Learning from Self and Learning from Others
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World Bank, Washington, DC
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Can decentralizing demonstration
accelerate learning about new technologies This paper
randomizes access to a fixed demonstration kit for new
flood-saline-resilient seeds across villages in Bangladesh,
with demonstration either by a single farmer or spread
across many farmers. In the short run, higher learning from
self and others under decentralization increases technology
adoption. In the long run, the impacts of any demonstration
persist, but the additional impacts of decentralization
vanish. A Bayesian model of learning the returns to a new
technology suggests belief dispersion caused noisy adoption
along the learning path, and farmers’ expected gains from
demonstration are four times higher under decentralization.
Palabras clave
AGRICULTURAL EXTENSION, DEMONSTRATION PLOT, SALINE-RESISTANT SEED, AGRICULTURAL TECHNOLOGY ADOPTION, BAYESIAN LEARNING MODEL, TEACHING FARM METHODS
