through this indicator it is possible to assess the extent of women’s disadvantages in ownership and tenure rights over agricultural land, providing a basis for policy measures aimed at securing women equal opportunities and access to economic resources. This brief is the first analysis that employs a harmonized methodology for measuring tenure rights over agricultural land based on RuLIS data.

Methods for estimating greenhouse gas emissions from food systems. Part I: domestic food transport. FAO Statistics Working Paper Series 21-27

Year: 2021

Abstract: This paper is the first in a series of ongoing and planned efforts to build on current knowledge and develop methodologies for estimating new components of food systems emissions, with a view to disseminate the information in FAOSTAT. It provides a methodology for estimating the GHG emissions associated with historic and current domestic food transport, in an effort to inform countries of the environmental impact of their food distribution systems. Our efforts respond to the call of the upcoming Food Systems Summit to characterize the role of food and agriculture to accelerate achievement of the Sustainable Development Goals. In particular, they align well with Goal 12 to ensure “sustainable consumption and production patterns’’, specifically Target 12.2, “achieve the sustainable management and efficient use of natural resources” and Indicator 12.2.1, which monitors the “material footprint, material footprint per capita, and material footprint per GDP” of different products. Last updated date 20/09/2021, see corrigendum

Lead authoring unit/office: Statistics Division (ESS)

The relationship between food insecurity and dietary outcomes. An analysis conducted with nationally representative data from Kenya, Mexico, Samoa and the Sudan. FAO Statistics Working Paper Series / 21-25

Year: 2021

Abstract: Little research has been conducted on the association of food insecurity, particularly at the moderate level, and dietary consumption in low- and middle-income countries. This study expands on previous works by considering cross-country comparable measures of food insecurity that are calibrated against the global Food Insecurity Experience Scale (FIES). The FAO Statistics Division has been publishing estimates of the prevalence of food insecurity, based on the FIES, since 2017. The FIES is the first standardized measure, of people's direct experiences of food insecurity, appropriate for application on a global scale. The prevalence of moderate or severe food insecurity based on the FIES is one of the official SDG indicators (2.1.2). The objective of this study is to explore the relationship between the severity of food insecurity, as measured with the FIES (or an analogous experience-based food insecurity scale calibrated to the global reference scale), and dietary intake using microdata from four middle-income countries from different world regions: Kenya, Mexico, Samoa, and Sudan.

Lead authoring unit/office: Statistics Division (ESS)

Methodological guideline for monitoring SDG indicator 5.a.1. Gender parity in tenure rights over agricultural land: Data collection methods and calculation

Year: 2021

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)

SDG-indicator 2.5.1.b Metadata

Year: 2021

Abstract: This document reflects the latest reference metadata information available on SDG-indicator 2.5.1.b "Number of animal genetic resources for food and agriculture secured in medium or long term conservation facilities". Last updated: March 2021.

Lead authoring unit/office: FAO

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Applying the degree of urbanisation — A methodological manual to define cities, towns and rural areas for international comparisons

Year: 2021

Abstract: Applying the Degree of Urbanisation — A methodological manual to define cities, towns and rural areas for international comparisons has been produced in close collaboration by six organisations — the European Commission, the Food and Agriculture Organization of the United Nations (FAO), the United Nations Human Settlements Programme (UN-Habitat), the International Labour Organization (ILO), the Organisation for Economic Co-operation and Development (OECD) and The World Bank.  The manual is intended to complement and not replace the definitions used by national statistical offices (NSOs) and ministries. It has been designed principally as a guide for data producers, suppliers and statisticians so that they have the necessary information to implement the methodology and ensure coherency within their data collections. It may also be of interest to users of subnational statistics so they may better understand, interpret and use official subnational statistics for taking informed decisions and policymaking. See also: GHSL - Global Human Settlement Layer and elearning course "The Degree of Urbanisation" from the EU Academy.

Lead authoring unit/office: FAO

SDG-indicator 2.5.1.a Metadata

Year: 2021

Abstract: This document reflects the latest reference metadata information available on SDG-indicator 2.5.1.a "Number of palnt genetic resources for food and agriculture secured in medium or long term conservation facilities". Last updated: March 2021.

Lead authoring unit/office: FAO

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SDG-indicator 2.1.1 Metadata

Year: 2021

Abstract: This document reflects the latest reference metadata information available on SDG-indicator 2.1.1 "Prevalence of undernourishment". Last updated: February 2021.

Lead authoring unit/office: FAO

SDG-indicator 2.1.2 Metadata

Year: 2021

Abstract: This document reflects the latest reference metadata information available on SDG-indicator 2.1.2 "Prevalence of moderate or severe food insecurity in the population, based on the Food Insecurity Experience Scale". Last updated: February 2021.

Lead authoring unit/office: FAO

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SDG-indicator 2.3.1 Metadata

Year: 2021

Abstract: This document reflects the latest reference metadata information available on SDG-indicator 2.3.1 "Volume of production per labour unit by classes of farming / pastoral / forestry enterprise size". Last updated: February 2021.

Lead authoring unit/office: FAO

SDG-indicator 2.3.2 Metadata

Year: 2021

Abstract: This document reflects the latest reference metadata information available on SDG-indicator 2.3.2 "Average income of small-scale food producers, by sex and indigenous status". Last updated: February 2021.

Lead authoring unit/office: FAO

SDG-indicator 2.4.1 Metadata

Year: 2021

Abstract: This document reflects the latest reference metadata information available on SDG-indicator 2.4.1 "Proportion of agricultural area under productive and sustainable agriculture". Last updated: March 2021.

Lead authoring unit/office: FAO

SDG-indicator 2.5.2 Metadata

Year: 2021

Abstract: This document reflects the latest reference metadata information available on SDG-indicator 2.5.2 "Proportion of local breeds classified as being at risk of extinction". Last updated in March 2021.

Lead authoring unit/office: FAO

SDG-indicator 2.a.1 Metadata

Year: 2021

Abstract: This document reflects the latest reference metadata information available on SDG-indicator 2.a.1 " Public Investment in agriculture". Last updated: March 2021.

Lead authoring unit/office: FAO

SDG-indicator 2.c.1 Metadata

Year: 2021

Abstract: This document reflects the latest reference metadata information available on SDG-indicator 2.c.1 "Indicator of (food) price anomalies". Last updated: March 2021.

Lead authoring unit/office: FAO

SDG-indicator 5.a.1 Metadata

Year: 2021

Abstract: This document reflects the latest reference metadata information available on SDG-indicator 5.a.1. "(a) Percentage of people with ownership or secure rights over agricultural land (out of total agricultural population), by sex; and (b) share of women among owners or rights-bearers of agricultural land, by type of tenure". Last updated: February 2021.

Lead authoring unit/office: FAO

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SDG-indicator 5.a.2 Metadata

Year: 2021

Abstract: This document reflects the latest reference metadata information available on SDG-indicator 5.a.2 "Proportion of countries where the legal framework (including customary law) guarantees women’s equal rights to land ownership and/or control". Last updated: February 2021.

Lead authoring unit/office: FAO

SDG-indicator 6.4.1 Metadata

Year: 2021

Abstract: This document reflects the latest reference metadata information available on SDG-indicator 6.4.1 "Change in water use efficiency over time". Last updated: February 2021.

Lead authoring unit/office: FAO

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SDG-indicator 6.4.2 Metadata

Year: 2021

Abstract: This document reflects the latest reference metadata information available on SDG-indicator 6.4.2 "Level of water stress: freshwater withdrawal as a proportion of available freshwater resources". Last updated: February 2021.

Lead authoring unit/office: FAO

SDG-indicator 12.3.1 Metadata

Year: 2021

Abstract: This document reflects the latest reference metadata information available on SDG-indicator 12.3.1 "Global Food Loss and Waste". Last updated: February 2021.

Lead authoring unit/office: FAO

SDG-indicator 14.4.1 Metadata

Year: 2021

Abstract: This document reflects the latest reference metadata information available on SDG-indicator 14.4.1 "Proportion of fish stocks within biologically sustainable levels". Last updated: February 2021.

Lead authoring unit/office: FAO

SDG-indicator 14.6.1 Metadata

Year: 2021

Abstract: This document reflects the latest reference metadata information available on SDG-indicator 14.6.1 "Progress by countries in the degree of implementation of international instruments aiming to combat illegal, unreported and unregulated fishing". Last updated: February 2021.

Lead authoring unit/office: FAO

SDG-indicator 14.7.1 Metadata

Year: 2021

Abstract: This document reflects the latest reference metadata information available on SDG-indicator 14.7.1 "Sustainable fisheries as a percentage of GDP in small island developing States, least developed countries and all countries". Last updated: February 2021.

Lead authoring unit/office: FAO

SDG-indicator 14.b.1 Metadata

Year: 2021

Abstract: This document reflects the latest reference metadata information available on SDG-indicator 14.b 1 "Degree of application of a legal / regulatory / policy /institutional framework which recognizes and protects access rights for small-scale fisheries". Last updated: February 2021.

Lead authoring unit/office: FAO

SDG-indicator 15.1.1 Metadata

Year: 2021

Abstract: This document reflects the latest reference metadata information available on SDG-indicator 15.1.1 "Forest area as a percentage of total land area". Last updated: February 2021.

Lead authoring unit/office: FAO

SDG-indicator 15.2.1 Metadata

Year: 2021

Abstract: This document reflects the latest reference metadata information available on SDG-indicator 15.2.1 "Progress towards sustainable forest management". Last updated: February 2021.

Lead authoring unit/office: FAO

SDG-indicator 15.4.2 Metadata

Year: 2021

Abstract: This document reflects the latest reference metadata information available on SDG-indicator 15.4.2 "Mountain Green Cover Index". Last updated: 14 February 2021

Lead authoring unit/office: FAO

A guide to 50x2030 survey tools and SDG Indicator 5.a.1. Measuring gender parity in ownership and tenure rights over agricultural land

Year: 2021

Abstract: This technical note describes how the survey tools of the 50x2030 Initiative satisfy the data requirements of SDG Indicator 5.a.1. It provides guidance on the calculation of the indicator and advises on the potential for detailed analysis beyond the Indicator. 

Lead authoring unit/office: Statistics Division (ESS)

Guidelines on the measurement of harvest and post-harvest losses. Estimation of crop harvest and post-harvest losses in Malawi. Maize, rice and groundnuts. Field test report

Year: 2020

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

Global and regional food availability from 2000 to 2017 – An analysis based on Supply Utilization Accounts data

Year: 2020

Abstract: One of the main pillars of food security is food supply, which refers to the availability of sufficient quantities of food of appropriate quality, supplied through domestic production or imports. In this paper, we use quantities of commercialized foods from the Supply and Utilization Accounts (SUA) compiled by the Food and Agriculture Organization of the United Nations (FAO) to analyze trends in food available for consumption based on by region and country income level group. Results show that, in general, food groups available for consumption differ across income-level country groups. There are nonetheless evident regional trends. Low-income and lower-middle-income countries have a high reliance on staple foods, and only upper-middle-income countries and Asia have enough fruits and vegetables available to meet the FAO/World Health Organization (WHO) recommendation of consuming a minimum of 400 grams per day. In addition, the availability of animal-source foods, as well as sugars and fats, overall is highest in high-income countries, but it is increasing fast in upper-middle-income countries. This document is part of FAO Statistics Working Paper Series.

Lead authoring unit/office: Statistics Division (ESS)

FAO’s methodology for damage and loss assessment in agriculture

Year: 2020

Abstract: This paper presents the FAO Damage and Loss Assessment Methodology as a framework for identifying, analyzing and evaluating the impact of disasters on agriculture, including crops, livestock, aquaculture, fisheries and forestry. Its potential is explored as a strategic tool for assembling and interpreting new or existing information to inform risk-related policy decision-making and planning. It is part of FAO Statistics Working Paper Series.

Lead authoring unit/office: Statistics Division (ESS)

Measuring SDG Indicator 5.a.1 - Background paper

Year: 2020

Abstract: The methodological work required to develop the 5.a.1 protocol was carried out by the Evidence and Data for Gender Equality (EDGE) project, an initiative jointly executed by the United Nations Statistics Division and the United Nations Entity for Gender Equality and the Empowerment of Women (UN Women) in collaboration with National Statistical Offices, the Asian Development Bank, the Food and Agriculture Organization of the United Nations, the Organization for Economic Co-operation and Development (OECD) and the World Bank.

Lead authoring unit/office: FAO

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Methodological note on new estimates of the prevalence of undernourishment in China

Year: 2020

Abstract: This paper presents new estimates of the extent of food consumption inequality in mainland China and discusses their implications for the estimated prevalence of undernourishment (PoU). The new food consumption inequality estimates are based on the joint analysis of food consumption and food expenditure data obtained from two separate household surveys, covering the period from 2011 to 2017. The results reveal much less inequality in dietary energy consumption than previously assumed and imply a substantial downward revision of the estimated series of the PoU for China, which becomes more in line with other assessments of food insecurity and with other development indicators. This document is part of FAO Statistics Working Paper Series. Revised 27 July 2020, minor edits made on p. 16

Lead authoring unit/office: Statistics Division (ESS)

FAO/Intake joint meeting report on dietary data collection, analysis and use

Year: 2020

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

Methodological note for SDG Indicator 2.4.1

Year: 2019

Abstract: This document serves as a methodological note for SDG-indicator 2.4.1 "Proportion of agricultural area under productive and sustainable agriculture". (Last updated: November 2019).

Lead authoring unit/office: FAO

The new FAO global database on agriculture investment and capital stock

Year: 2019

Abstract: This paper, which is part of FAO Statistics Working Paper Series, presents the new FAO analytical database on aggregate physical investment flows and capital stock in agriculture, forestry and fishing for 206 countries and territories from 1990 to 2015, the methodology used to deal with missing data, and the measurement issues underlying its development.

Lead authoring unit/office: Statistics Division (ESS)

Methodology for computing and monitoring the Sustainable Development Goal indicators 2.3.1 and 2.3.2

Year: 2019

Abstract: The purpose of this note, which is part of FAO Statistics Working Paper Series, is to inform on the statistical methodology for computing and monitoring target 2.3 and measure progress in SDG indicators 2.3.1 and 2.3.2 approved by the Inter-Agency and Expert Group on the Sustainable Development Goals.

Lead authoring unit/office: Statistics Division (ESS)

Methodological proposal for monitoring SDG target 12.3.1 sub-Indicator 12.3.1.a. The food loss index design, data collection methods and challenges

Year: 2019

Abstract: This paper, which is part of FAO Statistics Working Paper Series, delves into the rationale of the Food Loss Index, presenting the various elements of its methodology. It contains a set of definitional framework and scope of the index, it illustrates the rationale for estimating losses as the percentage of food quantities removed from the supply chain. The final section of the paper summarizes FAO’s approach to food loss data.

Lead authoring unit/office: Statistics Division (ESS)

Methodological paper on SDG sub-indicator 12.3.1.a

Year: 2018

Abstract: This paper delves into the rationale of the index design and then presents the various elements of the methodology. The paper starts with the definitional framework and scope of the index, it illustrates the rationale for estimating losses as the percentage of food quantities removed from the supply chain. It illustrates the commodities basket, their selection criteria, the compilation of the index weights and the steps for calculating the index. The final section of the paper summarizes FAO’s two pronged approach to food loss data. Last updated: November 2018.

Lead authoring unit/office: Office of Chief Statistician (OCS)

Measuring inadequate employment in Kenya: Field test report for decent work within an agricultural context in developing countries

Year: 2018

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)

Pilot tests of an international definition of urban-rural territories. Summary report

Year: 2018

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)

Methodology for definition and spatial delimitation of rural areas

Year: 2018

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)

Pilot testing on the food loss index

Year: 2018

Abstract: The objective of the Sustainable Development Goal (SDG) 12 is to ‘Ensure sustainable consumption and production patterns’, with the more specific Target 12.3 which aims, “by 2030, to 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 indicator for this target (Global Food Loss Index) was categorized as a Tier III indicator, meaning that the methodology, data collection mechanisms and a baseline needed to be fully developed, tested and adopted. This paper proposes the methodology for the Global Food Loss Index developed by FAO to measure and monitor losses for its up-grade to Tier II.

Lead authoring unit/office: Statistics Division (ESS)

Master sampling frames - The field experiments conducted in Nepal

Year: 2017

Abstract: Prepared by the Global Strategy to Improve Agricultural and Rural Statistics (GSARS), this technical report on Master Sampling Frames describes the field experiments conducted in Nepal.   

