Internationalization, Capital Structure, and Ownership Structure: A Case of Companies in Indonesia
Rendy Mardiansyah1*, Yohana Kusuma Djiram1, Yusuf Arifin Hia1
1 Master of Business Administration, Faculty of Economics and Business, Universitas Gadjah Mada, Yogyakarta, Indonesia
*Corresponding Author: [email protected] Accepted: 15 February 2023 | Published: 1 March 2023
DOI:https://doi.org/10.55057/ijaref.2023.5.1.3
_________________________________________________________________________________________
Abstract: This study aims to examine the influence of concentrated ownership, managerial ownership, and institutional ownership in moderating the influence of internationalization on capital structure. Test the hypothesis using the fixed effect model multiple regression method with the Driscoll-Kraay estimator as a robust standard error. The samples used were manufacturing industry sector companies listed on the Indonesia Stock Exchange in the 2017- 2021 period, so 81 companies were obtained that had passed the purposive sampling criteria in this study. The results showed that internationalization significantly positively affects capital structure. In the moderating variable, concentrated ownership and institutional ownership weakened the positive influence of internationalization on the capital structure. Meanwhile, managerial ownership does not significantly weaken the positive influence of internationalization on capital structure.
Keywords: capital structure, ownership structure, internationalization, moderating, manufacturing.
___________________________________________________________________________
1. Introduction
Indonesia has been actively involved in various international organizations such as the ASEAN Economic Community (AEC) since 2015 (MFA, 2015) ASEAN Free Trade Agreement (AFTA). It is the only ASEAN country to join and be involved in G-20 membership (EBTKE Public Relations, 2020). This encourages local companies to increase business activities internationally through exports and imports to compete in the global economic market. The Central Statistics Agency reported in 2021 that Indonesia's export volume peaked in 2013 and decreased in 2015, increasing again from 2016 to 2019. Furthermore, the report stated that in 2020 export volumes were dominated by the non-oil and gas sector; namely, 84.6% came from the manufacturing industry.
Increasing business activities internationally has resulted in the company's operational costs increasing, so the company needs new sources of funding that can be sourced from internal and external. External sources of income can come from debt and the issuance of new shares (Sjahrial, 2008). The increase in international business activity can indirectly affect the optimal capital structure. The optimal capital structure is when the value of the enterprise can be maximized. Maximum corporate value can be obtained by increasing the company's cash flow or by lowering the weighted average cost of capital (WACC), which depends on the cost of funding sources (Brigham & Ehrhardt, 2019).
Determining the optimal capital structure has remained a debate and mystery to researchers for decades. Some empirical evidence and literature state that companies prefer external funding sources in the form of debt. Increasing international activity theoretically gives hope of favorable prospects for the company; thus, using debt as a funding source will not lower shareholders' value. Sources of debt funding can also reduce the income tax burden from increased income (Shapiro, 2013; Hadianto, 2017; Joliet & Muller, 2013; Mahendra & Asri, 2020). However, other theories and studies reveal that internationally exposed companies have low debt ratios (Lee & Kwok, 1988; Mittoo & Zhang, 2008). One explanation of this phenomenon is that agency and bankruptcy costs are increasing as companies become more focused and exposed internationally.
The different results of the study suggest that other factors affect changes in the optimal structure directly and indirectly. The decision of the capital structure is inseparable from the manager's influence as an agent of the company. Nevertheless, the manager's decision is inseparable from the influence of the controlling shareholder (Moh'd et al., 1998). Therefore, the ownership structure influences managers to determine funding sources to create an optimal capital structure. Thus, this study aims to re-examine the effect of internationalization on the company's capital structure. Second, this study also examines ownership structure as a moderating variable on the influence of internationalization on capital structure. So, it is hoped that this research can provide empirical evidence supporting previous research and a new view of the optimal capital structure of companies in Indonesia.
2. Literature Review and Hypothesis
The modern theory of capital structure by Franco Modigliani and Merton Miller helps explain how companies would tend to a funding source. According to Brigham & Ehrhardt (2019), capital structure is a combination of debt and equity that can change to achieve optimal conditions. The optimal capital structure is based on maximizing the company's value by increasing free cash flow and lowering the cost of capital. According to the tax effect theory MM (1963), companies with high profitability tend to increase their debt to lower the income tax burden so that the operating profit is more excellent without debt. Nevertheless, Myers (1984), in the trade-off theory, states that the use of debt gets to the point when agency costs and bankruptcy costs do not exceed the benefits of the tax shield.
