The First Tranche

Welcome to the First Tranche, the AidData blog--a forum for analysis and discussion of information about development finance, and how it can be used to improve development practice and research. The First Tranche publishes independent views and analysis from a variety of bloggers who are interested in aid transparency, aid effectiveness, and better/more accessible aid information.
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The First Tranche | a blog by the staff of AidData

Monday, August 27, 2012


Bad Behavior, Good Politics, and Ideas: Making Sense of Theories of Aid Allocation

This is a continuation of the First Tranche’s look at the the effectiveness of aid allocation theories. See here for related posts on the subject.


Why do some countries give more aid than others? What determines how much aid a country receives, and why? What makes a ‘good donor’?  The existing literature offers an array of answers to these questions. Scholars have refined their measurements, identified new predictor variables, and employed more sophisticated econometric procedures. Yet, the aid allocation literature remains fragmented and largely inaccessible to many policymakers and practitioners.

Two books published in the past year could change that. Both books offer compelling and complementary arguments and insights about the way aid allocation is determined. In The Dictator’s Handbook, Bruce Bueno de Mesquita and Alastair Smith argue that donor partners give aid to benefit their own people by "purchasing" policy concessions from other countries. They present "coalition size," defined as the number of people whose support is required for a given regime to stay in power, as a variable to predict aid allocation. To stay in power, large coalitions (such as democracies) must "appease" a broad base of people, while smaller coalitions (such as autocracies) must only appease the ruling elite. 
The amount of aid awarded to a country partners is therefore determined by: 
          1.) how much money is needed by the country's chief executive to keep 
                his or her coalition happy (in spite of the policy concession), and 
          2.) how much money the donor partner is willing to pay for that policy concession. 

Bueno de Mesquita and Smith argue that it is cheaper for donor partners to buy their policy concessions from countries with smaller coalitions—even if the cost of the concession is high, there are fewer members of the coalition to pay off. Thus, even democratic countries give aid to autocratic regimes – under the right circumstances.

Meanwhile, in Ideas, Interests and Foreign Aid, Maurits van der Veen proposes that global patterns of aid allocation only emerge within the context of the political elite’s “frames” for conceptualizing foreign aid. For example, if the political elite in a donor country views aid as a means for improving the well-being of country partners (i.e. the humanitarianism frame is prominent), then aid provision will increase as the donor partner country's GDP grows. If development assistance is viewed as a mechanism for preserving a donor partner country’s international reputation (i.e. the reputation frame is prominent), then a strengthening of the “status quo” aid allocation pattern will increase the provision of aid.



While both books attempt to explain patterns of aid allocation, they come from two different schools of thought in the international relations (IR) discipline: rationalism (Mesquita and Smith) and constructivism (van der Veen). Some argue that these two approaches are fundamentally irreconcilable. However, others insist that the battle between the two "isms" is ultimately a false choice

Having read both books, I now see these two analytic paradigms as strongly complementary. Ideas, Interests and Foreign Aid asks how ideas about aid allocation are formed, and studies how to go about measuring those ideas. Dictator’s Handbook asks how we can predict the way donors will make decisions regarding development assistance, given the presence of varied perceptions of aid. Together, these books answer both parts of what Jeffery Legro calls the ‘two step’ in IR research: “first we describe preferences then we describe actions”.

Of course, areas of disagreement exist. Bueno de Mesquita and Smith assure us that we shouldn’t blame democratic governments for their seemingly self-interested decisions. Rather, we should blame ourselves: any change in aid allocation must begin with a major shift in voters’ attitudes towards aid and accountability. Van der Veen, however, attributes more agency to states in crafting aid priorities, arguing that “governments are far from passive participants in the aid discourse,” and political elites sometimes “expended considerable effort” bringing public opinion in line with their own views.  

However, here too I see opportunities for cross-fertilization. Maybe a change in aid allocation does have to begin with a change in voter attitudes, but how are voter attitudes formed in the first place? Maybe political elites do have agency in defining aid policy preferences, but how can this agency be understood as a function of leaders’ desire to stay in power, given the preferences of their constituents? 

In short, these two books significantly improve our understanding of aid allocation. More striking, though, is the joint value they offer without any direct collaboration. The potential for reconciliation between constructivist and rationalist scholars bodes well for the future of aid allocation research, and IR research more generally.


Chrissy Sherman (’14) is an AidData Intern at the College of William & Mary. 




Wednesday, August 22, 2012


Dirty Work: The Environmental Impact of DAC and Non-DAC Donor Projects

This is a continuation of the First Tranche’s look at the environmental impacts of development assistance. See here and here for related posts on the subject.


