Does Community-Based Adaptation Enhance Social Capital? Evidence from Senegal and Mali

Abstract

Climate change and extreme climate shocks pose a significant threat to resource-dependent rural communities. Successfully supporting households to anticipate and adapt to climate variability and shocks, as well as build long term climate resilience, is essential to facing these changes. Given the importance of social capital in facilitating collective action and adaptation, the development community has focused on bottom-up, participatory adaptation projects. This article explores the social capital impacts of a pilot community-based adaptation project in Senegal and Mali that aims to encourage inclusive decision making around public goods investments. The analysis uses both difference-in-differences and propensity score matching estimates to evaluate whether households that participated in the project realized enhanced social capital, as measured through participation in community development, and acts of reciprocity and community support. The findings indicate that engaging in the participatory process through the project increased the likelihood of future collective action and providing help to other community members in Mali.

Keywords:

• Climate change adaptation
• social capital
• public goods
• Senegal
• Mali

Acknowledgements

The authors gratefully acknowledge the financial support provided by the Department for International Development from the UK Government. They also wish to acknowledge the contributions from all members of the NEF/IIED/IED-Afrique consortium of the DCF BRACED project. The views expressed in this article are the authors’ own and do not necessarily reflect those of the individuals and organizations noted above. Authors are happy to provide data and code on request.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Notes

1 DCF broadly is a climate finance model that offers a mechanism for investing in public goods at the local level with the goal of encouraging and enabling climate resilient livelihoods. In this article, analysis focuses on the project as it was implemented and experienced Senegal and Mali (see https://www.neareast.org/braced/ for details).

2 A department is the administrative division in Senegal that is roughly equivalent to a district or county in the US. A cercle is the administrative division in Mali that is roughly equivalent to a district or county in the US.

3 Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS) is a 30+ year quasi-global rainfall dataset generated using satellite imagery with in-situ station data.

4 $Z-\mathit{scor}{e}_{i,j,k,l}=\frac{\mathit{Mean}\mathit{Observation}\mathit{Windo}{w}_{i,j,k,l}-\mathit{Mean}\mathit{Climate}\mathit{Norma}{l}_{i,l}}{\mathit{Standard}\mathit{Deviation}\mathit{Mean}\mathit{Climate}\mathit{Norma}{l}_i}$

5 We draw from Labonne et al., 2007 to create the fractionalization index. We estimate F_k = 1 - Σs_ik, where s_ik is the share of individuals from group i in village k. In this case, groups are the household reported different ethnicities in the countries.

6 Despite having a dichotomous outcome variable, we use a linear probability model (LPM) for our analysis instead of a logit model. The main concern with using LPM is that we are falsely imposing a linear fit to our data. However, given the outcome data distribution we are not concerned about this. We selected the LPM specification over the logit specification due to the intuitive ease of presenting LPM results as percentages.

Additional information

Funding

This work was supported by the Department for International Development, UK Government.