- Email: [email protected]
CEO Pay Slice as a measure of CEO dominance
Research in International Business and Finance xxx (xxxx) xxx–xxx
Contents lists available at ScienceDirect
Research in International Business and Finance journal homepage: www.elsevier.com/locate/ribaf
CEO Pay Slice as a measure of CEO dominance ⁎
Maxim Zagonova, , Galla Salganik-Shoshanb a
University of Toulouse, Toulouse Business School, 20 Boulevard Lascrosses, 31068, Toulouse, France Finance Division, Department of Business Administration, Guilford Glazer Faculty of Business and Management, Ben-Gurion University of the Negev, P.O. Box 653, 84105, Beer Sheva, Israel b
AR TI CLE I NF O
AB S T R A CT
JEL classification: D23 G38 J33
CEO Pay Slice (CPS), a measure of CEO relative compensation introduced by Bebchuk, Cremers and Peyer [2011. Journal of Financial Economics 102, 199–221], is used widely in the literature as a proxy for chief executive officer dominance. Nonetheless, CPS does not control for the distribution of pay among the top executives and, as we show empirically, often misestimates the level of CEO power. As a result, its empirical application exposes researchers to the risk of drawing false conclusions. We propose a number of supplementary measures that could be used in conjunction with CPS to improve the measurement accuracy of CEO dominance.
Keywords: Corporate governance Executive compensation Entrenchment Pay distribution
1. Introduction Several recent studies have examined the impact of various dimensions of CEO power1 on firm performance and outcomes (Adams et al., 2005; Bebchuk et al., 2011; Chang et al., 2010; Cheng et al., 2015; Cooper et al., 2014; Kale et al., 2009). The available empirical evidence on the issue points to a negative association between firm performance and measures of CEO dominance. Bebchuk et al. (2007, 2011) define one such measure that could reflect the “relative importance of the CEO” within the top executive team − the CEO Pay Slice2 (CPS hereafter) − as the proportion of the total annual compensation of the five highest paid executives in a firm captured by the CEO. As a measure of CEO dominance, CPS has the virtues of simplicity and applicability to a wide spectrum of empirical questions in corporate governance. The measure has featured widely in empirical investigations as a primary and often the only proxy for the CEO’s ability and power (Chen et al., 2013; Chintrakarn et al., 2014; Choe et al., 2014; Correa and Lel, 2013; Jiraporn and Chintrakarn, 2013; Liu and Jiraporn, 2010). It is documented to have strong explanatory power for a variety of corporate outcomes, relating negatively to firm value, accounting profitability and credit ratings, and positively to cost of debt and equity. Nevertheless, we argue that CPS suffers from a fundamental flaw: it implicitly makes restrictive assumptions about the distributional structure of compensation among the top executives. As we demonstrate in the paper, the measure discounts the valuable information contained in the compensation data for the executives in the top team other than the CEO, which may result in a deceptively high (low) CPS score assigned to a relatively weak (strong) CEO. Consequently, the application of CPS as a measure of CEO dominance exposes researchers to the risk of drawing misleading conclusions. In the remainder of the paper, we discuss the aforementioned limitations of CPS and demonstrate how they may impede accurate ⁎
Corresponding author. E-mail addresses: [email protected] (M. Zagonov), [email protected] (G. Salganik-Shoshan). One can distinguish among multifarious, often intertwined and unobservable, dimensions of power. Finkelstein (1992) proposes measuring top managers’ power according to four dimensions: structural power, ownership power, expert power and prestige power. 2 Also known as “CEO Centrality” (see Bebchuk et al., 2007). 1
http://dx.doi.org/10.1016/j.ribaf.2017.07.092 Received 10 October 2016; Accepted 3 July 2017 0275-5319/ © 2017 Elsevier B.V. All rights reserved.
Please cite this article as: Zagonov, M., Research in International Business and Finance (2017), http://dx.doi.org/10.1016/j.ribaf.2017.07.092
Research in International Business and Finance xxx (xxxx) xxx–xxx
M. Zagonov, G. Salganik-Shoshan
estimation of the actual CEO power. We focus primarily on the inability of CPS to capture the distributional structure of compensation among the top executives, which, if properly controlled for, may yield more accurate inferences. We also propose a number of supplementary measures that empiricists could use in conjunction with CPS to control for heterogeneity in the distribution structure of executive pay across firms. 2. CPS limitations and supplementary measures of CEO dominance 2.1. CPS and CEO dominance The CPS measure introduced by Bebchuk et al. (2011) is defined as follows:
CPS =
P1 P1 + P2 + P3 + P4 + P5
(1)
where P1, P2, P3, P4, and P5 denote the total compensation of the CEO, and of each of the next four top executives, respectively. Thus, CPS is the proportion of the total annual compensation received by the CEO relative to that of the top five highest paid managers in a firm.3 Accordingly, ceteris paribus, the higher the pay slice, the more dominant the CEO. Including information on remuneration for the CEO and the next four highest paid managers in the CPS estimate allows firmspecific characteristics that affect a firm’s compensation policy to be captured (Bebchuk et al., 2011). Nonetheless, CPS does not control for the distribution of pay among the top executive team and, as a result, may fail in some cases to accurately measure CEO dominance. To better illustrate this point, we construct a simple numerical example: consider four companies (A through D) for which the total pay of the executive team and the CEO compensation are identical (amounting to $25 million and $9 million per year, respectively). Thus, we ensure that CPS is 0.36 for all four companies, which is the average reported by Bebchuk et al. (2011). However, the distribution structure of executive compensation differs across firms, as described in Fig. 1. The