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Board Gender Diversity and Managerial Obfuscation: Evidence from the Readability of Narrative Disclosure in 10-K Reports

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Abstract

The readability of 10-K reports, in terms of linguistic complexity, determines the usefulness of information disclosure for stakeholders, particularly individual investors. Since investors largely depend on the financial communication in 10-K reports, firms have an ethical and legal responsibility to present disclosures in a language investors can understand. However, motivated by self-interest, managers obfuscate such disclosures to mask their own actions and hide unfavourable information. Building on the managerial obfuscation hypothesis grounded in stakeholder-agency and ethical-sensitivity theories, I hypothesize and empirically test the relationship between board gender diversity (BGD) and the readability of narrative disclosure in 10-K reports. Based on a relatively large sample of Russell 3000 firms for the years 2002–2018 (6,268 observations), I find a significant positive impact of BGD on 10-K reports’ readability, which in turn improves firm performance. Channel analysis reveals that the findings are driven by (a) female independent directors, and (b) their representation on audit and compensation committees; however, board activity (board meetings and directors’ attendance) does not appear to drive this relationship. Finally, I find that although gender discrimination in the appointment of directors spurs complex readability, the BGD-readability relationship is consistent in gender-biased and non-discriminant firms. I also check the robustness of our main empirical results in several ways. My study has important regulatory and managerial implications in that corporate governance is an important determinant of the readability of disclosure documents.

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Data Availability

The data sets used and/or analyzed during the current study are available from public sources identified in the manuscript.

Notes

  1. Loughran and McDonald (2016) provide an excellent survey of the contemporary literature on the method and uses of textual analysis.

  2. The Fog index has received criticism due to the fact that it treats all words as complex which use three or more syllables. However, there are a number of words (such as ‘liability’) that use three or more syllables but are still understandable to the least-sophisticated investors (Loughran & McDonald, 2014).

  3. See Bonsall IV et al. (2017) for more details on the construction of the Bog index.

  4. We adopt the managerial ability measure proposed by Demerjian et al. (2012), and the data are available from http://faculty.washington.edu/pdemerj/data.html.

  5. Bonsall and Miller (2017) suggest the following interpretation of the Bog index: “0–20 = Excellent; 21–40 = Good; 41–70 = Average; 71–100 = Poor; 101–130 = Bad; 131–1000 = Dreadful; 1000+  = Gobbledygook”.

  6. This exclusion restriction is also followed by Lara et al. (2017) and Srinidhi et al. (2011).

  7. We also check the validity of our instrument by employing Hansen’s J test, and untabulated results show that the instrument was valid.

  8. We check the validity of instruments in system GMM through AR(1), AR(2), Hansen test of over-identification and difference-in-Hansen test of exogeneity. The results show that only AR(1)’s null hypothesis can be rejected – this is what is required in system GMM (Wintoki et al., 2012).

  9. As with the case in Lara et al. (2017) that within non-discriminating firms, there will be firms that have a female director in some years and in some years they have not. Thus, we also apply this strategy at the firm-year level, where we identify as non-discriminating all firm-years with at least one female director, and our untabulated results were qualitatively indifferent.

  10. We follow Lara et al. (2017) and set a cut-off of low probability as ≤ 10%. In our untabulated analysis, we also consider firm-years in the lowest quartile as having low probability and our results were largely unchanged.

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Acknowledgements

I am thankful to Brian P. Miller for making Bog index data available online. I am also thankful to Bill McDonald for providing the file size and number of 10-K words data, and Peter Demerjian for making managerial ability data publicly available. I thank the associate editor, two anonymous reviewers, and Dr. Rashid Zaman for their useful comments on the earlier version of this paper. Finally, I thank the Department of Accountancy and Finance (University of Otago) for financial support and Khurshid Ali for helping with data collection. Any errors are my own.

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  1. Department of Accountancy and Finance, Otago Business School, University of Otago, 60 Clyde Street, Dunedin, New Zealand

    Muhammad Nadeem

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Appendix: Variables definition

Appendix: Variables definition

Variable

Definition

Dependent variables

 

BOG_INDEX

The ‘Bog index’ reported by Editor Software’s Stylewriter 4 provides a comprehensive measure of a document’s plain English problems, including passive voice, redundant verbs, use of jargon, and sentence complexity, among others (Bonsall & Miller, 2017). A higher level of the Bog index reflects worse document readability. We use the Bog index data of Bonsall et al. (2017)

FILE_SIZE

Net file size (in megabytes) of the 10-K document (Loughran & McDonald, 2014). In regression analysis, we use the natural logarithm of the FILE_SIZE

LOG_WORDS

Natural logarithm of total number of words in 10-K report

Independent variables

 

GENDER

Board gender diversity measured as percentage of female directors on board

GENDERt-1

Board gender diversity measured as percentage of female directors on board in year t-1

GENDERt-2

Board gender diversity measured as percentage of female directors on board in year t-2

WDUMMY

A dummy variable equal to 1 if there is at least one female director on board, 0 otherwise

BLAU

Blau index of heterogeneity

Control variables

 

BOARD_SIZE

Number of directors on board

BOARD_INDEP

Percentage of independent directors

DUALITY

A binary variable equal to 1 if a CEO is also the chair, 0 otherwise

CEO_TEN

Number of years the CEO has been in the position

CEO_AGE

CEO age

CEO_ABILITY

CEO managerial ability from Demerjian et al. (2012)

LN_CEO_SALARY

Natural logarithm of CEO total compensation

LN_OPTIONS

Natural logarithm of options awarded to a CEO

INTERNAL_CONTR

A dummy variable equal to 1 if a client received a NO for effective internal control, 0 otherwise

AUDITOR_IND_SPC

1 if a firm is audited by an audit firm that has a fee market share of at least 30 percent in the industry

Big4

A dummy variable equal to 1 if a client is audited by a Big 4 firm, 0 otherwise

SEGMENTS

Number of business segments

COMPLEXITY

The sum of receivables and inventory divided by total assets

M&A

An indicator variable equal to 1 if a firm was involved in merger and acquisition, 0 otherwise

ABACC

Absolute discretionary accruals based on modified Jones model

ROE

Net income before extraordinary items over total equity

FIRM_SIZE

Natural logarithm of the total assets of a firm

SALES_GROWTH

The ratio of change in sales to prior-year sales

LEVERAGE

Leverage measured as the ratio of long-term debt to total assets

CAPITAL_INT

Capital intensity measured as the net property, plant, and equipment scaled by total assets

R&D_INT

R&D intensity measured as total R&D scaled by total assets

INDUSTRY

Industry dummy to control for industry effects

YEAR

Year dummy to control for year effects

For channel analysis

 

B_MEETINGS

Number of board meetings held in a year

B_M_ATT

The average overall attendance percentage of board meetings

FEMALE_IND

The proportion of independent female directors

FEMALE_EXE

The proportion of female executive directors

F_AUD_COMM

A binary variable equal to 1 if there is at least one female director on the audit committee, 0 otherwise

F_COMP_COMM

A binary variable equal to 1 if there is at least one female director on the compensation committee, 0 otherwise

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Nadeem, M. Board Gender Diversity and Managerial Obfuscation: Evidence from the Readability of Narrative Disclosure in 10-K Reports. J Bus Ethics 179, 153–177 (2022). https://doi.org/10.1007/s10551-021-04830-3

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