This week we are trying out a new feature—a compilation of recent links on aid effectiveness, transparency, development, and so forth from around the web. Please comment and share other stories that caught your eye! And let us know if you’d like us to do this regularly. Here goes...

Will mobile phones and mobile technologies help reach development goals or is this another one of many overhyped development fads?  Watch a very lively panel discussion from the New America Foundation here, read panelist opinions here, and see an interactive map of mobile phone ownership around the world here.

Governments aren’t the only ones that become more accountable when there's greater transparency. 

USAID, other US donor agencies launch a new push for innovation. Rolf Rosenkranz wonders how tolerant lawmakers will be of failed innovations produced by this effort.

A new data visualization using AidData (requires Java).

Some interesting analysis from Nancy Birdsall here and here on the selection of a new president at the World Bank.

And from AidData’s own Brad Parks, a plug on the Monkey Cage Blog for using project-level data to analyze aid effectiveness.

Bangladesh is a country with thousands of development organizations, each with hundreds of concurrent projects. For some perspective, in 2003 there were 6,559 development NGOs operating in the country, almost one for every village. The proliferation of aid actors in every conceivable sector--from social welfare to governance and the environment--raises a fundamental question: What is actually happening on the ground? For all these projects, many of which share similar goals and locations, there is limited available information on how the aid actually assists impoverished peoples.

Last year, I worked for the World Food Programme in Bangladesh, and observed firsthand how a lack of information sharing on-the-ground can hinder effective targeting of aid projects. Since development organizations have limited resources, they generally attempt to target their projects to areas of greatest need. I assisted with the initial implementation of a flood Emergency Response Operation in Satkhira, Bangladesh, a program targeting individuals displaced by the flood as well as pregnant women and young children.

One of our tasks was to cross-check the beneficiaries selected by our NGO partner to ensure they were being chosen according to the proper needs-based criteria. As we drove along broken roads lined with makeshift shelters constructed from bamboo, jute, cloth, and plastic tarps, I anticipated meeting people in extremely dire conditions. But when we arrived at the first household on our list, a fully intact bamboo and mud house, I had a feeling that something was not quite right. As it turned out, the family had been economically hurt by the flood, but they had not been displaced. Other villagers who we talked to mentioned the same phenomenon: that certain people always seem to get selected for aid projects while others who are worse off do not. After checking a total of ten households, we found that four of them had been selected incorrectly, and reported to the WFP office immediately.

As much as development organizations try to closely monitor project implementation, it is impossible to account for every detail of on-the-ground activity. NGOs sometimes find it advantageous to select their existing beneficiaries, or those who are not severely affected, in order to report significant improvements to their donors. Therefore, even if an NGO does not completely follow the implementation guidelines by targeting the intended beneficiaries, donors will have the false satisfaction of believing their project had its intended outcome. In order to identify projects where the same well-off households are repeatedly included on the beneficiary list, villagers need to be able to report on the aid they are receiving and who is being left out. Such a system would impose a check on NGO activity, pressuring them to target households with greatest need.

Increased transparency can also encourage better coordination between all of the different agencies working in a single location. In the case of the Satkhira flooding, numerous aid organizations had a presence, each with their own objectives. Everywhere I went I saw an assortment of development organization logos on shelters, latrines, and food rations. It was difficult to discern if there was any overarching coordination strategy. Indeed, as we talked to more people, they explained that some groups came in for a few days to give away bags of rice, while others had longer-term plans for building up the infrastructure and embankments. Wouldn’t it be more useful if the recipients of the development assistance could report on what aid they were receiving and what aid they still needed?  Then, other donors could get a better picture of the situation and allocate funding for future projects accordingly.

In addition to improving aid coordination, transparency can enable development organizations to tailor projects to the specific needs of communities. For example, I am currently working with Innovations for Poverty Action on a randomized control trial (RCT) that is implementing demand and supply side treatments to bolster use of latrines and sanitation practices in Bangladeshi villages. As I monitored the baseline survey, I discussed the current sanitation situation with enumerators. Surprisingly, they discovered that not only was there a shortage of latrines in village households, but many village schools—built by a local NGO—also lacked latrine access. This could be for a variety of reasons. Perhaps the NGO had to build a certain number of schools and the budget did not allow for latrine construction, or perhaps they used the extra money for another project. But if the enumerators and villagers had a platform to report their observations on their latrines, donors could focus on funding the crucial sanitation component for the existing and future schools.

