Data and Statistics

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1.

What are the key challenges for food and agriculture statistics over the next 15-30 years?

A. Evidence-based decision-making. There is a growing demand from both public and private actors to have access to more timely, reliable, and accurate data for informed decision-making.

Private actors (farmers, extension workers, etc.) need better information to improve farm profitably, use their scarce resources efficiently, prepare for pest and disease pressure in the short-run and climate change and water scarcity in the long run.

Five hundred (500) million smallholder farmers are at the heart of this challenge. They have the least access to existing information, are most difficult to reach and have very specific information needs. They need information about growing conditions (weather), markets (output and input prices), pest and disease pressure, etc. In tandem, policy-makers need better data for evidence- based policy-making, to design and roll out food security schemes, social safety nets, to decide on supporting or taxing farmers, design and select research and development programmes, etc. They also need better information to monitor national policy goals or commitments taken in international processes, notably the WTO, the UNFCCC, and most importantly, the SDG process.

B. Monitoring the Sustainable Development Goals (SDGs). At the current stage, 228 indicators have been identified to monitor progress towards the 169 targets of the SDGs. The Statistics Division of FAO is intimately involved in the identification of indicators.

It also provides overall guidance to this process, not least through the Chief Statistician of FAO who is also the elected chair of the Chief Statisticians of the UN System. While the indicator selection process has not yet been concluded (see document attached), the results of the most recent IAEG-SDG meeting (Bangkok, October 2015) suggest that FAO will be called upon to play a major role in monitoring the SDGs and in supporting countries to produce the required data. In total, 30 global indicators proposed by FAO have been included in the new monitoring framework. This compares with only three indicators monitored by FAO in the MDG process.

2.

What new information sources can be tapped into to live up to these challenges and does FAO help countries in this process?

Improving traditional information channels and sources. Traditionally, surveys and censuses formed the basis for information on a country’s food and agricultural sector. While tried and tested over many years, these approaches do not allow countries to collect information that is specific enough, frequent enough and consistent enough to address the growing needs for evidence-based decision making. Neither are these sources sufficient to help smallholders improve their livelihoods; nor do they suffice for policy makers to design policies and monitor commitments. Particularly the high costs of these traditional data collection methods have led to a growing data dearth and an ever-larger information gap for decision makers in developing countries. The FAO has recognized these problems early on and developed a set of programmes to address these challenges.

©FAO/Alessia Pierdomenico

Data and Statistics

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A. The Global Strategy to Improve Rural and Agricultural Statistics (GS).

The GS is arguably the most significant programme to overcome the high costs of data collection for food and agriculture in developing countries. The GS supports countries in meeting current and emerging data requirements by developing innovative and cost-effective methodologies, by building their statistical capacities and by strengthening their statistical infrastructure and institutions. Thus far, the Global Strategy has already provided 21 new research methods that support countries in improving the efficiency and reliability of their data collection activities and in making ample use of new technological options. The GS also provides training to developing countries to implement and apply these new methods and IT tools. The Global Strategy is funded by a Global Trust Fund managed by FAO.

Examples:

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The AGRicultural Integrated Survey system (AGRIS). AGRIS is a farm-based modular ten-year survey programme, which relies on cost effective statistical methodologies and leverages the most recent IT innovations (including mobile phones and tablets for data collection, GPS for area measurement) and new data sources (including

“big data” and remote sensing data). AGRIS covers the technical, economic, environmental and social dimensions of agricultural holdings through its core module and its four rotating modules on the: “economy”, “labour force”, “machinery and equipment”, and “production methods and environment”. Fully implemented, it allows countries to replace agricultural censuses and traditional farm surveys at no additional costs.

AGRIS represents the ideal survey tool to collect many of the indicators requested to monitor the new Sustainable Development Agenda (e.g.

productivity of small-holders, sustainable farming practices, etc.) and many of the indicators from the new results framework of the CAADP (Comprehensive Africa Agriculture Development Programme). AGRIS will be implemented in

partnership with the WB (LSM-ISA project) and other key stakeholders (USDA-NASS and IFAD).

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Master Sampling Frames. One of the key pillars in reducing data collection costs are the so-called Master Sampling Frames (MSF), in part developed and in full promoted by the GS. MSFs allow (i) a joint collection of data on the same sampling unit, (ii) a reduced sample size and/or (iii) ex- post integration of data from different surveys.

