Datasets

× The Food Security Simulator is an innovative and easy-to-use, MS-Excel-based tool for assessing the potential short-term impacts of food price or household income shocks on food security and people’s diets. The Simulator is an ideal tool for first-cut forward-looking evaluations of direct, household-level outcomes of economic crises and policy responses in a timely manner. The tool allows users to enter positive and negative price or income changes in percentage terms and provides simulated changes for a diverse set of food-consumption- and diet-quality-related indicators. In addition to detailed tabular presentations of all simulation results by household income quintile and residential area, key indicator results are summarized in concise overview tables and visualized in graphs for easy export and use in reports. The underlying data include estimates from representative household survey data and rigorous, sophisticated food demand models to capture consumer behavior.

× This dataset is the result of a phone survey set up to measure the impact of COVID-19 on rural people in Kenya. As most governments have urged the population to stay at home to slow down the transmission of the disease, the impact of COVID-19 can affect women and men in different ways: as an income shock (directly or indirectly); as a health and caring shock; as a shock of mobility (affecting access to water, food, firewood, schooling); and as a risk of increased domestic conflict and violence. To capture these various effects on household welfare, this phone survey was conducted with (around) 600 individuals randomly drawn from an existing list of phone numbers collected from previous household surveys with an equal proportion of women and men. The same individuals were also interviewed during other rounds to generate a longitudinal panel allowing to analyze the impact of COVID-19 through time.

× 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 2019 Kenya SAM follows the Standard Nexus Structure. The open access version of the Kenya 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.

× The optimal design of informal contracts in agricultural value chains depends on when farmers prefer to be paid for their output. While the evidence from the time
preference experiments suggests a preference for early payments, ?eld studies often indicate that farmers will defer regular payments if given the opportunity. In this study, we explicitly test whether farmers are more patient regarding regular, earned income than regarding experimental windfall payments. We asked farmers in a dairy cooperative in Kenya to allocate both their milk income and a one-time gift between an early and a deferred payment date. We ?nd that a large majority of participants deferred their milk payments, while rarely choosing to defer the gift. Participants� survey responses suggest that we observe this di?erence because of mental accounting: participants earmarked their regular milk payments, but not the gift, to save for bulky expenditures. We conclude that deferred payments can provide value to producers by functioning as a savings device, even when decisions over windfall income suggest a preference for early payments. We are sharing the data collected through this experiment as well as our do-files for replication and further analysis purposes.

× This dataset is the result of a phone survey set up to measure the impact of COVID-19 on rural people in Kenya. As most governments have urged the population to stay at home to slow down the transmission of the disease, the impact of COVID-19 can affect women and men in different ways: as an income shock (directly or indirectly); as a health and caring shock; as a shock of mobility (affecting access to water, food, firewood, schooling); and as a risk of increased domestic conflict and violence. To capture these various effects on household welfare, this phone survey was conducted with (around) 600 individuals randomly drawn from an existing list of phone numbers collected from previous household surveys with an equal proportion of women and men. The same individuals were also interviewed during other rounds to generate a longitudinal panel allowing to analyze the impact of COVID-19 through time.

× This dataset is the result of a phone survey set up to measure the impact of COVID-19 on rural people in Kenya. As most governments have urged the population to stay at home to slow down the transmission of the disease, the impact of COVID-19 can affect women and men in different ways: as an income shock (directly or indirectly); as a health and caring shock; as a shock of mobility (affecting access to water, food, firewood, schooling); and as a risk of increased domestic conflict and violence. To capture these various effects on household welfare, this phone survey was conducted with (around) 600 individuals randomly drawn from an existing list of phone numbers collected from previous household surveys with an equal proportion of women and men. The same individuals were also interviewed during other rounds to generate a longitudinal panel allowing to analyze the impact of COVID-19 through time.

× This dataset is the result of a phone survey set up to measure the impact of COVID-19 on rural people in Kenya. As most governments have urged the population to stay at home to slow down the transmission of the disease, the impact of COVID-19 can affect women and men in different ways: as an income shock (directly or indirectly); as a health and caring shock; as a shock of mobility (affecting access to water, food, firewood, schooling); and as a risk of increased domestic conflict and violence. To capture these various effects on household welfare, this phone survey was conducted with (around) 500 individuals randomly drawn from an existing list of phone numbers collected from previous household surveys with an equal proportion of women and men. The same individuals were also interviewed during other rounds to generate a longitudinal panel allowing to analyze the impact of COVID-19 through time.

× This dataset is produced from the randomized controlled trial (RCT), which was conducted to test for a causal impact of aflatoxin exposure on child growth. Participants were recruited from among households containing women in the last 5 months of pregnancy in 28 maize-growing villages within Meru and Tharaka-Nithi Counties in Kenya. Households in villages assigned to the intervention group are offered rapid testing of their stored maize for the presence of aflatoxin each month; any maize found to contain more than 10 ppb aflatoxin is replaced with an equal amount of maize that contains less than this concentration of the toxin. They are also offered the opportunity to buy maize that has been tested and found to contain less than 10 ppb aflatoxin at local shops. Clusters (villages) were allocated to the intervention group (28 villages containing 687 participating households) or control group (28 villages containing 536 participating households) using a random number generator.

