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Compensation gaps among top executives: the role of the peer groups Chi-Hung Chang Min-Teh Yu Jen-Chih Kuo Graduate Institute of Finance National Chiao.

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Presentation on theme: "Compensation gaps among top executives: the role of the peer groups Chi-Hung Chang Min-Teh Yu Jen-Chih Kuo Graduate Institute of Finance National Chiao."— Presentation transcript:

1 Compensation gaps among top executives: the role of the peer groups Chi-Hung Chang Min-Teh Yu Jen-Chih Kuo Graduate Institute of Finance National Chiao Tung University

2 Abstract  This paper explores if the peer groups make a difference in the explanation of the compensation gaps between top executives.  We find that the productivity theory is applied to the large firm peer and the high CEO compensation peer.  The tournament effect is applied for the small firm peer and the pay gaps between non-CEO executives.

3 Background  Determinants of CEO compensation Personal characteristics – age, educational level, tenure, … Firm characteristics – firm performance Benchmarking pay level of peer groups (Bizjak et al. (2008, JFE); Faulkender and Yang (2010, JFE))  The relevance of benchmarking pay Representing reservation wage (Hokmstrom and Kaplan (2003, JACF)) Self-serving (Bizjak et al. (2011, JFE); Faulkender and Yang (2010, JFE))  How are peer groups determined? Industry and size – Bizjak et al. (2008, JFE) Actual disclosure – Faulkender and Yang (2010, JFE)

4 Background  Compensation of non-CEO executives Productivity – Higher level managers are more productive than lower level ones. Tournament – Compensation difference can motivate executives’ efforts.  Which one dominates? Tournament incentives (Kale et al. (2009, JF)) Productivity differential (Masulis and Zhang (2012, working))  Research question: Is the peer group responsible for the difference between the tournament and productivity effect?

5 Why is non-CEO executives’ pay relevant?  Team work of the corporation organization  The gaps between CEO and other top executives vary materially across companies (Masulis and Zhang (2012, working)). Why? Is the CEO really extremely talented? Does the firm want to stimulate non-CEO executives’ efforts to multiply the benefit of team work?  Contagion effect in CEO compensation across companies ( Bereskin and Cicero (2012, JFE) ). Non-CEO executives’ pay in other companies would be referred when determining their rewards.

6 Theories of compensation gaps  Productivity theory Rosen (1981, 1982); Gabaix and Landier (2008) – Multiplicative productivity models  Higher level managers are more productive than lower level ones.  Tournament theory Lazear and Rosen (1981); Green and Stokey (1983); Rosen (1986)  A mechanism to elicit executives’ efforts

7 Empirical evidence of compensation gaps  Productivity differentials Finkelstein and Hambrick (1988, SMJ); Gibbs (1995, JAE); Prendergast (1999, JEL); Anabtawi (2005, ELJ); Masulis and Zhang (2012, working)  Tournament effect Main et al. (1993, JLE); Eriksson (1999, JLE); Bognanno (2001, JLE)  Controversy still remains.

8 Hypotheses  H1: The compensation gap in the larger peer is more likely to reflect productivity differentials.  H2: The compensation gaps in the peer group with higher CEO pay would more likely support the productivity theory.  H3: The compensation gaps between executives below the CEO would more probably reflect the tournament theory.

9 Empirical strategy  Data: Compensation data from Execcucomp over 1993- 2005; firm characteristics data from Compustat.  Determining peers based on industry and size (following Bizjak et al., 2008, JFE).  Industry: 2-digit SIC code  Size: median sales Size peer groups CEO compensation peers Executives compensation peers

10 Variables  CEO compensation gap Total gap = log(total CEO compensation/median total compensation of non- CEO executives) Short-term and long-term gap are defined similarly.  Non-CEO executives compensation gap Total gap = log(Highest non-CEO total compensation/lowest non-CEO executives’ total compensation) Short-term and long-term gap are defined similarly.  Tournament measure: number of non-CEO executives  Productivity measure: executive’s position tenure, the average pay growth over the past three years

11 Variables (Cont.)  Control variables  Incentive variables CEO pay growth CEO tenure CEO alignment Executives alignment  Firm characteristics variables Lagged assets Lagged market-to-book ratio R&D intensity

