Learning about a changing state
Theoretical Economics
2026-01-29 v2
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.
Keywords
Cite
@article{arxiv.2401.03607,
title = {Learning about a changing state},
author = {Benjamin Davies},
journal= {arXiv preprint arXiv:2401.03607},
year = {2026}
}
Comments
23 pages; 2 figures. V2 fixes typos/grammar, adds some references, and removes some footnotes