The World Bank The 50x2030 Initiative to Close the Agriculture Data Gap | Data-Smart Agriculture Project Information Document/ Identification/Concept Stage (PID) Public Disclosure Copy Concept Stage | Date Prepared/Updated: 17-Oct-2019 | Report No: PIDC203267 Oct 17, 2019 Page 1 of 8 The World Bank The 50x2030 Initiative to Close the Agriculture Data Gap | Data-Smart Agriculture BASIC INFORMATION A. Basic Project Data Environmental and Project ID Parent Project ID (if any) Social Risk Project Name Classification Low The 50x2030 Initiative to P172299 Close the Agriculture Data Gap | Data-Smart Agriculture Region Country Date PID Prepared Estimated Date of Approval OTHER World 17-Oct-2019 Financing Instrument Borrower(s) Implementing Agency Public Disclosure Copy Food and Agriculture Food and Agriculture Investment Project Organization of the United Organization of the Financing Nations United Nations PROJECT FINANCING DATA (US$, Millions) SUMMARY -NewFin1 Total Project Cost 2.60 Total Financing 2.60 Financing Gap 0.00 DETAILS -NewFinEnh1 Non-World Bank Group Financing Trust Funds 2.60 Miscellaneous 1 2.60 B. Introduction and Context Country Context 1. Each year, hundreds of billions of dollars are invested and critical decisions are made in development policies, often without good evidence to inform those investments and decisions. The scarcity of high- quality, timely survey data is a key constraint for low and lower middle-income countries (L/LMICs) to effectively plan, finance, and implement development strategies as they strive to realize their full Oct 17, 2019 Page 2 of 8 The World Bank The 50x2030 Initiative to Close the Agriculture Data Gap | Data-Smart Agriculture potential. The lack of these data leads to sub-optimal decisions, causing losses in productivity and income and, ultimately, more hunger and poverty. 2. Sound decisions are based on good information. That reality is especially significant for low and middle-income countries, where programs and policy decisions fundamentally affect the lives of their citizens. Yet, each year nearly $239B is invested in agriculture in L/LMICs and critical policy decisions are made often without the benefit of recent, comparable, or accurate agricultural statistics. 3. Timely and reliable country data on agricultural productivity and income remain the exception rather than the rule. Countries need information about their subpopulations to appropriately target interventions and allocate resources for policy reform, but the countries with the largest populations of poor, hungry, and marginalized, including women, children, and indigenous peoples, severely lack the data needed to understand them. Some L/LMIC governments have already begun to address this gap through national surveys. Yet, current efforts are insufficient. 4. Sustainable Development Goal 2 (SDG2) provides a rallying cry to examine and resolve the data Public Disclosure Copy problem for agriculture. Without good data to inform decisions, we will not achieve SDG2 and its objectives to end hunger, achieve food security and improved nutrition, and promote sustainable agriculture. Nor will we have a way to track, measure, and build off the progress we do make, to help poor and hungry populations. Notably, three SDG2 indicators – those on labor productivity (2.3.1), small-holder income (2.3.2), and land area under sustainable production (2.4.1) – measure vital issues we must address in agriculture, but most countries cannot calculate them or other key agricultural indicators with existing data. 5. Sustainably closing the agricultural data gap is a critical precondition for the evidence-based decision- making and investments needed to foster all agricultural development. Though the constraints impeding achievement of SDG2 are numerous, closing the agricultural data gap is a critical problem that can be isolated and resolved. The data gaps in agriculture are widespread, and the dearth of data affects over 800 million, or 78% of the world’s poorest. Sectoral and Institutional Context 1. The lack of survey availability and of good, recent data is a manifestation of a deeper problem: many countries do not have well-functioning data systems to generate and use the data needed to make improved programmatic, investment, and policy decisions. Many L/LMICs have taken the first steps but many of those same countries have asked for help in strengthening key capacities and knowledge to form a comprehensive, sustainable system for data production and use. They need support to experience first-hand how good data can improve decision-making, creating public, private, and social demand to justify sustained investment by that government. 