Crowdsourcing may be one way to address these sorts of coordination and targeting issues. Through the rapid diffusion of mobile technologies, people living and working in developing communities now have a mechanism to deliver real-time information on local conditions and project performance to donors. However, a common platform to aggregate, share, and make sense of monitoring and evaluation data does not yet exist.

AidData has recently overseen an RCT in Uganda to help develop a workable crowdsourcing model, and I hope this work expands to other areas soon. My experiences in Bangladesh have given me a new appreciation for the importance of repairing the broken feedback loop gap between donors and their intended beneficiaries. Identifying whether and how projects are functioning in impoverished communities is the central to designing effective poverty alleviation projects.

Ishita Ahmed is a former AidData Research Assistant at the College of William and Mary (’11).

We are happy to announce the release of two additional publications in our Research Brief series. These 3-5 page publications seek to make the empirical findings of AidData-affiliated faculty more accessible to policymakers, development practitioners, journalists, and the general public.

Today’s release includes a brief entitled "Does Health Aid Reduce Mortality?". It is based on a full length journal article published by Sven Wilson in the November 2011 special issue of World Development.  We have also posted "When Does Education Aid Boost Enrollment Rates?", a brief by Zachary Christensen, Dustin Homer, and Daniel Nielson, which is also based on a full length article published in the November 2011 special issue of World Development.

AidData's research brief series is just one of several new research resources published as part of the late 2011 launch of AidData 2.0. To make the underlying data used to produce aid allocation and aid effectiveness research more accessible, we have posted or linked to 57 replication datasets. And we are adding more datasets every month. We have also assembled 18 “prepackaged” research datasets, derived from the core AidData database and from external sources. Additionally, we have compiled a list of ongoing projects overseen by AidData-affiliated scholars, and a comprehensive collection of all published articles and books which rely on AidData.org for empirical analysis. 

If you would like to contribute replication data from your peer-reviewed article or book for posting on AidData, please contact info@aiddata.org.

Over the last few weeks, we have been exploring whether there are new insights to glean from the World Bank's massive evaluation dataset.  The dataset consists of nearly 10,000 World Bank projects with discrete categorical ratings for variables such as 'Quality at Entry', 'Quality of Supervision', 'Bank Performance', 'Borrower Performance', and  'Project Outcome'. One of the advantages of the dataset is that it allows one to explore both the project-level and country-level determinants of project performance.  

In this post, we set out to assess the impact of project supervision on final project outcomes as well as the relative influence of country-level factors, such as corruption and government stability. The first potential correlation we examined was between 'Quality of Supervision' (QOS) and final project outcome. Consistent with the approach taken in an earlier post on this blog, we converted the Bank's six-point QoS and project outcome measures into binary (satisfactory/unsatisfactory) variables. Because the large majority of World Bank projects recorded in the database took place between the years 1984 and 2009, we excluded all prior years from our analysis. All borrower countries that did not have QoS and project outcome data for 10 discrete country-years during this timeframe were also excluded, reducing the sample size to 72 countries. Remaining project QoS and outcome values were averaged separately at the country-year level; these country-year averages were then averaged at the country level. Each recipient country was thus assigned a pair of unique QoS and outcome ratings between 0 (unsatisfactory) and 1 (satisfactory), which are displayed on a scatter plot below.

The results were not surprising: better project supervision generally yielded better project performance. But what else might help determine the success of a project? We used data from the PRS Group’s International Country Risk Guide to assess several contextual factors that may compromise project supervision and/or project outcomes: corruption, government stability, democratic accountability, bureaucratic quality and socioeconomic conditions. Specific country-year scores for each indicator were averaged for the period 1984-2009.These five composite indicators were then compared to their respective QoS and project outcome scores.

Several interesting trends emerge for borrowers with at least ten years of project outcome data (92 countries total) and QoS data (72 total). Only the socioeconomic conditions indicator had a significant impact on the project supervision: the better the socioeconomic conditions in a given country, the higher the QoS. Other country-level factors, such as government stability, did not appear to significantly influence QoS scores.

We obtained stronger results in a similar analysis of project outcomes. Whereas the borrower government’s level of stability still has no apparent role in determining a project’s success or failure, all other factors seem to have an impact; better socioeconomic conditions, lower levels of corruption, relatively efficient bureaucratic instititutions, and higher levels of democratic accountability seem to increase the likelihood that World Bank projects will succeed. In fact, socioeconomic conditions seem nearly as important as QOS to a project’s final outcome rating.