Data collection at baseline and follow-up were done at participants’ homes through face-to-face interviews. A pre-coded survey was administered to the expectant mother immediately after enrollment, her height and weight were measured, and self-reported month of pregnancy was recorded. Expectant mothers were also asked to provide a venous blood sample to be analyzed for serum aflatoxin. A similar survey was repeated during follow-up data collection at 24 months after enrollment. Participants enrolled in the fourth through sixth waves were additionally followed-up 24 months after the third enrollment wave. At each follow-up visit, the length and weight of the child in utero at baseline (reference child) were recorded, and a venous blood sample was taken from this child for serum aflatoxin analysis.

× Many developing-country farmers cultivating vegetatively propagated crops (VPCs)—crops such as cassava, potato, sweetpotato, and yam—face constrained access to quality planting material. This challenge is distinct from the challenges facing cereal crops, and is associated with both the unique biological and economic nature of vegetative propagation. Although technological solutions exist, there are other limiting factors relating to policies, institutions, and markets that shape VPC seed systems, e.g., quality assurance mechanisms, certification regulations, sanitary and phytosanitary standards, and plant variety protection.

This research project aims to provide actionable evidence on policy and investment options to accelerate seed system and market development in countries where VPCs are important to food security and agricultural development. By taking a collaborative and multidisciplinary approach to the research, the project (1) analyzes current policy initiatives and success factors underpinning models that incentivize cost-effective multiplication and distribution of VPC seed to smallholders; and (2) develops a set of crop-specific case studies in Kenya, Nigeria, and Vietnam that encourage closer consideration of more appropriate policy options. This document provides a brief summary of the project and accompanies the key informant interview guides to collect data for analysis purposes.

× The Financial and Health Diaries capture high-detail high-frequency data on how low-income households in developing countries manage money and make spending choices around healthcare. The data provide detailed weekly information on individuals’ financial activities, health events and interactions with healthcare providers.

× 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 IFPRI-CCAFS Gender and Climate Change Survey data were collected in four sites in Africa south of the Sahara in early 2013 as part of the CGIAR Research Program on Climate Change, Agriculture and Food Security (CCAFS) under the project "Increasing Women’s Resilience to Confront Climate Change." It aimed to enhance understanding of gendered climate change perceptions, impacts, adaptation and coping strategies, as well as the constraints to adaptation within selected CCAFS baseline sites in Kenya, Senegal, and Uganda. Specifically, the survey was designed to answer questions such as:
• How do men and women perceive climate change and, particularly, the livelihood risks associated with climate change?

• What are the gender disparities in access to and control over assets and how and to what degree does the disparity in assets affect how men and women experience climate shocks and change?

• How and to what degree does asset disparity determine how men and women respond to climate shocks and change?

• Which coping strategies and adaptation options are favored by women and men, respectively, and why?

The survey collected detailed gender-disaggregated data on these issues to inform strategies to increase climate change resilience among both women and men. The gender survey contained 13 modules, posing questions at the household and individual levels. These modules are: 1) a household roster; 2) sketch of the farm (pre-populated from a previous survey—IMPACT Lite); 3) land ownership, management, and decision making; 4) decision-making authority on agricultural, livestock, and household decisions; 5) adoption and knowledge of climate-smart agriculture practices; 6) access to and use of climate and agricultural information services; 7) access to and use of credit; 8) membership in groups; 9) fuel and water use; 10) experience with climate shocks and coping strategies; 11) perception of climate change and its potential impacts; 12) identification of adaptation strategies; and 13) cognitive decision-making and personal values questions.

Four sets of data are generated from the survey conducted in four sites-Nyando and Wote in Kenya, Rakai in Uganda, and Kaffrine in Senegal. This study contains data from Nyando.

× The IFPRI-CCAFS Gender and Climate Change Survey data were collected in four sites in Africa south of the Sahara in early 2013 as part of the CGIAR Research Program on Climate Change, Agriculture and Food Security (CCAFS) under the project "Increasing Women’s Resilience to Confront Climate Change." It aimed to enhance understanding of gendered climate change perceptions, impacts, adaptation and coping strategies, as well as the constraints to adaptation within selected CCAFS baseline sites in Kenya, Senegal, and Uganda. Specifically, the survey was designed to answer questions such as:
• How do men and women perceive climate change and, particularly, the livelihood risks associated with climate change?

• What are the gender disparities in access to and control over assets and how and to what degree does the disparity in assets affect how men and women experience climate shocks and change?

• How and to what degree does asset disparity determine how men and women respond to climate shocks and change?

• Which coping strategies and adaptation options are favored by women and men, respectively, and why?

