Based on prior research, we acknowledge the potential effects of firm performance and firm characteristics on payment asymmetry and add return on assets, market return, firm size and leverage in our further analysis. In addition, we also consider a nonlinearity check.
Table 5 provides the results after the effects of accounting-based and market-based
firm performance as well as the basic firm characteristics on payment asymmetry are controlled for. Specifically, we incorporate yearly industry-median-adjusted return on assets (ROA) and market-adjusted return (RET), firm size (SIZE) and leverage ratio (LEV) in equation (1) as additional control variables. As well-performing firms may pay more to reward their board members, we add ROA and RET into equation (1). Regarding SIZE and LEV, because firms smaller in size have less political costs (Watts and Zimmerman 1986) and firms with higher leverage are more influenced by debt covenants constraining their dividend payout ratios (Fenn and Liang 2001), they have an increased likelihood of payment asymmetry. In addition, as firms with more debt tend to have less free cash flows, we expect that SIZE and LEV have negative and positive signs, respectively.
Table 5 reports the results of the sensitivity checks. We find that the coefficients of BDSH, BLKSH and STMV are consistent with those in Table 4, therefore, H1, H2 and H6 hold. As for H4, supported in Table 4, the coefficients of FMDM in Table 5 (-0.071 for the Probit and -0.536 for the Tobit) reveal that their explanatory power is reduced to the one-tailed significance level (p-value < 0.10). However, for H3, which is not supported in Table 4, the coefficients of INDST in Table 5 (-0.003 for the Probit and -0.015 for the Tobit) reveal that they are significant at the one-tailed level (p-value < 0.10). We still find no evidence to confirm that there is an association between VMCF and payment asymmetry. Combining evidence from Table 4 and Table 5, we note strong evidence to support H1, H2 and H6. We find weak evidence in favor of H3 and H4, but we cannot find evidence to support H5.
With respect to the control variables, we find that the coefficients of MGST (-0.374 for the Probit and -2.833 for the Tobit) are significant at the two-tailed level (p-value <0.10).
One possible reason that MGST (the seat percentage of executives on the board) decreases the likelihood of payment asymmetry is that executives are entitled to receive a bonus and are therefore less concerned about board compensation. As for the newly-added control variables ROA, RET, SIZE and LEV, we find that the accounting-based performance, ROA, is significantly associated with the likelihood and severity of payment asymmetry. However, the market-based performance, RET, has no incremental explanatory power. Finally, Table 5 reveals that political cost, proxied by SIZE, and debt covenant, proxied by LEV, are significantly related to payment
asymmetry.
On the question of potential nonlinearity problems, Anderson et al. (2003) document a nonlinear relation between ownership and firm performance, and Wang (2006) reports the same finding but with a focus on earnings quality. So that our findings are not subject to nonlinearity issues, we further examine whether the relations between payment asymmetry and the variables of interests in this study are nonlinear. We use a dummy variable approach to untangle this issue.
Using BDSH as an example, we first equally divide the observations into High, Median and Low, i.e. into three subsamples based on shareholdings of board members. Second, we generate two dummy variables, BDSH_Low and BDSH_High. BDSH_Low equals one if that observation falls into the lowest subsample (i.e., the Low subgroup), and zero otherwise. Similarly, BDSH_High equals one if that observation falls into the highest subsample (i.e., the High subgroup), and zero otherwise. This means we adopt the Middle subgroup as the benchmark to conduct the nonlinearity check. The direction of the coefficient of BDSH_Low (BDSH_High) indicates the difference in the board member shareholding effect on payment asymmetry between the lowest (highest) subgroup and the middle subgroup. In addition, in cases where the coefficients of BDSH_Low and BDSH_High are significant and their signs are in the same direction, it indicates that the relationship between BDSH and payment asymmetry is nonlinear. Based on the same reasoning, BLKSH_High and BLKSH_Low (STMV_High and STMV_Low) are further derived from BLKSH (STMV).