distribution of executive pay for Company A in Fig. 1 shows a considerable gap in pay between the firm’s CEO and each of the next four executives, thereby clearly indicating CEO dominance. However, considering the form of pay distribution for Company B, it is more difficult to maintain that we are dealing with a dominant CEO: the magnitude of pay difference between the CEO and the next-in-line executive is trivial. The relative dominance of the top-three executives is also apparent, with the distributional structure of executives’ pay being significantly skewed. For Companies C and D, the CPS estimate is once again 0.36, but the CEO now looks weak. The CEO’s compensation is the same or lower than that of the next-in-line top executive, despite the fact that the growth in remuneration as the executive rank goes from 5 to 2 would lead to the expectation of a much higher pay level for the company top executive. According to the CPS measure, the CEOs of companies A through D should be recognised as equally dominant. In reality, the level of CEO dominance clearly diminishes as we move from company A to D. In this context, CPS underestimates the dominance of the CEO for Company A, while overestimating it for Company D. To assess the pertinence of the example above, we conduct an empirical assessment of CPS utilising a similar sample of companies, time period (1993–2004), and methodology as in Bebchuk et al. (2011). All data are from the Compustat’s ExecuComp database. We start with a sample of 2839 companies. To calculate CPS and other pertinent executive compensation variables, we only include companies with consistently available compensation data for the CEO and the next four highest paid managers in a given year. This reduces the sample to 11,831 firm-year observations for 2508 firms. The sample size is similar to that in Bebchuk et al. (2011),4 and so is the CPS value: the average CPS in our sample is 37% (vs. 36%) and its standard deviation is 11.4% (vs. 11.4%). While an extreme theoretical case, the pay distribution for Company C and D’s top-two executives depicted in Fig. 1 is in fact rather commonplace. Using the measure of CEO relative compensation (CRC) introduced by Hayward and Hambrick (1997) and calculated as the CEO’s total compensation divided by the total compensation of the highest paid executive other than the CEO, we observe a CRC of 1 or less for 16.3% of the sample firm-years.5 Fig. 2 presents two scatter plots of CEO Pay Slice (CPS) against CEO relative compensation (CRC) for the companies in our sample. Although the average pay slice of relatively weak CEOs (CRC ≤ 1) is well below the sample mean of 0.36 in Bebchuk et al. (2011), CPS varies significantly for each level of CRC. Inspection of the figure demonstrates that CPS often overestimates the relative importance of the CEO, reaching values of up to 0.47 for a corresponding CRC of only 0.98. It is instructive to note that a CPS of 0.47 would fall within approximately the 84th percentile based on the CEO’s pay slice mean and standard deviation reported in Bebchuk et al. (2011). Similarly, the measure of CEO relative compensation, CRC, varies significantly across the CPS decile portfolios. As reported in Table 1, over the 1993–2004 period, companies with relatively weak CEOs (i.e. companies with CRC ≤ 1) feature in all but the highest CPS decile portfolio. The standard deviation of CRC is also high (i.e., it is a substantial proportion of the mean CRC) for all CPS sorted portfolios. Taken together, these observations lead to the conclusion that CPS does a poor job of reliably distinguishing between a truly dominant CEO, with CRC > 1, and a relatively weak one, with CRC ≤ 1. Compensation data are consistently available across firms only for the top five highest paid managers. Bebchuk et al. (2011) utilise a comparable sample of 12,011 firm-year observations for 2015 different firms. CRC of 1 (or less) suggests that the CEO’s total compensation is the same as (or less than) that of the highest paid executive other than the CEO. We consider that a CEO is weak if CRC ≤ 1. 3 4 5
2
Research in International Business and Finance xxx (xxxx) xxx–xxx
M. Zagonov, G. Salganik-Shoshan
Fig. 1. Executive pay distributions with identical CPS value.
Fig. 2. CEO Pay Slice (CPS) and CEO Relative Compensation (CRC).
2.2. Supplementary measures of CEO dominance The example in Fig. 1 and a basic assessment of the compensation data accentuate the importance of the information contained in the distribution of pay among executives and the need to better exploit its potential. In this section, we propose and discuss two simple supplementary measures that researchers could use in conjunction with CPS to account for this information. We stress, however, that our focus is not to explore the most appropriate alternative to CPS. Instead we indicate possible ways of mitigating its aforementioned shortcomings through the use of additional variables that cater for specific needs and limitations of a researcher’s sample. Furthermore, we do not attempt to determine which of the two proposed measures constitutes a better proxy for the representation of CEO dominance.
2.2.1. Non-CEO highest paid executive pay slice (2PS) First, we construct a measure of pay slice for the highest paid executive in a firm other than the CEO: 2PS = P2/ 3
Research in International Business and Finance xxx (xxxx) xxx–xxx
M. Zagonov, G. Salganik-Shoshan
Table 1 CPS sorted executive compensation measures. CPS portfolio deciles
% CRC ≤ 1 % CRC ≤ 1.5
1 99.3% 100.0%
2 64.5% 99.2%
3 22.7% 78.3%
4 9.7% 51.3%
5 5.2% 33.6%
6 2.3% 18.9%
7 1.4% 9.4%
8 1.0% 5.4%
9 0.5% 3.0%
10 0.0% 0.0%
All 16.3% 39.9%
CPS CPS CPS CPS CPS
mean median maximum minimum std. dev.
0.168 0.184 0.237 0.000 0.059
0.266 0.267 0.289 0.237 0.015
0.306 0.307 0.322 0.289 0.010
0.335 0.336 0.348 0.322 0.008
0.359 0.359 0.371 0.348 0.007
0.382 0.382 0.394 0.371 0.007
0.407 0.407 0.421 0.394 0.008
0.437 0.437 0.455 0.421 0.010
0.479 0.477 0.510 0.455 0.016
0.587 0.566 0.830 0.511 0.066
0.373 0.371 0.830 0.000 0.114
CRC CRC CRC CRC CRC
mean median maximum minimum std. dev.
