Types of Research
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This brief presents an overview of EPAR’s previous research related to gender. We first present our key takeaways related to labor and time use, technology adoption, agricultural production, control over income and assets, health and nutrition, and data collection. We then provide a brief overview of each previous research project related to gender along with gender-related findings, starting with the most recent project. Many of the gender-related findings draw from other sources; please see the full documents for references. Reports available on EPAR’s website are hyperlinked in the full brief.
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.
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.
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.
In Sub-Saharan Africa, 12% of adults now report having a mobile money account, representing over a quarter of the share of those who have any kind of financial account at all. As mobile money expands, there is interest in how regulatory frameworks develop to support digital financial services (DFS) and also support broader financial inclusion. In theory, protecting consumers from risk, and ensuring that they have the information and understanding required to make informed decisions, may increase their confidence and trust in mobile money systems, leading to higher adoption and usage rates. However, consumer protection regulations may also carry certain trade-offs in terms of cost, usage, and innovation. The challenge, according to proponents of consumer protection, is to develop regulations that promote access and innovation, yet still offer an acceptable level of consumer protection. We review the literature on consumer protection institutions and regulatory documents for DFS (particularly mobile money) in 22 developing countries, and identify examples of specific consumer protection regulations relevant to mobile money in each country.
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.
Agricultural productivity growth has been empirically linked to poverty reduction across a range of measures for both staple and export crops. Many public and private organizations have thus made it a priority to increase farm productivity, and have invested billions toward this end.This report compiles measures commonly used to track agricultural productivity and discusses the ways in which they are subject to error, bias, and other data limitations. Though each measure has limitations, choosing the measure(s) most appropriate to the goals of an analysis and understanding the sources of variation allows for more effective and closely targeted investments and policy and program recommendations, particularly when measures suggest different drivers of productivity growth and links to poverty reduction.
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.