Paper short abstract:

This paper shows how cash transfers act as adaptive social protection, mitigating the combined impacts of climate change and conflict. Using machine learning and diverse datasets, it highlights the dual role of social protection in climate adaptation and humanitarian resilience.

Paper long abstract:

Armed conflict and climate change in Sub-Saharan Africa pose significant challenges to the well-being of vulnerable children and the broader sustainable development goals. This study examines the role of cash transfers in mitigating the adverse effects of these polycrises on individual outcomes, including school attendance and food insecurity. Using causal forests, a machine learning approach, we approximate the causal impact of three types of cash transfers under varying scenarios shaped by conflict intensity and climate-related stressors such as droughts. To achieve this, we integrate household survey data from UNICEF’s Multiple Indicator Cluster Surveys (MICS) with satellite-based rainfall and drought data, alongside geo-coded conflict records derived from news sources.

The analysis explores how cash transfers function as a form of adaptive social protection, particularly in regions where environmental shocks exacerbate vulnerabilities caused by armed conflict. By highlighting the interplay between climate variability, conflict, and social protection measures, this research underscores the critical role of cash transfers in enhancing resilience among affected populations. The findings contribute to a growing body of evidence on the potential for social protection systems to serve as climate change mitigation strategies while addressing urgent humanitarian needs.