Gradual learning from incremental actions

Tuomas Laiho (), Pauli Murto () and Julia Salmi ()
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Tuomas Laiho: Department of Economics, Aalto University School of Business and Ministry of Finance, Finland
Pauli Murto: Department of Economics, Aalto University School of Business and Helsinki Graduate School of Economics
Julia Salmi: Department of Finance and Economics, Hanken School of Economics and Helsinki Graduate School of Economics

Theoretical Economics, 2025, vol. 20, issue 1

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.

Keywords: Social learning; experimentation; optimal stopping; technology adoption (search for similar items in EconPapers)
JEL-codes: C61 C73 D82 D83 (search for similar items in EconPapers)
Date: 2025-01-28
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