Using Adaptive Learning to Integrate Social Protection Programs for Improved Resilience in Ethiopia’s Highlands

Rapid Feedback Monitoring, Evaluation, Research, and Learning (RF MERL) investigates how to effectively integrate social protection programs in Ethiopia to improve the of resilience of vulnerable households and communities to multi-sectoral shocks. This engagement will demonstrate how a whole system of programs can be greater than the sum of its parts and will also have implications for the integration of programs beyond Ethiopia.

The Challenge

Households living in the Ethiopian Highlands are vulnerable to shocks that span multiple sectors: weather shocks that affect agriculture production; health shocks that affect wellbeing and individual productivity; and employment shocks that affect income generation. Ethiopia has many social protection programs that assist households in mitigating, adapting to, and recovering from these shocks. However, many of these programs are not integrated, so if a household is enrolled in one program but experiences a shock that could be addressed by another program, they may not get access to the other program when they need it. This lack of integration undermines the resiliency of households, as well as the communities in which they live.

The Opportunity

There is promising evidence on the integration of social protection programs in Ethiopia, but many questions remain about which integration models can lead to the biggest resiliency gains. Questions also remain about how to implement promising integration models at scale. The context for program integration varies substantially from one district to the next due to Ethiopia’s diverse ethno-linguistic make-up and federal administrative structure. Finding effective, scalable solutions to program integration, therefore, requires a new approach: one where the process for identifying solutions matters as much as the solution itself.

USAID/Ethiopia has invested funding to support smart, scaled integration of Government of Ethiopia programming with the Transition into Graduation through Enhanced Resilience (TIGER) activity. To complete the Operations Research component of the program (TIGER-OR), USAID/Ethiopia has awarded Rapid Feedback Monitoring, Evaluation, Research, and Learning (RF MERL), a USAID-funded consortium that is led by R4D and part of the Monitoring, Evaluation, Research, and Learning Innovations (MERLIN) Program. RF MERL’s goal is to research, test, and refine promising models for program integration before those models are scaled up through the TIGER activity and beyond.

Our Work

RF MERL is partnering with USAID/Ethiopia to conduct mixed methods research to learn fast and generate evidence to support adaptations to integrated social protection programs through TIGER-OR. Building on the principals of Problem-Driven Iterative Adaptation, R4D will take a stepwise approach to identifying a problem; working with a local team to determine the problem’s causes; identifying ways to address the problem; and then acting quickly.

The team will work directly with district-level actors in Ethiopia to co-design solutions to program integration, drawing on R4D expertise in collaborative learning and coaching throughout the process. Ongoing qualitative and quantitative data collection will provide continuous feedback on what is working and what is not as each integration approach is carried out. RF MERL will hold regular “Learning Checks” during which district-level stakeholders will come together to review and reflect on the findings from data collection and develop action plans for iterating and improving the integration approach. Lessons learned from TIGER-OR will then inform future scale up of integration within Ethiopia and beyond.

This study is one of several pilots R4D is carrying out in partnership with the Rapid Feedback MERL Consortium as part of the USAID Global Development Lab’s MERLIN program.

For more information, please contact Christina Synowiec (csynowiec@r4d.org).

Photo Credit: Kebede Lulie, Food for the Hungry (Attribution-NonCommercial 2.0 Generic – CC BY-NC 2.0)

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