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Corporate governance, compensation consultants, and CEO pay levels

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Abstract

This study investigates the relation between corporate governance and CEO pay levels and the extent to which the higher pay found in firms using compensation consultants is related to governance differences. Using proxy statement disclosures from 2,110 companies, we find that CEO pay is higher in firms with weaker governance and that firms with weaker governance are more likely to use compensation consultants. CEO pay remains higher in clients of consulting firms even after controlling for economic determinants of compensation. However, when consultant users and non-users are matched on both economic and governance characteristics, differences in pay levels are not statistically significant, indicating that governance differences explain much of the higher pay in clients of compensation consultants. We find no support for claims that CEO pay is higher in potentially “conflicted” consultants that also offer additional non-compensation-related services.

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Notes

  1. Regulation S-X 407 (e) (3) (iii) states that companies are required to provide a “narrative description” of “any role of compensation consultants in determining or recommending the amount or form of executive and director compensation, identifying such consultants, stating whether such consultants are engaged directly by the compensation committee (or persons performing the equivalent functions) or any other person, describing the nature and scope of their assignment, and the material elements of the instructions or directions given to the consultants with respect to the performance of their duties under the engagement”.

  2. Propensity score matching is robust to misspecification of the functional form linking CEO compensation to selected determinants and allows us to assess the impact of the endogenous choice of compensation consultants on the results. See Rosenbaum (2002) and Rosenbaum and Rubin (1983) for theoretical background and Armstrong et al. (2010) for a detailed explanation of propensity score matching in compensation research and an application examining whether equity incentives motivate managers to engage in accounting manipulations.

  3. Journal of Corporate Law (2005). Beginning in 2004, NYSE and NASDAQ rules required all or nearly all members of the board’s compensation committee to be “independent” (that is, not an officer or employee of the company or a family member of such a director). However, if these “independent” directors owe their positions, future opportunities, or pay levels to the CEO, their compensation decisions may still be influenced by the CEO’s power over the board (Bebchuk and Fried 2004; Campos 2007).

  4. See Conyon et al. (2009), Cadman et al. (2010), and Murphy and Sandino (2010) for studies examining the association between CEO pay practices and the provision of additional (noncompensation) services by consultants, and Goh and Gupta (2010) for research on compensation consultant opinion-shopping.

  5. A common example of multiple consultants is an instance in which one consulting firm provides compensation advice for senior executives and another provides advice for lower-level management.

  6. Our results are similar if we include bonuses in the numerator to get a more inclusive measure of variable pay. As noted above, we examine total CEO pay levels because they have been the primary focus of recent CEO compensation debates. However, if Pay Mix is capturing differences in consultant use and governance, its inclusion will bias us against finding pay level differences due to these two factors. To examine this possibility, we repeated our analyses using Pay Mix as the dependent variable in place of CEO pay level. We find mixed governance results in a regression of Pay Mix on the economic and governance variables discussed later in the paper (model adjusted R 2 = 18.7%). Pay Mix is positively associated with the percentage of old board members and negatively associated with the percentages of busy board members and board members who are outsiders. The busy board result is inconsistent with higher Pay Mix in firms with weaker governance. In propensity scoring matched pair analysis, we find significantly higher Pay Mix in consultant users when only economic characteristics are included in the analyses but no significant pay differences when both economic and governance characteristics are included.

  7. New CEOs may also use talent agents or executive placement firms to help them negotiate new pay packages. For example, using a propensity score matched pair research design, Rajgopal et al. (2011) find that CEOs who use talent agents receive initial pay that is higher than predicted by either economic or governance characteristics, a result that does not persist after the initial year. Given the potential differences in the pay-setting practices used for new CEOs, we also conducted our tests after dropping the 252 firms with new CEOs in our sample. The only significant difference was that a variable capturing the use of dual-class voting shares became insignificant in a regression of pay levels on economic and governance variables. However, the model’s adjusted R 2 remained nearly identical. Our propensity scoring models and matched pairs tests of pay levels between consultant users and non-users exhibit no significant changes when these observations are removed, suggesting that the inclusion of new CEOs is not responsible for our results.

  8. The definitions of inside and outside board members are consistent with the NYSE definitions used for listing requirements. These definitions are used in proxy statements and are adopted in our measures.

  9. Albuquerque (2009) argues that a combination of industry and size quartile is a stronger peer group for benchmarking executive compensation than is industry alone. As a robustness check, we conducted the tests using the Albuquerque measure rather than our industry fixed effects. The results were virtually identical, with any significant (insignificant) results remaining significant (insignificant) and estimated coefficients changing little.

