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The Effects and the Mechanisms of Board Gender Diversity: Evidence from Financial Manipulation

Abstract

This study examines the impact of board gender diversity on financial misconduct. The findings suggest firms with gender-diverse boards commit fewer financial reporting mistakes and engage in less fraud. The findings hold after accounting for the potentially endogenous nature of board demographic characteristics via instrumental variable approach. Furthermore, the findings are consistent in pre- and post-regulation (Sarbanes–Oxley) periods and hold for firms with good and bad governance. The findings do not seem driven by differences in effort or quality, in terms of independence and expertise, of female and male directors. The benefit derived from increasing the number of female directors on corporate boards seems to diminish at higher levels of gender diversity, indicating that impact of gender diversity on decreasing the likelihood of financial misconduct may be a result of a change to board group dynamics.

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Notes

  1. 1.

    Policy Brief #106 by Brookings Institution quantifies the economic impact of fraud on the US economy and finds that financial scandals cost the economy $35 billion, equivalent to 34% of the GDP.

  2. 2.

    See, for instance, Feroz et al. (1991), Palmrose and Scholz (2004), Srinivasan (2005), Desai et al. (2006), Hennes et al. (2008), Karpoff et al. (2008), Files et al. (2009), Collins et al. (2009), and Murphy et al. (2009)..

  3. 3.

    Conversely, similar outcomes should theoretically be observed in firms whose boards are composed of majority female directors where at least some directors are male. Since there are virtually no such boards, it is not possible to test the symmetry of the gender ratio and its effect on accounting outcomes.

  4. 4.

    Audit Integrity is the former name of a database currently owned by GMI.

  5. 5.

    It is important to note only true restatements are considered, not restatements due to changes in accounting pronouncements.

  6. 6.

    This timing ensures the restatement event is attributed to the board which oversaw the financial reporting process review at the time, not to the board which subsequently discovered and/or corrected the issue. .

  7. 7.

    Prior literature suggests that the Blau index may be a better measure to capture diversity. Untabulated tests suggest all results hold if the Blau diversity measure is used instead of the other two measures presented in the tables.

  8. 8.

    Conceptually, there is little reason to believe the size of the female population at a firm’s headquarter location and the geographic longitude of the firm’s headquarters would be correlated with restatement patterns directly, or in any other way other than through the instrumented variable.

  9. 9.

    Evaluated at means of all covariates.

  10. 10.

    Stock and Yogo (2005) confirm the Staiger and Stock (1997) rule of thumb approach is appropriate for determining weak instruments in situations where there are fewer than 3 instruments used. .

  11. 11.

    The univariate test in Panel B is similar to the fixed effect analysis in Panel A with one notable exception. Unlike the firm-fixed effect analysis which controls for invariant fixed characteristics while assuming no significant time trends affecting firms, the analysis in Panel B relaxes the assumption little by limiting the within-firm variance to 2 years before and after. In other words, to the extent that there is a trend to improve governance during the decade, which firm-fixed effects would not control for, the analysis in Panel B would mitigate the concern partially by only including one closest observation for each firm i (within the 2 years before or after period), therefore limiting the impact of concurrent governance or other changes impacting the firm’s likelihood of restatements.

  12. 12.

    AGR (as formerly known) used to produce governance and accounting risk rating. The ratings assigned each firm to a low/medium risk group or a high risk group, based on governance and accounting policies in place at the firm for the year. Since, AGR has been acquired by GMI Ratings and the nature of the ratings may have changed.

  13. 13.

    All mediation effect estimates are computed using the approach discussed in Imai et al. (2010) and implemented in Hicks and Tingley (2012). Very similar inferences are obtained if the bootstrapping method proposed by Shrout and Bolger (2002) is applied.

  14. 14.

    There is a limitation to this analysis, however; it does not capture all types of connections directors can have with each other. To the extent only or mainly such personal connections arising outside of an institutionalized setting are the ones leading to friendliness of the boards, this analysis does not provide sufficient evidence to rule out the hypothesis that female directors are more effective monitors because they lack such personal relationships with others on board and are, therefore, less “friendly”.

  15. 15.