0.539 0.526 1.210 0.000 0.278
1.016 1.011 1.587 0.408 0.221
1.293 1.304 1.856 0.574 0.243
1.474 1.495 2.112 0.675 0.269
1.621 1.623 2.321 0.689 0.295
1.796 1.802 2.524 0.843 0.333
2.002 2.009 2.865 0.787 0.374
2.254 2.283 3.217 0.952 0.447
2.643 2.687 3.975 0.976 0.578
4.230 3.879 10.089 1.504 1.626
1.887 1.674 10.089 0.000 1.147
2PS 2PS 2PS 2PS 2PS
mean median maximum minimum std. dev.
0.433 0.390 0.980 0.250 0.143
0.374 0.353 0.811 0.251 0.092
0.355 0.339 0.772 0.251 0.074
0.355 0.336 0.755 0.250 0.074
0.358 0.345 0.845 0.253 0.075
0.358 0.343 0.703 0.252 0.076
0.356 0.341 0.846 0.250 0.078
0.361 0.342 0.833 0.250 0.087
0.368 0.340 0.944 0.250 0.098
0.374 0.344 0.823 0.251 0.100
0.369 0.346 0.980 0.250 0.095
This table presents information on the executive compensation measures over the 1993–2004 period sorted in deciles by the firm-year CEO Pay Slice (CPS). CRC the Hayward and Hambrick (1997) measure of CEO relative compensation calculated as CEO total compensation divided by the total compensation of the highest paid executive other than the CEO. 2PS is the measure of pay slice for the second highest paid executive in a firm, calculated as P2/(P2 + P3 + P4 + P5).
Fig. 3. CEO Pay Slice (CPS) and pay slice for the second highest paid executive (2PS).
(P2 + P3 + P4 + P5). Note that 2PS does not include the CEO’s pay and is algebraically independent of CPS. Therefore, it can be used both as an explanatory variable for CPS, and in conjunction with CPS to explain differences in firm performance. Empirically, 2PS may serve as a proxy for tournament-like incentives at the highest level, helping to distinguish an excess level of CPS from the optimal one. As Fig. 3 demonstrates, there are numerous examples of firms with a relatively weak CEO − characterised by low CPS − but a relatively strong “second-in-line”,6 and vice versa. In an unreported regression of CPS on 2PS, the relationship between the two measures is statistically significant (at one percent), with a one percent growth in 2PS leading, on average, to a reduction in CPS of 0.16 percent for the firms in our sample. When CEO dominance is a dependent variable in the model and the use of two separate metrics is impractical, CPS and 2PS could be combined into a single index of overall CEO dominance. Consider, for instance, the ratio of the former on the latter. Such a ratio increases with CEO dominance, as it takes higher values for companies with high CPS and low 2PS. 2.2.2. Pay slice gap (PSG) Another simple measure of CEO dominance, Pay Slice Gap (PSG), can be constructed as the difference between the pay of the CEO 6
Second-in-line refers to the highest paid executive in a firm other than the CEO.
4
Research in International Business and Finance xxx (xxxx) xxx–xxx
M. Zagonov, G. Salganik-Shoshan
Fig. 4. Pay Slice Gap (PSG) and CEO Relative Compensation (CRC).
and that of the highest paid non-CEO manager divided by the total compensation of the five highest paid executives in the firm: PSG = (P1-P2)/(P1 + P2 + P3 + P4 + P5). The calculation uses the same set of data as used to compute CPS. Researchers may find PSG to be particularly relevant in instances where the difference in pay between the CEO and the highest paid non-CEO executive is the main focus of research. As the example in Fig. 1 highlights, CPS does not explicitly account for the difference in pay between the two. Fig. 4 presents the scatter plot of PSG against CRC. It is evident from the figure that one of the key advantage of PSG is that, unlike CPS, it removes entirely ambiguity about the degree of CEO dominance at the pivotal level of CRC = 1. Furthermore, the risk of CEO dominance misidentification is now also minimised over the region adjacent to this intuitively clear point of distinction between the dominant − even if marginally so − CEOs (CRC > 1) and the dominated ones (CRC ≤ 1). Another feature of PSG that will appeal to researchers is that it controls for firm-specific biases affecting its compensation policy in much the same way as does CPS. 2.3. Further considerations on CPS Bebchuk et al. (2011) propose normalising the CEO’s pay by the total compensation received by the top five highest paid managers as a means of addressing firm-specific biases that could affect a firm’s compensation policy. However, the authors do not explicitly examine the question of whether their normalization approach is the best method of addressing these biases. Bebchuk et al. (2011) state in their paper (footnote 2; p. 201) that “Chang et al., 2010 examine […] whether abnormal stock returns around managerial departure announcements are related to CPS”. Yet Chang et al. (2010) do not use CPS. They instead use a variable called “Relative Total Pay”, defined as the CEO pay divided by the total compensation of the next four highest paid executives in the firm: RTP = P1/(P2 + P3 + P4 + P5), i.e. the CEO’s pay is not included in the denominator. This difference is very important, because it means that RTP is not bounded from above, whereas CPS is: CPS = RTP/(RTP + 1). On these grounds, RTP is superior, especially when relative CEO pay is being used as the dependent variable in a regression (due to well-documented problems with limited dependent variables). An alternative solution would be to use the logistic transformation of the fractional variable that is CPS (Papke and Wooldridge, 2008). When CPS is the dependent variable, such