The rise of non-DAC bilateral donors (NDBs) has forced development policy experts to rethink assumptions about the transparency and impact of development finance. The conventional wisdom [pdf] is that NDBs seldom condition their assistance on recipient countries meeting economic, environmental, and political standards, which undermines multilateral commitments made by members of the OECD’s Development Assistance Committee (DAC). However, this assumption rests largely on case study evidence and impressionistic accounts.

The public release of the AidData Environmental Impact CodeDataset makes it possible to examine whether NDBs have “dirtier” grant and loan portfolios than DAC bilateral donors. “Dirty” projects, such as projects that support resource extraction or electricity distribution, can cause environmental harm over the short, medium, or long-term. With a sample extending from 1992 to 2008, the most recent year in the PLAID 1.9 dataset, the graph below shows the proportion of donor commitments to each environmental impact code category.



 The large chunk of red in the NDB graph (Figure B) indicates that, between 1992 and 2008, 45-80% of the NDBs’ annual development finance flowed to dirty projects. The DAC donors (Figure A) provided far less funding to dirty projects, at 11-43% annually. On the environmentally beneficial side, NDB and DAC donors have similar average flows at 6.6% and 8.8% of their total portfolios, respectively. The other large discrepancy between the two groups occurs in the neutral category, comprising projects without any perceived environmental impact. During this timeframe, DAC donors contributed 70% of their financing per year to neutral projects, while NDBs committed about 30%.

Are the fears about NDBs’ relative disinterest in environmental protection substantiated by these numbers? In my view, it's too early to say. Consider these facts:
DAC donors as a whole provided approximately $61.7 billion a year in development finance,
          compared to the NDBs’ $1.05 billion. Therefore, even if NDB projects are “dirtier” on average,
          DAC donors contributed $200 billion more to “dirty” projects than NDBs from 1992 to 2008
Existing NDB aggregate statistics may be misleading. For example, NDBs make significant    
          contributions through in-kind technical assistance or cooperation (TA/TC) programs that are 
          difficult to monetize. Peter Kragelund [gated] cites a Brazilian official who estimates that its 
          Technical Cooperation among Developing Countries (TCDC) program may be worth ten times 
          its stated value because Brazil’s  implementation partners do not charge for TC. The PLAID 1.9 
          dataset also lacks information on the most significant and controversial of all the NDBs: China.
Donor countries that do not belong to the DAC are by no means an organized, coordinated, or 
          homogenous group: Poland, Brazil, and Saudi Arabia have distinct motives, behaviors, and 
          reporting mechanisms. Nor do they share a common definition of ODA with DAC (or other non-
          DAC) donors, quantitative comparisons of Non-DAC donors are inherently challenging. 
          Therefore, one must be cautious about drawing inferences about "Non-DAC" donor behavior.

In summary, the hard numbers offer some evidence that NDBs engage in “dirtier” projects than DAC donors, but we lack sufficient evidence to make any decisive claims about this issue.

The rise of Non-DAC donors also poses an important normative question: given that NDBs have become a major source of development finance, and developing countries have called for an increase in infrastructure and agricultural projects, should NDBs necessarily be deemed "dirtier" and faulted for providing demand-driven assistance? 


Steven Linett is a former AidData Senior Research Assistant at the College of William & Mary.



Friday, August 17, 2012


This week in aid, transparency and open development


Time published an article earlier this week on efforts in Uganda to Tracking Disease One Text at a Time. UNICEF's Innovation Team and the World Health Organization teamed up in Uganda to track the details of drug supplies and disease outbreak recorded by Ugandan health ministry workers using mobile phones. The Ureport group, which develops SMS-based communities of knowledge, also jumped on the project to help track health incidences, supplies, and access across the country. AidData previously worked with UNICEF Uganda and Ureport to run a randomized-control trial (RCT) in Uganda around what incentives citizens (Ureporters) to submit information on polling questions. The full paper on the results of the RCT is available on Zunia.


The Guardian's Tim Weber did a review its Activate Summit held over the summer. One of the major themes of the conference was that "technology is no panacea". Weber writes, however, that despite this realization, technology "offers huge opportunities: it can be a source of wealth and knowledge". One such example comes from Alex Torpey, the Mayor of South Orange in New Jersey, USA. wrote a piece in the Huffington Post on ways in which "open government" can move beyond just an idea or empty words into practical implementation. Alex points to open budget data, public document accessibility, and better communications as key to putting "open government" in place. He is cautious, however, to say that technology is the main driver of "open government", and that first and foremost it's about getting people involved. 


