Willy Sri Yuliandhari, Rizta Enggar Novitasari Telkom University, Bandung
[email protected], [email protected]
Abstract
Every company has the ultimate goal to be achieved, namely obtaining maximum profit or profitability. ROA is one ratio for measuring profitability. Where ROA is defined as the ratio used to measure how much net income will be generated from each rupiah of funds embedded in total assets. This study aims to examine the effect of managerial ownership, institutional ownership and the size of the independent board of commissioners on ROA in the consumer goods manufacturing companies listed on the IDX. The sampling method uses a purposive sampling method with a total sample of 8 companies and a study period of 5 years to obtain a total sample of 40 data units.
Data analysis techniques used descriptive statistics and hypothesis testing using panel data regression analysis using the Eviews 9 software application. The test results obtained from this study simultaneously showed mana- gerial ownership, institutional ownership and the independent board of commissioners had a significant effect on ROA. Partially shows managerial ownership, institutional ownership and the independent board of commissioners do not have a significant influence on ROA.
Keywords : Return on Assets; Managerial ownership; Institutional Ownership; Independent Board of Commis- sioners.
1. INTRODUCTION
Profitability is the basic thing that is seen by investors in valuing a company. Companies with high profitability, stable and tend to increase will certainly be liked by investors. The profitability of a company can be measured using ROA, where ROA is a ratio that shows how much the contribution of assets in creating net profit. In other words, this ratio is used to measure how much net income will be generated from each rupiah of funds embedded in total assets (Hery, 2015: 228).
According to data from the author if the annual report of the company that is sampled in this study, shows that ROA of consumer goods sector companies listed on the Indonesia Stock Exchange in 2014-2018 tended to decline. This decline is due to continued decline in product prices from the consumer goods sector. Besides being caused by a fall in product prices, the level of ROA of the company can also be influenced by how much share ownership of managerial and institutions as well as the proportion of independent commissioners.
According Alfinur (2016), defines that managerial ownership is the percentage of share ownership of the company by the directors, management, commissioners as well as every party directly involved in making decisions in the company. So in this case the management as the manager of the company is also the owner of the company or the company’s shareholders.
According Alfinur (2016), Institutional Ownership is ownership of shares owned by parties in the form of institutions such as insurance companies, investment and pension companies, and other institutions can reduce the influence of other interests in the company such as personal interests of managers and debtholders.
The board of commissioners can consist of Commissioners who are not from affiliated parties known as Independent Commissioners and affiliated Commissioners. Affiliated means parties that have business and family relations with the controlling shareholder, members of the board of directors and other board of commissioners.
The purpose of this study was to measure the value of managerial ownership, institutional ownership and the
size of the independent board of commissioners in the consumer goods sector manufacturing companies listed on the Indonesia Stock Exchange in 2014-2018. This study explains how to measure the effect of managerial ownership, institutional ownership, and independent board of commissioners on Return on Assets.
2. LITERATURE REVIEW 2.1 RETURN ON ASSETS
According to Hery (2015) the return on assets is a ratio that shows how much the contribution of assets in creating net income. In other words, this ratio is used to measure how much net income will be generated from each rupiah of funds embedded in total assets. This ratio is calculated by dividing net income from total assets.
2.2 MANAGERIAL OWNERSHIP
Managerial ownership is a number of shares owned by the internal company. Managerial ownership includes shareholders who have a position in the company as creditors or as a board of commissioners, or it can also be said that managerial ownership is shares owned by managers and directors of the company. This ownership will align the interests of management and shareholders, because with the amount of shares owned, management is expected to act more carefully in making decisions (Susanti and Riharjo, 2013).
According Alfinur (2016), defines that managerial ownership is the percentage of share ownership of the company by the directors, management, commissioners as well as every party directly involved in making decisions in the company. So in this case the management as the manager of the company is also the owner of the company or the company’s shareholders.
The formula used to calculate the percentage of managerial ownership based on Putrianis (2016) research is as follows:
2.3 INSTITUSIONAL OWNERSHIP
According Alfinur (2016), Institutional Ownership is ownership of shares owned by parties in the form of institutions such as insurance companies, investment and pension companies, and other institutions can reduce the influence of other interests in the company such as personal interests of managers and debtholders.