This post was contributed by William & Mary students Dylan Murray ‘12, an AidData research assistant, and Chris Salvi ’12, an AidData intern.

Only 3% of projects with low levels of project supervision had a final outcome rating of 'satisfactory'. However, 27% of projects that received a 'satisfactory' rating on the QPS indicator received a final outcome rating of  'unsatisfactory'. This pattern suggests that effective supervision is a necessary, but insufficient, predictor of project success.

A more thorough analysis is needed to determine the precise linkages between the quality of monitoring and evaluation, the quality of supervision, and project success, but our preliminary results support the current emphasis on strengthening monitoring and evaluation systems and improving project supervision.

This post was written by Ben Buch and Doug Nicholson. Ben and Doug are AidData Research Assistants at the College of William and Mary.

"We have to create a new international system, and we're doing it… 

The solution is in our hands. It's not in handouts from the North." –Hugo Chavez, 2009

The global development finance architecture is rapidly changing. Many low-income and middle-income countries and longtime recipients of Western aid are now engaging in a different form of development cooperation called "South-South cooperation." Broadly defined, South-South cooperation is an arrangement in which developing countries share knowledge, skills, expertise and resources to meet mutual development goals. 

Venezuela, a country known for promoting strong integration of Latin American and Caribbean countries, is an active sponsor of South-South development cooperation (SSDC) activities (see Chart 1). Its Ministry of Petroleum and Mining is one of the leading institutional actors involved in SSDC activities. It oversees Petroleos de Venezuela SA (PDVSA), a state owned oil company which offers oil to Venezuela’s partner countries on concessional terms  and funds social programs.

Venezuela also sponsors energy integration in Latin America and the Caribbean, channeling significant amounts of oil-related assistance to governments through the Caracas Energy Cooperation Agreement, the Energy Treaty of ALBA, and Petroamerica. These programs have helped Venezuela curry favor with governments in the region, but they have also made the Chávez administration the subject of intense criticism for its apparent lack of transparency.

Consider Nicaragua. In 2007, Nicaraguan President Daniel Ortega decided that his government would join ALBA and Petrocaribe, a Petroamerica initiative. Through this arrangement, Nicaragua gains access to 27,000 barrels of oil per day, effectively getting half of its purchase back in low-interest, long-term loans. Venezuelan aid through ALBA also led to the creation of ALBA de Nicaragua SA (ALBANISA), a private company in Nicaragua that manages joint revenues between PDVSA and Petroleos de Nicaragua (PETRONIC). ALBANISA is not required to disclose its funds to Nicaragua´s National Assembly; oversight rests solely with the executive branch. Thus, an estimated $450 million in 2009 escaped public scrutiny.

Venezuela's unwillingness to disclose detailed financial information has aroused suspicions. TIME Magazine argues that the Ortega administration’s exclusive oversight of ALBANISA and ability to purchase private ownership of Nicaraguan companies has increased opportunities for corruption and political patronage.

But others argue that Venezuelan assistance, which may constitute as much as 50% of all official financial flows received by the government, has played a major role in improving living conditions in Nicaragua's rural areas.  Dr. Alejandro Martinez Cuenca, who runs a think tank in Managua, points out that extreme poverty in Nicaragua declined from 17.2% in 2005 to 9.7% in 2009. He attributes this improvement to the fact that "the government has had access to unlimited resources from Venezuela, and these have gone toward the rural sector."

Transparency would, of course, give the Chávez administration an opportunity to counter its critics. It would also help the research community better understand the rapidly evolving paradigm of South-South development cooperation. But for the time being it appears that the intended beneficiaries of Venezuela's SSDC programs will be left to hold the Chávez administration accountable for results.

This post was written by Daniel Gamboa Galvez, a Visiting Research Associate at AidData, and Jaclyn Goldschmidt, an AidData Research Assistant.

I would argue that one of most important contributions PWYF has made is to move the policy discussion beyond the simple question of “What information is available?” and towards the more fundamental question: “Is the information that should be available actually available?” PWYF sheds light on the latter issue with detailed data for 58 organizations from 45 countries/IGOs. Their assessment examines three dimensions of each donor organization: organizational, country and activity level. At each level, PWYF has determined whether the organization collects and/or publishes commonly available information items, such as policy documents, country strategies, and details on project planning, implementation and evaluation. The complete methodology is available here.