  10. Although these results indicate that a riskier compensation mix has a significant influence on pay levels, the exclusion of Pay Mix has little effect on our other results. The economic variable that explains the most of the variation in pay levels is firm size (the natural logarithm of market capitalization), which has an adjusted R 2 of 58.0% when included alone in an untabulated model.

  11. In unreported analyses, we also include an indicator for whether Return on Assets is negative to allow for a different level of compensation for loss firms. This indicator variable is negative but not statistically significant, and the statistical significance of the other variables in the model is unchanged.

  12. Endogeneity can be addressed in OLS models using two-stage instrumental variable procedures. However, this approach requires identifying appropriate instruments that are correlated with the independent variable of interest but uncorrelated with the error term in the model, which can be difficult in a study such as this. In addition, two-stage least squares continues to rely on linearity assumptions. As a result, Larcker and Rusticus (2010) show that only under very restrictive conditions will two-stage least squares reduce endogeneity problems in OLS.

  13. One of the necessary conditions to implement a propensity score research design is known as the overlapping or common support assumption (Rosenbaum and Rubin 1983). This requirement rules out the possibility that the propensity score model perfectly classifies observations into either the treatment or control groups conditional on the observable covariates, X (that is, 0 < Pr (Treatment = 1|X) < 1). This condition is necessary to ensure that for each observation, there is a potential match that has a similar probability of receiving the treatment. In other words, it ensures that observations with the same observables (that is, X) have a positive probability of both receiving the treatment and not receiving the treatment. A related concern is a propensity score model with a low degree of explanatory power. If the explanatory power of the model is too low, the propensity score research design essentially forms matched pairs at random, which leaves a large scope for hidden bias to confound the results. In our case, the propensity score models of the conditional probability of using a compensation consultant have relatively high degrees of explanatory power (that is, 15.3% when only the economic variables are included and 21.8% when the economic and individual governance variables are included), suggesting that the matched pairs that we form in our next analysis are relatively similar on the basis of their observable covariates.

  14. To illustrate this point in the current context, suppose consulting firms consult only to relatively large companies. Further, suppose that it is not possible to form matched pairs of firms that use consultants with non-users of a similar size. In that case, there would be a lack of balance across the matched pairs with respect to firm size. Consequently, any difference in the level of total compensation across the matched pairs cannot be unambiguously attributed to using a compensation consultant, because the difference could also be attributable to differences in firm size. Examining the covariate balance across the matched pairs is therefore crucial for highlighting any identification problems that might exist.

  15. The separation into potentially “conflicted” and “nonconflicted” consultants is consistent with that used in U.S. government investigations (for example, U.S. House of Representatives 2007). Academic research to date provides mixed support for the prediction that consultants providing additional services are associated with higher pay levels, with Conyon et al. (2009) and Cadman et al. (2010) finding no support for these claims and Murphy and Sandino (2010) finding some support depending upon the type of additional service provided. However, these studies provide relatively little evidence on the extent to which governance influences these results.

  16. Further analysis indicates that governance characteristics help explain pay levels even within clients of individual consultants. This evidence indicates that it is not the use of specific consultants but governance differences that explain the observed relation between consultant use and excess pay levels. Additional analysis of the association between individual consultants and CEO pay levels is provided in an earlier version of this study, titled “Economic Characteristics, Corporate Governance, and the Influence of Compensation Consultants on Executive Pay Levels,” available at http://ssrn.com/abstract=1145548.

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Acknowledgments

This paper has benefited greatly from many insightful discussions with Paul Rosenbaum. We also thank Bo Lu for making available his code to perform the nonbipartite matching algorithm used in this study, and two anonymous reviewers and Katherine Schipper (editor) for their comments. Funding from the Dorinda and Mark Winkelman Distinguished Scholar Award (Armstrong) and Ernst & Young (Ittner) is gratefully acknowledged.

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Authors and Affiliations

  1. The Wharton School, University of Pennsylvania, 1300 Steinberg-Dietrich Hall, Philadelphia, PA, 9104, USA

    Christopher S. Armstrong & Christopher D. Ittner

  2. Graduate School of Business, Rock Center for Corporate Governance, Stanford University, 655 Knight Way, Stanford, CA, 94305, USA

    David F. Larcker

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  1. Christopher S. Armstrong
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Correspondence to Christopher D. Ittner.

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Armstrong, C.S., Ittner, C.D. & Larcker, D.F. Corporate governance, compensation consultants, and CEO pay levels. Rev Account Stud 17, 322–351 (2012). https://doi.org/10.1007/s11142-012-9182-y

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