
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
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Type
Communication / ConférenceDate
2020Conference title
Collaborative Research Center Transregio 224 Economics SeminarConference date
2020-12Conference city
Mannheim / OnlineConference country
GermanyMetadata
Show full item recordAuthor(s)
Chemla, GillesDauphine 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 / Keywords
Corporate Finance; Government Policy; household finance; investment; random assignmentRelated items
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