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Discussion Paper Details

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Title: Signaling, Random Assignment, and Causal Effect Estimation

Author(s): Gilles Chemla and Christopher Hennessy

Publication Date: August 2020

Keyword(s): Causal effect, CEO, Corporate Finance, Government Policy, household finance, investment, random assignment, selection and signal

Programme Area(s): Development Economics, Financial Economics, Industrial Organization, Labour Economics and Public Economics

Abstract: 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.

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Bibliographic Reference

Chemla, G and Hennessy, C. 2020. 'Signaling, Random Assignment, and Causal Effect Estimation'. London, Centre for Economic Policy Research. https://cepr.org/active/publications/discussion_papers/dp.php?dpno=15175