Methods and Standards

In response to a growing demand for high-quality and internationally-comparable statistics, FAO develops, implements and promotes methods and standards to guide national data producers in generating and using sound statistics. In particular, the Organization is committed to provide national statistical systems with internationally recognized definitions, concepts and classifications as well as methodological guidance for the production of high quality statistics related to food and agriculture.

This interface allows you to search for statistical classifications, guidelines and handbooks, technical reports, working papers and methodological documents, and capacity development resources. You can search by SUBJECT (general, agriculture, forestry, fishery and aquaculture, and natural resources) or use the ADVANCED SEARCH to search by keyword, country, language and lead authoring unit/office. Comments, suggestions and inquiries can be addressed to: [email protected].

General (including food and nutrition)

This section provides the main statistical classifications maintained and/or used by FAO.

Central Product Classification (CPC) version 2.1

General information

Status

Operational

Website

https://unstats.un.org/unsd/classifications/Econ/cpc

Custodian

United Nations Statistics Division

Year Published

2015

Availability

English only

Purpose of the Classification

Statistical Domain

Economic statistics

Purpose

The Central Product Classification (CPC) constitutes a comprehensive classification of all goods and services. CPC presents categories for all products that can be the object of domestic or international transactions or that can be entered into stocks. It includes products that are an output of economic activity, including transportable goods, non-transportable goods and services. CPC, as a standard central product classification, was developed to serve as an instrument for assembling and tabulating all kinds of statistics requiring product detail. Such statistics may cover production, intermediate and final consumption, capital formation, foreign trade or prices. They may refer to commodity flows, stocks or balances and may be compiled in the context of input/output tables, balance of payments and other analytical presentations. The CPC classifies products based on the physical characteristics of goods or on the nature of the services rendered. CPC was developed primarily to enhance harmonization among various fields of economic and related statistics and to strengthen the role of national accounts as an instrument for the coordination of economic statistics. It provides a basis for recompiling basic statistics from their original classifications into a standard classification for analytical use.

Methodology

Concept Being Classified

Goods, services

Relationship to Other International Classifications

HS 2012

With regard to transportable goods, a very close relationship exists between the Central Product Classification and the Harmonized System, as CPC subclasses in sections 0 to 4 generally constitute groupings and rearrangements of complete categories of the Harmonized System. As a result, a total of 1 617 CPC subclasses have been defined, using over 5 000 headings and subheadings of the 2012 Harmonized System as building blocks.

 

ISIC Revision 4

The Central Product Classification and the International Standard Industrial Classification of All Economic Activities are both general-purpose classifications, with the ISIC representing the activity side of these two interrelated United Nations classifications. Each subclass of the CPC consists of goods or services that are generally produced in a specific class or classes of the ISIC, Rev.4.

Classification Structure

Level

Level Name

Code Format

Number of Items

Level 1

Section

0

10 items

Level 2

Division

01

71 items

Level 3

Group

012

329 items

Level 4

Class

0123

1 229 items

Level 5

Subclass

01234

2 887 items

Revision Information

At the core of the revision process were several objectives, namely (a) to reflect in the CPC newly emerging products or products that better reflect changing production patterns; (b) to reflect outputs of newly defined industries of ISIC Revision 4; (c) to take into account the changes in the 2012 edition of the Harmonized Commodity Coding and Description System (HS); (d) to review the product detail necessary for statistics on agriculture, ICT and information products and (e) to review the conceptual basis of CPC, including issues concerning the scope of the classification and the definition of and distinction between goods and services.

 

In collaboration with the Food and Agriculture Organization of the United Nations (FAO), significant detail has been added in CPC Ver.2 in sections 0 and 2, related to agricultural and food products, fertilizers and agricultural machinery. Also fishery products in division 04 and forest products in divisions 03 and 31 have been updated.

Contact Information

United Nations Statistics Division

Economic Statistics Branch

Classifications Hotline

Email:

[email protected]

Fax:

+1 917 367 0135

Address:

United Nations Statistics Division

DC-2 15th Floor

2 UN Plaza New York, NY 10017

Central Product Classification (CPC) version 2.1 expanded for agriculture

General information

Status

Operational

Website

https://unstats.un.org/unsd/classifications/Econ/cpc

Custodian

United Nations Statistics Division

Year Published

2015

Availability

English only

Purpose of the Classification

Statistical Domain

Economic statistics

Purpose

The Central Product Classification (CPC) constitutes a comprehensive classification of all goods and services. CPC presents categories for all products that can be the object of domestic or international transactions or that can be entered into stocks. It includes products that are an output of economic activity, including transportable goods, non-transportable goods and services. CPC, as a standard central product classification, was developed to serve as an instrument for assembling and tabulating all kinds of statistics requiring product detail. Such statistics may cover production, intermediate and final consumption, capital formation, foreign trade or prices. They may refer to commodity flows, stocks or balances and may be compiled in the context of input/output tables, balance of payments and other analytical presentations. The CPC classifies products based on the physical characteristics of goods or on the nature of the services rendered. CPC was developed primarily to enhance harmonization among various fields of economic and related statistics and to strengthen the role of national accounts as an instrument for the coordination of economic statistics. It provides a basis for recompiling basic statistics from their original classifications into a standard classification for analytical use.

Methodology

Concept Being Classified

Goods, services

Relationship to Other International Classifications

HS 2012

With regard to transportable goods, a very close relationship exists between the Central Product Classification and the Harmonized System, as CPC subclasses in sections 0 to 4 generally constitute groupings and rearrangements of complete categories of the Harmonized System. As a result, a total of 1,617 CPC subclasses have been defined, using over 5,000 headings and subheadings of the 2012 Harmonized System as building blocks.

 

ISIC Revision 4

The Central Product Classification and the International Standard Industrial Classification of All Economic Activities are both general-purpose classifications, with the ISIC representing the activity side of these two interrelated United Nations classifications. Each subclass of the CPC consists of goods or services that are generally produced in a specific class or classes of the ISIC, Rev.4.

Classification Structure

Level

Level Name

Code Format

Number of Items

Level 1

Section

0

10 items

Level 2

Division

01

71 items

Level 3

Group

012

329 items

Level 4

Class

0123

1229 items

Level 5

Subclass

01234

2887 items

Revision Information

At the core of the revision process were several objectives, namely (a) to reflect in the CPC newly emerging products or products that better reflect changing production patterns; (b) to reflect outputs of newly defined industries of ISIC Revision 4; (c) to take into account the changes in the 2012 edition of the Harmonized Commodity Coding and Description System (HS); (d) to review the product detail necessary for statistics on agriculture, ICT and information products and (e) to review the conceptual basis of CPC, including issues concerning the scope of the classification and the definition of and distinction between goods and services.

 

In collaboration with the Food and Agriculture Organization of the United Nations (FAO), significant detail has been added in CPC Ver.2 in sections 0 and 2, related to agricultural and food products, fertilizers and agricultural machinery. Also fishery products in division 04 and forest products in divisions 03 and 31 have been updated.

Contact Information

United Nations Statistics Division

Economic Statistics Branch

Classifications Hotline

Email:

[email protected]

Fax:

+1 917 367 0135

Address:

United Nations Statistics Division

DC-2 15th Floor

2 UN Plaza

New York, NY 10017

Classification of Individual Consumption According to Purpose (COICOP)

General information

Status

Operational

Website

https://unstats.un.org/unsd/classifications/unsdclassifications

Custodian

United Nations Statistics Division

Year Adopted

2018

Year Published

2018

Availability

English only

Purpose of the Classification

Statistical Domain

Economic statistics

Purpose

The Classification of Individual Consumption According to Purpose (COICOP) is the international reference classification of household expenditure. The objective of COICOP is to provide a framework of homogeneous categories of goods and services, which are considered a function or purpose of household consumption expenditure. COICOP is an integral part of the System of National Accounts (SNA), but it is also used in several other statistical areas, such as: household expenditure statistics based on household budget surveys and the analysis of living standards; consumer price indices; international comparisons of gross domestic product (GDP) and its component expenditures through purchasing power parities; and statistics relating to culture, sports, food, health, and tourism.

Methodology

Concept Being Classified

Expenditures, goods, services

Relationship to Other International Classifications

Relation to COPNI, COPP, COFOG


COICOP 2018 is divided into three parts:

• Divisions 01 to 13 Individual consumption expenditure of households;

• Division 14 Individual consumption expenditure of NPISH;

• Division 15 Individual consumption expenditure of general government.


The purpose breakdowns within Divisions 14 and 15 of COICOP 2018 replicate the purposes in the classifications for NPISH in COPNI and general government in COFOG. Thus, once the consumption expenditures of NPISHs and general government have been classified according to COPNI and COFOG, the individual consumption expenditures in these two classifications can be transferred directly into Divisions 14 and 15 of COICOP 2018.


Relation to CPC

The Central Product Classification (CPC) is closely linked with COICOP, since expenditures on products are the basic building blocks of COICOP classes, and correspondences can be established between categories in the two classifications.


Relation to ISCED

The International Standard Classification of Education (ISCED 2011) of the United Nations Educational, Scientific and Cultural Organization (UNESCO) is used to define the breakdown of educational services in Division 10 (Education). The content of Division 10 was modified to better align it with ISCED 2011.


Relation to ICHA

Division 06 (Health) was considerably revised to improve the consistency of COICOP 2018 with the International classification for health accounts (ICHA). This will allow the reconciliation of health accounting with the SNA and its accompanying classifications.

Classification Structure

Level

Level Name

Code Format

Number of Items

Level 1

Section

00

15 items

Level 2

Division

0

63 items

Level 3

Group

0

186 items

Level 4

Class

0

338 items

Revision Information

Year Adopted: 2018

 

Previous version: COICOP 1999

 

Official Adopting Entity:

UN Statistical Commission

 

Coordinating Entity:

United Nations Expert Group on International Statistical Classifications

 

Reason for Latest Revision:

The new COICOP 2018 reflects the significant changes in goods and services in some areas, improves the links of COICOP to other classifications, and addresses emerging statistical and policy needs of several international organizations.

Contact Information

United Nations Statistics Division

Economic Statistics Branch

Classifications Hotline

Email:

[email protected]

Fax:

+1 917 367 0135

Address:

United Nations Statistics Division

DC-2 15th Floor

2 UN Plaza

New York, NY 10017

International Standard Industrial Classification of All Economic Activities (ISIC) Revision 4

General information

Status

Operational

Website

https://unstats.un.org/unsd/classifications/Econ/isic

Custodian

United Nations Statistics Division

Year Adopted

2006

Year Published

2007

Availability

Available in ArabicChineseEnglishFrenchRussian and Spanish

Purpose of the Classification

Statistical Domain

Economic statistics

Purpose

The purpose of the International Standard Industrial Classification of All Economic Activities (ISIC) is to provide a set of activity categories that can be utilized for the collection and reporting of statistics according to such activities. Since the adoption of the original version of ISIC in 1948, ISIC has provided guidance to countries in developing national activity classifications and has become an important tool for comparing statistical data on economic activities at the international level. Wide use has been made of ISIC, both nationally and internationally, in classifying data according to kind of economic activity in the fields of economic and social statistics, such as for statistics on national accounts, demography of enterprises, employment and others.

Methodology

Concept Being Classified

Economic activities

Relationship

ISIC Rev. 4 - CPC Ver. 2.1

 

ISIC Rev. 4 - CPC Ver. 2

 

ISIC Rev. 4 - NACE Rev. 2

 

ISIC Rev. 4 - NAICS 2007

 

ISIC Rev. 4 - NAICS 2012

 

ISIC Rev. 4 - JSIC Rev. 13

Classification Structure

Level

Level Name

Code Format

Number of Items

Level 1

Section

A (one-letter alpha code  –  A to U

21 items

Level 2

Division

01

88 items

Level 3

Group

012

238 items

Level 4

Class

0123

420 items

Revision Information

Year Adopted: 2006

 

Previous version:

ISIC Revision 3.1 (2002)

https://unstats.un.org/unsd/classifications/Econ/ISIC#ISIC31

 

Correspondence Table ISIC Revision 3.1-Rev.4:

https://unstats.un.org/unsd/classifications/Family/Detail/27 

ISIC Revision 3 (1989)

https://unstats.un.org/unsd/classifications/Econ/ISIC#ISIC3

 

ISIC Revision 2 (1968)

https://unstats.un.org/unsd/classifications/Econ/ISIC#ISIC2

 

ISIC Revision 1 (1958)

https://unstats.un.org/unsd/classifications/Econ/ISIC#isic1

 

ISIC 1948

https://unstats.un.org/unsd/classifications/Econ/ISIC#ISIC0

 

Contact Information

United Nations Statistics Division

Economic Statistics Branch

Classifications Hotline

Email:

[email protected]

Fax:

+1 917 367 0135

Address:

United Nations Statistics Division

DC-2 15th Floor

2 UN Plaza

New York, NY 10017

Harmonized Commodity Description and Coding System 2012 (HS 2012)

General information

Status

Operational

Website

http://www.wcoomd.org/en/topics/nomenclature/instrument-and-tools/hs_nomenclature_2012/hs_nomenclature_table_2012.aspx

Custodian

World Customs Organization

Year Adopted

2009

Year Published

2012 (Last revised 2017)

Availability

English, French, German, Portuguese, Russian and Spanish

Purpose of the Classification

Statistical Domain

Economic statistics

Purpose

The Harmonized Commodity Description and Coding System generally referred to as 'Harmonized System' or simply 'HS' is a multipurpose international product nomenclature developed by the World Customs Organization (WCO). It comprises about 5,000 commodity groups; each identified by a six digit code, arranged in a legal and logical structure and is supported by well-defined rules to achieve uniform classification. The system is used by more than 200 countries and economies as a basis for their Customs tariffs and for the collection of international trade statistics. Over 98 % of the merchandise in international trade is classified in terms of the HS. The HS contributes to the harmonization of Customs and trade procedures, and the non-documentary trade data interchange in connection with such procedures, thus reducing the costs related to international trade. It is also extensively used by governments, international organizations and the private sector for many other purposes such as internal taxes, trade policies, monitoring of controlled goods, rules of origin, freight tariffs, transport statistics, price monitoring, quota controls, compilation of national accounts, and economic research and analysis. The HS is thus a universal economic language and code for goods, and an indispensable tool for international trade.

Main Users

Customs administrations and customs and/or economic unions; international organizations; importers/exporters/traders.

