Program Area: GIE

Geospatial Impact Evaluations

Rigorous impact evaluations in a fraction of the time of an RCT

Measure real impact

Geospatial Impact Evaluations measure intended and unintended impacts of development programs. Leveraging readily available data like satellite observations or household surveys, GIE methods establish a reliable counterfactual to measure impact - at a fraction of the time and cost of a "traditional" randomized control trial (RCT).

Methodological rigor

Like RCTs, GIEs can estimate the net effect of a specific program by comparing similar units where the only difference was an intervention, or treatment. Unlike RCTs, GIEs use precise geographic data to establish this counterfactual retroactively, eliminating the need to assign program participants into randomized treatment and control groups within the program design.

Learn more efficiently

GIEs can be completed in a fraction of the time and financial cost of an RCT by eliminating the need for customized data collection in treatment and control groups before, during and after the program.

See portfolio-wide insights

GIE methods are also flexible tools that can either be used to evaluate individual projects or project portfolios.  Whereas RCTs are often implemented in narrowly bounded settings, GIEs can be used with data for an entire country (or even multiple countries), which makes it possible to draw conclusions about impacts and cost effectiveness that are broadly generalizable.

Ascertain long-term impact, even in inaccessible places

Additionally, GIEs can be implemented remotely, retrospectively, and affordably, opening up new opportunities to measure long-run programmatic impacts, which is especially useful to evaluators working in conflict and fragile state settings.

Blog Posts

November 2018

Good news for rare birds: Development projects that don’t harm the environment

New research evaluating World Bank development projects, including those that pose the most environmental risks, finds no harm to important bird habitats.

Sirocco the kākāpō among renga lilies on Maud Island, New Zealand. Photo by Chris Birmingham for New Zealand Department of Conservation via Flickr, licensed under (CC-BY-2.0).
October 2018

USAID roads project sparked—and shifted—economic activity in West Bank

AidData merged high-resolution nighttime lights imagery with precisely-located road improvements to discover how a $900-million investment impacted the Palestinian economy.

Where the coastline begins to curve gently in the lower center of the picture lies the West Bank. Photo by the ISS Crew Earth Observations Facility and the Earth Science and Remote Sensing Unit, Johnson Space Center, via NASA, in the public domain.
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.



Evaluation of the Infrastructure Needs Program II

Ariel BenYishay, Rachel Trichler, Dan Runfola, Seth Goodman



Evaluation of the Local Governance and Infrastructure Program

Pablo Beramendi, Soomin Oh, Erik Wibbels


Working Paper

The Donor Footprint and Gender Gaps

Maria Perrotta Berlin, Evelina Bonnier, Anders Olofsgård


Working Paper

Chinese Development Assistance and Household Welfare in Sub-Saharan Africa

Bruno Martorano, Laura Metzger, Marco Sanfilippo


Journal Article
World Development

Natural resource sector FDI, government policy, and economic growth: Quasi-experimental evidence from Liberia

Jonas B. Bunte, Harsh Desai, Kanio Gbala, Bradley C. Parks, Daniel Miller Runfola


Journal Article
Joint European Conference on Machine Learning and Knowledge Discovery in Databases

Quantifying Heterogeneous Causal Treatment Effects in World Bank Development Finance Projects

Jianing Zhao, Daniel M. Runfola, Peter Kemper