Types of Research
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In many countries in Sub-Saharan Africa and South Asia smallholder farmers are among the most vulnerable to climatic changes, and the observed shocks and stresses associated with these changes impact agricultural systems in many ways. This research brief offers findings on observed or measured changes in precipitation, temperature or both, on five biophysical pathways and systems including variable or changing growing seasons, extreme events, biotic stressors, plant species density, richness and range, impacts to streamflow, and impacts on crop yield. These findings are the result of a review of relevant documents cited in Kilroy (2015), references included in the IPCC draft Special Report on Food Security, and targeted searches from 2015 - present for South Asia and Sub-Saharan Africa.
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.
Previous research has shown that men and women, on average, have different risk attitudes and may therefore see different value propositions in response to new opportunities. We use data from smallholder farm households in Mali to test whether risk perceptions differ by gender and across domains. We model this potential association across six risks (work injury, extreme weather, community relationships, debt, lack of buyers, and conflict) while controlling for demographic and attitudinal characteristics. Factor analysis highlights extreme weather and conflict as eliciting the most distinct patterns of participant response. Regression analysis for Mali as a whole reveals an association between gender and risk perception, with women expressing more concern except in the extreme weather domain; however, the association with gender is largely absent when models control for geographic region. We also find lower risk perception associated with an individualistic and/or fatalistic worldview, a risk-tolerant outlook, and optimism about the future, while education, better health, a social orientation, self-efficacy, and access to information are generally associated with more frequent worry— with some inconsistency. Income, wealth, and time poverty exhibit complex associations with perception of risk. Understanding whether and how men’s and women’s risk preferences differ, and identifying other dominant predictors such as geographic region and worldview, could help development organizations to shape risk mitigation interventions to increase the likelihood of adoption, and to avoid inadvertently making certain subpopulations worse off by increasing the potential for negative outcomes.
Mobile technology is associated with a variety of positive development and social outcomes, and as a result reaching the “final frontier” of uncovered populations is an important policy issue. We use proprietary 2012 data on mobile coverage from Collins Bartholomew to estimate the proportion of the population living in areas without mobile coverage globally and in selected regions and countries, and use spatial analysis to identify where these populations are concentrated. We then compare our coverage estimates to data from previous years and estimates from the most recent literature to provide a picture of recent trends in coverage expansion, considering separately the trends for coverage of urban and rural populations. We find that mobile coverage expansion rates are slowing, as easier to reach urban populations in developing countries are now almost entirely covered and the remaining uncovered populations are more dispersed in rural areas and therefore more difficult and costly to reach. This analysis of mobile coverage trends was the focus of an initial report on mobile coverage estimates. In a follow-up paper prepared for presentation at the 2016 APPAM International Conference, we investigate the assumption that levels of mobile network coverage are related to the degree of market liberalization at the country level.
Common aid allocation formulas incorporate measures of income per capita but not measures of poverty, likely based on the assumption that rising average incomes are associated with reduced poverty. If declining poverty is the outcome of interest, however, the case of Nigeria illustrates that such aid allocation formulas could lead to poorly targeted or inefficient aid disbursements. Using data from the World Bank and the Nigerian National Bureau of Statistics, we find that while the relationship between economic growth and poverty in Nigeria varies depending on the time period studied, overall from 1992-2009 Nigeria’s poverty rate has only declined by 6% despite a 70% increase in per capita gross domestic product (GDP). A review of the literature indicates that income inequality, the prominence of the oil sector, unemployment, corruption, and poor education and health in Nigeria may help to explain the pattern of high ongoing poverty rates in the country even in the presence of economic growth. Our analysis is limited by substantial gaps in the availability of quality data on measures of poverty and economic growth in Nigeria, an issue also raised in the literature we reviewed, but our findings support arguments that economic growth should not be assumed to lead to poverty reduction and that the relationship between these outcomes likely depends on contextual factors.
Common estimates of agricultural productivity rely upon crude measures of crop yield, typically defined as the weight harvested of a crop divided by the area harvested. But this common yield measure poorly reflects performance among farm systems combining multiple crops in one area (e.g., intercropping), and also ignores the possibility that farmers might lose crop area between planting and harvest (e.g., partial crop failure). Drawing on detailed plot-level data from the LSMS-ISA in Tanzania, Nigeria, and Ethiopia, we show how various yield measurement decisions affect estimates of smallholder yields for a variety of crops. We consider the effect of measuring production by plot area, area planted, and area harvested, of trimming the top 1% and 2% of values, and of considering different groups of farmers according to total area planted.
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 literature review examines the environmental impacts of water buffalo in pastoral and mixed farming systems in Sub-Saharan Africa, South Asia, and South America). The environmental impacts of water buffalo are less widely studied than those of the other livestock species included in this series; typically, the environmental impacts of water buffalo are incorporated into discussions of cattle without more detailed impacts being broken down by bovine type. In Asia and India, where the majority of buffalo are raised, buffalo are typically kept in small herds of only a few animals, which may minimize the local impacts of their grazing on vegetation, soil erosion and water pollution. Some aspects of buffalo feeding and life cycle patterns, as observed in the Amazon, may cause their greenhouse gas emissions to differ from those of cattle: buffalo can fatten on a wider range of grasses, reach market size in a shorter time, transition better from dry to wet seasons, and are more resistant to bovine diseases. While buffalo grazing and trampling can lead to land degradation, buffalo can contribute to nutrient and resource cycling in farming systems because their manure is considered good fertilizer and they can remove and utilize biomass grown on agricultural plots. Mitigation strategies vary by category of environmental impact, but largely suggest improved productivity to reduce land conversion, modified management systems (e.g., biodiversity, water use and consumption, farm and pastures, and waste), and the reduction of livestock numbers altogether.
This literature review examines the environmental impacts of cattle in pastoral and mixed farming systems in Sub-Saharan Africa and South Asia. Cattle are frequently cited as having the most severe overall environmental impacts among livestock species due to: methane and nitrous oxide released from digestion and manure; land use and conversion; desertification; inefficient ratio of weight of feed and water consumed to weight of meat and dairy produced; conflicts between livestock herders and wildlife; the large volume of wastewater produced in meat and hide processing; and overgrazing of riparian areas. However, cattle have also been found to provide several environmental benefits such as keeping wildlife corridors open, preventing the spread of noxious weeds, and promoting the growth of local vegetative species. Mitigation strategies vary by category of environmental impact, but largely suggest improved productivity to reduce land conversion, modified management systems (e.g., biodiversity, water use and consumption, farm and pastures, grain and other feed, and waste), and the reduction of livestock numbers altogether.
This literature review examines the environmental impacts of goats in pastoral and mixed farming systems in Sub-Saharan Africa and South Asia. We find that the most notable environmental implications of goats stem from their ability to graze on a wide variety of biomass sources in frequently marginal environments; while this intensive grazing stimulates biodiversity loss and may be more severe than grazing by other livestock species, goats are not a major driver of forest clearing due to their low economic value. Environmental benefits of goat production include keeping wildlife corridors open, preventing the spread of noxious weeds, and promoting the growth of local vegetative species through moderate grazing. Goats are also more water-efficient than large ruminants such as cattle. Mitigation strategies vary by category of environmental impact, but largely suggest improved productivity to reduce land conversion, modified management systems (e.g., biodiversity, water use and consumption, grazing intensity and frequency, and waste), and the reduction of livestock numbers altogether.