Lead authoring unit/office: Statistics Division (ESS)

The social dimension of rural statistics

Year: 2017

Abstract: Prepared by the Global Strategy to Improve Agricultural and Rural Statistics (GSARS), this Technical Report focuses on the social dimension of rural statistics, offering ideas and possible solutions to improve information on rural populations that is relevant to the formulation of poverty reduction policies.

Lead authoring unit/office: Statistics Division (ESS)

Improving methods for estimating livestock production and productivity. Methodological report

Year: 2017

Abstract: Prepared by the Global Strategy to Improve Agricultural and Rural Statistics (GSARS), this Technical Report proposes methods for the collection of data to compile improved measures of selected indicators, based on analyses of existing methods and field-testing of alternatives.

Lead authoring unit/office: Statistics Division (ESS)

A literature review on frameworks and methods for measuring and monitoring sustainable agriculture

Year: 2017

Abstract: Prepared by the Global Strategy to Improve Agricultural and Rural Statistics (GSARS), this Literature Review shows that agricultural sustainability has been understood largely in its environmental dimensions, that it is affected by socio-economic and biophysical conditions, and that obstacles to sustainable agriculture are different in different countries.

Lead authoring unit/office: Statistics Division (ESS)

Defining smallholders to monitor target 2.3. of the 2030 Agenda for Sustainable Development

Year: 2017

Abstract: Despite the central position occupied by smallholder agriculture in the current development debate, a general and operational definition of smallholders still does not exist. The question “what is a small farm?” keeps receiving different answers depending on the context in which is posed. This paper is part of FAO Statistics Working Paper Series.

Lead authoring unit/office: Statistics Division (ESS)

A minimum set of environmental indicators for improving rural statistics

Year: 2016

Abstract: Prepared by the Global Strategy to Improve Agricultural and Rural Statistics (GSARS), this Technical Report provides an overview of the existing frameworks of environmental indicators that focus on the mutual interactions between rural livelihoods and their biophysical environment.

Lead authoring unit/office: Statistics Division (ESS)

Sex-disaggregated data and gender indicators in agriculture. A review of data gaps and good practices

Year: 2016

Abstract: Prepared by the Global Strategy to Improve Agricultural and Rural Statistics (GSARS), this document reviews the literature on the collection of sex-disaggregated data in agricultural surveys and the agricultural modules of national household surveys in preparation for a guidance document for national statistical institutions.

Lead authoring unit/office: Statistics Division (ESS)

Improving the methodology for using administrative data in an agricultural statistic system

Year: 2016

Abstract: Prepared by the Global Strategy to Improve Agricultural and Rural Statistics (GSARS), this technical report aims to find methods to improve the collection, management and use of administrative data for the production of agricultural statistics in developing countries. It includes a country-tested methodology.

Agricultural cost of production. Country field test and desk-study reports

Year: 2016

Abstract: Country field tests form an integral part of research projects under the Global Strategy to Improve Agricultural and Rural Statistics (GSARS). This technical report presents three field tests on agricultural cost of production statistics.

Lead authoring unit/office: Statistics Division (ESS)

Notes on an information system on damage and losses from disasters in agriculture, fisheries and forestry

Year: 2016

Abstract: FAO will launch an initiative for the development of an information system on damage and losses caused by disasters on the sector and its subsectors (crops, livestock, fisheries and forestry) as part of its commitment to enhancing the resilience of agriculture and rural livelihoods. This paper is part of FAO Statistics Working Paper Series.

Lead authoring unit/office: Statistics Division (ESS)

Decent work indicators for agriculture and rural areas. Conceptual issues, data collection challenges and possible areas for improvement

Year: 2015

Abstract: This paper, which is part of FAO Statistics Working Paper Series, aims to achieve three main objectives. First, to assess the relevance of concepts and indicators of Decent Work (DW) for rural areas and employment in agriculture, especially in low-income countries, where coverage, data availability and reliability are particularly problematic. Second, to examine some of the main reasons for the lack of data on DW for rural areas and agriculture, particularly with reference to problems with datacollection, such as: the scarcity of employment-focused surveys; sampling challenges that lead to some categories of the working poor to be missed out or under-represented; questionnaire design issues; challenges in survey implementation from selection to training to supervision of interviewers. Third, the paper proposes a selection of more relevant indicators as well as some ways to improve data collection and their quality to better capture the realities of DW, especially in low-income countries (LICs). In this regard the paper presents options for the integration of DW indicators in existing national agricultural surveys, noting the main practical challenges and possible solutions.

Lead authoring unit/office: Statistics Division (ESS)

Social protection and food security indicators. An inquiry through data from 10 household budget surveys

Year: 2015

Abstract: The aim of this paper, which is part of FAO Statistics Working Paper Series, is to provide empirical evidence on the association between social protection systems and food security conditions in selected developing countries, which will serve as a basis for building a global data set for monitoring and harmonizing indicators on these two thematic areas.

Lead authoring unit/office: Statistics Division (ESS)

Estimating food consumption patterns by reconciling food balance sheets and household budget surveys

Year: 2015

Abstract: This paper, which is part of FAO Statistics Working Paper Series, presents a method to improve the information on food consumption patterns of Food Balance Sheets by using national household budget surveys (HBS).

Lead authoring unit/office: Statistics Division (ESS)

Technical report on the Integrated Survey Framework

Year: 2014

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)

Now-casting regional consumer food inflation

Year: 2014

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)

Selecting a core set of indicators for monitoring global food security. A methodological proposal

Year: 2014

Abstract: This paper, which is part of FAO Statistics Working Paper Series, proposes a methodology to select indicators in multidimensional assessments, such as the ones required for the measurement of food security. By linking the overarching objectives of the evaluation to the nature of the indicators, this methodology is able to discriminate among the hundreds of indicators proposed.

Lead authoring unit/office: Statistics Division (ESS)

Refinements to the FAO methodology for estimating the prevalence of undernourishment indicator

Year: 2014

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)

Advances in hunger measurement: Traditional FAO methods and recent innovations

Year: 2014

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)

Methodological issues in the estimation of the prevalence of undernourishment based on dietary energy consumption data: A review and clarification

Year: 2014

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)

Regional food price inflation transmission

Year: 2014

Abstract: Understanding to what extent and speed agricultural commodity price changes on international markets are transmitted to consumers is key in assessing the vulnerability of households to price shocks. This paper, which is part of FAO Statistics Working Paper Series, provides estimates of the transmission of price changes from international commodity markets to consumers in different regions.

Lead authoring unit/office: Statistics Division (ESS)

Undernourishment and critical food poverty: Indicators at national and sub-national levels

Year: 2009

Abstract: Indicators to measure food poverty and undernourishment are useful for understanding food insecurity at national level and within countries. This paper, which is part of FAO Statistics Working Paper Series, discusses two indicators: proportion of undernourishment, and proportion of critical food poverty. 

Lead authoring unit/office: Statistics Division (ESS)

Monitoring hunger: Indicators at global and subnational levels

Year: 2009

Abstract: This paper, which is part of FAO Statistics Working Paper Series, presents three different hunger indicators and outlines how they can be used to assess the extent of food insecurity in population groups globally and within countries at community, regional, or other subnational levels.

Lead authoring unit/office: Statistics Division (ESS)

The effect of sampling design on the reliability of estimates of the variance of distributions derived from household survey data: A simulation study

Year: 2007

Abstract: On a regular basis, FAO produces estimates of the prevalence of undernourishment and related measures that require estimates of the frequency distribution of household per capita food consumption, expressed in terms of dietary energy (kilocalories). This paper is part of FAO Statistics Working Paper Series.

Lead authoring unit/office: Statistics Division (ESS)

On reliability of estimates of inequality in distributions derived from sample survey data

Year: 2007

Abstract: A non-parametric approach suggested by researchers from the International Food Policy Research Institute (IFPRI) for measuring food deprivation (undernourishment) is not an improvement to the current FAO parametric approach. This paper is part of FAO Statistics Working Paper Series.

Lead authoring unit/office: Statistics Division (ESS)

The FAO parametric versus the IFPRI non-parametric approach to estimating the prevalence of undernourishment: Issues relating to the use of household level data from National Household Surveys

Year: 2007

Abstract: A non-parametric approach suggested by researchers from the International Food Policy Research Institute (IFPRI) for measuring food deprivation (undernourishment) is not an improvement to the current FAO parametric approach. This paper is part of FAO Statistics Working Paper Series.

Lead authoring unit/office: Statistics Division (ESS)

The probability distribution framework for estimating the Prevalence of Undernourishment

Year: 2007

Abstract: In his pioneering study carried in the early 1960’s, Sukhatme had formulated the estimate of the prevalence of undernourishment in a population within a bivariate distribution framework where dietary energy consumption (DEC) and dietary energy requirement (DER) are considered as random variables. This paper is part of FAO Statistics Working Paper Series.

Lead authoring unit/office: Statistics Division (ESS)

Report on food deprivation towards the MDG on hunger reduction

Year: 2006

Abstract: Worldwide developing countries have reduced hunger since the MDG bench-mark period of 1990–1992 to the latest available of 2001–2003. A closer look at the proportion of population insufficient to their needs brings positive news on regional hunger reduction such as in Sub-Saharan Africa and Western Asia. This paper is part of FAO Statistics Working Paper Series.

Lead authoring unit/office: Statistics Division (ESS)

Food deprivation trends: Mid-term review of progress towards the World Food Summit target

Year: 2006

Abstract: Ten years after the World Food Summit (WFS) and less than 10 years before 2015 (the target year for halving the number of undernourished), the hunger situation in the Developing World still remains of great concern. This paper is part of FAO Statistics Working Paper Series.

Lead authoring unit/office: Statistics Division (ESS)

Household food wastage in Turkey

Year: 2006

Abstract: Household Budget Surveys, Household Income and Expenditure Surveys and Food Balance Sheets, provide useful data for epidemiological research and for developing National Food and Nutrition Policies. This paper is part of FAO Statistics Working Paper Series.

Lead authoring unit/office: Statistics Division (ESS)

Measuring hunger at subnational level: The FAO approach applied to household survey data

Year: 2006

Abstract: This manual, which is part of FAO Statistics Working Paper Series, provides a set of guidelines to professionals involved in the estimation of food security statistics, using food consumption data collected in National Household Surveys (NHS).

Lead authoring unit/office: Statistics Division (ESS)

Supplement to the report on the 1990 World Census of Agriculture. International comparison and primary results by country (1986–1995)

Year: 2001

Abstract: This supplement to the Report on the 1990 World Census of Agriculture (WCA) presents the census results collected from the reports issued by the countries that conducted censuses during the 1986-1995 decade and made them available to FAO after mid-1997. It is part of FAO Statistical Development Series.

Lead authoring unit/office: Statistics Division (ESS)

The sixth World Food Survey

Year: 1996

Abstract: While the scope and content of the sixth World Food Survey are broadly similar to its processor, the publication incorporates certain new features. First, China and those countries formerly known as Asian centrally planned economies, which were previously excluded in the traditional estimates. This publication is part of FAO Statistical Development Series.

Lead authoring unit/office: Statistics Division (ESS)

A system of economic accounts for food and agriculture

Year: 1996

Abstract: This revised handbook provides a broader framework to bring together various kinds of databases relating to food and agriculture in an integrated system. The concepts and accounting structure of the system are based on the revised System of National Accounts. This publication is part of FAO Statistical Development Series.

Lead authoring unit/office: Statistics Division (ESS)

Compendium of food consumption statistics from household surveys in developing countries. Volume 2 : Africa, Latin America and Oceania

Year: 1994

Abstract: This first issue of the publication presents data not only from the recent surveys but also, in a number of cases, from some undertaken as far back as the 1970's in order to provide some perspective of the changes over time. 

Lead authoring unit/office: Statistics Division (ESS)

Supplement for Africa: Programme for the 1990 World Census of Agriculture

Year: 1991

Abstract: This supplement provides specific recommendations for countries in Africa for carrying out agricultural censuses. It is part of the Programme for the 1990 World Census of Agriculture. This publication is part of FAO Statistical Development Series.

Lead authoring unit/office: Statistics Division (ESS)

Report on the 1990 World Census of Agriculture. International comparison and primary results by country (1986–1995)

Year: 1990

Abstract: This publication, which is part of FAO Statistical Development Series, provides, in an internationally comparible form, a summary of the data describing the main characteristics of agricultural structures, such as the number and area of holdings, land tenure, agricultural holders and land use.

Lead authoring unit/office: Statistics Division (ESS)

Supplement for Near East: Programme for the 1990 World Census of Agriculture

Year: 1990

Abstract: This supplement provides specific recommendations for countries in the Near East for carrying out agricultural censuses. It is part of the Programme for the 1990 World Census of Agriculture. This publication is part of FAO Statistical Development Series.

Lead authoring unit/office: Statistics Division (ESS)

Supplement for Asia and the Pacific: Programme for the 1990 World Census of Agriculture

Year: 1990

Abstract: This supplement provides specific recommendations for countries in Asia and the Pacific for carrying out agricultural censuses. It is part of the Programme for the 1990 World Census of Agriculture. This publication is part of FAO Statistical Development Series.

Lead authoring unit/office: Statistics Division (ESS)

Sampling methods for agricultural surveys

Year: 1989

Abstract: This publication is intended to assist statisticians in their work in designing agricultural sample surveys. Emphasis is placed on the need to conceptualise data sources within a framework of a national information system which requires standardised concepts. It is part of FAO Statistical Development Series.

Lead authoring unit/office: Statistics Division (ESS)

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Supplement for Europe: Programme for the 1990 World Census of Agriculture

Year: 1989

Abstract: This supplement provides specific recommendations for countries in the European region for carrying out agricultural censuses. It is part of the Programme for the 1990 World Census of Agriculture. This publication is part of FAO Statistical Development Series.

Lead authoring unit/office: Statistics Division (ESS)

Food and agricultural statistics in the context of a national information system

Year: 1986

Abstract: This is the first issue of the FAO Statistical Development Series of manuals. It is aimed to assist countries in planning, developing and operating the statistical component of a national information system for food and agriculture.

Lead authoring unit/office: Statistics Division (ESS)

Assessment and collection of data on pre-harvest food grain losses due to pests and diseases

Year: 1983

Abstract: The manual is intended to serve as a guide to the statistical methodology for assessing and collecting data on pre-harvest foood grain losses due to pests and diseases. It is part of FAO Economic and social development paper series.

Lead authoring unit/office: Statistics Division (ESS)

Use of household surveys for collection of food and agricultural statistics

Year: 1983

Abstract: This manual is part of the contribution of FAO in implementing the NHSCP. It is a guide to the collection of agricultural statistics through households, within the context of the programme. It is part of FAO Economic and social development paper series.

Lead authoring unit/office: Statistics Division (ESS)

Estimation of crop areas and yields in agricultural statistics

Year: 1982

Abstract: As determinants of crop production, statistics on crop areas and yields have been amongst the most important components of he international statistical activities of the Food and Agriculture Organization of the United Nations (FAO) since its inception. This publication is part of FAO Economic and social development paper series.

Lead authoring unit/office: Statistics Division (ESS)

Farm and input prices: Collection and compilation

Year: 1980

Abstract: The main objective of this manual is to assist countries in the improvement of their price statistics including its use in the training of national staff in the collection and compilation of agricultural producer prices. It is part of FAO Statistical Development Series.

Lead authoring unit/office: Statistics Division (ESS)

Assessment and collection of data on post-harvested food grain losses

Year: 1980

Abstract: The manual is intended to serve as a guide to the statistical methodology for assessing and collecting data on post-harvested food grain losses. It is part of FAO Statistical Development Series.

Lead authoring unit/office: Statistics Division (ESS)

Collecting statistics on agricultural population and employment

Year: 1978

Abstract: This guide is intended to assist countries in the planning and execution of programmes for the collection of agricultural population and employment statistics which are a major component of the statistics needed for agraria reform and rural development. It is part of FAO Statistical Development Series.

Lead authoring unit/office: Statistics Division (ESS)

Elearning course "The Degree of Urbanisation"

Year: 2022

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.

Annual land cover production in Google Earth Engine - Workflow in Google Earth Engine to produce an annual land cover map

Year: 2022

Abstract: In 2021, FAO delivered training aimed at building capacity for the use of Earth Observations data and machine learning to produce annual national land cover maps and to extract land cover statistics.

Lead authoring unit/office: Office of Chief Statistician (OCS)

Lesotho Land Cover Database (2017–2021) - A new methodology for annual land cover production based on Sentinel-2

Year: 2022

Abstract: In 2021, FAO delivered training aimed at building capacity for the use of Earth Observations data and machine learning to produce annual national land cover maps and to extract land cover statistics.

