Attention is a scarce resource

I think this is important in many contexts (not just farming). For example, to harp on some of our recent themes, I don't think that most people are aware of how much their productivity falls when their temperature rises or how much quicker they are to anger when their environment is uncomfortable. My guess is that most people know that these kinds of things are issues, in some sort of qualitative story-like sense, but that they don't have any idea about the quantitative size of the effect -- and they certainly don't optimize their lifestyle by taking these things into account.

In an example I was just mentioning to a colleague: I was recently trying to sell two air-conditioning units to students from my PhD program (most of whom know about my work on temperature and productivity). At $50 a unit, buying one of these as an investment would have paid for itself in productivity after one or two hot days.  But I couldn't sell the ACs until I dropped the price and just gave them away!  Despite knowing that it will dramatically improve their productivity, even students trained to think about these problems will make mistakes in the optimization of their lifestyle. (Although, it's also possible that in this case the students were colluding to get me to lower the price...) Enough editorializing, here's the paper:

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.

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