Gradual learning from incremental actions
Loading...
Access rights
openAccess
CC BY-NC
CC BY-NC
publishedVersion
URL
Journal Title
Journal ISSN
Volume Title
A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä
This publication is imported from Aalto University research portal.
View publication in the Research portal (opens in new window)
View/Open full text file from the Research portal (opens in new window)
View publication in the Research portal (opens in new window)
View/Open full text file from the Research portal (opens in new window)
Authors
Date
Department
Major/Subject
Mcode
Degree programme
Language
en
Pages
38
Series
Theoretical Economics, Volume 20, issue 1, pp. 93-130
Abstract
We introduce a collective experimentation problem where a continuum of agents choose the timing of irreversible actions under uncertainty and where public feedback from the actions arrives gradually over time. The leading application is the adoption of new technologies. The socially optimal expansion path entails an informational trade-off where acting today speeds up learning but postponing capitalizes on the option value of waiting. We contrast the social optimum to the decentralized equilibrium where agents ignore the social value of information they generate. We show that the equilibrium can be obtained by assuming that agents ignore the future actions of other agents, which lets us recast the complicated two-dimensional problem as a series of one-dimensional problems.Description
Publisher Copyright: Copyright © 2025 The Authors.
Keywords
Other note
Citation
Laiho, T, Murto, P & Salmi, J 2025, 'Gradual learning from incremental actions', Theoretical Economics, vol. 20, no. 1, pp. 93-130. https://doi.org/10.3982/TE5452