Exploring the Socioeconomic Co-benefits of Global Environment Facility Projects in Uganda Using a Quasi-Experimental Geospatial Interpolation (QGI) Approach

Daniel Runfola, Geeta Batra, Anupam Anand, Audrey Way and Seth Goodman
Additional contact information
Daniel Runfola: Department of Applied Science, William & Mary, 540 Landrum Drive, Williamsburg, VA 23185, USA
Geeta Batra: Independent Evaluation Office, Global Environment Facility, 1899 Pennsylvania Ave NW, Washington, DC 20006, USA
Anupam Anand: Independent Evaluation Office, Global Environment Facility, 1899 Pennsylvania Ave NW, Washington, DC 20006, USA
Audrey Way: Geospatial Evaluation and Observation Lab, William & Mary, 540 Landrum Drive, Williamsburg, VA 23185, USA
Seth Goodman: Department of Applied Science, William & Mary, 540 Landrum Drive, Williamsburg, VA 23185, USA

Sustainability, 2020, vol. 12, issue 8, 1-13

Abstract: 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.

Keywords: co-benefits; sustainable development; causal methods; geospatial impact evaluation; quasi-experimental design; interpolation; GIS; remote sensing (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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