Types of Research
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.
Cereal yield variability is influenced by initial conditions such as suitability of the farming system for cereal cultivation, current production quantities and yields, and zone-specific potential yields limited by water availability. However, exogenous factors such as national policies, climate, and international market conditions also impact farm-level yields directly or provide incentives or disincentives for farmers to intensify production. We conduct a selective literature review of policy-related drivers of maize yields in Ethiopia, Kenya, Malawi, Rwanda, Tanzania, and Uganda and pair the findings with FAOSTAT data on yield and productivity. This report presents our cumulative findings along with contextual evidence of the hypothesized drivers behind maize yield trends over the past 20 years for the focus countries.
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.
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.
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.
Cassava production is prone to many constraints throughout the production cycle, including biotic, abiotic, and management constraints. This brief reviews the literature on the production impacts of two key cassava stressors: cassava bacterial blight (CBB) and postharvest physiological deterioration (PPD). We summarize available estimates of the frequency and magnitude of these constraints relative to other drivers of cassava production losses that affect smallholder farmers in Sub-Saharan Africa (SSA), review the control strategies proposed in the literature, report on the views of several experts in the field, and identify research gaps where relatively little appears to be known about CBB or PPD yield impacts or best practices for CBB or PPD management.
Cassava (Manihot esculenta Crantz) is a widely-grown staple food in the tropical and subtropical regions of Africa, Asia, and Latin America. In this brief we examine the environmental constraints to, and impacts of, smallholder cassava production systems in Sub-Saharan Africa (SSA) and South Asia (SA), noting where the analysis applies to only one of these regions. We highlight crop-environment interactions at three stages of the cassava value chain: pre-production (e.g., land clearing), production (e.g., soil, water, and input use), and post-production (e.g., crop storage). At each stage we emphasize environmental constraints on production (poor soil quality, water scarcity, crop pests, etc.) and also environmental impacts of crop production (e.g., soil erosion, water depletion and pesticide contamination). We then highlight good practices for overcoming environmental constraints and minimizing environmental impacts in smallholder cassava production systems. Evidence on environmental issues in smallholder cassava production is relatively thin, and unevenly distributed across regions. The literature on cassava in South Asian smallholder systems is limited, reflecting a crop of secondary importance (though it is widely found elsewhere in Asia such as South East Asia), in comparison to cassava in much of SSA. The majority of the research summarized in this brief is from SSA. The last row of Table 1 summarizes good practices currently identified in the literature. However, the appropriate strategy in a given situation will vary widely based on contextual factors, such as local environmental conditions, market access, cultural preferences, production practices and the policy environment.
This overview introduces a series of EPAR briefs in the Agriculture-Environment Series that examine crop-environment interactions for a range of crops in smallholder food production systems in Sub-Saharan Africa (SSA) and South Asia (SA). The briefs cover the following important food crops in those regions; rice (#208), maize (#218), sorghum/millets (#213), sweet potato/yam (#225), and cassava (#228).
Drawing on the academic literature and the field expertise of crop scientists, these briefs highlight crop-environment interactions at three stages of the crop value chain: pre-production (e.g., land clearing and tilling), production (such as water, nutrient and other input use), and post-production (e.g., waste disposal and crop storage). At each stage we emphasize environmental constraints on crop yields (including poor soils, water scarcity, crop pests) and impacts of crop production on the environment (such as soil erosion, water depletion and pest resistance). We then highlight best practices from the literature and from expert experience for minimizing negative environmental impacts in smallholder crop production systems.
This overview (along with the accompanying detailed crop briefs) seeks to provide a framework for stimulating across-crop discussions and informed debates on the full range of crop-environment interactions in agricultural development initiatives.