Types of Research
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Cash transfer programs are interventions that directly provide cash to target specific populations with the aim of reducing poverty and supporting a variety of development outcomes. Low- and middle-income countries have increasingly adopted cash transfer programs as central elements of their poverty reduction and social protection strategies. Bastagli et al. (2016) report that around 130 low- and middle-income countries have at least one UCT program, and 63 countries have at least one CCT program (up from 27 countries in 2008). Through a comprehensive review of literature, this report primarily considers the evidence of the long-term impacts of cash transfer programs in low- and lower middle-income countries. A review of 54 reviews that aggregate and summarize findings from multiple studies of cash transfer programs reveals largely positive evidence on long-term outcomes related to general health, reproductive health, nutrition, labor markets, poverty, and gender and intra-household dynamics, though findings vary by context and in many cases overall conclusions on the long-term impacts of cash transfers are mixed. In addition, evidence on long-term impacts for many outcome measures is limited, and few studies explicitly aim to measure long-term impacts distinctly from immediate or short-term impacts of cash transfers.
According to AGRA's 2017 Africa Agriculture Status Report, smallholder farmers make up to about 70% of the population in Africa. The report finds that 500 million smallholder farms around the world provide livelihoods for more than 2 billion people and produce about 80% of the food in sub-Saharan Africa and Asia. Many development interventions and policies therefore target smallholder farm households with the goals of increasing their productivity and promoting agricultural transformation. Of particular interest for agricultural transformation is the degree to which smallholder farm households are commercializating their agricultural outputs, and diversifying their income sources away from agriculture. In this project, EPAR uses data from the World Bank's Living Standards Measurement Study - Integrated Surveys on Agriculture (LSMS-ISA) to analyze and compare characteristics of smallholder farm households at different levels of crop commercialization and reliance on farm income, and to evaluate implications of using different criteria for defining "smallholder" households for conclusions on trends in agricultural transformation for those households.
Land tenure refers to a set of land rights and land governance institutions which can be informal (customary, traditional) or formal (legally recognized), that define relationships between people and land and natural resources (FAO, 2002). These land relationships may include, but are not limited to, rights to use land for cultivation and production, rights to control how land should be used including for cultivation, resource extraction, conservation, or construction, and rights to transfer – through sale, gift, or inheritance – those land use and control rights (FAO, 2002). In this project, we review 38 land tenure technologies currently being applied to support land tenure security across the globe, and calculate summary statistics for indicators of land tenure in Tanzania and Ethiopia.
By examining how farmers respond to changes in crop yield, we provide evidence on how farmers are likely to respond to a yield-enhancing intervention that targets a single staple crop such as maize. Two alternate hypotheses we examine are: as yields increase, do farmers maintain output levels but change the output mix to switch into other crops or activities, or do they hold cultivated area constant to increase their total production quantity and therefore their own consumption or marketing of the crop? This exploratory data analysis using three waves of panel data from Tanzania is part of a long-term project examining the pathways between staple crop yield (a proxy for agricultural productivity) and poverty reduction in Sub-Saharan Africa.
This research considers how public good characteristics of different types of research and development (R&D) and the motivations of different providers of R&D funding affect the relative advantages of alternative funding sources. We summarize the public good characteristics of R&D for agriculture in general and for commodity and subsistence crops in particular, as well as R&D for health in general and for neglected diseases in particular, with a focus on Sub-Saharan Africa and South Asia. Finally, we present rationales for which funders are predicted to fund which R&D types based on these funder and R&D characteristics. We then compile available statistics on funding for agricultural and health R&D from private, public and philanthropic sources, and compare trends in funding from these sources against expectations. We find private agricultural R&D spending focuses on commodity crops (as expected). However contrary to expectations we find public and philanthropic spending also goes largely towards these same crops rather than staples not targeted by private funds. For health R&D private funders similarly concentrate on diseases with higher potential financial returns. However unlike in agricultural R&D, in health R&D we observe some specialization across funders – especially for neglected diseases R&D - consistent with funders’ expected relative advantages.
A growing body of evidence suggests that empowering women may lead to economic benefits (The World Bank, 2011; Duflo, 2012; Kabeer & Natali, 2013). Little work, however, focuses specifically on the potential impacts of women’s empowerment in agricultural settings. Through a comprehensive review of literature this report considers how prioritizing women’s empowerment in agriculture might lead to economic benefits. With an intentionally narrow focus on economic empowerment, we draw on the Women’s Empowerment in Agriculture Index (WEAI)’s indicators of women’s empowerment in agriculture to consider the potential economic rewards to increasing women’s control over agricultural productive resources (including their own time and labor), over agricultural production decisions, and over agricultural income. While we recognize that there may be quantifiable benefits of improving women’s empowerment in and of itself, we focus on potential longer-term economic benefits of improvements in these empowerment measures.
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.
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 Tanzania’s National Panel Survey, our research contrasts measures of smallholder productivity using production per hectare harvested and production per hectare planted.
An initial analysis (Research Brief - Rice Productivity Measurement) looking at rice production finds that yield by area planted differs significantly from yield by area harvested, particularly for smaller farms and female-headed households. OLS regression further reveals different demographic and management-related drivers of variability in yield gains – and thus different implications for policy and development interventions – depending on the yield measurement used. Findings suggest a need to better specify “yield” to more effectively guide agricultural development efforts.
A farmer’s decision of how much land to dedicate to each crop reflects their farming options at the extensive and intensive margins. The extensive margin represents the total amount of agricultural land area that a farmer has available in a given year (referred to interchangeably as ‘farm size’ or ‘agricultural land’). A farmer increases land use on the extensive margin by planting on new agricultural land. The intensive margin represents area planted of crops as a proportion of total farm size. A farmer increases the intensive margin by increasing output within a fixed area. This analysis examines cropping patterns for households in Tanzania between 2008 and 2010 using data from the Tanzania National Panel Survey (TZNPS). This brief describes changes in farm size, total area planted, and area planted of select annual crops to highlight the dynamic nature of farmer’s cropping choices for a sample population of 2,246 agricultural households that reported having any agricultural land in 2008 or 2010. Throughout the brief, we present summary statistics at the national level and compare them with household-level data to show how results vary depending on how the sub-population is defined and how average measures can mask household level changes. We analyze these questions in the context of smallholders (defined as households with total agricultural land area as less than two hectares) and farming systems.