Learning from Neighbours

Clicks: 10
ID: 305169
1998
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Abstract
When payoffs from different actions are unknown, agents use their own past experience as well as the experience of their neighbours to guide their decision making. In this paper, we develop a general framework to study the relationship between the structure of these neighbourhoods and the process of social learning. We show that, in a connected society, local learning ensures that all agents obtain the same payoffs in the long run. Thus, if actions have different payoffs, then all agents choose the same action, and social conformism obtains. We develop conditions on the distribution of prior beliefs, the structure of neighbourhoods and the informativeness of actions under which this action is optimal. In particular, we identify a property of neighbourhood structures-local independencewhich greatly facilitates social learning. Simulations of the model generate spatial and temporal patterns of adoption that are consistent with empirical work.
Reference Key
openalex_W2034586501 Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Balasubramanian Venkatesh, Sanjeev Goyal
Journal The Review of Economic Studies
Year 1998
DOI
10.1111/1467-937x.00059
URL
https://doi.org/10.1111/1467-937x.00059
Keywords Keywords not found

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