In the case of FMDM, we further divide the sample into three subgroups, and we assign firms with FMDM = 0 to the FMDM_Low subgroup and those with FMDM = 1 into the FMDM_High and FMDM_Middle subgroups on the basis of the median percentage of controlling family members on the board. In our major finding, since INDST and VMCF are not related to payment asymmetry, we conduct no further analysis.
Therefore, we use the following regression model to explore the potential nonlinearity effect on the issue of asymmetric payment following the dummy variable approach.
ε Table 6 presents the results of the nonlinearity tests. When the coefficients of the variables underscored with Low and High have opposite directions, it is indicative of a linear relation. When the coefficients are both significant and in the same direction, there is a potential nonlinearity problem. As shown in Table 6, for each variable, the coefficients attached to Low and High are either in opposite directions (i.e. BDSH and STMV) or in the same direction but insignificant (i.e. BLKSH and FMDM). Hence, we conclude that our findings are not sensitive to the potential nonlinearity problem. 26
Finally, our non-tabulated results show that our main conclusions are qualitatively unchanged when those firms with net earnings that do not pay dividends are included.
7. CONCLUSIONS
Against the backdrop of the OECD’s plea for corporate boards to be responsible for aligning key executive and board remuneration with the longer-term interests of their company and its shareholders (OECD 2004, p.24), this study examines whether and how ownership structure, board structure and deviation between ownership and control affect the fairness of payments between board members and shareholders. By examining the asymmetric payment between board and shareholders, this study contributes to the line of research on board effectiveness vis-à-vis minority shareholders. To structure our analysis, we construct six research hypotheses related to the determinants of payment asymmetry.
Three major findings emerge from our analysis. First, we find how ownership structure affects payment asymmetry. Admittedly, there is a tradeoff between board remuneration and dividends (if the board member is also a large shareholder), but given that the total amount of payment available for distribution is fixed, we find that the smaller the
26 We also perform Ramsey RESET (regression specification error test) on equation (2). The purpose of RESET is to detect omitted variables and incorrect functional form, and the results suggest that our linear model is adequate.
monetary reward received by shareholders in the form of dividends, the greater is the severity of payment asymmetry. More specifically, we find compelling evidence to support our first hypothesis that the percentage of shares held by board members is negatively associated with the likelihood and extent of payment asymmetry. On the question of the role of outside blockholders, we also find convincing evidence to substantiate the second hypothesis that larger shareholding by outside blockholders diminishes the likelihood and extent of payment asymmetry.
Second, we show how board structure influences payment asymmetry, the bases of our third and fourth hypotheses. We only find weak evidence that these two factors have an effect on reducing payment asymmetry.
Finally, we find evidence on how deviation between ownership and control affects asymmetric payment. While our fifth hypothesis postulates that the conventional measure, voting deviation, affects payment asymmetry, our sixth hypothesis posits that the new measure, seat-control deviation, does affect unfair payment. What our empirical results confirm is worth noting: although the conventional measure does not have the ability to explain payment asymmetry, by all means the new measure, seat-control deviation, does have the explanatory power.
To check for robustness, we perform additional sensitivity tests, which include incorporating accounting- and market-based performances as well as several firm characteristics into our basic model. We also conduct test of nonlinearity. The results of these additional analyses fully support the conclusions discussed above.
Our study contributes to the extant literature on the effectiveness of boards. We formally document factors affecting payment asymmetry, one of the core governance principles underscored by the OECD (1999, 2004). Prior literature has mainly focused on how the board interacts with other agents (e.g., executive and auditor), while ignoring the board per se. This paper is unique in large measure because it investigates situations where the self-interests of the board predominate with the result that it constitutes a potential conflict of interest between the board and the external shareholders.
Several caveats must be considered when interpreting the findings of this study. First, although our findings have implications for board effectiveness, on account of expected institutional differences across countries, caution should be taken before making any
generalizations based on our conclusions. For example, La Porta et al. (1998, 2000, 2006) document cross-country differences in legal institutions and investor protection, and Shleifer and Wolfenzon (2002) analytically examine investor protection and equity markets. In fact, earnings management (Leuz, Nanda and Wysocki 2003) and disclosure incentives and their effects on the cost of capital (Franncis, Khurana and Pereira 2005) around the world are different. We believe that it would be fruitful to re-examine issues surrounding payment asymmetry in a cross-country context. Finally, also promising would be an examination of the economic consequences of payment asymmetry, such as the cost of capital and analyst ratings.
