The primary purpose of international statistical classifications is to provide a framework for the collection and analysis of data and for the presentation and comparison of official statistics at international level. Indeed, statistical classifications can be used to standardize statistical information, aggregate and disaggregate data sets in a meaningful way, and support policy and decision-making. They function as “international languages” for communicating in statistics (UNSD, n.d.-c).
International statistical classifications are essential mechanisms for the harmonization and coordination of data compilation worldwide. They enable the comparison of national data and indicators with those of other countries at global level, thus facilitating the inclusion of countries in global statistical activities and benchmarking of performance.
The International Organization for Standardization (ISO) defines international standards as follows: “[s]tatistical standards are usually documents established by consensus and approved by a recognised body that provides for common and repeated use, rules, guidelines for activities or their results, aimed at the achievement of the optimum degree of order in a given context.” (ISO, 1996)
International standards should be taken as points of reference for the development of national and regional schemes. To enable uptake at country level, they can be adapted (consistently with the relevant international classification framework) to suit the country’s requirements and its statistical needs.
Principle 9 of the UN Fundamental Principles of Official Statistics states:
“[t]he use by statistical agencies in each country of international concepts, classifications and methods promotes the consistency and efficiency of statistical systems at all official levels.”
This is particularly relevant in a world in which globalization increases the need for the interconnectedness and integration of production processes, communication and technologies – including the statistical world – to produce consistency and efficiency in all areas of life.
As reported by the United Nations Statistics Division (UNSD):
“[w]hen international reference standards are not employed, national statistical offices risk their data not being comparable with those of other countries and miss out an opportunity to see how their statistical indicators compare with overall world development. They forego the opportunity to promote their data, and subsequently their country, when their data cannot be published within internationally recognizable frameworks.” (UNSD, n.d.-c)
Statistical classifications have been on the agenda of the United Nations Statistical Commission (UNSC)1 – the apex body of the global statistical system – ever since its inception in 1947. Almost seventy years ago, therefore, the founders of the UNSC affirmed the need for international classifications to receive “urgent consideration”, to make “statistics compiled by different countries more comparable” (UNSC, 1947).
Today, the implementation of international classifications at global scale remains a priority for many statistical organizations. International classifications are a powerful tool in facing the challenges posed by a globalized world. Indeed, a widespread use of common classification frameworks facilitates the integration of data at global level and at the same time achieves savings in resources and capability, avoids the proliferation of classifications that are separately developed, implemented and maintained, and reduces overall costs for national statistical agencies. Efficiency gains are significant for individual countries adopting international schemes and for the global statistical system as a whole.
In agricultural and rural statistics, the need for more meaningful international statistical classifications has increased dramatically in recent years. This is due, on one hand, to the increasing demand for new official statistics and the need to integrate data on agriculture, forestry and fisheries within national statistical systems (NSSs) and, on the other, the lack of country-level capacities to produce and report statistical information. In developing countries especially, this has generated a decline in the quantity and quality of agricultural and rural statistics (WB, FAO & UN, 2010).
In addition, international classifications have been more often used in statistical domains other than that of agriculture; for which ad hoc lists were usually adopted at national level. In some cases, these lists may have originally been designed as legal – rather than statistical – tools, also in the light of the strategic role played by the agricultural sector in many countries. The different approach followed for agricultural statistics, as compared to other statistical domains, has often contributed to the isolation or exclusion of agricultural statistics from NSSs.
The Food and Agriculture Organization of the United Nations (FAO) has responded to this challenge by advancing its collaboration with other international organizations2 to better integrate agriculture into major international schemes, and by revising FAO’s classification system to enhance its relevance and ensure its compatibility with other international standards3 . For this reason, the implementation of international standards at country level is particularly important and is recommended by these Guidelines, to improve the integration of agricultural statistics into NSSs.