a transformation is an econometric necessity. When CPS is an explanatory variable, the transformation is called for by the underlying economics: CPS changing from 0.7 to 0.8 (with the corresponding RTP value increasing from 2.3 to 4.0) represents a much smaller increase in CEO dominance than when CPS goes from 0.8 to 0.9 (with RTP increasing from 4.0 to 9.0). The scatter plot of RTP against CPS for our sample firms is presented in Fig. 5. As the figure illustrates, CPS compresses the variability in relative CEO pay when CEOs are highly dominant. Instead, most of the variability in relative CEO pay as captured by the CPS metric occurs when the CEO is rather weak (e.g. when P1 < P2 + P3 + P4 + P5), and this latter variation completely stifles the effect of variation in CEO pay when the CEO is strong. To summarise, there are numerous measures that can be constructed using compensation data for executives in the top team. Empirical researchers should therefore carefully consider and justify their choice of the best measure. A good starting point would be to set out the criteria for what constitutes a good measure of CEO dominance for their purpose. 3. Conclusions Despite the extensive popularity in the literature of the CEO Pay Slice, the rationale behind its conceptual definition and its empirical use as an unequivocal proxy for CEO dominance is questionable, as is its superiority in the class of measures one can construct from the top-five executive compensation data. Further, as we demonstrate in the paper, CPS discounts the valuable information contained in the compensation data for the executives in the top team other than the CEO. This often results in CPS failing to account accurately for any aberrant but widespread characteristics of the distribution of decision-making power among the 5
Research in International Business and Finance xxx (xxxx) xxx–xxx
M. Zagonov, G. Salganik-Shoshan
Fig. 5. CEO Pay Slice (CPS) and Relative Total Pay (RTP).
top executives, as well as in misestimating the CEO’s relative power and ability to influence decisions that materially affect the firm’s outcomes. It is, therefore, important to carefully consider the precise applications for which its suitability and use as the only proxy for CEO dominance may be justified. Acknowledgements We are grateful to Alex Elias, Natalia Ostanina, and David Stolin for stimulating discussions and suggestions. Part of this paper was written while the first author was visiting the Krannert School of Management at Purdue University. All errors are ours. References Adams, R.B., Almeida, H., Ferreira, D., 2005. Powerful CEOs and their impact on corporate performance. Rev. Finance Stud. 18, 1403–1432. http://dx.doi.org/10. 1093/rfs/hhi030. Bebchuk, L.A., Martijn Cremers, K.J., Peyer, U.C., 2007. CEO Centrality. National Bur. Econ. Res, Cambridge, MA (Discuss. Pap. no.13701). Bebchuk, L.A., Cremers, K.J.M., Peyer, U.C., 2011. The CEO pay slice. J. Finance Econ. 102, 199–221. http://dx.doi.org/10.1016/j.jfineco.2011.05.006. Chang, Y.Y., Dasgupta, S., Hilary, G., 2010. CEO ability, pay, and firm performance. Manag. Sci. 56, 1633–1652. http://dx.doi.org/10.1287/mnsc.1100.1205. Chen, Z., Huang, Y., Wei, K.C.J., 2013. Executive pay disparity and the cost of equity capital. J. Finance Quant. Anal. 48, 849–885. http://dx.doi.org/10.1017/ S0022109013000306. Cheng, I.H., Hong, H., Scheinkman, J.A., 2015. Yesterday’s heroes: compensation and risk at financial firms. J. Finance 70, 839–879. http://dx.doi.org/10.1111/jofi. 12225. Chintrakarn, P., Jiraporn, P., Tong, S., 2014. How do powerful CEOs view corporate risk-taking? Evidence from the CEO pay slice (CPS). Appl. Econ. Lett. 22, 104–109. http://dx.doi.org/10.1080/13504851.2014.927565. Choe, C., Tian, G.Y., Yin, X., 2014. CEO power and the structure of CEO pay. Int. Rev. Finance Anal. 35, 237–248. http://dx.doi.org/10.1016/j.irfa.2014.10.004. Cooper, M.J., Gulen, H., Rau, P.R., 2014. Performance for Pay? The Relation Between CEO Incentive Compensation and Future Stock Price Performance. University of Cambridge (Working paper). Correa, R., Lel, U., 2013. Say on pay laws, executive compensation, CEO pay slice, and firm value around the world Work. Pap. − U.S. Fed. Reserv. Board’s. Int. Finance Discuss. Pap. 2–55. http://dx.doi.org/10.2139/ssrn.2274823. Finkelstein, S., 1992. Power in top management teams: dimensions, measurement, and validation. Acad. Manag. J. 35, 505–538. http://dx.doi.org/10.2307/256485. Hayward, M.L., Hambrick, D.C., 1997. Explaining the premiums paid for large acquisitions: evidence of CEO hubris. Adm. Sci. Q. 103–127. http://dx.doi.org/10. 2307/2393810. Jiraporn, P., Chintrakarn, P., 2013. How do powerful CEOs view corporate social responsibility (CSR)? An empirical note. Econ. Lett. 119, 344–347. http://dx.doi.org/ 10.1016/j.econlet.2013.03.026. Kale, J.R., Reis, E., Venkateswaran, A., 2009. Rank-order tournaments and incentive alignment: the effect on firm performance. J. Finance 64, 1479–1512. http://dx. doi.org/10.1111/j.1540-6261.2009.01470.X. Liu, Y., Jiraporn, P., 2010. The effect of CEO power on bond ratings and yields. J. Empir. Finance 17, 744–762. http://dx.doi.org/10.1016/j.jempfin.2010.03.003. Papke, L.E., Wooldridge, J.M., 2008. Panel data methods for fractional response variables with an application to test pass rates. J. Econ. 145 (1), 121–133. http://dx. doi.org/10.1016/j.jeconom.2008.05.009.
