Reputation, Exposure, and Exit: Organizational Turnover after #MeToo

This paper provides causal evidence that the #MeToo movement acted as an economy-wide reputational shock, triggering significantly higher board and executive turnover at firms with greater pre-existing exposure to governance risks through dynamic, belief-driven resignation mechanisms.

The Gist

Imagine the corporate world as a giant, bustling city of skyscrapers. Inside these buildings sit the "boards of directors"—the people in charge who make sure the company runs well. Usually, these directors stay put unless the building is on fire (the company is failing) or they decide to move to a better job.

Then, in October 2017, a massive earthquake hit the city. This wasn't a physical earthquake, but the #MeToo movement, sparked by revelations about Harvey Weinstein. Suddenly, the entire city's atmosphere changed. The "air" became thick with a new kind of scrutiny. People started paying much closer attention to how leaders behaved, and the social cost of bad behavior skyrocketed.

This paper asks a simple question: Did this earthquake shake the foundations of the corporate buildings, causing more directors to jump ship?

Here is the breakdown of what the authors found, using simple analogies:

1. The "Glass House" vs. The "Fortress"

The researchers realized that not all buildings were equally affected by the earthquake.

• The Glass Houses: Some companies were already very transparent. They frequently filed public reports (called "Item 5.02" forms) about leadership changes, even before the earthquake. These companies were like glass houses; everyone could see inside, and they were used to being watched.
• The Fortresses: Other companies rarely filed these reports. They were like fortresses with thick walls; what happened inside stayed inside.

The authors hypothesized that when the earthquake hit, the Glass Houses would shake much harder. Because they were already used to being watched, the new, stricter social norms would make their directors feel much more nervous about staying. The Fortresses, being less exposed to public scrutiny, wouldn't feel the tremors as intensely.

2. The "Alarm System" Theory

The paper uses a clever theory to explain why this happened. Imagine every director has an internal alarm system.

• Before the earthquake: The alarm only went off if someone actually committed a crime or the company was losing money.
• After the earthquake: The alarm system got a software update. Now, it goes off not just for crimes, but for anyone who might be a reputational risk.

The directors in the "Glass Houses" had their alarms turned up to maximum volume. They realized that staying in a company that might have a problem was now too dangerous. So, they started leaving in droves, not necessarily because they knew a specific crime happened, but because the risk of staying had become too high.

3. The Ripple Effect

The study found that this wasn't just a one-day panic.

• The Initial Shock: Right after the movement started, the Glass Houses saw a massive spike in directors quitting.
• The Long Tail: This didn't stop after a month. The directors kept leaving for years. It was like a slow-motion domino effect. One person leaving made the next person nervous, who then left, which made the next person nervous, and so on.
• The "Who" and "Where": The effect was strongest in industries where reputation is everything (like media, entertainment, and consumer goods). If your business relies on people liking you, you can't afford a bad reputation. In these sectors, the "Glass Houses" saw the most turnover.

4. What the Data Actually Says

The researchers looked at thousands of companies over several years. They didn't find proof that every company that lost a director was hiding a secret scandal. Instead, they found a pattern:

• Companies that were already used to being watched (high exposure) saw a much bigger increase in directors quitting after #MeToo started.
• Companies that were less used to being watched saw a smaller increase.

The Big Takeaway

The paper concludes that social movements can change how companies work, even without passing a single new law.

Think of it like a change in the weather. Before, it was okay to wear a light jacket. After the "storm" of #MeToo, everyone realized that if you wore a light jacket, you might get soaked and shamed. So, even if you weren't the one who got caught in the rain, you put on a heavy coat (or left the party entirely) just to be safe.

The #MeToo movement didn't just expose bad apples; it changed the rules of the game. It made the "cost" of staying in a potentially risky leadership position so high that even good directors decided it was time to leave, especially if their company was already under the microscope.

In short: The movement acted like a giant spotlight. Companies that were already standing in the light (high exposure) felt the heat the most and saw the most people walking out the door.

Technical Summary

Technical Summary: Reputation, Exposure, and Exit: Organizational Turnover after #MeToo

Problem and Motivation
The paper investigates how economy-wide reputational shocks reshape corporate governance, specifically focusing on board and executive turnover following the #MeToo movement. The authors conceptualize the October 2017 revelations surrounding Harvey Weinstein not merely as a sequence of specific misconduct allegations, but as a common informational and reputational shock that altered the expected costs of organizational inaction and intensified scrutiny across the entire corporate sector.

A central identification challenge arises because the shock was economy-wide; there is no natural untreated control group of firms unaffected by the movement. Furthermore, securities laws (specifically Item 5.02 of Form 8-K) require firms to disclose departures but do not mandate disclosure of the reasons, making it impossible to attribute specific exits to sexual misconduct. Consequently, the paper asks whether firms with greater pre-existing exposure to governance-sensitive disclosure environments experienced systematically larger changes in exit behavior after the movement altered accountability norms, rather than attempting to link departures to specific revealed misconduct.

