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Learning in a Bandit Game and Technology Choice

Author

Listed:
  • Kaywana Raeburn
  • Jim Engle-Warnick
  • Sonia Laszlo
  • Jian Li

Abstract

We present a decision-making experiment, conducted in the field, that explores the extent to which learning in a bandit game predicts technology choice on the farm. We find evidence of heterogeneity of learning in the bandit game, including overweighting of winning draws and Bayesian updating. Our results suggest that learners who overweight recent draws are more likely to have adopted new farm crops within the previous year.

Suggested Citation

  • Kaywana Raeburn & Jim Engle-Warnick & Sonia Laszlo & Jian Li, 2016. "Learning in a Bandit Game and Technology Choice," CIRANO Working Papers 2016s-47, CIRANO.
    • Handle: RePEc:cir:cirwor:2016s-47
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    File URL: https://cirano.qc.ca/files/publications/2016s-47.pdf
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    References listed on IDEAS

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    Cited by:

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    2. Holland, Heinrich & Zand-Niapour, Sam, 2017. "Einflussfaktoren der Adoption von "Connected Cars" durch Endnutzer in Deutschland: Eine empirische Untersuchung," UASM Discussion Paper Series 5/2017, University of Applied Sciences Mainz.

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    More about this item

    Keywords

    Bandit Games; Technology Choice; Field Experiment;
    All these keywords.

    JEL classification:

    • C90 - Mathematical and Quantitative Methods - - Design of Experiments - - - General
    • O33 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Technological Change: Choices and Consequences; Diffusion Processes
    • Q16 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - R&D; Agricultural Technology; Biofuels; Agricultural Extension Services

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