6
Contents lists available at ScienceDirect
Research in International Business and Finance journal homepage: www.elsevier.com/locate/ribaf
CEO Pay Slice as a measure of CEO dominance ⁎
Maxim Zagonova, , Galla Salganik-Shoshanb a
University of Toulouse, Toulouse Business School, 20 Boulevard Lascrosses, 31068, Toulouse, France Finance Division, Department of Business Administration, Guilford Glazer Faculty of Business and Management, Ben-Gurion University of the Negev, P.O. Box 653, 84105, Beer Sheva, Israel b
AR TI CLE I NF O
AB S T R A CT
JEL classification: D23 G38 J33
CEO Pay Slice (CPS), a measure of CEO relative compensation introduced by Bebchuk, Cremers and Peyer [2011. Journal of Financial Economics 102, 199–221], is used widely in the literature as a proxy for chief executive officer dominance. Nonetheless, CPS does not control for the distribution of pay among the top executives and, as we show empirically, often misestimates the level of CEO power. As a result, its empirical application exposes researchers to the risk of drawing false conclusions. We propose a number of supplementary measures that could be used in conjunction with CPS to improve the measurement accuracy of CEO dominance.
Keywords: Corporate governance Executive compensation Entrenchment Pay distribution
1. Introduction Several recent studies have examined the impact of various dimensions of CEO power1 on firm performance and outcomes (Adams et al., 2005; Bebchuk et al., 2011; Chang et al., 2010; Cheng et al., 2015; Cooper et al., 2014; Kale et al., 2009). The available empirical evidence on the issue points to a negative association between firm performance and measures of CEO dominance. Bebchuk et al. (2007, 2011) define one such measure that could reflect the “relative importance of the CEO” within the top executive team − the CEO Pay Slice2 (CPS hereafter) − as the proportion of the total annual compensation of the five highest paid executives in a firm captured by the CEO. As a measure of CEO dominance, CPS has the virtues of simplicity and applicability to a wide spectrum of empirical questions in corporate governance. The measure has featured widely in empirical investigations as a primary and often the only proxy for the CEO’s ability and power (Chen et al., 2013; Chintrakarn et al., 2014; Choe et al., 2014; Correa and Lel, 2013; Jiraporn and Chintrakarn, 2013; Liu and Jiraporn, 2010). It is documented to have strong explanatory power for a variety of corporate outcomes, relating negatively to firm value, accounting profitability and credit ratings, and positively to cost of debt and equity. Nevertheless, we argue that CPS suffers from a fundamental flaw: it implicitly makes restrictive assumptions about the distributional structure of compensation among the top executives. As we demonstrate in the paper, the measure discounts the valuable information contained in the compensation data for the executives in the top team other than the CEO, which may result in a deceptively high (low) CPS score assigned to a relatively weak (strong) CEO. Consequently, the application of CPS as a measure of CEO dominance exposes researchers to the risk of drawing misleading conclusions. In the remainder of the paper, we discuss the aforementioned limitations of CPS and demonstrate how they may impede accurate ⁎
Corresponding author. E-mail addresses: [email protected] (M. Zagonov), [email protected] (G. Salganik-Shoshan). One can distinguish among multifarious, often intertwined and unobservable, dimensions of power. Finkelstein (1992) proposes measuring top managers’ power according to four dimensions: structural power, ownership power, expert power and prestige power. 2 Also known as “CEO Centrality” (see Bebchuk et al., 2007). 1
http://dx.doi.org/10.1016/j.ribaf.2017.07.092 Received 10 October 2016; Accepted 3 July 2017 0275-5319/ © 2017 Elsevier B.V. All rights reserved.
Please cite this article as: Zagonov, M., Research in International Business and Finance (2017), http://dx.doi.org/10.1016/j.ribaf.2017.07.092
Research in International Business and Finance xxx (xxxx) xxx–xxx
M. Zagonov, G. Salganik-Shoshan
estimation of the actual CEO power. We focus primarily on the inability of CPS to capture the distributional structure of compensation among the top executives, which, if properly controlled for, may yield more accurate inferences. We also propose a number of supplementary measures that empiricists could use in conjunction with CPS to control for heterogeneity in the distribution structure of executive pay across firms. 2. CPS limitations and supplementary measures of CEO dominance 2.1. CPS and CEO dominance The CPS measure introduced by Bebchuk et al. (2011) is defined as follows:
CPS =
P1 P1 + P2 + P3 + P4 + P5
(1)
where P1, P2, P3, P4, and P5 denote the total compensation of the CEO, and of each of the next four top executives, respectively. Thus, CPS is the proportion of the total annual compensation received by the CEO relative to that of the top five highest paid managers in a firm.3 Accordingly, ceteris paribus, the higher the pay slice, the more dominant the CEO. Including information on remuneration for the CEO and the next four highest paid managers in the CPS estimate allows firmspecific characteristics that affect a firm’s compensation policy to be captured (Bebchuk et al., 2011). Nonetheless, CPS does not control for the distribution of pay among the top executive team and, as a result, may fail in some cases to accurately measure CEO dominance. To better illustrate this point, we construct a simple numerical example: consider four companies (A through D) for which the total pay of the executive team and the CEO compensation are identical (amounting to $25 million and $9 million per year, respectively). Thus, we ensure that CPS is 0.36 for all four companies, which is the average reported by Bebchuk et al. (2011). However, the distribution structure of executive compensation differs across firms, as described in Fig. 1. The distribution of executive pay for