In developing these frames, it has employed new technological options such as Global Positioning System (GPS), Geographic Information Systems (GIS), and remote sensing (RS).

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Application of CAPI for rapid evidence based policy making in Tanzania. The Tanzanian National Panel Survey showed that despite the importance of livestock for income and nutrition in rural populations in Tanzania, very few livestock farmers receive extension services. With technical assistance from the Global Strategy, and the London School of Economics, the government implemented a baseline survey using Computer Assisted Personal Interview (CAPI) software developed under the research programme of the GS to rapidly assess the constraints facing veterinary extension officers and design an intervention. The benefits of applying CAPI were realized as preliminary results were available within one week of completing data collection, and a trial policy intervention will take place in January. Following the success of the CAPI survey, the National Bureau of Statistics, and Ministry of Agriculture are planning to extend the technology to other data collection initiatives.

B. Agricultural Market Information Systems (AMIS) While the Global Strategy tries to provide innovative

methods to improve the long-term viability of statistical data systems in developing countries, AMIS addresses the information need to be prepared for and resilient to short-term swings in basic food markets. Just like for the Global Strategy, AMIS has helped pioneer a number of new data collection, analysis and dissemination methods.

Examples:

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Agricultural price crowdsourcing in Indonesia.

Together with WFP and the UN-Global Pulse, FAO is working with Premise Inc. in piloting innovative data

©FAO/Giulio Napolitano

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collection systems to monitor prices fetched and volumes traded on agricultural markets. The project addresses the practical challenges of working in very remote rural locations with limited connectivity, and of testing different approaches to assess product quality and quantities. Network data systems are a promising avenue to monitor agriculture prices and their underlying determinants.

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Crowdsourcing in Nigeria. A proposal is being designed in the context of AMIS to set-up versatile and decentralized agricultural information systems around professional associations. Data flows will connect various market stakeholders (farmers, traders, transporters and their professional associations) and will focus on prices (farm gate, wholesale and retail) as well as production forecasts.

Implementation is starting in early 2016 and its objective is to fill data gaps which are not addressed by National Statistical Offices.

C. Voices of the Hungry (VoH) project

Traditional statistical systems to gauge food security are often plagued by long time delays, high costs of data collection and limited comparability of the data and metrics. The VoH project overcomes all three limitations. In addition, it establishes the Food Insecurity Experience Scale (FIES) as global standard to calibrate the measures obtained from several experience-based food security scales (HFSSM, EBIA, ELCSA, HFIAS, EMSA). This also allows analysts to overcome the lack of comparability of food security measures across different languages, cultures and living conditions. A preliminary baseline on the prevalence of moderate and of severe food insecurity in 2014 has been established for 146 countries covering 95 percent of the world’s population. The FIES indicator has been endorsed for monitoring progress towards SDG Target 2.1.

3.

Why FAO, why partner with FAO, what is the organization’s comparative advantage?

Technical competence, premier Global Public Goods provider in statistics. Based on the 2015 report of the Partnership in Statistics for Development in the 21st Century, FAO one of the five top providers

of development cooperation in statistics. Its Statistics Division is the centre for technical excellence in all areas of food and food security statistics and the leading provider for food and agriculture statistics globally.

The Division hosts FAOSTAT, the largest database on food and natural resource statistics globally. A recent cybermetrics-based evaluation suggests that FAOSTAT receives three times more hits than the UN data warehouse (data.un.org), and about seven times more than the World Bank (data.worldbank.org). The number of citations was 20 times higher than for the UN

database and about twice as high as for the World Bank database. FAOSTAT covers not only production, trade and use statistics, but a host of different data domains including food security, investments, prices, ODA, GHG inventories, and forestry.

FAO has developed and continues to pioneer methodological innovations and constantly improves established methods (FIES, SEEA-Agriculture,

Classifications in food and agriculture, Investment and trade statistics, Food Balance Sheets, GHG inventories, etc.). It has supported the world census for agriculture (WCA) since the 1950s and is currently preparing for the new round of censuses (WCA2020). It always submits its methods to its own regional commissions and eventually to the UNSC, the apex of the UN statistical system. This technical competence is another key criterion for partners to engage with FAO.