Methodology

Concept Being Classified

Goods

Relationship to Other International Classifications

HS 2012 - CPC Ver. 2.1

SITC Revision 4

SITC Revision 3

HS 2012 - SITC Rev.2

HS 2012 - SITC Rev.1

BEC Revision 4

Classification Structure

Level

Level Name

Code Format

Number of Items

Level 1

Section

IV

21 items

Level 2

Chapter

24

96 items

Level 3

4-digit heading

24.03

1 224 items

Level 4

6-digit subheading

2403.19

5 205 items

Revision Information

The latest revision, as well as the previous ones, were made on the basis of a permanent process, in order to keep the Harmonized System updated in light of developments in technology and changes in trade patterns.

 

In a press release dated 3 January 2012, issued at the occasion of the entry into force of the 5th edition of the Harmonized System Nomenclature, the main changes were described as follows : 'The 2012 version includes 220 sets of amendments: 98 relating to the agricultural sector; 27 to the chemical sector; 9 to the paper sector; 14 to the textile sector; 5 to the base metal sector; 30 to the machinery sector; and an additional 37 that apply to a variety of other sectors. Environmental and social issues are the major feature of these amendments, particularly the use of the HS as the standard for classifying and coding goods of specific importance to food security and the early warning data system of the Food and Agriculture Organization of the United Nations (FAO). HS 2012 also features new classification provisions for specific chemicals controlled under the Rotterdam Convention and ozone-depleting substances controlled under the Montreal Protocol to further respond to global environment protection efforts. Changing trade patterns too played a role in the new version as did efforts to simplify the HS, recognized universally as a multi-purpose tool and used extensively as a basis for Customs tariffs and for the collection of national and international trade statistics.

 

From the legal point of view, according to the International Convention on the Harmonized Commodity Description and Coding System, the Harmonized System is not amended between two successive editions (presently issued every 5 years). The amendments finalized during each review cycle are published as soon as they are agreed in the successive reports of the Review Sub-Committee (which met twice a year) and, subsequently, of the Harmonized System Committee (which met twice a year) as soon as they have been approved, under the status of “provisionally adopted amendments”. As far as the availability of information regarding scheduled corrections between two revisions is concerned, it should be noted that all the relevant working documents and reports (Harmonized System Committee / Review Sub-Committee / Scientific Sub-Committee) are available on our website – in electronic PDF format – to WCO Members (*) as soon as they have been issued. So, during a particular review cycle, the Members which are not attending HSC, RSC and SSC sessions on a regular basis are nevertheless informed about the development of the list of amendments agreed for further implementation.

(*) : Specific area within our web site, restricted to WCO Members (and some intergovernmental organizations, e.g. WTO) and accessible through a password.

Contact Information

World Customs Organization

Tariff and Trade Affairs Directorate

Director

Email:

[email protected]

Website:

http://www.wcoomd.org

Address:

Rue du Marché, 30

B-1210 Brussels, Belgium

Standard International Trade Classification (SITC) Revision 4

General information

Status

Operational

Website

http://unstats.un.org/unsd/trade/sitcrev4.htm

Custodian

United Nations Statistics Division

Year Adopted

2006

Year Published

2006

Availability

Arabic, Chinese, English, French, Russian and Spanish

Purpose of the Classification

Statistical Domain

Economic statistics

Purpose

For compiling international trade statistics on all merchandise entering international trade, and to promote international comparability of international trade statistics. The commodity groupings of SITC reflect (a) the materials used in production, (b) the processing stage, (c) market practices and uses of the products, (d) the importance of the commodities in terms of world trade, and (e) technological changes.

Main Users

Data compilers, economists, researchers and market analysts, trade policy analyst

Methodology

Concept Being Classified

Goods

Relationship to Other International Classifications

HS 2012

basically the same The HS structure is foremost based on material composition of the goods, not so much the use of the goods

 

SITC Rev.4 - HS 2007

basically the same The HS structure is foremost based on material composition of the goods, not so much the use of the goods

 

BEC Revision 4

basically the same BEC is much more based on use than SITC

 

SITC Rev.4 - CPC Ver. 2

 

CPC covers not only goods but also services CPC goods part is similar to SITC, but contains only 5 main sections, whereas SITC is built on 10 main sections The concept of CPC goods differs mainly in respect to the classification of recorded media

 

SITC Rev.4 - ISIC

ISIC is activity based and not based on products

 

SITC Rev.4 - HS 2002

basically the same The HS structure is foremost based on material composition of the goods, not so much the use of the goods

 

HS 1996

basically the same The HS structure is foremost based on material composition of the goods, not so much the use of the goods

 

SITC Rev.4 - HS 1992

basically the same The HS structure is foremost based on material composition of the goods, not so much the use of the goods

 

SITC Rev. 4 - CN 2007

SITC Rev. 4 - CN 2008

SITC Rev. 4 - CN 2009

SITC Rev. 4 - CN 2010

SITC Rev. 4 - CN 2011

SITC Rev. 4 - CN 2012

SITC Rev. 4 - CN 2013

SITC Rev. 4 - CN 2014

SITC Rev. 4 - CN 2015

SITC Rev. 4 - CN 2016

Classification Structure

Level

Level Name

Code Format

Number of Items

Level 1

Section

0

9 items

Level 2

Division

01

67 items

Level 3

Group

012

262 items

Level 4

Sub-group

012.1

1023 items

Level 5

Heading

012.13

2970 items

Revision Information

 

Year Adopted:

SITC 1950

 


 

SITC Revised

1974

SITC Revision 2

1985

SITC Revision 3

http://unstats.un.org/unsd/cr/registry/regcst.asp?Cl=14

2006

SITC Revision 4

http://unstats.un.org/unsd/trade/sitcrev4.htm

http://unstats.un.org/unsd/trade/conversions/HS%20Correlation%20and%20Conversion%20tables.htm

http://unstats.un.org/unsd/trade/conversions/HS%20Correlation%20and%20Conversion%20tables.htm

 

Official Adopting Entity:

UN Statistical Commission

 

Coordinating Entity:

Inter-Agency Task Force on International Trade Statistics

 

Reason for Latest Revision:

Major change was updating of the most recent goods with up-to-date technology and current economic importance. SITC Rev 4 retains the overall structure of SITC, revision 3 and consists of the same number of sections and groups. The changes made were at the level of basic heading and some subgroups. It took into considerations changes in codes of HS88 (which SITC Rev.3 based on) and HS07 (which SITC Rev.4 based on)

Correspondence with Other Classifications

HS 2012

http://unstats.un.org/unsd/trade/conversions/HS%20Correlation%20and%20Conversion%20tables.htm

SITC Rev.4 - HS 2007

http://unstats.un.org/unsd/publication/SeriesM/SeriesM_34rev4E.pdf

BEC Revision 4

http://unstats.un.org/unsd/trade/conversions/HS%20Correlation%20and%20Conversion%20tables.htm

SITC Rev.4 - CPC Ver. 2

(link not available)

SITC Rev.4 - ISIC

http://unstats.un.org/unsd/trade/conversions/HS%20Correlation%20and%20Conversion%20tables.htm

SITC Rev.4 - HS 2002

http://unstats.un.org/unsd/trade/conversions/HS%20Correlation%20and%20Conversion%20tables.htm

HS 1996

http://unstats.un.org/unsd/trade/conversions/HS%20Correlation%20and%20Conversion%20tables.htm

SITC Rev.4 - HS 1992

SITC Rev. 4 - CN 2007

SITC Rev. 4 - CN 2008

SITC Rev. 4 - CN 2009

SITC Rev. 4 - CN 2010

SITC Rev. 4 - CN 2011

SITC Rev. 4 - CN 2012

SITC Rev. 4 - CN 2013

SITC Rev. 4 - CN 2014

SITC Rev. 4 - CN 2015

SITC Rev. 4 - CN 2016

Contact Information

United Nations Statistics Division

Trade Statistics Branch

UN Comtrade Hotline

Email:

[email protected]

Classification of the Functions of Government (COFOG)

General information

Status

Operational

Website

https://unstats.un.org/unsd/classifications/Econ

Custodian

United Nations Statistics Division

Year Adopted

1999

Year Published

2000

Availability

Arabic, Chinese, English, French, Russian and Spanish

Purpose of the Classification

Statistical Domain

FAOSTAT Government Expenditure 

 

SDG Indicator 2.a.1 

Purpose

To classify the purpose of transactions such as outlays on final consumption expenditure, intermediate consumption, gross capital formation and capital and current transfers, by general government.

Methodology

Concept Being Classified

Government activities, expenditures, goods, services

Relationship to Other International Classifications

Major Differences (Scope, Structure, and Concepts):

ISIC Revision 3.1

Classification Structure

Level

Level Name

Code Format

Number of Items

Level 1

Divisions (two-digit)

-

x items

Level 2

Groups (three-digit)

-

x items

Level 3

Classes (four-digit)

-

x items

Revision Information

Chronology of revisions/versions of the classification:

 

Year Adopted:

1999

 

Title or Version Number:

COFOG

 

Website:                                          

https://unstats.un.org/unsd/classifications/Econ

 

Official Adopting Entity:

UN Statistical Commission

 

Coordinating Entity:

Organization for Economic Co-operation and Development

Contact Information

United Nations Statistics Division

Industrial and Energy Statistics Section

Email:

[email protected]

Telephone:

+1 212 963 4600

Fax:

+1 212 963 0623 

Address:

United Nations Statistics Division

DC2-1414

2 UN Plaza

New York, NY 10017

General (including food and nutrition)

This section contains the main statistical guidelines and handbooks produced by FAO.

Documents listed under the general subject cover topics that are more overarching in nature and encompass several dimensions of the food and agriculture sector (in a broad sense). They include for example: broad conceptual frameworks (e.g. System of Environmental-Economic Accounts, SDG indicators, etc.), economic-related statistics and frameworks (e.g. food prices, costs of production, etc.), social-related statistics and frameworks (labour and employment, gender, etc.) and food and nutrition statistics and frameworks (e.g. food balance sheets, food loss, food consumption, food security and hunger, etc.).

Guidelines on data disaggregation for SDG Indicators using survey data

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

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

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)

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

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)

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

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

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

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

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)

français

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

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)

françaisEspañol

Guidelines on the Integrated Survey Framework

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)

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

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)

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

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)

General (including food and nutrition)

This section contains the main technical reports, working papers and methodological documents produced by FAO. They include:

  • FAO Statistical Development Series
  • FAO Statistics Working Paper Series
  • Global Strategy to Improve Agricultural and Rural Statistics (GSARS) Technical Report and Working Paper Series
  • FAO methodological documents on the SDG indicators under its custodianship

Documents listed under the general subject cover topics that are more overarching in nature and encompass several dimensions of the food and agriculture sector (in a broad sense). They include for example: broad conceptual frameworks (e.g. System of Environmental-Economic Accounts, SDG indicators, etc.), economic-related statistics and frameworks (e.g. food prices, costs of production, etc.), social-related statistics and frameworks (labour and employment, gender, etc.) and food and nutrition statistics and frameworks (e.g. food balance sheets, food loss, food consumption, food security and hunger, etc.).

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

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

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

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)

SDG-indicator 2.1.1 Metadata

Abstract: This document reflects the latest reference metadata information available on SDG-indicator 2.1.1 "Prevalence of undernourishment". Last updated: March 2020.

Lead authoring unit/office: FAO

العربيةРусский

SDG-indicator 2.4.1 Metadata

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: September 2020.

Lead authoring unit/office: FAO

SDG-indicator 2.a.1 Metadata

Abstract: This document reflects the latest reference metadata information available on SDG-indicator 2.a.1 " Public Investment in agriculture". Last updated: March 2020.

Lead authoring unit/office: FAO

العربيةРусский

SDG-indicator 2.c.1 Metadata

Abstract: This document reflects the latest reference metadata information available on SDG-indicator 2.c.1 "Indicator of (food) price anomalies". Last updated: September 2020.

Lead authoring unit/office: FAO

العربيةРусский

Measuring SDG Indicator 5.a.1 - Background paper

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

françaisEspañol

SDG-indicator 15.2.1 Metadata

Abstract: This document reflects the latest reference metadata information available on SDG-indicator 15.2.1 "Progress towards sustainable forest management". Last updated: September 2020.

Lead authoring unit/office: FAO

العربيةРусский

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

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)

SDG-indicator 6.4.2 Metadata

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: August 2020.

Lead authoring unit/office: FAO

العربيةРусский

SDG-indicator 14.4.1 Metadata

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: July 2020.

Lead authoring unit/office: FAO

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

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

SDG-indicator 15.1.1 Metadata

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: March 2020.

Lead authoring unit/office: FAO

العربيةРусский

SDG-indicator 2.1.2 Metadata

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: March 2020.

Lead authoring unit/office: FAO

العربيةРусский

SDG-indicator 2.5.2 Metadata

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 2020.

Lead authoring unit/office: FAO

Methodological note for SDG Indicator 2.4.1

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

SDG-indicator 5.a.2 Metadata

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: October 2019.

Lead authoring unit/office: FAO

The new FAO global database on agriculture investment and capital stock

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

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

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)

SDG-indicator 12.3.1 Metadata

Abstract: This document reflects the latest reference metadata information available on SDG-indicator 12.3.1 "Global Food Loss and Waste". Last updated: October 2019.

Lead authoring unit/office: FAO

SDG-indicator 14.7.1 Metadata

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: March 2019.

Lead authoring unit/office: FAO

Русский

SDG-indicator 2.5.1 Metadata

Abstract: This document reflects the latest reference metadata information available on SDG-indicator 2.5.1 "Number of plant and animal genetic resources for food and agriculture secured in medium or long term conservation facilities". Last updated: March 2019.

Lead authoring unit/office: FAO

العربيةРусский

SDG-indicator 6.4.1 Metadata

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: March 2019.

Lead authoring unit/office: FAO

Русский

Methodological paper on SDG sub-indicator 12.3.1.a

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

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

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

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)

SDG-indicator 2.3.1 Metadata

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: October 2018.

Lead authoring unit/office: FAO

Русский

SDG-indicator 2.3.2 Metadata

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: October 2018.

Lead authoring unit/office: FAO

Русский

Pilot testing on the food loss index

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)

SDG-indicator 14.6.1 Metadata

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: May 2018.

Lead authoring unit/office: FAO

Русский

SDG-indicator 14.b.1 Metadata

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: May 2018.

Lead authoring unit/office: FAO

Русский

Master sampling frames - The field experiments conducted in Nepal

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)

SDG-indicator 5.a.1 Metadata

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: October 2017.

Lead authoring unit/office: FAO

The social dimension of rural statistics

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

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

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

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)

SDG-indicator 15.4.2 Metadata

Abstract: This document reflects the latest reference metadata information available on SDG-indicator 15.4.2 "Mountain Green Cover Index". Last updated: July 2017.

