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Corporate stakeholders and CEO-worker pay gap: evidence from CEO pay ratio disclosure

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Abstract

Based on the recent SEC-mandated disclosures of CEO-worker pay ratios, we find that firms significantly decrease (increase) their CEO-worker pay ratios when their prior pay ratios are high (low) relative to peers. More importantly, the decrease in pay ratio among high pay ratio firms is significantly more pronounced with stronger stakeholder influences, proxied by employees with greater bargaining power, communities with higher social capital, and states with more stringent minimum wage legislation. These results are robust to controlling for CEO and median worker pay benchmarking as well as the influences of shareholders. Using state-level pay ratio tax proposals as another proxy for stakeholder influence, we find high pay ratio firms in states with these proposals reduce pay ratios significantly more than firms with similar high pay ratios in other states. Overall, our results highlight the influence of corporate stakeholders in mitigating high CEO-worker pay gap.

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Data Availability

All data from this study is available from public sources.

Notes

  1. Before this mandated disclosure, although employees knew their own salaries and stakeholders could observe salary statistics for different industries, they did not have accurate information about firm-specific median worker pay or the distribution of the pay ratios across firms.

  2. Following the stakeholder literature (Clarkson 1995; Luoma and Goodstein 1999), “public stakeholders” refers to stakeholders who have no business relationships with a firm, such as governments and communities. Unless otherwise indicated, “stakeholders” in the rest of the paper refers to employees and public stakeholders. Other stakeholders, including shareholders, creditors, customers, and suppliers, have business relations with firms and may not advocate for pay equality as strongly. While we leave detailed analyses of the roles of other stakeholders for future research, in Sect. 4.3.2, we control for the effects of shareholders, given the importance of their influence.

  3. Whether high pay ratios benefit firms is still debatable. Some researchers argue that a high CEO-worker pay gap exacerbates inequality, undermines worker morale and productivity, and impairs pay structures both in individual corporations and throughout the economy (Akerlof and Yellen 1990; Baker et al. 2019; Wingard 2020). Others, however, posit that the market for talent drives high pay for CEOs (Kaplan 2007; Goel and Thakor 2008; Jung et al. 2021), and that the pay gap between CEOs and workers is positively associated with firm performance and value (Faleye et al. 2013; Cheng et al. 2017; Mueller et al. 2017).

  4. Our results on stakeholder influence also suggest that the negative association between pay ratios and subsequent pay ratio changes is not due to alternative explanations, such as a mechanical process driven by mean reversion in pay or other concurrent economic or regulatory changes. This is because effects of these alternative explanations should not vary with the influences of stakeholders. In Sect. 4.3.3, we provide detailed discussions that seek to rule out mean reversion as an alternative explanation for our results.

  5. Stakeholders are likely to focus more on pay ratio benchmarking as opposed to CEO pay benchmarking or median worker pay benchmarking because of their emphasis on equality between executives and the average worker. Consistent with this view, our reading of popular press articles on the public’s reaction to the pay ratio disclosures finds that pay ratio is mentioned significantly more frequently than either the CEO pay or worker pay, highlighting the public’s focus on the pay ratio.

  6. The disclosure requirement applies to all companies required to provide executive compensation disclosure under Item 402(c)(2)(x) of Regulation S-K. Certain firms, such as smaller reporting companies, foreign private issuers, and emerging growth companies, would not be subject to the requirement (SEC 2015).

  7. Unionization could be a channel for employee influence. However, the effects of collective bargaining are controversial in the literature (Ormazábal 2018), as research suggests agency problems between union leaders and workers (Martin 1984), as evidenced by the often-large pay gaps between union leaders and workers. In the presence of such evidence, it is less likely that union leaders are sensitive to high CEO-worker pay ratios. We also note various other value-decreasing consequences of union actions documented in the literature, including corruption among union leaders, rent extraction during negotiations with management, and lower firm profitability (Ormazábal 2018).

  8. In an additional analysis, we also define R&D indicator based on by-industry median of R&D expense per employee. Our results remain robust. While this proxy, HIGHTEC, and INDRDX are likely to capture industry characteristics to a certain extent, we note that our dependent variable of interest is change in the pay ratio (CHGRATIO), which is less likely to be affected by industry characteristics. We also directly control for industry fixed effects in our models.

