Observational Learning with a Budget

• URL: http://arxiv.org/abs/2504.19396v1
• Date: Mon, 28 Apr 2025 00:12:30 GMT
• Title: Observational Learning with a Budget
• Authors: Shuo Wu, Pawan Poojary, Randall Berry,
• Abstract summary: We consider a model of observational learning in which a sequence of agents receives a private signal about an underlying binary state of the world.<n>A central planner seeks to improve the accuracy of these signals by allocating a limited budget to enhance signal quality across agents.
• Score: 0.3499870393443268
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: We consider a model of Bayesian observational learning in which a sequence of agents receives a private signal about an underlying binary state of the world. Each agent makes a decision based on its own signal and its observations of previous agents. A central planner seeks to improve the accuracy of these signals by allocating a limited budget to enhance signal quality across agents. We formulate and analyze the budget allocation problem and propose two optimal allocation strategies. At least one of these strategies is shown to maximize the probability of achieving a correct information cascade.

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