Evaluating Development Impact in Low- and Middle-Income Countries

Knowing whether a social program or policy actually works is the cornerstone of effective international development. This course introduces you to the essential methodologies used to measure the true causal impact of interventions in low- and middle-income countries. Through clear written explanations and real-world case studies, you will transition from understanding basic development concepts to critically analyzing complex evaluation designs. You will gain the confidence to determine which statistical methods are best suited for different policy environments and how to interpret evaluation results accurately. What you'll learn: - Understand the foundational principles of causal attribution and the counterfactual framework. - Design randomized controlled trials (RCTs) to evaluate development projects effectively. - Apply quasi-experimental methods, including difference-in-differences and regression discontinuity. - Analyze evaluation data using regression techniques to estimate program impacts. - Integrate modern research transparency practices, including study pre-registration and ethical data workflows. The course begins with foundational concepts of causal inference and the challenges of measuring impact. You will then progress through experimental designs, quasi-experimental statistical techniques, and modern standards for research transparency and ethics. This course is designed for aspiring development practitioners, policy analysts, and researchers who are new to impact evaluation, requiring no prior advanced statistical training. Start reading today to build the skills needed to design and interpret rigorous development evaluations.