Self-selection versus population-based sampling for evaluation of an agronomy training program in Uganda

Abstract

ABSTRACT One of the challenges in evaluating the impact of agronomy training programs, particularly on downstream impacts such as yield, is identifying a sample of farmers who are likely to participate in the training. We assess farmers’ participation in a farm business training activity before the agronomy training intervention as a sample identification mechanism. The screening activity was designed to appeal to the same group of farmers targeted by a coffee agronomy training program, while having minimal impact on the program’s goal of increasing coffee yields. A three-session training on farm business management was conducted in 22 study villages in central Uganda. Coffee agronomy training was then offered in half of these villages, based on random assignment. The results show that 52% of coffee farmers who attended the first business training session subsequently attended agronomy training, compared to 22% of those identified through a census. Applying these results to the design of a large ongoing randomised controlled trial, we find that using a self-selected sample reduces the minimum detectable effect of agronomy training on coffee yield to 15.83%, compared to 38% if population-based sampling were used.