2. There are existing and tested solutions that are ready for scale-up, as they have proven to be: (i) effective in collecting agriculture primary data where there was previously little, (ii) strong in building local capacity through “learning by doing,” and (iii) popular with host countries, multinational institutions, and bilateral donors, especially as they put the partner country in the driver’s seat to design and implement the survey, receiving guidance from the technical partner. Oct 17, 2019 Page 3 of 8 The World Bank The 50x2030 Initiative to Close the Agriculture Data Gap | Data-Smart Agriculture 3. Over the past decade, donors, multinational institutions, and host countries have together developed and implemented several approaches to help fill the agricultural data gap. The Living Standards Measurement Study (LSMS) is a household survey program housed within the Production and Methods Unit of the World Bank's Development Data Group that provides technical assistance to national statistical offices (NSOs) in the design and implementation of multi-topic household surveys. For the past four decades the LSMS Program has worked with dozens of statistics offices around the world generating high-quality data, incorporating innovative technologies and improved survey methodologies, and building technical capacity. The LSMS team has also provided technical support across the World Bank in the design and implementation of household surveys and in the measurement and monitoring of poverty. In addition, the LSMS-Integrated Surveys on Agriculture (LSMS-ISA) initiative, established in 2008 and modeled on the integrated household survey design of the LSMS, was aimed at supporting governments in Sub-Saharan African countries to generate household panel data with a strong focus on rural livelihoods, including detailed information on Public Disclosure Copy agricultural and non-farm income activities. Likewise, the Agricultural Integrated Survey (AGRISurvey) of the Food and Agriculture Organization’s (FAO) of the United Nations has proven valuable to build local capacity and to generate statistically valid and timely data. Relationship to CPF While the grant is global in nature, activities will be target country data and capacity needs based on the country’s initial conditions, needs, wishes, capacity, and potential for technical and financial take-over by the respective governments. These should be aligned with the CPF. C. Project Development Objective(s) Proposed Development Objective(s) The Project Development Objective (PDO) is to improve the availability, quality, use and usability of integrated household and agricultural surveys data in low and lower middle-income countries. Key Results The project will contribute to improve evidence-based decision making at national level with the aim of ending hunger, increasing food security, improving nutrition and promoting sustainable agriculture and rural development. D. Preliminary Description Activities/Components The implementation of the 50x2030 Initiative will be carried out or coordinated under three Implementation Components: (i) Data Production; (ii) Methods and Tools Development; and (iii) Data Use. This Oct 17, 2019 Page 4 of 8 The World Bank The 50x2030 Initiative to Close the Agriculture Data Gap | Data-Smart Agriculture implementation model will ensure the program builds upon the mandate as well as strengths and capacities of each Implementing Partner in supporting countries across the elements of the data cycle. 1. Data Production Component Under the 50x2030 Initiative, countries will receive support to conduct a survey program leading to the adoption of either an Agricultural Survey Program or an Integrated Agricultural and Rural Survey Program. The approach the country will adopt will be determined through consultations during the country onboarding process. 2. Methods and Tools Development Component This component will include activities that produce new, better, and more cost-effective tools and methodologies for data collection and analysis. Based on priorities among the 50x2030 partners, the work Public Disclosure Copy under this component will fall under three main pillars: Integration of survey approaches; Integration of technology, updating of methodologies; Integration with other data sources. 3. Data Use Component This component aims to promote the use of data and evidence generated under the Data Production component to inform decisions that will spur the agricultural growth needed to achieve development objectives, including SDG2. Initiative activities are designed to ensure increased and improved use of survey data to inform decision making, by achieving 1) stronger capacity to analyze, interpret, and present data; 2) stronger capacity of decision-makers to interpret and apply data; and 3) improved data sharing and communication practices in partner governments. Within this recipient-executed activity the project will focus on component 1 and 3. Component 1 – Data Production (US$2.3 million) The Data Production component aims to support countries to produce and disseminate more, better, and more timely agricultural data as they build sustainable agricultural statistical systems. Through this component, partner countries will receive technical assistance and financial support to collect data and establish a survey program that addresses the countries’ data needs and builds capacities across all steps of the data production cycle. For implementation of this component, the Bank will partner with FAO that is a leading specialized agency in the area of agriculture and rural statistics through a recipient-executed grant to FAO. FAO will be responsible for the provision of technical assistance in data