Types of Research
- (-) Remove East Africa Region and Selected Countries filter East Africa Region and Selected Countries
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- (-) Remove Sustainable Agriculture & Rural Livelihoods filter Sustainable Agriculture & Rural Livelihoods
There is a wide gap between realized and potential yields for many crops in Sub-Saharan Africa (SSA). Experts identify poor soil quality as a primary constraint to increased agricultural productivity. Therefore, increasing agricultural productivity by improving soil quality is seen as a viable strategy to enhance food security. Yet adoption rates of programs focused on improving soil quality have generally been lower than expected. We explore a seldom considered factor that may limit farmers’ demand for improved soil quality, namely, whether farmers’ self-assessments of their soil quality match soil scientists’ assessments. In this paper, using Tanzania National Panel Survey (TZNPS) data, part of the Living Standards Measurement Study – Integrated Surveys on Agriculture (LSMS-ISA), we compare farmers’ own assessments of soil quality with scientific measurements of soil quality from the Harmonized World Soil Database (HWSD). We find a considerable “mismatch” and most notably, that 11.5 percent of survey households that reported having “good” soil quality are measured by scientific standards to have severely constrained nutrient availability. Mismatches between scientific measurements and farmer assessments of soil quality may highlight a potential barrier for programs seeking to encourage farmers to adopt soil quality improvement activities.
Labor is one of the most productive assets for many rural households in developing countries. Despite the importance of labor—and time use more generally—little research has empirically examined the quality of time-use data in household surveys. Many household surveys rely on respondent recall, the reliability of which may decrease as recall length increases. In addition, respondents often report on time allocation for the entire household, which they may not know or recall as clearly as their own time allocation. Finally, simultaneous activities such as tending children while preparing dinner, may lead to the systematic underestimation of certain activities, particularly those that tend to be performed by women. This paper examines whether the identity of the survey respondent affects estimates of time allocation within the household. Drawing on the Ugandan LSMS-ISA household survey, we find that individuals responding for themselves report higher levels of time use over the previous week than when responding for other household members. Moreover, male respondents tend to underreport time allocation for females over the age of 15 as compared to female respondents, especially time spent on domestic activities. In addition, an analysis of the effects of two economics shocks—having a baby and floods or droughts—suggests that the identity of the respondent can affect substantive conclusions about the effects of shocks on household time use.
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.
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.
The FAO defines a farming system as “a population of individual farm systems that have broadly similar resource bases, enterprise patterns, household livelihoods and constraints, and for which similar development strategies and interventions would be appropriate. Depending on the scale of the analysis, a farming system can encompass a few dozen or many millions of households.” We use the farming systems as defined by the Food and Agriculture Organization (FAO) for Sub-Saharan Africa. The FAO identifies eight main farming systems in Tanzania 1) maize mixed, 2) root crop, 3) coastal artisanal fishing, 4) highland perennial, 5) agro-pastoral millet/sorghum, 6) tree crop, 7) highland temperate mixed, and 8) pastoral. This analysis uses data from the Tanzanian National Panel Survey (TZNPS) LSMS – ISA to provide a comparison of farming systems throughout Tanzania. The TZNPS is a nationally-representative panel survey that includes households from seven of the eight FAO farming systems with only the smallest farming system, pastoral, lacking any representation.
After cereals, root and tuber crops - including sweetpotato and yam (in addition to cassava and aroids), are the second most cultivated crops in tropical countries. This literature review examines the environmental constraints to, and impacts of, sweetpotato and yam production systems in Sub-Saharan Africa (SSA) and South Asia (SA). The review highlights crop-environment interactions at three stages of the sweetpotato/yam value chain: pre-production (e.g., land clearing), production (e.g., soil, water, and input use), and post-production (e.g., waste disposal, crop storage and transport). We find that sweetpotato and yam face similar environmental stressors. In particular, because sweetpotato and yam are vegetatively propagated, the most significant (and avoidable) environmental constraints to crop yields include disease and pest infection transmitted through the use of contaminated planting materials. Published estimates suggest yield gains in the range of 30–60% can be obtained through using healthy planting material. Moreover, reducing pest damage in the field can greatly increase the storage life of root and tuber crops after harvest – currently losses from rot and desiccation can claim up to 100% of stored sweetpotato and yam on smallholder farms.
Maize has expanded through the 20th and into the 21st century to become the principle staple food crop produced and consumed by smallholder farm households in Sub-Saharan Africa (SSA), and maize production has also expanded in South Asia (SA) farming systems. In this brief we examine the environmental constraints to, and impacts of, smallholder maize production systems in SSA and SA, noting where findings apply to only one of these regions. We highlight crop-environment interactions at three stages of the maize value chain: pre-production (e.g., land clearing), production (e.g., fertilizer, water, and other input use), and post-production (e.g., waste disposal and crop storage). At each stage we emphasize environmental constraints on maize production (such as poor soil quality, water scarcity, or crop pests) and also environmental impacts of maize production (such as soil erosion, water depletion, or chemical contamination). We then highlight best or good practices for overcoming environmental constraints and minimizing environmental impacts in smallholder maize production systems. Evidence on environmental constraints and impacts in smallholder maize production is uneven. Many environmental concerns such as biodiversity loss are commonly demonstrated more broadly for the agroecology or farming systems in which maize is grown, rather than specifically for the maize crop. And more research is available on the environmental impacts of agrochemical-based intensive cereal farming in Asia (where high-input maize is a common component) than on the low-input subsistence-scale maize cultivation more typical of SSA. Decisive constraint and impact estimates are further complicated by the fact that many crop-environment interactions in maize and other crops are a matter of both cause and effect (e.g., poor soils decrease maize yields, while repeated maize harvests degrade soils). Fully understanding maize-environment interactions thus requires recognizing instances where shortterm adaptations to environmental constraints might be exacerbating other medium- or long-term environmental problems. Conclusions on the strength of published findings on crop-environment interactions in maize systems further depend on one’s weighting of economic versus ecological perspectives, physical science versus social science, academic versus grey literature, and quantity versus quality of methods and findings.
In this brief we examine the environmental constraints to, and impacts of, smallholder sorghum and millet production systems in Sub-Saharan Africa (SSA) and South Asia (SA). Millet in this paper primarily refers to pearl millet (Pennisetum glaucum), although a number of other millets of significance to smallholder production and food security are also discussed. Sorghum and millets are known for being more tolerant of major environmental stresses including drought and poor soil quality than other major cereals. But water availability is still among the greatest constraints to increased grain production, and soil fertility also significantly limits yields, especially in cases where cultivation occurs on marginal lands and where crop residues are removed for alternative uses. Ultimately sorghum and millets’ relatively higher tolerance to abiotic stresses is expected to promote an increase in global cropping area for sorghum and millets as an adaptation to climate change. Sorghum and millet exhibit relatively few of the environmental impacts commonly associated with more intensively cultivated crops such as fertilizer runoff, pesticide contamination, or water depletion, since both of these crops are overwhelmingly grown by smallholder farmers with few, if any, chemical or irrigation inputs. Nevertheless, the tendency to grow sorghum and millet on marginal and heavily sloped lands does pose some environmental risks – including soil degradation and erosion – that can be mitigated through the adoption of best practices as described in the brief.