Workers’ Voices Matter: Crowdsourced Employee Reviews and Insider Trading
Yifei Chen & Dan Palmon
Abstract
This study investigates the influence of crowdsourced employee reviews on insider trading behavior. Leveraging the staggered timing of first‐time employee reviews about their employers on Glassdoor.com, we employ a stacked difference‐in‐differences (DID) model comparing firms with review initiations to those without reviews during the same period. Our findings reveal a statistically and economically significant decrease in insider trading activities for firms with review initiations. The results hold across a series of robustness tests, including propensity score matching, entropy balancing, and alternative time windows for the DID setting. Further analyses suggest that insiders scale back their informed trading activities and earn lower abnormal trading profits following review initiations. The effect is stronger for firms with higher litigation risk, greater reputational cost, stronger labor market pressure, recent employee exploitation incidents, and when the reviews are more negative. Overall, these findings suggest that crowdsourced employee reviews discipline unethical insider trading behavior.
Evidence weight
Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40
| F · citation impact | 0.50 × 0.4 = 0.20 |
| M · momentum | 0.50 × 0.15 = 0.07 |
| V · venue signal | 0.50 × 0.05 = 0.03 |
| R · text relevance † | 0.50 × 0.4 = 0.20 |
† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.