2.4 INDEPENDENT COMMISSIONER
The board of commissioners can consist of Commissioners who are not from affiliated parties known as Independent Commissioners and affiliated Commissioners. According to the Financial Services Authority Regulation (POJK) Number 33 Article 20 of 2014, states that the number of Independent Commissioners must be at least 30% of the total members of the Board of Commissioners. The composition of the independent board of commissioners is calculated using the following formula:
2.5 HYPOTHESIS DEVELOPMENT
Mangerial ownership Institusional Ownership Independent Commissioner
ROA
+
+ +
Figure 1. Framework for Thinking Information :
3. RESEARCH RESULT AND DISCUSSION 3.1 DESCRIPTIVE STATISTICS
Table 1. Descriptive Statistics
ROA KM KI DKI
mean 0,12897 0,10545 0,37732 0,38021
median 0,07284 0,00673 0,36130 0,33333
maximum 0,64094 0,68275 0,75020 0,50000
minimum -0,05897 0,00016 0,15461 0,33333 st. Dev 0,17465 0,18100 0,15155 0,07135
3.2 DATA PANEL REGRESSION ANALYSIS a. Chow Test
Table 2. Significance Test of Fixed Effect
Redundant Fixed Effects Tests Equation: Untitled
Test cross-section fixed effects
Effects Test Statistic d.f. Prob.
Cross-section F 14.203858 (9,27) 0.0000 Cross-section Chi-square 69.860854 9 0.0000
Chow test results in the table above shows, the value of prob (Cross-section Chi-square) of 0.0000 <0.05 (significance level = 5%). Based on these data, it can be concluded that the panel data regression model used is the fixed effect model which is better than the common effect model.
b. Hausman Test
Table 3. Significance Test of Random Effect
Correlated Random Effects - Hausman Test Equation: Untitled
Test cross-section random effects
Test Summary Chi-Sq. Statistic Chi-Sq. d.f. Prob.
Cross-section random 0.608302 3 0.8945
Hausman test results in the table above show, the value of prob (cross-section random) of 0.8945> 0.05 (significance level = 5%). Based on these results, according to the provisions of the decision that H1 was rejected, so the model used is a random effect model.
c. Lagrange Multiplier Test
Table 4. Lagrenge Multiplier Test Results
Lagrange Multiplier Tests for Random Effects Null hypotheses: No effects
Alternative hypotheses: Two-sided (Breusch-Pagan) and one-sided (all others) alternatives
Test Hypothesis
Cross-section Time Both
Breusch-Pagan 33.24538 1.683748 34.92912 (0.0000) (0.1944) (0.0000)
Honda 5.765880 -1.297593 3.159556
(0.0000) -- (0.0008)
Langrange Multiplier test results in the table above shows, the value of prob (Cross-section Breusch-Pagan) of 0.0000 <0.05 (significance level = 5%). Based on these results, it is according to the decision making provisions that H1 is accepted, so the model used is the random effect model.
Based on the results of tests conducted by researchers using eviews 10. The results obtained through the Chow test, Hausman test and Lagerage Multiplier test get a panel data regression model in the form of Random Effect Model with the following equation:
Table 5. Random Effect Model
Dependent Variable: Y
Method: Panel EGLS (Cross-section random effects) Date: 08/27/19 Time: 22:22
Sample: 2014 2017 Periods included: 4 Cross-sections included: 10
Total panel (balanced) observations: 40
Swamy and Arora estimator of component variances
Variable Coefficient Std. Error t-Statistic Prob.
X1 -0.075493 0.112390 -0.671710 0.5061
X2 -0.112603 0.165865 -0.678881 0.5016
X3 -0.016996 0.419767 -0.040488 0.9679
C 0.185880 0.203301 0.914310 0.3666
Effects Specification
S.D. Rho
Cross-section random 0.190710 0.8310
Idiosyncratic random 0.086016 0.1690
Weighted Statistics
R-squared 0.022016 Mean dependent var 0.028372 Adjusted R-squared -0.059483 S.D. dependent var 0.080743 S.E. of regression 0.083109 Sum squared resid 0.248659 F-statistic 0.270139 Durbin-Watson stat 1.426708 Prob(F-statistic) 0.846496
ROA = 0,185880 – 0,075493 (KM) – 0,112603 (KI) – 0,016996 (DKI) + e