The impact of corporate governance to the economic value added listed company in BEI 2003-2004 ∗
4. Result
(2) Companies have EVA during two year 2003-2004, based on SWA magazine. SWA publicized 100 companies that create EVA.
(3) Companies have the complete data that are needed to the models. The data are retrieved from Jakarta stock exchanges website www.jsx.co.id.
Based on research of Siagian, Siregar, and Rahadian (2006), there are 97 companies that have CG index during two year 2003-2004. From all the companies, only 32 companies which are during two years include in the 100 companies creator EVA The sample size in the model is 32 companies during 2 years, so there are 64 firm years.
First, the research used mean equality test to investigate average value of main variables between different categories. Second, we used Pearson correlation to investigate relation between variables in the models. The correlation can indicate the multicolinearity among independent variables in the models. Third, we used simple regression to test the relation between corporate governance and economic value added. Fourth, we used multiple regression to test the relation between CG and EVA that enter controlled variables in the model. Finally, we conduct the robustness test.
The impact of corporate governance to the economic value added listed company in BEI 2003-2004
33 Table 4 Test of mean of EVA and CGI based on controlled variables
Control variable Groups Average CGI Sig. Average EVA(%) Sig.
Growth High 0.6974 0.3099 4.66 0.3580
Low 0.6788 1.60
Leverage High 0.7219 0.0006* 7.30 0.0214**
Low 0.6614 -0.02
Size High 0.7073 0.0054* 4.69 0.1974
Low 0.6572 0.38
Age High 0.7012 0.0549*** 6.54 0.0067*
Low 0.6661 -2.32
Notes: * significant 0.01; ** significant 0.05; *** significant 0.10.
Table 4 shows test of different mean of two groups of companies. Grouping is based on upper or lower of means control variables. We calculate average CGI and EVA for each group. This result shows that high leverage, size and age have high average EVA and CGI.
Some differences are statistically significant. Different CGI and EVA for grouping firm by sales growth is not statistically significant.
Pearson correlation matrix at Table 5, shows that CGI have significant correlation with EVA. All the control variables except sales growth have significant correlation with CGI. Only size and age have significant correlation with EVA. All the relationship is positive except the relation between CGI and growth. Leverage had positive relation with EVA and CGI. This result is not in line with finding Salmi and Virtanen (2001) that found positive correlation between leverage and EVA. This result is in line with investor pressure story. Companies that have high leverage will get tighter monitored from creditor.
Relation between size, age, EVA and CGI are positive and significant. This result is inline with the finding of Black, Jang and Kim (2005). The research found any anomaly. The relation between CGI and sales growth are negative but not significant, but the relation between EVA and sales growth was not significant.
Table 5 Correlation pearson matrix of all variables
EVA CGI GROWTH LEVERAGE SIZE AGE
EVA 1 0.488* 0.053 0.204 0.331* 0.289**
(0.000) (0.678) (0.105) (0.008) (0.021)
CGI 0.448* 1 -0.137 0.256** 0.522* 0.289**
(0.000) (0.280) (0.041) (0.000) (0.020)
GROWTH 0.053 -0.137 1 0.072 -0.138 -0.227***
(0.678) (0.280) (0.570) (0.277) (0.072)
LEVERAGE 0.204 0.256** 0.072 1 0.256** 0.282**
(0.105) (0.041) (0.570) (0.041) (0.024)
SIZE 0.331* 0.522* -0.138 0.256** 1 0.341*
(0.008) (0.000) (0.277) (0.041) (0.006)
AGE 0.289** 0.289** -0.227*** 0.282** 0.341* 1
(0.021) (0.020) (0.072) (0.024) (0.006)
Notes: * significant 0.01; ** significant 0.05; *** significant 0.10.
Before running the regression, we conducted test of classic assumption to ensure that model regression met the classic assumptions. All the models met the classic assumptions. Table 6 and Table 7 showed the result. In the simple regression model (model 1), R2 is 0.747607. It means that 74.76% variability of EVA can be explained by CGI.
In the simple regression model, EVA and CGI have positive relationship and statistically significant. This result proved first hypothesis that was developed in this research. This result is in line with result of Utama and Afriani (2005) that found positive relation between CGPI and spread EVA. This result also in line with previous research that proved the positive relationship between EVA and CG (Klapper & Love, 2002; Durnev & Kim, 2003;
Black, Jang & Kim, 2005).
Multiple regression result showed the existence of positive relation between all independent variable with EVA as dependent variable. Statistical F test show that index CG, sales growth, leverage, size and the company age together influenced EVA. In the multiple regression model, R2 is 0.9003. The R2 is higher compared to simple regression result because in the multiple regression used more variables.
Table 6 Result of simple regression and multiple regression Hasil Uji Regresi Sederhana
Variabel Koefisien Std. Error t-Statistic Prob.
C -0.5932 0.0206 -28.8065 0.0000
CGI 0.9293 0.0308 30.1541 0.0000
R-squared 0.7476 Mean dependent var 0.0709
Adjusted R-squared 0.7435 S.D. dependent var 0.2353 S.E. of regression 0.1192 Sum squared resid 0.8806
F-statistic 183.6485 Durbin-Watson stat 1.4726
Prob(F-statistic) 0.0000
Hasil Uji Regresi Berganda
Variabel Koefisien Std. Error t-Statistic Prob.