The Global Strategy to Improve Agricultural and Rural Statistics (WB et al., 2010) also includes work on international classifications for agricultural statistics in its Action Plan, because it is particularly relevant to the endeavours aimed at implementing its basic principles. These endeavours are:
•harmonization of concepts, definitions, classifications and standards across different data producers within the country, which promotes the integration of agriculture into NSSs and facilitates a country’s inclusion in global statistical activities; •enhancement of communication on classifications across different institutions in the country, which facilitates the harmonization and integration of data sources;
•promotion of exchange of information and good practices across countries, which reinforces cooperation with regional and national organizations in the implementation of international classifications for agricultural statistics and boosts data comparability across countries and over time;
• implementation of common international classifications, which improves data quality and decreases countries’ reporting burden to international organizations;
•provision of support to countries through capacity development on classifications, thus enabling greater uptake and correct application;
•facilitation of countries’ participation in international governance mechanisms on the development, management and review of standards and classifications for agricultural statistics, which ensures the sustainability of agricultural statistics worldwide.
A global survey conducted by FAO in 2012 on the classifications used by countries for agriculture and food products has shown a high demand for capacity development in the field of statistical classifications. Out of the 102 countries that participated in the survey, 60 per cent asked for capacity development and technical assistance by FAO in this domain4 .
These Guidelines were developed to meet the needs for capacity development expressed by countries. The aims are the following:
•bringing together comprehensive information on statistical classifications, and in particular those used for agricultural statistics;
•equipping users with a better understanding of these schemes; and
•providing a convenient and practical reference framework for the application of international standards at national level, thus enhancing data quality and comparability across countries and over time.
Strengthening cooperation on classifications and standards between FAO and the countries, Regional Organizations (ROs) and other institutions involved is essential to enhance the harmonization of data collection at global level and to give countries greater voice in the international governance of classifications and standards for agricultural statistics.
Consultation with countries is a crucial mechanism for ensuring the relevance, uptake and updating of international classifications. It is hoped that the Guidelines will facilitate this consultation and assist countries that are willing to engage or are already engaged in the adoption of international classifications or their adaptation to NSSs.
The Guidelines comprise five Chapters and an Annex:
•Chapter 1 introduces the theoretical framework of statistical classifications, including key definitions, basic principles and core components;
•Chapter 2 provides information on correspondence and conversion tables, and on how to convert data from one classification to another;
•Chapter 3 includes information sheets on the major classifications used for agricultural statistics; six main features (what, when and who, versions, purpose and applications, sections on agriculture, structure) are presented for each of the classifications below: • International Standard Industrial Classification of All Economic Activities (ISIC) • Central Product Classifications (CPC) and its expansion for agricultural statistics • Standard International Trade Classification (SITC) • Harmonized Commodity Description and Coding System (HS) • Classifications of Individual Consumption According to Purpose (COICOP) • Classifications of the Functions of Government (COFOG) • International Standard Classification of Occupations (ISCO) • International Classification by Status in Employment (ICSE) • International Standard Classification of Education (ISCED) • SEEA Land Use (LUC) and Land Cover Classification (LCC) • FAO classifications in the World Programme for the Census of Agriculture (WCA) • FAO classifications for fisheries and aquaculture statistics.
•Chapter 4 illustrates the benefits of using international classifications at country level and explains, with examples, how these can be adapted to meet the needs of NSSs;
•Chapter 5 summarizes the key information and recommendations set out in the Guidelines;
•the Annex looks at successful practices worldwide, showcasing efforts undertaken by countries and ROs to support the implementation and adaptation of international classifications. This section brings together lessons learnt and illustrates how international classifications have been applied at both regional and country level. This is a “living” section, and will be expanded and updated as soon as more information becomes available: countries are therefore encouraged to contact us to share and present their experience. 1. For further information on the UNSC, see the official webpage: “UN Statistical Commission” http://unstats.un.org/unsd/statcom/commission.htm. 2. In particular, the UNSD and the World Customs Organization (WCO). 3. For further information on the activities carried out by FAO on statistical classifications, see Ramaschiello 2011, 2013 and Ramaschiello and Vannuccini 2015a, 2015b. 4. Updates on FAO’s work on classifications is provided annually to the FAO Regional Commissions on Agricultural Statistics. For further details, see FAO (2013) and (2014b).
Texto de Guidelines on International Classifications for Agricultural Statistics (Documento en linea)
|Fotografía de Mauro Arias|