Two-Sided Learning and the Ratchet Principle
Review of Economic Studies, 2018, vol. 85, issue 1, 307-351
I study a class of continuous-time games of learning and imperfect monitoring. A long-run player and a market share a common prior about the initial value of a Gaussian hidden state, and learn about its subsequent values by observing a noisy public signal. The long-run player can nevertheless control the evolution of this signal, and thus affect the market’s belief. The public signal has an additive structure, and noise is Brownian. I derive conditions for an ordinary differential equation to characterize equilibrium behavior in which the long-run player’s actions depend on the history of the game only through the market’s correct belief. Using these conditions, I demonstrate the existence of pure-strategy equilibria in Markov strategies for settings in which the long-run player’s flow utility is nonlinear. The central finding is a learning-driven ratchet principle affecting incentives. I illustrate the economic implications of this principle in applications to monetary policy, earnings management, and career concerns.
Keywords: Learning; Private beliefs; Ratchet effect; Brownian motion (search for similar items in EconPapers)
JEL-codes: C73 D82 D83 (search for similar items in EconPapers)
References: Add references at CitEc
Citations View citations in EconPapers (1) Track citations by RSS feed
Downloads: (external link)
Access to full text is restricted to subscribers.
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
Persistent link: https://EconPapers.repec.org/RePEc:oup:restud:v:85:y:2018:i:1:p:307-351.
Access Statistics for this article
Review of Economic Studies is currently edited by Andrea Prat, Bruno Biais, Kjetil Storesletten and Enrique Sentana
More articles in Review of Economic Studies from Oxford University Press
Bibliographic data for series maintained by Oxford University Press ().