Signaling, Random Assignment, and Causal Effect Estimation
Chemla, Gilles (2020), Signaling, Random Assignment, and Causal Effect Estimation, Virtual Finance Theory Seminar, ESCP Europe, 2020-06, Paris, France
TypeCommunication / Conférence
External document linkhttps://ssrn.com/abstract=3688123
Conference titleVirtual Finance Theory Seminar, ESCP Europe
MetadataShow full item record
Dauphine Recherches en Management [DRM]
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 / KeywordsCausal effect; CEO; Corporate Finance; Government Policy; household finance; investment; random assignment; selection, signal
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