Implementing Evidence Acquisition: Time Dependence in Contracts for Advice

Yingkai Li and Jonathan Libgober

Papers from arXiv.org

Abstract: An expert with no inherent interest in an unknown binary state can exert effort to acquire a piece of falsifiable evidence informative of it. A designer can incentivize learning using a mechanism that provides state-dependent rewards within fixed bounds. We show that eliciting a single report maximizes information acquisition if the evidence is revealing or its content predictable. This conclusion fails when the evidence is sufficiently imprecise, the failure to find it is informative, and its contents could support either state. Our findings shed light on incentive design for consultation and forecasting by showing how learning dynamics qualitatively shape effort-maximizing contracts.

Date: 2023-10, Revised 2024-09
New Economics Papers: this item is included in nep-gth and nep-mic
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://arxiv.org/pdf/2310.19147 Latest version (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:arx:papers:2310.19147

Access Statistics for this paper

More papers in Papers from arXiv.org
Bibliographic data for series maintained by arXiv administrators ().