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January 2015

Review of Global Food Price Databases Overlaps, Gaps and Opportunities to Improve Harmonization

This paper supports the overall objectives of the Food Security Information Network (FSIN) to strengthen information systems for food and nutrition security and promote evidence-based analysis and decision making. The views expressed and the designations employed in this document are those of the author and do not necessarily reflect the views of FAO, IFPRI, WFP or their governing bodies. This paper has not undergone standard peer review procedures of FAO, IFPRI, or WFP.

The designations employed and the presentation of material do not imply the expression of any opinion whatsoever on the part of FAO, IFPRI and WFP and their governing bodies concerning the legal or development status of any country, territory, city or area or of its authorities, or concerning the delimitation of its frontiers or boundaries.

The mention of specific companies or products of manufacturers, whether or not these have been patented, does not imply that these have been endorsed or recommended by FAO, IFPRI, or WFP in preference to others of a similar nature that are not mentioned.

FAO, IFPRI, or WFP encourage the use and dissemination of material in this information product. Reproduction and dissemination thereof for non-commercial uses are authorized provided that appropriate acknowledgement of FAO, IFPRI, or WFP as the source is given and that FAO’s, IFPRI’s, or WFP’s endorsement of users’ views, products or services is not implied in any way.

This publication has received funding from the European Union through the “Improved Global Governance for Hunger Reduction Programme” and from USAID. The views expressed herein can in no way be taken to reflect the official opinion of the European Union or USAID.

All requests for translation and adaptation rights and for resale and other commercial use rights should be addressed to the FSIN secretariat at [email protected]. © WFP 2015

Photo creditsWFP / Diego Fernandez Gabaldon.

January 2015



Review of Global Food Price Databases Overlaps, Gaps and Opportunities to Improve Harmonization

Review of Global Food Price Databases: Overlaps, Gaps and Opportunities to Improve Harmonization

This report has been prepared under the auspices of the Food Security Information Network (FSIN, a global community of practice jointly established by FAO, IFPRI and WFP), which aims

to strengthen food and nutrition security information systems and networks. The financial support from USAID and the European Commission for this work is greatly appreciated. The overall goal of the report is to take stock of the existing situation of global food price collection and to provide guidance on the harmonized price data system and management. A consultation process was carried out with the main providers and users of global food price data, namely FAO, IFPRI, IMF, FEWS NET, WFP and the World Bank.

The study has been carried out by Kisan Gunjal, international consultant and primary author, under the supervision of Issa Sanogo and Tobias Flaemig (from the Economic and Market Analysis Unit, WFP) and Mark Smulders (Senior Economist and FSIN Steering Committee member, FAO). The team is grateful to Arif Husain (Chief Economist and Deputy Director PPI, Analysis and Nutrition Service, WFP), Gary Eilerts (USAID Program Manager for FEWS NET) and Maximo Torero (Director, Markets, Trade and Institutions Division, IFPRI) for their support and overall guidance.

The author gratefully acknowledges a significant contribution to this study through a consultation process and/or review comments from the following individuals:

FAO: Shukri Ahmed, Liliana Balbi, Felix Baquedano, Franc Cachia, Sangita Dubey, Yanyun Lee, Cristian Morales, Fabio Palmeri, Paul Racionzer and Luca Russo

FEWS NET/USAID: Sonja Perakis and Felix Lee (FEWS NET); Michele McNabb (USAID) and Frank Riely (Kimetrica)

IMF: Marina Rousset

WFP: Wael Attia, Jean-Martin Bauer, Oscar Caccavale, Marine Lalique, Joyce Luma, and John McHarris

World Bank: John Baffes, Jose Cuesta, Aira Htenas, Talip Kilic, and Will Martin.

Finally, the author would like to thank the FSIN Secretariat team: Alexis Hoskins (WFP Secretariat Coordinator), Lavinia Antonaci (FAO) and Michele Kiermeier (FAO) for their technical and organizational support and Zoe Hallington for editorial and review comments.

Acknowledgements


ACF Action contre la faimACTED Agency for Technical Cooperation and Development AfDB African Development BankALPS Alert for Price Spikes (WFP)AMIS Agricultural Market Information SystemAPI Application programming interfaceCME Chicago Mercantile ExchangeCPC UN’s Central Product ClassificationCPI Consumer price indexESS FAO Statistics DivisionEST FAO Trade and Markets DivisionFAO Food and Agriculture Organization of the United NationsGIEWS Global Information and Early Warning System on food and agricultureFAOSTAT FAO’s Statistics DatabaseFEWS NET Famine Early Warning System NetworkFNS Food and nutrition securityFPMA Food Price Monitoring and AnalysisFSIN Food Security Information NetworkFSMS Food security monitoring systemIFPRI International Food Policy Research InstituteIMF International Monetary FundJRC European Commission’s Joint Research CentreNGO Non-governmental organizationUSAID United States Agency for International DevelopmentUSD United States dollarUSDA United States Department of AgricultureVAM Vulnerability Analysis and Mapping WFP World Food Programme

Acronyms


1. Executive Summary 32. Background and Introduction 63. Objectives and Approach 84. Global Food Price Databases: Primary Purpose and Uses 9

4.1. FAO datasets 94.2. WFP 104.3. FEWS NET 104.4. World Bank 114.5. IFPRI 114.6. IMF 124.7. JRC/AfDB initiative 12

5. Metadata Used by FAO, WFP and FEWS NET Datasets 135.1. Dataset size 135.2. Country coverage 145.3. Total number of price series per country 145.4. Market coverage 175.5. Commodities 195.6. Level of price 205.7. Starting date 205.8. End date 215.9. Data sources 22

6. Overlaps and Gaps 246.1. Overlaps 246.2. Gaps 26

7. Database Management 277.1. The process 277.2. Data format and database platform to improve interoperability 287.3. Quality control methods used by each agency 297.4. Human resources used by each agency 29

8. Opportunities to Improve the Inter-Operability of Different Datasets 308.1. Strengthening back-end cooperation 308.2. Cooperation in sharing CPI and exchange rates data 308.3. Making datasets inter-operable with a common structure 308.4. Technical aspects of database management 31

9. Recommendations for Improved Integration and Harmonization 32

Annex 1 - Sources of Price Data Cited in the WFP, FAO and FEWS NET Datasets 34Annex 2 - GIEWS Food Price Data and Analysis Tool – Data Format and Platform 36

Table of Contents


List of Figures

Figure 1. International prices of the main cereals 6Figure 2. Number of price series by country 16Figure 3. Number of price series per commodity (aggregated) in combined three datasets 19Figure 4. Distribution of different types of prices (% share) 20Figure 5. Flow chart of steps involved in price database system 27

List of Tables

Table 1. Metadata comparison of the three global datasets 13Table 2. Number of countries covered in WFP, FAO and FEWS NET price datasets 14Table 3. List of countries covered in the global datasets 15Table 4. Number of price series in the three datasets 17Table 5. Markets covered - Top 10 and bottom 10 developing countries 18Table 6. Comparison of price series starting dates (% of dataset) 20Table 7. How up-to-date are the global price datasets? 21Table 8. Countries with WFP, FEWS NET and partners as the source of data 23Table 9. Number of price series and overlapped series in different datasets 24Table 10. Developing countries with no price information in the global datasets 26

Figures and Tables

1. Executive Summary 3


The rising volatility and periodic hikes in food prices in recent years have become a major concern for policymakers worldwide. Sharp spikes in food prices have serious food security consequences

as they can affect large numbers of vulnerable people and governments/countries that are heavily dependent on food imports. To address food security and agricultural development challenges, policymakers need easy access to up-to-date prices and analysis not only from within developing countries, but also across borders, regionally and globally. Whether for early warnings or longer term development planning, the need for a comprehensive, reliable and timely global dataset(s) is apparent and urgent.

This study aims to take stock of the existing global food price datasets, examining overlaps and gaps, and identifying opportunities for greater harmonization to improve end-user access to information.

