Abstract
It is widely recognized that workplace sexual harassment has significant negative psychological and personal consequences, and employees facing harassment suffer reductions in productivity. Our contribution is to propose a novel measure of workplace sexual harassment risk and provide a fuller estimation of the firm value impact of sexual harassment. In contrast to recent studies that focus on short-run market reactions to media announcements of harassment scandals, we use employee job reviews to identify low-profile harassment incidents that better reflect the pervasive, toxic environment pertaining to sexual harassment than do newsworthy scandals, and we measure the longer-term effect on firm value starting from the date when harassment risk affects employee morale. We identify firm harassment risk by analyzing employee job reviews and estimate the sexual harassment score (SH) through textual analysis of online job reviews. Our sample of high-SH firms, or firms with unusually high-SH scores, exhibits significant reductions in future stock performance and profitability. For example, firms with a top 2% SH score earn a value-weighted risk-adjusted stock return of − 17% in the 1-year period after high-SH classification, and this damage is concentrated in firms with higher investor attention. Furthermore, high-SH firms experience a decline in operating profitability and an increase in labor costs during a 5-year period around high-SH classification. Our evidence suggests that sexual harassment can cause greater damages to firm value than previously documented.
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Notes
Even though there is no standard definition of “long-term” effects in finance research, the literature typically treats one year or above as long-term (e.g., Ma et al., 2019). We find the effect on stock returns disappears after 1 year, although the effect on operating profitability takes longer to disappear.
The accounting and finance literatures document that market reactions persist long after initial corporate events. For example, the post-earnings announcement drift lasts for several quarters after the earnings release (Bernard & Thomas, 1989) and the short-run acquirer announcement returns do not reflect the long-run, multiyear acquirer stock abnormal returns (Ben-David et al., 2022).
Title VII is the federal law that protects against sexual harassment, and the $300,000 cap on damages was instituted as part of the Civil Rights Act of 1991; see https://www.eeoc.gov/remedies-employment-discrimination.
One could also argue that sexual harassment may affect a relatively low-hierarchy workforce and therefore has an inconsequential economic impact, despite the negative perception on employees.
In a perfectly efficient market, stock prices immediately react to new information including expected future operating profitability. With the presence of market frictions and investor biases, stock prices tend to underreact to intangibles such as toxic culture. Because we find it takes up to one year for the stock market to react to sexual harassment information, and since accounting metrics respond more slowly than stock prices, we use a five-year window to capture the influence of sexual harassment on accounting performance.
There are sparse sexual harassment reviews in 2011 and 2012, and therefore very few high-SH firms in those two years. Our results remain if we remove 2011 and 2012 observations from the sample (results untabulated).
For ease of comparison with our main results (Table 3), Table IA.3 presents results with alternative filters.
This review is for Visa, Inc., published on 9/11/2017.
Because as pointed out by the EEOC, the definition of sexual harassment is independent of the sex, gender, or job status of both the plaintiff and the perpetrator, we do not control for these characteristics, because the victims or plaintiffs only need to show that a reasonable person who shares the perspective of the victim would also consider the behavior as abusive or offensive (Schneider et al., 2010).
Table 2 also shows that reports of sexual harassment on social media predate the October 2017 #MeToo movement (Tarana Burke created the Me Too movement in 2006). Because our return tests do not consider reviews published after June 2017, our results cannot be attributed to the surge in denunciations triggered by the #MeToo movement.
We do not rule out the possibility that some employees report fake harassment incidences. However, both Glassdoor and Indeed use filters (undisclosed to the public) to ensure that reviews are authentic. Moreover, fake reports should introduce noise to the SH score and weaken its return predictability. The high magnitude of SH-related abnormal returns we document suggests that such fake reporting is inconsequential.
The finding that the long side of the hedge portfolio, which is the vast majority of the sample firms, earns a moderately and significantly positive alpha, is related to sample selection; we restrict our sample firms to have a minimum of 200 reviews and these firms tend to perform slightly better than the CRSP value-weighted index. Defining low-SH firms differently, e.g., as those with a zero SH score, does not alter results.
The literature (e.g., Li & Nagar, 2013) typically multiplies the monthly alpha (\(\alpha\)) by 12 to get the annualized alpha. This simplified annualization leads to large errors when applied to negative \(\alpha\). Instead, our annualized alpha is \({(1+\alpha )}^{12}-1.\)
The HiSH effect remains if we use the ex ante, year-over-year change in (rather than the level of) Star, or its five subcategories, in the Fama–MacBeth return regressions.
One result of Table 4 is the insignificance of previously identified return predictors such as size, book-to-market, and BC, which aligns with other research (Green et al., 2019; McLean & Pontiff, 2016). In unreported tests, we run regressions of monthly return on size, value and momentum only, over July 1963-December 2013, and find significant size, value and momentum effects on returns, similar to those reported by Fama and French (2015).
The corporate violation data are from The Violation Tracker, available from https://www.goodjobsfirst.org/violation-tracker. It tracks a wide variety of regulatory violations or crimes that firms have been sanctioned for, including employment discrimination, labor relations violations, violations to the Family and Medical Leave Act, and workplace whistleblower retaliation, among others.
In untabulated tests, we do not find a significant interaction effect of HiSH * SVI on five-year change in ROA or ROE, indicating that high investor attention speeds up market reaction on harassment issues, but does not affect accounting profitability.
Due to the rarity of reporting of Settle, the HiSH_98 and HiSH_99 definitions return the same sample.