Company A in Fig. 1 shows a considerable gap in pay between the firm’s CEO and each of the next four executives, thereby clearly indicating CEO dominance. However, considering the form of pay distribution for Company B, it is more difficult to maintain that we are dealing with a dominant CEO: the magnitude of pay difference between the CEO and the next-in-line executive is trivial. The relative dominance of the top-three executives is also apparent, with the distributional structure of executives’ pay being significantly skewed. For Companies C and D, the CPS estimate is once again 0.36, but the CEO now looks weak. The CEO’s compensation is the same or lower than that of the next-in-line top executive, despite the fact that the growth in remuneration as the executive rank goes from 5 to 2 would lead to the expectation of a much higher pay level for the company top executive. According to the CPS measure, the CEOs of companies A through D should be recognised as equally dominant. In reality, the level of CEO dominance clearly diminishes as we move from company A to D. In this context, CPS underestimates the dominance of the CEO for Company A, while overestimating it for Company D. To assess the pertinence of the example above, we conduct an empirical assessment of CPS utilising a similar sample of companies, time period (1993–2004), and methodology as in Bebchuk et al. (2011). All data are from the Compustat’s ExecuComp database. We start with a sample of 2839 companies. To calculate CPS and other pertinent executive compensation variables, we only include companies with consistently available compensation data for the CEO and the next four highest paid managers in a given year. This reduces the sample to 11,831 firm-year observations for 2508 firms. The sample size is similar to that in Bebchuk et al. (2011),4 and so is the CPS value: the average CPS in our sample is 37% (vs. 36%) and its standard deviation is 11.4% (vs. 11.4%). While an extreme theoretical case, the pay distribution for Company C and D’s top-two executives depicted in Fig. 1 is in fact rather commonplace. Using the measure of CEO relative compensation (CRC) introduced by Hayward and Hambrick (1997) and calculated as the CEO’s total compensation divided by the total compensation of the highest paid executive other than the CEO, we observe a CRC of 1 or less for 16.3% of the sample firm-years.5 Fig. 2 presents two scatter plots of CEO Pay Slice (CPS) against CEO relative compensation (CRC) for the companies in our sample. Although the average pay slice of relatively weak CEOs (CRC ≤ 1) is well below the sample mean of 0.36 in Bebchuk et al. (2011), CPS varies significantly for each level of CRC. Inspection of the figure demonstrates that CPS often overestimates the relative importance of the CEO, reaching values of up to 0.47 for a corresponding CRC of only 0.98. It is instructive to note that a CPS of 0.47 would fall within approximately the 84th percentile based on the CEO’s pay slice mean and standard deviation reported in Bebchuk et al. (2011). Similarly, the measure of CEO relative compensation, CRC, varies significantly across the CPS decile portfolios. As reported in Table 1, over the 1993–2004 period, companies with relatively weak CEOs (i.e. companies with CRC ≤ 1) feature in all but the highest CPS decile portfolio. The standard deviation of CRC is also high (i.e., it is a substantial proportion of the mean CRC) for all CPS sorted portfolios. Taken together, these observations lead to the conclusion that CPS does a poor job of reliably distinguishing between a truly dominant CEO, with CRC > 1, and a relatively weak one, with CRC ≤ 1. Compensation data are consistently available across firms only for the top five highest paid managers. Bebchuk et al. (2011) utilise a comparable sample of 12,011 firm-year observations for 2015 different firms. CRC of 1 (or less) suggests that the CEO’s total compensation is the same as (or less than) that of the highest paid executive other than the CEO. We consider that a CEO is weak if CRC ≤ 1. 3 4 5
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M. Zagonov, G. Salganik-Shoshan
Fig. 1. Executive pay distributions with identical CPS value.
Fig. 2. CEO Pay Slice (CPS) and CEO Relative Compensation (CRC).
2.2. Supplementary measures of CEO dominance The example in Fig. 1 and a basic assessment of the compensation data accentuate the importance of the information contained in the distribution of pay among executives and the need to better exploit its potential. In this section, we propose and discuss two simple supplementary measures that researchers could use in conjunction with CPS to account for this information. We stress, however, that our focus is not to explore the most appropriate alternative to CPS. Instead we indicate possible ways of mitigating its aforementioned shortcomings through the use of additional variables that cater for specific needs and limitations of a researcher’s sample. Furthermore, we do not attempt to determine which of the two proposed measures constitutes a better proxy for the representation of CEO dominance.
2.2.1. Non-CEO highest paid executive pay slice (2PS) First, we construct a measure of pay slice for the highest paid executive in a firm other than the CEO: 2PS = P2/ 3
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Table 1 CPS sorted executive compensation measures. CPS portfolio deciles
% CRC ≤ 1 % CRC ≤ 1.5
1 99.3% 100.0%
2 64.5% 99.2%
3 22.7% 78.3%
4 9.7% 51.3%
5 5.2% 33.6%
6 2.3% 18.9%
7 1.4% 9.4%
8 1.0% 5.4%
9 0.5% 3.0%
10 0.0% 0.0%
All 16.3% 39.9%
CPS CPS CPS CPS CPS
mean median maximum minimum std. dev.
0.168 0.184 0.237 0.000 0.059
0.266 0.267 0.289 0.237 0.015
0.306 0.307 0.322 0.289 0.010
0.335 0.336 0.348 0.322 0.008
0.359 0.359 0.371 0.348 0.007
0.382 0.382 0.394 0.371 0.007
0.407 0.407 0.421 0.394 0.008
0.437 0.437 0.455 0.421 0.010
0.479 0.477 0.510 0.455 0.016
0.587 0.566 0.830 0.511 0.066
0.373 0.371 0.830 0.000 0.114
CRC CRC CRC CRC CRC
mean median maximum minimum std. dev.