Global stakeholders: International food price data and related analytical products are currently provided by United Nations agencies (FAO and WFP), international organizations (the World Bank, IMF and IFPRI) and other national or regional systems (USAID’s FEWS NET). Among these, FAO, WFP and FEWS NET are the main providers of national and sub-national food commodity price data, together covering 104 countries. Therefore, this study primarily focuses on these three datasets. The World Bank, IMF and IFPRI also collect raw commodity price data and develop various aggregated price indices, indicators and other analytical products to inform policymakers about global food market changes and food security impacts. However, depending on their source, there is generally no open access to most of their raw price data. That said, their analysis and analytical products are disseminated as global public goods.

FAO has four main food price datasets: (a) International Commodity Prices, covering around 40 price quotations of all major food and agricultural commodities; (b) FAO Food Price Index, with the 70 price quotations that go into its calculations; (c) the Global Information and Early-Warning System (FAO GIEWS) food price data and analysis tool, which presents over 1200 price series for 89 countries;1 and (d) the FAOSTAT historical dataset, including producer prices and consumer price indices for most countries.

The FAO GIEWS price dataset, the main focus of this study, displays commodity prices for selected markets in urban and rural areas (or the national averages in some cases). The tool aims to give early warning of impending food emergencies and to provide markets and food security analysis. The dataset includes consumer price indices and official US dollar exchange rates of national currencies to allow quick conversions to real and USD prices for more meaningful comparisons over time and across countries. The entire price dataset is intended to be an open access global public good as part of FAO’s global data provision mandate. It also meets food security monitoring, analysis and policymaking needs within and outside the organization.

The FAO GIEWS price tool allows users to download and create various price charts, over-time comparisons and the basic statistical descriptors of the series. However, it requires fast internet access. The price tool is a component of the Food Price Monitoring and Analysis (FPMA) activities, which include a website and the Global Food Price Monitor. Analysis of current price data is also

1. On the basis of the results of the assessment, assurance activities are planned with each of the executing partners. These are described, along with the agreed cash transfer modality, in the annual work plan and SOPs.

1. Executive Summary

1. Executive Summary4


presented in other GIEWS publications such as the quarterly Crop Prospects and Food Situation reports and through periodic alerts/updates on food security analysis. With 75 percent of the price series updated during the previous month, FAO GIEWS prices are the most up-to-date among the three datasets compared in this study.

WFP’s Vulnerability Analysis Mapping (VAM) food and commodity prices data system includes food price information from 75 countries, mainly where WFP is active. Although the system primarily serves internal demand to support programme decision-making, the price collection and the analytical information generated is a global public good. WFP’s food price dataset is the largest of the three datasets in terms of the number of price series; it is ten times larger than that of FAO and seven times that of FEWS NET. It has wider coverage in terms of sub-national rural remote markets and in some cases, in addition to basic food commodities, it incorporates the prices of other food security related items such as fuel, wages and non-food products. It sometimes contains prices of nutritionally important commodities such as vegetables, fruits and animal products.

The system does not support the automatic conversion of nominal prices to real or USD prices. However, users can make USD-equivalent conversions using the formal/informal exchange rates reported as part of the dataset. WFP price series are less up-to-date than those of FAO and FEWS NET.

The WFP VAM price tool allows data downloads and price charts. Analytical products include the Alert for Price Spikes (ALPS), seasonally adjusted prices, changes to the cost of the food basket, country-specific bulletins and the quarterly publication, The Market Monitor.

USAID’s FEWS NET maintains 1790 monthly price series for selected regions and countries. It covers 52 countries, divided into 21 FEWS NET Presence Countries, 14 Remote Monitoring Countries and the remaining Other Countries that cover internationally or regionally important reference markets. Its coverage of markets and commodities is wider than that of FAO, but smaller than that of WFP. The data is primarily intended for internal use and thus not meant to be a global public good. Data sharing is limited since some of the countries and data providers may not want their data disseminated. The strengths of the system include the ability to collect or facilitate price data generation in countries where FEWS NET operates.

FEWS NET publishes analysis of market prices and other changes affecting food security via its monthly price bulletins and food security reports, as well as periodic web alerts/updates.

Overlaps:2 The three datasets contain a huge number of price series, so the overlaps analysis was done using a randomly drawn sample of 15 out of the 76 countries where the datasets overlap.3 The overlap between any two datasets is fairly high. Overall, 44 percent of FEWS NET series in this 15-country sample also appear in WFP set, and 12 percent appear in the FAO dataset. Around a quarter of FAO’s price series also appear in WFP’s dataset, and 30 percent feature in the FEWS NET dataset. Given the large number of its price series, WFP has a much lower relative overlap: 2 percent with FAO and 9 percent with FEWS NET. However, in absolute terms, 37 WFP series overlapped with FAO and 166 overlapped with FEWS NET.

2. Two or more series are considered overlapping if they refer to the same commodity, market and price level (retail/wholesale). Further explanation is provided in Section 6.

3. The sample approach was used because of time and resource constraints. The actual results based on all 76 countries with overlapping datasets or on all 104 countries may vary.

1. Executive Summary 5


The overlapping datasets may provide opportunities for collaboration and data sharing, especially if additional resources are devoted to collecting these data independently.

Complementarities: The two UN datasets complement each other by covering macro versus micro level. FAO is relatively strong in front-end data management, while WFP is strong in back-end data collection. The FAO dataset includes international or main exporter prices, continuously updated consumer price indices (CPI), and the official currency exchange rates, which could be potential areas of cooperation and data sharing. By contrast, WFP data covers a large number of markets and commodities and includes nutritionally important foods.

Gaps: Of the 104 countries in the three datasets, six countries had prices that had not been updated since December 2013 or earlier.4 About two dozen developing countries have no food price information. There is also no uniformity in terms of the coverage of commodities, and most country price collections do not have prices for commodities that represent the nutritional wellbeing of the population, such as vegetables, fruit or animal/fish products.

Recommendations for increased harmonization: Based on analysis of the three datasets, the following recommendations are made to help improve cooperation, integration and harmonization, thereby raising the overall efficiency, usefulness and timeliness of the price data for the end user.

• Increase cooperation, especially in the back-end of the database process. This covers the collection, collation and uploading of price data. Other areas include sharing international food prices, fuel prices, CPI and currency exchange rates for meaningful geo-temporal comparisons by converting nominal prices to real and USD prices.

• Use a standard structure for metadata, including the names of countries, markets and commodities, level of market price, units of measurement and currency. This would improve the inter-operability and merging of data from different sets.

• Set up a technical working group to provide guidance on an ideal set of market information needs – including a basket of essential food security commodities – to meet food security monitoring and programming needs. The group could also help develop a strategy to safeguard the sustainability of maintaining useful and timely information for early warnings and policy analysis.

• Develop a data collection/dissemination strategy to fill the gaps in the global datasets. Based on national information needs and gaps analysis, the strategy should prioritize the 23 missing major developing countries and develop national capacity for countries with major food security concerns.

4. As of August 2014, when the data for this study was analysed. The six countries are the Central African Republic, Eritrea, Liberia, Namibia, Sierra Leone and Timor-Leste. Subsequent to the analysis, updated price data has been provided for some of these countries.

2. Background and Introduction6


Increased price volatility and periodic price spikes have the potential to affect many people, especially in low-income food-deficit countries, as they increase food insecurity, hunger and the

number of people requiring food assistance. As seen from Figure 1, the nominal USD prices of the three main staple cereals tripled between the beginning of 2005 and mid-2008, when they reached their new peaks. They fell in 2009 and 2010 but rose again in 2011: wheat and maize prices reached double their lowest levels, while rice prices rose by a third. Price increases for cereals and other commodities are a significant factor driving household food expenditure.

Price volatility is also a major concern for exporters, importers and producers as it makes income more unpredictable. For consumers, it creates uncertainty over expenditure. Food and commodity price data play an important role in monitoring people’s purchasing power and their access to food. The timely release of market data at all levels increases market transparency and helps reduce volatility. More in-depth analysis of market data and information can provide early warnings, inform household food security analysis and help formulate and implement food policies and food assistance programmes. Thus, reliable, timely and easily accessible data on food prices is essential to managing food security and mitigating adverse impacts, especially for vulnerable people.Given the wide public interest in market data and analysis, various agencies with a global food

2. Background and Introduction

Figure 1. International prices of the main cereals

Source: FAO GIEWS.

