Datasets

× The Nexus Project is a collaboration between IFPRI and its partners, including national statistical agencies and research institutions. Our aim is to improve the quality of social accounting matrices (SAMs) used for computable general equilibrium (CGE) modeling. The Nexus Project develops toolkits and establishes common data standards, procedures, and classification systems for constructing and updating national SAMs. The 2021 Rwanda SAM follows the Standard Nexus Structure. The open access version of the Rwanda SAM separates domestic production into 42 activities. Factors are disaggregated into labor, agricultural land, and capital. Labor is further disaggregated across three education categories. Representative households are disaggregated by rural and urban areas and by per capita expenditure quintile. The remaining accounts include enterprises, government, taxes, savings-and-investment, and the rest of the word.

× An impact assessment (IA) study was conducted in Rwanda in 2015 to determine the adoption and diffusion rates of high iron beans (HIB) varieties after eight seasons of active dissemination; understand HIB adoption and diffusion patterns across varieties and over time (the percentage of farmers currently planting, the percentage rate of addition, the percentage rate of dropout, the percentage of bean area currently under HIB, and so forth); and assess the socioeconomic and nutrition impacts resulting from HIB adoption. A nationally representative listing exercise preceded the main household survey for the impact assessment. The listing exercise was conducted across 120 rural villages in 29 provinces of Rwanda and was administered to a total of 19,575 households. The data included here are from both the listing exercise and the main impact assessment survey.

× Anemia remains a public health problem in Rwanda, affecting 38% of young children and 17% of reproductive-aged women (Demographic and Health Survey [DHS] 2010). The importance of iron deficiency (ID) as a cause of anemia in Rwanda is not known. We conducted a cluster randomized survey, selecting 408 rural households each in the Northern and Southern Provinces of Rwanda in 2010, to estimate the prevalence of ID and iron deficiency anemia (IDA) among young children and women of reproductive age.

× This dataset include survey instrument and data used in a collaborative technology adoption study conducted by the Association for Strengthening Agricultural Research in Eastern and Central Africa (ASARECA) and IFPRI. The study aimed to track the adoption and diffusion of selected technologies generated and promoted by in Tanzania, DRC and Rwanda. The studies were undertaken under the "Monitoring the Geospatial Diffusion of Agricultural Technologies" project funded Research Program on Policies, Institutions and Markets (PIM). The studies involved use of cost-effective ICT-based survey technique to track adoption and diffusion of agricultural technologies and explore scalable options for monitoring farmer's use of agricultural technologies. This innovative approach sought to document extent of technology adoption and diffusion over time and space since there is little evidence in this area with other approaches. The main objective of the survey was to test innovative methodologies for tracking adoption and generate data, knowledge and information on how far the agricultural technologies have been adopted by smallholder farmers and diffused over time and space. The specific objectives of the diffusion surveys were to: (i) establish the level of adoption of the technologies promoted by ASARECA within the target countries; (ii) identify, track and map out new areas where the technologies promoted by ASARECA have been adopted and diffused over time within the target countries; (iii) identify factors that are limiting the adoption of the technologies promoted by ASARECA within the target countries; and (iv) establish why farmers have stopped using the technologies and estimate level of technology dis-adoption among the target farmers. These studies looked at two technologies promoted by ASARECA within the region: QPM in Tanzania and DRC; and Climbing beans in Rwanda. Survey tools developed by IFPRI in collaboration with ASARECA and implemented as the TechTracker Survey Application developed by Spatial Development International.

× The 2011 Social Accounting Matrix for Rwanda is based on newly estimated supply-use tables, national accounts, state budgets, and balance of payments. The SAM reconciles these data using cross-entropy estimation techniques. The final SAM is a detailed representation of Rwanda's economy. It separates 54 activities and commodities; labor by different sectoral types; and households by rural/urban areas as well expenditure quintiles. Labor and household information is drawn from the most recent Rwanda Living Expenditure Survey. Finally, the SAM identifies government, investment and foreign accounts. It is therefore an ideal tool for economywide impact assessments, including SAM-based multiplier analysis and computable general equilibrium (CGE) modeling.