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TABLE1: Sample Selection and Distribution by Year (1997-2005)
Selection procedures 1997 1998 1999 2000 2001 2002 2003 2004 2005 Total
Original sample 999 1,089 1,131 1,163 1,176 1,187 1,188 1,188 1,185 10,306
Less:
mple
banking & financial industries (21) (24) (25) (27) (31) (41) (42) (42) (41) (294) missing data on governance
variables (408) (416) (371) (333) (262) (104) (34) 0 0 (1928) firms with net loss (60) (144) (149) (179) (260) (246) (206) (243) (298) (1785) firms with net income but pay
no dividends (76) (58) (83) (96) (96) (121) (130) (95) (87) (842)
Final sample 434 447 503 528 527 675 776 808 759 5,457
Fair payment sa
DIV > MDIV 212 218 248 258 258 333 385 400 375 2,687
DIV ≤ MDIV & CMP < MCMP 104 101 117 140 134 173 211 220 202 1,402
Total 316 319 365 398 392 506 596 620 577 4,089
Unfair payment sample
DIV≤ MDIV & CMP ≥ MCMP 118 128 138 130 135 169 180 188 182 1,368 Notes: Sample included are firms with dividend payout ratios more than zero.
DIV = the dividend payout ratio;
MDIV = industry median of DIV;
CMP = total compensation of board members scaled by net earnings; and MCMP = industry median of CMP.
TABLE 2: Descriptive Statistics
Panel A: Continuous variables
A: UFDM =1 (N= 1,368) B: UFDM = 0 (N= 4,089) difference variable mean median std. dev. mean median std. dev. mean median BDSH 26.71 24.15 13.80 30.58 27.47 16.06 -3.87*** -3.32***
BLKSH 14.68 13.72 9.98 15.65 14.29 11.50 -0.96*** -0.57***
INDST 8.30 0.00 14.07 8.70 0.00 14.93 -0.39 0.00
VMCF 5.62 1.82 9.41 6.86 1.47 11.81 -1.25*** 0.35***
STMV 30.86 29.41 21.77 27.08 25.77 24.01 3.78*** 3.64***
BDSZ 9.88 9.00 3.71 9.44 9.00 3.14 0.44*** 0.00
PLDG 9.52 0.00 17.13 8.50 0.00 17.40 1.01** 0.00
INST 1.54 0.00 3.51 1.56 0.00 3.65 -0.02 0.00
FINST 0.07 0.00 0.54 0.10 0.00 0.93 -0.03 0.00
MGST 0.13 0.10 0.13 0.13 0.10 0.13 0.00 0.00
Panel B: Dichotomous variables
A: UFDM =1 (N= 1,368) B: UFDM = 0 (N= 4,089) difference
variable mean mean χ2
FMDM 49% 55% 11.42***
DUAL 27% 30% 5.17**
Notes:
*, ** and ***: significant at the 0.10, 0.05 and 0.10 level using a two-tailed test Variable definitions:
BDSH = board member shareholding %;
BLKSH = outside blockholder shareholding %;
INDST = % of independent board member;
FMDM = one if the firm is a family-controlled firm, and zero otherwise;
VMCF = voting right minuses cash flow right;
STMV = seat control right minuses voting right;
BDSZ = board size in seat number;
DUAL = whether CEO serves as chair of the board;
INST: = % of stock by domestic financial institutes;
FINST = % of stock by foreign financial institutes;
MGST = % of executive members on the board; and PLDG = % of stock pledged by board members.