2. Background and Introduction 7


security mandate5 maintain their own market information systems and databases, as do national government agencies and private sector entities. Technical meetings of the Food Security Information Network (FSIN) in October 2012 concluded that the roles of the different global players appear to be largely complementary. However, some overlap and duplication of efforts in data collection, data management and analysis was observed. As a first step, it was agreed to review the practices of the key players in food price market data collection, management and analysis in order to increase cooperation and harmonization efforts nationally and internationally.

The above-mentioned international players also support national and regional capacity development. Better coordination could help develop more uniform and efficient approaches to improving national and regional capacities in market price data collection, management and analysis. Efforts should build on existing system capacities and complementarities, promoting harmonization and avoiding duplication as much as possible.

The FSIN was established by the Food and Agriculture Organization of the United Nations (FAO), the International Food Policy Research Institute (IFPRI) and the United Nations World Food Programme (WFP) in October 2012. It is a global community of practice that aims to strengthen food and nutrition security (FNS) information systems and networks to promote greater evidence-based decision-making by all actors, including governments, NGOs and the private sector. Its main objectives are to provide access to harmonized methods for FNS data collection, analysis, communication and decision-making, and to facilitate national capacity development on FSN information systems. This study has been undertaken under the auspices of FSIN to provide guidance on harmonized price data collection and management.

5. Including FAO, IFPRI, FEWS NET and WFP.

3. Objectives and Approach8


This comparative study is the first phase6 of a three-phased approach. It aims to assess the complementarities and overlaps of global food market price databases maintained by key

development agencies. The study will review the data collection, quality control mechanisms, management, usage, analysis methods and tools of cross-country databases. The output will be a set of proposed options and actions to improve global collaboration and harmonization, and hence greater efficiency in development efforts.

The main objectives of the study are as follows:

1. To outline the data and information captured in global food price databases established by the main global food price data providers, including FAO, WFP, FEWS NET, IFPRI, World Bank and the International Monetary Fund (IMF). This means taking stock of information content including the data structure, main features, information sources and quality control of the various databases.

2. To identify overlaps and gaps in content and functionality between the reviewed databases.

3. To identify opportunities to improve complementary/unique parts of the databases in order to make them more useful to stakeholders, particularly to make them more ‘inter-operable’.

4. To provide concrete suggestions to help further integration and better harmonization of the databases, depending on the complementarities/overlaps identified.

6. Phase 2 will focus on how market price data is collected and used nationally, with support from regional institutions. A small Technical Working Group (TWG) will be established to validate and take forward the recommendations from Phase 1, developing guidance on how to ensure consistent, comparable market price data collection and management at country level. Phase 3 will focus on building national capacity for market price data harmonization activities.

3. Objectives and Approach

4. Global Food Price Databases: Primary Purpose and Uses 9


Currently, international food price data is provided by United Nations agencies (FAO and WFP), international organizations (the World Bank, IMF and IFPRI) and other national or regional

systems (e.g. USAID’s FEWS NET). FAO, WFP and FEWS NET are the main providers of national and sub-national food commodity price data, and together they cover about 100 countries. The others provide international commodity prices, more aggregated price indices and other analytical products. Different agencies collect market prices for different purposes, but the common primary purpose of all three datasets is to provide early warnings of food insecurity and to inform the public of evolving market anomalies and food insecurity. WFP also requires the price dataset for its own programming needs, such as for food procurement, cash and vouchers, and to monitor household food insecurity for assessing food assistance. The FAO and WFP data are provided as a global public good. Some of it, depending on the length of the series, can be used for short or long-term analyses such as market transparency, integration, efficiency, transmission, volatility and policy formulation. FEWS NET price data has the additional purpose of meeting the domestic political needs of informing US polices and responses regarding global food security.

4.1 FAO datasets7

FAO collects food prices in its Economic and Social Department. The data is intended for different audiences and purposes. There are four main food price datasets, three in its Trade and Markets Division (EST) and one in its Statistics Division (ESS).

1. International Commodity Prices: weekly prices of 15 commodities – bananas, cocoa, coffee, cotton, jute, maize, rubber, sisal, sorghum, soybeans, sugar, tea, wheat, wool and rice – and monthly prices of 25 animal products, oils and others.

2. FAO Food Price Index: This monthly index is based on 73 price quotations: cereal (27 quotations), vegetable oil (10), dairy (8), meat (27), and sugar (1). The raw data is primarily for internal use, but it can be downloaded from FAO’s World Food Situation portal (http://www.fao.org/worldfoodsituation/foodpricesindex/en/).

3. FAO GIEWS Food Price Data and Analysis Tool:8 presenting more than 1,200 price series from 89 countries, including domestic prices for 85 countries. The GIEWS price dataset, the main focus of this study, presents prices for selected cities or the national average to indicate changes in general price trends. GIEWS provides export prices (43 international food price series) of the main world suppliers of different key commodities. The dataset also includes CPIs and the official US dollar exchange rates of national currencies, so nominal prices can be quickly converted to real and USD prices for more meaningful comparisons over time and across countries. The data is primarily intended as a global public good as part of FAO’s global data provision mandate. It also meets internal and external needs for food security monitoring, analysis and policymaking.

7. FAO have recently established the Agricultural Market Information System (AMIS). This multi-agency information system aims to improve global market transparency and to stabilize global food market prices. It covers four commodities: wheat, rice, maize and soybeans. Besides the G20 countries, AMIS includes seven other major food exporting and importing countries. It does not replace national and regional market information systems. It does not maintain a separate price dataset but relies on existing EST price data.

8. Available at http://www.fao.org/giews/pricetool/

4. Global Food Price Databases: Primary Purpose and Uses

4. Global Food Price Databases: Primary Purpose and Uses10


The FAO GIEWS Price Tool allows users to create and download price charts, over-time comparisons and the basic statistical descriptors of the series. The price data is used for the monthly publication Global Food Price Monitor and the quarterly Crop Prospects and Food Situation, as well as periodic alerts on early warnings and food security analysis. It is the most up-to-date dataset, with 75 percent of the price series updated during the current or previous month.

4. FAOSTAT Prices - historical data on producer prices (latest data for 2012) and also consumer price indices for most countries (most updated for 2013, some countries updated up to April 2014).

4.2 WFP

WFP’s food price monitoring includes food price information for 75 countries, primarily where WFP is active. The system mostly serves in-house demand to support decision-making for modality choices (in-kind versus cash and vouchers) as well as for procurement, emergency response, early warnings, monitoring and analysis. The information generated has become a public good that is used by other parties, including companies, international NGOs, donors and research organizations. WFP works with the national agriculture (or other) ministry to obtain the data from their market information system, but if the existing system does not cover WFP’s information needs, the organization sets up its own local data collection system.

WFP’s dataset is the largest of the global datasets in terms of the number of price series: it is ten times that of FAO and seven times that of FEWS NET. It has a wider coverage in terms of sub-national remote markets and food security related commodities, including fuel prices and in some cases, wage rates. In addition to the main staples, it contains the prices of nutritionally important foods such as fruits, vegetables and animal products. It does not support the automatic conversion of nominal prices to real or USD prices. However, users can make USD conversions using the formal/informal exchange rates reported as part of the dataset. The prices in the dataset are not as up to date as those of the other two datasets.

The WFP VAM Price Tool9 allows data downloads and price charts. The price data is analysed and presented in its quarterly publication, The Market Monitor. WFP’s analytical products also include the Alert for Price Spikes (ALPS), a new price indicator that monitors the extent to which a local food commodity market experiences unusually high price levels.

4.3 FEWS NET

USAID’s Famine Early Warning Systems Network (FEWS NET) uses market data and information collected nationally and sub-nationally by in-country market information systems to conduct its own food and nutrition security analysis. Its dataset contains 1,791 monthly price series. The 52 countries covered are divided into 21 ‘FEWS NET presence’ countries, 14 ‘remote monitoring’ countries and 17 ‘other’ countries. The latter category comprises internationally or regionally important reference markets, of which 6 are updated from the FAO GIEWS dataset. It has a wider coverage of markets and commodities than WFP, although fewer average markets per country. The data is primarily intended

9. Available at http://Foodprices.vam.wfp.org

4. Global Food Price Databases: Primary Purpose and Uses 11


for internal use and is thus not meant to be a global public good. FEWS Net does not consider data collection and storage for public use as its function. It also has limitations on open sharing as some of countries and data providers do not allow their data to be disseminated.