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

A minimum set of environmental indicators for improving rural statistics

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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)

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

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

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

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

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)

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

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

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

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

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

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

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

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

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

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

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

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)

General (including food and nutrition)

This section provides the main capacity development resources produced by FAO. They include:

  • Global Strategy to Improve Agricultural and Rural Statistics (GSARS) training materials
  • E-learning courses related to the SDG indicators under FAO custodianship
  • Other e-learning courses, training material or webinars.
E-learning course | System of Environmental-Economic Accounting (SEEA)

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

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

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

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

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

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 Indicator 6.4.1 - Change in water-use efficiency over time

Abstract: The course provides guidance on the rationale and the main characteristics of Indicator 6.4.1, and on how to compute the two dimensions constituting the indicator: the hydrologic and the economic component. It also highlights possible challenges related to data availability, and the impact that monitoring results may have on national decision-making and identification of development policies.

Lead authoring unit/office: FAO

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E-learning course | SDG indicators 15.1.1 and 15.2.1 - Forest area and sustainable forest management

Abstract: This course has been developed to guide countries in reporting on Indicators 15.1.1 and 15.2.1. It illustrates the rationale of the indicators, the definitions and methodologies on which monitoring activities are based, and explains the process and the tools available for compiling data related to the two indicators through the Global Forest Resources Assessment (FRA) Programme.

Lead authoring unit/office: FAO

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

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)

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

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)

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

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

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

françaisEspañolРусский

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

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

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 6.4.2 - Level of water stress

Abstract: This course provides tools, methods and processes to support countries in monitoring and reporting on SDG Indicator 6.4.2 "Level of water stress: freshwater withdrawal in percentage of available freshwater resources".

Lead authoring unit/office: FAO

françaisEspañolРусский

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

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

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

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

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

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

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

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

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

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

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

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

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

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)

français

Training course on food balance sheets - Food availability

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Agriculture

This section provides the main statistical classifications maintained and/or used by FAO.

FAOSTAT Commodity List (FCL)

General information

Status

Operational

Website

FAOSTAT commodity list (to be discontinued soon)

Custodian

http://www.fao.org/economic/ess/ess-standards/commodity/comm-chapters/en/  

Custodian

Food and Agriculture Organization of the United Nations

Year Published

1960's

Availability

English, French and Spanish

Purpose of the classification

Statistical Domain

Agriculture statistics

Purpose

FCL is a unique commodity tree-based classification established by FAO for the purpose of bringing together Agricultural Production and Trade data into the framework of Food Balance sheet and Commodity balances.

Main Applications

Agricultural statistics, agricultural censuses, Food Balance Sheets.

Main Users

FCL has been phased out and is currently used in the context of mapping CPC and HS classifications for internal purpose only.

Methodology

Scope

The FAOSTAT Commodity List (FCL) is the classification of food and agriculture commodities (originally 683 items grouped in 20 chapters) that has been used in FAOSTAT since the 1960s.

In the new FAOSTAT Statistical Working System, the FCL has been replaced by the Central Product Classification of the United Nations (CPC) expanded for agriculture, in order to ensure a better alignment with international standards.

Concept Being Classified

Crops, livestock and their derived products

Relationship to Other International Classifications

Related To:

Central Product Classification (CPC) Ver. 2.1

Harmonized Commodity Description and Coding System (HS) 2017

 

Major Differences (Scope, Structure, and Concepts):


Discrepancies can be noticed in structure, as the FCL follows the pattern of the so-called “commodity tree”, in which the parent item is the primary commodity (e.g. wheat) and the children items are its derived products (e.g. flour made from wheat).

Classification Structure

Level

Level Name

Code Format

Number of Items

Level 1

Groups

00

23 items

Level 2

Commodities

0000

776 items

Revision Information

Chronology of revisions/versions of the classification:

Previous version:

Definition and Classification of Commodities (1994)

(Available in English, French and Spanish

 

Official Adopting Entity:

Food and Agriculture Organization of the United Nations


Coordinating Entity:

Food and Agriculture Organization of the United Nations


Next Review:

N/A


Reason for Latest Revision:

Additional domains have been included.


Major Changes:

Pesticides, fertilizers and machineries commodities have been added.

Contact Information

Food and Agriculture Organization of the United Nations

Statistics Division (ESS)

Contact Name:

Salar Tayyib

Email:

[email protected]

Telephone:

+39 06570 52548

Address:

Viale delle Terme di Caracalla, 1

00153 Rome, Italy

Classification of livestock for the agricultural census

General information

Status

Operational

Website

http://www.fao.org/3/a-i4913e.pdf

Custodian

Food and Agriculture Organization of the United Nations

Year Published

2015

Availability

Arabic, Chinese, English, French, Russian and Spanish

Purpose of the Classification

Statistical Domain

Agriculture statistics

Purpose

The classification of livestock covers all livestock of any type being raised on the holding; livestock refers to all animals, birds and insects kept or reared in captivity mainly for agricultural purposes (domestic animals such as cats and dogs are excluded, unless they are being raised for food or other agricultural purposes).

Main Applications

Agricultural statistics and agricultural censuses

Main Users

Ministries of Agriculture and National Statistical Offices carrying out agricultural censuses

Methodology

Scope

The classification of livestock covers all livestock of any type being raised on the holding; livestock refers to all animals, birds and insects kept or reared in captivity mainly for agricultural purposes (domestic animals such as cats and dogs are excluded, unless they are being raised for food or other agricultural purposes). The animals raised include those present on the holding, as well as those being grazed on communal grazing land or in transit at the time of enumeration; bees are counted in terms of number of hives. A holding raises an animal if it has primary responsibility for looking after the animal on a long-term basis and making day-to-day decisions about its use, regardless of ownership. If countries wish to subdivide a livestock type by breed or raising method, they may expand the classification accordingly.

Concept Being Classified

Goods, animals

Relationship to Other International Classifications

Related To:

Classification of livestock - Central Product Classification (CPC) Ver. 2.1

 

Major Differences (Scope, Structure, and Concepts):

No major differences; however, differently from livestock in CPC, this classification is focused on the livestock raised on the holding exclusively. This results in only minor differences as compared to CPC in its structure. The classification of livestock has a two-level structure. No major differences.

Classification Structure

Level

Level Name

Code Format

Number of Items

Level 1

Group

0

8 items

Level 2

Class

00

26 items

Revision Information

Chronology of revisions/versions of the classification:

 

Website:

http://www.fao.org/3/a-i4913e.pdf

 

Official Adopting Entity:

Food and Agriculture Organization of the United Nations

 

Coordinating Entity:

Food and Agriculture Organization of the United Nations

 

Next Review:

2025

 

Reason for Latest Revision:

The revision took place as part of the WCA periodical review; the aim was to enhance harmonization with the latest CPC Ver.2.1.

 

Major Changes:

Higher harmonization with CPC.

Contact Information

Food and Agriculture Organization of the United Nations

Statistics Division (ESS)

Contact Name:

Jairo Castano

Email:

[email protected]

Telephone:

+39 06 570 55166

Address:

Viale delle Terme di Caracalla, 1

00153 Rome, Italy

Classification of machinery and equipment for the agricultural census

General information

Status

Operational

Website

http://www.fao.org/3/a-i4913e.pdf

Custodian

Food and Agriculture Organization of the United Nations

Year Published

2015

Availability

ArabicChineseEnglishFrenchRussian and Spanish

Purpose of the Classification

Statistical Domain

Agriculture statistics

Purpose

The WCA classification of machinery and equipment classifies machinery and equipment (manually operated, animal-powered and machine-powered) used on the holding, wholly or partly for agricultural production (machinery and equipment used exclusively for purposes other than agricultural production are excluded, as well as those owned by the holder but not used). A broad concept of machinery and equipment is used for the agricultural census, covering all machinery, equipment and implements used as inputs to agricultural production (including everything from simple hand tools, such as a hoe, to complex machinery such as a combine harvester).

Main Applications

Agricultural statistics and agricultural censuses

Main Users

Ministries of Agriculture and National Statistical Offices carrying out agricultural censuses

Methodology

Scope

Machinery and equipment (manually operated, animal-powered and machine-powered) used on the agricultural holding.

Concept Being Classified

Goods, equipment

Relationship to Other International Classifications

Related To:

HS 2012

 

Major Differences (Scope, Structure, and Concepts):

Machinery in the HS is the most relevant for international trade while in this classification is the machinery and equipment most used on the holding therefore it is often more detailed than the HS. Three-digits (and three-level) structure in the Classification of Machinery and Equipment vs six-digit structure in the HS. The high level categories in the WCA livestock classification (groups) do not exist in the HS; lower level subclasses in links to the HS are 1:1 but at different level (can be at six or four digits).

Classification Structure

Level

Level Name

Code Format

Number of Items

Level 1

Group

0

3 items

Level 2

Class

00

5 items (including group levels without 2 digit codes: 7 items)

Level 3

Subclass

000

4 items (including group levels without 2 or 3 digit codes: 10 items)

Revision Information

Website:

http://www.fao.org/3/a-i4913e.pdf

 

Official Adopting Entity:

Food and Agriculture Organization of the United Nations

 

Coordinating Entity:

Food and Agriculture Organization of the United Nations

 

Next Review:

2025

 

Reason for Latest Revision:

The revision took place as part of the WCA periodical review; the aim was to inhance harmonization with the latest HS 2012.

 

Major Changes:

Minor changes: additional detail and higher harmonization with HS.

Correspondence with Other Classifications

 

Coding Index Available: 

No

Correspondence with Other Classifications:

 

Classification:

HS 2012

 

Correspondence Table: 

http://www.fao.org/3/a-i4913e.pdf

Contact Information

Food and Agriculture Organization of the United Nations

Statistics Division (ESS)

Contact Name:

Jairo Castano

Email:

[email protected]

Telephone:

+39 06 570 55166

Address:

Viale delle Terme di Caracalla, 1

00153 Rome, Italy

Indicative Crop Classification for the agricultural census (ICC) Version 1.1

General information

Status

Operational

Website

http://www.fao.org/3/a-i4913e.pdf

Custodian

Food and Agriculture Organization of the United Nations

Year Published

2015

Availability

ArabicChineseEnglishFrenchRussian and Spanish

Purpose of the Classification

Statistical Domain

Agriculture statistics

Purpose

This classification classifies crops growing in the agricultural holding.

Main Applications

Agricultural statistics and agricultural censuses.

Main Users

Ministries of Agriculture and National Statistical Offices

Methodology

Scope

ICC classifies crops growing in the agricultural holding.

Concept Being Classified

Goods, plants

Relationship to Other International Classifications

Related To:

Central Product Classification Ver.2.1

Indicative crop classification 1.1

 

Major Differences (Scope, Structure, and Concepts):

The key difference between product and crop classifications is that the ICC refers to crops that are grown in the field (i.e. to the plant), while the CPC refers to the product(s) generated from that crop; for example, “mustard” is an oilseed crop, whereas “mustard seed” is the oilseed product. ICC has four level structure and seven-digit codes. However, both high level and detailed categories are highly harmonized with CPC. No major difference.

Classification Structure

Level

Level Name

Code Format

Number of Items

Level 1

Group

0

9 items

Level 2

Class

0.00

63 items

Level 3

Sub-class

0.00.00

110 items

Level 4

Order

0.00.00.00

27 items

Revision Information

Chronology of revisions/versions of the classification:

 

Title or Version Number:

ICC Version 1.1

 

Website:

http://www.fao.org/3/a-i4913e.pdf

Indicative Crop Classification 1.0

http://www.fao.org/3/a-i4913e.pdf

 

Official Adopting Entity:

Food and Agriculture Organization of the United Nations

 

Coordinating Entity:

Food and Agriculture Organization of the United Nations

 

Next Review:

2025

 

Reason for Latest Revision:

The revision took place as part of the WCA periodical review; the aim was to enhance harmonization with the latest CPC Ver.2.1.

 

Major Changes:

Higher harmonization with Central Product Classification (CPC) Ver. 2.1, additional detail, revised codes.

 

Updates:

In the World Programme for the Census of Agriculture 2020. Volume I: Programme, concepts and definitions, a correspondence table is available between the current Ver.1.1 and the past version 1.0.

Contact Information

Food and Agriculture Organization of the United Nations

Statistics Division (ESS)

Contact Name:

Jairo Castano

Email:

[email protected]

Telephone:

+39 06 570 55166

Address:

Viale delle Terme di Caracalla, 10

0153 Rome, Italy

Agriculture

This section contains the main statistical guidelines and handbooks produced by FAO.

Documents listed under the agriculture subject cover topics such as Integrated agricultural survey programme (e.g. Master Sampling Frames, AGRISurvey, etc.), Agricultural Census and statistics and frameworks specific to crops, livestock and livestock products. 

Guidelines on improving and using administrative data in agricultural statistics

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

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)

françaisEspañol

Guidelines on methods for estimating livestock production and productivity

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)

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

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

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

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

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

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

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

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

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)

françaisEspañol

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

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

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)

françaisEspañolالعربية中文Русский

Guidelines for assessing country capacity to produce agricultural and rural statistics

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

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

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)

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

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

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

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

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

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

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

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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Agriculture

This section contains the main technical reports, working papers and methodological documents produced by FAO. They include:

  • FAO Statistical Development Series (agricultural census methods and standards, sample survey methods for agricultural surveys, the world census of agriculture and the system of economic accounts for food and agriculture);
  • FAO Statistics Working Paper Series (preliminary methodological and technical notes);
  • Global Strategy to Improve Agricultural and Rural Statistics (GSARS) Technical Report and Working Paper Series.

Documents listed under the agriculture subject cover topics such as Integrated agricultural survey programme (e.g. Master Sampling Frames, AGRISurvey, etc.), Agricultural Census and statistics and frameworks specific to crops, livestock and livestock products. 

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

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

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

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

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)

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

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

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

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

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

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

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

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

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

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

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

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

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)

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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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Agriculture

This section provides the main capacity development resources produced by FAO. They include:

  • Global Strategy to Improve Agricultural and Rural Statistics (GSARS) training materials
  • Other e-learning courses, training material or webinars.
E-learning course | Using the FAO methodology to compute damage and loss

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

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

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”

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)

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

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

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

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

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)

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

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

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

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

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

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

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

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?

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

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

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

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)

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

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

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

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

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

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

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?

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

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

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

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

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

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

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

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

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

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

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

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

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

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)

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

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?

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

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

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

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

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

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

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

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

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

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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Training course on nomadic & semi-nomadic livestock (Module 2/3) - Enumeration methods

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 second module of this training material are the following: 1. Methods for enumeration of nomadic and semi-nomadic (transhumant) livestock; 2. Data collection tools; 3. Indicative cost of enumerating nomadic and semi-nomadic (transhumant) livestock.

