Types of Research
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Studies of improved seed adoption in developing countries almost always draw from household surveys and are premised on the assumption that farmers are able to self-report their use of improved seed varieties. However, recent studies suggest that farmers’ reports of the seed varieties planted, or even whether seed is local or improved, are sometimes inconsistent with the results of DNA fingerprinting of farmers' crops. We use household survey data from Tanzania to test the alignment between farmer-reported and DNA-identified maize seed types planted in fields. In the sample, 70% of maize seed observations are correctly reported as local or improved, while 16% are type I errors (falsely reported as improved) and 14% are type II errors (falsely reported as local). Type I errors are more likely to have been sourced from other farmers, rather than formal channels. An analysis of input use, including seed, fertilizer, and labor allocations, reveals that farmers tend to treat improved maize differently, depending on whether they correctly perceive it as improved. This suggests that errors in farmers' seed type awareness may translate into suboptimal management practices. In econometric analysis, the measured yield benefit of improved seed use is smaller in magnitude with a DNA-derived categorization, as compared with farmer reports. The greatest yield benefit is with correctly identified improved seed. This indicates that investments in farmers' access to information, seed labeling, and seed system oversight are needed to complement investments in seed variety development.
Self-Help Groups (SHGs) in Sub-Saharan Africa can be defined as mutual assistance organizations through which individuals undertake collective action in order to improve their own lives. “Collective action” implies that individuals share their time, labor, money, or other assets with the group. In a recent EPAR data analysis, we use three nationally-representative survey tools to examine various indicators related to the coverage and prevalence of Self-Help Group usage across six Sub-Saharan African countries. EPAR has developed Stata .do files for the construction of a set of self-help group indicators using data from the Living Standards Measurement Study - Integrated Surveys on Agriculture (LSMS-ISA), Financial Inclusion Index (FII), and FinScope.
We compiled a set of summary statistics for the final indicators using data from the following survey instruments:
- Ethiopia Socioeconomic Survey (ESS), Wave 3 (2015-16)
- Kenya FinScope, Wave 4 (2015)
- Kenya FII, Wave 4 (2016)
- Nigeria FII, Wave 4 (2016)
- Rwanda FII, Wave 4 (2016)
- Tanzania National Panel Survey (TNPS), Wave 4 (2014-15)
- Tanzania FinScope, Wave 4 (2017)
- Tanzania FII, Wave 4 (2016)
- Uganda FinScope, Wave 3 (2013)
- Uganda FII, Wave 4 (2016)
The raw survey data files are available for download free of charge from the World Bank LSMS-ISA website, the Financial Sector Deepening Trust website, and the Financial Inclusion Insights website. The .do files process the data and create final data sets at the household (LSMS-ISA) and individual (FII, FinScope) levels with labeled variables, which can be used to estimate summary statistics for the indicators.
All the instruments include nationally-representative samples. All estimates from the LSMS-ISA are household-level cluster-weighted means, while all estimates from FII and FinScope are calculated as individual-level weighted means. The proportions in the Indicators Spreadsheet are therefore estimates of the true proportion of individuals/households in the national population during the year of the survey. EPAR also created a Tableau visualization of these summary statistics, which can be found here.
We have also prepared a document outlining the construction decisions for each indicator across survey instruments and countries. We attempted to follow the same construction approach across instruments, and note any situations where differences in the instruments made this impossible.
The spreadsheet includes estimates of the following indicators created in our code files:
- Proportion of individuals who have access to a mobile phone
- Proportion of individuals who have official identification
- Proportion of individuals who are female
- Proportion of individuals who use mobile money
- Proportion of individuals who have a bank account
- Proportion of individuals who live in a rural area
- Individual Poverty Status
- Two Lowest PPI Quintiles
- Middle PPI Quintile
- Two Highest PPI Quintiles
Coverage & Prevalence
- Proportion of individuals who have interacted with a SHG
- Proportion of individuals who have used an SHG for financial services
- Proportion of individuals who depend most on SHGs for financial advice
- Proportion of individuals who have received financial advice from a SHG
- Proportion of households that have interacted with a SHG
- Proportion of households in communities with at least one SHG
- Proportion of households in communities with access to multiple farmer cooperative groups
- Proportion of households who have used an SHG for financial services
In addition, we produced estimates for 29 indicators related to characteristics of SHG use including indicators related to frequency of SHG use, characteristics of SHG groups, and individual/household trust of SHGs.
How development organizations, NGOs, and governments can best allocate scarce resources to those in need has long been debated. As opposed to universal allocation of resources, a more targeted approach attempts to minimize program costs while maximizing benefits among those with the greatest need or market opportunity. Drawing on literature from several sectors,this brief presents two categories of beneficiary targeting in the development context: administrative targeting and self-targeting. The paper includes a brief overview of targeting and segmentation in development, a summary of reasons for targeting, theoretical and practical critiques of targeting, and a discussion of targeting methods in research and practice, including examples from the literature. Implementation examples cited in this body of research include food aid program targeting by self-reported household income in Egypt; fertilizer use in low-potential zones of Uganda; and seven strategic initiatives to improve drought and disease resistance in crops in Asia and Sub-Saharan Africa. We find that beneficiary segmentation has several theoretical advantages. Improved targeting may increase the efficiency and equity of organizational and program efforts and help better match interventions to recipient preferences, increasing the likelihood of adoption and participation. Development organizations may improve the focus of both their strategic priorities and budgets through customized targeting methods. However, concerns exist regarding the accuracy, reliability, cost, and time-constraints of targeting methodologies. Creating valid and reliable target groups with implementation potential remains a significant challenge.