  9. As a robustness check, we also use median employee salary as another measure for employee bargaining power (Cahuc et al. 2006) and find similar results. Another possible measure of employee bargaining power is the extent of unionized work force. In untabulated analyses, we use a proxy for the extent of organized labor based on industry-level union information, following Hilary (2006), and find that organized labor does not affect the pay ratios. These results are consistent with (i) industry-level union data being a noisy proxy for firm-level unionization, (ii) the extent of unionization failing to represent employee interests and failing to influence pay gap, or both, which is consistent with our discussion in footnote 7.

  10. In an untabulated analysis, we define the relative pay ratio variables HIGH, MD and LOW in three alternative ways. First, we use the mean, instead of the median, pay ratio of the same set of peer firms. Second, we define industry based on two-digit SIC codes. Third, we use firm-disclosed executive compensation peers as an alternative benchmarking group (Faulkender and Young 2013; Albuquerque et al. 2013). The inferences regarding HIGH, MD, and LOW remain qualitatively similar to those in Table 3. In an additional analysis, we also find a significant stakeholder influence conditioning on high, median, and low unadjusted levels of pay ratios. However, the results related to the unadjusted pay ratios become statistically insignificant, once we also include the relative pay ratios HIGH, MD, and LOW and their respective interactions with stakeholder influence. These results are consistent with stakeholders using relative pay ratios to assess pay equality.

  11. We further estimate Model (2) for 2018 and 2019 separately and find that our results are significant and similar in both years. In an additional analysis, we also find that stakeholders’ influence does not have a significant association with the initial reported pay ratio (the absolute or relative pay ratio). Such a finding is consistent with our argument that stakeholders started to pay attention to relative pay ratios mainly after the public disclosure mandate.

  12. In an untabulated analysis, we find that, within our sample, the reported pay ratio has no significant association with abnormal returns around the proxy statement filing dates.

  13. In robustness tests, we find similar results when using [0, 1] and [-1, 1] trading day windows to measure abnormal returns around the proxy statement filing dates.

  14. The correlation between HIGH (LOW) and LRATIO is 0.50 (0.52) and significant at the 0.01 level for our sample.

  15. See https://cooleypubco.com/2018/06/11/pay-ratio-catalyst-for-local-action/ for more details.

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Acknowledgements

We thank an anonymous reviewer, Leah Baer, Rafael Copat, Yonca Ertimur (editor), Jayanthi Sunder, and workshop participants at Arizona State University and the University of Arizona Joint Conference, University of Calgary, the University of Texas at Dallas, and 2021 AAA Annual Conference for helpful comments and suggestions. We thank Jinseo Kang for her valuable research assistance. We acknowledge financial support from the University of Arizona and the University of Texas at Dallas.

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Appendices

Appendix 1: Sample Pay Ratio Disclosures

Nike, Inc. 2019.

For fiscal 2019, our last completed fiscal year:

  • The employee identified at the median of all Nike employees (other than our CEO) was a retail store employee in the United States;

  • The annual total compensation of the median employee was $25,386;

  • The annual total compensation of our CEO, Mr. Parker, was $13,968,022; and

  • The estimated ratio of the annual total compensation of our CEO to the median annual total compensation of all other Nike employees was 550 to 1.

This pay ratio is a reasonable estimate calculated in a manner consistent with SEC rules based on the methodology described below. The SEC rules for identifying the median compensated employee and calculating the pay ratio allow companies to adopt a variety of methodologies, apply certain exclusions, and make reasonable estimates and assumptions that reflect their compensation practices. As such, the pay ratio reported by other companies may not be comparable to the pay ratio reported above, as other companies may utilize different methodologies, exclusions, estimates, and assumptions in calculating their own pay ratios.