Open development sets out a new vision of what development means, how it comes about and what role the various partners play. This means new spaces for new actors, and new roles and responsibilities for actors who've been entrenched in the ways in which development was done for so long. The UN-APCICT launched its online communities of practice. The virtual space is meant to bring together and connect those wishing to learn about ICT4D with experts in the field. The rise of these new online knowledge sharing platforms is helping create dynamic communities around themes. For example, in Zimbabwe, the Development Reality Institute (begun by ICT4D specialist Verengai Mabika) with support from UN Volunteers and SIDAhas created a virtual school on climate change challenges and adaptation practices.


Featured Dataset: On the AidData Research Datasets page, visitors can find the new Climate Change and African Political Stability (CCAPS) program database on climate aid. This is the first ever look at where international assistance targeted at addressing the impacts of climate change are flowing within a country. In addition to downloading the data, users can go to the CCAPS Aid Dashboard and see if climate aid is going to areas of highest climate vulnerability within Malawi. CCAPS and AidData, partners in the climate coding and geocoding efforts, will be rolling out the methodology to track additional countries and donor agencies.



Thursday, August 16, 2012


New climate data and tools featured on CCAPS aid dashboard

The Strauss Center's Climate Change and African Political Stability (CCAPS) program and AidData have been working together for a while on mapping and visualizing aid to Africa. Now, an interactive aid dashboard makes the information easier to browse and interpret. The dashboard includes a map (using Esri’s ArcGIS software) as well as graphing tools that allow users to explore trends in aid allocation by donor, sector, and demographics across Africa. 

Among other information, the dashboard features the first-ever dataset tracking all climate aid activities in a single country. In a pilot study, CCAPS researchers applied their new "climate coding" methodology to all official development aid projects in Malawi's Aid Management Platform assessing each project activity for its relevance to climate change adaptation. The resulting database reveals how much of Malawi's current aid portfolio represents funding allocated specifically for climate-oriented development. It also reveals how much of Malawi's aid is not explicitly climate-related, comprised of development projects that could have varied degrees of positive or negative impacts on climate change adaptation. This new Malawi Climate-coded and Geocoded Aid Dataset can be searched and downloaded online or mapped on the aid dashboard.


"Our goal is to generate more timely, detailed, and useful information on climate finance to Africa to better understand where resources are being effectively mobilized to address the continent's vulnerability to climate change," said Dr. Catherine Weaver, Associate Professor at the LBJ School of Public Affairs and a lead researcher on the CCAPS program.

CCAPS researchers "climate coded" over 700 projects in Malawi and found that climate aid, narrowly defined, makes up just 1-2% of aid to Malawi. Norway, the World Bank, USAID, and the European Union are among the donors most involved in adaptation aid in Malawi. Japan and Ireland have several adaptation-related projects, yet their financial contributions are much smaller.

The new dataset opens the door for detailed comparative analysis of climate change adaptation programs and their effectiveness in targeting specific climate risks within a country. Through a collaboration between CCAPS, AidData, and the Government of Malawi, the data were also geocoded, allowing analysts to assess the aid allocation visually as well.

In addition, the aid dashboard includes African Development Bank projects continent-wide geocoded by AidData, and World Bank projects continent-wide geocoded through the World Bank-AidData Mapping for Results initiative.


"The CCAPS aid dashboard allows analysts to explore aid spending as big picture trends or local project information," said CCAPS program manager Ashley Moran. "Our aim is to provide these new data in a way that is as useful as possible to policymakers and researchers needing to ask very focused questions about aid investments and impacts."

The CCAPS research team plans to expand the climate-coding effort continent-wide for several large donors over the next year. The data will be updated on the CCAPS aid dashboard as they become available. 


Tuesday, August 14, 2012


How Eco-Friendly is Nigeria’s Foreign Aid Portfolio?

This is a continuation of the First Tranche’s look at the environmental impacts of development assistance. See here for related posts on the subject.



Two years ago, the Deepwater Horizon explosion turned a spotlight on lesser-known sites of environmental degradation caused by extractive industries. Many saw parallels to the last fifty years of oil leakage in the Niger Delta (also see here or here ).

We were curious how the costs of the two spills compared, so we examined the estimated crude oil spilled vis-à-vis the actual clean-up costs. The results indicated an alarming lack of clean-up funding provided to Nigeria by international donors, especially in light of the total amount of external funding spent on developing Nigeria’s oil and gas sectors.  Considering Nigeria’s role as one of the world's top ten oil exporters, it would appear that donors benefit from natural resource extraction in the Niger Delta without shouldering much of the environmental remediation burden.

