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Research paper

Supporting local institutions for inclusive green growth: Developing an Evidence Gap Map

, , &
Pages 51-71 | Received 05 Dec 2016, Accepted 06 Oct 2017, Published online: 18 Jun 2021
 

Highlights

Structured literature search for rigorous studies on local institutions development.

Focus on agriculture and rural development for achieving Inclusive Green Growth.

Evidence Gap Map visualizes outcomes, revealing key evidence clusters and gaps.

Knowledge repository to policy-makers on institutional interventions.

Improved research prioritization and prerequisite for meta-analysis.

Abstract

We conduct a structured search of the academic literature that assesses the impact of development interventions that aim to build and strengthen local-level institutions to facilitate Inclusive Green Growth. Inclusive Green Growth extends the standard growth perspective to include welfare enhancements both the poor (‘inclusive’) and for future (‘green’) generations. We restrict our search to studies in the domain of agriculture and poverty alleviation in the developing world. We access ten online databases and various working paper series and focus on summarising evidence from quantitative studies that use rigorous evaluation methods. Together, this yields 158 studies. We then retain 66 studies that contain a credible counterfactual. We visualize the interventions and outcomes in an Evidence Gap Map, highlighting both the available evidence and remaining knowledge gaps. Most studies suggest that strengthening local institutions can improve the delivery and targeting of public services and overall satisfaction with local governance. There are however, clear limitations and knowledge gaps highlighting priorities for future work. Few studies assess impacts on final outcomes such as household income or agricultural productivity and no studies assess inclusive and green outcomes jointly. We discuss the key benefits of a structured literature search and Evidence Gap Map for policy-makers and development practitioners and illustrate how it serves as a knowledge repository and identifies where evidence is lacking, thus setting the agenda for future work.

Acknowledgements

We thank the editors and two referees for helpful comments. Thanks to Filip de Blois (image editor at the Netherlands Environmental Assessment Agency) for the design of figures. PBL Netherlands Environmental Assessment Agency received funding from the Netherlands Directorate-General for International Cooperation (DGIS) for conducting this research. We further acknowledge financial support from the Netherlands Organisation for Scientific Research [N.W.O. grant #451-14-001] We declare no competing interests. The funders had no role in the study design, data collection, data analysis, data interpretation, or writing.

Notes

1 We have followed the Effective Public Health Practice Project (EPHPP) framework (http://www.ephpp.ca/tools.html). It presents a systemized method to test the specific assumptions underlying claims of causality in statistical studies. As the name suggests, it has initially been developed to assess health interventions, but the framework is sufficiently general to apply it in other settings also and matches closely with other risk of bias tools. See e.g. CitationWaddington et al. (2012).

2 It proved to be impossible to assess studies on the categories Data Collection Methods, Blinding, Analysis and Intervention Integrity as outlined in the EPHPP framework. Either the relevant information was not provided, or the variation was minimal across the studies, or the category was less relevant to interventions in the social sciences (e.g. double blinding).

3 For instance, two famous and long running cash transfer programs are Oportunidades in Mexico and Bolsa Familia in Brazil.

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