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Learning through Noticing: Theory and Experimental Evidence in Farming

  • Hanna, Rema

    (Harvard University)

  • Mullainathan, Sendhil

    (Harvard University)

  • Schwartzstein, Joshua

    (Dartmouth College)

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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Paper provided by Harvard University, John F. Kennedy School of Government in its series Working Paper Series with number rwp12-044.

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Date of creation: Oct 2012
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Handle: RePEc:ecl:harjfk:rwp12-044
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  15. Paul Niehaus, 2011. "Filtered Social Learning," Journal of Political Economy, University of Chicago Press, vol. 119(4), pages 686 - 720.
  16. Xavier Gabaix, 2011. "A Sparsity-Based Model of Bounded Rationality," NBER Working Papers 16911, National Bureau of Economic Research, Inc.
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