Types of Research
- (-) Remove Agricultural Inputs & Farm Management filter Agricultural Inputs & Farm Management
- (-) Remove Sub-Saharan Africa filter Sub-Saharan Africa
- (-) Remove Risk, Preferences, & Decision-Making filter Risk, Preferences, & Decision-Making
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.
A large and growing body of scholarship now suggests that many household outcomes, including children’s education and nutrition, are associated with a wife’s bargaining power and control over household decision-making. In turn, bargaining power in a household is theorized to be driven by a wife’s financial and human capital assets – in particular the degree to which these assets contribute to household productivity and/or to the wife’s exit options. This paper draws on the detailed Farmer First dataset in Tanzania and Mali to examine husband and wife reports of a wife’s share of decision-making authority in polygynous households, where multiple wives jointly contribute to household productivity, and where exit options for any single wife may be less credible. We find that both husbands and wives assign less authority to the wife in polygynous households relative to monogamous households. We also find that a wife’s assets are not as strongly associated with decision-making authority in polygynous versus monogamous contexts. Finally, we find that responses to questions on spousal authority vary significantly by spouse in both polygynous and monogamous households, suggesting interventions based on the response of a single spouse may incorrectly inform policies and programs.
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 brief reviews the evidence of realized yield gains by smallholder farmers attributable to the use of high-quality seed and/or improved seed varieties. Our analysis suggests that in most cases, use of improved varieties and/or quality seed is associated with modest yield increases. In the sample of 395 trials reviewed, positive yield changes accompanied the use of improved variety or quality seed, on average, in 10 out of 12 crops, with rice and cassava as the two exceptions.
This desk study reports on the small-scale machinery sector in China and a selection of SSA countries: Ethiopia, Tanzania, Nigeria, Burkina Faso, and Uganda. The report is organized into three sections. Section 1 discusses the current state of small-scale agricultural machinery in SSA for crop and livestock production in each of the SSA countries identified. It also seeks to identify major areas of need in terms of agricultural mechanization and major constraints to agricultural machinery adoption, dissemination and maintenance. Section 2 focuses on the agricultural machinery sector in China and Chinese Africa relationships in agricultural development. It also identifies the major government players in the Chinese agricultural machinery sector. Section 3 is a “directory” of small-scale agricultural machinery manufactured in China with potential relevance for SSA smallholder farmers. We divide machines by function (e.g. threshing) although many Chinese machines are multi-function and can serve multiple purposes. We also note applicable crops, if listed by the manufacturers, and technical specifications as available.
This brief presents selected material from the Fourth African Agricultural Markets Program (AAMP) policy symposium, Agricultural Risks Management in Africa: Taking Stock of What Has and Hasn’t Worked, organized by the Alliance for Commodity Trade in Eastern and Southern Africa and the Common Market for Eastern and Southern Africa that took place in Lilongwe, Malawi, September 6-10, 2010. We draw almost exclusively from Rashid and Jayne’s summary, “Risk Management in African Agriculture: A review of experiences.” This article summarizes across the background papers, with major findings grouped into three broad categories: cross cutting, government-led policies, and modern instruments.
In recent years, product supply chains for agricultural goods have become increasingly globalized. As a result, greater numbers of smallholder farmers in South Asia (SA) and Sub-Saharan Africa (SSA) participate in global supply chains, many of them through contract farming (CF). CF is an arrangement between a farmer and a processing or marketing firm for the production and supply of agricultural products, often at predetermined prices. This literature review finds empirical evidence that demonstrates that the economic and social benefits of CF for smallholder farmers are mixed. A number of studies suggest that CF may improve farmer productivity, reduce production risk and transaction costs, and increase farmer incomes. However, critics caution that CF may undermine farmers’ relative bargaining power and increase health, environmental, and financial risk through exposure to monopsonistic markets, weak contract environments, and unfamiliar agricultural technologies. There is consensus across the literature that CF has the best outcomes for farmers when farmers have more bargaining power to negotiate the terms of the contract. In reviewing the literature on CF, we find a number of challenges to comparing studies and evaluating outcomes across contracts. This literature review summarizes empirical findings and analyses regarding contract models and best practices to increase farmers’ bargaining power and decrease contract default.
Introducing technology that is designed to be physically appropriate and valuable to women farmers can increase yields and raise income. But gender issues for agricultural technology projects in Sub-Saharan Africa (SSA) are extremely complex. The EPAR series on Gender and Cropping in SSA offers examples of how these issues can affect crop production and adoption of agricultural technologies at each point in the crop cycle for eight crops (cassava, cotton, maize, millet, rice, sorghum, wheat, and yam). This executive summary highlights innovative opportunities for interventions that consider these dimensions of gender. We encourage readers to consult the crop specific briefs for more details. We find that involving both men and women in the development, testing, and dissemination of agricultural technology has been shown to be successful in helping both benefit. Nevertheless, a consistent finding throughout the Gender and Cropping in SSA series is that maximum benefits from technological innovations cannot be realized when upstream factors like education, power, and land tenure heavily influence outcomes. Addressing these more basic upstream causes of gender inequality may be even more important in helping households increase productivity and maximize the benefits of technological interventions.
A widely quoted estimate is that women produce 70 to 80 percent of Sub-Saharan Africa’s (SSA) food. Increasing farmer productivity in SSA therefore requires understanding how these women make planting, harvesting, and other decisions that affect the production, consumption, and marketing of their crops. This brief provides an overview of the gender cropping series highlighting similar themes from the various crops studied, presenting an overarching summary of the findings and conclusion of the individual literature reviews. The studies reviewed suggest that differential preferences and access to assets by men and women can affect adoption levels and the benefits that accrue to men and women. Findings show that women have less secure access to credit, land, inputs, extension, and markets. Similarly, women’s multi-faceted role in household management gives rise to preferences that may very well be different from those of men. Participatory Breeding and Participatory Varietal Selection are two methods shown to be successful in developing technology that is more appropriate and more likely to avoid unintended consequences. Regularly collecting gender-disaggregated statistics can also result in a greater understanding of how technology has affected both men and women. Agricultural technology has the potential to enhance both men’s and women’s welfare and productivity, but unless gender is sufficiently integrated into every step of the development and dissemination process, efforts will only achieve a fraction of their total possible benefit.
Estimates suggest that women grow 70-80 percent of Africa’s food crops, which may constrain their involvement in cash crop production, if food crop production places additional demands their time, resources and labor. There is little evidence regarding women’s motivations or decisions to grow cash versus food crops. Similarly, the policy literature on cotton production and markets in Sub-Saharan Africa (SSA) does not explicitly address the issue of gender, further limiting the information available on the impact of cotton production on women. This brief provides an overview of the role of women in cotton production, and provides a framework for analyzing barriers to women and technology’s impact on women throughout the cropping cycle. We find that women are typically not the primary cultivators of cotton, and that cotton production is a household cultivation strategy, especially in West and Central Africa. Cotton cultivation often provides access to fertilizers, pesticides and extension services that are otherwise unavailable to households. Women have benefitted from household cotton income when they have input in intra-household resource allocation decisions or when they are able to grow cotton on personal plots and have control over the income it generates. Women also benefit from cotton when it offers them the opportunity to engage in paid labor. The data suggests, however, that cotton cultivation can negatively impact women when it increases their unpaid agricultural labor burden or exposes them to harmful chemicals.