Keeping in the Dark with Hard Evidence

Daniel Bird and Alexander Frug

No 1534, Working Papers from Barcelona School of Economics

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.

Keywords: long-run beliefs; manipulation; selective forced disclosure (search for similar items in EconPapers)
JEL-codes: D83 (search for similar items in EconPapers)
Date: 2025-11
New Economics Papers: this item is included in nep-mic
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