Types of Research
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
- how much countries are borrowing from each institution. and
- 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.
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
This document is an initial scoping of the theory and evidence linking digital services to women’s rural-to-urban migration. The document contains (1) a survey of the literature on digital financial services to discern how often this body of literature considers gender-disaggregated impacts on migration, (2) a detailed review of 13 hypotheses regarding the effects of digital services on women’s migration to cities, and (3) an illustrative overview of rural-urban migration patterns and digital technology usage in two East African countries (Ethiopia and Tanzania).
This report reviews and summarizes the existing evidence on the impact of access to financial services/products on measures of production, income and wealth, consumption and food security, and resilience for smallholder farmers and other rural customers and their households in Sub-Saharan Africa. This study covers four main types of financial products/services: 1) credit; 2) savings; 3) insurance; 4) transactional products. We also review the very limited evidence on the effectiveness of bundling these products/services together and of combining them with other offerings such as trainings or support for access to markets, and of providing them via digital channels. We note when financial products/services have been specifically designed to serve the needs of rural customers or smallholder farmers, since the needs of these groups are often very different from those of other stakeholders.
Common estimates of agricultural productivity rely upon crude measures of crop yield, typically defined as the weight harvested of a crop divided by the area harvested. But this common yield measure poorly reflects performance among farm systems combining multiple crops in one area (e.g., intercropping), and also ignores the possibility that farmers might lose crop area between planting and harvest (e.g., partial crop failure). Drawing on detailed plot-level data from Tanzania’s National Panel Survey, our research contrasts measures of smallholder productivity using production per hectare harvested and production per hectare planted.
An initial analysis (Research Brief - Rice Productivity Measurement) looking at rice production finds that yield by area planted differs significantly from yield by area harvested, particularly for smaller farms and female-headed households. OLS regression further reveals different demographic and management-related drivers of variability in yield gains – and thus different implications for policy and development interventions – depending on the yield measurement used. Findings suggest a need to better specify “yield” to more effectively guide agricultural development efforts.
This report provides a summary of findings from six Financial Inclusion Insights (FII) data analysis reports conducted by various agencies for the Bill & Melinda Gates Foundation (BMGF). These reports investigate barriers to financial inclusion and use of digital financial services (DFS) in Bangladesh, India, Kenya, Nigeria, Pakistan, Tanzania, and Uganda. We compile comparable gender-specific statistics, summarize the authors’ findings to determine commonalities and differences across countries, and highlight gender-specific conclusions and recommendations provided in the studies.
This brief reviews the evidence of realized yield gains by smallholder farmers attributable to the use of high-quality seed and/or improved seed varieties. Our analysis suggests that in most cases, use of improved varieties and/or quality seed is associated with modest yield increases. In the sample of 395 trials reviewed, positive yield changes accompanied the use of improved variety or quality seed, on average, in 10 out of 12 crops, with rice and cassava as the two exceptions.
Cassava production is prone to many constraints throughout the production cycle, including biotic, abiotic, and management constraints. This brief reviews the literature on the production impacts of two key cassava stressors: cassava bacterial blight (CBB) and postharvest physiological deterioration (PPD). We summarize available estimates of the frequency and magnitude of these constraints relative to other drivers of cassava production losses that affect smallholder farmers in Sub-Saharan Africa (SSA), review the control strategies proposed in the literature, report on the views of several experts in the field, and identify research gaps where relatively little appears to be known about CBB or PPD yield impacts or best practices for CBB or PPD management.