TABLE 3: Correlation Matrix
Panel A: UFDM on the corporate governance variables studied
UFRK BDSH BLKSH INDST FMDM VMCF STMV BDSZ DUAL INST FINST MGST PLDG UFRK 1.00 -0.10*** -0.02* 0.00 -0.05*** 0.01 0.08*** 0.05*** -0.03** -0.02 -0.03*** 0.01 0.05***
BDSH -0.09*** 1.00 -0.21*** -0.03*** 0.05*** 0.20*** -0.43*** 0.01 -0.03** -0.15*** -0.14*** -0.02 -0.25***
BLKSH -0.03*** -0.25*** 1.00 0.22*** -0.03** -0.12*** -0.20*** -0.09*** 0.03** 0.00 -0.02 -0.02* -0.08***
INDST 0.01 -0.03*** 0.20*** 1.00 -0.12*** -0.05*** -0.37*** 0.09*** 0.07*** 0.08*** -0.07*** -0.06*** -0.28***
FMDM -0.06*** 0.07*** -0.02* -0.12*** 1.00 -0.14*** 0.34*** -0.15*** -0.06*** 0.06*** 0.11*** -0.31*** 0.09***
VMCF -0.04*** 0.42*** -0.15*** -0.03*** 0.00 1.00 0.05*** 0.15*** -0.12*** 0.03** -0.01 0.50*** -0.05***
STMV 0.04*** -0.44*** -0.23*** -0.39*** 0.35*** -0.09*** 1.00 -0.06*** -0.07*** 0.15*** 0.20*** 0.18*** 0.33***
BDSZ 0.05*** 0.01 -0.11*** -0.04*** -0.13*** 0.10*** -0.01 1.00 -0.16*** 0.21*** 0.03** -0.07*** 0.07***
DUAL -0.02 -0.05*** 0.03** 0.07*** -0.06*** -0.15*** -0.07*** -0.17*** 1.00 -0.06*** -0.05*** 0.05*** -0.09***
INST 0.00 0.00 0.01 0.04*** 0.00 0.00 0.04*** 0.15*** -0.03*** 1.00 0.23*** -0.04*** 0.15***
FINST -0.02 -0.06*** 0.01 -0.03*** 0.03** -0.02 0.09*** 0.02 -0.01 0.02* 1.00 -0.00 0.16***
MGST 0.00 -0.04*** -0.03*** -0.08*** -0.30*** 0.24*** 0.20*** -0.09*** 0.05*** -0.07*** 0.02 1.00 -0.05***
PLDG 0.02 -0.21*** -0.04*** -0.20*** 0.11*** -0.08*** 0.28*** 0.01 -0.07*** 0.00 0.07*** -0.07*** 1.00
TABLE 3 (continued)
Panel B: UFRK on the corporate governance variables studied
UFRK BDSH BLKSH INDST FMDM VMCF STMV BDSZ DUAL INST FINST MGST PLDG UFRK 1.00 -0.10*** -0.02* 0.00 -0.05*** 0.01 0.07*** 0.05*** -0.03** -0.02 -0.03*** 0.00 0.05***
BDSH -0.09*** 1.00 -0.21*** -0.03*** 0.05*** 0.19*** -0.43*** 0.01 -0.03** -0.15*** -0.14*** -0.02 -0.25***
BLKSH -0.03** -0.25*** 1.00 0.22*** -0.03** -0.11*** -0.20*** -0.08*** 0.03** 0.00 -0.018 -0.02* -0.08***
INDST 0.01 -0.03** 0.20*** 1.00 -0.12*** -0.05*** -0.37*** 0.09*** 0.07*** 0.08*** -0.07*** -0.06*** -0.28***
FMDM -0.06*** 0.07*** -0.02* -0.12*** 1.00 -0.14*** 0.34*** -0.15*** -0.06*** 0.06*** 0.11*** -0.31*** 0.09***
VMCF -0.04*** 0.42*** -0.15*** -0.03* 0.00 1.00 0.05*** 0.15*** -0.12*** 0.03** -0.0103 0.49*** -0.05***
STMV 0.04*** -0.44*** -0.23*** -0.39*** 0.35*** -0.09*** 1.00 -0.06*** -0.07*** 0.15*** 0.20*** 0.18*** 0.33***
BDSZ 0.05*** 0.01 -0.11*** -0.04*** -0.13*** 0.10*** -0.01 1.00 -0.16*** 0.21*** 0.03** -0.07*** 0.07***
DUAL -0.02 -0.05*** 0.03** 0.07*** -0.06*** -0.15*** -0.07*** -0.17*** 1.00 -0.07*** -0.05*** 0.05*** -0.09***
INST -0.00 -0.00 0.01 0.04*** 0.00 0.00 0.04*** 0.15*** -0.03*** 1.00 0.23*** -0.04 0.15***