Lead authoring unit/office: Office of Chief Statistician (OCS)

Accelerating FAO support on SDG monitoring - Resources available

Year: 2022

Abstract: FAO is committed to scaling up support to countries to ensure that high quality and comparable data for the SDGs are produced and used in support to decision-making and SDG national, regional and global monitoring. The Organization has developed regional roadmaps to ensure that this support is embedded in FAO’s cooperation framework and activities at country level. This document, prepared by FAO’s Office of the Chief Statistician, contains a wealth of relevant information which can support countries in producing, analyzing and using SDG indicators, as well as understanding how they can receive support from FAO.

Lead authoring unit/office: Office of Chief Statistician (OCS)

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Farm data management, sharing and services for agriculture development

Year: 2021

Abstract: This book aims to strengthen the skills of professionals who use, manage data for the benefit of farmers and farmers organizations by exposing them to the topics of importance of data in the agriculture value chain and how new and existing technologies, products and services can leverage farm level and global data to improve yield, reduce loss, add value and increase profitability and resilience.

Lead authoring unit/office: FAO

Lesotho Land Cover (2017–2021) Dashboard. A Google Earth engine dashboard to monitor land cover change and land degradation

Year: 2021

Abstract: In 2021, FAO delivered training aimed at building capacity  for the use of Earth Observations data and machine learning to produce annual national land cover maps and to extract land cover statistics.

Lead authoring unit/office: Office of Chief Statistician (OCS)

E-learning course | System of Environmental-Economic Accounting (SEEA)

Year: 2020

Abstract: This e-learning course provides an overview of the System of Environmental Economic Accounting (SEEA) Central Framework, the statistical standard to measure the relationship between the economy and the environment. The System of Environmental-Economic Accounting 2012—Central Framework is a multipurpose conceptual framework for measuring the interactions between the environment and the economy. By providing an internationally agreed standard with agreed concepts, definitions and classifications, the SEEA is an invaluable tool for compiling integrated statistics on the economy and the environment and deriving coherent and comparable indicators to measure progress towards sustainable development. 

Lead authoring unit/office: United Nations Statistics Division (UNSD)

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E-learning course | SDG Sub-indicator 12.3.1.a – Food loss index

Year: 2020

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

Conducting tablet-based field data collection with Survey Solutions: A Handbook

Year: 2020

Abstract: Prepared by the Asian Development Bank (ADB) and the Food and Agriculture Organization (FAO) of the United Nations, this handbook is designed to help national statistical officers and other interested readers embrace the efficiencies of CAPI-based data collection to supersede the traditional pen and paper interviewing method. We hope that it contributes to the adoption of other innovative tools and technologies that further strengthen national statistical systems.

Lead authoring unit/office: FAO

Conducting Tablet-Based Field Data Collection with CSPro: A Handbook

Year: 2020

Abstract: Prepared by the Asian Development Bank (ADB) and the Food and Agriculture Organization (FAO) of the United Nations, this handbook is designed to help national statistical officers and other interested readers embrace the efficiencies of CAPI-based data collection to supersede the traditional pen and paper interviewing method. We hope that it contributes to the adoption of other innovative tools and technologies that further strengthen national statistical systems.

Lead authoring unit/office: FAO

E-learning course | SDG Indicator 14.4.1 – Fish stocks sustainability

Year: 2019

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

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E-learning course | SDG Indicators 2.3.1 and 2.3.2 - Labour productivity and income of small-scale food producers

Year: 2019

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

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E-learning course | SDG Indicators 2.5.1 and 2.5.2 - Plant and animal genetic resources

Year: 2018

Abstract: This course has been developed to support countries in the analysis and reporting for SDG Indicators 2.5.1 and 2.5.2. These indicators measure the achievement of SDG target 2.5, which focuses on maintaining genetic diversity of seeds, cultivated plants and farmed and domesticated animals and their related wild species. The course illustrates the fundamental concepts upon which the methodology is based.

Lead authoring unit/office: FAO

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E-learning course | SDG Indicator 2.1.1 - Prevalence of Undernourishment (PoU)

Year: 2018

Abstract: This course focuses on SDG Indicator 2.1.1, which is one of two indicators that focus on food insecurity. The PoU is an estimate of the proportion of the population facing serious food deprivation, and is derived from official national level information on food supply and consumption, and energy needs. This course has been developed to support countries in analysis and reporting for Indicator 2.1.1.

Lead authoring unit/office: FAO

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E-learning course | Introduction to Sustainable Development Goal indicators under FAO custodianship

Year: 2018

Abstract: This short e-learning course introduces the process of monitoring progress towards the achievement of the Sustainable Development Goals (SDG). It highlights the role of UN agencies in supporting data collection and analysis, and it presents the SDG indicators under FAO custodianship.

Lead authoring unit/office: FAO

E-learning course | SDG Indicator 2.1.2 - Using the Food Insecurity Experience Scale (FIES)

Year: 2018

Abstract: In the context of reporting on the SDG Indicator 2.1.2, this course introduces the Food Insecurity Experience Scale (FIES) and explains how it can be used to measure food security. The course provides guidance on the collection and analysis of data, and on how the information provided by the FIES can be used to inform and guide policy.

Lead authoring unit/office: FAO

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E-learning course | SDG Indicator 2.a.1 - Agriculture orientation index

Year: 2018

Abstract: This course focuses on SDG Indicator 2.a.1 – Agriculture orientation index for government expenditure. The course illustrates the indicator, its rationale, the methodology and statistical classifications it is based on, and the challenges that countries may face when compiling the data.  

Lead authoring unit/office: FAO

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E-learning course | SDG Indicator 2.c.1 - Food price anomalies

Year: 2018

Abstract: This course is a clear and easy-to-use guide to understand Indicator 2.c.1 (Indicator of food price anomalies) and the methodology to estimate it. It covers basic concepts related to market functioning, prices determination and price volatility and explains how to calculate the indicator and use the online Food Price Monitoring and Analysis (FPMA) tool to interpret indicator results, at national and international level.

Lead authoring unit/office: FAO

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E-learning course | SDG Indicator 5.a.1 - Equal tenure rights for women on agricultural land

Year: 2018

Abstract: This course focuses on SDG Indicator 5.a.1, which is one of two indicators that focus on women’s ownership and/or control over agricultural land. As this is a statistical based indicator, after introducing its key concepts, definitions and rationale, the course offers detailed guidance both on data collection and manipulation, and computation of the various sub-indicators.

Lead authoring unit/office: FAO

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E-learning course | SDG Indicator 5.a.2 - Ensuring women’s legal rights to land ownership and/or control

Year: 2018

Abstract: This course focuses on SDG Indicator 5.a.2 which assesses women’s equal rights to land ownership and/or control. The course describes the indicator, explains its rationale and provides countries with step-by-step guidance for conducting the assessment.

Lead authoring unit/office: FAO

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E-learning course | SDG Indicator 14.b.1 - Securing sustainable small-scale fisheries

Year: 2017

Abstract: This course has been designed to support countries in their data collection, analysis and reporting of SDG Indicator 14.b.1 - Securing sustainable small-scale fisheries: "Progress by countries in the degree of application of a legal/regulatory/policy/institutional framework which recognizes and protects access rights for small-scale fisheries".

Lead authoring unit/office: FAO

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Training course on food balance sheets - Users' guide

Year: 2017

Abstract: Prepared by the Global Strategy to improve agricultural and rural statistics, this training material on the revised Food Balance Sheet (FBS) methodology targets managers and technical staff of national statistical offices, ministries of agriculture and other institutions (in particular, those dealing with food safety issues) in charge of or involved in the compilation of supply and use tables and FBS. The training material can also be used to train trainers and experts involved in the delivery of capacity-building activities on the compilation of SUA and FBS using the revised methodology and newly developed tool and to introduce the concept and methodology of FBS to students of agricultural statistics and statisticians/data analysts not specialized in agricultural or food security statistics.

Lead authoring unit/office: Statistics Division (ESS)

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Training course on food balance sheets - Introduction

Year: 2017

Abstract: Prepared by the Global Strategy to improve agricultural and rural statistics, this training material on the revised Food Balance Sheet (FBS) methodology targets managers and technical staff of national statistical offices, ministries of agriculture and other institutions (in particular, those dealing with food safety issues) in charge of or involved in the compilation of supply and use tables and FBS. At the end of this session, the audience will: a) Know the historical background of the FBS framework; b) Understand the basic SUA/FBS equation; c) Be informed about some of the potential uses of FBS; d) Be aware of the major caution on FBS interpretation and of the fundamental principles of FBS construction.  

Lead authoring unit/office: Statistics Division (ESS)

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Training course on food balance sheets - Methodological principles for the construction of country-level FBS

Year: 2017

Abstract: Prepared by the Global Strategy to improve agricultural and rural statistics, this training material on the revised Food Balance Sheet (FBS) methodology targets managers and technical staff of national statistical offices, ministries of agriculture and other institutions (in particular, those dealing with food safety issues) in charge of or involved in the compilation of supply and use tables and FBS. At the end of this session, the audience will: a) Know all the relevant concepts involved in compiling FBS; b) Be able to understand the difference between supply utilization accounts (SUA) and Food Balance Sheets (FBS); c) Understand how commodity trees link SUA back to the primary commodity equivalent-level FBS; d) Know the recommended balancing mechanism and their alternatives. Outline of this module: 1. Basic identity and approach; 2. Definitions of FBS components; 3. Additional variables; 4. Supply Utilization Accounts (SUAs) and link with FBS; 5. Balancing mechanisms.

Lead authoring unit/office: Statistics Division (ESS)

Training course on food balance sheets - Involvement of FAO Statistics Division (ESS) in the Food Security and SDGs Framework

Year: 2017

Abstract: Prepared by the Global Strategy to improve agricultural and rural statistics, this training material on the revised Food Balance Sheet (FBS) methodology targets managers and technical staff of national statistical offices, ministries of agriculture and other institutions (in particular, those dealing with food safety issues) in charge of or involved in the compilation of supply and use tables and FBS. At the end of this session, the audience will: a) Know all the relevant concepts involved in compiling FBS; b) Be able to understand the difference between supply utilization accounts (SUA) and Food Balance Sheets (FBS); c) Understand how commodity trees link SUA back to the primary commodity equivalent-level FBS; d) Know the recommended balancing mechanism and their alternatives. Outline of the session: 1.Overall view of the SUA/FBS; 2.Contribution to SDGs; 3.The FBS as a snapshot tool beyond just the food component.  

Lead authoring unit/office: Statistics Division (ESS)

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Training course on food balance sheets - Food balance sheets and household surveys

Year: 2017

Abstract: Prepared by the Global Strategy to improve agricultural and rural statistics, this training material on the revised Food Balance Sheet (FBS) methodology targets managers and technical staff of national statistical offices, ministries of agriculture and other institutions (in particular, those dealing with food safety issues) in charge of or involved in the compilation of supply and use tables and FBS. At the end of this session, the audience will: a) Know what FBS and HH surveys are; b) Understandi the differences between FBS and HH surveys; c) Know how FBS and HH surveys can complement each others. Outline of this module: 1. FBS and HH surveys: main differences; 2. Annual production questionnaire example; 3. Household survey example.

Lead authoring unit/office: Statistics Division (ESS)

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Training course on food balance sheets - FBS component: additional parameters

Year: 2017

Abstract: Prepared by the Global Strategy to improve agricultural and rural statistics, this training material on the revised Food Balance Sheet (FBS) methodology targets managers and technical staff of national statistical offices, ministries of agriculture and other institutions (in particular, those dealing with food safety issues) in charge of or involved in the compilation of supply and use tables and FBS. At the end of this session, the participants will know: a) What additional parameters are; b) What’s the rationale behind the best option among different sources; c) What FAO recommendations are; and d) International recognized standards. Outline of this module: 1. Population Estimates; 2. Nutrient Estimates; 3. Extraction Rates; 4. Processing shares.

Lead authoring unit/office: Statistics Division (ESS)

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Training course on food balance sheets - FBS component: residual or other uses

Year: 2017

Abstract: Prepared by the Global Strategy to improve agricultural and rural statistics, this training material on the revised Food Balance Sheet (FBS) methodology targets managers and technical staff of national statistical offices, ministries of agriculture and other institutions (in particular, those dealing with food safety issues) in charge of or involved in the compilation of supply and use tables and FBS. The training material can also be used to train trainers and experts involved in the delivery of capacity-building activities on the compilation of SUA and FBS using the revised methodology and newly developed tool and to introduce the concept and methodology of FBS to students of agricultural statistics and statisticians/data analysts not specialized in agricultural or food security statistics. Outline of this module: Residuals or other uses - definition, purpose and use.  

Lead authoring unit/office: Statistics Division (ESS)

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Training course on food balance sheets - FBS component: Industrial Use

Year: 2017

Abstract: Prepared by the Global Strategy to improve agricultural and rural statistics, this training material on the revised Food Balance Sheet (FBS) methodology targets managers and technical staff of national statistical offices, ministries of agriculture and other institutions (in particular, those dealing with food safety issues) in charge of or involved in the compilation of supply and use tables and FBS. The training material can also be used to train trainers and experts involved in the delivery of capacity-building activities on the compilation of SUA and FBS using the revised methodology and newly developed tool and to introduce the concept and methodology of FBS to students of agricultural statistics and statisticians/data analysts not specialized in agricultural or food security statistics. Outline of this module: 1. Data sources; 2. Imputation and Estimation.

Lead authoring unit/office: Statistics Division (ESS)

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Training course on food balance sheets - FBS-component: Loss

Year: 2017

Abstract: Prepared by the Global Strategy to improve agricultural and rural statistics, this training material on the revised Food Balance Sheet (FBS) methodology targets managers and technical staff of national statistical offices, ministries of agriculture and other institutions (in particular, those dealing with food safety issues) in charge of or involved in the compilation of supply and use tables and FBS. The training material can also be used to train trainers and experts involved in the delivery of capacity-building activities on the compilation of SUA and FBS using the revised methodology and newly developed tool and to introduce the concept and methodology of FBS to students of agricultural statistics and statisticians/data analysts not specialized in agricultural or food security statistics. Outline of this module: 1. Concept of Loss in the FBS setting; 2. Data sources: 2.1 Official data sources 2.2 Alternative data sources; 3. Imputation and Estimation 3.1 Recommended Approach 3.2 Alternative Approach.  

Lead authoring unit/office: Statistics Division (ESS)

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Training course on food balance sheets - FBS component: Tourist food

Year: 2017

Abstract: Prepared by the Global Strategy to improve agricultural and rural statistics, this training material on the revised Food Balance Sheet (FBS) methodology targets managers and technical staff of national statistical offices, ministries of agriculture and other institutions (in particular, those dealing with food safety issues) in charge of or involved in the compilation of supply and use tables and FBS. The training material can also be used to train trainers and experts involved in the delivery of capacity-building activities on the compilation of SUA and FBS using the revised methodology and newly developed tool and to introduce the concept and methodology of FBS to students of agricultural statistics and statisticians/data analysts not specialized in agricultural or food security statistics. Outline of this module: 1. Introduction (Concepts and Definitions); 2. Data sources 3. Imputation and Estimation.  

Lead authoring unit/office: Statistics Division (ESS)

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Training course on food balance sheets - FBS component: feed

Year: 2017

Abstract: Prepared by the Global Strategy to improve agricultural and rural statistics, this training material on the revised Food Balance Sheet (FBS) methodology targets managers and technical staff of national statistical offices, ministries of agriculture and other institutions (in particular, those dealing with food safety issues) in charge of or involved in the compilation of supply and use tables and FBS. The training material can also be used to train trainers and experts involved in the delivery of capacity-building activities on the compilation of SUA and FBS using the revised methodology and newly developed tool and to introduce the concept and methodology of FBS to students of agricultural statistics and statisticians/data analysts not specialized in agricultural or food security statistics. Outline of this module: 1. Definitions; 2. Data sources; 3. Imputation and Estimation.

Lead authoring unit/office: Statistics Division (ESS)

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Training course on food balance sheets - FBS component: Seed

Year: 2017

Abstract: Prepared by the Global Strategy to improve agricultural and rural statistics, this training material on the revised Food Balance Sheet (FBS) methodology targets managers and technical staff of national statistical offices, ministries of agriculture and other institutions (in particular, those dealing with food safety issues) in charge of or involved in the compilation of supply and use tables and FBS. The training material can also be used to train trainers and experts involved in the delivery of capacity-building activities on the compilation of SUA and FBS using the revised methodology and newly developed tool and to introduce the concept and methodology of FBS to students of agricultural statistics and statisticians/data analysts not specialized in agricultural or food security statistics. Outline of this module: 1. Introduction (Concepts and Definitions); 2. Data sources; 3. Imputation and Estimation.  