production. Support will be tailored based on each country’s data and capacity development needs, which are usually already part of their national strategic plans (NSDS or SPARS), its data user demands, its current capacities and existing survey program, and its potential capacity for financial and technical take-over. Oct 17, 2019 Page 5 of 8 The World Bank The 50x2030 Initiative to Close the Agriculture Data Gap | Data-Smart Agriculture Technical assistance activities under this component will be primarily the responsibility of the Economic and Social Statistics Division (ESS) of FAO, FAO being the custodian for SDG2 indicators and having the global mandate to support the production and reporting of these data, as well as . As such, they are in a unique position to lead the engagement with countries to ensure the regular production and reporting of agricultural statistics at the national, regional and global level. FAO is also regarded by countries as the leading agency on agricultural data, with a long tradition of supporting countries’ agricultural data systems. Component 3- Data Use (US$275,000): The primary objective of the Data Use component is to ensure increased and improved use of agricultural survey data to inform decision making by key actors, particularly in partner countries but also at the global level. Focusing explicitly on data use is an attempt to ensure that decision makers in countries have the capacity and motivation to access data to make informed decisions that facilitate progress towards achieving Public Disclosure Copy SDG 2.3 and 2.4 and that the data produced and analyzed by National Statistical Offices, line ministries and researchers is aligned with the needs of decision makers. The implementation of the Data Use component includes sets of activities at the country, regional and global level. Activities include: (1) Assessment of data ecosystems; (2) Strengthening of the data ecosystems; (3) Promotion of evidence-informed decision making; (4) Data use monitoring; (5) Global and regional-level implementation. While there is and will be overlap between the country and regional/global level, the first four sets of activities focus primarily on the country level and are designed to achieve the set outputs and outcomes for each country where activities are envisioned; while these four sets of actions are not necessarily chronologically ordered, actions linked to each area will need to be appropriately sequenced. Environmental and Social Standards Relevance E. Relevant Standards ESS Standards Relevance Assessment and Management of Environmental and Social ESS 1 Relevant Risks and Impacts ESS 10 Stakeholder Engagement and Information Disclosure Relevant ESS 2 Labor and Working Conditions Relevant Resource Efficiency and Pollution Prevention and ESS 3 Not Currently Relevant Management ESS 4 Community Health and Safety Not Currently Relevant Land Acquisition, Restrictions on Land Use and Involuntary ESS 5 Not Currently Relevant Resettlement Biodiversity Conservation and Sustainable Management of ESS 6 Not Currently Relevant Living Natural Resources Oct 17, 2019 Page 6 of 8 The World Bank The 50x2030 Initiative to Close the Agriculture Data Gap | Data-Smart Agriculture Indigenous Peoples/Sub-Saharan African Historically ESS 7 Not Currently Relevant Underserved Traditional Local Communities ESS 8 Cultural Heritage Not Currently Relevant ESS 9 Financial Intermediaries Not Currently Relevant Legal Operational Policies Safeguard Policies Triggered Explanation (Optional) Projects on International Waterways OP No 7.50 Projects in Disputed Areas OP 7.60 No Summary of Screening of Environmental and Social Risks and Impacts The Environmental and Social Risks Classification of the project is assessed to be low given the scope of Public Disclosure Copy project activities. No ES risks are expected to manifest during project preparation or subsequently, during implementation. Consistent with the requirements of ESS1, no further environmental and social assessment (ESA) has been determined necessary following screening and initial scoping, as the project is likely to have minimal or no adverse environmental or social risks and impacts. No ESA instruments will be prepared and an Appraisal ESRS will not be required. CONTACT POINT World Bank Contact : Anushka Thewarapperuma Title : Senior Operations Officer Telephone No : 473-1217 Email : Contact : Alberto Zezza Title : Senior Economist Telephone No : 5795+231 / 3 Email : Borrower/Client/Recipient Borrower : Food and Agriculture Organization of the United Nations Contact : Christophe Duhamel Title : Global Coordinator, FAO Telephone No : 390657054443 Email : christophe.duhamel@fao.org Implementing Agencies Implementing Food and Agriculture Organization of the United Nations Agency : Contact : Ana Pizzaro Title : Programme Officer Telephone No : 390657052911 Email : ana.pizarro@fao.org Oct 17, 2019 Page 7 of 8 The World Bank The 50x2030 Initiative to Close the Agriculture Data Gap | Data-Smart Agriculture FOR MORE INFORMATION CONTACT The World Bank 1818 H Street, NW Washington, D.C. 20433 Telephone: (202) 473-1000 Web: http://www.worldbank.org/projects Public Disclosure Copy Oct 17, 2019 Page 8 of 8