Evans School Policy Analysis & Research Group (EPAR)

The purpose of this analysis is to provide a measure of marketable surplus of maize in Tanzania. We proxy marketable surplus with national-level estimates of total maize sold, presumably the surplus for maize producing and consuming households. We also provide national level estimates of total maize produced and estimate “average prices” for Tanzania which allows this quantity to be expressed as an estimate of the value of marketable surplus. The analysis uses the Tanzanian National Panel Survey (TNPS) LSMS – ISA which is a nationally representative panel survey, for the years 2008/2009 and 2010/2011. A spreadsheet provides our estimates for different subsets of the sample and using different approaches to data cleaning and weighting. The total number of households for Tanzania was estimated with linear extrapolation based on the Tanzanian National Bureau of Statistics for the years 2002 and 2012. The weighted proportions of maize-producing and maize-selling households were multiplied to the national estimate of total households. This estimate of total Tanzanian maize-selling and maize-producing households was then multiplied by the average amount sold and by the average amount produced respectively to obtain national level estimates of total maize sold and total maize produced in 2009 and 2011.

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. 

Without availability and access to a variety of foods, populations in the developing world are suffering from deficiencies in iron, zinc, iodine, vitamin A, and other micronutrients in addition to deficiencies in energy and protein. Supplementation and fortification programs have demonstrated effectiveness, but there is an increasing interest in potentially more sustainable solutions via agricultural interventions. The review examines the literature regarding agricultural interventions and pathways to diet diversification and whether desired nutritional outcomes are achieved.  We find a strong sentiment that agricultural interventions can improve dietary diversity, and that dietary diversity can improve nutrition and related health outcomes. The programs with demonstrated ability to improve nutrition outcomes are most often cross-cutting interventions, borrowing from the agriculture, nutrition, and public health traditions. While these multi-platform programs can be costly to evaluate and difficult to implement, the evidence supports their potential to create sustainable quality-of-life improvements in target regions. The pathways by which agricultural interventions achieve impact are not fully clear, however. The greatest knowledge gaps are directly related to the lack of integration between program design and evaluation. Many evaluations are based on small sample sizes, lack control groups or baseline data, are subject to selection bias, or face other challenges to rigorous statistical analysis. 

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.