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Keeping in the dark with hard evidence

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Abstract

We present a dynamic learning setting in which the periodic data observed by the decision-maker is mediated by an agent. We study when, and to what extent, this mediation can distort the decision-maker’s long-run learning, even though the agent’s reports are restricted to consist of verifiable hard evidence and must adhere to certain standards. We introduce the manipulation-proof law of large numbers – that delivers a sharp dichotomy: when it holds, the decision-maker’s learning is guaranteed in the long-run; when it fails, the scope for manipulation is essentially unrestricted.

Suggested Citation

  • Daniel Bird & Alexander Frug, 2025. "Keeping in the dark with hard evidence," Economics Working Papers 1927, Department of Economics and Business, Universitat Pompeu Fabra.
    • Handle: RePEc:upf:upfgen:1927
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    1. , & ,, 2006. "A study in the pragmatics of persuasion: a game theoretical approach," Theoretical Economics, Econometric Society, vol. 1(4), pages 395-410, December.
    2. Krishna, Vijay & Morgan, John, 2004. "The art of conversation: eliciting information from experts through multi-stage communication," Journal of Economic Theory, Elsevier, vol. 117(2), pages 147-179, August.
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    JEL classification:

    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness

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