FEWS NET uses the price datasets to analyse market price and condition changes affecting food security. The analysis is published in its monthly price bulletins and food security reports, as well as via periodic web alerts on food insecurity issues.10

4.4 World Bank

The World Bank maintains around 100 price series covering agricultural and non-agricultural commodities, published monthly. The list is limited as they have to have data stretching back to 1960. Of the 100 series, 40 are for agricultural commodities, which include 7 different types of fertilizer. The data mainly contains world prices, typically those of world leaders or exporters. It is used to construct 12 different price indices including agriculture and main food items, raw materials, grain, oil and meal prices, as well as a forecast deflator. Price data is procured from commercial companies so the raw data is not made public. The World Bank’s Commodity Markets Outlook is published quarterly and contains analysis of domestic prices of key grains. A small section on the domestic prices in this publication is based on FAO GIEWS price data. All of the analytical products and processed data are a global public good.

4.5 IFPRI

IFPRI currently focuses on food price volatility. It has developed a tool called the Excessive Food Price Variability Early Warning System, which depicts the historical price volatility (daily, weekly, monthly or annual) of hard wheat, soft wheat, maize, rice and soybeans from 2000 to the present. The dataset requires high frequency data – daily or weekly – to make the price volatility calculations. The tool identifies whether prices are erratic at a certain point in time, particularly during food price crises. This is useful for food-importing countries, which will be able to detect when international prices are not supported by market fundamentals. IFPRI’s food security portal11 brings together different sources of market information. The indicators to measure excessive volatility are created using daily price data from the Chicago Mercantile Exchange.12 Additional data is purchased from Reuters and Bloomberg and thus IFPRI cannot publish the raw data, except for the CME data on the main grains.

4.6 IMF

The IMF price data set contains 54 commodities, including 24 foods, 3 beverages and certain agricultural raw materials such as cotton, rubber and hide. Agriculture is big in terms of commodities but smaller in terms of weight based on its trade value; energy is the largest sector with a 60-percent

10. See http://www.fews.net/

11. Available at www.foodsecurityportal.org and the price variability tool at http://www.foodsecurityportal.org/policy-analysis-tools/excessive-food-price-variability-early-warning-system

12. See http://www.cmegroup.com/trading/agricultural/

4. Global Food Price Databases: Primary Purpose and Uses12


weighting. The IMF Commodity Price Indices serve as international benchmarks (from global leaders) for observing general trends and changes in commodity markets, as well as in their various sectors. Commodity price projections are used to calculate changes in terms of trade and forecasts of national accounts.

Most of the data is purchased from data providers such as Bloomberg, Platts, Data Stream of Thompson and Reuters. As a result, the IMF cannot disseminate raw data. Some data is also collected from USDA and CME. The processed data is used as an input for internal research, as well as by external users from central banks, investment firms, and research and academic institutions. All analytical products and indices are in the public domain.

4.7 JRC/AfDB initiative

A new initiative called the Africa Food Prices Collection was launched in June 2014 by the European Commission’s Joint Research Centre (JRC) and the African Development Bank (AfDB), in partnership with Knoema. Its main objective is to collect weekly prices in Africa of various agricultural products including cereals, meat, fish, vegetables, oils, fruits and dairy products, using modern technologies and crowd-sourcing techniques. The dataset is intended to be open-access. The consultation process is currently underway. Various issues such as reliability, representativeness and sustainability will be critical in assessing the usefulness of the price data collected in this way. If and when proven effective and efficient, this approach would force changes in standard price datasets, such as those discussed in this study.

5. Metadata Used by FAO, WFP and FEWS NET datasets 13


This section describes the metadata of three main datasets, examining data structure, sources, and the quality control and analysis features of the price databases.

The metadata includes the country name, markets (with geo-reference), commodity, level/type of price (e.g. retail, wholesale or farm gate), frequency (weekly or monthly), start and end date, and source. This information will help map the prices and determine the coverage, overlaps, and gaps set out in the terms of reference of this study.

5.1 Dataset size

The overall size of the three datasets is shown in Table 1. The food price datasets maintained by WFP, FAO and FEWS NET are fairly large and together cover 104 countries. Of these, 89 are covered by FAO, 75 by WFP and 52 by FEWS NET. With over 13,000 price series, the WFP dataset is the biggest, being seven times larger than that of FEWS NET and ten times that of FAO. WFP data coverage is much deeper in most countries, with 16 markets13 per country and more commodities on average.

WFP FAO FEWS NET

Total number of price series 13075 1221 1794

Number of countries 75 89 52

Number of markets 1237 256 419

Number of commodities 239 193 117

Average price series per country 174 14 35

Average markets per country 16 3 8

13.Theactualnumberofmarketsisdifficulttodeterminesincethepricesofsomecountriesarenationalaverages.Here,aoneprice,onemarketprincipleis used.

Table 1. Metadata comparison of the three global datasets

Note: The numbers of price series, markets and commodities have been counted from the metadata files obtained from each agency in July and August 2014. They may differ slightly from the actual numbers in the respective datasets, especially at a different point in time.

5. Metadata Used by FAO, WFP and FEWS NET Datasets

5. Metadata used by FAO, WFP and FEWS NET datasets14


5.2 Country coverage

Thirty-six countries are common to all three datasets. A further 76 potentially overlap in two or three datasets (see Tables 2 and 3). FAO and WFP cover 60 of the same countries; there are a further 18 countries unique to FAO, and another 10 unique to WFP. All 52 countries covered by FEWS NET are covered by WFP, FAO or both. See Table 3 for a complete breakdown of countries by dataset.

Limitations on the country coverage are due to each agency’s focus or a lack of access to national data. There are around 150 Emerging Market and Developing Economies;14 the three datasets cover 96 of them: WFP includes 74, FAO 81 and FEWS NET 48, omitting some important food security countries. Any effort to harmonize the three datasets and reduce duplication could be an opportunity to expand coverage to the missing countries.

5.3 Total number of price series per country

There are 16,090 price series in the three datasets, that is, if all the series are added together without eliminating overlaps and duplication. Among developing countries, they range from as few as 3 (for Kazakhstan) to 2,465 (for Rwanda), with the average of 155 series per country. A ranked list of all countries is presented in Figure 2.

No. of countries coveredBy all 3 36WFP & FAO 24WFP & FEWS NET 5FAO & FEWS NET 11WFP alone 10FAO alone 18Total 104No. of countries covered including overlapWFP 75FAO 89FEWS NET 52Total 104No. of countries missing from current 104WFP 29FAO 15FEWS NET 52

14 . On the World Bank’s list, found at http://www.imf.org/external/pubs/ft/weo/2012/02/pdf/statapp.pdf

Table 2. Number of countries covered in WFP, FAO and FEWS NET price datasets



Table 3. List of countries covered in the global datasets

Note: Breakdown based on the metadata file information valid in July and August 2014. The FAO GIEWS country count is that of 24 July 2014 when the metadata file was received; since then, five new countries (Liberia, Morocco, Paraguay, Sierra Leone and Swaziland) have been added to their database.