Lead authoring unit/office: Statistics Division (ESS)

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Training course on nomadic & semi-nomadic livestock (Module 3/3) - Survey designs and estimators

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 third module of this training material are the following: Introduction; 1. Survey designs and estimators for ground surveys; 2. Survey designs and estimators for aerial surveys.

Lead authoring unit/office: Statistics Division (ESS)

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Forestry

This section provides the main statistical classifications maintained and/or used by FAO.

Classification of Forest Products

General information

Status

Operational

Website

http://www.fao.org/forestry/statistics/80572/en/

Custodian

Food and Agriculture Organization of the United Nations 

Year Adopted

1981

Year Published

1982

Availability

Arabic, Chinese, English, French, Russian and Spanish

Purpose of the Classification

Statistical Domain

Forestry statistics

Purpose

This classification is designed to cover the wood and wood-based products for which Food and Agriculture Organization of the United Nations (FAO) and United Nations Economic Commission for Europe (UNECE) collect statistics on a regular basis. Included is wood taken from forests or from trees outside the forest, bark and cork; charcoal; wood and wood-based materials resulting from the first processing of the wood available from forest operations (including sawnwood, railway sleepers, veneer sheets, wood pulp and wood residues); and materials resulting from further processing of some of these materials (e.g. wood-based panels, paper and paperboard); recovered paper and recoverable wood products.

Main Users

Users of datasets on forest products disseminated by international organizations (FAOSTAT, UNECE's Timber database).

Methodology

Concept Being Classified

Goods

Relationships to Other International Classifications

Classification of Forest Products - SITC Rev.2

Classification of Forest Products - Harmonized System (HS)

Classification of Forest Products - Customs Cooperation Council Nomenclature for the Classification of Goods in Customs Tariffs (CCCN)

Classification of Forest Products - International Standard Industrial Classification of All Economic Activities (ISIC)

Classification of Forest Products - UN Classification by Broad Economic Categories (BEC)

Classification Structure

Level

Level Name

Code Format

Number of Items

Level 1

Section

0

9 items

Level 2

Division

01

67 items

Level 3

Group

012

262

Level 4

Subgroup

012.1

1023 items

Level 5

Heading

012.13

2970 items

Revision Information

Year Adopted:

1950

 

Title or Version Number:

SITC 1950

 

Website:

http://unstats.un.org/unsd/cr/registry/regdntransfer.asp?f=263

-

SITC Revised

1974

SITC Revision 2

http://unstats.un.org/unsd/cr/registry/regdntransfer.asp?f=221

1985

SITC Revision 3

http://unstats.un.org/unsd/cr/registry/regcst.asp?Cl=14

2006

SITC Revision 4

http://unstats.un.org/unsd/trade/sitcrev4.htm

http://unstats.un.org/unsd/trade/conversions/HS%20Correlation%20and%20Conversion%20tables.htm

http://unstats.un.org/unsd/trade/conversions/HS%20Correlation%20and%20Conversion%20tables.htm

http://unstats.un.org/unsd/cr/registry/regdntransfer.asp?f=259

 

Official Adopting Entity:

UN Statistical Commission

 

Coordinating Entity:

Inter-Agency Task Force on International Trade Statistics

 

Reason for Latest Revision:

Major change was updating of the most recent goods with up-to-date technology and current economic importance. SITC Rev 4 retains the overall structure of SITC, revision 3 and consists of the same number of sections and groups. The changes made were at the level of basic heading and some subgroups. It took into considerations changes in codes of HS88 (which SITC Rev.3 based on) and HS07 (which SITC Rev.4 based on)

Correspondence with Other Classifications

HS 2012

http://unstats.un.org/unsd/trade/conversions/HS%20Correlation%20and%20Conversion%20tables.htm

SITC Rev.4 - HS 2007

http://unstats.un.org/unsd/publication/SeriesM/SeriesM_34rev4E.pdf

BEC Revision 4

http://unstats.un.org/unsd/trade/conversions/HS%20Correlation%20and%20Conversion%20tables.htm

SITC Rev.4 - CPC Ver. 2

http://unstats.un.org/unsd/cr/registry/regso.asp?Ci=69&Lg=1

SITC Rev.4 - ISIC

http://unstats.un.org/unsd/trade/conversions/HS%20Correlation%20and%20Conversion%20tables.htm

SITC Rev.4 - HS 2002

http://unstats.un.org/unsd/trade/conversions/HS%20Correlation%20and%20Conversion%20tables.htm

HS 1996

http://unstats.un.org/unsd/trade/conversions/HS%20Correlation%20and%20Conversion%20tables.htm

SITC Rev.4 - HS 1992

http://unstats.un.org/unsd/trade/conversions/HS%20Correlation%20and%20Conversion%20tables.htm

SITC Rev. 4 - CN 2007

http://ec.europa.eu/eurostat/ramon/other_documents/combined%20nomenclature/conversion_tables/SITC4_CN07.zip

SITC Rev. 4 - CN 2008

http://ec.europa.eu/eurostat/ramon/other_documents/combined%20nomenclature/conversion_tables/CN08_SITC4.zip

SITC Rev. 4 - CN 2009

http://ec.europa.eu/eurostat/ramon/other_documents/combined%20nomenclature/conversion_tables/cn09_sitc4.zip

SITC Rev. 4 - CN 2010

http://ec.europa.eu/eurostat/ramon/other_documents/combined%20nomenclature/conversion_tables/CN2010_SITC4.zip

SITC Rev. 4 - CN 2011

http://ec.europa.eu/eurostat/ramon/other_documents/combined%20nomenclature/conversion_tables/CN2011_SITC4.zip

SITC Rev. 4 - CN 2012

http://ec.europa.eu/eurostat/ramon/other_documents/combined%20nomenclature/conversion_tables/CN2012_SITC4.zip

SITC Rev. 4 - CN 2013

http://ec.europa.eu/eurostat/ramon/other_documents/combined%20nomenclature/conversion_tables/CN2013_SITC4.zip

SITC Rev. 4 - CN 2014

http://ec.europa.eu/eurostat/ramon/other_documents/combined%20nomenclature/conversion_tables/CN2014_SITC4.zip

SITC Rev. 4 - CN 2015

http://ec.europa.eu/eurostat/ramon/other_documents/combined%20nomenclature/conversion_tables/CN2015_SITC4.zip

SITC Rev. 4 - CN 2016

http://ec.europa.eu/eurostat/ramon/documents/cn_2016/CN2016_SITC4.zip

Classification Structure

Level

Level Name

Code Format

Number of Items

Level 1

Group

1

10 items

Level 2

N/A

11

32 items

Level 3

N/A

111

71 items

Level 4

N/A

1111

140 items

Level 5

N/A

11111

169 items

Revision Information

Chronology of revisions/versions of the classification:

Year Adopted:

1981

 

Website:

http://www.fao.org/forestry/statistics/80572/en/

 

Official Adopting Entity:

Joint FAO/ECE Working Party on Forest Economics and Statistics

 

Coordinating Entity:

Food and Agriculture Organization of the United Nations

 

Next Review:

2016

 

Reason for Latest Revision:

In 1979 the Joint FAO/ECE Working Party on Forest Economics and Statistics recommended that the classification should be brought up to date to take account of revisions of the Standard International Trade Classification, the work of the Customs Cooperation Council on a harmonized commodity description and coding system, and to take account of changes in technology, industry and trade practice and the appearance of new products. It was also recommended that this revision should ensure that the needs of all regions of the world are accommodated.

 

Major Changes:

The 1982 revision included cross-references to SITC and HS. The classifications has not been revised since 1982.

Contact Information

Food and Agriculture Organization of the United Nations

Unit:

Statistics Division

Contact Name:

José Rosero Moncayo

Email:

[email protected]

Address:

Viale delle Terme di Caracalla 00153 Rome Italy

Joint Forect Sector Questionnaire Definitions

General information

Status

Operational

Website

http://www.fao.org/forestry/statistics/80572/en/

Custodian

Food and Agriculture Organization of the United Nations 

Year Adopted

1981

Year Published

1982

Availability

Arabic, Chinese, English, French, Russian and Spanish

Purpose of the Classification

Statistical Domain

Forestry statistics

Purpose

This classification is designed to cover the wood and wood-based products for which Food and Agriculture Organization of the United Nations (FAO) and United Nations Economic Commission for Europe (UNECE) collect statistics on a regular basis. Included is wood taken from forests or from trees outside the forest, bark and cork; charcoal; wood and wood-based materials resulting from the first processing of the wood available from forest operations (including sawnwood, railway sleepers, veneer sheets, wood pulp and wood residues); and materials resulting from further processing of some of these materials (e.g. wood-based panels, paper and paperboard); recovered paper and recoverable wood products.

Main Users

Users of datasets on forest products disseminated by international organizations (FAOSTAT, UNECE's Timber database).

Methodology

Concept Being Classified

Goods

Relationships to Other International Classifications

Classification of Forest Products - SITC Rev.2

Classification of Forest Products - Harmonized System (HS)

Classification of Forest Products - Customs Cooperation Council Nomenclature for the Classification of Goods in Customs Tariffs (CCCN)

Classification of Forest Products - International Standard Industrial Classification of All Economic Activities (ISIC)

Classification of Forest Products - UN Classification by Broad Economic Categories (BEC)

Classification Structure

Level

Level Name

Code Format

Number of Items

Level 1

Section

0

9 items

Level 2

Division

01

67 items

Level 3

Group

012

262 items

Level 4

Subgroup

012.1

1023 items

Level 5

Heading

012.13

2970 items

Revision

Information

Year Adopted:

1950

 

Title or Version Number:

SITC 1950

 

Website:

http://unstats.un.org/unsd/cr/registry/regdntransfer.asp?f=263

 

Official Adopting Entity:

UN Statistical Commission

 

Coordinating Entity:

Inter-Agency Task Force on International Trade Statistics

 

Reason for Latest Revision:

Major change was updating of the most recent goods with up-to-date technology and current economic importance. SITC Rev 4 retains the overall structure of SITC, revision 3 and consists of the same number of sections and groups. The changes made were at the level of basic heading and some subgroups. It took into considerations changes in codes of HS88 (which SITC Rev.3 based on) and HS07 (which SITC Rev.4 based on)

 

Official Adopting Entity:

UN Statistical Commission

 

Coordinating Entity:

Inter-Agency Task Force on International Trade Statistics

 

Reason for Latest Revision:

Major change was updating of the most recent goods with up-to-date technology and current economic importance. SITC Rev 4 retains the overall structure of SITC, revision 3 and consists of the same number of sections and groups. The changes made were at the level of basic heading and some subgroups. It took into considerations changes in codes of HS88 (which SITC Rev.3 based on) and HS07 (which SITC Rev.4 based on)

Classification Structure

Level

Level Name

Code Format

Number of Items

Level 1

Group

1

10 items

Level 2

N/A

11

32 items

Level 3

N/A

111

71 items

Level 4

N/A

1111

140 items

Level 5

N/A

11111

169 items

Revision Information

Chronology of revisions/versions of the classification:

 

Year Adopted:

1981

 

Website:

http://www.fao.org/forestry/statistics/80572/en/

 

Official Adopting Entity:

Joint FAO/ECE Working Party on Forest Economics and Statistics

 

Coordinating Entity:

Food and Agriculture Organization of the United Nations

 

Next Review:

2016

 

Reason for Latest Revision:

In 1979 the Joint FAO/ECE Working Party on Forest Economics and Statistics recommended that the classification should be brought up to date to take account of revisions of the Standard International Trade Classification, the work of the Customs Cooperation Council on a harmonized commodity description and coding system, and to take account of changes in technology, industry and trade practice and the appearance of new products. It was also recommended that this revision should ensure that the needs of all regions of the world are accommodated.

 

Major Changes:

The 1982 revision included cross-references to SITC and HS. The classifications has not been revised since 1982.

Contact Information

Food and Agriculture Organization of the United Nations

Unit:

Statistics Division

Contact Name:

José Rosero Moncayo

Email:

[email protected]

Telephone:

(+39) 06 5705 3599

Fax:

(+39) 06 5705 5615

Address:

Viale delle Terme di Caracalla, 00153 Rome, Italy

Forestry

This section contains the main statistical guidelines and handbooks produced by FAO. They include:

  • Global Forest Resources Assessment (FRA) guidelines 
  • Global Strategy to Improve Agricultural and Rural Statistics (GSARS) Guidelines and handbooks series.

Documents listed under the forestry subject include topics related to forest and forest products, forestry production and development, forestry-related statistics and sustainable forest management.

Global forest resources assessment 2020 terms and definitions

Abstract: This document contains a comprehensive list of terms and definitions as well as explanatory notes for FRA 2020 reporting variables.

Lead authoring unit/office: Forestry Division (NFO)

françaisEspañolРусский

Guidelines on data collection for national statistics on forest products

Abstract: Prepared by the Global Strategy to Improve Agricultural and Rural Statistics (GSARS), these Guidelines on data collection for national statistics on forest products aim to present and discuss best practices with respect to the collection, compilation and dissemination of statistics on forest products statistics.

Lead authoring unit/office: Statistics Division (ESS)

Guidelines for the incorporation of a woodfuel supplementary module into existing household surveys in developing countries

Abstract: Prepared by the Global Strategy to Improve Agricultural and Rural Statistics (GSARS), the purpose of these Guidelines is to develop a tool named the Woodfuel Supplementary Module (WSM), to be incorporated in existing national household surveys. The ultimate goal is to enable developing countries to gather accurate data on woodfuel production and consumption, the sustainability of its production, and related socio-economic and health outcomes.

Lead authoring unit/office: Statistics Division (ESS)

Global Forest Resources Assessment - FRA 2020 - Guidelines and specifications Version 1.0 Working Paper No. 189

Abstract: This document provides information about the country reporting process, including an introduction to the new FRA 2020 on-line reporting platform.  

Lead authoring unit/office: Forestry Division (NFO)

françaisEspañolРусский

Forestry

This section contains the main technical reports, working papers and methodological documents produced by FAO. They include:

  • Global Strategy to Improve Agricultural and Rural Statistics (GSARS) Technical Report and Working Paper Series.

Documents listed under the forestry subject include topics related to forest and forest products, forestry production and development, forestry-related statistics and sustainable forest management.

Forest product conversion factors

Abstract: Forest products conversion factors provides ratios of raw material input to the output of wood-based forest products for 37 countries of the world. Analysts, policymakers, forest practitioners and forest-based manufacturers often have a need for this information for understanding the drivers of efficiency, feasibility and economics of the sector. In addition, conversion factors are often needed to convert from one unit of measure to another. The publication also includes explanations on the units of measure, the drivers of the ratios, as well as information on physical properties of wood-based forest products. Finally, where reported factors were unavailable, factors from other sources are given.