Lead authoring unit/office: Statistics Division (ESS)

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Training course on food balance sheets - Food availability

Year: 2017

Abstract: Prepared by the Global Strategy to improve agricultural and rural statistics, this training material on the revised Food Balance Sheet (FBS) methodology targets managers and technical staff of national statistical offices, ministries of agriculture and other institutions (in particular, those dealing with food safety issues) in charge of or involved in the compilation of supply and use tables and FBS. The training material can also be used to train trainers and experts involved in the delivery of capacity-building activities on the compilation of SUA and FBS using the revised methodology and newly developed tool and to introduce the concept and methodology of FBS to students of agricultural statistics and statisticians/data analysts not specialized in agricultural or food security statistics. Outline of this module: 1. Concept of “Food Availability” in the FBS setting; 2. Data sources: a. Official data sources b. Alternative data sources; 3. Imputation and Estimation a. Recommended Approach b. Alternative Approach.

Lead authoring unit/office: Statistics Division (ESS)

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Training course on food balance sheets - FBS component: Food processing

Year: 2017

Abstract: Prepared by the Global Strategy to improve agricultural and rural statistics, this training material on the revised Food Balance Sheet (FBS) methodology targets managers and technical staff of national statistical offices, ministries of agriculture and other institutions (in particular, those dealing with food safety issues) in charge of or involved in the compilation of supply and use tables and FBS. The training material can also be used to train trainers and experts involved in the delivery of capacity-building activities on the compilation of SUA and FBS using the revised methodology and newly developed tool and to introduce the concept and methodology of FBS to students of agricultural statistics and statisticians/data analysts not specialized in agricultural or food security statistics. Outline of this module: 1. Data sources; 2. Imputation and estimation.

Lead authoring unit/office: Statistics Division (ESS)

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Training course on food balance sheets - FBS component: Stocks and stock changes

Year: 2017

Abstract: Prepared by the Global Strategy to improve agricultural and rural statistics, this training material on the revised Food Balance Sheet (FBS) methodology targets managers and technical staff of national statistical offices, ministries of agriculture and other institutions (in particular, those dealing with food safety issues) in charge of or involved in the compilation of supply and use tables and FBS. The training material can also be used to train trainers and experts involved in the delivery of capacity-building activities on the compilation of SUA and FBS using the revised methodology and newly developed tool and to introduce the concept and methodology of FBS to students of agricultural statistics and statisticians/data analysts not specialized in agricultural or food security statistics. Outline of this module: 1. Definitions; 2. Data sources; 3. Imputation and Estimation.

Lead authoring unit/office: Statistics Division (ESS)

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Training course on food balance sheets - Trade: import and export

Year: 2017

Abstract: Prepared by the Global Strategy to improve agricultural and rural statistics, this training material on the revised Food Balance Sheet (FBS) methodology targets managers and technical staff of national statistical offices, ministries of agriculture and other institutions (in particular, those dealing with food safety issues) in charge of or involved in the compilation of supply and use tables and FBS. The training material can also be used to train trainers and experts involved in the delivery of capacity-building activities on the compilation of SUA and FBS using the revised methodology and newly developed tool and to introduce the concept and methodology of FBS to students of agricultural statistics and statisticians/data analysts not specialized in agricultural or food security statistics. Outline of this module: 1. Main features of trade data; 2. Official data sources; 3. Importance of accurate data; 4. Alternative data sources; 5. Imputation and estimation.

Lead authoring unit/office: Statistics Division (ESS)

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Training course on food balance sheets - FBS component: Production

Year: 2017

Abstract: Prepared by the Global Strategy to improve agricultural and rural statistics, this training material on the revised Food Balance Sheet (FBS) methodology targets managers and technical staff of national statistical offices, ministries of agriculture and other institutions (in particular, those dealing with food safety issues) in charge of or involved in the compilation of supply and use tables and FBS. The training material can also be used to train trainers and experts involved in the delivery of capacity-building activities on the compilation of SUA and FBS using the revised methodology and newly developed tool and to introduce the concept and methodology of FBS to students of agricultural statistics and statisticians/data analysts not specialized in agricultural or food security statistics. Outline of this module: 1. Agricultural production domain; 2. Production data sources; 3. Imputation and estimation.  

Lead authoring unit/office: Statistics Division (ESS)

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Short training course on agricultural cost of production statistics - Users’ guide

Year: 2017

Abstract: The overall objective of the training on AgCoP is to strengthen the technical capacity of statistical producers (statistical offices and other institutions) to apply relevant methods and standards in the compilation of agricultural cost of production statistics. This users’ guide describes the intended objectives, content and target audience of this training material. It provides recommendations on organizational aspects related to the organization of training on AgCoP. Examples of course content and possible agenda are provided in an appendix.

Lead authoring unit/office: Statistics Division (ESS)

Short training course on agricultural cost of production statistics - Main concepts

Year: 2017

Abstract: Prepared by the Global Strategy to Improve Agricultural and Rural Statistics (GSARS), this training material on the estimation of CoP targets statisticians, analysts and data producers from the National Statistical System (NSOs or statistical departments within the Ministry of Agriculture, for example) as well as from other public or private institutions that are either producers or users of information on CoP. This training module covers the main concepts of agricultural cost of production statistics.

Lead authoring unit/office: Statistics Division (ESS)

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Short training course on agricultural cost of production statistics - Uses and users

Year: 2017

Abstract: Prepared by the Global Strategy to Improve Agricultural and Rural Statistics (GSARS), this training material on the estimation of CoP targets statisticians, analysts and data producers from the National Statistical System (NSOs or statistical departments within the Ministry of Agriculture, for example) as well as from other public or private institutions that are either producers or users of information on CoP. This training module covers the uses and users of costs of production statistics: farmers and agricultural markets, system of national accounts, research, government and policy makers.

Lead authoring unit/office: Statistics Division (ESS)

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Short training course on agricultural cost of production statistics - Data collection

Year: 2017

Abstract: Prepared by the Global Strategy to Improve Agricultural and Rural Statistics (GSARS), this training material on the estimation of CoP targets statisticians, analysts and data producers from the National Statistical System (NSOs or statistical departments within the Ministry of Agriculture, for example) as well as from other public or private institutions that are either producers or users of information on CoP. This training module covers the data collection methods: surveys, censuses, typical farm approaches, identifying the advantages and limitations of each approach.

Lead authoring unit/office: Statistics Division (ESS)

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Short training course on agricultural cost of production statistics - Typical farms and hybrid approaches

Year: 2017

Abstract: Prepared by the Global Strategy to Improve Agricultural and Rural Statistics (GSARS), this training material on the estimation of CoP targets statisticians, analysts and data producers from the National Statistical System (NSOs or statistical departments within the Ministry of Agriculture, for example) as well as from other public or private institutions that are either producers or users of information on CoP. This training module covers the typical farms and hybrid approaches.

Lead authoring unit/office: Statistics Division (ESS)

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Short training course on agricultural cost of production statistics - Sample design strategies

Year: 2017

Abstract: Prepared by the Global Strategy to Improve Agricultural and Rural Statistics (GSARS), this training material on the estimation of CoP targets statisticians, analysts and data producers from the National Statistical System (NSOs or statistical departments within the Ministry of Agriculture, for example) as well as from other public or private institutions that are either producers or users of information on CoP. This training module covers the sample design strategies.

Lead authoring unit/office: Statistics Division (ESS)

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Short training course on agricultural cost of production statistics - Cash costs

Year: 2017

Abstract: Prepared by the Global Strategy to Improve Agricultural and Rural Statistics (GSARS), this training material on the estimation of CoP targets statisticians, analysts and data producers from the National Statistical System (NSOs or statistical departments within the Ministry of Agriculture, for example) as well as from other public or private institutions that are either producers or users of information on CoP. This training module covers cash costs.

Lead authoring unit/office: Statistics Division (ESS)

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Short training course on agricultural cost of production statistics - Labour costs

Year: 2017

Abstract: Prepared by the Global Strategy to Improve Agricultural and Rural Statistics (GSARS), this training material on the estimation of CoP targets statisticians, analysts and data producers from the National Statistical System (NSOs or statistical departments within the Ministry of Agriculture, for example) as well as from other public or private institutions that are either producers or users of information on CoP. This training module covers the estimation of costs of paid and unpaid labour. 

Lead authoring unit/office: Statistics Division (ESS)

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Short training course on agricultural cost of production statistics - Land costs

Year: 2017

Abstract: Prepared by the Global Strategy to Improve Agricultural and Rural Statistics (GSARS), this training material on the estimation of CoP targets statisticians, analysts and data producers from the National Statistical System (NSOs or statistical departments within the Ministry of Agriculture, for example) as well as from other public or private institutions that are either producers or users of information on CoP. This training module covers land costs. 

Lead authoring unit/office: Statistics Division (ESS)

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Short training course on agricultural cost of production statistics - Capital costs

Year: 2017

Abstract: Prepared by the Global Strategy to Improve Agricultural and Rural Statistics (GSARS), this training material on the estimation of CoP targets statisticians, analysts and data producers from the National Statistical System (NSOs or statistical departments within the Ministry of Agriculture, for example) as well as from other public or private institutions that are either producers or users of information on CoP. This training module covers the different types of capital goods in agriculture and the estimation of capital costs.

Lead authoring unit/office: Statistics Division (ESS)

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Short training course on agricultural cost of production statistics - Allocation

Year: 2017

Abstract: Prepared by the Global Strategy to Improve Agricultural and Rural Statistics (GSARS), this training material on the estimation of CoP targets statisticians, analysts and data producers from the National Statistical System (NSOs or statistical departments within the Ministry of Agriculture, for example) as well as from other public or private institutions that are either producers or users of information on CoP. This training module covers the allocation of costs in complex cropping and mixed farming systems.

Lead authoring unit/office: Statistics Division (ESS)

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Short training course on agricultural cost of production statistics - Allocation modelling

Year: 2017

Abstract: Prepared by the Global Strategy to Improve Agricultural and Rural Statistics (GSARS), this training material on the estimation of CoP targets statisticians, analysts and data producers from the National Statistical System (NSOs or statistical departments within the Ministry of Agriculture, for example) as well as from other public or private institutions that are either producers or users of information on CoP. This training module covers the modeling approaches for the allocation of costs.

Lead authoring unit/office: Statistics Division (ESS)

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Short training course on agricultural cost of production statistics - Pre-production costs

Year: 2017

Abstract: Prepared by the Global Strategy to Improve Agricultural and Rural Statistics (GSARS), this training material on the estimation of CoP targets statisticians, analysts and data producers from the National Statistical System (NSOs or statistical departments within the Ministry of Agriculture, for example) as well as from other public or private institutions that are either producers or users of information on CoP. This training module covers the allocation of pre-production costs in multi-year enterprises.

Lead authoring unit/office: Statistics Division (ESS)

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Short training course on agricultural cost of production statistics - Dairy cattle

Year: 2017

Abstract: Prepared by the Global Strategy to Improve Agricultural and Rural Statistics (GSARS), this training material on the estimation of CoP targets statisticians, analysts and data producers from the National Statistical System (NSOs or statistical departments within the Ministry of Agriculture, for example) as well as from other public or private institutions that are either producers or users of information on CoP. This training module covers the determination of costs and revenues for dairy cattle.

Lead authoring unit/office: Statistics Division (ESS)

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Short training course on agricultural cost of production statistics - Uncertainty

Year: 2017

Abstract: Prepared by the Global Strategy to Improve Agricultural and Rural Statistics (GSARS), this training material on the estimation of CoP targets statisticians, analysts and data producers from the National Statistical System (NSOs or statistical departments within the Ministry of Agriculture, for example) as well as from other public or private institutions that are either producers or users of information on CoP. This training module covers the treatment of uncertainty in the results.

Lead authoring unit/office: Statistics Division (ESS)

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Short training course on agricultural cost of production statistics - Data dissemination

Year: 2017

Abstract: Prepared by the Global Strategy to Improve Agricultural and Rural Statistics (GSARS), this training material on the estimation of CoP targets statisticians, analysts and data producers from the National Statistical System (NSOs or statistical departments within the Ministry of Agriculture, for example) as well as from other public or private institutions that are either producers or users of information on CoP. This training module covers data dissemination.

Lead authoring unit/office: Statistics Division (ESS)

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E-learning course | Linking population and housing censuses with agricultural censuses

Year: 2015

Abstract: The aim of this course is to provide practical guidance for implementing a cost-effective census strategy by coordinating the population and housing census with the agricultural census.

Lead authoring unit/office: Statistics Division (ESS)

E-learning course | Food composition data

Year: 2013

Abstract: This course explains the importance of food composition tables and databases, food description (selection and nomenclature), food components (analysis, calculation, conversion and units), covers the aspects of quality and food biodiversity, as well as compilation principles. The course is designed to be primarily used in universities, as it is important that future generations of nutritionists, food scientists, dieticians, chemists analysing food components, food composition data compilers, health professionals and agronomists appreciate food composition data and use them adequately in their respective fields to improve data quality, availability and usage worldwide. It can also be used by self-learners interested in food composition, or in conjunction with food composition courses, or within institutes for capacity development in food composition.  (Released in: September 2013. 10 h of learning).

Lead authoring unit/office: FAO

E-learning course | Management of spatial information

Year: 2012

Abstract: This course covers the techniques for spatial data acquisition, spatial analysis, modelling, integration of various data sources and sharing spatial information (international standards and interoperability, spatial data infrastructure).

Lead authoring unit/office: FAO

​Shiny RIMA Guidelines

Year: 2022

Abstract: At the heart of this product is the introduction of Shiny RIMA and its advantages as a tool for the monitoring and measurement of resilience. Particularly, this guidance note focuses on today’s relevance of the resilience index measurement and analysis (RIMA), adopted by FAO in 2008, and how Shiny RIMA facilitates resilience analysis. For policymakers and especially for households in risk-prone environments, evaluating resilience and changes over time is deeply meaningful. This document, therefore, aims at shedding light on the improvements that Shiny RIMA can bring to resilience analysis.

Lead authoring unit/office: FAO

Guidelines on improving and using administrative data in agricultural statistics

Year: 2018

Abstract: Developed by the Global Strategy to Improve Agricultural and Rural Statistics (GSARS), the ultimate goal of this document is to provide operational guidance to developing countries on how to set up an effective Administrative Data System for Agricultural Statistics (ADSAS), as well as on the improvement, use and integration of administrative data in the national statistical system. The concept of ADSAS refers to the set of all administrative institutions producing administrative agricultural data that may be used for the purposes of agricultural statistics and providing them to the national institution in charge of agricultural statistics for official use and publication.

Lead authoring unit/office: Statistics Division (ESS)

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AGRIS Handbook on the Agricultural Integrated Survey

Year: 2018

Abstract: Developed by the Global Strategy to Improve Agricultural and Rural Statistics (GSARS), the AGRIS handbook presents the rationale of the system, focusing on the new needs and challenges in surveying farms in the 21st century. In this handbook, the link with SDGs is acknowledged, as the proposed AGRIS Generic Questionnaires will generate basic data for monitoring directly four SDG indicators and provide essential information for another 15 SDG indicators.

Lead authoring unit/office: Statistics Division (ESS)

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Guidelines on methods for estimating livestock production and productivity

Year: 2018

Abstract: Given the importance of the livestock sector’s contribution to the reduction of poverty and improvement of global human health, the Global Strategy has implemented a line of research on Improving methods for estimating livestock production and productivity, one of the key priorities of the Research Program. These Guidelines overlap to some extent with the final technical report on Improving methods for estimating livestock production and productivity, produced by the University of New England (UNE), Australia. In addition to the findings presented in the technical reports of the research line, further additional operational inputs from relevant literature were also used to develop these Guidelines. These Guidelines are intended to be a reference document providing country statisticians with technical and operational guidance on various aspects of livestock production and productivity statistics, in a broad range of country conditions, with particular attention being paid to developing countries. This document addresses an important gap, given that the most recent FAO publication on the subject dates back to 1992 (FAO, 1992).

Lead authoring unit/office: Statistics Division (ESS)

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Guidelines on the measurement of harvest and post-harvest losses Recommendations on the design of a harvest and post-harvest loss statistics system for food grains (cereals and pulses)

Year: 2018

Abstract: These Guidelines are the result of a research project undertaken within the Global Strategy to improve Agricultural and Rural Statistics (GSARS), a statistical capacity-building initiative whose Global Office is hosted by the Statistics Division of FAO. The Guidelines build upon methodologies presented in other papers, technical reports and manuals published by FAO and other organizations. They provide recent findings on the measurement of harvest and post-harvest losses in developing countries.