No. Country Count DATASET No. Country Count DATASET

1 Afghanistan 3 WFP FAO FEWS 53 Lesotho 2 WFP FAO 2 Benin 3 WFP FAO FEWS 54 Myanmar 2 WFP FAO 3 Burkina Faso 3 WFP FAO FEWS 55 Nepal 2 WFP FAO 4 Burundi 3 WFP FAO FEWS 56 State of Palestine 2 WFP FAO 5 Cape Verde 3 WFP FAO FEWS 57 Peru 2 WFP FAO 6 Chad 3 WFP FAO FEWS 58 Philippines 2 WFP FAO 7 Costa Rica 3 WFP FAO FEWS 59 Sri Lanka 2 WFP FAO 8 Djibouti 3 WFP FAO FEWS 60 Timor-Leste 2 WFP FAO 9 El Salvador 3 WFP FAO FEWS 61 Côte d'Ivoire 2 WFP FEWS10 Ethiopia 3 WFP FAO FEWS 62 Gambia 2 WFP FEWS11 Ghana 3 WFP FAO FEWS 63 Liberia 2 WFP FEWS12 Guatemala 3 WFP FAO FEWS 64 South Sudan 2 WFP FEWS13 Guinea 3 WFP FAO FEWS 65 Yemen 2 WFP FEWS14 Haiti 3 WFP FAO FEWS 76 Argentina 2 FAO FEWS15 Honduras 3 WFP FAO FEWS 77 Australia 2 FAO FEWS16 Kenya 3 WFP FAO FEWS 78 Canada 2 FAO FEWS17 Kyrgyzstan 3 WFP FAO FEWS 79 France 2 FAO FEWS18 Madagascar 3 WFP FAO FEWS 80 Kazakhstan 2 FAO FEWS19 Malawi 3 WFP FAO FEWS 81 Mexico 2 FAO FEWS20 Mali 3 WFP FAO FEWS 82 South Africa 2 FAO FEWS21 Mauritania 3 WFP FAO FEWS 83 Thailand 2 FAO FEWS22 Mozambique 3 WFP FAO FEWS 84 Togo 2 FAO FEWS23 Nicaragua 3 WFP FAO FEWS 85 USA 2 FAO FEWS24 Niger 3 WFP FAO FEWS 86 Viet Nam 2 FAO FEWS25 Nigeria 3 WFP FAO FEWS 66 Central African Republic 1 WFP 26 Pakistan 3 WFP FAO FEWS 67 Congo 1 WFP 27 Panama 3 WFP FAO FEWS 68 Guinea-Bissau 1 WFP 28 Rwanda 3 WFP FAO FEWS 69 Iran 1 WFP 29 Senegal 3 WFP FAO FEWS 70 Iraq 1 WFP 30 Somalia 3 WFP FAO FEWS 71 Jordan 1 WFP 31 Sudan 3 WFP FAO FEWS 72 Sierra Leone 1 WFP 32 Tajikistan 3 WFP FAO FEWS 73 Swaziland 1 WFP 33 Uganda 3 WFP FAO FEWS 74 Syrian Arab Republic 1 WFP 34 United Rep. of Tanzania 3 WFP FAO FEWS 75 Turkey 1 WFP 35 Zambia 3 WFP FAO FEWS 87 Angola 1 FAO 36 Zimbabwe 3 WFP FAO FEWS 88 Belarus 1 FAO 37 Armenia 2 WFP FAO 89 Brazil 1 FAO 38 Azerbaijan 2 WFP FAO 90 Chile 1 FAO 39 Bangladesh 2 WFP FAO 91 China 1 FAO 40 Bhutan 2 WFP FAO 92 Ecuador 1 FAO 41 Bolivia 2 WFP FAO 93 Eritrea 1 FAO 42 Cambodia 2 WFP FAO 94 Gabon 1 FAO 43 Cameroon 2 WFP FAO 95 Israel 1 FAO 44 Colombia 2 WFP FAO 96 Mongolia 1 FAO 45 Dem. Republic of the Congo 2 WFP FAO 97 Namibia 1 FAO 46 Dominican Republic 2 WFP FAO 98 Republic of Moldova 1 FAO 47 Egypt 2 WFP FAO 99 Russian Federation 1 FAO 48 Georgia 2 WFP FAO 100 Samoa 1 FAO 49 India 2 WFP FAO 101 Tunisia 1 FAO 50 Indonesia 2 WFP FAO 102 UK 1 FAO 51 Italy 2 WFP FAO 103 Ukraine 1 FAO 52 Lao People's Democratic Republic 2 WFP FAO 104 Uruguay 1 FAO



Most countries have far fewer than 100 price series. Six developing countries have five or fewer series usually from 1 or 2 markets (partly because their prices are national averages). An adequate coverage for food security monitoring purposes may require many more series per country, even just to know the degree of market integration. For example, a country with 10 regions and 5 crucial commodities in a food basket may require 50 price series.

At the top of the range, Rwanda has nearly 2,500 price series with 2,314 for WFP, 148 for FEWS NET and 3 for FAO. These price series include three types of fruits and ten different vegetables from markets throughout the country. The second biggest is India with 934 series followed by Mozambique with 815, covering a vast number of markets and commodities available from national price datasets. Note that there may be more data collected and available locally than is shown in the three datasets.

Figure 2. Number of price series by country

Note: This chart includes the overlap of some series between different datasets.



TopfivedevelopingcountriesRwanda 2465India 934Mozambique 815Myanmar 723Syrian Arab Republic 696BottomfivedevelopingcountriesChile 5Samoa 5Gabon 4Namibia 4Kazakhstan 3

The primary reason behind the extent of coverage in many countries is supply: if the data is available nationally, it is included. However, this is not always the case. FAO GIEWS only reports data for four selected major city markets for the main commodities, even when the national database includes many markets and commodities.

The type and nature of price data needed for particular purposes should rationalized and standardized. If fruit and vegetable prices are important for economic and nutritional considerations, it is necessary to decide how many and which types should be part of the global price data. Some governments may collect very little or no price data, in which case the question is how to ensure a decent coverage of critical price information. By contrast, some governments collect a vast amount of market price data. How much of that should be displayed in the global price datasets? Does the global dataset replace or mirror the national ones? What should be the relationship between a national and global dataset? All these questions need to be answered to make global food price collection adequate, cost efficient and sustainable in the long run. The right answers will depend on the monitoring purposes of each organization, but guidance is required.

5.4 Market coverage

For a large number of countries, including around 30 developing nations, the global datasets report prices from just one or two markets. Yet there is great variation, with as many as 82 different markets reported for Rwanda. Table 5 lists countries at the both ends of the spectrum. Note that the market count does not apply to countries where national average prices are reported, rather than prices from specific markets. This is the case for Egypt, Indonesia, Swaziland, Tunisia, Turkey, Uruguay and others. The national average may provide a general trend of the prices in a country, especially where price uniformity and market integration are evident, but in general it is of less value in identifying pockets of food insecurity in various parts of the country and hence less useful for early warnings of sub-national food insecurity. Of course, the more markets, the better. However, needs and resources required have to be balanced according to each country’s priorities.

Table 4. Number of price series in the three datasets



Top 10

Rwanda 82

Niger 77

Mali 71

Malawi 70

Zambia 70

Ethiopia 62

Senegal 55

Somalia 55

India 54

Madagascar 36

Bottom 10

Central African Republic 4

State of Palestine 4

Kazakhstan 3

Namibia 3

Eritrea 2

Republic of Moldova 2

Ukraine 2

Angola 1

Guinea-Bissau 1

Mongolia 1

There are around 20 developing countries with four or fewer reported markets (excluding those with national average prices). Conversely, 36 countries report prices for more than 10 markets. The high market coverage is mainly due to WFP’s local VAM units reporting from the available domestic data for a large number of markets and commodities. The number of markets reported is also high in countries where FEWS NET is present.

Note: Data series not updated in the six months preceding the study have been excluded.

Table 5. Markets covered - Top 10 and bottom 10 developing countries



5.5 Commodities

Looking at the current data series, cereal grains are the main commodities reported in the price datasets, with rice15 and maize the top two groups. Beans and pulses are prominant in third place, surprisingly followed by animal products, animals, fish etc. Wheat and wheat products are included but appear much less frequently than rice and maize price series. Vegetables and fruits are reported in large numbers but they are concentrated in just a few countries, e.g. in Rwanda, India, Kyrgyzstan and Yemen. There is a lack of systematic coverage of non-cereal staple commodities in many countries. This can make it difficult to obtain a comprehensive picture of consumption changes when the prices of non-cereal commodities change dramatically.

15. The price series grouped under ‘rice’ include 78 different types, for example, local rice, imported rice, various percentages of broken rice, glutinous rice, basmatirice,specificvarietiesandqualities(lowgrade,firstgrade,secondgrade,etc.),differentorigins(Japonica,Indica,etc.),longgrain,mediumgrainorwellmilled.Thisshowsthedifficultiesinvolvedinunifyinghowcommoditiesareclassified.

Figure 3. Number of price series per commodity (aggregated) in combined three datasets

Note: Chart includes the overlap of some series between different datasets.



