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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

Type
Communication / Conférence
External document link
https://ssrn.com/abstract=3688123
Date
2020
Conference title
Virtual Finance Theory Seminar, ESCP Europe
Conference date
2020-06
Conference city
Paris
Conference country
France
Metadata
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Author(s)
Chemla, Gilles
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 / Keywords
Causal effect; CEO; Corporate Finance; Government Policy; household finance; investment; random assignment; selection, signal
JEL
D82 - Asymmetric and Private Information; Mechanism Design
G14 - Information and Market Efficiency; Event Studies; Insider Trading
G18 - Government Policy and Regulation
G28 - Government Policy and Regulation
J24 - Human Capital; Skills; Occupational Choice; Labor Productivity

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