Appendix 2

Variable definitions

Variables

Definition

Pay Variables

 

CHGRATIO

log (pay ratiot) – log (pay ratiot-1)

CHGCEO

log (CEO payt) – log(CEO payt-1)

CHGWORKER

log (median worker payt) – log (median worker payt-1)

HIGH

log (pay ratiot-1) – log (median pay ratiot-1 of firms with the same Fama-French 12-industry and the same within-industry decile of the number of employees) for the top by-year tercile and 0 otherwise

MD

log (pay ratiot-1) – log (median pay ratiot-1 of firms with the same Fama-French 12-industry and the same within-industry decile of the number of employees) for the middle by-year tercile and 0 otherwise

LOW

log (pay ratiot-1) – log (median pay ratiot-1 of firms with the same Fama-French 12-industry and the same within-industry decile of the number of employees) for the bottom by-year tercile and 0 otherwise

HIGHCEO

log (CEO payt-1) – log (median CEO Payt-1 of firms with the same Fama-French 12-industry and the same within-industry decile of the number of employees) for the top by-year tercile and 0 otherwise

MDCEO

log (CEO payt-1) – log (median CEO Payt-1 of firms with the same Fama-French 12-industry and the same within-industry decile of the number of employees) for the middle by-year tercile and 0 otherwise

LOWCEO

log (CEO payt-1) – log (median CEO Payt-1 of firms with the same Fama-French 12-industry and the same within-industry decile of the number of employees) for the bottom by-year tercile and 0 otherwise

HIGHWORKER

log (median worker payt-1) – log (median worker payt-1 of firms with the same Fama-French 12-industry and the same within-industry decile of the number of employees) for the top by-year tercile and 0 otherwise

MDWORKER

log (median worker payt-1) – log (median worker payt-1 of firms with the same Fama-French 12-industry and the same within-industry decile of the number of employees) for the middle by-year tercile and 0 otherwise

LOWWORKER

log (median worker payt-1) – log (median worker payt-1 of firms with the same Fama-French 12-industry and the same within-industry decile of the number of employees) for the bottom by-year tercile and 0 otherwise

Ps.ChgRatio_Salary

pseudo ratio changes from year t-1 to year t based on the changes in CEO salary, while holding all other components constant

Ps.ChgRatio_Bonus

pseudo ratio changes from year t-1 to year t based on the changes in CEO bonus, while holding all other components constant

Ps.ChgRatio_Other

pseudo ratio changes from year t-1 to year t based on the changes in CEO other compensation, while holding all other components constant

Stakeholder Variables

HIGHTEC

1 if in high tech industry as defined by Francis and Schipper (1999) and 0 otherwise

INDRDX

1 if RDX > 0 and 0 otherwise

INDSC

1 if the county of headquarters in the top half counties of the social capital index and 0 otherwise

INDMINWAGE

1 if the state of headquarters in the top half states of minimum wage and 0 otherwise

S_INDEX

sum of HIGHTEC, INDRDX, INDSC, and INDMINWAGE

TAX

1 if the pay ratio is in the highest bracket of the proposed pay ratio tax for the corresponding state with a pay ratio tax proposal and 0 otherwise

Control Variables

CHGROA_R

(NIt—NIt-1) / ATt-1 minus the changes of ROA for firms in the same Fama-French 12-industry and the same within-industry decile of the number of employees, where NI is income before extraordinary items, and AT is total assets

CHGSALE

(SALESt—SALESst-1) / SALESt-1

RET_R

market-adjusted annual stock returnt minus the market-adjusted annual stock returns for firms in the same Fama-French 12-industry and the same within-industry decile of the number of employees

LRET_R

lagged market-adjusted annual stock returnt minus the lagged market-adjusted annual stock returns for firms in the same Fama-French 12-industry and the same within-industry decile of the number of employees

CHGSIZE

SIZEt—SIZEt-1, where SIZE = log(AT)

CHGQ

Qt—Qt-1, where Q = (MV + AT—CEQ) / AT and MV and CEQ are the market and book value of common equity, respectively

CHGLEV

LEVt-LEVt-1, where LEV = Total Debt/AT

CHGPPE

PPEt—PPEt-1, where PPE = Net PPE / AT and net PPE is net property, plant, and equipment

CHGEMP

log (1 + number of employeest)—log (1 + number of employeest-1)

LRATIO

lagged value of log (pay ratiot)

Investor Influence Variables

INST

percentage of institutional investors

BLOCK

percentage of blockholders

ARET

market-adjusted abnormal returns within [-1,5] window around proxy statement filing dates

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Cheng, M., Zhang, Y. Corporate stakeholders and CEO-worker pay gap: evidence from CEO pay ratio disclosure. Rev Account Stud (2023). https://doi.org/10.1007/s11142-023-09803-7

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