Oil remains a contentious issue in Nigeria. A recent tanker explosion highlighted the fatal combination of poor infrastructure and a combustible natural resource. Last year, an independent report revealed that the damage from a 2008 Shell oil spill was 60 times greater than originally estimated. 

Our original questions remain mostly unanswered.
          1.) Is foreign aid to Nigeria mostly ignoring, worsening, or remediating the   
                  environmental damage caused by oil? 
          2.) How does Nigeria compare to other Sub-Saharan countries with similar levels of 
                  environmental vulnerability? 
A recently released environmental impact dataset, PLAID 1.9 with Environmental Codes, may shed light on some of these questions.

We isolated all Nigerian aid between 1973 and 2008, and collapsed the environmental categories into four types: “dirty”, “environmental”, “neutral”, and “unsure (not enough information)”. (Click here for data used in this report.)

Given that Nigeria agreed to a massive debt forgiveness deal with the Paris Club in 2005, we excluded neutral projects with “debt relief” purpose codes. (Between 2003 and 2007 alone, donors committed $16.7 billion in debt relief to Nigeria, a full 32% of all Nigerian aid since 1973.)



While the majority of incoming aid flows are environmentally neutral (e.g. health, education, civil society support), dirty aid (e.g. extractive industries, agriculture, livestock) accounts for a third of all Nigerian aid committed during this 35-year period.




When viewed over time, the environmental profile of international assistance to Nigeria seems to mirror the country’s tumultuous history. Following an annulled election in June 1993, the United States and other key donors imposed sanctions on the Nigerian military dictatorship and suspended most aid programs. After the country’s return to democracy, the international funding floodgates opened, resulting in a spike of environmentally neutral aid. 

However, the environmental composition of Nigerian aid is not unusual when compared to its peers in Sub-Saharan Africa. We averaged 2000-2008 environmental vulnerability scores in Sub-Saharan Africa, as reported by Yale’s Environmental Performance Index (EPI), and compared these averages with incoming aid flows since 1980. Of the dozen states with the lowest EPI scores in Africa, Nigeria has received the highest percentage  of environmentally friendly aid: 12.5%. Given Nigeria’s troubling record of oil spills, the high levels of aid for locally-oriented projects with explicitly environmental aims (9.25% of total) suggests much of this environmental (eco-friendly) aid is related to oil spill response.

Interestingly, there is a positive correlation between the proportion of “dirty” aid received and a recipient government's level of environmental performance. In the chart provided below, lower EPI scores represent lower levels of environmental policy performance. This pattern suggests that more environmentally risky funding goes to African states with policies and institutions that can handle such risk.




One would hope that “dirty” aid to Nigeria is being targeted to local governments with relatively high levels of administrative capacity and oversight. The World Bank’s “Mapping For Results” initiative shows substantial Bank funding for energy, mining, and industry projects in Nigeria’s oil-rich southern Delta regions. But this begs the question: how is such aid being distributed relative to the specific locations of oil fields, wells, and spills? 

This question cannot be answered without more transparency from the donors and oil corporations operating in Nigeria. The World Bank’s recent initiative to geocode active extractive industry sites as well as project locations in Ghana might serve as a good model. An online platform mapping Nigeria’s oil drilling sites and international aid activities, overlaid with sub-national indicators of government regulation and environmental risk, could lead to smarter targeting of environmentally impactful aid projects.



Kevin McCrory is a former AidData Research Assistant at the College of William & Mary. Brian O’Donnell is an AidData Project Manager at the College of William & Mary.




Friday, August 10, 2012


This week in aid and transparency



Global Integrity (member of the new OpenGov Hub, along with Development Gateway, FrontlineSMS and others) announced that they have published their data to the International Aid Transparency Initiative (IATI). As readers are familiar, IATI is a multi-stakeholder initiative meant to increase aid transparency by helping "implement the transparency commitments made at the Accra Agenda for Action". You can access Global Integrity's data directly in XML format from their website, or find it (along with all other data published to IATI) on the IATI Registry.

Linda Raftree of PLAN USA, who blogs at "Wait...What?", provided a great summary of the Tech Salon held earlier this week in NYC. The Salon focused on the use of new technologies for social monitoring and evaluation (M&E). As one participant said:


The next Tech Salon will take place August 30th, and will focus on the role of intermediaries in building capacity for new technologies for M&E.