5.6 Level of price

Almost 90 percent of prices reported in the datasets are at retail/consumer level; around 10 percent are wholesale prices. Almost 60 price series of export or international prices are also reported. The international or relevant regional market prices are important for countries that are import-dependent. Therefore, there needs to be a standard method of selecting the big regional players that influence regional export and import markets.

5.7 Starting date

WFP FAO FEWS NET1990–1994 0.8 4.4 0.01995–1999 0.1 4.2 5.92000–2004 3.0 27.8 35.02005–2009 18.3 60.8 38.32010–2014 77.7 2.9 20.7Started 10 or more years ago 4.0 36.4 40.9

Figure 4. Distribution of different types of prices (% share)

0.54

89.1

0.0610.2

Export

Producer

Retail

Wage

Wholesale

Table 6. Comparison of price series starting dates (% of dataset)



The starting date of the price series indicates how far back in time the series goes. Of the three global datasets, FAO’s has the largest proportion of series that go as far back as January 1990. As shown in Table 6, most of FAO’s and FEWS NET’s price series go back to the period 2005–2009, while WFP’s date from 2010–2014.

Examining each of the 16,000 price series for their completeness and missing values is a very time-consuming task. Thus, given the time and resource limitations, this study has not been able to analyse the time length of the series. Long price series are of particular importance to research.

5.8 End date

Data needs to be timely to be useful. In order to assess timeliness, price series that had not been updated for the previous six months were removed. Generally, price datasets are dynamic: some series drop out when data becomes unavailable and new ones are added. At the time of this study, almost a third of the price series had not been updated. To gauge timeliness, the number of series that had been updated within the previous month was divided by the number of current series. The same calculation was performed for series updated within the previous two months (see Table 7).

WFP

(As of 24 June 2014)

FAO GIEWS (As of 24 July

2014)

FEWS NET (As of 24 Oct.

2014)

Total number of monthly price series 13075 1221 2534

Discontinued series? (no data for past 6 months) 5221 291

Effective current series (Total minus discontinued) 7854 930 2534

Updated data in previous 2 months 5515 840 1977

Updated data in previous month 4006 693 1854

Percent data series updated in previous 2 months 70% 90% 78%

Percent data series updated in previous month 51% 75% 73%

Table 7. How up-to-date are the global price datasets?

Note: There are some discrepancies in the number of price series of FEWS NET data in this table compared to the data used for other elements in this report. FEWS NET price data management is in a transition period, moving from manual Excel-based entry to a direct online entry. Therefore the ‘ending dates’ for their series indicated in the metadata received at the beginning of this study were not accurate and complete. The FEWS NET data in this table is based on new information, including data entered by both methods, received on 24 October 2014.



The results show that the FAO GIEWS dataset is the most updated at 75 percent. When this measure is extended back to two previous months, the results improve significantly ranging from 70 to 90 percent. From discussions with the staff involved, keeping the datasets up to date represents considerable and constant work. However, the value of the price information for early warning purposes is in making the most updated data available to decision-makers.

5.9 Data sources

In the vast majority of the cases, primary data is collected by national government agencies – typically statistical departments, line government ministries or food security information units. Almost all data comes from official sources, except when data is cross sourced from the other two datasets.16 Over time, sources have changed in several countries. In such cases, only the latest source is shown. For 14 countries, WFP is listed as a sole source of the data, indicating the data collection is fully supported or organized by WFP (see Table 8). WFP collects primary data in Syria and in some other countries, but it is not clear from the metadata records which countries these are. Further enquiry is required to determine the exact role played by country offices and the ownership of the data. FEWS NET is involved in primary data collection in Haiti (since 2005), Sudan (2012) and Nigeria (2003). To improve transparency, a practice of clearly identifying the source of each price series and providing a hyperlink if the data is available on the web should be adopted uniformly across the datasets.

16 . For a full list of sources by country and by database, see Annex 1.



Table 8. Countries with WFP, FEWS NET and partners as the source of data

Note: Most of the other countries in the datasets have an official source of data.

WFP as source of data

Afghanistan WFP

Armenia WFP

Congo WFP

Georgia WFP

Kyrgyzstan WFP

Liberia WFP

Sierra Leone WFP

Somalia WFP

South Sudan WFP

Sudan WFP

Syrian Arab Republic Primary Data WFP CO Food aid monitors

Tajikistan WFP

Yemen WFP

Zimbabwe WFP

WFP and partners and other sources

Burundi FAO/DPAE/WFP/FSMS

Cambodia WFP;AgMarketingOffice,Min.ofAgriculture,Forestry&Fisheries

Cameroon DRADER Nord/WFP; DDADER Extrême-Nord/WFP

Central African Republic WFP; ACF/ACTED/Solidarite/WFP

Chad WFP -SO; SIM; SIM &FEWS NET

Cote d'Ivoire WFP;OfficedelaCommercialisationdesproduitsVivriers(OCPV)

Democratic Republic of the Congo FAO/PAM/INS

Guinea WFP; Govt.

Guinea-Bissau WFP; WFP - GW; GNB WFP CO

Myanmar WFP and Cooperating Partners

FEWS NET and partners listed as source of data

Chad FEWS NET, Chad

Haiti CNSA/FEWSNET, Haiti

Kenya NDMA; MOA; FEWS

Mauritania FEWS NET, Mauritania

Nigeria FEWS; SIMA

Somalia FSNAU/FEWSNET, Somalia

Zimbabwe WFP; FEWS NET

6. Overlaps and gaps24


6.1 Overlaps

In the three datasets, there are 76 countries with potential overlap, or a total of 14,734 current price series (i.e. those updated in last six months). Given that this is too large a number of series to examine in detail, the study has used a random sample of 15 countries – about 20 percent of the total – to carry out a detailed assessment of overlaps and data uniqueness. The sample contains 10 countries that are represented in all three datasets, and five others present in any two datasets. It is more appropriate to use the sample of 15 countries (rather than just the 10 countries that appear in all three datasets) because that way, the overlap between any two of the datasets is also reflected.

Total Number of Series Number of Overlapped Series Percent of Overlapped Series (%)

Selected Countries 1/

WFP FAOFEWS-

NetTotal series

Overlap in all 3

Overlap between WFP &

FAO

Overlap between WFP & FEWS

Overlap between

FAO & FEWS

Overlap in all 3

Overlap between

WFP&FAO

Overlap between

WFP&FEWS

Overlap between

FAO&FEWS

For

WFPFor FAO

For WFP

For FEWS

For FAO

For FEWS

1 Afghanistan 16 12 30 58 4 4 16 8 7 25 33 100 53 67 27

2 Armenia 56 5 61 0 0 0

3 Bolivia 45 20 65 0 0 0

4 Ethiopia 222 20 105 347 13 14 89 18 4 6 70 40 85 90 17

5 Kenya 24 10 48 82 8 8 23 8 10 33 80 96 48 80 17

6 Lao PDR 364 10 374 2 1 20

7 Madagascar 226 2 38 266 0 0 0 0 0 0 0 0 0 0 0

8 Malawi 301 10 26 337 6 9 17 6 2 3 90 6 65 60 23

9 Mexico 16 7 23 0 0 0

10 Nigeria 20 3 38 61 0 0 3 3 0 0 0 15 8 100 8

11 Panama 2 11 4 17 0 0 0 1 0 0 0 0 0 9 25

12 South Africa 3 3 6 0 0 0

13 Sudan 23 18 30 71 0 0 0 0 0 0 0 0 0 0 0

14 Zambia 425 3 20 448 0 0 18 0 0 0 0 4 90 0 0

15 Zimbabwe 43 1 25 69 0 0 0 1 0 0 0 0 0 100 4

Total of above 1767 144 374 2285 31 37 166 45 1 2 26 9 44 31 12

6. Overlaps and Gaps

Table 9. Number of price series and overlapped series in different datasets

6. Overlaps and gaps 25


Any two series are considered overlapping (or common) only if they refer to the same commodity, the same market and the same price level (retail or wholesale). For example, if the source of the data is the same, maize, corn, maize grain or maize (white) are considered to be the same commodity. Whereas maize (mixed) is treated as different from maize (white), or maize (yellow). In the next phase of this study, the actual data would be examined to determine if the price values are in fact the same for the overlapping series and to explore the reason if they are not.

