Causal Persuasion

Anastasia Burkovskaya and Egor Starkov

Papers from arXiv.org

Abstract: Correlation is not causation... until the right variables are on the table. We propose a model of causal persuasion, in which a sender selectively discloses variables alongside a subjective causal model linking them. Persuasion requires that the model rules out rival explanations, on top of being consistent with the underlying data distribution. To establish a causal link, the sender often needs to disclose at most two well-chosen variables, whereas dispelling a perceived link, every common cause must be disclosed. This highlights a fundamental asymmetry: Establishing causality is often much easier than ruling it out.

Date: 2026-04, Revised 2026-09
New Economics Papers: this item is included in nep-gth
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