Lead authoring unit/office: FAO

Proceedings of the FRA 2020 launch: technical meeting of national correspondents and CFRQ partners Toluca, Mexico, 5-9 March 2018

Abstract: Since the formalization of the FRA network of National Correspondents in 2005, FAO has been organizing Global Meeting of National Correspondents with the objectives to officially launch the reporting process and strengthen the National Correspondents network. The first two global meetings for FRA 2005 and FRA 2010 were held in 2003 and 2008 respectively, in Rome at FAO headquarters. The FRA 2015 global meeting of National Correspondents was held in 2013 in Chiang Mai, Thailand and organized in collaboration with the FAO Regional Office for Asia and the Royal Forest Department of Thailand. Building on this positive experience, the FRA 2020 technical meeting of National Correspondent was organized in collaboration with the National Forestry Commission of Mexico (CONAFOR) and with the involvement and support of the Regional Office for South America and the Caribbean and the FAO representation in Mexico. Since the formalization of the FRA network of National Correspondents in 2005, FAO has been organizing Global Meeting of National Correspondents with the objectives to officially launch the reporting process and strengthen the National Correspondents network. The first two global meetings for FRA 2005 and FRA 2010 were held in 2003 and 2008 respectively, in Rome at FAO headquarters. The FRA 2015 global meeting of National Correspondents was held in 2013 in Chiang Mai, Thailand and organized in collaboration with the FAO Regional Office for Asia and the Royal Forest Department of Thailand. Building on this positive experience, the FRA 2020 technical meeting of National Correspondent was organized in collaboration with the National Forestry Commission of Mexico (CONAFOR) and with the involvement and support of the Regional Office for South America and the Caribbean and the FAO representation in Mexico.

Lead authoring unit/office: Forestry Division (NFO)

How to Include the woodfuel supplementary module into existing surveys and derive woodfuel indicators

Abstract: Prepared by the Global Strategy to Improve Agricultural and Rural Statistics (GSARS), this Technical Report is to introduce a revised version of the short form and the long form of the Woodfuel Supplementary Module (WSM); to describe the proposed methodology to incorporate the WSM into existing surveys; and to describe the indicators of consumption and production of woodfuel that can be derived from the data collected.

Lead authoring unit/office: Statistics Division (ESS)

Developing a woodfuel survey module for incorporation into existing household surveys and censuses in developing countries

Abstract: Prepared by the Global Strategy to Improve Agricultural and Rural Statistics (GSARS), this technical report illustrates the quality of current surveys and censuses, indicating those that are more suitable for inclusion of a woodfuel module; and introduces a Woodfuel Supplementary Module that covers the most relevant aspects of woodfuel consumption and production.

Lead authoring unit/office: Statistics Division (ESS)

Report of the Expert Consultation on Global Forest Resources Assessment: Towards FRA 2020, Joensuu, Finland, 12–16 June 2017

Abstract: This report presents the key findings and recommendations of the Expert Consultation on Global Forest Resources Assessment: Towards FRA 2020 organised on 11.-16.6.2017 in Joensuu, Finland. The objective of the Expert Consultation was to provide guidance on the scope and reporting framework for the next Global Forest Resources Assessment (FRA 2020), by identifying key information needs related to forests at both the national and international level and by making recommendations about the content and process for FRA, in order to help ensure consistent and accurate reporting while reducing the reporting burden on countries.

Lead authoring unit/office: Forestry Division (NFO)

National statistics related to woodfuel and international recommendations

Abstract: Prepared by the Global Strategy to Improve Agricultural and Rural Statistics (GSARS), this Technical Report is a first step towards improving national statistics on the production and consumption of woodfuel in developing countries.

Lead authoring unit/office: Statistics Division (ESS)

Forestry

This section provides the main capacity development resources produced by FAO. They include:

  • Global Strategy to Improve Agricultural and Rural Statistics (GSARS) training materials
  • Other e-learning courses, training material or webinars.
No records found.

Fishery and Aquaculture

This section provides the main statistical classifications maintained and/or used by FAO.

FAO Major Fishing Areas for statistical purposes

General information

Status

Operational

Website

http://www.fao.org/cwp-on-fishery-statistics/handbook/general-concepts/major-fishing-areas-general/en/

and

http://www.fao.org/cwp-on-fishery-statistics/handbook/general-concepts/fishing-areas-for-statistical-purposes/en/

Custodian

Food and Agriculture Organization of the United Nations (Secretariat of the Coordinating Working Party on Fishery Statistics)

Availability

Arabic, Chinese, English, French, Russian and Spanish

Purpose of the Classification

Statistical Domain

Fishery and aquaculture statistics

Purpose

For statistical purposes, particularly for reporting fishery and aquaculture production. FAO Major Fishing Areas for Statistical Purposes are arbitrary areas, the boundaries of which have been determined in consultation with international fishery agencies. The rationale of the FAO Major Fishing Areas has been that the areas should, as far as possible, coincide with the areas of competence of other fishery commissions when existing. This system facilitates comparison of data, and improves the possibilities of cooperation in statistical matters in general.

Main Applications

To classify capture fisheries and aquaculture production by areas where the fish is caught or harvested. When establishing new regional fishery bodies, FAO Major Areas often becomes a basis to determine the scope of their jurisdiction.

Main Users

FAO, national fishery and aquaculture statistical offices, international organizations, regional fisheries bodies

Methodology

Scope

Global

Concept Being Classified

Geographic areas

Statistical Units

Fishing area

Classification Structure

Level

Level Name

Code Format

Number of Items

Level 1

Major Area

xx

26 items

Level 2

Subarea

xx.x

n/a items

Level 3

Divisions

xx.x.x

n/a items

Level 4

Subdivisions

xx.x.xx

n/a items

Criteria for Definition of Levels

The FAO Major Fishing Areas for Statistical Purposes are arbitrary areas the boundaries of which were determined in consultation with international fishery agencies on the basis of various considerations, including: the boundary of natural regions and the natural divisions of oceans and seas; the boundaries of adjacent statistical fisheries bodies that had already been established in intergovernmental conventions and treaties; existing national practices; national boundaries; the longitude and latitude grid system; the distribution of the aquatic fauna; the distribution of resources and the environmental conditions within an area.

For statistical purposes, 26 major areas currently exist. These comprise:  seven major inland areas covering the inland waters of the continents and 19 major marine areas covering the waters of the Atlantic, Indian, Pacific and Southern Oceans, with their adjacent seas. Until 1990, another area existed for inland area “Former USSR area”.

Some FAO major marine areas are further divided into subareas, divisions and subdivisions, according to the needs of the regional fishery management bodies responsible for managing the fisheries and fishery resources of the individual FAO Major Areas. These systems of subareas, divisions and subdivisions have been successfully developed and implemented by relevant regional fishery bodies; any modifications are duly reported to CWP.

Revision Information

Chronology of revisions/versions of the classification:

 

Websites:

http://www.fao.org/cwp-on-fishery-statistics/handbook/general-concepts/major-fishing-areas-general/en/

and

http://www.fao.org/cwp-on-fishery-statistics/handbook/general-concepts/fishing-areas-for-statistical-purposes/en/


Official Adopting Entity:

Coordinating Working Party on Fishery Statistics

 

Coordinating Entity:

Coordinating Working Party on Fishery Statistics

 

Documenting Website:

http://www.fao.org/fishery/area/search/en

 

Reason for Latest Revision:

Member requested revisions

 

Major Changes:

No major changes

Contact Information

Coordinating Working Party on Fishery Statistics

FAO Statistics and Information Branch (FIAS), Fisheries Division (NFI)

Contact Name:

Stefania Vannuccini

Email:

[email protected]

Address:

FAO Room F-202 Viale delle Terme di Caracalla, 00153 Rome, Italy 

ASFIS List of Species for Fishery Statistics Purposes (ASFIS)

General information

Status

Operational

Website

http://www.fao.org/fishery/collection/asfis/en

Custodian

Food and Agriculture Organization of the United Nations (Secretariat of the Coordinating Working Party on Fishery Statistics)

Year Adopted

2000

Year Published

First version (2002); Last version (2019)

Availability

Arabic, Chinese, English, French, Russian and Spanish

Purpose of the Classification

Statistical Domain

Fishery and aquaculture statistics

Purpose

Please note that this is a list, not a classification. ASFIS is a list of species used to classify fisheries and aquaculture data at either the species, genus, family or higher taxonomic levels in statistical categories referred to as species items.

Main Applications

Classifying aquaculture and fisheries data by species items. Used by countries, regional and international organizations when reporting and exchanging information.

Main Users

FAO, national fishery and aquaculture statistical offices, international organizations, regional fisheries bodies

Methodology

Scope

To classify fisheries and aquaculture species items by an ISSCAAP code, a taxonomic code, a 3-alpha code, a scientific name, taxonomic classification at family and at a higher taxonomic level.

Concept Being Classified

Goods, aquatic animals

Statistical Units

Species item

Relationship to Other International Classifications

Related To:

International Standard Statistical Classification for Aquatic Animals and Plants (ISSCAAP)

Classification Structure

Level

Level Name

Code Format

Number of Items

Level 1

Scientific Name+English Name+French Name+Spanish Name+Arabic Name+Chinese Name+Russian Name

ISSCAAP code: 123 + 3-alpha code: ABC

+ taxonomic code: 1234567890 

+taxonomic information

12 771 items (2019 version)

Criteria for Definition of Levels

ASFIS is a list of species that includes 12 771 species items (2019 version), selected on the basis of their interest or relation to fisheries and aquaculture. For each species item stored in a record, the following descriptors are available:

  • 3-alpha code has been developed by the CWP and it is assigned to a species item permanently (it is, thus, a permanent reference to that species item). The 3-alpha code is issued only for species of commercial significance and it is widely used for exchange of data among fisheries agencies and for national submission of data to FAO and other agencies. FAO is the depository agency for the 3-alpha codes: requests for information and for the allocation of a 3-alpha code to new species should be addressed to FAO.


  • ISSCAAP code classifies aquatic commercial species on the basis of their taxonomic, ecological and economic characteristics. More information is available under ISSCAAP classification.


  • Taxonomic code is a ten-digit numerical code covering the following information: main groupings, orders, families, genera and species. In a few special cases, three additional digits have been added.


  • Taxonomic information related to scientific name, author(s), family, and higher taxonomic classification.

Revision Information

Chronology of revisions/versions of the classification:


Title or Version Number:

ASFIS 2019  


Website:

http://www.fao.org/fishery/collection/asfis/en


Official Adopting Entity:

Food and Agriculture Organization of the United Nations (FAO)


Coordinating Entity:

FAO - Statistics and Information Branch (FIAS), Fisheries Division (NFI)

Next Review:

2020. An updated version of the ASFIS List is released each year at about April-May after the annual closure of the FAO capture and aquaculture production databases.


Reason for Latest Revision:

Additions of new species for which statistics became available and/or due to changes in the scientific names and taxonomic classifications proposed in the scientific literature by taxonomists.

 

Major Changes:

Minor changes are generally implemented in every annual release. The approach followed is that in case of changes of scientific names and creation of new species proposed in the scientific literature by taxonomists, they are included in the ASFIS list only when such changes have been recognized by the majority of taxonomists and are well consolidated among people dealing with fishery matters and, in particular, fishery statistics.

Contact Information


Food and Agriculture Organization of the United Nations

Fisheries Division (NFI)

Contact Name:

Stefania Savoré

Email:

[email protected]

Website:

http://www.fao.org/cwp-on-fishery-statistics/handbook/general-concepts/identifiers-for-aquatic-animals-and-plants/en/

Fax:

+39 06 57052476

Address:

Viale delle Terme di Caracalla, 00153 Rome, Italy

International Standard Statistical Classification for Aquatic Animals and Plants (ISSCAAP)

General information

Status

Operational

Website

http://www.fao.org/fishery/static/ASFIS/ISSCAAP.pdf

Custodian

Food and Agriculture Organization of the United Nations (Secretariat of the Coordinating Working Party on Fishery Statistics)

Year Adopted

1969

Year Published

2001

Availability

English, French and Spanish

Purpose of the Classification

Statistical Domain

Fishery and aquaculture statistics

Purpose

ISSCAAP classifies aquatic commercial species into 50 groups and nine divisions on the basis of their taxonomic, ecological and economic characteristics.

Currently, all species in the ASFIS List are classified by ISSCAAP group, with the exception of marine birds and snakes.

Main Applications

For aggregating aquatic species on the basis of their taxonomic, ecological and economic characteristics.

It also serves as a) a framework for compilation and presentation of statistics on fishery and aquaculture production and trade; b) aggregates and elements for analyses; c) a set of elements (or building blocks) suitable for rearrangement or expansion for special studies or for special purpose classification systems

Main Users

FAO, national fishery and aquaculture statistical offices, international organizations, regional fisheries bodies and users of the FAO Fishery and aquaculture statistics.

Methodology

Scope

ISSCAAP classifies aquatic commercial species into 50 groups and nine divisions on the basis of their taxonomic, ecological and economic characteristics. 

Concept Being Classified

Goods, animals

Statistical Units

Species

Relationship to Other International Classifications

Related To:

ASFIS list

Classification Structure

Level

Level Name

Code Format

Number of Items

Level 1

Division

0

9 items

Level 2

Group

00

50 items

Criteria for Definition of Levels

The ISSCAAP comprises 50 groups under nine divisions. The first eight divisions are dedicated to major groups of marine and freshwater animals, the ninth division is for aquatic plants. Species are classified by these groups and divisions on the basis of their taxonomic, ecological and economic characteristics.

Revision Information

Chronology of revisions/versions of the classification:


Title or Version Number:

2001


Website:

http://www.fao.org/fishery/static/ASFIS/ISSCAAP.pdf


Official Adopting Entity:

Coordinating Working Party on Fishery Statistics


Coordinating Entity:

FAO as Secretariat of CWP


Next Review:

Under discussion at CWP - dates not fixed yet.

 

Reason for Latest Revision:

For the 2001 version, to better classify demersal and pelagic species and refine the coverage of some of the groups

 

Major Changes:

Modification of three main groups “Miscellaneous demersal fishes”, “Miscellaneous coastal fishes” and “Miscellaneous pelagic fishes”

Contact Information

Coordinating Working Party on Fishery Statistics

FAO FIAS, Fisheries Division (NFI)

Contact Name:

Stefania Vannuccini

Email:

[email protected]

Website:

http://www.fao.org/cwp-on-fishery-statistics/handbook

Address:

Viale delle Terme di Caracalla, 1

00153 Rome, Italy

International Standard Statistical Classification of Fishery Commodities (ISSCFC)

General information

Status

Operational

Website

http://www.fao.org/3/a-bt967e.pdf

Custodian

Food and Agriculture Organization of the United Nations (Secretariat of the Coordinating Working Party on Fishery Statistics)

Year Adopted

1965

Year Published

2019

Availability

English, French and Spanish

Purpose of the Classification

Statistical Domain

Fishery and aquaculture statistics

Purpose

This classification is designed to cover the products derived from fish, crustaceans, molluscs, other aquatic animals and plants for which the Food and Agriculture Organization of the United Nations (FAO) collects national statistics on production and trade on a regular basis. It includes live species as well products resulting from further processing of species destined to human consumption or to other purposes including ornamental.