Lead authoring unit/office: Statistics Division (ESS)

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Guidelines for the measurement of productivity and efficiency in agriculture

Year: 2018

Abstract: These Guidelines are the result of a research project undertaken within the Global Strategy to improve Agricultural and Rural Statistics (GSARS), a statistical capacity-building initiative whose Global Office is hosted by the Statistics Division of Food and Agriculture Organization of United Nations (FAO). The Guidelines build upon methodologies presented in papers, technical reports and manuals published by FAO and other organizations. They also build on the findings of technical assistance activities conducted in developing countries, especially in sub-Saharan Africa, where data collection tools have been designed and tested. These Guidelines provide recommendations on the measurement of agricultural productivity, with an emphasis on developing countries.

Lead authoring unit/office: Statistics Division (ESS)

Handbook on crop statistics: improving methods for measuring crop area, production and yield

Year: 2018

Abstract: Prepared by the Global Strategy to Improve Agricultural and Rural Statistics (GSARS), this Handbook aims to serve as a guide for statisticians from National Statistical Services seeking to improve their data collection methods to produce crop statistics, and to become the new reference document for estimating crop area, yield and production.

Lead authoring unit/office: Statistics Division (ESS)

Master sampling frames for agriculture. Supplement on selected country experiences

Year: 2018

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)

World Programme for the Census of Agriculture 2020. Volume 2. Operational guidelines

Year: 2018

Abstract: Volume 2 is a revised and updated edition of “Conducting Agricultural Censuses and Surveys”, published by FAO in 1996. The revision is opportune not only in view of the recent publication of the new census programme and methodology but also in view of the substantial changes witnessed in the census technological environment over the last two decades. The availability of digital, mobile and more affordable tools for data capture, geo-positioning, remote sensing imaging, digital archiving and online dissemination have provided new cost-effective alternatives to traditional ways of conducting the agricultural census. This publication is part of FAO Statistical Development Series.

Lead authoring unit/office: Statistics Division (ESS)

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Guidelines for designing and implementing grain stock surveys

Year: 2017

Abstract: These guidelines are intended for statisticians and managers in national statistics offices wanting to develop or improve survey programmes for the direct measurement of grain and other food stocks. They provide guidance and tools for direct measurement of food stocks, discuss current and best practices for stock estimation through sample surveys, reflect on conceptual, technical, human and budgetary issues related to stock surveys and provide examples and tools for countries wishing to develop their stock survey programmes.

Lead authoring unit/office: Statistics Division (ESS)

Guidelines for the enumeration of nomadic and semi-nomadic (transhumant) livestock

Year: 2016

Abstract: Developed by the Global Strategy to Improve Agricultural and Rural Statistics (GSARS), these Guidelines are intended to be a reference document providing technical and operational guidance on various aspects of the Enumeration of Nomadic and Semi-Nomadic (Transhumant) Livestock in various country conditions, with particular attention being paid to developing countries. It will address an important gap, because the most recent FAO publication on the subject dates back to 1992.

Lead authoring unit/office: Statistics Division (ESS)

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Guidelines on international classifications for agricultural statistics

Year: 2015

Abstract: These Guidelines were developed within the framework of the Global Strategy to Improve Agricultural and Rural Statistics. The publication aims to support countries’ capacity development and to facilitate their participation in the international governance mechanisms of standards and classifications, thus ensuring the sustainability of agricultural statistics worldwide. The Guidelines bring together comprehensive information on statistical classifications, in particular those used for agricultural statistics, and provide a convenient reference framework for the application of international standards at national level. The Guidelines were drafted following a capacity development approach, and have been conceived as a practical tool that would be easy to apply. Some best practices and experiences from countries and regions are also presented in the Annex to this publication.

Lead authoring unit/office: Statistics Division (ESS)

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Handbook on master sampling frames for agricultural statistics. Frame development, sample design and estimation

Year: 2015

Abstract: This Handbook on Master Sampling Frames for Agriculture has been prepared within the framework of the Global Strategy to Improve Agricultural and Rural Statistics (Global Strategy). The Global Strategy is an initiative endorsed in 2010 by the United Nations Statistical Commission. It provides a framework and a blueprint to meet current and emerging data requirements and the needs of policymakers and other data users. Its goal is to contribute to greater food security, reduced food price volatility, higher incomes and greater well-being for rural populations, through evidence-based policies. The Global Strategy is centred upon 3 pillars: (1) establishing a minimum set of core data (2) integrating agriculture into National Statistical Systems (NSSs) and (3) fostering the sustainability of the statistical system through governance and statistical capacity building.

Lead authoring unit/office: Statistics Division (ESS)

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World Programme for the Census of Agriculture 2020. Volume I: Programme, concepts and definitions

Year: 2015

Abstract: This publication, which is part of FAO Statistical Development Series, provides guidance on agricultural censuses carried out by countries in the period between 2016 and 2025. The World Census of Agriculture (WCA) 2020 will ensure that data collected are comparable at the international level while also addressing emerging information needs of the 21st century.

Lead authoring unit/office: Statistics Division (ESS)

World Programme for the Census of Agriculture 2020. Volume 2: Census web-resources of the operational guidelines

Year: 2015

Abstract: This page contains the Web-based resources cited in the WCA Operational Guidelines (Volume 2) ordered by chapter and paragraph. These resources include relevant specialized methodological publications and actual country examples. They intend to illustrate or provide more guidance on certain implementation aspects of agricultural census as well as to learn from experience on how to overcome practical issues.

Lead authoring unit/office: Statistics Division (ESS)

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Guidelines for assessing country capacity to produce agricultural and rural statistics (2014)

Year: 2014

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)

SPARS - Strategic plan for agriculture and rural statistics

Year: 2014

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)

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Providing access to agriculture microdata: A guide

Year: 2014

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)

2000 World Census of Agriculture. Methodological review (1996–2005)

Year: 2013

Abstract: This publication, which is part of FAO Statistical Development Series, is a methodological review of the agricultural censuses conducted within the framework of the Programme for the World Census of Agriculture 2000. It covers methodological aspects like enumeration methods and techniques, census frames, geographical and holding type coverage, census scope, etc.

Lead authoring unit/office: Statistics Division (ESS)

Guidelines for linking population and housing censuses with agricultural censuses with selected country practices

Year: 2012

Abstract: This publication, which is part of FAO Statistical Development Series, aims to provide practical guidance for population and housing census and agricultural census planners looking to implement a cost-effective census strategy by coordinating the population and housing census with the agricultural census.

Lead authoring unit/office: Statistics Division (ESS)

World Programme for the Census of Agriculture 2010. Volume 1: A system of integrated agricultural censuses and surveys

Year: 2005

Abstract: This publication, which is part of FAO Statistical Development Series, presents guidelines for the 2010 round of agricultural censuses, covering agricultural censuses to be undertaken between 2006 and 2015. For this round, a new approach is being used, with the emphasis on conducting agricultural censuses within the framework of the system of integrated agricultural censuses and surveys and in the broader context of the national statistics system. 

Lead authoring unit/office: Statistics Division (ESS)

Guidelines on employment: supplement to the programme for the world census of agriculture 2000

Year: 2002

Abstract: This publication, which is part of FAO Statistical Development Series, is a supplement to the definitions, concepts and standards presented in the Programme for the World Census of Agriculture 2000. It is intended to help countries generate databases that are internationally comparable.

Lead authoring unit/office: Statistics Division (ESS)

Conducting agricultural censuses and surveys

Year: 1996

Abstract: This publication is a revised and updated edition of Taking Agricultural Censuses (FAO, 1978). It complements the Programme for the World Census of Agriculture 2000 and provides practical information on the steps involved in actually conducting an agricultural census. It is part of FAO Statistical Development Series.

Lead authoring unit/office: Statistics Division (ESS)

Programme for the World Census of Agriculture 2000

Year: 1995

Abstract: The Programme for the World Census of Agriculture 2000 is intended to assist countries by providing definitions, concepts, standards and guidelines for censuses in the decade 1996-2005 in order to generate a data base of internationally comparable figures. It is part of FAO Statistical Development Series.

Lead authoring unit/office: Statistics Division (ESS)

Microcomputer-based data processing: 1990 World Census of Agriculture

Year: 1987

Abstract: This book provides guidance on processing the census of agriculture data in an effecient and cost-efficient way. It is part of FAO Statistical Development Series.

Lead authoring unit/office: Statistics Division (ESS)

Programme for the 1990 World Census of Agriculture

Year: 1986

Abstract: This publication provides information about the 1990 World Census of Agriculture. It is aimed to assist countries in planning, developing and operating the statistical component of a national information system for food and agriculture. It is part of FAO Statistical Development Series.

Lead authoring unit/office: Statistics Division (ESS)

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Methods for estimating greenhouse gas emissions from food systems Part VI: fluorinated gas emissions FAO Statistics Working Paper Series / 23-35

Year: 2023

Abstract: This paper is part of a series detailing new methodologies for estimating key components of agrifood systems emissions, with a view to disseminate the information in FAOSTAT. It describes methods for estimating greenhouse gas (GHG) emissions from the agrifood system, and in particular fluorinated gases (F-gases) from refrigeration systems in the food system cold chain, from food processing to food transport, retailing and household consumption processes. Based on the proposed methodology, we build a new database of GHG from F-gases used in the agrifood system, by country and with global coverage, for the period 1990–2021.

Lead authoring unit/office: Statistics Division (ESS)

Producing agricultural population estimates using an area frame. FAO Statistics Working Paper Series / 23-31

Year: 2023

Abstract: Estimating with a high precision the number of agricultural holdings and other population-related indicators is one of the main targets of the agricultural surveys. Achieving this objective is not straightforward when using an area frame: the choice of the estimator is indeed delicate since it depends on the criterion to link the observation units (e.g. agricultural holdings or tracts) and the sampling units (e.g. segments or points). According to the rule chosen, different types of estimators are defined: the open segment estimator, the closed segment estimator, the weighted segment estimator, the Horvitz–Thompson estimator and the multiplicity estimator. Moreover, auxiliary variables correlated to the population indicators can be used to produce the estimates: this is the case of the ratio estimator. In this paper, we describe the estimators mentioned above, focusing particularly on the comparison between them when the target parameter to be estimated is the number of agricultural holdings.

Lead authoring unit/office: Statistics Division (ESS)

Estimating global and country-level employment in agrifood systems. FAO Statistics Working Paper Series / 23-24

Year: 2023

Abstract: Global and national policy discourse and agendas are moving beyond traditional silos of agriculture, nutrition, health, and climate change to address the challenges facing agrifood systems (AFS). In this paper, we use international labour force statistics to provide the first systematic and documented global estimate quantifying the total number of people employed in AFS. We estimate that 1.23 billion people are employed in AFS and that 3.83 billion people worldwide live in households linked to AFS-based livelihoods. However, international labour force statistics focus on the main labour activity in the last seven days and are likely to undercount the total number of people who are engaged in AFS. Using household survey data from the harmonized multi-country Rural Livelihoods Information System (RuLIS) database, we find that the number of people engaged in AFS is on average 24 percent higher than employment defined only by the main labour activity. This analysis shows the relevance of counting secondary jobs and household farming activities to identify all individuals whose livelihoods depend to some degree on AFS.

Lead authoring unit/office: Statistics Division (ESS)

Methods for estimating greenhouse gas emissions from food systems Part V: Household food consumption. FAO Statistics Working Paper Series Issue 23/33

Year: 2023

Abstract: This paper is part of a series detailing new methodologies for estimating key components of agrifood systems emissions, with a view to disseminate the information in FAOSTAT. It describes methods for estimating greenhouse gas (GHG) emissions in households, which include fossil fuel-based energy use and non-renewable (i.e. beyond sustainable wood harvesting levels) woodfuel use. The publication is part of FAO Statistics Working Paper Series.

Lead authoring unit/office: Statistics Division (ESS)

Methods for estimating greenhouse gas emissions from food systems Part IV: Pesticides manufacturing. FAO Statistics Working Paper Series 22/32

Year: 2022

Abstract: This paper is part of a series detailing new methodologies for estimating key components of agrifood systems emissions, with a view to disseminate the information in FAOSTAT. It describes methods for estimating greenhouse gas (GHG) emissions associated with historic and current pesticide manufacturing, as part of an overall aim to inform countries of the environmental impacts of agrifood systems and the possible options to reduce them.

Lead authoring unit/office: Statistics Division (ESS)

Measuring rural poverty with a multidimensional approach: The Rural Multidimensional Poverty Index

Year: 2022

Abstract: This report presents the results of a collaboration between FAO and the Oxford Poverty and Human Development Initiative (OPHI), at the University of Oxford. The first part of the report proposes a framework for measuring multidimensional poverty in rural areas and describes the motivation for the Rural Multidimensional Poverty Index (R-MPI) proposal, which departs from the established global Multidimensional Poverty Index (global MPI), first designed in 2010 as an international measure of acute poverty covering over 100 developing countries by adding modifications in the dimensions and embedded indicators. The second part of this report presents an empirical test of the proposed R-MPI, using data from four household surveys conducted in Ethiopia, Malawi, the Niger, and Nigeria which are harmonized within the Rural Livelihoods Information System (RuLIS).

Lead authoring unit/office: Statistics Division (ESS)

Integrating surveys with geospatial data through small area estimation to disaggregate SDG indicators: A practical application on SDG Indicator 2.3.1

Year: 2022

Abstract: With the adoption of the 2030 Agenda for Sustainable Development, the production of high quality disaggregated estimates of Sustainable Development Goal (SDG) indicators has taken greater significance. In this context, sample surveys are characterized by samples that are either not large enough to guarantee reliable direct estimates for all relevant sub-populations, or that do not cover all possible disaggregation domains. To address these issues, indirect estimation approaches such as small area estimation (SAE) techniques can be adopted. The literature on the use of SAE in official statistics is broad and in continuous progress, yet the number of case studies on SAE methods applied to SDG indicators can still be expanded. After a brief review of the main SAE approaches available along with their principal fields of application, the present paper aims contributing to fill this gap by presenting a case study on SAE to produce disaggregated estimates of SDG Indicator 2.3.1, measuring average labour productivity of small-scale food producers. The discussed empirical exercise is based on a Fay-Herriot area-level SAE model, integrating survey data with area-level auxiliary information retrieved from multiple trustworthy geospatial information systems. Area-level SAE models have the advantage of being easy to implement and do not require accessing survey microdata and unit-level auxiliary information. These characteristics, jointly with the great potentials offered by modern geospatial information systems, offer the possibility of producing good quality disaggregated estimates of SDG indicators at high frequency and granular disaggregation level.

Lead authoring unit/office: Office of Chief Statistician (OCS)

Operational Use of EO Data for National Land Cover Official Statistics in Lesotho

Year: 2022

Abstract: The Food and Agriculture Organization of the United Nations (FAO) is building a land cover monitoring system in Lesotho in support of ReNOKA (‘we are a river’), the national program for integrated catchment management led by the Government of Lesotho. The aim of the system is to deliver land cover products at a national level on an annual basis that can be used for global reporting of official land cover statistics and to inform appropriate land restoration policies. This paper presents an innovative methodology that has allowed the production of five standardized annual land cover maps (2017–2021) using only a single in situ dataset gathered in the field for the reference year, 2021. A total of 10 land cover classes are represented in the maps, including specific features, such as gullies, which are under close monitoring. The mapping approach developed includes the following: (i) the automatic generation of training and validation datasets for each reporting year from a single in situ dataset; (ii) the use of a Random Forest Classifier combined with postprocessing and harmonization steps to produce the five standardized annual land cover maps; (iii) the construction of confusion matrixes to assess the classification accuracy of the estimates and their stability over time to ensure estimates’ consistency. Results show that the error-adjusted overall accuracy of the five maps ranges from 87% (2021) to 83% (2017). The aim of this work is to demonstrate a suitable solution for operational land cover mapping that can cope with the scarcity of in situ data, which is a common challenge in almost every developing country.

