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).
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.
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.
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.
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.
The project is designed to enhance the use of health data by the government of Côte d’Ivoire, civil society organizations and local communities.
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.
Researchers from AidData will travel to Côte d’Ivoire to lead development of a USAID-funded geospatial data center.
Geocoding the globe! In our five years of partnership with USAID, we located over 130,000 development activities and $750 billion in assistance.
AidData Working Paper
Jun 25, 2018
Maria Perrotta Berlin, Evelina Bonnier, Anders Olofsgård
A geospatial analysis finds Chinese aid is positively affecting household wealth and education in 13 sub-Saharan African countries.
May 23, 2018
Bruno Martorano, Laura Metzger, Marco Sanfilippo
Mar 20, 2018
Jonas B. Bunte, Harsh Desai, Kanio Gbala, Bradley C. Parks, Daniel Miller Runfola
Dec 30, 2017
Jianing Zhao, Daniel M. Runfola, Peter Kemper
Nov 01, 2017
Ariel BenYishay, Silke Heuser, Daniel Runfola, Rachel Trichler
A review of the advantages, disadvantages, and use cases of GIEs across countries, sectors, interventions, and development organizations.
Sep 01, 2017
Ariel BenYishay, Daniel Runfola, Rachel Trichler, Carrie Dolan, Seth Goodman, Bradley Parks, Jeffery Tanner, Silke Heuser, Geeta Batra, Anupam Anand
Mar 09, 2017
Daniel Runfola, Ariel BenYishay, Jeffery Tanner, Graeme Buchanan, Jyoteshwar Nagol, Matthias Leu, Seth Goodman, Rachel Trichler, Robert Marty
Mar 01, 2017
Daniel L. Nielson, Bradley C. Parks, Michael J. Tierney
Georeferenced project data is merged with a long series of high-resolution satellite data to identify project impacts on forest cover.
Dec 01, 2016
Ariel BenYishay, Bradley Parks, Daniel Runfola, Rachel Trichler
Satellite-based forest cover data and variation in timing is used to study whether formalization of land rights affects deforestation rates.
Apr 01, 2016
Project impact on biodiverse areas is assessed using remote-sensed forest change data and in situ monitoring data on conservation outcomes.
Feb 01, 2016
Graeme M. Buchanan, Bradley C. Parks, Paul F. Donald, Brian F. O'Donnell, Daniel Runfola, John P. Swaddle, Lukasz Tracewski, Stuart H.M. Butchart
Jan 01, 2016
Daniel Miller Runfola, Ashley Napier
Jan 01, 2015
Ariel BenYishay, Keith Kranker
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