Main Applications


For collection and dissemination of fisheries commodities production and trade statistics by FAO. One basic purpose of the classification system for fish and fishery products was to improve presentation of comparability of statistics of different types collected from a wide range of sources. It also serves as: a) a basis for statistical collection procedures; b) a framework for compilation and presentation of statistics; c) aggregates and elements for analyses; d) a set of elements (or building blocks) suitable for rearrangement or expansion for special studies or for special purpose classification systems.

Main Users

Users of the FAO Fisheries commodities production and trade statistics and Fishery statistical offices.

Methodology

Scope

The ISSCFC classification is designed to cover fish, crustaceans, molluscs, other aquatic animals, plants and their based products for which FAO collects production and trade statistics on a regular basis. Products are classified according to the species and to the degree of processing. It also includes species for ornamental purposes, for culture (i.e. fingerlins, fry, etc), corals, sponges, residues, seaweeds and other algae. At present, it does not include aquatic mammals, frogs and crocodiles. Fisheries operations and services are also excluded, along with other fishery-based activities.

Concept Being Classified

Goods

Statistical Units

Commodity

Relationship to Other International Classifications

Related To:

International Standard Statistical Classification for Aquatic Animals and Plants (ISSCAAP)

Standard International Trade Classification (SITC) Revision 4

Harmonized System (HS) Classification version 2017

Central Product Classification (CPC) version 2.1

 

Major Differences (Scope, Structure, and Concepts):

ISSCFC has been constructed as an expansion of SITC and it is also directly linked with the Harmonized System (HS), Central Product Classification (CPC) and ISSCAAP. It is focused on fish and fish-based products (primary and secondary) and it contains more than 1 200 codes. Therefore it presents an improved breakdown by species and product forms compared to SITC, HS and CPC. The enhanced coverage and the links with other international classifications facilitate the collation of national data received in different formats/codes, including national classification based on HS or SITC. It is based on the structure of SITC, but presenting additional codes to include links to ISSCAAP and enhanced breakdown by species and product forms. Main difference with SITC and HS is related on the enhanced detail by species/product forms included in ISSCFC, which allows the analysis, comparison and dissemination of more detailed data on fisheries commodities production and trade. ISSCFC is based on following criteria: stage of processing, group of similar biological characteristics (ISSCAAP) and purpose or intended use.

Classification Structure

Level

Level Name

Code Format

Number of Items

Level 1

=SITC Division

0

8 items

Level 2

=SITC Group

00

26 items

Level 3

N/A

000.0.0

Level 4

N/A

000.0.0.0

Level 5

N/A

000.0.0.0.00

Level 6

N/A

...

Note

This classification is based on the SITC’s structure, with additional codes to include links to ISSCAAP and breakdown by additional species and product forms. It is a hierarchical classification, but the number of codes is not fixed.

Revision Information


Chronology of revisions/versions of the classification:


Title or Version Number:

ISSCFC


Website:

www.fao.org/cwp-on-fishery-statistics/handbook/socio-economic-data/fishery-commodities-classification/en/

Official Adopting Entity:

Food and Agriculture Organization of the United Nations (FAO)


Coordinating Entity:

FAO as Secretariat of CWP


Next Review:

2020


Reason for Latest Revision:

Maintenance includes a yearly updating in the light of new emerging commodities/species in international trade and of changes in international/national commodity classifications


Major Changes:

The 2019 version includes an improved breakdown of species and product form due to the significant changes of the HS2017 for fish and fishery codes.

Contact Information

Food and Agriculture Organization of the United Nations

Coordinating Working Party on Fishery Statistics

FAO FIAS, Fisheries Division (NFI)

Contact Name:

Stefania Vannuccini

Email:

[email protected]

Website:

http://www.fao.org/fishery/cwp/en

Address:

Viale delle Terme di Caracalla, 1

00153 Rome, Italy

International Standard Statistical Classification of Fishery Vessels - Simplified Classification of Fishing Vessels by Vessel Types (ISSCFV)

General information

Status

Operational

Website

http://www.fao.org/cwp-on-fishery-statistics/handbook/capture-fisheries-statistics/fishery-fleet/en/

Custodian

Food and Agriculture Organization of the United Nations (Secretariat of the Coordinating Working Party on Fishery Statistics)

Year Adopted

1984

Year Published

2015

Availability

English

Purpose of the Classification

Statistical Domain

Fishery statistics

Purpose

Under the ISSCFV, the CWP adopted three classifications, which cover the major features critical in classifying vessels based on type by GRT, length classes (length overall) and vessel types.

This component, the International Standard Statistical Classification of Fishery Vessels by Vessel Types, is based on the structure and type of vessel. 

Main Applications

Assessing fleet capacity and classification in vessel registries.

Main Users

FAO, statistical officers, fishery scientists, MCS (management, control and surveillance) of fishing activities, Regional Fisheries Bodies

Methodology

Scope

To classify fishing vessels Classification should be applied based on vessel structure and type.

Concept Being Classified

Equipment, vehicles

Statistical Units

Fishing operational unit

Classification Structure

Level

Level Name

Code Format

Number of Items

Level 1

Vessel Types Code

xx.x.x

20 items

Level 2

Vessel Types

xx.xx

44 items

Revision Information

Chronology of revisions/versions of the classification:


Title or Version Number:

ISSCFV


Website:

http://www.fao.org/3/a-bt983e.pdf


Official Adopting Entity:

Coordinating Working Party on Fishery Statistics


Coordinating Entity:

Coordinating Working Party on Fishery Statistics


Reason for Latest Revision:

In general, revision is made according to the request from the CWP participating organizations (i.e. members).


Major Changes:

A simplified list was implemented with elaboration of the classification of vessels supporting fishing related activities to meet the demand from member states also complying with the Agreement on Port State Measures (PSMA). 

Contact Information

Food and Agriculture Organization of the United Nations

Coordinating Working Party on Fishery Statistics

FAO FIAS, Fisheries Division (NFI)

Contact Name:

Stefania Vannuccini

Email:

[email protected]

Website:

http://www.fao.org/fishery/cwp/en

Address:

Viale delle Terme di Caracalla, 1

00153 Rome, Italy

International Standard Statistical Classification of Fishery Vessels by GRT Categories (ISSCFV-GRT)

General information

Status

Operational

Website

http://www.fao.org/cwp-on-fishery-statistics/handbook/capture-fisheries-statistics/fishery-fleet/en

Custodian

Food and Agriculture Organization of the United Nations (Secretariat of the Coordinating Working Party on Fishery Statistics)

Year Adopted

1977

Year Published

1990

Availability

English

Purpose of the Classification

Statistical Domain

Fishery statistics

Purpose

Under the ISSCFV, the CWP adopted three classifications, which cover the major features critical in classifying vessels based on type by GRT, length classes (length overall) and vessel types.

The International Standard Statistical Classification of Fishery Vessels by Gross Register Tonnage (GRT) Categories, is based on the Gross Register Tonnage of the vessels. It covers the dimension of gross registered tonnage using either the London Convention, which has been adopted for vessels of 24 meters in length and over, or with the older Oslo Convention method.

Main Applications

Assessing fleet capacity, classification in vessel registration.

Main Users

FAO, Statistical officers, fishery scientists, MCS (management, control and surveillance) of fishing activities, Regional Fisheries Bodies

Methodology

Scope

To classify  fishing vessels. Classification should be applied based on gross registered tonnage measurement.

Concept Being Classified

Equipment, vehicles

Statistical Units

Fishing operational unit

Classification Structure

Level

Level Name

Code Format

Number of Items

Level 1

GRT Division Code

xx

12 items

Level 2

GRT Group Codes

xxx

30 items

Revision Information

Chronology of revisions/versions of the classification:


Year Adopted:

1990

Title or Version Number:

ISSCFV-GRT


Website:

http://www.fao.org/3/a-bt982e.pdf


Official Adopting Entity:

Coordinating Working Party on Fishery Statistics


Coordinating Entity:

Coordinating Working Party on Fishery Statistics


Reason for Latest Revision:

In general, revision is made according to the request from the CWP participating organizations (i.e. members).


Major Changes:

Change from the Oslo convention to the London Convention (in force from July 1994 for vessels > 24 meters in length)

Contact Information

Coordinating Working Party on Fishery Statistics


Unit:

FAO FIAS, Fisheries Division (NFI)

Contact Name:

Stefania Vannuccini

Email:

[email protected]

Website:

http://www.fao.org/fishery/cwp/en

Address:

Viale delle Terme di Caracalla, 1

00153 Rome, Italy

International Standard Statistical Classification of Vessels by Length Classes

General information

Status

Operational

Website

http://www.fao.org/cwp-on-fishery-statistics/handbook/capture-fisheries-statistics/fishery-fleet/en

Custodian

Food and Agriculture Organization of the United Nations (Secretariat of the Coordinating Working Party on Fishery Statistics)

Year Adopted

1982

Year Published

1982

Availability

English

Purpose of the Classification

Statistical Domain

Fishery statistics

Purpose

Under the ISSCFV, the CWP adopted three classifications, which cover the major features critical in classifying vessels based on type by GRT, length classes (length overall) and vessel types.

This component, the International Standard Statistical Classification of Vessels by Length Classes, is based on the length of the Vessels as measured between perpendiculars.

Main Applications

Assessing fleet capacity, classification in vessel registration.

Main Users

FAO, Statistical officers, fishery scientists, MCS (management, control and surveillance) of fishing activities

Methodology

Scope

To classify fishing vessels. Classification should be applied based on vessel shapes, structure and size measurements. The classification contains three determinates of vessel, i.e. type and two types of sizes (gross tonnage and length overall).

Concept Being Classified

Equipment, vehicles

Statistical Units

Fishing operational unit

Classification Structure

Level

Level Name

Code Format

Number of Items

Level 1

Length Class

Xxx

11 items

Contact Information

Coordinating Working Party on Fishery Statistics

FAO FIAS, Fisheries Division (NFI)

Contact Name:

Stefania Vannuccini

Email:

[email protected]

Website:

http://www.fao.org/fishery/cwp/en

Address:

Viale delle Terme di Caracalla, 1

00153 Rome, Italy

International Standard Statistical Classification of Fishing Gear (ISSCFG) Revision 1

General information

Status

Operational

Website

http://www.fao.org/cwp-on-fishery-statistics/handbook/capture-fisheries-statistics/fishing-gear-classification/en/

Custodian

Food and Agriculture Organization of the United Nations (Secretariat of the Coordinating Working Party on Fishery Statistics)

Year Adopted

1980

Availability

English, French and Spanish

Purpose of the Classification

Statistical Domain

Fishery statistics

Purpose

Although this classification was initially designed to improve the compilation of harmonized catch and effort data on the STATLANT B questionnaires and in fish stock assessment exercises, it has also been found very useful for fisheries technology and the training of fishers. It has been used in particular for reference in works dealing with the theory and construction of gear and for the preparation of specialized catalogues on artisanal and industrial fishing methods.

Main Applications

Identifying the fishing technology in reporting on fishing CATCH and EFFORT; a part of basic definition of different "fisheries".

Main Users

Fishery statistical offices, fishery scientists, MCS (management, control and surveillance) of fishing activities, fisheries technology and training fishers

Methodology

Scope

The classification is developed based on fish entangling mechanisms and gear structure used with a global emphasis on existing major fishing areas in the Atlantic, Indian, Pacific and Antarctic Oceans.

Concept Being Classified

Goods, equipment

Statistical Units

Fishing operational unit; holding

Classification Structure

Level

Level Name

Code Format

Number of Items

Level 1

Gear Categories

01

12 items

Level 2

Gear Categories

01.1

60 items

Revision Information

Chronology of revisions/versions of the classification:


Year Adopted:

2013


Title or Version Number:

ISSCFG Revision 1


Website:

http://www.fao.org/3/a-bt987e.pdf


Official Adopting Entity:

Coordinating Working Party on Fishery Statistics


Coordinating Entity:

Coordinating Working Party on Fishery Statistics

Contact Information

 

Coordinating Working Party on Fishery Statistics

FAO FIAS, Fisheries Division (NFI)

Contact Name:

Stefania Vannuccini

Email:

[email protected]

Website:

http://www.fao.org/fishery/cwp/en

Address:

Viale delle Terme di Caracalla, 1

00153 Rome, Italy

Fishery and aquaculture

This section contains the main statistical guidelines and handbooks produced by FAO. 

Documents listed under the fishery and aquaculture subject include topics related to fishery and aquaculture statistics, fishing and aquaculture operations and small-scale fisheries.

Coordination Working Party (CWP) Handbook on fishery statistics

Abstract: The CWP Handbook covers the concepts, definitions, classifications and data exchange protocols – and not least the codes as applied to fishery statistics globally. Many of these concepts and definitions are applied in a wider context, but the user is advised to check the validity of such applications. The handbook indicates the principles applied by the international agencies and no attempt has been made to include details of national systems, many of which, having been developed for specific national purposes, may differ from those employed internationally.

Lead authoring unit/office: Fisheries Division (NFI)

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Handbook for fisheries socio-economic sample survey

Abstract: This handbook aims at supporting staff, resource partners and member countries in implementing and running socio-economic data collection for fisheries. Improved data availability in the socio-economic realm is a foundation for work to promote standardization of data collection formats and protocols. It is part of FAO Fisheries and Aquaculture Technical Paper Series. 

Lead authoring unit/office: Fisheries Division (NFI)

Guidelines to enhance small-scale fisheries and aquaculture statistics through a household approach

Abstract: Prepared by the Global Strategy to Improve Agricultural and Rural Statistics (GSARS), 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)

Guidelines to enhance fisheries and aquaculture statistics through a census framework

Abstract: Prepared by the Global Strategy to Improve Agricultural and Rural Statistics (GSARS), these guidelines describe a method that can be employed to accurately capture the actual contribution of small-scale fisheries and aquaculture to rural communities. In principle, the basic structure of these survey stages follows the concepts adopted by the World Census of Agriculture, including the modular approach, to enhance utility and reduce implementation costs.

