Intervention(s)
We study the impacts of mechanistic explanations on beliefs about fertilizers and adoption choices among smallholder tomato farmers in Eastern Uganda. Mechanistic explanations are explanations which break down a system or process into the causal interactions among its parts. In the context of this study, these explanations include descriptions of fertilizer nutrients, their roles in plant growth, and the processes through which they move through the soil and the plant. We recruit 900 smallholder farmers in Bugisu sub-region, Uganda. Fieldwork conducted by the authors found that farmers in this region have little understanding of how fertilizers work, rarely experiment with novel combinations on their own, and rely on outside recommendations that may or may not fit their own context or be based in agronomic evidence. We design a set of treatments to test whether mechanistic explanations can address these challenges. One-third of the farmers will receive a placebo training that introduces an agronomist-recommended fertilizer recipe and demonstrates it yield, but provides no further explanations. Another third will receive the same training, plus a short module that identifies the primary macronutrients contained in fertilizers and teaches the macronutrient composition of fertilizers available in the area. The final third will in addition receive mechanistic explanations about fertilizers and the mechanistic rationale behind the demonstrated recipe.
In the first group, the control group, farmers attend a demonstration of a specific agronomist-recommended fertilizer recipe for grey soil. The training will inform the farmers of the types, timings, and amounts of fertilizer used, and the yields that were generated. Farmers will be able to see for themselves the condition of the fruiting plants, and ask the facilitator questions about the fertilizer recipe. The training will also cover methods of fertilizer application, such as how fertilizer should be inserted into planting holes or dispersed around the plant stem as a top dressing. Importantly, this control training will not inform farmers about the macronutrients that are contained in fertilizers, nor the functions of these nutrients and the processes through which they affect plant growth. The control training corresponds in content to what is typically seen in a standard extension or commercial demo.
The second group, treatment 1, will consist of the same activities as the control training. The only difference is that farmers will receive an additional module that describes which macronutrients are contained in synthetic fertilizers, and the macronutrient composition of common fertilizers on the market. This training will not inform farmers about the causal mechanisms through which each nutrient affects plant growth, nor the specific roles that different nutrients play. This training corresponds to an intermediate level of mechanistic understanding in which the learner is able to unpack the black box of a technology and identify which components drive its operation, but has not yet learned how these components work and interact — only that they exist. This group is important for two reasons. Theoretically, it allows us to identify the importance of dimension reduction in learning processes. That is, does knowing which elements of a technology are essential allow one to better learn and apply it, even if one does not know how these elements work? Practically, it also corresponds to a light-touch, low-cost version of a full mechanistic training, and so understanding its impact is relevant for policy.
The third group, treatment 2, will receive the treatment 1 training, as well as an additional module that describes how nutrients affect plant growth, and the processes by which they move and interact in the soil and the plant. This module will describe different soil archetypes, including how soil texture and components affect the ability to retain nutrients, the nutrients that are naturally available in different soils, and mechanisms through which nutrients are retained or lost (e.g., nitrogen leaching, potassium binding). The module also also describes the roles of each of the primary macronutrients in plant growth. These roles are then given mechanistic explanations: for example, phosphorus is needed early in the planting season because the plant can recycle this nutrient many times throughout the season. This training, if leveraged by the farmer, can generate beliefs about the production function through deductive reasoning. It can do this ex-ante. For example, a farmer who learns about clay’s tendency to contain and retain potassium can deduce ex ante (without experimentation) that a soil with high clay content needs little potassium supplementation. A farmer who understands mechanisms can also generalize more effectively from observed experiments (ex-post learning). If the above farmer observes a high return to a certain amount of potassium supplementation on a high-clay soil, he can extrapolate that the marginal return will be even higher on a gray soil that is low in clays.