Working Paper: NBER ID: w18401
Authors: Rema Hanna; Sendhil Mullainathan; Joshua Schwartzstein
Abstract: Existing learning models attribute failures to learn to a lack of data. We model a different barrier. Given the large number of dimensions one could focus on when using a technology, people may fail to learn because they failed to notice important features of the data they possess. We conduct a field experiment with seaweed farmers to test a model of "learning through noticing". We find evidence of a failure to notice: On some dimensions, farmers do not even know the value of their own input. Interestingly, trials show that these dimensions are the ones that farmers fail to optimize. Furthermore, consistent with the model, we find that simply having access to the experimental data does not induce learning. Instead, farmers change behavior only when presented with summaries that highlight the overlooked dimensions. We also draw out the implications of learning through noticing for technology adoption, agricultural extension, and the meaning of human capital.
Keywords: Learning; Farming; Technology Adoption; Field Experiment; Selective Attention
JEL Codes: D83; J24; J43; O33
Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.
| Cause | Effect |
|---|---|
| Failure to notice critical dimensions (L68) | Barrier to learning (I24) |
| Farmers' beliefs about dimensions that matter (Q15) | Inattentiveness to critical inputs (D91) |
| Learning through noticing (C45) | Effective technology adoption and optimization in farming practices (Q16) |
| Farmers' inattentiveness to critical dimensions of production processes (Q12) | Suboptimal choices and learning failures (D91) |
| Presenting summarized trial results (Y10) | Change in farmers' methods (Q15) |