12 Descriptive statistics  Executives pay is substantially higher in larger firms. Industry-size above the peer medianIndustry-size below the peer medianDiff. Compensation level CEO_Total6673.24 (9188) 2906.11 (4967) 3767.12*** CEO_ST1793.26 (9188) 841.50 (4967) 951.76*** CEO_LT4879.98 (5287) 2064.61 (4374) 2815.37*** Executives_Total2376.06 (37418) 1040.55 (19653) 1335.51*** Executives_ST792.85 (37418) 377.32 (19653) 415.53*** Executives_LT1583.21 (22396) 663.23 (17645) 919.98*** Notes: Figures in parenthesis are observations. *** Significant at the 1% level.

13 Descriptive statistics (Cont.)  Compensation gaps between CEO and other executives are substantial. Industry-size above the peer medianIndustry-size below the peer medianDiff. Compensation gap (dollar term, in thousand) Total gap4594.06 (9188) 1995.24 (4967) 2598.82*** Short term gap1056.24 (9188) 489.57 (4967) 566.67*** Long term gap3551.69 (9188) 1151.50 (4967) 2040.19*** Compensation gap (ratio) Total gap3.31 (9188) 3.08 (4967) 0.24*** Short term gap2.52 (9187) 2.32 (4967) 0.19*** Long term gap4.67 (9188) 4.49 (4967) 0.18 Notes: Figures in parenthesis are observations. *** Significant at the 1% level.

14 Regression results on size peers  Tournament effect is more significant and the magnitude is larger for the small size peer. Total GapShort-term GapLong-term Gap Size above peer group median Size below peer group median Size above peer group median Size below peer group median Size above peer group median Size below peer group median VP_Num0.023*0.044***-0.0070.0080.035**0.051** (0.013)(0.016)(0.013)(0.015)(0.017)(0.024) CEO_Alignment0.0000.007***-0.006**0.005***-0.0000.005* (0.002) (0.003)(0.002)(0.003) VP_Alignment-0.038*-0.068***-0.024-0.062***-0.049*-0.086*** (0.019)(0.010)(0.015)(0.011)(0.026)(0.013) CEO_Tenure0.007-0.039***0.073***0.062***-0.024*-0.074*** (0.011)(0.014)(0.013)(0.015)(0.014)(0.021) Lag_Assets0.020***0.065***-0.0120.024*0.0100.045** (0.006)(0.012)(0.009)(0.013)(0.008)(0.018) Lag_MTB0.0010.010**-0.031**-0.004-0.013**0.001 (0.006)(0.004)(0.013)(0.003)(0.006)(0.005) R&D_Intensity-0.025*0.019-0.088***-0.039-0.035*0.074** (0.014)(0.021)(0.022)(0.024)(0.019)(0.031) Constant0.808***0.376***1.051***0.632***1.109***0.518*** (0.103)(0.109)(0.121)(0.132)(0.142)(0.165) Observations6,4983,6546,4883,6416,4983,654 Year dummies and industry fixed effects Yes R-squared0.0530.1050.0510.1390.0460.079 Adj R_squ0.04220.08740.04040.1220.03500.0605

15 Regression results on size peers (Cont.)  Productivity effect is significant for the large size peer. Total GapShort-term GapLong-term Gap Size above peer group median Size below peer group median Size above peer group median Size below peer group median Size above peer group median Size below peer group median VP_Pay_Growth0.000 -0.000*0.000-0.0000.000 (0.000) Vp_Tenure-0.137***-0.056-0.064*-0.015-0.155***-0.103* (0.026)(0.039)(0.038)(0.030)(0.036)(0.059) CEO_pay_Growth0.000*** 0.000-0.0000.000***0.000** (0.000) CEO_Alignment-0.0020.002-0.008**0.005**-0.0030.000 (0.002)(0.003) (0.002)(0.003)(0.004) VP_Alignment-0.018-0.068***-0.006-0.057***-0.024-0.085*** (0.017)(0.010)(0.012)(0.008)(0.023)(0.014) CEO_Tenure0.108***0.0450.128***0.047**0.088***0.063 (0.015)(0.028)(0.021)(0.022)(0.021)(0.041) Lag_Assets0.024***0.075***-0.0210.056***0.0150.044* (0.008)(0.017)(0.016)(0.011) (0.026) Lag_MTB0.0010.009-0.0280.003-0.010-0.004 (0.006)(0.007)(0.020)(0.004)(0.007)(0.010) R&D_Intensity-0.048**0.006-0.140***-0.025-0.059**0.051 (0.019)(0.028)(0.041)(0.021)(0.027)(0.043) Constant1.014***0.543***1.133***0.444***1.406***0.930*** (0.114)(0.141)(0.178)(0.080)(0.163)(0.200) Observations3,4541,6543,4521,6533,4541,654 Year dummies and industry fixed effects Yes R-squared0.0920.2000.0720.2900.0720.142 Adj R_squ0.07290.1650.05250.2600.05230.105