    Calculated as − β1/(2 × β2) where β1 is the coefficient on #Female and β2 is the coefficient on #Female2. .

  16. 16.

    Presence of female directors impacts the incidence of restatements and the likelihood of irregularity restatements in pre-Sox period (coefficient − 0.255, p value < 0.01; and coefficient − 0.412, p value 0.016, respectively) as well as in the post-SOX period (coefficient − 0.194, p value < 0.001; and coefficient − 0.289, p value < 0.001, respectively). Though the coefficients on gender diversity in pre-SOX period are larger, the effect of gender is not significantly different statistically across the two periods.

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Acknowledgements

I gratefully acknowledge financial and research support at Harvard Business School and Rotman School of Management at the University of Toronto. I think seminar participants at Harvard University and University of Toronto

Funding

There are no funding sources to report; all data are obtained from publicly available sources or accessed via subscription-based databases paid for by the research funds provided by the University.

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Correspondence to Aida Sijamic Wahid.

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This article does not contain any studies with human participants or animals performed by any of the authors.

Appendix

Appendix

Variable Definition Source of data
Diverse (1) Dummy variable equal to 1 if any female director on board, 0 otherwise. Alternative specifications robustness: (2) percentage of female directors on the board; and (3) dummy variable equal to one if multiple female directors on board and 0 otherwise BoardEx
Restatement: all Dummy variable equal to 1 if a firm announces restatement which spans years of the current board tenure, 0 otherwise AuditAnalytics
Restatement: irregularities Dummy variable equal to 1 if a firm is subject to litigation or regulatory investigation within a year after a restatement announcement, pertaining to a restatement which spans years of the current board tenure, 0 otherwise AuditAnalytics
# Board meetings Number of times a board met during year t Corporate Library
Meeting attendance (1) Dummy variable equal to 1 if at least one of the directors failed to meet the 75% attendance requirement, 0 otherwise; (2) Number of directors who failed to meet the 75% attendance requirement Corporate Library, Risk Metrics
Financial experts Indicator variable equal to 1 if director holds a degree in accounting or an accounting designation and has worked in accounting-related position, 0 otherwise BoardEx
All Connections Total # of connections between each director and all other directors on the board through various organizations (other boards, charities, employment, educational institutions and any other organizations). Board-level All Connection variable is obtained by computing the average of all connections across all of the directors on the board BoardEx
Stock returns Market-adjusted (CRSP value-weighted) returns for year t − 1, compounded monthly CRSP
Firm size Natural log of total assets in year t − 1 Compustat
Book to market Ratio of book value (total assets—total liabilities) to market value of equity in year t − 1 Compustat
ROA Net income excluding extraordinary items divided by average total assets in period t − 1 Compustat
Leverage Total liabilities divided by total assets in year t Compustat
Return volatility Standard deviation of monthly stock returns over three years prior to t CRSP
Market value Market value of equity at the end of the period t − 1 Compustat
Sales growth % increase in sales from year t − 1 to year t Compustat
CEO age Age of CEO at the end of the period t BoardEx
CEO gender Indicator variable equal to 1 if CEO is female, 0 otherwise BoardEx
CEO tenure Number of years, measured at the end of year t, that the CEO has been at the position BoardEx
CEO’s pay slice % of total top five earner compensation paid to the CEO ExecuComp
CEO duality Indicator variable equal to 1 if CEO is the Chairman, 0 otherwise BoardEx
Inst. ownership Percentage of float shares held by institutional investors in year t Thomson Financial
Board size Natural log of the # of directors on the board at the end of period t BoardEx
Board independence Percentage of board directors considered unaffiliated in year t BoardEx
# of business segments Number of reporting business segments measured in year t Compustat
# of geo. segments Number of reporting geographic segments measured in year t Compustat

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Wahid, A.S. The Effects and the Mechanisms of Board Gender Diversity: Evidence from Financial Manipulation. J Bus Ethics 159, 705–725 (2019). https://doi.org/10.1007/s10551-018-3785-6

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Keywords

  • Corporate governance
  • Board of directors
  • Gender
  • Board composition
  • Board diversity
  • Accounting quality
  • Restatement

JEL Classification

  • G10
  • G30
  • G38
  • J10
  • J16
  • M41