Types of Research
The following brief details the various policies surrounding donor agency salary supplementation (or top-up) to individuals employed in project countries. The goal of this research was to understand the landscape of different agency’s policies regarding salary top-ups for government experts and scientists advising on donor projects. However, information on this specific scenario was limited. The brief covers a range of scenarios in which donor agencies may pay salary top-ups to local, in-country individuals and aims to draw out a number of hypothesized advantages and disadvantages associated with the practice of donor salary supplementation.
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.
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.
This literature review provides a summary of the risks that potentially limit private sector agribusiness investment in Sub-Saharan Africa (SSA), and some responses to those risks. The report reviews risks that limit private sector investment and interventions used to mitigate risk to agricultural investment including government policy, international financial institutions, philanthropic efforts and other private initiatives. Risk is defined as a potential negative impact to assets, investments, or profitability of investments in the agricultural industry that may arise from some present process or future event. There is currently limited information examining how particular risk factors influence private-sector agribusiness investment in the region. However, the information that is available suggests that economic and political instability are among the most significant risks to agribusiness investors in SSA. Further, the literature notes that agricultural risks in SSA are particularly pronounced due to environmental risks that contribute to unreliable cash flows and uncertain profitability. We find that these risk factors are compounded by a lack of data and information for investors to use in assessing and pricing risks appropriately.
This research brief reports on full time equivalent (fte) positions devoted to research and development of major food and cash crops in Sub-Saharan Africa (SSA). Data on fte by country and crop were collected from individual Agricultural Science and Technology Indicator (ASTI) country briefs. ASTI data are obtained from unpublished surveys conducted by CGIAR centers. Our report includes 23 countries in SSA.