0.539 0.526 1.210 0.000 0.278
1.016 1.011 1.587 0.408 0.221
1.293 1.304 1.856 0.574 0.243
1.474 1.495 2.112 0.675 0.269
1.621 1.623 2.321 0.689 0.295
1.796 1.802 2.524 0.843 0.333
2.002 2.009 2.865 0.787 0.374
2.254 2.283 3.217 0.952 0.447
2.643 2.687 3.975 0.976 0.578
4.230 3.879 10.089 1.504 1.626
1.887 1.674 10.089 0.000 1.147
2PS 2PS 2PS 2PS 2PS
mean median maximum minimum std. dev.
0.433 0.390 0.980 0.250 0.143
0.374 0.353 0.811 0.251 0.092
0.355 0.339 0.772 0.251 0.074
0.355 0.336 0.755 0.250 0.074
0.358 0.345 0.845 0.253 0.075
0.358 0.343 0.703 0.252 0.076
0.356 0.341 0.846 0.250 0.078
0.361 0.342 0.833 0.250 0.087
0.368 0.340 0.944 0.250 0.098
0.374 0.344 0.823 0.251 0.100
0.369 0.346 0.980 0.250 0.095
This table presents information on the executive compensation measures over the 1993–2004 period sorted in deciles by the firm-year CEO Pay Slice (CPS). CRC the Hayward and Hambrick (1997) measure of CEO relative compensation calculated as CEO total compensation divided by the total compensation of the highest paid executive other than the CEO. 2PS is the measure of pay slice for the second highest paid executive in a firm, calculated as P2/(P2 + P3 + P4 + P5).
Fig. 3. CEO Pay Slice (CPS) and pay slice for the second highest paid executive (2PS).
(P2 + P3 + P4 + P5). Note that 2PS does not include the CEO’s pay and is algebraically independent of CPS. Therefore, it can be used both as an explanatory variable for CPS, and in conjunction with CPS to explain differences in firm performance. Empirically, 2PS may serve as a proxy for tournament-like incentives at the highest level, helping to distinguish an excess level of CPS from the optimal one. As Fig. 3 demonstrates, there are numerous examples of firms with a relatively weak CEO − characterised by low CPS − but a relatively strong “second-in-line”,6 and vice versa. In an unreported regression of CPS on 2PS, the relationship between the two measures is statistically significant (at one percent), with a one percent growth in 2PS leading, on average, to a reduction in CPS of 0.16 percent for the firms in our sample. When CEO dominance is a dependent variable in the model and the use of two separate metrics is impractical, CPS and 2PS could be combined into a single index of overall CEO dominance. Consider, for instance, the ratio of the former on the latter. Such a ratio increases with CEO dominance, as it takes higher values for companies with high CPS and low 2PS. 2.2.2. Pay slice gap (PSG) Another simple measure of CEO dominance, Pay Slice Gap (PSG), can be constructed as the difference between the pay of the CEO 6
Second-in-line refers to the highest paid executive in a firm other than the CEO.
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M. Zagonov, G. Salganik-Shoshan
Fig. 4. Pay Slice Gap (PSG) and CEO Relative Compensation (CRC).
and that of the highest paid non-CEO manager divided by the total compensation of the five highest paid executives in the firm: PSG = (P1-P2)/(P1 + P2 + P3 + P4 + P5). The calculation uses the same set of data as used to compute CPS. Researchers may find PSG to be particularly relevant in instances where the difference in pay between the CEO and the highest paid non-CEO executive is the main focus of research. As the example in Fig. 1 highlights, CPS does not explicitly account for the difference in pay between the two. Fig. 4 presents the scatter plot of PSG against CRC. It is evident from the figure that one of the key advantage of PSG is that, unlike CPS, it removes entirely ambiguity about the degree of CEO dominance at the pivotal level of CRC = 1. Furthermore, the risk of CEO dominance misidentification is now also minimised over the region adjacent to this intuitively clear point of distinction between the dominant − even if marginally so − CEOs (CRC > 1) and the dominated ones (CRC ≤ 1). Another feature of PSG that will appeal to researchers is that it controls for firm-specific biases affecting its compensation policy in much the same way as does CPS. 2.3. Further considerations on CPS Bebchuk et al. (2011) propose normalising the CEO’s pay by the total compensation received by the top five highest paid managers as a means of addressing firm-specific biases that could affect a firm’s compensation policy. However, the authors do not explicitly examine the question of whether their normalization approach is the best method of addressing these biases. Bebchuk et al. (2011) state in their paper (footnote 2; p. 201) that “Chang et al., 2010 examine […] whether abnormal stock returns around managerial departure announcements are related to CPS”. Yet Chang et al. (2010) do not use CPS. They instead use a variable called “Relative Total Pay”, defined as the CEO pay divided by the total compensation of the next four highest paid executives in the firm: RTP = P1/(P2 + P3 + P4 + P5), i.e. the CEO’s pay is not included in the denominator. This difference is very important, because it means that RTP is not bounded from above, whereas CPS is: CPS = RTP/(RTP + 1). On these grounds, RTP is superior, especially when relative CEO pay is being used as the dependent variable in a regression (due to well-documented problems with limited dependent variables). An alternative solution would be to use the logistic transformation of the fractional variable that is CPS (Papke and Wooldridge, 2008). When CPS is the dependent variable, such a transformation is an econometric necessity. When CPS is an explanatory variable, the transformation is called for by the underlying economics: CPS changing from 0.7 to 0.8 (with the corresponding RTP value increasing from 2.3 to 4.0) represents a much smaller increase in CEO dominance than when CPS goes from 0.8 to 0.9 (with RTP increasing from 4.0 to 9.0). The scatter plot of RTP against CPS for our sample firms is presented in Fig. 5. As the figure illustrates, CPS compresses the variability in relative CEO pay when CEOs are highly dominant. Instead, most of the variability in relative CEO pay as captured by the CPS metric occurs when the CEO is rather weak (e.g. when P1 < P2 + P3 + P4 + P5), and this latter variation completely stifles the effect of variation in CEO pay when the CEO is strong. To summarise, there are numerous measures that can be constructed using compensation data for executives in the top team. Empirical researchers should therefore carefully consider and justify their choice of the best measure. A good starting point would be to set out the criteria for what constitutes a good measure of CEO dominance for their purpose. 3. Conclusions Despite the extensive popularity in the literature of the CEO Pay Slice, the rationale behind its conceptual definition and its empirical use as an unequivocal proxy for CEO dominance is questionable, as is its superiority in the class of measures one can construct from the top-five executive compensation data. Further, as we demonstrate in the paper, CPS discounts the valuable information contained in the compensation data for the executives in the top team other than the CEO. This often results in CPS failing to account accurately for any aberrant but widespread characteristics of the distribution of decision-making power among the 5
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Fig. 5. CEO Pay Slice (CPS) and Relative Total Pay (RTP).