Decentralized structure and country presence.

FAO has access to countries and other partners through a number of channels. It maintains country offices in 83 countries, covers its regions with five regional and nine subregional offices and works with international organizations and development partners through six liaison offices. The strong presence at country level and the partnerships with international organizations hold the key for effective programme delivery and FAO’s role as an international coordinator. Coordination in the SDG process is a case in point. Unlike the MDG process, the SDG process is country-driven, goals and targets have been set by countries and indicators need to be endorsed by the 28 member countries of the IAEG-SDG.

With its decentralized structure, FAO is best placed to support both the goals and the process, to help countries monitor progress and provide a framework for accountability at country level.

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Goals:

FAO’s new Strategic Framework (SF) is fully consistent with the goals of the new SDG process, which means that the main activities of FAO both at HQs and in countries are directly supporting the goals that countries have identified for themselves for the next 15 years. The FAO SF is particularly important for SDG 2, but also spans into a series of other SDGs.

Process:

The new SF places special emphasis on country presence and the ability to deliver concrete results at country level. The strong alignment with the SDG goals process ensures that FAO activities support countries in their development process. This also holds for FAO’s work in the area of data, indicators and statistics. As a result, FAO has been called upon in a particular way to provide indicators for SDG monitoring. Its statistical governance bodies (e.g.

regional commissions) ensure a permanent dialogue with member countries, promote an exchange of information, and facilitate the country-driven process.

This country presence makes FAO a particularly interesting partner to engage with for many activities at country level, for statistics but also more generally.

Convening power: One of FAO’s particular strengths lies in its convening power. Through its many commissions, committees and intergovernmental bodies, it has direct access to member countries and development partners.

In the area of statistics, it regularly submits its work to its three regional commissions (APCAS, AFCAS, IICA) for discussion and peer-review and seeks guidance for future work. In tandem, FAO provides both from headquarters, its regional and increasingly its sub-regional offices training and capacity development programmes to roll out new methods, approaches and software packages. This includes work on the FIES, Food Balance Sheets and food security statistics, software (Adept) and indicators, trade statistics, training on methods and technological advances in the context of the global strategy or data dissemination in the context of CountryStat, to mention just a few.

Its convening power also offers an important pillar for partnerships with NGOs, CSOs, and resource partners. No other organization can provide the same multiplier effects

for advocacy work of partners, for sensitizing the civil society to development concerns in food and agriculture, or to raise awareness to current and emerging food security challenges.

Forum for discussions and neutral broker. Over the past 70 years, FAO has helped forge many international agreements and conventions in all its areas of work (RAI, IPPC, Responsible Fisheries, Codex Alimentarius, etc.).

In this work, it has earned a reputation as a neutral broker and a reliable partner. Some of its committees (CFS) have been opened up to other partners and stakeholders and are now committees in FAO rather than committees of FAO.

This reputation as a neutral broker and a reliable partner is also critical in the area of statistics. It is particularly important in the process of development monitoring.

Together with its technical excellence, its reputation as a neutral broker makes FAO an interesting partner in all international statistics and monitoring efforts. To mention just one example (apart from the general SDG process), FAO has received full recognition as a neutral provider of information for GHG emissions, and quality assurance and quality control for national notifications to the UNFCCC. The same holds for trade and trade policy assistance, measuring support to agriculture, monitoring MDG goals, etc.

Example:

Helping countries monitor and report GHG inventories, Quality Control (QC/QA) and Quality Assurance (QA) with the FAOSTAT/GHG tool. The EU-29 routinely uses FAOSTAT for QC of their GHG inventory for agriculture. Mexico and Uruguay undertook a formal QA/QC with FAO before submitting their first annual Biennial Update Reports (BUR) to the UNFCCC. The US and China use FAOSTAT informally as a QC tool. Many UNREDD countries use FAOSTAT as part of their official REDD activities; these include Ecuador, Colombia, and Paraguay. The UNFCCC West Africa Project employs FAOSTAT in capacity development for BUR submissions for Benin, Burkina Faso, Cabo Verde, Côte d’Ivoire, Ghana, Senegal and Togo. Many other countries use FAOSTAT for routine checks on their GHG inventories, including Lebanon, Mongolia and South Africa.

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