The purpose of this literature review is to examine research and decision-making tools that model the impacts of agricultural interventions. We begin with a short explanation of what model features are being described. We then review decision-support tools and user-end modeling tools (menu-driven tools with an interface designed for easy use), as well as academic and professional research models for assessing the potential impacts of agricultural interventions. This review also includes decision tools and models for analyzing agricultural and environmental policies outside of technology impacts in Sub-Saharan Africa and South Asia. The other tools mentioned here, for example a tool that considers nutritional intervention impacts, are included to help provide a broader understanding of the structure and availability of user-end, decision-making tools. In the final section of this brief, we review the most complex models used more in academic research than for in-field decision-making.
Market-oriented agricultural production can be a mechanism to increase smallholder farmer welfare, rural market performance, and contribute to overall economic growth. Cash crop production can allow households to increase their income by producing output with higher returns to land and labor and using the income generated from sales to purchase goods for consumption. However, in the face of missing and underperforming markets, African smallholder households are often unable to produce efficiently or obtain staple foods reliably and cheaply. This literature review summarizes the available literature on the impact of smallholder participation in cash crop and export markets on household welfare and rural markets. The review focuses exclusively on evidence from Sub-Saharan Africa regarding top and emerging export crops, with the addition of tobacco and horticulture due to the volume of research relevant to smallholder welfare gains from the production of these crops. It includes theoretical frameworks, case studies, empirical evidence, and historical analysis from 42 primary empirical studies and 112 resources overall.
How development organizations, NGOs, and governments can best allocate scarce resources to those in need has long been debated. As opposed to universal allocation of resources, a more targeted approach attempts to minimize program costs while maximizing benefits among those with the greatest need or market opportunity. Many international development organizations strategically target clients based on geographic location (e.g., community, region, country) or socio-economic indicators, such as the World Bank’s “$1 a day” poverty line. Drawing on literature from several sectors, this brief presents additional methods of beneficiary targeting that international development organizations might consider. We find that beneficiary targeting/segmentation has the potential to make organizational and program efforts more equitable and efficient. With limited resources, smaller organizations have tended to use single robust indicators or simple heuristics, whereas agribusinesses and private sector firms have used more data-intensive marketing tools to position their products. Technological innovation and better access to data have made targeting more prevalent and potentially more affordable in agricultural development. However, creating valid and reliable target segments remains the most significant challenge.
Ecosystem services are the benefits people obtain from ecosystems, such as provisioning of fresh water, food, feed, fiber, biodiversity, energy, and nutrient cycling. Agricultural production can substantially affect the functioning of ecosystems, both positively and negatively. The purpose of this report is to provide an overview of the impacts of agricultural technologies and practices on ecosystem services such as soil fertility, water, biodiversity, air, and climate. The report describes the environmental impacts of different aspects of intensive cropping practices and of inputs associated with intensification. We further explore these impacts by examining intensive rice systems and industrial crop processing. Although this report focuses on the impacts of agricultural practices on the environment, many of the practices also have implications for plant, animal, and human health. Farmers and others who come in contact with air, water, and soils polluted by chemical fertilizers and pesticides may face negative health consequences, for instance. By impacting components of the ecosystem, these practices affect the health of plants and animals living within the ecosystem. We find that the unintended environmental consequences of intensive agricultural practices and inputs are varied and potentially severe. In some cases, sustaining or increasing agricultural productivity depends upon reducing impacts to the environment, such as maintaining productive soils by avoiding salinization from irrigation water. However, in other cases, eliminating negative environmental impacts may involve unacceptable trade-offs with food provision or other development goals. Determining the appropriate balance of costs and benefits from intensive agricultural practices is a location-specific exercise requiring knowledge of natural, economic, and social conditions.
In recent years, product supply chains for agricultural goods have become increasingly globalized. As a result, greater numbers of smallholder farmers in South Asia (SA) and Sub-Saharan Africa (SSA) participate in global supply chains, many of them through contract farming (CF). CF is an arrangement between a farmer and a processing or marketing firm for the production and supply of agricultural products, often at predetermined prices. This literature review finds empirical evidence that demonstrates that the economic and social benefits of CF for smallholder farmers are mixed. A number of studies suggest that CF may improve farmer productivity, reduce production risk and transaction costs, and increase farmer incomes. However, critics caution that CF may undermine farmers’ relative bargaining power and increase health, environmental, and financial risk through exposure to monopsonistic markets, weak contract environments, and unfamiliar agricultural technologies. There is consensus across the literature that CF has the best outcomes for farmers when farmers have more bargaining power to negotiate the terms of the contract. In reviewing the literature on CF, we find a number of challenges to comparing studies and evaluating outcomes across contracts. This literature review summarizes empirical findings and analyses regarding contract models and best practices to increase farmers’ bargaining power and decrease contract default.
Introducing technology that is designed to be physically appropriate and valuable to women farmers can increase yields and raise income. But gender issues for agricultural technology projects in Sub-Saharan Africa (SSA) are extremely complex. The EPAR series on Gender and Cropping in SSA offers examples of how these issues can affect crop production and adoption of agricultural technologies at each point in the crop cycle for eight crops (cassava, cotton, maize, millet, rice, sorghum, wheat, and yam). This executive summary highlights innovative opportunities for interventions that consider these dimensions of gender. We encourage readers to consult the crop specific briefs for more details. We find that involving both men and women in the development, testing, and dissemination of agricultural technology has been shown to be successful in helping both benefit. Nevertheless, a consistent finding throughout the Gender and Cropping in SSA series is that maximum benefits from technological innovations cannot be realized when upstream factors like education, power, and land tenure heavily influence outcomes. Addressing these more basic upstream causes of gender inequality may be even more important in helping households increase productivity and maximize the benefits of technological interventions.