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Experiences with systematic triangulation at the Global Environment Facility

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  • Carugi, Carlo

Abstract

Systematic triangulation may address common challenges in evaluation, such as the scarcity or unreliability of data, or the complexities of comparing and cross-checking evidence from diverse disciplines. Used to identify key evaluation findings, its application has proven to be effective in addressing the limitations encountered in country-level evaluation analysis conducted by the Independent Evaluation Office of the Global Environment Facility (GEF). These include the scarcity or unreliability of national statistics on environmental indicators and data series, especially in Least Developed Countries; challenges in evaluating the impacts of GEF projects; and inherent difficulties in defining the GEF portfolio of projects prior to the undertaking of the evaluation. In addition to responding to the need for further developing triangulation protocols, procedures and/or methodologies advocated by some authors, the approach offers a contribution to evaluation practice. This applies particularly to those evaluation units tasked with country-level evaluations in international organizations, facing similar constraints.

Suggested Citation

  • Carugi, Carlo, 2016. "Experiences with systematic triangulation at the Global Environment Facility," Evaluation and Program Planning, Elsevier, vol. 55(C), pages 55-66.
    • Handle: RePEc:eee:epplan:v:55:y:2016:i:c:p:55-66
    DOI: 10.1016/j.evalprogplan.2015.12.001
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    References listed on IDEAS

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    1. Emma Näslund-Hadley & Scott Kipp & Jessica Cruz & Pablo Ibarrarán & Gita Steiner-Khamsi, 2009. "OLPC Pre-Pilot Evaluation Report (Haiti)," IDB Publications (Working Papers) 23758, Inter-American Development Bank.
    2. Paul Downward & Andrew Mearman, 2007. "Retroduction as mixed-methods triangulation in economic research: reorienting economics into social science," Cambridge Journal of Economics, Cambridge Political Economy Society, vol. 31(1), pages 77-99, January.
    3. Richard M. Burton & Børge Obel, 2011. "Computational Modeling for What-Is, What-Might-Be, and What-Should-Be Studies---And Triangulation," Organization Science, INFORMS, vol. 22(5), pages 1195-1202, October.
    4. Layug, Allan S., 2009. "Triangulation Framework for Local Service Delivery," Discussion Papers DP 2009-37, Philippine Institute for Development Studies.
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    Cited by:

    1. Chen, Yizhong & Lu, Hongwei & Li, Jing & Huang, Guohe & He, Li, 2016. "Regional planning of new-energy systems within multi-period and multi-option contexts: A case study of Fengtai, Beijing, China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 65(C), pages 356-372.
    2. Daniel Runfola & Geeta Batra & Anupam Anand & Audrey Way & Seth Goodman, 2020. "Exploring the Socioeconomic Co-benefits of Global Environment Facility Projects in Uganda Using a Quasi-Experimental Geospatial Interpolation (QGI) Approach," Sustainability, MDPI, vol. 12(8), pages 1-13, April.

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