Nevertheless, this is contrary to the results of Donaldson's research (1961). It is stated that companies with high profitability tend to have low debt values. Thus, Myers & Majluf (1984) further with the pecking order theory stated that companies would use the safest and cheapest funding source, namely internal funding sources obtained from income profits.
Another factor affecting the capital structure is the agency conflict between the agent and the principal. It is explained by Jensen (1986) that agency conflicts occur due to differences in interests between agents who prioritize personal interests over shareholder interests to maximize the company's value. These conflicts can be mitigated by designing ownership structures (insider and outside), increasing dividend payments, and using debt as a funding source so that it can indirectly affect the company's capital structure.
Ownership structures are an alternative to using debt in mitigating agency conflicts. The higher percentage of institutional ownership results in investors will act as supervisory agents to ensure the value of their investments remains safe. Thus, institutional ownership can reduce agency problems and costs (Permansari, 2020). Managerial ownership of company shares can
give rise to common interests between agents and principals so that managers will act to meet the interests of shareholders, namely maximizing the company's value (Jensen, 1996). Thus, management's ownership of the company's shares can reduce the potential for agency conflicts to arise and lower agency costs. Concentrated ownership impacts the controlling stake's efforts to monitor and exercise control over agents more effectively. The higher the shareholding, the easier it will be to supervise and control the agent to suit the shareholders' goal, maximizing the company's value. Thus, concentrated ownership is inversely proportional to agency problems and agency costs.
Exporting companies need more working capital than non-exporter companies, so they need a source of funding from debt (Maes et al., 2019). The research results by Nguyen & Almodovar (2018) show a positive relationship between debt and the company's export level. Export activities are a step of geographical diversification of the company. The research results of Joliet & Muller (2013) show that well-diversified companies geographically have low business risk overall, so they have a higher debt ratio. Based on the description of the results of previous studies, the development of this research hypothesis is as follows.
H1: Internationalization has a positive effect on capital structure.
Brailsford et al. (2002) state that managers' decisions are inseparable from shareholder influence and control. So, the ownership structure affects determining the capital structure. The more significant the controlling shareholding, the easier it will be to monitor and control managers, thus reducing the potential for agency conflicts and minimizing agency costs (Jensen, 1996). In line with the research results by Shahar et al. (2016), concentrated ownership in companies has a lower debt ratio, thus lowering the use of debt to mitigate agency conflicts.
Based on the description of the results of previous studies, the development of this research hypothesis is as follows.
H2: Concentrated ownership weakens the positive influence of internationalization on capital structure.
Wahidahwati (2002) shows that companies with managerial ownership tend to have low debt ratios. According to agency theory, managers who own several shareholdings will work harmoniously with investors and other shareholders to maximize the company's value, thus minimizing agency conflict and reducing the use of debt. Based on the description of the results of previous studies, the development of this research hypothesis is as follows.
H3: Managerial ownership weakens the positive influence of internationalization on capital structure.
Putri & Natsir (2006) in Wijayati (2017), one of the monitoring mechanisms from outside parties is to increase supervision through institutional investors. Other company ownership by the institution will increase more effective supervision due to the institution's ability to evaluate the company's performance. Wahidahwati's research (2002) shows that institutional ownership negatively influences capital structures. This is in line with the research of David et al. (2015) and Wijayati (2017), which showed a significant negative influence of institutional ownership on capital structure. Based on the description of the results of previous studies, the development of this research hypothesis is as follows.
H4: Institutional Ownership weakens the positive influence of internationalization on capital structure.
Figure 1: Research Framework
3. Methods
Secondary data is sourced from the company's financial statements, website, Refinitive, and Osiris. Researchers use purposive sampling in determining the samples used. According to the characteristics of the study, researchers use manufacturing industry companies that have been IPO listed on the Indonesia Stock Exchange before 2017 and report total foreign sales during the 2016-2021 research period. Based on the sampling technique, 81 manufacturing industry companies registered on the IDX were obtained during the 5-year research period. The necessary data, such as the number of foreign sales and the total of all sales, total debt, total assets, the most significant percentage of ownership by owners (OC), percentage of ownership by management (OM), and the most significant percentage of ownership by institutions (OI), are obtained from Osiris, Refinitiv, and the company's annual report. Researchers use independent variables, namely the ratio of foreign sales to total sales, as a measure of the level of Internationalization (INT) and the dependent variable, namely the Debt to Asset Ratio (DAR), as a measure of capital structure. The ownership structure is a moderating variable represented by its percentage value. Researchers also used control variables: AGE, SIZE, growth, ROA, and asset tangibility.