These data are collected by the EEOC from any private employer with more than 100 employees, and is compiled by industry. We retrieve the data from: https://www.eeoc.gov/statistics/employment/jobpatterns/eeo1.
In untabulated tests, we find similar results if the control firms are matched on ROA in year t – 1 instead of the change in ROA from t – 2 to t – 1. For each firm in year t, we need 2 years of past data and 2 years of future data. This lowers the number of observations for both the treated and matched firms, resulting in less than 5 matched firms per treated firm.
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Acknowledgements
We thank the Section Editor (Greg Shailer), two anonymous reviewers, Renee Adams, Marie-Claude Beaulieu, Frederick Bereskin, Philippe Bertrand, Pierre Chaigneau, Samra Chaudary, Douglas Cumming, Rui Dong, Ran Duchin, Marie Dutordoir, Joey Engelberg, Lei Gao, Wenxia Ge, John Griffin, Ben Haimowitz, Joni Hersch, Vince Intintoli, Kiridaran Kanagaretnam, Minzhi Liu, Amin Mawani, Bill McDonald, Moshe Milevsky, Cameron Morrill, Venky Nagar, Lin Peng, Aline Pundrich, Jay Ritter, Elena Simintzi, Piers Steel, Hongping Tan, Siew Hong Teoh, Chris Veld, Adam Yore, Leyuan You, Xinyao Zhou, and seminar participants at University of Manitoba, York University, SCSE conference in Quebec City, CSR across the Atlantic Conference in Boston, EFiC conference at the University of Essex, AFFI conference in Quebec City, CICF conference in Guangzhou, AAA 2020 annual meeting, and FMA 2020 conference for helpful comments, Gady Jacoby and Ursula Mead (CEO of InHerSight.com) for valuable discussions, Benjamin Gahtan for excellent research assistance, and Social Science and Humanities Research Council of Canada (SSHRC) for financial support.
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Appendix A: Variable Definitions
Appendix A: Variable Definitions
Variable | Definition |
|---|---|
Advert | Advertising expenditures (Compustat XAD) scaled by Sales |
AT | Total assets at end of fiscal year adjusted to 2017 dollars using the Consumer Price Index (CPI) |
BC | Indicator variable that is equal to 1 if the firm is on the “100 Best Companies to Work for” list in year t, and zero otherwise |
BM | Ratio of book equity/market capitalization |
Capex | Capital expenditure (Compustat item CAPX) scaled by lagged total assets |
ChgSale | Growth in Sales from year t – 1 to year t |
EEOC_lit | Indicator variable that equals 1 if the firm experiences an EEOC sexual harassment litigation over the previous year |
Ex_ret | Excess monthly stock return over risk free rate |
Firm_Age | Age of firm calculated as the current year less the first year the firm appears in Compustat |
ETKLD | Indicator variable that equals 1 if the firm’s employee treatment score in year t is above the full-sample median. Calculated as per Bae et al. (2011) except the retirement benefits and employee health and safety indicators were discontinued before the sample period begins. Data are from MSCI KLD |
EmpGr | Growth rate of number of employees |
HiSH_9Y | Indicator variable that equals 1 if a firm’s annual SH score is above the 9Yth percentile of the full sample SH distribution in that year. LoSH is an indicator variable that equals 1 if a firm’s annual SH score is below the 9Yth percentile of the full sample SH distribution in that year. Applicable to HiSH_99, HiSH_98, and HiSH_95 |
HR_per | The percentage of top 5 paid executives that have the title “Human Resources,” or “HR” or related titles |
KZ | Kaplan and Zingales (1997) index of financial constraints (the 4-variable definition excluding Tobin’s Q as in Baker et al. (2003)) |
LAB | Annual staff expenses (Compustat item XLR) scaled by lagged total sales |
Law_per | The percentage of top 5 paid executives that have the title “Legal,” or “Counsel” or related titles |
LEV | Leverage defined as total debt (long-term and current) to total assets |
ME | Market capitalization of the firm at the end of June adjusted to 2017 dollars using the CPI |
Mkt_rf | Excess market return over risk-free rate |
NAnalysts | Number of analysts following the firm |
Pension | Pension expenses (Compustat XPR) scaled by sales |
Return -x, -y | Cumulative return from month t – x to month t – y |
ROA | Return on assets. Net Income divided by lagged total assets |
ROE | Return on equity. Net income divided by lagged book value of equity |
Settle | Settlement provision (SETP from Compustat)/lagged total assets |
SH | Percentage of reviews for firm k published in year t that mention sexual harassment, relative to the total number of reviews for firm k published in year t. Measured from July (year t – 1) to June (year t) for stock return tests or over the financial year for accounting profitability tests |
SH_Exp | As SH above, except that this variable uses the expanded word list to measure sexual harassment. See Table IA.12 for the additional words included |
Star | Mean of 5 numerical ratings (job, work, life balance; compensation/benefits; job security; management; job culture) in each review. Each individual rating is out of 5, with 1 being the lowest and 5 being the highest |
SVI | Monthly Search Volume Index (SVI) for each firm’s ticker symbol in the investing subcategory from Google Trends, which measures the search activities of Google users, is a proxy for investor attention, per Da et al. (2011) |
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Au, SY., Dong, M. & Tremblay, A. How Much Does Workplace Sexual Harassment Hurt Firm Value?. J Bus Ethics 190, 861–883 (2024). https://doi.org/10.1007/s10551-023-05335-x
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DOI: https://doi.org/10.1007/s10551-023-05335-x