16 Regression results on CEO compensation peers  Tournament proxy is significant for the low CEO pay peer. Total GapShort-term GapLong-term Gap CEO pay above peer group median CEO pay below peer group median CEO pay above peer group median CEO pay below peer group median CEO pay above peer group median CEO pay below peer group median VP_Num0.0240.038***0.0060.0010.0380.048*** (0.019)(0.012)(0.022)(0.011)(0.024)(0.017) CEO_Alignment0.007**0.002-0.002-0.0000.008*0.000 (0.003)(0.002)(0.004)(0.001)(0.004)(0.002) VP_Alignment-0.044-0.058***-0.022-0.050***-0.062-0.072*** (0.031)(0.009)(0.023)(0.009)(0.042)(0.012) CEO_Tenure0.046**-0.056***0.071**0.046***0.052*-0.098*** (0.019)(0.009)(0.030)(0.009)(0.026)(0.014) Lag_Assets0.017**0.043***-0.0090.018***0.0050.030*** (0.007)(0.006)(0.012)(0.006)(0.010)(0.008) Lag_MTB-0.0070.005-0.022***-0.015**-0.016**-0.008 (0.006)(0.005)(0.008)(0.007) (0.006) R&D_Intensity-0.015-0.016-0.094***-0.068***-0.005-0.001 (0.019)(0.015)(0.035)(0.017)(0.026)(0.021) Constant0.827***0.582***1.115***0.693***1.010***0.804*** (0.151)(0.079)(0.163)(0.081)(0.206)(0.115) Observations3,4316,7213,4286,7013,4316,721 Year dummies and industry fixed effects Yes R-squared0.0870.0620.0540.0600.0820.049 Adj R_squ0.06750.05150.03440.04980.06270.0385

17 Regression results on CEO compensation peers (Cont.)  Productivity proxy is significant for the high and low CEO pay peers. Total GapShort-term GapLong-term Gap CEO pay above peer group median CEO pay below peer group median CEO pay above peer group median CEO pay below peer group median CEO pay above peer group median CEO pay below peer group median VP_Pay_Growth-0.0000.000-0.000***-0.000 0.000 (0.000) VP_Tenure-0.094**-0.136***0.016-0.094***-0.143***-0.151*** (0.041)(0.025)(0.053)(0.029)(0.055)(0.037) CEO_pay_Growth0.0000.000***0.000-0.0000.0000.000*** (0.000) CEO_Alignment0.008*-0.003-0.005-0.0020.007-0.005 (0.004)(0.002)(0.007)(0.002)(0.005)(0.003) VP_Alignment-0.024-0.051***-0.001-0.045***-0.033-0.065*** (0.025)(0.010)(0.014)(0.009)(0.034)(0.015) CEO_Tenure0.128***0.057***0.108*0.095***0.172***0.030 (0.030)(0.015)(0.057)(0.013)(0.044)(0.022) Lag_Assets0.018**0.049***-0.0250.020**0.0050.039*** (0.009)(0.007)(0.019)(0.008)(0.012)(0.011) Lag_MTB-0.012*0.004-0.028-0.011**-0.025***-0.018* (0.007)(0.008)(0.019)(0.006)(0.009)(0.011) R&D_Intensity-0.052**-0.031-0.157**-0.087***-0.057-0.025 (0.026)(0.021)(0.062)(0.026)(0.036)(0.030) Constant1.160***0.932***1.292***0.683***1.445***1.388*** (0.201)(0.096)(0.240)(0.074)(0.303)(0.137) Observations1,9893,1191,9883,1171,9893,119 Year dummies and industry fixed effects Yes R-squared0.0940.1160.0700.1030.0920.088 Adj R_squ0.06100.09550.03640.08250.05920.0674