Overlap calculation

The overlap between any two sets is defined as the number of price series that are the same in both sets, thus,

% Overlap for FAO with WFP = No. of common series in the sample / No. of FAO series in the sample= 37 / 144 = 0.26 = 26%

% Overlap for WFP with FAO = No. of common series in the sample / No. of WFP series in the sample= 37 / 1767 = 0.02 = 2%

If we consider the number of price series overlapping in the context of the total price series, it is a very small percentage (about 1 percent in all three datasets). However, in terms of the absolute number of series and their percentage in relation to their respective total series, the overlap between any two sets is fairly high, as shown in the bottom row of Table 9. Overall, 44 percent of FEWS NET series overlap with the WFP dataset, meaning that 44 percent of FEWS NET series are the same as those in WFP dataset. Roughly a quarter of FAO’s price series appear in WFP’s dataset, and 30 percent are in the FEWS NET dataset. In relative terms, WFP has the lowest overlap because it has such a large number of series.

One reason for overlap is when the original source of the data is the same. The large amount of overlap may provide opportunities for collaboration and data sharing by agreement, especially if additional resources are currently devoted to compiling the data independently.

6. Overlaps and gaps26


6.2 Gaps

AFRICA1 Algeria2 Botswana3 Central African Republic* (last data Dec 13)4 Eritrea* (last data Feb 09)5 Liberia* (last data Dec 11)6 Libya7 Mauritius8 Morocco9 Namibia* (last data Dec. 13)

10 Sierra Leone* (last data May 13)11 Timor-Leste* (last data Oct 13)

EUROPE & CENTRAL ASIA12 Albania13 Bosnia and Herzegovina14 Bulgaria15 Kosovo16 Romania17 Serbia18 Turkmenistan19 Uzbekistan

LATIN AMERICA & CARIBBEAN20 Cuba21 Jamaica22 Paraguay23 Venezuela, RB

Of the 104 countries in the three datasets, at the time of the analysis (July-August 2014), six countries had not been updated since December 2013 or earlier: Central African Republic, Eritrea, Liberia, Namibia, Sierra Leone and Timor-Leste. Liberia, Namibia and Sierra Leone have been updated since the analysis. In total, there are 24 developing countries with no food price information. Another gap is the lack of uniformity in terms of commodity coverage. Furthermore, most country price collections do not have prices for commodities that represent the nutritional wellbeing of a population, such as vegetables, fruit or animal/fish products. Most of the gaps are due to a lack of available data. However, a strategy may be needed to overcome this, at least for priority food security countries.

Table 10. Developing countries with no price information in the global datasets

Note: As of July-August 2014 when the Metadata files were received. Since then some countries may have been updated. Also, five new countries (Liberia, Morocco, Paraguay, Sierra Leone and Swaziland) have been added to FAO/GIEWS database.

7. Database Management 27


7. Database Management

7.1 The process

Database management comprises a back-end and a front-end. Figure 5 is a flow chart showing a range of steps beginning with primary data collection through to the final display used by analysts, policymakers and the public. The bottom of the chart identifies areas for greater cooperation among the current database providers at different stages of the process.

Figure 5. Flow chart of steps involved in price database system

Back-end

Price database system

Front-end

PrimaryData

Collection

DataGathering/Collation

DataStorage/Maintain

DataDisplay/Analysis

DatabaseAccess/

Download

DataInput/Upload

Cooperation in compilation/uploadinto a common central base, use of

standard template & protocol,harmonized country & market names,

measurements, commodityclassification, ....

Cooperation as technical level. Neednot be a common database, easy

access to CPI, USD exchange rates andother harmonized data through FAOand WFP portals and to individual

price analysis tools

Primarly by government but also by contacted agent/NGO; WFP, FEWS NET and partners.

Decentralizedprocess byWFP and FEWS NET from field, FAO mostly centralized.

WFP field officers usestandardtemplates,upload intolocal server.FAO Excelfile at HQto upload.

Each agencywith itsserver partof network,each usingdifferenttechnicalplatform.FEWS NETdevelopingnew system.

Openaccess toFAO andWFP price data;Restrictedaccess toFEWS NETdata.Downloadconditionsdiffer.

GIEWS pricetool, data,graphics,analysis;WFP VAM price toolfor datadownload,graphics;FEWS NETfor internaluse.

7. Database Management28


7.2 Data format and database platform to improve interoperability

Relevant features of each of the three systems are outlined below. Market locations in all three datasets are geo-referenced using FAO Gaul codes.

FAO GIEWS system

The technical process from initial data format to the presentation of the processed data, graphics and analysis involves the following:

• 100percentofuploadingisdoneatHQ.Validationdonebydatamangerandsupervisor.• RawdatamaintainedinExcelformatandauto-fedintoadatabaseservermanagedwithMySQL5.6.• Onclientside,GUIAdobe(nowApache)Flex4.0isusedasaplatformtopresentthedata.• Metadata,actualdata,pricecharts,realpriceconversion,USDconversionofmultipleseriesacross

the dataset (up to 9 series at a time) and download into Excel or CSV format is possible in the GIEWS Food Price and Data Analysis Tool.

• Fast internetaccess is requiredthroughouttheanalysis.Access tothetoolanddata isslow incountries with low bandwidth/poor internet speed.

To illustrate the technical process followed in database management, a flow diagram of FAO GIEWS is provided in Annex 2.

WFP system

• Almostalluploadingisdoneatcountrylevelusingasettemplate.Officersworkofflinetoinputdata in Excel files. The templates are filled and uploaded on the central server at HQ, which is managed at HQ level.

• FirstqualitycontrolisbyaCountryOfficesupervisor,followedbyvalidationatHQ.• WFP uses the Microsoft SQL database platform, WFP corporate standard, for back-end data

management including data storage. Microsoft Access is used for analysis and to perform queries. • TheendusercandownloaddataandpricechartsinExcel.Cross-countrypriceseriescomparisons

by download are possible but are less user friendly. WFP plan to improve graphics and optimize user-friendliness.

• The USD exchange rates (informal rates where appropriate) are available, so it is possible toconvert local price series to USD with added calculations.

• WFP uses ASP.NET as a platform to present the data. They are discouraged fromusing Flashbecause of bandwidth and accessibility problems in the field.

FEWS NET system

Data management is in transition from the Excel-based large dataset to a new data management system being developed by a commercial contractor (Kimetrica). The new system will allow the following:

• Easyremotebulkdatauploads–eitherautomatedspreadsheetuploadsordirectwebentry.• Dataoncesetupcanstayontheanalyst’sdesktopintheirpersonalworkspaces.Automaticor

quick updates are refreshed to add more recent data.

7. Database Management 29


• Advanced graphics and pivot tables, charts, and analytical capabilities with URL links inspreadsheets. The system will use DRUPAL, an open source content management platform for graphics and report creation.

• Focusonofflinecapabilitiestominimizeinternetaccess.Also,fewergraphicstokeepthesystemlight for download.

• Accesstocross-countrydataforeveryofficerinfieldoffices.• FEWS NET are interested in transferring this system/technology to country level for data

management.

7.3 Quality control methods used by each agency

For all three datasets, quality control is done with a combination of manual checking and certain automated indicators. Error identification is based on a calculation of a particular indicator, such as a ratio of the current price to last month’s price. The data collected/fed from the field is usually checked and verified by country/regional supervisors. Price series in all three sets are also checked centrally by the data managers and officers monitoring food security and market spikes for early warning purposes. For WFP, plans are under discussion to a) improve error detection through more efficient automation processes; and b) limit the likelihood of input oversights.

7.4 Human resources used by each agency

Approximate human resources used to collect and maintain the current datasets are listed below by agency.

1. FAO – 4 full-time price data project posts and IT consultants, 1 full-time clerk for data entry, and partial time for supervisory and technical oversight by 3 GIEWS officers.

2. WFP - Data input by country officers (focal points) - a few hours a day to collate, copy/paste and upload data. Back stopping from HQ, mostly by VAM supervisor, with a full-time information management officer, and partial input from 6 team members of the VAM/Markets team and from 2 regional market officers (Dakar and Johannesburg).

3. FEWS NET - At HQ, 50 percent of a market data manager post; part-time input by a market trade analyst; and part time of a supervisor (markets and trade advisor). Regional officer verifies data - a day or two to check review and preliminary analysis.

