Geography

Dataset

EPAR TECHNICAL REPORT #411
Publication Date: 09/09/2022
Type: Research Brief
Abstract

Climate change is predicted to have increasingly dire effects on the largely rainfed agriculture of sub-Saharan agriculture, a livelihood that also contributes to climate change. Within this context, multilateral funding institutions are increasingly funding projects devoted to the adaptation to or mitigation of climate change. Data from the Organisation for Economic Development (OECD) provide an overview of climate-related project data, but the intersection of climate-related projects and projects intended to develop rural and agricultural economies is less explored. This paper focuses on climate-related projects in sub-Saharan Africa in the context of rural and agricultural project funding. We use a custom dataset from three separate multilaterals (the World Bank, African Development Bank, and International Fund for Agricultural Development) to answer the following research questions:

  1. What proportion of agriculture-related lending across the three multilaterals of interest has a climate component?
  2. Which countries are borrowing most for climate-related agricultural projects? Is the amount of borrowing correlated with a country’s climate risk?

 

Of all financing projects in our dataset (N = 1,846), we identified 203 as being climate-related (11%) and 505 as being related to rural agricultural economies (27%). Of the $26.5 billion annualized project funding, rural and agricultural financing accounts for $6.5 billion (24.6%) while climate projects receive $1.97 billion (7.4%). The World Bank funds approximately half of all agriculture projects in the dataset, with the AfDB funding just under 30% and IFAD just over 20%.

Annual average borrowing amounts from multilaterals for climate-related rural/agricultural economies projects varies widely across sub-Saharan Africa. The major borrowers include Ethiopia ($150 million), Nigeria ($105 million), and Kenya ($102 million). The proportion of multilateral borrowing for climate-related projects among all rural agricultural borrowing also varies substantially across sub-Saharan Africa; the Seychelles and Eswatini devote the largest proportions of rural agricultural borrowing toward climate work (100% and 69.8%, respectively). Fourteen SSA countries devote between 15% and 30% of rural agricultural borrowing to climate-related projects and fifteen have not received any multilateral financing for climate-related rural/agricultural economies projects.

We do not find a statistically significant relationship between a country’s Climate Risk Index and the proportion of annual rural/agricultural economies borrowing focused on climate.

 

Suggested Citation:

Financing for Climate Change in Africa: A View of Sovereign Borrowing in Agriculture from Multilateral Funding Institutions . EPAR Technical Report #411 (2022). Evans School of Public Policy & Governance, University of Washington. Retrieved <Day Month Year> from https://epar.evans.uw.edu/research

EPAR TECHNICAL REPORT #424
Publication Date: 09/01/2022
Type: Research Brief
Abstract

Key Takeaways

  • A survey of poverty indicators surfaced 139 candidates, of which 36 were ultimately selected for inclusion in the study based on indicator construction, use, and timeliness.

  • The selected 36 poverty indicators relied primarily on 26 data sources, mainly household surveys and administrative government data.

  • Most indicators relied on household survey data and used multidimensional indices to comprehensively measure poverty, aside from poverty line and poverty gap measures which relied exclusively on income and consumption.

  • Indicators or indicator components were typically based on quantitative estimates of income or consumption, although an increasing number of measurements are instead classifying households according to deprivation of assets, food, or access to services and basic infrastructure.

  • Overall, critics find that an emphasis on poverty line measurements has led to an incomplete understanding of poverty’s prevalence and trends over the last several decades (UN Special Rapporteur, 2020).

  • No single indicator dominates on considerations of reliability, dimensions, depth or intensity, comparability, etc., but rather each measure involves tradeoffs.

  • If the goal is to increase the utility of commonly used indicators, including those considering multiple dimensions of poverty, then investments focused on expanding the coverage, frequency, or scope of nationally representative household surveys is a necessary first step.