PWYF's pilot Index also draws our attention to an area where there is tremendous scope for improvement: benchmarking the transparency practices of development finance agencies outside of the OECD-DAC. PWYF and their CSO/university collaborators gathered data largely from DAC agencies, but their methodological approach lends itself to inclusion of non-DAC agencies. In fact, some of the initial groundwork has already been laid by Michael Hubbard and Pranay Sinha at University of Birmingham. In their “Non DAC Donor’s Data Availability Index,” Hubbard and Sinha investigate the depth and quality of non-DAC data already available from the AidData.org web portal. They also provide information about the sources of the records published by AidData.

Given that primary sources of information have been identified and a strong methodology for measurement is in place, the table is set for an industrious graduate student, junior faculty member, or CSO to begin collecting non-DAC data that are comparable with the (mostly) DAC data included in the PWYF assessment.

My colleagues and I believe that including non-DAC development finance agencies in future benchmarking exercises would be a great service to the aid transparency policy discussion, as many of these countries (e.g. India, Mexico, and Russia) are currently establishing new agencies and working out how information will be gathered and published for years to come. Including these organizations in benchmarking assessments like PWYF’s 2011 Index would enable non-DAC agency leaders to track their own progress. It might also foster a bit of healthy competition.

Robert Mosolgo is an AidData Project Manager at the College of William and Mary. He oversees AidData's work with non-DAC development finance agencies. 

 “With networked research, all can help collect and share the data that is sorely lacking... We need more hands and minds to confront theory with evidence on major policy issues. This is the direction that I want the World Bank to take. This is democratizing development economics.”

- Robert Zoellick, President of the World Bank Group, 

speech delivered at Georgetown University, September 2010

B.K. Bangash / AP

The World Bank’s Open Data initiative has demonstrated—in spades—that universally accessible data can provoke new research questions and turn conventional wisdom on its head. However, for a variety of reasons, donors seldom release comparable project evaluation data. The scarcity of reliable project-level evaluation data has created an important gap in the aid effectiveness literature. While economists and political scientists have undertaken hundreds and hundreds of econometric studies to assess the impact of aggregate aid flows on various development outcomes, the research community still knows relatively little about the project-level determinants of successful donor-sponsored projects.

In a huge step forward for aid transparency, the World Bank's Independent Evaluation Group recently published its entire store of approximately 10,000 WB project evaluations from the 1960s to present. And importantly, the Bank’s unique project identification system allows users to track individual database records back to project documents.

Shortly after the Bank released these records, we geo-coded all of the World Bank’s publicly available project evaluation data in Afghanistan since the fall of the Taliban in 2001. By “mashing-up” these geo-coded data and other statistical sources, we may begin exploring the spatial determinants of aid effectiveness in Afghanistan.

To conduct an initial "plausibility probe" of the popular hypothesis that security is a key determinant of successful projects, we overlaid all geo-coded and IEG-evaluated World Bank projects from 2002-2007 with sub-national violence data from the Long War Journal.

The resulting map reveals a puzzling pattern. The spatial distribution of violence and project performance do not correspond as closely as one might expect. Conventional wisdom holds that aid projects are generally less successful in conflict-affected areas. But this map suggests that many failed World Bank projects actually cluster in the relatively less violent provinces north of Kabul. Additionally, this map calls attention to the fact that a fair number of World Bank projects succeed in the country's most violent southern provinces, e.g. Kandahar and Helmand.

Several explanations may account for this unusual pattern. Projects in the most dangerous provinces may receive a higher level of donor supervision (since they are located in areas where "the stakes are highest"), which previous research identifies as an important predictor of project success. It could also be the case that donor supervision is lower in these areas, which makes it easier for local officials to avoid micro-management from Western capitals and tailor projects to local needs and conditions.

The key point is that aid effectiveness scholars cannot answer a puzzling question like this one until they know it exists. This is why we have expressed great enthusiasm for the World Bank's ambitious effort to "liberate" development data and promote "networked research".  Finally, we should acknowledge that more comprehensive, time-series data from all donors in Afghanistan would provide a much stronger empirical basis for systematic hypothesis testing. A recent pilot project in Malawi strongly suggests that geocoding the universe of aid is feasible when donors agree to disclose detailed project documentation.  However, mobilizing the necessary political will and capacity necessary to ensure that project evaluation documents are placed in the public domain will likely prove far more challenging. The latest Publish What You Fund benchmarking exercise demonstrates that only a handful of donors receive high scores on evaluation disclosure practices.

Brian O'Donnell is an AidData Post-Baccalaureate Fellow at the College of William and Mary. Brad Parks is Co-Executive Director of AidData and Research Faculty at the College of William and Mary.