Donor Coordination in Kenya and Mozambique
Geo-referencing development projects is one very promising method that could facilitate greater coordination and dialogue between policymakers, development practitioners, researchers, NGOs, recipient governments, and citizens.
Responding to long-held concerns about uncoordinated donor behavior, the Paris Declaration of 2005 made harmonization one of its five pillars, pledging to work towards “eliminating duplication of efforts and rationalizing donor activities to make them as cost-effective as possible.”
Among the problems of uncoordinated action are elevated transaction costs as recipient governments struggle to comply with variegated donor rules and procedures (Knack and Rahman 2007) and decreased donor specialization as “all donors seem to want to give to all sectors in all countries” (Easterly 2007).
All of the attention given to coordination problems begs the questions: how much do donors coordinate their activities? And is coordination effectively targeting needs within a country – both spatially (aid to villages or provinces) and sectorally (aid for different purposes)? Recent work by the World Bank – AidData partnership (Mapping for Results Initiative) sheds new light on the topic.
Using new geo-referenced aid data, we considered the spatial and sectoral coordination of all of the currently active projects of two donors – The World Bank and the African Development Bank – within Kenya and Mozambique. An AidData query places the World Bank and the AfDB as the first and twenty-third highest active donors to Kenya and Mozambique. Because of their influence, analyzing the funding patterns of these two donors offers a sense of where a large proportion of the funding to Kenya and Mozambique is going. (It also calls attention to the need to mainstream geo-referencing for the other approximately 50 active donors.)
World Bank and AfDB aid flows to Kenya demonstrate a tremendous concentration of aid from both donors in the Mombassa-Nairobi-Lake Victoria corridor. This is not entirely surprising, as these are the main population centers of Kenya, but this corridor is also comparatively much better off than the more arid North and East, which receives virtually no aid from either donor. Neither donor appears to be coordinating efforts nor effectively targeting the neediest areas of the country.
World Bank and AfDB aid flows to Kenya
The situation in Mozambique paints a different picture: AfDB projects are primarily directed to the northern parts of the country whereas World Bank projects are clustered near the capital city, Maputo. As in Kenya, however, there appear to be manifold financing gaps in the poorest parts of Mozambique, especially in the northwest provinces - Niassa and Tete - and the provinces just north of Maputo – Gaza and Inhambane. Geographic coordination in Mozambique is encouraging, yet the areas of greatest need appear to be neglected still.
Using the same active World Bank and AfDB projects, we then examined sectoral coordination. In Kenya, we find a high degree of sectoral specialization between the two donors. The AfDB is largely focused on central government budget support, allocating 58% of its spending towards this sector. By contrast, the World Bank’s emphasis has been Transportation (29%) and Agriculture (17%).
While the production sectors, such as transportation, power, and agriculture, receive a great deal of aid from both donors, sectors targeting human capital, such as education, health, and social services, are relatively neglected by both donors.
Sectoral coordination in Mozambique is quite different from Kenya: the Power and Transportation sectors are targeted heavily by both the World Bank and the AfDB. But beyond these two sectors, the World Bank and the AfDB spend on quite different purposes as shown below:
In Kenya, uncoordinated donor specialization may neglect particular sectors and geographic regions as the World Bank and the AfDB seem to target the same geographic area and the same sectors. In Mozambique, the donors specialize in different sectors and different areas. By cross referencing this finding with the distribution of sectorally-specific indicators of need, we could assess whether the different types of aid received by northern and southern Mozambique are tailored to the specific needs of those areas. It is possible that the geographic variation in aid portfolios is matched to the geographic variation in need. However, without more complete analysis, including a wider group of geo-coded donors, it is difficult to draw strong conclusions about the significance of the revealed patterns of sectoral and spatial coordination. Areas and sectors that appear neglected by the World Bank and AfDB might be covered by other donors. We would love the opportunity to test this proposition, but that would require that more donors geo-reference their own projects or provide access to their project documents so that we could geo-reference their projects as we have done for the World Bank and AfDB.
Geo-referencing development projects is one very promising method that could facilitate greater coordination and dialogue between policymakers and development practitioners, as well as researchers, NGOs, recipient governments, and citizens. As geo-referenced data become more common, donors and other interested parties (like us) can use the data to find and publicize areas and sectors that are not receiving an amount of aid that is proportional to need (measured in various objective ways). Such visualizations do not provide clear answers about where aid should be allocated, but they raise important questions with striking clarity and will encourage donors and recipient governments to explain allocation patterns to beneficiaries and taxpayers. We think this will improve the prospect of aid dollars arriving where they are needed most.
The following is a post by two of our research assistants, Alena Stern (William and Mary '12) and Josh Powell (BYU Public Policy Graduate School '11).
Alena Stern managed AidData's USAID Higher Educations Solution Network (HESN) award from 2013-2017.
The views expressed here are those of the authors alone, and do not necessarily reflect the views of the institutions to which the authors belong.