Lead authoring unit/office: Office of Chief Statistician (OCS)

Earth observations for official crop statistics in the context of scarcity of in-situ data

Year: 2022

Abstract: Remote sensing offers a scalable and low cost solution for the production of large-scale crop maps, which can be used to extract relevant crop statistics. However, despite considerable advances in the new generation of satellite sensors and the advent of cloud computing, the use of remote sensing for the production of accurate crop maps and statistics remain dependant on the availability of ground truth data. Such data are necessary for the training of supervised classification algorithms and for the validation of the results. Unfortunately, in-situ data of adequate quality for producing crop statistics are seldom available in many countries. In this paper we compare the performance of two supervised classifiers, the Random Forest (RF) and the Dynamic Time Warping (DTW), the former being a data intensive algorithm and the latter a more data frugal one, in extracting accurate crop type maps from EO and in-situ data. The two classifiers are trained several times using datasets which contain in turn an increasing number in-situ samples gathered in the Kashkadarya region of Uzbekistan in 2018. We finally compare the accuracy of the maps produced by the RF and the DTW classifiers with respect to the different number of training data used. Results show that when using only 5 and 10 training samples per each crop class, the DTW reaches a higher Overall Accuracy than the RF. Only when using five times more training samples, the RF starts to perform slightly better that the DTW. We conclude that the DTW can be used to map crop types using EO data in countries where limited in/situ data are available. We also highlight the critical importance in the choice of the location of the in-situ data and its thematic reliability for the accuracy of the final map, especially when using the DTW.

Lead authoring unit/office: Office of Chief Statistician (OCS)

Methods for estimating greenhouse gas emissions from food systems Part II: waste disposal. FAO Statistics Working Paper Series Issue 21/28

Year: 2021

Abstract: This paper is part of a series detailing novel methodologies for estimating key components of food systems emissions, with a view to disseminate the information in FAOSTAT. It provides a methodology for estimating the GHG emissions associated with emissions from waste in the food system (e.g., food-related processes in landfills, incineration, wastewater management processes), in an effort to inform countries of the environmental impacts and possible options to reduce them.

Lead authoring unit/office: Statistics Division (ESS)

Research on the measurement of post-harvest losses. Minimum losses by commodity and region: insights from the literature. FAO Statistics Working Paper Series / 21-26

Year: 2021

Abstract: The reduction of agricultural losses, especially among smallholder farmers, should be an essential component of food security strategies in developing countries. Loss reduction strategies should be informed by evidence on optimal loss levels, or the point below which loss reduction efforts become economically unviable, characterized by reduction costs greater than benefits. Information on minimum losses can help provide a benchmark for farm management, formulation of policies, and investment decisions. This study connects information on minimum losses with farming practices or production technologies, to help in assessing the effectiveness of loss reduction practices and of the underlying policies and incentives that promote them. While most empirical research and data collection activities on losses tend to focus on average losses, this paper provides evidence on minimum losses levels for several commodities and regions of the world.

Lead authoring unit/office: Statistics Division (ESS)

Measuring progress towards sustainable agriculture

Year: 2021

Abstract: This FAO Statistics working paper presents a new methodological approach aimed at measuring progress towards sustainable agriculture in countries and across agri-food systems typologies, by measuring socio-economic and environmental dimensions with available national statistics, with sixteen indicators defined and constructed from FAOSTAT data. A trend analysis is carried out at country level over the time series 1961-2018, with country results aggregated by four agri-food systems typologies: traditional; land-intensive and capital-intensive mixed systems; and modern food systems. The analysis provides a novel framework for the analysis of progress in achieving sustainable agriculture by country and agri-food system type, that can be implemented effectively and allows for exploring solutions across development pathways.

Lead authoring unit/office: Statistics Division (ESS)

Operational guidelines on listing and survey preparation for household and non-household agricultural holdings and special farms

Year: 2021

Abstract: This document is part of the FAO Statistics working paper series and part of the series of operational guidelines of the FAO Survey Team providing practical cost effective orientations to countries on agricultural surveys from the conception and implementation to data dissemination. The present document is focused on operational clarifications on the definitions of agricultural holdings and operational guidance for establishing lists of agricultural holdings for agricultural surveys.

Lead authoring unit/office: Statistics Division (ESS)

FAO Statistics Operational procedures for selecting samples for repeated agricultural surveys with a rotation design

Year: 2021

Abstract: FAO Statistics Working Paper 21/22 is part of the methodological works of the FAO’s Survey Team to provide operational guidance on selected areas of agricultural survey methodology with an overall objective to promote cost effective practices in agricultural surveys implementation.

Lead authoring unit/office: Statistics Division (ESS)

World Programme for the Census of Agriculture 2010. Global review of agricultural census methodologies and results (2006–2015)

Year: 2021

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)

Guidelines on the measurement of harvest and post-harvest losses. Estimation of maize harvest and post-harvest losses in Zimbabwe. Field test report

Year: 2020

Abstract: In the framework of the Global strategy to improve agriculture and rural statistics (GSARS), FAO provided technical assistance to Zimbabwe on the measurement of harvest and post-harvest losses through sample surveys. The technical assistance was provided in the form of a pilot study on estimating harvest and post-harvest losses for major crops in the Makonde district in the communal and A1 farming sectors. The survey focused on maize and sorghum and included the measurement of on-farm losses. The survey captured losses through interviews of farmers as well as through physical measurements. The number of usable data points for sorghum were too few to provide reliable production and loss estimates, hence the results presented in this report mostly refer to maize. The results show that 5.2 percent of grain is lost at harvest and 3.8 percent lost at drying. The comparison of the loss estimates according to the measurement method used shows mixed results; in A1 farming sectors, farmers’ own loss estimates tend to be lower than physical measurement, while the opposite is evidenced in the communal sector (except for drying). Timely harvesting was used by most farmers to limit losses, followed by stooking when harvesting and the use of chemicals to protect crops from pest infestations during storage. Keywords: Post-harvest losses, Zimbabwe, Makonde, Grains

Lead authoring unit/office: Statistics Division (ESS)

Guidelines on the measurement of harvest and post-harvest losses. Findings from the field test on estimating harvest and postharvest losses of fruits and vegetables in Mexico. Field test report

Year: 2020

Abstract: This technical report provides findings of field test conducted in identified states / districts / municipalities / study area in Mexico on the basis of sampling methodology for estimation of postharvest losses of horticultural crops (fruits and vegetables) developed by the team led by Dr. Tauqueer Ahmad, Head, Division of Sample Surveys, Indian Agricultural Statistics Research Institute, Institute of Indian Council of Agricultural Research (ICAR-IASRI), New Delhi, India. The Technical Report entitled “Findings from the field test conducted on estimating post-harvest losses of fruits and vegetables in Mexico” contains details of findings of the developed methodology implemented in Mexico, including challenges encountered and lessons learnt. It is expected that this report will help the users from different countries in designing surveys for measurement of post-harvest losses of horticultural crops (fruits and vegetables).

Lead authoring unit/office: Statistics Division (ESS)

Guidelines on the measurement of harvest and post-harvest losses. Estimating harvest and post-harvest losses in Zambia Meat and milk. Field test report

Year: 2020

Abstract: This technical report provides findings of a field test conducted in identified districts / study area in Zambia on the basis of sampling methodology for estimation of harvest and post-harvest losses of animal products (meat and milk) developed by the team led by Dr. Tauqueer Ahmad, Head, Division of Sample Surveys, Indian Agricultural Statistics Research Institute, Institute of Indian Council of Agricultural Research (ICAR-IASRI), New Delhi, India. The Technical Report entitled “Findings from the field test conducted on estimating harvest and post-harvest losses in Zambia. Meat and milk” contains details of findings of the developed methodology implemented in Zambia including challenges encountered and lessons learnt. It is expected that this report will help the users from different countries in designing surveys for measurement of harvest and post-harvest losses of animal products (meat and milk).

Lead authoring unit/office: Statistics Division (ESS)

World Programme for the Census of Agriculture 2010. Main results and metadata by country (2006–2015)

Year: 2019

Abstract: This publication, which is part of FAO Statistical Development Series, is a compendium of reviews of country agricultural censuses conducted during the WCA 2010 round (which covers the period 2006–2015) and their main results. Apart from providing information on historical background, legal, institutional frameworks and international collaboration, the publication also provides an overview of the census staff, reference and enumeration periods, scope and coverage, methodological modalities, frame, data collection methods, questionnaires used, new technology used, data processing and archiving, and census data quality and dissemination. Data sources and contact information is provided for each country. These concise two-page overviews of national censuses present a unique panorama of country practices on agricultural censuses to which national census agencies can refer when planning their censuses.

Lead authoring unit/office: Statistics Division (ESS)

Measuring vegetable crops area and production. Technical report on a pilot survey in two districts of Ghana. Final report

Year: 2018

Abstract: Prepared by the Global Strategy to improve Agricultural and Rural Statistics, this Report introduces and discusses the problem of measuring area and yield of vegetable crops, by exploring and testing methods such as farmer inquiry and objectives measurement and to propose a methodology for the production of data and statistics. A pilot test has been performed in two selected districts in Ghana to assess the methodology and the workability of the methods.

Lead authoring unit/office: Statistics Division (ESS)

Case-studies on the measurement of productivity and efficiency in agriculture

Year: 2018

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)

Field test report on agri-environmental indicators (AEls). Towards a sustainable agriculture

Year: 2018

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)

Productivity and efficiency measurement in agriculture - Literature review and gaps analysis

Year: 2017

Abstract: This literature review and gaps analysis is undertaken in the context of the research line on the measurement of agricultural productivity and efficiency of the Global Strategy to Improve Agricultural and Rural Statistics. It seeks to define the different concepts and present the main measurement methods for agricultural productivity and efficiency.

Lead authoring unit/office: Statistics Division (ESS)

A literature review and key agri/environmental indicators

Year: 2017

Abstract: The objective of the research topic “SUST-3, Data Collection Methods for Agri-environmental Indicators” is to provide a framework for agricultural sustainability indicators and related statistical definitions, and measurements tools covering the economic, social and environmental dimensions. This document was produced by the Global Strategy to improve Agricultural and Rural Statistics (GSARS).

Lead authoring unit/office: Statistics Division (ESS)

Technical report on reconciling data from agricultural censuses and surveys

Year: 2017

Abstract: Prepared by the Global Strategy to Improve Agricultural and Rural Statistics (GSARS), this report introduces the problem of reconciling agricultural census and survey data by exploring methods to recalculate the survey weights, focusing on how to combine information from agricultural censuses.

Lead authoring unit/office: Statistics Division (ESS)

Field test report on the estimation of crop yields and post-harvest losses in Ghana

Year: 2017

Abstract: A pilot survey was conducted in Ghana from October 2016 to March 2017, testing a survey-based approach to measure harvest and post-harvest losses on the farm. Prepared by the Global Strategy to Improve Agricultural and Rural Statistics (GSARS), this document describes the methodological approach that was tested and subsequently adopted.

Lead authoring unit/office: Statistics Division (ESS)

Methodology for estimation of crop area and crop yield under mixed and continuous cropping

Year: 2017

Abstract: On the basis of a gaps analysis, a methodology has been developed to estimate crop area and crop yield in mixed and continuous cropping scenarios. In this regard, several alternatives have been considered, depending upon the information available in the agricultural statistical system. The different methods for the area apportionment of a crop mixture’s various component crops are explained, as are methods for crop area and yield measurement, along with their respective advantages and disadvantages. Situations in which particular methods are suitable are described. The questionnaires mentioned in this technical report have been designed for data collection on crop area and crop yield for the alternative methodologies developed. The importance of Computer-Assisted Personal Interviewing (CAPI) software for the efficient collection of survey data is emphasized. The methodology developed for crop area and yield estimation is demonstrated through a series of field tests conducted in district/study areas in Indonesia, Jamaica and Rwanda. The report ends with a number of Conclusions.

Lead authoring unit/office: Statistics Division (ESS)

Literature review on reconciling data from agricultural censuses and surveys

Year: 2016

Abstract: Prepared by the Global Strategy to Improve Agricultural and Rural Statistics (GSARS), this technical paper reviews the literature on the methodologies for reconciling data from agricultural censuses and surveys. The techniques that can be used for data reconciliation are described, and the main advantages and disadvantages of each are assessed. On the basis of the literature, for each relevant methodology, this paper formulates recommendations to be considered in the reconciliation of census and survey data. It also provides a gap analysis that documents and assesses the differences between the various methods.

Lead authoring unit/office: Statistics Division (ESS)

Literature review report and proposal for an international framework for farm typologies

Year: 2016

Abstract: Prepared by the Global Strategy to Improve Agricultural and Rural Statistics (GSARS), this report contains a literature review of classifications and typologies developed in agriculture and a preliminary proposal for classification principles that can feed into the guidelines for establishing an international framework for farm typologies.

Lead authoring unit/office: Statistics Division (ESS)

Improving methods for estimating livestock production and productivity. Literature review

Year: 2015

Abstract: Timely and accurate data is critically important for the development of food security programs, agricultural development, poverty reduction policies, investment strategies and natural disaster responses. This literature review was prepared by the Global Strategy to Improve Agricultural and Rural Statistics (GSARS).

Lead authoring unit/office: Statistics Division (ESS)

Linking area and list frames in agricultural surveys

Year: 2015

Abstract: Prepared in the framework of the Global Strategy to improve Agricultural and Rural Statistics, this Technical Report introduces and discusses methods for linking area frames and list frames, and considers the effects of these linkages during a survey’s design and estimation stages. 

Lead authoring unit/office: Statistics Division (ESS)

2000 World Census of Agriculture: Main results and metadata by country (1996-2005)

Year: 2010

Abstract: This publication, which is part of FAO Statistical Development Series, presents a comparison of data (not without limitations) received from different countries. It provides selected data on number and area of holdings, gender of the holder, farm population, employment, land tenure, land use, main crops, livestock, irrigation and machinery and equipment.

Lead authoring unit/office: Statistics Division (ESS)

Multiple frame agricultural surveys. Volume 2. Agricultural survey programme based on area frame or dual frame (area and list) sample designs

Year: 1998

Abstract: This publication, which is part of FAO Statistical Development Series, is the second volume of an introduction to establishing and conducting area and multiple frame probability sample survey programmes, emphasizing methods and practices applicable in developing countries.

Lead authoring unit/office: Statistics Division (ESS)

Multiple frame agricultural surveys. Volume 1. Current surveys based on area and list sampling methods

Year: 1996

Abstract: 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, multipurpose agricultural data collection programmes called current agricultural surveys. This paper is part of FAO Statistical Development Series.

Lead authoring unit/office: Statistics Division (ESS)

Collecting data on livestock

Year: 1992

Abstract: This publication on livestock statistics is intended to assist statisticians in their work. Emphasis is placed on the need to conceptualise data sources within a framework of a national information system which requires standardised concepts. It is part of FAO Statistical Development Series.

Lead authoring unit/office: Statistics Division (ESS)

1980 World Census of Agriculture - Methodological review

Year: 1992

Abstract: This publication is a review of methodological aspects of the national agricultural censuses conducted within the framework of the Programme for the 1980 World Census of Agriculture of the Food and Agriculture Organization of the United Nations. It is part of FAO Statistical Development Series.

Lead authoring unit/office: Statistics Division (ESS)

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Manual on agricultural price index numbers

Year: 1988

Abstract: Price observation of individual agricultural commodities and input items represent important information for data users in government, business management, or in other areas, conducting economic analysis. However, individual commodity price data alone do not always provide sufficient guidance for studying general price trends. This publication is part of FAO Statistical Development Series.

Lead authoring unit/office: Statistics Division (ESS)

The FAO agricultural production index

Year: 1986

Abstract: The purpose of this report is to present a description of the FAO's production index and its evolution, published regularly in the FAO Production Yearbook and in the FAO Monthly Bulletin of Statistics, as well as in The State of Food and Agriculture report. This publication is part of FAO Statistical Development Series.

Lead authoring unit/office: Statistics Division (ESS)

Socio-economic indicators relating to the agricultural sector and rural development

Year: 1984

Abstract: This publication provides a compendium of internationally comparable series of statistical indicators which are currently available using the data bank of the Food and Agricultural Organization of the United Nations, called the Interlinked Computerized and Processing System on Food and Agricultural Comodity Data (ICS). This publication is part of FAO Statistical Development Series.

Lead authoring unit/office: Statistics Division (ESS)

Agricultural census legislation

Year: 1984

Abstract: This publication is part of FAO Statistical Development Series. The first part sets out the reasons why specific legislation is needed. The second consists of a comparative study of the main aspects of such legislation. The third part contains the texts of several laws, regulations and similar enactments of various countries. 

Lead authoring unit/office: Statistics Division (ESS)

Agricultural holdings in the 1970 World Census of Agriculture: A statistical analysis

Year: 1984

Abstract: The information presented in this report gives the results of a statistical analysis of the agricultural holdings main characteristics (i.e. distribution of the number and area by size, using the log normal distribution). This publication is part of FAO Statistical Development Series.

Lead authoring unit/office: Statistics Division (ESS)

Community level statistics

Year: 1983

Abstract: The Statistics Division is re-evaluating all of its Statistical Programme Development Manuals with the intent to formulate a system approach to the planning, developmet and conduct of national statistical programmes for food and agriculture with enphasis on developing countries. This publication is part of FAO Economic and social development paper series.

