A Learning Agenda for Community-Driven Development: Responding to Complex Contextual, Evaluation, and Inference Challenges

This policy research working paper examines the methodological and practical challenges involved in evaluating community-driven development (CDD) programs. The authors argue that the complexity and context-specific nature of CDD initiatives require more adaptive learning approaches that go beyond conventional impact evaluation methods. The paper proposes a “learning agenda” focused on addressing contextual variation, improving causal inference, and strengthening implementation learning to better understand how participatory development programs operate across diverse settings.