Lead authoring unit/office: Statistics Division (ESS)

Safety in sampling: methodological notes

Abstract: While the present paper was written with the special concern of sample-based catch/effort assessment surveys for artisanal fisheries, it is envisaged that several of its methodological and utility aspects could be applicable to other types of sample-based fishery surveys, particularly in cases where large-scale data collection programmes operate under financial and personnel constraints. Emphasis is placed on “safety in sampling” and some simple approaches are presented by means of which statistical indicators regarding sampling accuracy are formulated in advance. Methodological aspects and statistical indicators that relate to the accuracy and reliability of estimates are presented in handbook form. They summarize experience gained over the recent years in fishery statistical development by the Fishery Information, Data and Statistics Unit (FIDI) of the FAO. The concepts and methods included in the paper apply equally to both marine and inland capture fisheries and are presented in a manner that is generic enough to make them adaptable in commonly used data collection systems.

Lead authoring unit/office: Fisheries Division (NFI)

Sample-based fishery surveys. A technical handbook

Abstract: The purpose of this handbook is to summarize experience gained over recent years in fishery statistical development by the Fishery Information, Data and Statistics Unit (FIDI) of FAO, and provide planners and users of fishery surveys with simple and step-by-step guidance for developing and implementing cost-effective and sustainable fishery surveys. The methodological and operational concepts discussed here apply equally to both marine and inland capture fisheries and are presented in a manner that is generic enough to make them adaptable to most commonly used data collection systems. Statistical aspects are presented in a descriptive rather than theoretical manner. Emphasis is placed on the understanding and interpretation of the statistics and related indicators collected, rather than on the computations producing them. Readers interested in a more in-depth discussion on statistical and computing approaches may make use of the list of references that is given at the end of the handbook. This publication is part of FAO Fisheries Technical Paper Series.

Lead authoring unit/office: Fisheries Division (NFI)

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Guidelines for the routine collection of capture fishery data

Abstract: These guidelines aim to help those who design routine data collection programmes, focusing on the relationship between typical questions asked by policy-makers and managers, and the data required for providing reliable answers. This publication is part of FAO Fisheries Technical Paper Series. 

Lead authoring unit/office: Fisheries Division (NFI)

Guidelines on the collection of structural aquaculture statistics: Supplement to the Programme for the World Census of Agriculture 2000

Abstract: This supplement, which is part of FAO Statistical Development Series, is intended to assist countries in improving their current surveys of aquaculture and to provide a framework for those countries planning to develop databases on aquaculture.

Lead authoring unit/office: Statistics Division (ESS)

Fishery and aquaculture

This section contains the main technical reports, working papers and methodological documents produced by FAO. 

Documents listed under the fishery and aquaculture subject include topics related to  fishery and aquaculture statistics, fishing and aquaculture operations and small-scale fisheries.

Master Sampling Frames (MSF) for fishery and aquaculture statistics

Abstract: This publication provides guidance for a statistical office to use when forming an MSF. The goals of this document are to (1) describe a process for building, maintaining and using MSFs; (2) discuss interrelations among survey objectives, core data elements, construction of sampling frames, estimation, and archival of results; and (3) offer guidance for using multiple sources of information. The statistical office will need to consider how the directives presented in this document apply to a particular situation. When deciding on an MSF approach, the statistical office should consider the ultimate uses of the collected data and the desired estimates.

Lead authoring unit/office: Statistics Division (ESS)

Gaps and methodological approach: A critical analysis of methods for surveys of fisheries and aquaculture

Abstract: In this technical report prepared by the Global Strategy to Improve Agricultural and Rural Statistics (GSARS), the literature search is linked to the pilot project by identifying salient issues and gaps in surveys of fisheries and aquaculture. Also discussed in the report are ways in which various methods for conducting surveys of fisheries and aquaculture deal with different aspects of these challenges.  

Lead authoring unit/office: Statistics Division (ESS)

A review of literature related to master sampling frames for fisheries and aquaculture surveys

Abstract: Prepared by the Global Strategy to Improve Agricultural and Rural Statistics (GSARS), this technical report reviews the literature related to the monitoring of characteristics of fisheries and anglers. It begins with an overview of why monitoring several dimensions of a fishery is important for the development of effective management plans, and considers aspects that might have particular relevance for developing and emerging economies.

Lead authoring unit/office: Statistics Division (ESS)

Fishery and Aquaculture

This section provides the main capacity development resources produced by FAO. They include:

  • Global Strategy to Improve Agricultural and Rural Statistics (GSARS) training materials
  • Other e-learning courses, training material or webinars.
Training course to enhance fishery and aquaculture statistics (Module 0/7) - Users' guide

Abstract: Prepared by the Global Strategy to improve agricultural and rural statistics (GSARS), This training material on the collection of small-scale fishery and aquaculture statistics is designed to bring together the persons within national statistical systems who are responsible for producing small-scale fishery and aquaculture statistics. The training therefore targets decision-makers in agriculture or fishery ministries and National Statistical Offices (NSOs), survey managers, trainers of field staff, data analysts, researchers, teaching staff and students at training centres of statistics and agriculture or fisheries. This user guide describes the intended training objectives, content and target audience of the training in the collection of SSF and aquaculture statistics. It also provides recommendations on aspects of the organization of training, such as a sample training duration timetable (see appendix).

Lead authoring unit/office: Statistics Division (ESS)

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Training course to enhance fishery and aquaculture statistics (Module 1/7) - Introduction and overview

Abstract: Prepared by the Global Strategy to improve agricultural and rural statistics (GSARS), this training material on the collection of small-scale fishery and aquaculture statistics is designed to bring together the persons within national statistical systems who are responsible for producing small-scale fishery and aquaculture statistics. The training therefore targets decision-makers in agriculture or fishery ministries and National Statistical Offices (NSOs), survey managers, trainers of field staff, data analysts, researchers, teaching staff and students at training centres of statistics and agriculture or fisheries. The training topics covered by the training material are the following: 1. Definition of Small-Scale Fishery (SSF) and aquaculture; 2. Why SSF and aquaculture statistics (including map of SSF distribution worldwide and statistics on output, consumption, employment) ‒ SDGs (food security, sustainability, economy) ‒ National data needs ‒ Regional data needs; 3. Indicators for SSF and aquaculture a. Biological indicators b. Fishing operations indicators c. Economic indicators d. Community indicators; 4. Criteria for selecting indicators to collect; 5. International classifications for fisheries statistics ‒ Boat gear classifications ‒ Fish species classifications, etc.

Lead authoring unit/office: Statistics Division (ESS)

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Training course to enhance fishery and aquaculture statistics (Module 2/7) - Refresher on biostatistics

Abstract: Prepared by the Global Strategy to improve agricultural and rural statistics (GSARS), this training material on the collection of small-scale fishery and aquaculture statistics is designed to bring together the persons within national statistical systems who are responsible for producing small-scale fishery and aquaculture statistics. The training therefore targets decision-makers in agriculture or fishery ministries and National Statistical Offices (NSOs), survey managers, trainers of field staff, data analysts, researchers, teaching staff and students at training centres of statistics and agriculture or fisheries. The training topics covered by the training material are the following: 1.1 Why a refresher on biostatistics; 1.2 Statistical terms: population versus sample; 1.3 Statistics/Estimates (mean, variance, standard deviation); 1.4 Reliability, precision and accuracy of estimates (confidence intervals, relative error, bias).

Lead authoring unit/office: Statistics Division (ESS)

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Training course to enhance fishery and aquaculture statistics (Module 3/7) - Data collection and sampling methods

Abstract: Prepared by the Global Strategy to improve agricultural and rural statistics (GSARS), this training material on the collection of small-scale fishery and aquaculture statistics is designed to bring together the persons within national statistical systems who are responsible for producing small-scale fishery and aquaculture statistics. The training therefore targets decision-makers in agriculture or fishery ministries and National Statistical Offices (NSOs), survey managers, trainers of field staff, data analysts, researchers, teaching staff and students at training centres of statistics and agriculture or fisheries. The training topics covered by the training material are the following: 1. Data sources and collection methods 2. Data sampling strategies 3. Setting up a stratified sampling scheme for routine SSF data collection.

Lead authoring unit/office: Statistics Division (ESS)

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Training course to enhance fishery and aquaculture statistics (Module 4/7) - Producing SSF statistics

Abstract: Prepared by the Global Strategy to improve agricultural and rural statistics (GSARS), this training material on the collection of small-scale fishery and aquaculture statistics is designed to bring together the persons within national statistical systems who are responsible for producing small-scale fishery and aquaculture statistics. The training therefore targets decision-makers in agriculture or fishery ministries and National Statistical Offices (NSOs), survey managers, trainers of field staff, data analysts, researchers, teaching staff and students at training centres of statistics and agriculture or fisheries.

Lead authoring unit/office: Statistics Division (ESS)

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Training course to enhance fishery and aquaculture statistics (Module 5/7) - Obtaining SSF and aquaculture statistics through a household

Abstract: Prepared by the Global Strategy to improve agricultural and rural statistics (GSARS), this training material on the collection of small-scale fishery and aquaculture statistics is designed to bring together the persons within national statistical systems who are responsible for producing small-scale fishery and aquaculture statistics. The training therefore targets decision-makers in agriculture or fishery ministries and National Statistical Offices (NSOs), survey managers, trainers of field staff, data analysts, researchers, teaching staff and students at training centres of statistics and agriculture or fisheries. The training topics covered by the training material are the following: 1. Building a frame of SSF and aquaculture households through population or agriculture censuses ‒ Screening questionnaires to identify SSF and aquaculture households during the census; 2. Survey designs for collecting household and community data for SSF and aquaculture through the household approach.

Lead authoring unit/office: Statistics Division (ESS)

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Training course to enhance fishery and aquaculture statistics (Module 6/7) - Tools to support data collection, compilation and analysis

Abstract: Prepared by the Global Strategy to improve agricultural and rural statistics (GSARS), this training material on the collection of small-scale fishery and aquaculture statistics is designed to bring together the persons within national statistical systems who are responsible for producing small-scale fishery and aquaculture statistics. The training therefore targets decision-makers in agriculture or fishery ministries and National Statistical Offices (NSOs), survey managers, trainers of field staff, data analysts, researchers, teaching staff and students at training centres of statistics and agriculture or fisheries. The topics covered by this module are the following: 1. Computer-Assisted Personal Interview (CAPI) for reduced data collection costs and improved data quality ‒ CAPI versus PAPI ‒ CAPI software – a quick introduction to ODK and Survey Solutions 2. Open ArtFish for compiling indicators for total catch from effort and landing surveys.

Lead authoring unit/office: Statistics Division (ESS)

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Training course to enhance fishery and aquaculture statistics (Module 7/7) - Exercises

Abstract: Prepared by the Global Strategy to improve agricultural and rural statistics (GSARS), this training material on the collection of small-scale fishery and aquaculture statistics is designed to bring together the persons within national statistical systems who are responsible for producing small-scale fishery and aquaculture statistics. The training therefore targets decision-makers in agriculture or fishery ministries and National Statistical Offices (NSOs), survey managers, trainers of field staff, data analysts, researchers, teaching staff and students at training centres of statistics and agriculture or fisheries. The training topics covered by the training material are the following: Exercises with case studies for compiling SSF statistics. Hands-on exercises in small groups, with examples of data sets.

Lead authoring unit/office: Statistics Division (ESS)

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International training course in fisheries statistics and data collection

Abstract: The primary objective of the course is to illustrate sampling methods for improving routine data collection, which can provide the desired precision of estimates at the lowest possible cost and yet possess a higher degree of accuracy. The design techniques are based on international standards, illustrated with the collection of fisheries statistics and analysis from the region. The specific objectives are: (i) to introduce basic concepts of the importance of fisheries information; (ii) to introduce international standards and concepts in fisheries data collection; (iii) to introduce the basic concepts of sampling and design of routine fisheries data collection schemes; (iv) to introduce basic concepts of statistical data analyses; (v) to introduce basic concepts of data storage and dissemination; and (vi) to provide practical issues and examples relevant to fisheries statistics and data collection.

Lead authoring unit/office: Fisheries Division (NFI)

Natural Resources

This section provides the main statistical classifications maintained and/or used by FAO.

Classification of land use (LU) for the agricultural census

General information

Status

Operational

Website

http://www.fao.org/3/a-i4913e.pdf

Custodian

Food and Agriculture Organization of the United Nations

Year Published

2015

Availability

Arabic, Chinese, English, French, Russian and Spanish

Purpose of the Classification

Statistical Domain

Land use statistics

Purpose

To classify land use types.

Main Applications

Agricultural statistics and agricultural censuses.

Main Users

Ministries of Agriculture and National Statistical Offices carrying out agricultural censuses.

Methodology

Concept Being Classified

Land use

Relationship to Other International Classifications

This classification focuses on how land/area are used within the agricultural holding. The WCA classification of land use contains nine basic land use classes, LU1 to LU9; six of the basic land use classes can be grouped into four aggregate classes: the nine basic classes are less detailed than in the SEEA, the WCA LU aggregates are ad hoc classes, not provided in the SEEA.

Notes: LU1 (in WCA) includes greenhouses and land in family gardens while 1.1.1 (in SEEA) does not. LU4 includes greenhouses and land in family gardens while 1.1.4 does not. 1.1.6 (in SEEA) includes greenhouses and land in family gardens while LU6 in WCA) does not.

Classification Structure

Level

Level Name

Code Format

Number of Items

Level 1

Basic class

LUO

9 items

Revision Information

Chronology of revisions/versions of the classification:

 

Website:

http://www.fao.org/world-census-agriculture/wcarounds/wca2020/en/

 

Official Adopting Entity:

Food and Agriculture Organization of the United Nations

 

Coordinating Entity:

Food and Agriculture Organization of the United Nations

 

Next Review:

2025

 

Reason for Latest Revision:

The revision took place as part of the WCA periodical review; the aim was to harmonize with the SEEA Land Use Classification.

 

Major Changes:

Increased number of classes (from seven to nine), better alignment to the SEEA LUC that resulted in the following changes: (1) two categories: “land under farm buildings and farmyards” and “area used for aquaculture” have been detached from the category “other land”. “Area used for aquaculture” may also include inland and coastal waters if they are part of the holding. (2 The concept of “land used for agriculture” has been introduced in order to match the category “agriculture” of the SEEA Land Use Classification. It represents the total of “agricultural land” and “land under farm buildings and farmyards”. (3) A minimum size threshold of 0.5 hectares (ha) has been introduced for the “forest land” and “other wooded land”. The differences between WCA 2020 and WCA 2010 LUC are clearly specified in WCA 2020, paragraph 8.2.14.