top executives, as well as in misestimating the CEO’s relative power and ability to influence decisions that materially affect the firm’s outcomes. It is, therefore, important to carefully consider the precise applications for which its suitability and use as the only proxy for CEO dominance may be justified. Acknowledgements We are grateful to Alex Elias, Natalia Ostanina, and David Stolin for stimulating discussions and suggestions. Part of this paper was written while the first author was visiting the Krannert School of Management at Purdue University. All errors are ours. References Adams, R.B., Almeida, H., Ferreira, D., 2005. Powerful CEOs and their impact on corporate performance. Rev. Finance Stud. 18, 1403–1432. http://dx.doi.org/10. 1093/rfs/hhi030. Bebchuk, L.A., Martijn Cremers, K.J., Peyer, U.C., 2007. CEO Centrality. National Bur. Econ. Res, Cambridge, MA (Discuss. Pap. no.13701). Bebchuk, L.A., Cremers, K.J.M., Peyer, U.C., 2011. The CEO pay slice. J. Finance Econ. 102, 199–221. http://dx.doi.org/10.1016/j.jfineco.2011.05.006. Chang, Y.Y., Dasgupta, S., Hilary, G., 2010. CEO ability, pay, and firm performance. Manag. Sci. 56, 1633–1652. http://dx.doi.org/10.1287/mnsc.1100.1205. Chen, Z., Huang, Y., Wei, K.C.J., 2013. Executive pay disparity and the cost of equity capital. J. Finance Quant. Anal. 48, 849–885. http://dx.doi.org/10.1017/ S0022109013000306. Cheng, I.H., Hong, H., Scheinkman, J.A., 2015. Yesterday’s heroes: compensation and risk at financial firms. J. Finance 70, 839–879. http://dx.doi.org/10.1111/jofi. 12225. Chintrakarn, P., Jiraporn, P., Tong, S., 2014. How do powerful CEOs view corporate risk-taking? Evidence from the CEO pay slice (CPS). Appl. Econ. Lett. 22, 104–109. http://dx.doi.org/10.1080/13504851.2014.927565. Choe, C., Tian, G.Y., Yin, X., 2014. CEO power and the structure of CEO pay. Int. Rev. Finance Anal. 35, 237–248. http://dx.doi.org/10.1016/j.irfa.2014.10.004. Cooper, M.J., Gulen, H., Rau, P.R., 2014. Performance for Pay? The Relation Between CEO Incentive Compensation and Future Stock Price Performance. University of Cambridge (Working paper). Correa, R., Lel, U., 2013. Say on pay laws, executive compensation, CEO pay slice, and firm value around the world Work. Pap. − U.S. Fed. Reserv. Board’s. Int. Finance Discuss. Pap. 2–55. http://dx.doi.org/10.2139/ssrn.2274823. Finkelstein, S., 1992. Power in top management teams: dimensions, measurement, and validation. Acad. Manag. J. 35, 505–538. http://dx.doi.org/10.2307/256485. Hayward, M.L., Hambrick, D.C., 1997. Explaining the premiums paid for large acquisitions: evidence of CEO hubris. Adm. Sci. Q. 103–127. http://dx.doi.org/10. 2307/2393810. Jiraporn, P., Chintrakarn, P., 2013. How do powerful CEOs view corporate social responsibility (CSR)? An empirical note. Econ. Lett. 119, 344–347. http://dx.doi.org/ 10.1016/j.econlet.2013.03.026. Kale, J.R., Reis, E., Venkateswaran, A., 2009. Rank-order tournaments and incentive alignment: the effect on firm performance. J. Finance 64, 1479–1512. http://dx. doi.org/10.1111/j.1540-6261.2009.01470.X. Liu, Y., Jiraporn, P., 2010. The effect of CEO power on bond ratings and yields. J. Empir. Finance 17, 744–762. http://dx.doi.org/10.1016/j.jempfin.2010.03.003. Papke, L.E., Wooldridge, J.M., 2008. Panel data methods for fractional response variables with an application to test pass rates. J. Econ. 145 (1), 121–133. http://dx. doi.org/10.1016/j.jeconom.2008.05.009.
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