DP15175 Signaling, Random Assignment, and Causal Effect Estimation

Author(s): Gilles Chemla, Christopher Hennessy
Publication Date: August 2020
Keyword(s): Causal effect, CEO, Corporate Finance, Government Policy, household finance, investment, random assignment, selection, signal
JEL(s): D82, E6, G14, G18, G28, G3, J24
Programme Areas: Labour Economics, Public Economics, Financial Economics, Industrial Organization, Development Economics
Link to this Page: cepr.org/active/publications/discussion_papers/dp.php?dpno=15175

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.