Lead authoring unit/office: Statistics Division (ESS)

Carryover stocks of cereals 1975-1980 / Stocks céréaliers de report 1975-1980 / Existencias remanentes de cereales 1975-1980

Year: 1982

Abstract: Stocks play an important role in achieving the objectives of world food security by maintaining the continuity of cereal supplies to the consumer and offsetting year to year fluctuation in production. It is part of FAO Economic and social development paper series.

Lead authoring unit/office: Statistics Division (ESS)

1970 World Census of Agriculture Analysis and international comparison of the results

Year: 1981

Abstract: This publication provides, in an internationally comparable form, a summary of data describing the main characteristics of agricultural structures, such as number and area of agricultural holdings, land tenure, agricultural holders and land use. It contains data from 89 countries. This paper is part of FAO Statistical Development Series.

Lead authoring unit/office: Statistics Division (ESS)

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Taking agricultural censuses. Guidelines supplementing the Programme for the 1980 World Census of Agriculture

Year: 1978

Abstract: These guidelines contain information based mainly on the experience of selected international and national agricultural census experts working and/or having worked in the developing countries. They are part of FAO Statistical Development Series.

Lead authoring unit/office: Statistics Division (ESS)

Report on the 1970 World Census of Agriculture

Year: 1977

Abstract: The 1970 World Census of Agriculture was the third decennial census of agri­culture promoted by FAO. The present publication, which is part of FAO Statistical Development Series, deals with the concepts, definitions and methodology of census taking as applied by countries participating in the 1970 World Census of Agriculture. The information presented is drawn from the available national census reports, documents of various FAQ meetings and sessions, and from the FAO experts who were actually involved in the planning and implementation of the census of agriculture taken around 1970 in the developing countries. While every effort was made to pool together all possible sources of information, it is by no means claimed to be exhaustive. Most of the census reports available from the countries were lacking in adequate information on the planning and methodological procedures. On a number of items the information presented in some of the national reports was too scanty for a comparative analysis to be included in the present volume. Naturally these limitations reflect correspondingly on the contents of this publication.

Lead authoring unit/office: Statistics Division (ESS)

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Quality of statistical data

Year: 1966

Abstract: This book provides material presented at various seminars and workshops organised by FAO. The aim of these lectures was to spread awareness of the quality problem of statistical data and to promote interest in quality checks.

Lead authoring unit/office: Statistics Division (ESS)

Report on the 1960 World Census of Agriculture - Census results by countries

Year: 1966

Abstract: The aim of this publication is primarily to provide, in an uniformed form, census results for countries that have particpated in the 1960 world census of agriculture.

Lead authoring unit/office: Statistics Division (ESS)

Report on the 1950 World Census of Agriculture Census results by countries: Volume 1

Year: 1955

Abstract: The 1950 Census of Agriculture was taken as of 1 April 1950. Inventory items relate to 1 April. Data on acreage and quantity of crops harvested are for crop year 1949.

Lead authoring unit/office: Statistics Division (ESS)

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FAO elearning course on "Monitoring public expenditure on food and agriculture: the MAFAP method"

Year: 2021

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

FAO elearning course on Monitoring price incentives for food and agriculture: the MAFAP method

Year: 2021

Abstract: Knowing how policies influence prices at different stages of the value chain, such as at producer, wholesale and retail level, is fundamental to determine if changes in policy are needed to encourage production or ensure food security. Through price incentives indicators, we can monitor the effects of agricultural policies to see whether they incentivise - or disincentivise - farmers or traders to produce or market an agricultural commodity.​ This course explains how to produce these indicators, what data you need and how to calculate and analyse them in order to shape and optimise public policy for agri-food systems transformation.

Lead authoring unit/office: FAO

FAO Training Series on SDG indicator 2.4.1

Year: 2021

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)

E-learning course | Using the FAO methodology to compute damage and loss

Year: 2020

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

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E-learning course | Introduction to FAO's damage and loss assessment methodology

Year: 2020

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)

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Virtual Training on SDG indicator 2.4.1. “Proportion of Agricultural Area under Productive and Sustainable Agriculture”

Year: 2020

Abstract: The overall objective of this virtual training was to provide (government officials responsible for monitoring SDG indicator 2.4.1) capacity development on the methodology, data collection and analysis relevant to sustainable food and agriculture and how to asses data gaps starting from available national and subnational (farm-level) information and associated reporting processes through 3 half-days virtual trainings. 

Lead authoring unit/office: Statistics Division (ESS)

E-learning course | SDG Indicator 2.4.1 - Sustainable agriculture

Year: 2019

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)

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Training course on Agricultural Integrated Survey (AGRIS) (Module 0/3) - Training material

Year: 2018

Abstract: Prepared by the Global Strategy to improve agricultural and rural statistics (GSARS), this AGRIS training aims to provide enumerators with the skills and knowledge necessary to successfully collect high quality AGRIS data. This training plan covers the training essentials (timing, the training team, physical and technical requirements and ways to keep enumerators engaged), the components of training (elements common to all training sessions and those that vary depending on the AGRIS module(s) being presented), and the training schedule. 

Lead authoring unit/office: Statistics Division (ESS)

Training course on Agricultural Integrated Survey (AGRIS) (Module 1/3) - Introduction

Year: 2018

Abstract: Prepared by the Global Strategy to improve agricultural and rural statistics (GSARS), this AGRIS training aims to provide enumerators with the skills and knowledge necessary to successfully collect high quality AGRIS data. At the end of this training unit, you will have: an introduction to your fellow enumerators and supervisor; the beginning of a network of resource people to support you during data collection; and an understanding of the importance of your role as an enumerator in ensuring the quality of the data collected.

Lead authoring unit/office: Statistics Division (ESS)

Training course on the Agricultural Integrated Survey (AGRIS) (Module 2/3) - Economy module

Year: 2018

Abstract: Prepared by the Global Strategy to improve agricultural and rural statistics (GSARS), this AGRIS training aims to provide enumerators with the skills and knowledge necessary to successfully collect high quality AGRIS data. At the end of this training unit, you will have: knowledge of the Economy (ECO) Module questionnaire’s subject matter; practice in the administration of the ECO Module questionnaire; comprehension of the ECO Module survey methodology. You will also: reinforce your hands-on familiarity with the survey Computer assisted personal interview (CAPI) application for AGRIS; test the usability of the CAPI application for the Core module.

Lead authoring unit/office: Statistics Division (ESS)

Training course on the Agricultural Integrated Survey (AGRIS) (Module 3/3) - Core module

Year: 2018

Abstract: Prepared by the Global Strategy to improve agricultural and rural statistics (GSARS), this AGRIS training aims to provide enumerators with the skills and knowledge necessary to successfully collect high quality AGRIS data. At the end of this training unit, you will have: knowledge of the Core Module questionnaire’s subject matter; practice in the administration of the Core Module questionnaire; comprehension of the Core Module survey methodology. You will also: reinforce your hands-on familiarity with the survey Computer assisted personal interview (CAPI) application for AGRIS; test the usability of the CAPI application for the Core module.  

Lead authoring unit/office: Statistics Division (ESS)

Training course on post-harvest losses (Module 0/6) - Training material (Users' guide)

Year: 2018

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)

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Training course on post-harvest losses (Module 1/6) - Conceptual framework and definitions

Year: 2018

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)

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Training course on post-harvest losses (Module 2/6) - Measuring grain losses on a farm

Year: 2018

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)

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Training course on post-harvest losses (Module 3/6) - Analysis of losses at the lab

Year: 2018

Abstract: Prepared by the Global Strategy to improve agricultural and rural statistics (GSARS), this session deals with the objective measurements and analyses of losses performed in laboratories. It presents the different methods and formulas used to calculate losses once the grains taken from the farms reach the laboratory. It also discusses the selection of grains that arrives at the laboratory and the different formulas that could be applied after the selection is done. Outline of the session: a) Introduction; b) Standard Volume/Weight Method (SVM); c) Conventional count and weigh or gravimetric method; d) Modified count and weigh method; e) Thousand Grain Mass Method (TGM); f) Converted percentage damaged method.

Lead authoring unit/office: Statistics Division (ESS)

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Training course on post-harvest losses (Module 4/6) - Sampling design

Year: 2018

Abstract: Prepared by the Global Strategy to improve agricultural and rural statistics (GSARS), this session aims to discuss the different farm-level and off-farm sampling approaches (processors, millers etc.). It presents the methods used to select farmers, fields, and crops, and describes the crop-cutting method used in objective measurements. It also covers sampling methods for grain at the storage stage. Outline of the session: a) Introduction; b) Sampling approach at farm-gate level; c) Off-farm sampling approach.

Lead authoring unit/office: Statistics Division (ESS)

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Training course on post-harvest losses (Module 5/6) - Loss assessment through experimental design-field trial

Year: 2018

Abstract: Field trials or experimental designs are approaches adopted to assess losses for specific grains or for specific stages or methods used by the farmers. It is used by research stations in certain circumstances to test methods, types of seeds or other inputs, to reduce the losses experienced by farmers. Prepared by the Global Strategy to improve agricultural and rural statistics (GSARS), this session explains how this approach can be used to produce better statistics on PHL. Outline of the session: a) Introduction; b) Concepts and definitions; c) Statistical designs; d) Loss assessment at different stages; e) Example: Ghana.

Lead authoring unit/office: Statistics Division (ESS)

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Training course on post-harvest losses (Module 6/6) - Loss assessment through modelling

Year: 2018

Abstract: Prepared by the Global Strategy to improve agricultural and rural statistics (GSARS), this session is mainly used to improve the analysis once the data is obtained, such as by providing the link between losses and the practices followed by farmers. In this session, different models are presented, with examples. Outline of the session: a) Introduction; b) Concepts and type of data; c) Regression analysis: general linear regression model; d) Example: Pakistan.  

Lead authoring unit/office: Statistics Division (ESS)

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Training course on livestock production and productivity (Module 0/4) - Users' guide

Year: 2018

Abstract: Prepared by the Global Strategy to improve agricultural and rural statistics (GSARS), this training material on the measurement of livestock production and productivity targets decision makers, statisticians, analysts and data producers from National Statistical Systems (NSOs or statistical departments within the Ministry of Agriculture, for example) as well as analysts, researchers, teaching staff and students from training centres of statistics and agriculture and other relevant institutions. This user guide describes the intended goals, content and target audience of the training material on the estimation of livestock production and productivity. It also outlines the structure of the training material and provides recommendations on organizational aspects.

Lead authoring unit/office: Statistics Division (ESS)

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Training course on livestock production and productivity (Module 1/4) - Advocacy: why do we need accurate livestock statistics?

Year: 2018

Abstract: Prepared by the Global Strategy to improve agricultural and rural statistics (GSARS), the goal of this module is to discuss the importance of livestock statistics within countries and the requirements for producing better statistics in this domain. It also discusses the scope of livestock statistics in the GS context. Outline of the session: a) Introduction; b) Scope of animal production activities and livestock statistics; c) Contribution of livestock to poverty reduction and development; d) Livestock statistics in policy agendas.

Lead authoring unit/office: Statistics Division (ESS)

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Training course on livestock production and productivity (Module 2/4) - Items and indicators

Year: 2018

Abstract: Prepared by the Global Strategy to improve agricultural and rural statistics (GSARS), this session presents the main indicators that should be compiled when conducting livestock studies and the different items to be collected in the field. It also briefly discusses the data sources for each indicator and presents some practical considerations to recall when compiling data. Outline of the session: a) Introduction; b) Livestock stocks; c) Meat production; d) Milk production; e) Egg production; f) Animal health; g) Feed availability; h) Watering practices.

Lead authoring unit/office: Statistics Division (ESS)

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Training course on livestock production and productivity (Module 3/4) - Data collection and survey design

Year: 2018

Abstract: Prepared by the Global Strategy to improve agricultural and rural statistics (GSARS), this module tackles an important component of livestock statistics. It discusses, in detail, the different ways to obtain data on livestock statistics. The main goal of the session is to build the capacity of technical staff involved in survey design and data collection operations. It discusses the best approaches to adopt when collecting data with livestock keepers and the various estimation methods that can contribute to the calculation of more accurate statistics. Outline of the session: a) Introduction; b) Main data sources; c) Data collection methods; d) Survey design and implementation.

Lead authoring unit/office: Statistics Division (ESS)

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Training course on livestock production and productivity (Module 4/4) - Field work organization, cost and integrated survey

Year: 2018

Abstract: Prepared by the Global Strategy to improve agricultural and rural statistics (GSARS), the main objective of this session is to present the possible approaches towards reducing the cost of livestock surveys. It presents the best practices related to fieldwork organization and the budget components to take into account when designing livestock surveys. It also discusses the integration of livestock-data gathering into an integrated agricultural survey, as thisis considered a cost-effective way to collect data on agriculture in general and on livestock in particular. Outline of the session: a) Introduction; b) Fieldwork organization; c) Cost of livestock surveys; d) Integrated surveys.

Lead authoring unit/office: Statistics Division (ESS)

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Training course on Master Sampling Frame for agricultural statistics: Frame Development, Sample Design And Estimation (Users' Guide)

Year: 2017

Abstract: Prepared by the Global Strategy to Improve Agricultural and Rural Statistics (GSARS), this training material is designed for managers, statisticians, sampling experts, GIS specialists and professional staff from the National Statistical Offices and statistical units of the Ministries of Agriculture. It may also be used to train students in agricultural statistics as well as targeted trainers or technical assistance providers in statistical training centres, Regional Economic Communities and regional and subregional organizations specialized in statistical development. This user guide has been prepared to guide the users through this training material.    

Lead authoring unit/office: Statistics Division (ESS)

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Training course on Master Sampling Frames (MSF) - Master sampling frame for agricultural statistics: basic principles

Year: 2017

Abstract: Prepared by the Global Strategy to Improve Agricultural and Rural Statistics (GSARS), this training material is designed for managers, statisticians, sampling experts, GIS specialists and professional staff from the National Statistical Offices and statistical units of the Ministries of Agriculture. It may also be used to train students in agricultural statistics as well as targeted trainers or technical assistance providers in statistical training centres, Regional Economic Communities and regional and subregional organizations specialized in statistical development. This session aims to a) Introduce the concept of Master Sampling Frame (MSF); b) Inform the audience about the benefits of constructing and using an MSF; and c) Advocate for an agricultural survey system based on a single Master Sampling Frame.

Lead authoring unit/office: Statistics Division (ESS)

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Training course on Master Sampling Frames (MSF) – Using list frames to build and maintain an MSF

Year: 2017

Abstract: Prepared by the Global Strategy to Improve Agricultural and Rural Statistics (GSARS), this training material is designed for managers, statisticians, sampling experts, GIS specialists and professional staff from the National Statistical Offices and statistical units of the Ministries of Agriculture. This session aims to: a) Inform the audience about how to build an MSF using list Frame; b) Discuss about main issues from the use of list Frame; c) Provide guidelines for maintaining and updating list Frame.

Lead authoring unit/office: Statistics Division (ESS)

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Training course on Master Sampling Frames (MSF) – Defining the Master Sampling Frame for agricultural statistics: basic principles

Year: 2017

Abstract: Prepared by the Global Strategy to Improve Agricultural and Rural Statistics (GSARS), this training material is designed for managers, statisticians, sampling experts, GIS specialists and professional staff from the National Statistical Offices and statistical units of the Ministries of Agriculture. This session aims to: a) Introduce the concept of MSF; b) Inform the audience about the benefit of constructing and using an MSF; and c) Provide guidelines for the construction, maintenance and use of Master Sampling Frames (MSFs) in agricultural statistics.

Lead authoring unit/office: Statistics Division (ESS)

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Training course on Master Sampling Frames (MSF) – Using a Multiple Sampling Frame as an MSF

Year: 2017

Abstract: Prepared by the Global Strategy to Improve Agricultural and Rural Statistics (GSARS), this training material is designed for managers, statisticians, sampling experts, GIS specialists and professional staff from the National Statistical Offices and statistical units of the Ministries of Agriculture. This session ams to: a) Review the principles of multiple frame sampling; b) Deal with issues arising from the use of multiple frame sampling; and c) Provide lessons from countries examples.  

