Learning about a changing state

Benjamin Davies

Papers from arXiv.org

Abstract: A long-lived Bayesian agent observes costly signals of a time-varying state. He chooses the signals' precisions sequentially, balancing their costs and marginal informativeness. I compare the optimal myopic and forward-looking precisions when the state follows a Brownian motion. I also compare the myopic precisions induced by other Gaussian processes.

Date: 2024-01
New Economics Papers: this item is included in nep-mic
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