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Aid Transparency Data Camp-Students for Development

Soren Gigler's picture

How can we better track aid flows? Which donor is working where in the DRC, Afghanistan, CAR, Peru  or Bolivia? How can we better analyze the spatial distribution of aid flows within countries?  How can we use mobile telephony to enhance the social accountability of international aid programs?  These were some of the questions 45 students from the College of William & Mary, Georgetown University and George Washington addressed during the aid transparency data camp which we organized jointly with the Aiddata Initiative last Monday, March 8.

Why does is matter that we have better overview of aid flows at the country and local level?   Bolivia for instance is not only one of the poorest countries in Latin America it also has one of the highest levels of inequality—In terms of inequality and poverty there is a clear and direct link between geography and poverty. While there has been important progress made in terms of reducing poverty and improving people’s living conditions at the national level, pockets of extreme poverty persist. For instance while at the national level infant mortality rates were reduced from 67 per 1,000 live births to 48 in the last decade, in Potosi- one of the poorest and most indigenous departments, still today more than 80 out of 1000 children die in the first year of their lives. 

“As a result of their historic exclusion, indigenous peoples continue to have low levels of human capital, limited access to productive land, basic services, and financial markets, and poor infrastructure,” explains Emmanuel Skoufias, World Bank lead economist and the co-author of recent World Bank study on Economic Opportunities for Indigenous Peoples in Latin America.

At the same time, Bolivia remains highly dependent on aid flows and has received $62 per capita aid flows in 2006. The question which come us is to what extent is this aid reaching the poorest of the poor?

Back view of Bartolinas Sisas

During the data camp, the participants split into four groups to analyze the aid data and worked together to geo-code the geographic location of all WB-funded projects in Afghanistan, Bolivia, the CAR, DRC and Peru.  As Michael from Georgetown explained: 

”The workshop helped us to better understand how to analyze the WB project data, we really had the chance to delve deep and to learn where the Bank is targeting is projects within Peru. It is very exciting to be involved in this initiative since we have seen that we can make a contribution towards making the data more accessible and openly available to a larger audience.”

Data worked on during the camp will form part of the dataset used in the upcoming 'Aid Transparency - Data Camp' taking place on Friday, March 12. Full reports from the camp will be posted here.


Soren, the aid transparency data camp you report on is, no question, making great progress in mapping visual data that can improve operations -- from both the host countries' and donors' perspectives. As this process continues to take hold, I think it will be desirable to map not only "hard" data, like roads and poverty, but "soft" data, like social organization, especially at the community level. One of the criticisms of implementation of the Paris Declaration and Accra Action Accords aid reforms is that the new emphasis on results-based management, while desirable, may sometimes be overdone. If the new data visualization focuses only on gaps, but ignores sometimes hard-to-pinpoint strengths (i.e. in those "soft" areas, especially locally), then aid might end up going in yet another less-than-satisfactory direction. Developing countries and donors alike need to see both the gaps and the strengths to make good decisions at the operations level.

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