× This dataset includes national-level time series data on researcher capacity by qualification level, age bracket, discipline mix, and commodity, as well as a detailed breakdown of agricultural research investment across government, higher education, nonprofit, and (where possible) private for-profit agricultural research agencies. These data were derived through a series of primary survey rounds conducted by IFPRI’s Agricultural Science and Technology Indicators (ASTI) and in close collaboration with a large network of national collaborators. The ASTI data constitute a powerful resource for national and regional research managers, policymakers, donor organizations, and other stakeholders. ASTI’s key indicators provide both a diagnostic tool for assessing the allocation and use of existing resources and an advocacy tool for increasing resources and improving the efficiency and effectiveness of resource use. The ASTI website offers interactive pages that allow users to access country-level time series data, make cross-country comparisons, create graphs, and download country datasets and publications as well as detailed institutional information on agencies involved in agricultural research. The interactive benchmarking tool on the ASTI website is a convenient map-based instrument allowing users to make cross-country comparisons and rankings based on a wide set of financial and human resource indicators. The detailed ASTI datasets are available in an easy-to-use data download tool. Detailed information on definitions, methodology, and calculation procedures are available at www.asti.cgiar.org

× The motivation to measure food policy research capacity stems from a pressing need to understand what a country's primary constraints are in undertaking food policy research and using it effectively in the policy process. With such understanding, capacity-development interventions can become easier to design and capacity building programs can be more effective. Food policy research is defined here as any socioeconomic or policy-related research in the food, agriculture, and natural-resource sectors. In this database, two country-level food policy research capacity indicators are presented. The first indicator is the number of full-time equivalent analysts or researchers with PhDs or their equivalent analysts or researchers with PhDs or their equivalent per one million rural citizens. This number is indicative of a country's investment in policy research activities. Although financial and physical resources are not explicitly included in this measure, it is assumed that the number of researchers acts as a proxy for these other food policy research inputs. This indicator includes staff at government ministries, higher education institutes, and research organizations that undertake food policy research as defined above. Staff members with a master's degree are valued at half of a PhD, and those with a bachelor's degree are valued at a quarter of a PhD. The number of staff is also scaled by the proportion of time spent on food policy research which is dependent on the type of institution.

The second indicator is the number of food policy relevant journal articles published internationally within the last five years per full-time PhD-equivalent researcher. This input-output ratio measure is indicative of the efficiency of the policy research environment. The number of publications was determined from searches in the EconLit and Web of Science databases for journal articles related to food policy and authored by experts who were counted in the assessment of the first indicator. Earlier attempts to quantify and collect comparable data on other policy research outputs, such as policy briefs, interactions with government ministries, or conference contributions presented numerous challenges. For this reason, and because international publications guarantee a minimum and comparable level of quality, this indicator was chosen.

× The 2006 Social Accounting Matrix (SAM) for Rwanda represents the structure of Rwandan economy and the links among various production activities, income distribution, household consumption of goods and services, savings and investments, and foreign trade for the year 2006. This SAM has been modified from the o
riginal SAM, which was constructed by Arnault Emini (2007) under a joint project between the Ministry or Economy and Finance (MINECOFIN) in collaboration with the Ministry of Agriculture (MINAGRI) and the World Bank. In this SAM, the three main components of Rwandan economy: (i) agriculture, (ii) industry, and (iii) services are disaggregated into 53 sectors. The agriculture sector includes 16 crops, 7 livestock, 1 fishery and 1 forestry sub-sector. The industry sector comprises 13 manufacturing, 1 mining, and 1 construction, and 1 electricity, gas and water subsector. Similarly, the service sector consists of 9 private and 3 public service subsectors. The 2006 SAM data files comprises of two worksheets; one for the SAM data and the other containing legend to the SAM data. The value for each entry is reported in million Rwandan francs (2006 prices). The data used for building this SAM was obtained from various sources including National Institutes of Statistics of Rwanda, Rwandan Revenue Authority, National Bank of Rwanda, and 2005-2006 Household Living Conditions Survey.