Initial field offices used Excel under the old system; they are now shifting to direct online submission. Field officers spend just a couple of hours a month or a few minutes a day on this task.Under the new data management system, arrangements are expected to change with the possible involvement of a private sector company.

Primary data collection requirements are different (10 to 16 enumerators, coordinators, etc.).

8. Opportunities to Improve the Inter-Operability of Different Datasets30


8.1 Strengthening back-end cooperation

Of the 104 countries covered, FAO, WFP and FEWS NET report data for the same 36 countries. FAO and WFP cover additional 24 countries in common. Furthermore, of these 60 countries, there is a significant overlap in the specific series covered. Judging from the differences in the level and depth of price data coverage, there is an opportunity to explore sharing data collection, possibly by dividing countries and responsibilities based on relative strengths and efficiency. This would require agreement on the selection of markets and commodities in each country. The country-level data would then be made available to all agencies. This cooperation would allow each dataset to expand to cover new priority food security countries where all agencies have difficulty in accessing decent market information. Better back-end cooperation can help avoid duplication of effort, increase coverage, reduce costs and improve inter-operability.

8.2 Cooperation in sharing CPI and exchange rates data

Besides the raw data on commodity prices, for a proper evaluation of food price changes over time and across countries, it is necessary to convert the downloadable series into real or USD prices. This requires continually updated datasets to have auxiliary data on the CPI (or other deflator), international benchmark or major exporter prices, fuel/energy prices and USD exchange rates. Currently, exchange rate data is collected by all three datasets, while CPI data is collected by FAO and to some extent by FEWS NET. There is an opportunity to collaborate on maintaining one set of this auxiliary data accessible to all three datasets. This would increase the overall efficiency of resources used and make the datasets even more useful.

8.3 Making datasets inter-operable with a common structure

To improve the ability of the three datasets to share and access data, there is a need to follow a standard structure, with common definitions and nomenclature. Most of these obstacles are relatively easy to overcome. WFP uses market names in a given country using the Global Naming Standard. A standardized format for naming and coding data items also needs to be followed. This study has identified some of the inconsistencies in the current datasets (see examples below). However, it would be useful to comb through the entire datasets, identify inconsistencies and replace them with a common nomenclature.

Country namesCape Verde/ Cabo VerdeCote d’Ivoire/ Côte d’IvoireState of Palestine/Occupied Palestinian TerritoryUnited Republic of Tanzania/Tanzania, United Republic ofUnited States/USA

8. Opportunities to Improve the Inter-Operability of Different Datasets

8. Opportunities to Improve the Inter-Operability of Different Datasets 31


Market namesVarious spellings are used, as well as local names in some datasets and English names in others. To name a few:

Afghanistan markets: Fayzabad/Faizabad, Hirat/Herat, Maymana/Maimana, Mazar/ Mazar e Serif

El Salvador markets: San Fco. Gotera/San Francisco

Ethiopia markets: Baher Dar/Bahir Dar/Bahirdar, Debre Marcos/Debra Markos, Desse/Dessie, Dire Dawa/Diresawa

Commodity namesBeans (Dry)/Dry beansFuel (Diesel)/Diesel/fuel (Gasoline/Petrol)Local names atta (wheat flour), lentils (masur)Groundnut/groundnuts (shelled)/groundnuts (In Shell)Maize/corn/maize dry/maize grain,Maize white/white maize/maize (white)/Maize (White)Wheat/wheat grainWheat flour, wheat (flour)Low grade/Low qualityManioc (cassava)/Manioc (cassava, local)/Cassava

In addition to commodity names, commodity codes could be useful for data exchange and presentation. One possibility could be to use the UN’s Central Product Classification (CPC) codes and agree on modifications to describe commodities not covered by the basic CPC codes. Work begun by FEWS NET could be a starting point in determining the modifications to the UN CPC codes.

8.4 Technical aspects of database management

Some of the IT experts interviewed during the consultation process for this study (for example, from Kimetrica and WFP) mentioned that it does not matter which platform/format is used for data input and data output. Rather, the databases should facilitate sharing through application programming interface (API) linkages, allowing applications and implementation to vary without compromising each other. This means the datasets do not have to look the same; they just need to be able to link to each other easily. API comes in the form of a library that includes specifications for routines, data structures, object classes, and the variables and makes/allows queries to extract. This approach makes it possible to take chunks of data from one database and plug them into another. Such technical improvements may be possible for these three datasets. 17

17. Note that the technical aspects of data sharing and improving linkages are beyond the scope of the current terms of reference of this study. These issues would require IT experts to create and implement the technical design of the datasets.

9. Recommendations for improved integration and harmonization 32


Having examined the detailed characteristics, overlaps, complementarities and gaps of the three global food price datasets, this study has identified several areas that could help

improve the efficiency, usefulness and timeliness of price information for users. Presented here as recommendations, the issues are highlighted for further deliberation by the FSIN and the individual dataset providers.

1. Currently, each agency spends a lot of effort and resources to collect, collate and upload data, in WFP’s and FEWS NET’s case from the field, and in FAO’s case at central level. It is recommended that full cooperation be sought, especially in the back-end stage of the database process, to promote the shared collection, collation and upload of price data. Price series that overlap could be used as a starting point to come to an agreement on the division of responsibilities.

2. In order to develop further harmonization, it is recommended that one agency maintain a common auxiliary dataset on international food and fuel prices, CPI and currency exchange rates, promoting data sharing among all.

3. The inter-operability of the three datasets should be improved by using a common format. When the metadata of all the datasets is combined, it is evident that even though the data is the same, it has different labels and definition characteristics and consequently the computer cannot identify them as the same data. It takes hours of manual processing to make them uniform. The global price datasets should use a standard structure for metadata, including the names of the countries, markets and commodities, as well as the level of market price, unit of measurement and currency used. The Global Naming Standards used by WFP could be a starting point.

4. The databases should facilitate sharing definitions and data structure elements through API linkages, allowing applications and implementation to vary without compromising each other.

5. Appropriately modified CPC codes should be used to classify commodities. In large datasets, it is more efficient to convert most data elements to numeric codes. The UN has developed CPC Version 2, completed in 2008,18 which could serve as a basis, with the modifications needed to reflect the commodity details found in these price datasets. FEWS NET uses a set of modified CPC codes in its crosstab data tabulation in order to accommodate variations in the standard commodity listing. It is therefore recommended that the harmonization of commodity classification based on modified CPC codes be explored to determine its costs and benefits.

18 . Available at https://unstats.un.org/unsd/cr/registry/docs/CPCv2_structure.pdf

9. Recommendations for Improved Integration and Harmonization

9. Recommendations for improved integration and harmonization 33


6. There is a need to establish principles describing an ideal (and minimum) set of price information needed for food security monitoring and policy decision-making. This would cover the types and number of commodities, the number and locations of markets, etc. in each country. Beyond food security monitoring and early warning, it is also necessary to consider the other purposes of each agency, such as programming needs and the long-term sustainability of the database. Guidance could also helpful regarding the relationship between the national dataset (maintained by countries themselves) and global price dataset(s). Should the entire national level data be replicated in the global dataset? What part of the national data is critical to the global setting? To help resolve these issues, it is recommended that FSIN set up a technical working group to provide specific guiding principles on the structure and the sustainability of maintaining useful and timely information for early warnings, programming needs and policy analysis.

7. In the current list of the 104 countries represented in the three datasets, six are no longer

updated, primarily because the usual sources of data do not provide the price data. In addition, there are at least 20 more developing countries not represented or omitted from the combined dataset. As a first step, it is necessary to evaluate the need for price information in these countries. It is therefore recommended that an urgent effort be made to assess the price information needs and gaps, as well as to examine ways to fill these gaps so that the global food price information is as complete as possible.

8. It is clear that several developing countries carry out inadequate data collection and/or dissemination. It is therefore recommended that FSIN carry out the next phases of this project by closely examining the status of national food price data collection in high-priority countries, identifying areas of weakness and opportunities, and proposing solutions including a national capacity-building strategy to improve their information base.

Annexes 34

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Annexes 36

Annex 2. GIEWS Food Price Data and Analysis Tool – Data Format and Platform

Source: FAO GIEWS.



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