Contact Information

Food and Agriculture Organization of the United Nations

Statistics Division (ESS)

Contact Name:

Jairo Castano

Email:

[email protected]

Telephone:

+39 06 570-55166

Address:

Viale delle Terme di Caracalla, 1

00153 Rome, Italy

SEEA Land cover classification

General information

Status

Operational

Website

https://seea.un.org/content/seea-central-framework

Custodian

United Nations Statistics Division

Year Adopted

2012

Year Published

2012

Availability

Arabic, Chinese, English, French, Portuguese, Russian and Spanish

Purpose of the Classification

Statistical Domain

Environment; land cover statistics

Purpose

The purpose of the classification is to provide categories for the observed physical and biological cover of the Earth's surface, including natural vegetation and abiotic (non-living) surfaces. It allows for the standardization and harmonization across statistical data sets, a classification of land cover based on the FAO Land Cover Classification System comprised of 14 classes has been established.

Main Applications

Environmental economic accounts

Main Users

Environmental economic accounts compilers and users: international organizations, governments, ministries of environment as well as other economic and environmental bodies in the public and private sectors, as e.g. analysts and forecasters.

Methodology

Concept Being Classified

Land cover

Classification Structure

Level

Level Name

Code Format

Number of Items

Level 1

Basic category

00

14 items

Revision Information

Chronology of revisions/versions of the classification:

SEEA-2003

SEEA-1993

 

Website:

https://seea.un.org/content/seea-central-framework

 

Official Adopting Entity:

United Nations Statistical Commission

 

Coordinating Entity:

United Nations Committee of Experts on Environmental-Economic Accounting (UNCEEA)

 

Next Review:

N/A

 

Reason for Latest Revision:

Update of the SEEA central framework.

 

Major Changes:

Interim classifications for land cover have been developed.

Contact Information

United Nations Statistics Division

Economic Statistics Branch

Environmental-Economic Accounts Section

Email:

[email protected]

Website:  

https://seea.un.org/

Address:

United Nations

New York, NY 10017

SEEA Land use classification

General information

Status

Operational

Website

https://seea.un.org/content/seea-central-framework

Custodian

United Nations Statistics Division

Year Adopted

2012

Year Published

2012

Availability

ArabicChineseEnglishFrenchPortugueseRussian and Spanish 

Purpose of the Classification

Statistical Domain

Environment; land use statistics

Purpose

Land use reflects both (a) the activities undertaken and (b) the institutional arrangements put in place for a given area for the purposes of economic production, or the maintenance and restoration of environmental functions.

Main Applications

Environmental economic accounts

Main Users

Environmental economic accounts compilers and users: international organizations, governments, ministries of environment as well as other economic and environmental bodies in the public and private sectors, as e.g. analysts and forecasters

Methodology

Concept Being Classified

Land use

Classification Structure

Level

Level Name

Code Format

Number of Items

Level 1

Primary type of surfaces

0

2 items

Level 2

Category

01

11 items

Revision Information

Chronology of revisions/versions of the classification:

SEEA-2003

SEEA-1993

 

Website:

https://seea.un.org/content/seea-central-framework

 

Official Adopting Entity:

United Nations Statistical Commission

 

Coordinating Entity:

United Nations Committee of Experts on Environmental-Economic Accounting (UNCEEA)

 

Next Review:

N/A

 

Reason for Latest Revision:

Update of the SEEA central framework.

 

Major Changes:

Interim classifications for land use have been developed

Contact Information

United Nations Statistics Division

Environmental-Economic Accounts Section

Email:

[email protected]

Website:  

https://seea.un.org/

Address:

United Nations

New York, NY 10017

Natural resources

This section contains the main statistical guidelines and handbooks produced by FAO. 

Documents listed under the natural resources subject include topics related to water and land and geospatial information (e.g. land cover, land use classification, remote sensing & use of geospatial information).

Incorporating environmental flows into “water stress” indicator 6.4.2 - Guidelines for a minimum standard method for global reporting

Abstract: These guidelines are intended to assist countries to participate in the assessment of SDG 6.4.2 on water stress by contributing data and information on environmental flows (EF). These data are necessary for calculation of the SDG 6.4.2 (UNSD, 2017) indicator on water stress, for which countries are required to submit information to FAO who is custodian of this SDG indicator. This guideline provides a minimum standard method, principally based on the Global Environmental Flows Information System (GEFIS), which is accessible via http://eflows.iwmi.org, and is the approach that will be used to generate the country EF data that will make up the global 6.4.2 report. Countries that have more comprehensive and accurate EF data will be able to make use of that data when checking the global dataset produced by FAO and also to add additional details to their Voluntary National report on SDG 6.4.2.

Lead authoring unit/office: Land and Water Division (NSL)

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Change in water-use efficiency over time (SDG indicator 6.4.1) - Analysis and interpretation of preliminary results in key regions and countries

Abstract: This publication, which is the second of a new series of water resources papers on SDG 6.4, is intended to provide suggestions for the interpretation of the indicator 6.4.1. In particular, it focuses on the concept of economic decoupling from water-use, and its application in policy making.  The evolution in water-use and water-use efficiency in four selected regions: Europe, Latin America and the Caribbean, Southeast Asia and Sub-Saharan Africa, is discussed. Particular attention is given to the evolution in water-use, water-use efficiency and related drivers in two groups of countries, including major developed economies and newly industrialized countries, and in different economic sectors. 

Lead authoring unit/office: Land and Water Division (NSL)

Guidelines for development of a classification system related to farm typology

Abstract: Prepared by the Global Strategy to Improve Agricultural and Rural Statistics (GSARS), these Guidelines on Farm Typology propose a tool to be used to classify agricultural holdings by multiple dimensions, aiming at enhancing comprehension of the farm structures and production diversity both between and within countries, and at more efficient targeting in agricultural and rural policies and investments.

Lead authoring unit/office: Statistics Division (ESS)

Progress on water-use efficiency. Global baseline for SDG indicator 6.4.1

Abstract: This report is part of a series that track progress towards the various targets set out in SDG 6 using the SDG global indicators. The reports are based on country data, compiled and verified by the responsible United Nations organizations, and sometimes complemented by data from other sources. The main beneficiaries of better data are countries. The 2030 Agenda specifies that global follow-up and review “will be primarily based on national official data sources”, so we sorely need stronger national statistical systems. This will involve developing technical and institutional capacity and infrastructure for more effective monitoring.

Lead authoring unit/office: Land and Water Division (NSL)

Progress on level of water stress. Global baseline for SDG indicator 6.4.2

Abstract: This report is part of a series that track progress towards the various targets set out in SDG 6 using the SDG global indicators. The reports are based on country data, compiled and verified by the responsible United Nations organizations, and sometimes complemented by data from other sources. The main beneficiaries of better data are countries. The 2030 Agenda specifies that global follow-up and review “will be primarily based on national official data sources”, so we sorely need stronger national statistical systems. This will involve developing technical and institutional capacity and infrastructure for more effective monitoring.

Lead authoring unit/office: Land and Water Division (NSL)

Handbook on remote sensing for agricultural statistics

Abstract: The purpose of this handbook on Remote Sensing for Agricultural Statistics is to provide guidelines on the use of remote sensing in the context of agricultural statistics. Since the mid-1970s, remote sensing has been considered a promising technique for improving agricultural statistics. Various applications of remote sensing have taken place on all continents and today, several approaches may be considered mature enough to contribute to the sustainability of agricultural statistics. In the context of the Global Strategy to improve Agricultural and Rural Statistics (hereafter, GSARS or Global Strategy; see World Bank, 2011), remote sensing has been identified as a prime contributor to the localization and geocoding of the sampling units, a point of reference for Master Sampling Frames (MSFs), a methodological improvement in design and estimation terms, as a way to achieve sustainability and as a core data set for indicators linked to land uses and covers.

Lead authoring unit/office: Statistics Division (ESS)

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Natural resources

This section contains the main technical reports, working papers and methodological documents produced by FAO. 

Documents listed under the natural resources subject include topics related to water and land and geospatial information (e.g. land cover, land use classification, remote sensing & use of geospatial information).

GEMI – Integrated monitoring initiative for SDG 6. Step-by-step monitoring methodology for SDG Indicator 6.4.1

Abstract: Through the UN-Water Integrated Monitoring Initiative for SDG 6 (IMI-SDG6), the United Nations seeks to support countries in monitoring water- and sanitation-related issues within the framework of the 2030 Agenda for Sustainable Development, and in compiling country data to report on global progress towards SDG 6.  This document serves as a step-by-step monitoring methodology for SDG Indicator 6.4.1 "Change in water use efficiency over time". It explains how to monitor the change in water use efficiency over time, including definitions, computational steps, and recommendations on spatial and temporal resolutions. Last updated: July 2019.

Lead authoring unit/office: Land and Water Division (NSL)

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GEMI – Integrated monitoring initiative for SDG 6. Step-by-step monitoring methodology for indicator 6.4.2

Abstract: Through the UN-Water Integrated Monitoring Initiative for SDG 6 (IMI-SDG6), the United Nations seeks to support countries in monitoring water- and sanitation-related issues within the framework of the 2030 Agenda for Sustainable Development, and in compiling country data to report on global progress towards SDG 6. This document serves as a step-by-step monitoring methodology for SDG Indicator 6.4.2 "Level of water stress: freshwater withdrawal as a proportion of available freshwater resources". The guidelines intend to assist countries in the assessment on water stress by contributing data on environmental flows (EF) which are necessary for the calculation of SDG 6.4.2, indicator on water stress. Assessing environmental flows improves water management by ensuring a sustainable water supply that meets the needs of people, agriculture, energy, industry and the environment within the limits of availability. Last updated: February 2019.

Lead authoring unit/office: Land and Water Division (NSL)

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Improving methods for using existing land cover databases and classification methods. A literature review

Abstract: Prepared by the Global Strategy to Improve Agricultural and Rural Statistics (GSARS), this literature review presents the  main findings of bibliographic research on the application of remote sensing to agricultural and rural statistics.

Lead authoring unit/office: Statistics Division (ESS)

Information on land in the context of agricultural statistics

Abstract: Prepared by the Global Strategy to Improve Agricultural and Rural Statistics (GSARS), this Technical Report aims to provide guidelines for the application of different remote sensing products in various agricultural landscapes, and for the preparation of an integrated database to be used as a baseline in constructing the Master Sampling Frame.

Lead authoring unit/office: Statistics Division (ESS)

Technical report on cost-effectiveness of remote sensing for agricultural statistics in developing and emerging economies

Abstract: Prepared by the Global Strategy to Improve Agricultural and Rural Statistics (GSARS), this Technical Report on Cost-Effectiveness of Remote Sensing for Agricultural Statistics in Developing and Emerging Economies carries out a cost-efficiency analysis on the use of remote sensing through a literature review and the analysis of case studies in a series of 31 developing and emerging countries.

Lead authoring unit/office: Statistics Division (ESS)

Technical report on improving the use of GPS, GIS and remote sensing in setting up master sampling frames

Abstract: Prepared by the Global Strategy to Improve Agricultural and Rural Statistics (GSARS), this Technical Report on Improving the Use of GPS, GIS and Remote Sensing in Setting Up Master Sampling Frames is the result of a comprehensive literature review on the subject, followed by a gap analysis and a development of innovative methodological proposals for addressing the various issues that arise.

Lead authoring unit/office: Statistics Division (ESS)

Identifying the most appropriate sampling frame for specific landscape types

Abstract: Prepared in the framework of the Global Strategy to improve Agricultural and Rural Statistics (GSARS), this technical paper on identifying the most appropriate sampling frame for specific landscape types is the result of a comprehensive literature review on the subject, followed by a gap analysis and development of innovative methodological proposals for addressing any issues that emerged.

Lead authoring unit/office: Statistics Division (ESS)

Technical report on developing more efficient and accurate methods for the use of remote sensing in agricultural statistics

Abstract: Prepared by the Global Strategy to Improve Agricultural and Rural Statistics (GSARS), this technical report on Developing More Efficient and Accurate Methods for the Use of Remote Sensing is the result of a comprehensive literature review on the subject, followed by a gap analysis and, finally, the development of innovative methodological proposals for addressing the various issues arising.

Agriculture, forestry and other land use emissions by sources and removals by sinks: 1990-2011 Analysis

Abstract: This report, which is part of FAO Statistics Working Paper Series, discusses new knowledge on anthropogenic greenhouse gas (GHG) emissions from agriculture, forestry and other land use (AFOLU) activities made available through the new FAOSTAT Emission database.

Lead authoring unit/office: Statistics Division (ESS)

Natural resources

This section provides the main capacity development resources produced by FAO. They include:

  • Global Strategy to Improve Agricultural and Rural Statistics (GSARS) training materials
  • Other e-learning courses, training or webinars.
Webinar | AQUASTAT: Accounting water for the SDG 6.4 indicators

Abstract: This webinar presents the AQUASTAT Programme, the data available and the updated methodology. The annual questionnaire on water and agriculture is also detailed as part of the data collection through the recently established AQUASTAT National Correspondents network. The webinar was recorded as part of a series on Water Accounting organized by the FAO Near East and North Africa Regional Office.

Lead authoring unit/office: Land and Water Division (NSL)

Training course on Master Sampling Frames (MSF) - Exercises: Design of an area frame using QGIS, Open foris collect and Collect Earth/Google Earth Pro

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 are to initiate the audience on the use of GIS and remote sensing tools to build an area frame. It will be based on these tools: Qgis (Design of segments and points and execution of some processing tasks); Open foris collect (design of the land use/cover survey form); Collect earth and google earth pro (remote data collection of the land use/cover survey).

Lead authoring unit/office: Statistics Division (ESS)

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E-learning course | Hyper-temporal remote sensing to support agricultural monitoring

Abstract: The course presents an approach for improved mapping and differentiating spatial-temporal facts at country-level (agro-environmental stratification), using the best remotely sensed data and most modern interpretation/analysis methods.

Lead authoring unit/office: FAO

E-learning course | Spatial planning in the context of the responsible governance of tenure

Abstract: The course introduces spatial planning, identifying its rationale and benefits, its key principles and the main stages in the spatial planning process. It represents a useful reference for all those who want to promote and implement spatial planning in their countries as an instrument to reconcile and harmonize different, often conflicting, public and private interests on land, fisheries and forests.

Lead authoring unit/office: FAO

E-learning course | Remotely sensed information for crop monitoring and food security - Techniques and methods for arid and semi-arid areas

Abstract: This course describes how the information derived from remote sensing is obtained and best used for crop monitoring in a food security context. It outlines what the exact meanings of the products are and shows how their early warning and food availability information contents can be combined efficiently with other sources (e.g. households surveys, market analyses, nutritional surveys, etc.).

Lead authoring unit/office: FAO