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Banerjee, Abhijit; Breza, Emily; Chandrasekhar, Arun G.; Mobius, Markus – National Bureau of Economic Research, 2019
The DeGroot model has emerged as a credible alternative to the standard Bayesian model for studying learning on networks, offering a natural way to model naive learning in a complex setting. One unattractive aspect of this model is the assumption that the process starts with every node in the network having a signal. We study a natural extension…
Descriptors: Alternative Assessment, Bayesian Statistics, Incidental Learning, Networks

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