FINST -0.02 -0.06*** 0.01 -0.03*** 0.03** -0.02 0.09*** 0.02 -0.01 0.02 1.00 -0.00 0.16***
MGST 0.00 -0.04*** -0.03*** -0.08*** -0.30*** 0.24*** 0.20*** -0.09*** 0.05*** -0.07*** 0.02 1.00 -0.05***
PLDG 0.02 -0.21*** -0.04*** -0.20*** 0.11*** -0.08*** 0.28*** 0.01 -0.07*** 0.00 0.07*** -0.07*** 1.00
Notes:
The lower (upper) half on the left (right) of the matrix reports the Pearson (Spearman) correlation coefficients.
*, **, and***: significant at the 0.10, 0.05 and 0.10 level using a two-tailed test Variable definitions:
UFDM: a dummy variable equals 1 if the firm has payment asymmetry, and 0 otherwise; UFRK: the severity of payment asymmetry; BDSH: board member shareholding %; BLKSH: outside blockholder shareholding %; INDST: % of independent director; FMDM: one if the firm is a family-controlled firm, and zero otherwise; VMCF: voting right minuses cash flow right; STMV: seat control right minuses voting right; BDSZ: board size in seat number; DUAL: whether the CEO serves as chair of the board; INST: % of stock by domestic financial institutes; FINST: % of stock by foreign financial institutes; MGST: % of executive members on the board; and PLDG: % of stock pledged by directors.
TABLE 4: Empirical Results for Unfair Payment (N=5,457) Depend variable: UFDM
(Probit model)
Depend variable: UFRK (Tobit model) variables predicted sign coefficient p-value coefficient p-value
constant ? -0.403 0.000 -2.882 0.001
BDSH – -0.009 0.000 -0.066 0.000
BLKSH – -0.006 0.002 -0.045 0.002
INDST – 0.001 0.702 0.007 0.493
FMDM – -0.157 0.001 -1.166 0.001
VMCF + -0.002 0.264 -0.014 0.352
STMV + 0.003 0.045 0.016 0.093
BDSZ ? 0.017 0.003 0.118 0.004
DUAL ? -0.096 0.024 -0.603 0.051
INST ? -0.004 0.493 -0.029 0.458
FINST ? -0.048 0.113 -0.395 0.082
MGST ? -0.218 0.198 -1.481 0.226
PLDG ? -0.000 0.720 -0.002 0.769
LR χ2 (12) =124.25 LR χ2 (12) = 119.79 p-value (χ2) =0.000 p-value (χ2) = 0.000
Note: all p-values are two-tailed.
Variable definitions:
UFDM = a dummy variable equals 1 if the firm has payment asymmetry, and 0 otherwise;
UFRK = the severity of payment asymmetry;
BDSH = board member shareholding %;
BLKSH = outside blockholder shareholding %;
INDST = % of independent director;
FMDM = one if the firm is a family-controlled firm, and zero otherwise;
VMCF = voting right minuses cash flow right;
STMV = seat control right minuses voting right;
BDSZ = board size in seat number;
DUAL = whether the CEO serves as chair of the board;
INST: = % of stock by domestic financial institutes;
FINST = % of stock by foreign financial institutes;
MGST = % of executive members on the board; and PLDG = % of stock pledged by board members.
TABLE 5: Control for Firm Performance and Firm Characteristics
Depend variable: UFDM
(Probit model)
Depend variable: UFRK
Depend variable: UFRK