Exploring the Socioeconomic Co-benefits of Global Environment Facility Projects in Uganda Using a Quasi-Experimental Geospatial Interpolation (QGI) Approach
Department of Applied Science, William & Mary, 540 Landrum Drive, Williamsburg, VA 23185, USA
Geospatial Evaluation and Observation Lab, William & Mary, 540 Landrum Drive, Williamsburg, VA 23185, USA
Independent Evaluation Office, Global Environment Facility, 1899 Pennsylvania Ave NW, Washington, DC 20006, USA
Author to whom correspondence should be addressed.
Sustainability 2020, 12(8), 3225; https://doi.org/10.3390/su12083225
Received: 13 February 2020 / Revised: 10 March 2020 / Accepted: 11 March 2020 / Published: 16 April 2020
(This article belongs to the Special Issue Environment-Poverty Nexus and Sustainable Development)
Since 1992, the Global Environment Facility (GEF) has mobilized over $131 billion in funds to enable developing and transitioning countries to meet the objectives of international environmental conventions and agreements. While multiple studies and reports have sought to examine the environmental impact of these funds, relatively little work has examined the potential for socioeconomic co-benefits. Leveraging a novel database on the geographic location of GEF project interventions in Uganda, this paper explores the impact of GEF projects on household assets in Uganda. It employs a new methodological approach, Quasi-experimental Geospatial Interpolation (QGI), which seeks to overcome many of the core biases and limitations of previous implementations of causal matching studies leveraging geospatial information. Findings suggest that Sustainable Forest Management (SFM) GEF projects with initial implementation dates prior to 2009 in Uganda had a positive, statistically significant impact of approximately $184.81 on the change in total household assets between 2009 and 2011. Leveraging QGI, we identify that (1) this effect was statistically significant at distances between 2 and 7 km away from GEF projects, (2) the effect was positive but not statistically significant at distances less than 2 km, and (3) there was insufficient evidence to establish the impact of projects beyond a distance of approximately 7 km.