  • Making cross-country comparisons using any poverty indicator runs the risk of using a common metric based on different data sources and collected in different years that may not fully reflect a household’s welfare. Indices which include multiple subcomponents may be more holistic, but even less reliable as the number of components requiring data increases.

 

Suggested citation:

Landscape Review of Poverty Measures. EPAR Technical Report #424 (2022). Evans School of Public Policy & Governance, University of Washington. Retrieved <Day Month Year> from https://epar.evans.uw.edu/research

EPAR TECHNICAL REPORT #411
Publication Date: 05/24/2021
Type: Data Analysis
Abstract

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

Code
EPAR Research Brief #143
Publication Date: 04/18/2011
Type: Literature Review
Abstract

Asset-Based Community Development (ABCD) is a development framework which focuses on the capacities, skills and social resources of people and their communities, rather than initially focusing on the needs, deficiencies, constraints and problems of a community.1 This document contains three sections. The first section summarizes several papers which either (1) apply ABCD or similar asset-focused development frameworks in a rural/agricultural context and to development in Sub-Saharan Africa, or (2) provide general guidance on the implementation of ABCD approaches to development. The second section provides more detail on how Oxfam and the Coady International Institute have applied ABCD in Ethiopian communities.
Finally, in order to provide an example of how ABCD might be applied to a Foundation project, the third section briefly notes how an ABCD strategy might differ from the Foundation’s proposed constraints-based Bihar strategy.

EPAR Technical Report #131
Publication Date: 03/01/2011
Type: Literature Review
Abstract

This brief reviews the literature and empirical evidence on waste extraction and treatment in the developing world.  The brief assesses the quantity and quality of research supporting key components of program theory related to the extraction of sludge from on-site sanitation facilities and pre-disposal transport. In general, we find few empirical studies that directly evaluate the assertions of the program theory. Most of the evidence in the literature that addresses the target components of program theory is based upon case studies or general observational and experiential assertions by sanitation experts. Where appropriate, we have identified evidence in the literature according to whether case studies or informal observations formed the basis of the conclusion. 

EPAR Technical Report #130
Publication Date: 01/29/2011
Type: Literature Review
Abstract

The purpose of this literature review is to provide qualitative and quantitative examples of technologies, constraints and incentives for efficient waste treatment and reuse in Sub-Saharan Africa and Southeast Asia.  We present relevant case studies and expert observations and experiences on the nutrient content in urine and feces, contaminants frequently found in untreated sludge and wastewater, waste treatment technologies that may be relevant for low-income countries, risks associated with waste reuse, benefits to resource recovery in agriculture. We further discuss reasons for waste treatment failures, including urbanization, observations on challenges with market-driven reuse in less developed countries, and examples of net-positive energy facilities in Europe and the United States. Much of the evidence presented in the literature relates to wastewater treatment processes or the sludge produced from wastewater treatment as opposed to untreated fecal sludge.  However, examples of risks, failures, and opportunities for raw sludge treatment and reuse are discussed when available.  In some cases, empirical evidence or case studies were not available for developing countries and alternatives are presented.  Overall we found the empirical evidence on waste treatment and reuse in developing countries is quite thin. 

EPAR Technical Report #121
Publication Date: 01/10/2011
Type: Literature Review
Abstract

The purpose of this literature review is to identify the linkages between increases in agricultural productivity and poverty reduction. The relevant literature includes economic theory and evidence from applied growth and multiplier models as well as micro-level studies evaluating the impact of specific productivity increases on local poverty outcomes. We find that cross-country and micro-level empirical studies provide general support for the theories of a positive relationship between growth in agricultural productivity and poverty alleviation, regardless of the measures of productivity and poverty that are used. The evidence also suggests multiple pathways through which increases in agricultural productivity can reduce poverty, including real income changes, employment generation, rural non-farm multiplier effects, and food prices effects. However, we find that barriers to technology adoption, initial asset endowments, and constraints to market access may all inhibit the ability of the poorest to participate in the gains from agricultural productivity growth.