18 Regression results on non-CEO executives compensation peers  Tournament proxy is significant for the high and low non-CEO executives pay peers. Total GapShort-term GapLong-term Gap VP pay above peer group median VP pay below peer group median VP pay above peer group median VP pay below peer group median VP pay above peer group median VP pay below peer group median VP_Num0.216***0.209***0.116***0.098***0.274***0.301*** (0.018)(0.012)(0.016)(0.012)(0.026)(0.019) CEO_Alignment0.076***0.040***0.054***0.022***0.065***0.037*** (0.017)(0.007)(0.013)(0.006)(0.022)(0.008) VP_Alignment-0.032-0.014-0.015-0.0090.0090.004 (0.025)(0.014)(0.021)(0.009)(0.036)(0.019) CEO_Tenure-0.003-0.077***-0.012-0.008-0.019-0.116*** (0.015)(0.010)(0.013)(0.008)(0.023)(0.015) Lag_Assets0.014**0.026***0.017***0.008-0.004-0.005 (0.006) (0.005) (0.009) Lag_MTB0.007**0.020***0.001 -0.0080.004 (0.004) (0.002)(0.009)(0.005)(0.006) R&D_Intensity0.0250.030**0.016-0.0030.0300.044* (0.019)(0.015) (0.012)(0.029)(0.023) Constant-0.344**-0.361***0.0010.116-0.173-0.245* (0.136)(0.085)(0.117)(0.075)(0.266)(0.127) Observations3,7926,3753,7906,3593,7926,375 Year dummies and industry fixed effects Yes R-squared0.1630.1420.1700.0870.1130.110 Adj R_squ0.1480.1320.1540.07680.09600.0999

19 Regression results on non-CEO executives compensation peers (Cont.)  Productivity proxy is generally not significant for the high and low non-CEO peers. Total GapShort-term GapLong-term Gap VP pay above peer group median VP pay below peer group median VP pay above peer group median VP pay below peer group median VP pay above peer group median VP pay below peer group median VP_Pay_Growth-0.001*0.000-0.000-0.001***-0.001*0.000 (0.001) (0.000) (0.001) VP_Tenure0.029-0.0140.0140.020-0.010-0.057 (0.048)(0.031)(0.036)(0.024)(0.064)(0.045) CEO_pay_Growth0.001*0.000 0.001***0.001*0.000 (0.001) (0.000) (0.001) CEO_Alignment0.067***0.032***0.048***0.021***0.066***0.030*** (0.019)(0.009)(0.016)(0.006)(0.024)(0.010) VP_Alignment-0.031-0.019-0.022-0.009-0.011-0.014 (0.029)(0.014)(0.024)(0.010)(0.039)(0.015) CEO_Tenure-0.063***-0.073***-0.056***-0.021-0.077**-0.105*** (0.024)(0.022)(0.020)(0.017)(0.033) Lag_Assets0.025**0.046***0.0080.016**0.0200.033** (0.010)(0.009)(0.008)(0.007)(0.013) Lag_MTB0.009-0.0030.003-0.016**-0.004-0.035** (0.006)(0.011)(0.004)(0.007)(0.008)(0.015) R&D_Intensity-0.0140.056**0.0150.028-0.0340.043 (0.029)(0.028)(0.022)(0.019)(0.040) Constant0.710***0.412***0.389***0.433***1.167***0.878*** (0.213)(0.112)(0.090)(0.103)(0.345)(0.164) Observations1,6722,3411,6712,3371,6722,341 Year dummies and industry fixed effects Yes R-squared0.1880.1300.2220.1410.1320.101 Adj R_squ0.1530.1030.1880.1150.09420.0732

20 Conclusions  This paper examines the role of the peer group on the tournament and productivity effect of the compensation gaps.  Major findings Productivity differentials are observed in the large size peer and high CEO compensation peer. Tournament effect is observed in the small size peer and the pay gap among non-CEO executives.  Our findings could help reconcile the debate on the tournament and productivity effect of the compensation gaps of top executives.

21 Thank You!

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