Evans School Policy Analysis & Research Group (EPAR)

In this dataset, we compile current project data from three major international financial institutions (or IFIs) - the World Bank, African Development Bank, and the International Fund for Agricultural Development - to understand

1. how much countries are borrowing from each institution. and
2. how much of that funding is devoted to small scale producer agriculture.

We begin by gathering publicly accessible data through downloads and webscraping Python and R scripts. These data are then imported into the statistical software program, Stata, for cleaning and export to Excel for analysis. This dataset contains rich information about current projects (active, in implementation, or recently approved), such as project title, project description, borrowing ministry, commitment amount, and sector. We then code relevant projects into two categories: On Farm (projects pertaining directly to small scale producer agriculture) and Rural/Agricultural Economies (inclusive of On Farm, but broader to include projects that impact community livelihoods and wellbeing). Finally, we annualize and aggregate these coded projects by IFI and then by country for analysis. Bilateral funding, government expenditures on agriculture, and development indicators are also included as supporting data to add context to a country's progress towards agricultural transformation.

The primary utility of this dataset is having all projects collected in a single spreadsheet where it is possible to search by key terms (e.g. commodity, market, financial, value chain) for lending by IFI and country, and to get some level of project detail.  We have categorized projects by lending category (e.g. irrigation, livestock, agricultural development, research/extention/training) to aggregate across IFI so that the total funding for any country is easier to find. For example, Ethiopia and Nigeria receive the most total lending from these IFIs (though not on a per capita basis), with each country receiving more than $3 billion per year on average. Ethiopia receives the most lending devoted to On Farm projects, roughly $585 million per year.  Overall, these data provide a snapshot of the magnitude and direction of these IFI's lending over the past several years to sub-Saharan Africa. 

Suggested Citation: 

Figone, K., Porton, A., Kiel, S., Hariri, B., Kaminsky, M., Alia, D., Anderson, C.L., and Trindade, F. (2021). Summary of Three International Financial Institution (IFI) Investments in Sub-Saharan Africa. EPAR Technical Report #411. Evans School of Public Policy & Governance, University of Washington. Retrieved <Day Month Year> from https://epar.evans.uw.edu/research/tracking-investment-landscape-summary-three-international-financial-institutions-ifis

The FAO defines a farming system as “a population of individual farm systems that have broadly similar resource bases, enterprise patterns, household livelihoods and constraints, and for which similar development strategies and interventions would be appropriate. Depending on the scale of the analysis, a farming system can encompass a few dozen or many millions of households.” We use the farming systems as defined by the Food and Agriculture Organization (FAO) for Sub-Saharan Africa. The FAO identifies eight main farming systems in Tanzania 1) maize mixed, 2) root crop, 3) coastal artisanal fishing, 4) highland perennial, 5) agro-pastoral millet/sorghum, 6) tree crop, 7) highland temperate mixed, and 8) pastoral. This analysis uses data from the Tanzanian National Panel Survey (TZNPS) LSMS – ISA to provide a comparison of farming systems throughout Tanzania. The TZNPS is a nationally-representative panel survey that includes households from seven of the eight FAO farming systems with only the smallest farming system, pastoral, lacking any representation.

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.

This research brief provides an overview of the banana and plantain value chains in West Africa. Because of the greater production and consumption of plantains than bananas in the region, the brief focuses on plantains and concentrates on the major plantain-producing countries of Ghana, Cameroon, and Nigeria. The brief is divided into the following sections: Key Statistics (trends in banana and plantain production, consumption, and trade since 1990), Production, Post-Harvest Practices and Challenges, Marketing Systems, and Importance (including household consumption and nutrition). West Africa is one of the major plantain-producing regions of the world, accounting for approximately 32% of worldwide production. Plantains are an important staple crop in the region with a high nutritional content, variety of preparation methods, and a production cycle that is less labor-intensive than many other crops. In addition to plantains, bananas are also grown in West Africa, but they account for only 2.3% of worldwide production. Bananas are more likely than plantains to be grown for export rather than local consumption. Major constraints to banana and plantain production include pests and disease, short shelf life, and damage during transportation.