Evans School Policy Analysis & Research Group (EPAR)

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.

Common aid allocation formulas incorporate measures of income per capita but not measures of poverty, likely based on the assumption that rising average incomes are associated with reduced poverty. If declining poverty is the outcome of interest, however, the case of Nigeria illustrates that such aid allocation formulas could lead to poorly targeted or inefficient aid disbursements. Using data from the World Bank and the Nigerian National Bureau of Statistics, we find that while the relationship between economic growth and poverty in Nigeria varies depending on the time period studied, overall from 1992-2009 Nigeria’s poverty rate has only declined by 6% despite a 70% increase in per capita gross domestic product (GDP). A review of the literature indicates that income inequality, the prominence of the oil sector, unemployment, corruption, and poor education and health in Nigeria may help to explain the pattern of high ongoing poverty rates in the country even in the presence of economic growth. Our analysis is limited by substantial gaps in the availability of quality data on measures of poverty and economic growth in Nigeria, an issue also raised in the literature we reviewed, but our findings support arguments that economic growth should not be assumed to lead to poverty reduction and that the relationship between these outcomes likely depends on contextual factors.

This brief provides a summary of background research for future aid-related EPAR projects. We first review prominent measures of aid, examining the definition and scope of Official Development Assistance (ODA) as well as common criticisms and alternatives to this measurement. We also provide a summary of current research on bilateral and multilateral aid allocation trends. The aid allocation literature broadly concludes that donor countries target aid based on both the needs of recipients and on strategic interests, but that aid allocation criteria differ by donor and by type of aid. Finally, we summarize current aid effectiveness literature and key challenges in exploring the impact of aid. A number of challenges in determining the effectiveness of aid were common in the literature, including the micro-macro paradox, difficulties in identifying causal mechanisms and direction of causality, and data limitations.

Maize has expanded through the 20th and into the 21st century to become the principle staple food crop produced and consumed by smallholder farm households in Sub-Saharan Africa (SSA), and maize production has also expanded in South Asia (SA) farming systems. In this brief we examine the environmental constraints to, and impacts of, smallholder maize production systems in SSA and SA, noting where findings apply to only one of these regions. We highlight crop-environment interactions at three stages of the maize value chain: pre-production (e.g., land clearing), production (e.g., fertilizer, water, and other input use), and post-production (e.g., waste disposal and crop storage). At each stage we emphasize environmental constraints on maize production (such as poor soil quality, water scarcity, or crop pests) and also environmental impacts of maize production (such as soil erosion, water depletion, or chemical contamination). We then highlight best or good practices for overcoming environmental constraints and minimizing environmental impacts in smallholder maize production systems. Evidence on environmental constraints and impacts in smallholder maize production is uneven. Many environmental concerns such as biodiversity loss are commonly demonstrated more broadly for the agroecology or farming systems in which maize is grown, rather than specifically for the maize crop. And more research is available on the environmental impacts of agrochemical-based intensive cereal farming in Asia (where high-input maize is a common component) than on the low-input subsistence-scale maize cultivation more typical of SSA. Decisive constraint and impact estimates are further complicated by the fact that many crop-environment interactions in maize and other crops are a matter of both cause and effect (e.g., poor soils decrease maize yields, while repeated maize harvests degrade soils). Fully understanding maize-environment interactions thus requires recognizing instances where shortterm adaptations to environmental constraints might be exacerbating other medium- or long-term environmental problems. Conclusions on the strength of published findings on crop-environment interactions in maize systems further depend on one’s weighting of economic versus ecological perspectives, physical science versus social science, academic versus grey literature, and quantity versus quality of methods and findings.