Signaling, Random Assignment, and Causal Effect Estimation
Chemla, Gilles; Hennessy, Christopher A. (2020), Signaling, Random Assignment, and Causal Effect Estimation, Collaborative Research Center Transregio 224 Economics Seminar, 2020-12, Mannheim / Online, Germany
TypeCommunication / Conférence
Conference titleCollaborative Research Center Transregio 224 Economics Seminar
Conference cityMannheim / Online
MetadataShow full item record
Dauphine Recherches en Management [DRM]
Hennessy, Christopher A.
London Business School
Abstract (EN)Causal evidence from random assignment has been labeled "the most credible." We argue it is generally incomplete in finance/economics, omitting central parts of the true empirical causal chain. Random assignment, in eliminating self-selection, simultaneously precludes signaling via treatment choice. However, outside experiments, agents enjoy discretion to signal, thereby causing changes in beliefs and outcomes. Therefore, if the goal is informing discretionary decisions, rather than predicting outcomes after forced/mistaken actions, randomization is problematic. As shown, signaling can amplify, attenuate, or reverse signs of causal effects. Thus, traditional methods of empirical finance, e.g. event studies, are often more credible/useful.
Subjects / KeywordsCorporate Finance; Government Policy; household finance; investment; random assignment
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