Our partners, the Climate Change and African Political Stability (CCAPS) program, based at the University of Texas, just announced the release of the first-ever dataset tracking all climate aid activities in a single country. The data uses a new methodology to assess all projects from Malawi's Aid Management Platform, and builds on the joint activity coding and geocoding efforts between the Government of Malawi, CCAPS, and AidData. The data is available on the CCAPS Dashboard or on the newly released CCAPS Aid Dashboard, which allows users to overlay climate aid on climate vulnerability maps to see if aid is meeting local needs.

This past week, the Aspen Institute hosted its annual Forum on Communications and Society (FOCAS). This year's Forum focused on open and innovative government. The three day Forum looked at issues in governance, innovations in governance, and the role of ICTs in governance. Despite the heavy focus on technology and innovation, the Forum returned to the humanistic side of the open data and open government movements. Said Jeff Gomez, CEO of Starlight Runner Entertainment: "Data is fantastic but hearing the voices of the people...is vital."

Featured Dataset: On the AidData Research Datasets page, users can find the GDP Deflators and Exchange Rates dataset from the OECD. The dataset contains the deflators and exchange rates used to convert all transactions in the AidData web portal to constant USD-2009. Earlier this week, however, AidData launched an easy and interactive web service that allows users to dynamically convert financial and aid commitment amounts rather than simply relying on the dataset.




Wednesday, August 8, 2012


USD-2009 Deflator Web Service now in Beta



An important step in performing statistical analysis across many countries and many years is converting financial amounts to a single currency. 

In the AidData web portal and AidData 2.0 research release, we use historical exchange rates to convert transactions to US Dollar and GDP deflators to bring all transactions to 2009. Our methodology is based on the work of the OECD CRS, which publishes deflators for DAC donors. We use the methodology that they apply to DAC donors in order to generate new deflators for non-DAC donors.

The whole deflator dataset is available here, but AidData has also made the deflators available through a simple web service:


This service, hosted at the College of William and Mary’s Institute for the Theory and Practice of International Relations, makes AidData’s deflator methodology readily available to anyone. Users may use the drop-downs to select country of origin, currency, and year of the transaction(s), enter a single value or comma-separated values (eg. “435, 500.50, 32511.69”) as amount, and then click “Send” to deflate each value to USD-2009.  For more tech-interested users, the API is described under “Documentation.”

We invite feedback from our users at info@aiddata.org. We hope to make this web service a valuable resource for years to come.


Robert Mosolgo is a Project Manager at AidData. He handles data management, standardization and quality assurance.




Friday, August 3, 2012


This week in aid and transparency


NITA-U, Uganda’s national ICT authority, announced plans to enable a cloud server in the country as the center point for storing all government data. The Government sees this as the first step towards opening up its data to citizens. Hopefully Uganda’s “move to the cloud” will lead to similar results as Kenya’s openData initiative, and encourage users to push the limits of what the data can and tell us.

The Sahel Food Crisis dashboard is a new collaborative data and map sharing initiative to bring together organizations focused on the mounting food crisis in western Africa. With the interactive dashboard, users can mashup various data (such as malnutrition rates, food security conditions, or population density) to get a better understanding of the crisis. More on the dashboard, the data, and underlying TileMill technology can be found at the PBS Idea Lab.

UN Secretary-General Ban Ki-Moon announced the appointments on the panel looking at the post-2015 development agenda. The 26-member panel has been asked to create a “bold yet practical” agenda for development efforts following the 2015 Millennium Development Goals. Beyond2015, an international civil society campaign focused on advancing the discussions on the post-2015 agenda, largely supports the Secretary-General’s appoints, but notes the “failure to explicitly acknowledgethe role of people living in poverty” in shaping the agenda. What do you think? The UN is encouraging citizens to have their say at the World We Want portal.

Development Gateway’s Director of Operations, Nancy Choi, is featured on the Huffington Post to discuss girls’ empowerment through sports, and U.S. Sectary of State Hillary Clinton’s call to close the gender data gap. Choi argues that expanding efforts like Mapping for Results are key to closing the broken feedback loop as to whether development impacts are taking place. Meanwhile, USAID also takes a look at the impact of sports on development.

Featured dataset: On the AidData Research Datasets page, you can access the History of U.S. Aid and Reimbursements to Pakistan dataset from the Center for Global Development. It contains budget level information on U.S. military and economic assistance to Pakistan from 1948 to 2010. Earlier this week, CGD announced its new study, “More Money, More Problems” to evaluate U.S. development strategy in Pakistan.