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Geospatial Impact Evaluations

Recent Posts

May 2018

AidData wins $2.95 million to track HIV/AIDS in Côte d’Ivoire

The project is designed to enhance the use of health data by the government of Côte d’Ivoire, civil society organizations and local communities.

Testing for AIDS: A young woman is tested for HIV/AIDS. Photo by Martin Mugo Muiga/Horec Kenya, courtesy USAID Office of HIV/AIDS.
February 2018

Filling the missing middle: A method for impact evaluators on a budget

Faster and cheaper than a randomized control trial but more rigorous than a performance evaluation, Geospatial Impact Evaluations (GIEs) fill the “missing middle” for organizational learning.

December 2017

Strengthening Côte d’Ivoire’s health sector with open data

Researchers from AidData will travel to Côte d’Ivoire to lead development of a USAID-funded geospatial data center.

A USAID Preventative Mini-University in Côte d'Ivoire.
September 2017

Building a geospatial revolution

Geocoding the globe! In our five years of partnership with USAID, we located over 130,000 development activities and $750 billion in assistance.

AidData's Pat Austria (College of William and Mary Class of '13) speaks at the U.S. Global Development Lab Launch April 3, 2014. Photo by David Trichler for AidData, all rights reserved.
February 2017

What are development corridor strategies, and do they work?

Liberia made foreign direct investment (FDI) the centerpiece of its development strategy. We examine how these natural resource concessions affected local economic growth.

Sunrise in Beira, Mozambique in 2011. Photo by Andrew Moore, licensed under (CC BY-SA 2.0).
February 2017

Chinese-funded infrastructure in endangered forests: What is the data telling us?

The picture becomes clearer when breaking down the effects within each country.

The first Chinese-backed railway, Tazara Rail (pictured above), was funded in the 1970s. Now China has agreed to help Tanzania build a new 2,561km railway worth USD 7 billion that will run between the Tanzanian port of Dar es Salaam and the Great Lakes states of Rwanda and Burundi.
February 2017

Want to reform aid? Double down on impact evaluations

More investment in evaluation would determine which types of projects deliver the best results, and reassure American taxpayers that foreign aid can provide good value-for-money.

US and Philippines soldiers unload relief supplies to a school on Panay Island in the Philippines. Photo by DVIDSHUB, licensed under (CC BY 2.0).
January 2017

Using machine learning to combat environmental degredation on a global scale

Leveraging machine learning algorithms to sift through terabytes of high-resolution satellite data, a new report by AidData and the Global Environment Facility has identified the factors that contribute to land degradation on a global scale.

A bird's eye view of the stark contrast between the forest and agricultural landscapes near Rio Branco, Acre, Brazil. Photo by Kate Evans for Center for International Forestry Research (CIFOR), licensed under CC BY-NC 2.0.
November 2016

Parceling out prosperity? Tracking and evaluating the impacts of natural resource concessions in Liberia

How concerned would you be if a third of your country's land was granted to foreign investors?

Martha Togdbba of Kpaytno, Liberia, grows vegetables, including tomatoes and chili peppers. Photo by Laura Elizabeth Pohl and Bread for the World, licensed under CC BY-NC-ND 2.0.
October 2016

Untangling the complex relationship between aid and conflict with subnational data

Outside actors frequently try to address the causes and consequences of civil conflict by offering aid to “one side” or to innocents caught in the middle. However, there are still some unanswered fudamental questions regarding aid's real effect on conflict.

This map of RGA departments and municipalities within Colombia was generated using GADM administrative boundaries.
September 2016

AidData publishes geocoded dataset on Chinese financing in ecological hotspots

The dataset captures $161 billion in financial commitments between 2000 and 2014 and extends the geographical coverage of AidData’s existing database of Chinese development projects in Africa to parts of Asia and Latin America.

This map draws on Chinese infrastructure project location data from AidData and forest cover loss data from Hansen et al. (2013).
August 2016

Viewing poverty more clearly — from space

Ground-breaking research by Stanford University scientists has combined satellite imagery taken from space and machine learning to bring better measurements of poverty and economic development within reach.

Photo of the International Space Station and the aurora by NASA.
March 2016

“Beyond Africa”: A glimpse into AidData’s forthcoming dataset on Chinese financing in ecological hotspots

The forthcoming dataset captures more than 1100 Chinese projects from 2000 to 2014 in 19 countries, totaling $95 billion in total official financing.

Media reports comprise ~55% of the total resources for all projects, whereas government sources consist of 20% of the total resource distribution.

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