Journal Of The Econometric Society

An International Society for the Advancement of Economic
Theory in its Relation to Statistics and Mathematics

Edited by: Guido W. Imbens • Print ISSN: 0012-9682 • Online ISSN: 1468-0262

Econometrica: Nov, 2017, Volume 85, Issue 6

Progressive Learning
p. 1965-1990

Avidit Acharya, Juan Ortner

We study a dynamic principal–agent relationship with adverse selection and limited commitment. We show that when the relationship is subject to productivity shocks, the principal may be able to improve her value over time by progressively learning the agent's private information. She may even achieve her first‐best payoff in the long run. The relationship may also exhibit path dependence, with early shocks determining the principal's long‐run value. These findings contrast sharply with the results of the ratchet effect literature, in which the principal persistently obtains low payoffs, giving up substantial informational rents to the agent.

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Supplemental Material

Supplement to "Progressive Learning"

This Online Appendix to the paper titled “Progressive Learning” presents the proof of Lemma 0, an extension of our equilibrium characterization allowing for mixed strategies, an analysis of the full commitment case, and details for Example 4 showing that path dependence can arise when shocks are ergodic.