Types of Research
- (-) Remove Household Well-Being & Equity filter Household Well-Being & Equity
- (-) Remove Monitoring & Evaluation filter Monitoring & Evaluation
- (-) Remove Southern Africa Region and Selected Countries filter Southern Africa Region and Selected Countries
- (-) Remove Aid & Other Development Finance filter Aid & Other Development Finance
- (-) Remove Sub-Saharan Africa filter Sub-Saharan Africa
- (-) Remove ASTI filter ASTI
- (-) Remove LSMS & LSMS-ISA filter LSMS & LSMS-ISA
Recent research has used typologies to classify rural households into categories such as “subsistence” versus “commercialized” as a means of targeting agricultural development interventions and tracking agricultural transformation. Following an approach proposed by Alliance for a Green Revolution in Africa, we examine patterns in two agricultural transformation hallmarks – commercialization of farm output, and diversification into non-farm income – among rural households in Ethiopia, Nigeria, and Tanzania from 2008-2015. We classify households into five smallholder farm categories based on commercialization and non-farm income levels (Subsistence, Pre-commercial, Transitioning, Specialized Commercial, and Diversified Commercial farms), as well as two non-smallholder categories (Largeholder farms and Non-farm households). We then summarize the share of households in each of these categories, examine geographic and demographic factors associated with different categories, and explore households’ movement across categories over time. We find a large amount of “churn” across categories, with most households moving to a different (more or less commercialized, more or less diversified) category across survey years. We also find many non-farm households become smallholder farmers – and vice versa – over time. Finally, we show that in many cases increases in farm household commercialization or diversification rates actually reflect decreased total farm production, or decreased total income (i.e., declines in the denominators of the agricultural transformation metrics), suggesting a potential loss of rural household welfare even in the presence of “positive” trends in transformation indicators. Findings underscore challenges with using common macro-level indicators to target development efforts and track progress at the household level in rural agrarian communities.
Relative to chronic hunger, seasonal hunger in rural and urban areas of Africa is poorly understood. No estimates are compiled, and limited evidence exists on prevalence, causes, and impacts. This paper contributes to the body of evidence by examining the extent and potential drivers of seasonal hunger using panel data from the Malawi Integrated Household Panel Survey (IHPS). Farmers are commonly thought to use various strategies to smooth consumption, including planting “off-season” crops, investing in post-harvest storage technologies, or generally diversifying farm portfolios including livestock products and/or wild crops. Similarly, when markets are available, farmers may diversify through off-farm income sources in order to purchase food in lean seasons. We investigate whether seasonal hunger – distinct from chronic hunger – exists in Malawi, drawing on two waves of panel data from the LSMS-ISA series. We examine the extent of seasonal hunger, factors associated with variation in seasonal hunger, and how recurring and longer-term seasonal hunger might be associated with various household welfare measures. We find that both urban and rural households report experiencing seasonal hunger in the pre-harvest months, with descriptive evidence suggesting male gender, age, and education of household head, livestock ownership, and storage of crops are associated with lower levels of seasonal hunger. In addition, we find that Malawian households with seasonal hunger harvest crops earlier than average – a short-term coping mechanism that can reduce the crop’s yield and nutritional value, possibly perpetuating hunger.
Household survey data are a key source of information for policy-makers at all levels. In developing countries, household data are commonly used to target interventions and evaluate progress towards development goals. The World Bank’s Living Standards Measurement Study - Integrated Surveys on Agriculture (LSMS-ISA) are a particularly rich source of nationally-representative panel data for six Sub-Saharan African countries: Ethiopia, Malawi, Niger, Nigeria, Tanzania, and Uganda. To help understand how these data are used, EPAR reviewed the existing literature referencing the LSMS-ISA and identified 415 publications, working papers, reports, and presentations with primary research based on LSMS-ISA data. We find that use of the LSMS-ISA has been increasing each year since the first survey waves were made available in 2009, with several universities, multilateral organizations, government offices, and research groups across the globe using the data to answer questions on agricultural productivity, farm management, poverty and welfare, nutrition, and several other topics.
This report provides a general overview of trends in public and private agricultural research and development (R&D) funding and expenditures in Sub-Saharan Africa (SSA). The request is divided into two sections, covering public funding and private funding. Within each section, relevant data is presented on historical funding patterns, the types of research conducted, and which countries within SSA are financing R&D at the highest level. We find that the majority of growth in African public agricultural research funding took place in the 1960s, when real public spending on agricultural research increased 6% a year. From 1971 to 2000 annual growth averaged 1.4% a year. Public financing of agricultural R&D experienced a moderate shift in the 1990s from bilateral and multilateral donor funding to domestic government financing. The shift varied by country, but donor funding dropped for all SSA countries an average of 10%. Private research and development funding is heavily concentrated in developed countries with the United States and Japan the two biggest spenders. Within SSA, private R&D expenditures comprise 2% of all R&D spending. The main private actors in SSA are companies based in South Africa and Nigeria. The private sector is focused on research areas that involve marketable inputs, such as chemicals, seeds, and machines/