Regression Results and Discussion

The main results from estimating the panel data regressions are presented in table 5. The predicted direction of the relationship is presented in column 2 and the coefficient estimates are presented in column 3-8.

Table 4: Difference-in-Difference Results

Estimate

EG 0.306***

(0.004)

PE 1.174***

(0.027)

D 0.250***

(0.046)

Adjusted R² 0.372

Number of Observations 503,146

This table presents the estimates of the difference-in-difference equation defined in model (5) of the main text. The sample period is 2000-2015, where the pre-event period is 2000-2007 and the post-event period is 2008-2015.

Companies operating with financial and insurance activities are excluded from the sample. CEO compensation is winsorized at 1% and 99% tails. EG is a dummy variable which takes the value of 1 if the company is in the event group and 0 if the company is in the non-event control group. Furthermore, the dummy variable PE is 1 if the company is in the post-event period, and 0 if the company is in the pre-event period. The difference-in-difference coefficient (D) reflects the effect on the CEO compensation if the observation is a public company (rather than a private company) in the event period (rather than in the non-event period).

23 7.2.1. Main Results

The results show that diversity on boards is not significantly related to CEO compensation in the time period from 2000 to 2015 for any of the three measures of diversity. The results are found to be robust to different measures of diversity and different models for CEO compensation. Nevertheless, we suspect that gender diversity may have had an impact on CEO compensation towards 2008, when the GBL became mandatory. Therefore, we will further analyze the relationship between gender diversity on boards and CEO compensation by examining different time periods in section 7.3.

7.2.2. Other Determinants of CEO Compensation

The findings support our prediction of a positive relationship between financial performance and diversity. This is in accordance with agency theory suggesting that the CEO should be rewarded for their contribution to the company’s good financial performance.

Table 5: Main Results

Independent Variables Prediction Model 1 Model 2 Model 1 Model 2 Model 1 Model 2

%Women +/- 0.001

CEO Gender (Female) +/- -0.192*

(0.093)

Fixed Effects Yes Yes Yes Yes Yes Yes

Time Effects No Yes No Yes No Yes

Adjusted R² 0.224 0.176 0.224 0.176 0.224 0.176

Number of Observations 3,214 3,214 3,214 3,214 3,214 3,214

Number of Companies 740 740 740 740 740 740

This table presents the estimated coefficients of the diversity measures and the control variables. The regression models are specified in model (1) and model (2) of the main text. Model (1) include all the control variables. Model (2) exclude the company size variable due to high correlation with the board size variable. Including both variables in the regression model could involve some degree of redundancy. The predicted signs of the coefficients are presented in column 2. For each model and measure of gender diversity, we report the coefficient estimates, the standard errors (in parenthesis) and the significance level where 1%, 5% and 10% significance level are denoted by ***, ** and * , respectively. The data sample consists of Norwegian public companies in the period from 2000 to 2015. Companies operating with financial and insurance activities are excluded from the sample. Financial performance and CEO compensation are winsorized at the 1% and 99% tails. Appendix 5 defines the variables.

CEO Compensation

24

As expected, board size and CEO compensation have a positive association. This result is in line with the findings of previous research showing that smaller boards may be more successful in reducing agency costs (Randøy & Nielsen, 2002). In addition, previous research documents that larger boards often experience coordination problems which may reduce the effectiveness of board monitoring, resulting in higher CEO compensation (Lin, Kuo, & Wang, 2013). This is consistent with managerial power theory.

Larger companies are often more complex and difficult to manage and thus require a larger board and higher competence of management skills, which may explain the high correlation (0.51) between board size and company size.⁶ As predicted, we find a positive relationship between company size and CEO

compensation. In line with previous studies, we find company size to be the most important determinant of CEO compensation (Tosi et al., 2000). Managerial power theory claims that risk averse managers prefer to link compensation to company size since it is a good indicator of the amount of responsibility the position holds.⁷

In model (1), we find company size to have the largest effect on CEO

compensation. When excluding company size in model (2), the significance level of board size improves from 10% to 1% and the coefficient almost doubles from 0.031 to 0.059. Larger boards often have a greater amount of coordination problems than smaller boards which may give the CEO more negotiating power.

Hence, the managerial power theory is a possible explanation of the positive relationship between board size and CEO compensation.

The regression results show that company age is positively associated with CEO compensation. As shown in section 6.2.3, company age is significantly correlated with both company size (0.42) and board size (0.31), suggesting that company size increases over time and thus the CEO compensation rises accordingly.

6 Table 3 in section 6.2.3.

7 This paragraph only accounts for model (1), as model (2) does not include company size.

25

CEO tenure is positively related to CEO compensation, suggesting that the longer a CEO has been in the position, the more influence he has on the board of

directors (Hill & Phan, 1991). In line with human capital theory, longer tenure gives the CEO more work-related experience and competence, and should therefore be rewarded with higher CEO compensation. In addition, managerial power theory argues that longer tenure gives the CEO more bargaining power which may increase the CEO compensation.

As predicted, CEO ownership is negatively related to CEO compensation. This could indicate that the CEO is rewarded with shares in the company when the CEO compensation is lower. Jensen and Meckling (1976) supports this argument and claim that CEO ownership may lead to a reduction in agency costs and better alignment of interests between executives and owners.

CEO age is not statistically significant for any of the models. We are therefore not able to evaluate the relationship between CEO age and CEO compensation. In addition, CEO gender is only significant at the 10% level when using Blau’s Index and D_Div as measures of gender diversity. This indicates that female CEOs receive lower CEO compensation than male CEOs.

7.3. Gender Diversity and CEO Compensation in Different Time Periods