This paper provides an alternative explanation on the mechanisms from which learning failures occur. The previous literature has focused on data availability and suggested only insufficient information led to learning failures. Hanna et al. show, besides data limitations, that they stem from limited attention on the key features of the available data. Using Schwartzstein’s (2014) model of selective attention, the authors build a model of learning by attending and test its predictions with seaweed farmers. Their model shows that farmers failed to optimize the input dimensions they do not notice but making them realize the underlying overlapping of these dimensions helps them adjust their input choices.
The contribution of this paper has important implications on the use of information to break down learning failures and experience: getting used to a technology (experience) or learning a new one (more data) do not guarantee special attention to intrinsic aspects that might be important in the learning process.
A must read.
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