The survey collected detailed gender-disaggregated data on these issues to inform strategies to increase climate change resilience among both women and men. The gender survey contained 13 modules, posing questions at the household and individual levels. These modules are: 1) a household roster; 2) sketch of the farm (pre-populated from a previous survey—IMPACT Lite); 3) land ownership, management, and decision making; 4) decision-making authority on agricultural, livestock, and household decisions; 5) adoption and knowledge of climate-smart agriculture practices; 6) access to and use of climate and agricultural information services; 7) access to and use of credit; 8) membership in groups; 9) fuel and water use; 10) experience with climate shocks and coping strategies; 11) perception of climate change and its potential impacts; 12) identification of adaptation strategies; and 13) cognitive decision-making and personal values questions.

Four sets of data are generated from the survey conducted in four sites-Nyando and Wote in Kenya, Rakai in Uganda, and Kaffrine in Senegal. This study contains data from Wote.

× This data study includes social accounting matrix (SAM) for Kenya for the year 2013. The SAM is an extension of the Standard Nexus Structure. It consists of 54 activity sectors, 56 commodity sectors, three types of factors of production: labor (rural and urban disaggregated by level of education), land, and capital (disaggregated by crops, livestock, mining and other sectors). The household sector is divided spatially into urban and rural households. Rural households are further disaggregated into households that earn crop and/or livestock incomes (i.e., farm households) and those that do no earn incomes from either source (i.e., nonfarm households). Households are further disaggregated into per capita expenditure quintiles. This SAM allows analyzing issues at the detailed level and to better understand the potential impacts of policy changes for both better off and more vulnerable households.

× Resilience of food security in the arid and semi-arid lowlands (ASAL) in Kenya, were assessed using repeated cross-sectional data (collected in 1993, 1998, 2003, and 2008). We measure short- and long-term food security in response to changing agro-climatic conditions, using indicators of child and woman nutritional status. Since measurements over time on the same units of analysis are not available, synthetic cohorts of individuals (children and women) having similar characteristics have been reconstructed, resulted in a pseudo-panel dataset. The dataset is used to observe resilience to agro-climatic shocks, including temperature increases, drought, and changes in vegetation cover.

× 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.

× This is a unique primary household and community level survey data in Kenya, Tanzania, and Uganda. The study was started in 2008/2009 and the data collection took place in selected districts in Kenya, Tanzania, and Uganda. The project’s goal was to provide strong evidence to policy makers and other stakeholders in development on the effectiveness of Farmer Field Schools (FFS) in fighting poverty and fostering innovation. The specific objectives of the field data collection were to characterize farm households in terms of poverty and well-being, members-and non- FFS members, on the basis of socio-economic parameters; analyze farmers’ access to agricultural services (markets, credit and extension); and assess household’s level of individual and collective empowerment. (2012-04-09)

× The 2003 Kenya Social Accounting Matrix (SAM) is a consistent data framework that captures the information contained in the national income and product accounts and the input-output table, as well as the monetary flows between households, government and other institutions. The Kenya SAM also used surveys to estimate the production technology underlying different sectors of the economy. By combining this information with the country's household income and expenditure survey, the SAM provides a comprehensive picture of the structure of the Kenyan real economy in 2003.

× The Kenya 2001 Social Accounting Matrix (SAM) is the base for a dynamic computable general equilibrium (CGE) model of Kenya, which is an extension of the standard CGE modelling framework developed at IFPRI. The SAM disaggregates the entire Kenyan economy into 33 production sectors, of which 15 are agricultural sectors. Several structural and annual data sources such as national accounts, government accounts, balance of payments and foreign trade data, as well as the most recent IO table, SAMs for earlier base years and the 1997 Welfare Monitoring Survey for Kenya were used for the construction of the SAM.

× The Land Tenure, Agricultural Productivity and the Environment: Suba and Laikipia Districts, Kenya, 2001 dataset accompanies a study that examines the relationships between the land tenure, agricultural productivity, and the environment in order to provide the necessary policy guidelines to the Government and other stakeholders. The study was carried out in two districts, Suba and Laikipia. It is believed that these two districts provide a wide range of tenure systems, cultural backgrounds and agro-ecological diversities on which reasonable policy conclusions can be made. Specific objectives of this study were: Establish the relationship between security of tenure and agricultural productivity; Identify and establish the link between security of tenure and investment in environmental conservation and soil fertility enhancement and maintenance; Establish the link between tenure system and environmental degradation; and Analyze gender relations, land tenure and productivity. The dataset contains information on household characteristics such as household income, occupation, socioeconomic background, land characteristics such as parcel size, sale of land, security of access to land, and others including environmental degradation, conservation measures, hired labor, livestock ownership, infrastructure, and access to credit. The survey was undertaken in 4 sub-locations per district. These were randomly selected from a cluster of 10 sub-locations in each district. Each of these clusters was expected to have almost the same agro-ecological conditions with a wide range of tenure systems. In each selected cluster, a list of the household heads were compiled. The target respondents were then randomly selected from this list. A total of 40 respondents was randomly selected from each cluster (sub-location).