Do low-income households in Tanzania derive income and nutrition benefits from dairy innovations?

Irish Ai

Evaluating value chain interventions: A review of recent evidence

Value chain interventions are rarely evaluated as rigorously as interventions in agricultural production or health. This is due to various reasons, including the intrinsic complexity of value chain interventions, intricate contextual support factors, presence of multilevel system actors, constant adaption to market and nonmarket forces and the cost associated with conducting an evaluation. This paper discusses a range of approaches and benchmarks that can guide future design of value chain impact evaluations. Twenty studies were reviewed to understand the status and direction of value chain impact evaluations. A majority of the studies focus on evaluating the impact of only a few interventions, at several levels within the value chains. Few impact evaluations are based on well-constructed, well-conceived comparison groups. Most of them rely on use of propensity score matching to construct counterfactual groups and estimate treatment effects. Instrumental variables and difference-in-difference approaches are the common empirical approaches used for mitigating selection bias due to unobservables. More meaningful value chain impact evaluations should be prioritized from the beginning of any project and a significant amount of rigor should be maintained; targeting a good balance of using model-based and theory-based approaches