Theoretical Framework
The authors develop a structural model of board resignation based on dynamic discrete choice, Bayesian belief updating, and hazard-based exit behavior.

• Mechanism: Directors face a trade-off between the benefits of board membership (compensation, prestige) and the expected costs of affiliation (reputational risk, legal liability). The #MeToo movement is modeled as a structural break that increases both the aggregate reputational price of adverse information ($\rho_t$) and the precision of public signals regarding organizational vulnerability ($\kappa_t$).
• Exposure Heterogeneity: The model posits that firms differ in their "exposure" ($\phi_i$), defined as their sensitivity to governance-related reputational risk. High-exposure firms (those with histories of frequent governance disclosures or complex structures) experience a larger marginal increase in expected costs when the reputational price rises.
• Strategic Interaction: The model incorporates strategic complementarities, where the resignation of one director increases the reputational pressure and exit hazard for remaining directors, potentially leading to self-reinforcing waves of turnover.
• Prediction: The model predicts that a common reputational shock will generate heterogeneous organizational responses, with high-exposure firms experiencing significantly larger increases in resignation intensity compared to low-exposure firms.

Methodology and Identification
To address the lack of a control group, the authors employ a continuous-treatment difference-in-differences (DiD) design.

• Treatment Intensity: Instead of a binary treatment, the "intensity" of the shock is proxied by a firm's pre-shock exposure. This is measured by the frequency of Item 5.02 Form 8-K filings (governing leadership departures) prior to October 2017. This measure is predetermined and captures ex ante organizational susceptibility to reputational pressure.
• Outcome Variable: The dependent variable is the log of cumulative resignation intensity (board and executive departures) at the firm-month level.
• Estimation Strategy:
  1. Baseline DiD: A dynamic specification with firm and month fixed effects, including lags of the outcome to account for persistence.
  2. Event Study: To test for pre-trends and examine the dynamic evolution of effects.
  3. Dynamic Matrix Completion: Following Athey et al. (2021), the authors use matrix completion to reconstruct counterfactual untreated outcomes. This relaxes the parallel trends assumption by allowing for latent, low-rank interactive structures in the data, accommodating complex heterogeneity in organizational trajectories.
  4. Inference: The study utilizes firm-clustered standard errors and wild-cluster bootstrap procedures (up to 1,000 replications) to ensure robustness against serial dependence and finite-sample distortions.

Data
The analysis utilizes a hand-collected dataset of 3,841 leadership-change disclosures from S&P 500 firms between 2016 and 2023. The sample includes 51,791 firm-month observations across 498 firms. The data captures various dimensions of turnover, including voluntary vs. forced resignations, board member departures, and specific executive roles (CFOs, VPs, female executives).

Key Results

1. Positive Exposure Gradient: Firms with higher pre-shock exposure (higher frequency of pre-2017 Item 5.02 filings) experienced significantly larger increases in resignation intensity following the #MeToo shock. The preferred saturated specification (including firm, industry, and month fixed effects) estimates a 12% to 13% increase in resignation intensity for exposed firms relative to less exposed firms.
2. Persistence: The effects are not transitory. Dynamic estimates show that the increase in resignation intensity persists for multiple years (up to 50 months in matrix completion estimates) before gradually attenuating, suggesting a process of sustained organizational adaptation rather than a temporary media reaction.
3. Mechanisms: The increase in turnover is driven by multiple channels:
   • Forced Departures: A ~19% increase, indicating heightened disciplinary governance.
   • Voluntary Resignations: A ~13.5% increase, suggesting anticipatory exits due to reputational self-insurance.
   • Board Turnover: A ~14% increase, indicating restructuring of oversight mechanisms.
   • Demographic and Role Specificity: Significant increases in turnover for female executives, CFOs, and VPs, as well as an increase in allegation-related disclosures.
4. Sectoral Heterogeneity: The effects are heterogeneous across sectors. Communication Services, Energy, and Consumer Staples show the strongest responses, consistent with sectors where reputation and public scrutiny are critical assets. However, the effect remains statistically significant even when excluding these high-impact sectors, indicating a broad-based organizational response.

Claims of Significance
The paper makes two principal contributions:

1. Substantive Contribution to Governance Literature: It provides causal evidence that social movements, even without changing formal corporate law, can alter corporate behavior by shifting accountability norms. The findings demonstrate that reputational shocks operate through mechanisms extending beyond individual misconduct, inducing systematic restructuring across governance layers (boards, management, compliance) in firms with latent vulnerabilities.
2. Methodological Contribution: The paper advances the study of common shocks by utilizing an exposure-based continuous-treatment design. It demonstrates how pre-treatment textual data from mandatory disclosures can be used to construct a predetermined measure of organizational vulnerability, allowing for the identification of heterogeneous responses to economy-wide informational events.

The authors conclude that the #MeToo movement acted as a large-scale informational shock that changed the "expected cost" of retaining executives in vulnerable organizational environments. The results suggest that information and reputational pressure can function as powerful mechanisms of institutional change, altering internal governance structures even in the absence of new regulations.