C -0.7093 0.0192 -36.8644 0.0000
CGI 0.7393 0.0270 27.4237 0.0000
GROWTH 0.0587 0.0023 25.9216 0.0000
LEVERAGE 0.0047 0.0009 5.2692 0.0000
SIZE 0.0164 0.0015 10.8679 0.0000
AGE 0.0844 0.0064 13.1093 0.0000
R-squared 0.9003 Mean dependent var 0.0664
Adjusted R-squared 0.8917 S.D. dependent var 0.3391 S.E. of regression 0.1116 Sum squared resid 0.7226
F-statistic 104.7085 Durbin-Watson stat 1.3511
Prob(F-statistic) 0.0000
CGI have positive relation to EVA and the relationship is statistically significant. All control variables have positive relation with EVA and statistically significant. This result different from Utama and Afriani (2005) research that unsuccessful found the relation between indexes of CG with spread in the multiple regression model.
Sales growth have positive relation to EVA the relationship is statistically significant, this result proved the second hypothesis. This finding prove that sales growth will influence company ability in yielding value added to
The impact of corporate governance to the economic value added listed company in BEI 2003-2004
35 stockholder. Company with high growth will adopt good CG practice (Durnev & Kim, 2003), and have ability yield high NOPAT as one of the important component in EVA. This result was consistent with Salmi and Virtanen (2001) finding that profitability and growth of company represent important factor influencing EVA.
Leverage had positive relation to EVA and statistically significant. This result proved the third hypothesis.
This result was inline with investor of pressure story. Creditor have higher level power than stockholder to force management to running the business according to principles of CG so, the target of maximizing value of company can be reached, for example by increasing EVA. This result was in line with Salmi and Virytanen (2001) finding.
They found positive relation between leverage and EVA. Company with good profitability would conduct many investments to maintain its growth level. One of the sources of fund in the investment was external fund. The company also got tighter monitored from its creditor so all company resource really used to maximize value.
Company size had positive relation with EVA and statistically significant. This result proved the fourth hypothesis that was developed in this research. The big company tend to adopt better of CG (Black, Jang & Kim, 2005) compared to small company. The big company had ability to create higher EVA than small companies. Big company had high quality of resources compared to small companies, so value creation of big company would company age have positive relation with EVA and statistically significant. This result proved the fifth hypothesis that was developed in this research. Old companies tend to apply principles CG better and have ability to yield higher EVA. Older company had better experience compared to by a new company so that can run its operating activity more effective and efficient.
4.1 Sensitivity analysis
Based on correlation matrix among variables, component of CGI and EVA have positive correlation. Only the relation between rights of shareholders and EVA was not statistically significant. Disclosure and transparency had strongest correlation among other components.
The result of multiple regressions between CGI component and EVA show varied result. Only equitable treatment of shareholders and disclosure and transparency had significant influence to EVA. Right of shareholders, role of stakeholders, and responsibility of the board did not have a significant influence to EVA (appendix 2.1 and appendix 2.2).
Relation between responsibility of the board with performance EVA of course represents surprising result because many theories during the period exactly express important role of board in creating company performance and value. Teen and Kusnadi (2003) and Syakroza (2003) expressed that board represent important aspect in CG practice. Syakhroza even expressed that CG have to focus at board because board of commissioner and board of directors have full authority in making decision in the company. This result was in line with Nuryanah (2004). She investigated 144 listed companies. She felt to find the relation between board governance with value of company that measured by Tobin’s Q. According to Nuryanah, value of company was more influenced by external factors that can be influenced by board.
The insignificant influence of role of stakeholders to EVA indicates that stakeholders did not have influence in value creating of company. Company in Indonesia still fetched up all standing at management and stockholder.
While other stakeholders for example employees were still overruled. To create maximal EVA, the companies must coordinate all resources in company (Young & O’Byrne, 2001).
Right of shareholders nor have significant relation to EVA. This result oppose against research by Zheka (2006) that found strong influence of shareholder rights to company value in Ukraina. Disclosure and transparency had positive relation to EVA and statistically significant. This result in line with Zheka (2006), and
Berglof and Pajuste (2005) finding that finance performance of company closely related to which how easy the information available at public.
Appendix 3.1 showed Pearson correlation between CGI and other control variable with ROE and ROA. But only CGI, company age had significant correlation to ROA. All variable had positive relation with ROE and statistically significant except sales growth that have negative relation but not significant.
Multiple regression result indicated the existence of positive relationship between CG and control variables to ROA. All variables were statistically significant at level 1% except company size significant at level 5%.
Multiple regression with ROE showed that all variables have positive relationship except sales growth have negative relation to ROE but not significant.
Result of sensitivity analysis found finding positive relation between CG with ROA and ROE as a financial performance measurement. This result was in line with research Miyajima (2005) that found positive relation between CGI and ROA in Japan. This result also as in line with Brown and Caylor (2006) expressing that company that have better corporate governance will have high ROE and ROA also.
Result of sensitivity analysis strengthens the hypothesis expressing that CG have positive correlation with company performance. This result found the relationship CGI with the three performance measurement EVA, ROA and ROE. Based on this coefficient CG more stronger influence ROE compared to EVA and ROA.