Lead authoring unit/office: Statistics Division (ESS)

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Training course on Master Sampling Frames (MSF) - Using Area Sampling Frames to build and maintain a MSF

Year: 2017

Abstract: Prepared by the Global Strategy to Improve Agricultural and Rural Statistics (GSARS), this training material is designed for managers, statisticians, sampling experts, GIS specialists and professional staff from the National Statistical Offices and statistical units of the Ministries of Agriculture. At the end of this session, the audience will: a) Know the utility of area frame and is able to identify the main types; b) Know the differents steps required to build an area sampling frame and do a pratical exercise; c) Be able to choose between different segment area methodologies taking into account the reality of the countries; d) Know how to avoid the source of non-sampling errors when designing an area frame; and e) Be able to make link between census or administrative data and an area frame.  

Lead authoring unit/office: Statistics Division (ESS)

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Training course on Master Sampling Frames (MSF) - Sampling design and estimation when the MSF is an area frame

Year: 2017

Abstract: Prepared by the Global Strategy to Improve Agricultural and Rural Statistics (GSARS), this training material is designed for managers, statisticians, sampling experts, GIS specialists and professional staff from the National Statistical Offices and statistical units of the Ministries of Agriculture. At the end of this session, the audience will: a) Be able to know the kind of observation mode that should adopted for their survey; b) Be able to establish the formula of the the estimation of the variable of interest depending whether the sampling unit is a point or a segment; and c) Understand how to avoid non-sampling errors when designing the survey.

Lead authoring unit/office: Statistics Division (ESS)

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Training course on Master Sampling Frame for agricultural statistics: What is the Agricultural Integrated Survey (AGRIS)? How does an MSF fit in AGRIS or integrated survey programs?

Year: 2017

Abstract: Prepared by the Global Strategy to Improve Agricultural and Rural Statistics (GSARS), this training material is designed for managers, statisticians, sampling experts, GIS specialists and professional staff from the National Statistical Offices and statistical units of the Ministries of Agriculture. It may also be used to train students in agricultural statistics as well as targeted trainers or technical assistance providers in statistical training centres, Regional Economic Communities and regional and subregional organizations specialized in statistical development.  

Lead authoring unit/office: Statistics Division (ESS)

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Training course on Master Sampling Frame for agricultural statistics: Countries’ experiences

Year: 2017

Abstract: Prepared by the Global Strategy to Improve Agricultural and Rural Statistics (GSARS), this training material is designed for managers, statisticians, sampling experts, GIS specialists and professional staff from the National Statistical Offices and statistical units of the Ministries of Agriculture. The objectives of the presentation is to inform the audience on: the diversity of countries’ situations and national factors that guided the choice of particular options for building sampling frames for agriculture and using them as master sampling frame (MSF); and the lessons learnt by countries in building and using an MSF.

Lead authoring unit/office: Statistics Division (ESS)

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Training course on Master Sampling Frame for agricultural statistics: Requirements to building an MSF

Year: 2017

Abstract: Prepared by the Global Strategy to Improve Agricultural and Rural Statistics (GSARS), this training material is designed for managers, statisticians, sampling experts, GIS specialists and professional staff from the National Statistical Offices and statistical units of the Ministries of Agriculture. At the end of this session, the audience will: a) Be familiar with the recommended steps when developing an MSF; and b) Understand the background information, competencies, time and resources investments required when implementing an MSF.

Lead authoring unit/office: Statistics Division (ESS)

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Training course on Master Sampling Frame for agricultural statistics - Using different frames to build and use a Master Sampling Frame

Year: 2017

Abstract: Prepared by the Global Strategy to Improve Agricultural and Rural Statistics (GSARS), this training material is designed for managers, statisticians, sampling experts, GIS specialists and professional staff from the National Statistical Offices and statistical units of the Ministries of Agriculture.The objectives of this presentation are to: a) Discuss the types of master sampling frames and data sources; b) Discuss the advantages and disadvantages of using an Area frame as an MSF; c) Discuss the advantages and disadvantages of using an List frame as an MSF; and d) Discuss the advantages and disadvantages of using a Multiple frame as an MSF.

Lead authoring unit/office: Statistics Division (ESS)

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Training course on Master Sampling Frame for agricultural statistics: Sampling design and estimation when the MSF is a list frame

Year: 2017

Abstract: Prepared by the Global Strategy to Improve Agricultural and Rural Statistics (GSARS), this training material is designed for managers, statisticians, sampling experts, GIS specialists and professional staff from the National Statistical Offices and statistical units of the Ministries of Agriculture. The objectives of this presentatin are to: a) Present different sampling designs and estimation techniques when the MSF is a list frame; and b) Provide guidelines for the use of auxiliary information to improve the sampling design.

Lead authoring unit/office: Statistics Division (ESS)

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Training course on Master Sampling Frame for agricultural statistics: Sampling design considerations when developing an MSF

Year: 2017

Abstract: Prepared by the Global Strategy to Improve Agricultural and Rural Statistics (GSARS), this training material is designed for managers, statisticians, sampling experts, GIS specialists and professional staff from the National Statistical Offices and statistical units of the Ministries of Agriculture. At the end of this session, the audience will: a) Be able to identify the different concepts when designing a survey; b) Know the elements that impact the sampling variability and errors; and c) Understand the particularities of the different probability sampling designs to be considered in deciding which ones are more adapted to the objectives of the survey.  

Lead authoring unit/office: Statistics Division (ESS)

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Training course on CAPI - Getting Started

Year: 2017

Abstract: Prepared by the Global Strategy to Improve Agricultural and Rural Statistics (GSARS), this material for in-classroom training on the use of CAPI for agricultural surveys targets decision makers, survey managers, questionnaire designers, trainers of field staff and data analysts. At the end of this session, the audience will be able to: Describe role of Designer; Find and register for Designer; Describe role Tester; and Find, download, and install Tester on tablet.

Lead authoring unit/office: Statistics Division (ESS)

Training course on CAPI - Overview of Survey Solutions System and organization of training

Year: 2017

Abstract: Prepared by the Global Strategy to Improve Agricultural and Rural Statistics (GSARS), this material for in-classroom training on the use of CAPI for agricultural surveys targets decision makers, survey managers, questionnaire designers, trainers of field staff and data analysts.

Lead authoring unit/office: Statistics Division (ESS)

Training course on CAPI - Basic Designer

Year: 2017

Abstract: Prepared by the Global Strategy to Improve Agricultural and Rural Statistics (GSARS), this material for in-classroom training on the use of CAPI for agricultural surveys targets decision makers, survey managers, questionnaire designers, trainers of field staff and data analysts. At the end of this session, the audience will: a) Know how to create a questionnaire; b) Know the major question types (text, numeric, date, single and multi answer, list); c) Understand the concept for enablement conditions; d) Be familiar with the fields to be completed for questions; and e) Know about static text.  

Lead authoring unit/office: Statistics Division (ESS)

Training course on CAPI - Use of CAPI for agricultural surveys - Intermediate Designer 1

Year: 2017

Abstract: Prepared by the Global Strategy to Improve Agricultural and Rural Statistics (GSARS), this material for in-classroom training on the use of CAPI for agricultural surveys targets decision makers, survey managers, questionnaire designers, trainers of field staff and data analysts. At the end of this session, the audience will: a) Know what validation conditions and messages are; and b) Apply basic C# syntax for creating validation and enablement conditions.

Lead authoring unit/office: Statistics Division (ESS)

Training course on CAPI - Intermediate Designer 2

Year: 2017

Abstract: Prepared by the Global Strategy to Improve Agricultural and Rural Statistics (GSARS), this material for in-classroom training on the use of CAPI for agricultural surveys targets decision makers, survey managers, questionnaire designers, trainers of field staff and data analysts. At the end of this session, the audience will: a) Know how to build a roster; b) Know about nesting rosters; c) Know about html tags; and, d) Know about piping.

Lead authoring unit/office: Statistics Division (ESS)

Training course on CAPI - Interviewer application

Year: 2017

Abstract: Prepared by the Global Strategy to Improve Agricultural and Rural Statistics (GSARS), this material for in-classroom training on the use of CAPI for agricultural surveys targets decision makers, survey managers, questionnaire designers, trainers of field staff and data analysts. This training session will give an overview of the interview application.

Lead authoring unit/office: Statistics Division (ESS)

Training course on CAPI - Data export

Year: 2017

Abstract: Prepared by the Global Strategy to Improve Agricultural and Rural Statistics (GSARS), this material for in-classroom training on the use of CAPI for agricultural surveys targets decision makers, survey managers, questionnaire designers, trainers of field staff and data analysts. This training session will give an overview of data export.

Lead authoring unit/office: Statistics Division (ESS)

Training course on CAPI - Tablet management, configuration, useful apps, and equipment/accessories

Year: 2017

Abstract: Prepared by the Global Strategy to Improve Agricultural and Rural Statistics (GSARS), this material for in-classroom training on the use of CAPI for agricultural surveys targets decision makers, survey managers, questionnaire designers, trainers of field staff and data analysts. This training session will provide an overview of: Tablet management; Tablet configuration; Useful apps and Equipment/Accessories.  

Lead authoring unit/office: Statistics Division (ESS)

Training course on CAPI for agricultural surveys (Users’ guide – Training material)

Year: 2017

Abstract: Prepared by the Global Strategy to Improve Agricultural and Rural Statistics (GSARS), this material for in-classroom training on the use of CAPI for agricultural surveys targets decision makers, survey managers, questionnaire designers, trainers of field staff and data analysts.  

Lead authoring unit/office: Statistics Division (ESS)

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Training course on the use of CAPI for agricultural surveys - Introduction and case management with Admin/Headquarters/Supervisor

Year: 2017

Abstract: Prepared by the Global Strategy to Improve Agricultural and Rural Statistics (GSARS), this material for in-classroom training on the use of CAPI for agricultural surveys targets decision makers, survey managers, questionnaire designers, trainers of field staff and data analysts. At the end of this session, the audience will: a) Know the difference between Administrator, HQ, and Supervisor; b) Be familiar with workflow of Survey Solutions and events in the life a case; c) Know how to access HQ and Supervisor; d) HQ primary functions (create Supervisor, Interviewers, Import Template, Create Cases, Assign Cases to Supervisor); e) Supervisor primary functions (assign cases to Interviewers); f) Use HQ and Supervisor to approve/reject completed cases; f) Know about creating field reports with HQ and Supervisor.

Lead authoring unit/office: Statistics Division (ESS)

Training course on the use of CAPI for agricultural surveys - Is CAPI right for my survey?

Year: 2017

Abstract: Prepared by the Global Strategy to Improve Agricultural and Rural Statistics (GSARS), this material for in-classroom training on the use of CAPI for agricultural surveys targets decision makers, survey managers, questionnaire designers, trainers of field staff and data analysts.  

Lead authoring unit/office: Statistics Division (ESS)

Training course on the use of CAPI for agricultural surveys - Advanced designer topics demonstrative, not instructional

Year: 2017

Abstract: Prepared by the Global Strategy to Improve Agricultural and Rural Statistics (GSARS), this material for in-classroom training on the use of CAPI for agricultural surveys targets decision makers, survey managers, questionnaire designers, trainers of field staff and data analysts.

Lead authoring unit/office: Statistics Division (ESS)

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Basic training on agricultural statistics (Module 0a/4) - Introduction

Year: 2017

Abstract: Prepared by the Global Strategy to improve agricultural and rural statistics, this training material aims to provide basic knowledge and skills in agricultural statistics to data producers, in particular to statisticians with no or limited background in agriculture statistics, and to economists or agronomists with some basic knowledge in statistics. The following will be described: The agricultural statistics framework; Data sources; Statistics to be produced; Statistical units; Collection methods in relation to new technologies; Processing, analysis and dissemination; Statistics obtained.

Lead authoring unit/office: Statistics Division (ESS)

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Basic training on agricultural statistics (Module 0b/4) - Statistical review

Year: 2017

Abstract: Prepared by the Global Strategy to improve agricultural and rural statistics, this training material aims to provide basic knowledge and skills in agricultural statistics to data producers, in particular to statisticians with no or limited background in agriculture statistics, and to economists or agronomists with some basic knowledge in statistics.

Lead authoring unit/office: Statistics Division (ESS)

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Basic training on agricultural statistics (Module 1/4) - Overview of the general framework of agricultural statistics

Year: 2017

Abstract: Prepared by the Global Strategy to improve agricultural and rural statistics, this training material aims to provide basic knowledge and skills in agricultural statistics to data producers, in particular to statisticians with no or limited background in agriculture statistics, and to economists or agronomists with some basic knowledge in statistics. The topics included in this module are the following: Scope of the course; Conceptual framework of the global strategy to improve agricultural and rural statistics and its economic, social and environmental dimensions; Strategic plans for agricultural and rural statistics (SPARS) and National strategies for the development of statistics (NSDS), Users and uses of agricultural statistics.

Lead authoring unit/office: Statistics Division (ESS)

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Basic training on agricultural statistics (Module 2/4) - Statistics to be produced, producers, data sources, statistical units and data collection methods

Year: 2017

Abstract: Prepared by the Global Strategy to improve agricultural and rural statistics, this training material aims to provide basic knowledge and skills in agricultural statistics to data producers, in particular to statisticians with no or limited background in agriculture statistics, and to economists or agronomists with some basic knowledge in statistics. This module is the core of the agricultural statistics course. Its objective is to allow the targeted audience to gain a good understanding of agricultural statistics and basic methodological issues. The following topics are developed: Statistics to be produced: they correspond to the demand for agricultural statistics (what people want to know); Data producers: centralized and decentralized statistical systems; The main sources of agricultural statistics; Statistical units in relation to specific topics; Data collection and the specific features of the agricultural sector.

Lead authoring unit/office: Statistics Division (ESS)

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Basic training on agricultural statistics (Module 3/4) - Data processing, analysis and dissemination

Year: 2017

Abstract: Prepared by the Global Strategy to improve agricultural and rural statistics, this training material aims to provide basic knowledge and skills in agricultural statistics to data producers, in particular to statisticians with no or limited background in agriculture statistics, and to economists or agronomists with some basic knowledge in statistics. This module describes all the processing and analysis operations on a data set to obtain the desired information from a source such as a census, sample survey or administrative record. It also covers concepts relating to area and yield, resulting in methods of evaluating production and crop forecasting.  

Lead authoring unit/office: Statistics Division (ESS)

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Basic training on agricultural statistics (Module 4/4) - Analytical frameworks and derived statistics

Year: 2017

Abstract: Prepared by the Global Strategy to improve agricultural and rural statistics, this training material aims to provide basic knowledge and skills in agricultural statistics to data producers, in particular to statisticians with no or limited background in agriculture statistics, and to economists or agronomists with some basic knowledge in statistics. The following topics will be covered: Economic accounts for agriculture and environmental-economic accounts (subnational and national level); Costs of production statistics; Post-harvest losses: types of post-harvest losses; methods of estimating post-harvest losses; loss estimation and magnitude; factors influencing post-harvest losses; impacts of post-harvest losses. Agricultural producer prices and price indexes (monthly and annual); Food security and food balance sheets.

Lead authoring unit/office: Statistics Division (ESS)

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Training course on nomadic & semi-nomadic livestock (Module 0/3) - Users' guide

Year: 2017

Abstract: Prepared by the Global Strategy to improve agricultural and rural statistics (GSARS), this training material on the enumeration of nomadic and semi-nomadic (transhumant) livestock targets decision makers, statisticians, analysts and data producers from National Statistical Systems (NSOs or statistical departments within the Ministry of Agriculture, for example) as well as analysts, researchers, teaching staff and students from training centres of statistics and agriculture and other relevant institutions. The present users’ guide describes the intended objectives, content and target audience of the training material on the enumeration of nomadic and semi- nomadic (transhumant livestock) provided on the Global Strategy website. It provides recommendations on organizational aspects of training on enumeration of nomadic and semi nomadic (transhumant) livestock. An example of the course content and possible agenda is also included in the appendix.

Lead authoring unit/office: Statistics Division (ESS)

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Training course on nomadic & semi-nomadic livestock (Module 1/3) - General information and advocacy

Year: 2017

Abstract: Prepared by the Global Strategy to improve agricultural and rural statistics (GSARS), this training material on the enumeration of nomadic and semi-nomadic (transhumant) livestock targets decision makers, statisticians, analysts and data producers from National Statistical Systems (NSOs or statistical departments within the Ministry of Agriculture, for example) as well as analysts, researchers, teaching staff and students from training centres of statistics and agriculture and other relevant institutions. The topics covered by the first module of this training material are the following: 1. Definition of nomadism and semi-nomadism (transhumance); 2. Why enumerate nomadic and semi-nomadic (transhumant) livestock; 3. Integrating enumeration of nomadic and semi-nomadic (transhumant) livestock into the mainstream Agricultural Survey Framework; 4. General recommendations for the enumeration of nomadic and semi-nomadic (transhumant) livestock.

Lead authoring unit/office: Statistics Division (ESS)

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