M&E Guidance Series: What are Impact Evaluations?

Community feedback indicated strong adoption rates for irrigation techniques, with 75% of farmers reporting increased crop yields. The program's success can be attributed to the effective implementation of the interventions, which included the establishment of a robust monitoring and evaluation framework. This framework allowed for the tracking of progress and the identification of areas for improvement. Impact Evaluations Impact evaluations are a crucial tool for assessing the effectiveness of development programs. They measure the change in a development outcome that is attributable to a defined intervention. Impact evaluations are based on models of cause and effect, requiring a credible and rigorously defined counterfactual to control for factors other than the intervention that might account for the observed change. The purpose of impact evaluation is to provide feedback to help improve the design of programs and policies. Impact evaluations are also a tool for dynamic learning, allowing development stakeholders to improve ongoing programs and ultimately better allocate funds across programs. They are needed to inform policy makers on decisions, from curtailing programs to scaling up interventions that work. Role of Impact Evaluation in Monitoring and Evaluation Impact evaluations fit into the chain of monitoring and evaluation in several ways. They help to assess the causal link between an intervention and an outcome. Impact evaluations provide evidence of the effectiveness of an intervention, which can be compared with other similar interventions. This process establishes credible cost-effectiveness comparisons. Impact evaluations can serve to build the knowledge base of what works. With an increasing demand for evidence of USAID effectiveness, rigorous evaluations provide a method through which development successes can be highlighted. To measure the impact of an intervention, a clear, well-designed evaluation strategy is necessary. Impact Evaluation Design under FTF Under FTF, impact evaluations will use target and control groups to compare situations and changes. The control group, or counterfactual, should be a group that is as similar as possible in observable and unobservable dimensions to those receiving the intervention. This comparison allows for the establishment of definitive causality, attributing observed changes to the program while removing confounding factors. Impact evaluations will be grouped into two categories: experimental design (Category 1) and quasi-experimental design (Category 2). Category 1 evaluations will be those that are designed as Randomized Controlled Trials (RCTs). Category 2 evaluations will use quasi-experimental designs, including propensity score matching, double differences methods, instrumental variable methods, or reflective comparisons. Impact Evaluation Methods under FTF Data collection and analysis under FTF impact evaluations can use quantitative or qualitative methods or both. An evaluation that uses "mixed methods (both quantitative and qualitative)" is usually best, as it offers both rigor and richness of data. Quantitative methods help to understand the basic relationship between variables, specifically looking for correlation and causation. Qualitative methods provide a deeper understanding of particular phenomena, offering a wider range of explanations and helping to identify unintended impacts.