Table 1: Research Variables and Description of Measurements
Dependent variables Operational Definition
Capital Structure Debt to asset ratio (DAR) (Total debt / total assets) x 100 Independent variables
Internationalization Foreign sales to total sales (INT) (Foreign sales / total sales) x 100 Moderating variables
Ownership Structure
Concentrated ownership (OC) (Concentrated shares / total shares) x 100 Managerial ownership (OM) (Managerial shares / total shares) x 100 Institutional ownership (OI) (Institutional shares / total shares) x 100
Dummy ownership structure
DUM_OC If the OC value < mean, then = 0
If the OC value > mean, then = 1
DUM_OM If the value of OM > 0, then = 1
If the value of OM = 0 then = 0
DUM_OI If the OI value < mean, then = 0
If the OI value > mean, then = 1 Control variables
Control Company age (age) Year of a deed of an establishment to the year of study
Growth ability (GRWT) [(Total Salest – Total Salest-1) / Total Salest-1] x 100
Profitability (ROA) (Income after tax / total assets) x 100
Company size Ln (total assets)
Tangibility (TANG) (Fix assets / total assets) x 100
4. Results
This study used panel data to determine the effect of internationalization on capital structure.
Classical assumption tests such as normality, multicollinearity, heteroskedasticity, and autocorrelation were also performed to obtain regression models that met the BLUE (Best Linear Unbiased Estimator) criteria (Kuncoro, 2009). Then, to determine the type and test the nature of moderating variables on the influence of independent variables on dependent variables, researchers used the moderated regression analysis (MRA) method (Sharma et al., 1981). The MRA method is carried out in several stages. First, it regresses the INT independent variable against the dependent variable DAR (model 1). Second, perform regression by adding ownership structure moderating variables (OC, OM, and OI) into three separate models (models 2a, 3a, 4a). Third, the three models were regressed by adding the interaction variables of the independent variable INT and the dummy variables of moderating the ownership structure (DUM_OC, DUM_OM, and DUM_OI) so that they became three models (models 2b, 3b, 4b). Fourth, moderating variables can be said to weaken or strengthen the influence of independent variables on dependent variables by looking at the value of the β coefficient and the significance of the interaction variable.
DARi,t=α0+β1INTi,t-1+β2AGEi,t+β3GRWTi,t+β4ROAi,t-1+β5SIZEi,t-1+β6TANGi,t-1+ε (1)
DARi,t=α0+β1INTi,t-1+β2OCi,t-1+β4AGEi,t+β5GRWTi,t+β6ROAi,t-1+β7SIZEi,t-1+β8TANGi,t-1+ε (2a) DARi,t=α0+β1INTi,t-1+β2OCi,t-1+β3INT*DUM_OCi,t-1+β4AGEi,t+β5GRWTi,t+β6ROAi,t-1+β7SIZEi,t-1+β8TANGi,t-1+ε (2b) DARi,t=α0+β1INTi,t-1+β2OMi,t-1+β4AGEi,t+β5GRWTi,t+β6ROAi,t-1+β7SIZEi,t-1+β8TANGi,t-1+ε (3a) DARi,t=α0+β1INTi,t-1+β2OMi,t-1+β3INT*DUM_OMi,t-1+β4AGEi,t+β5GRWTi,t+β6ROAi,t-1+β7SIZEi,t-1+β8TANGi,t-1+ε (3b) DARi,t=α0+β1INTi,t-1+β2OIi,t-1+β4AGEi,t+β5GRWTi,t+β6ROAi,t-1+β7SIZEi,t-1+β8iTANGi,t-1+ε (4a) DARi,t=α0+β1INTi,t-1+β2OIi,t-1+β3INT*DUM_OIi,t-1+β4AGEi,t+β5GRWTi,t+β6ROAi,t-1+β7SIZEi,t-1+β8TANGi,t-1+ε (4b)
Information:
DAR= capital structure GRWT= growth ability
INT= Internationalization SIZE= company size
OC= concentrated ownership ratio TANG= asset tangibility
OM= managerial ownership ratio DUM_OC = dummy OC
OI= institutional ownership ratio DUM_OM = dummy OM
AGE= age of the company DUM_OI= dummy OI =
Table 2: Moderating Variable Type Criteria
Variables Criteria
β2 for equation ii β3 for equation iii
Independent (significant)
β2 ≠ 0
(insignificant) β3 = 0
No Moderating (insignificant) β2 = 0
(insignificant) β3 = 0 Pseudo-Moderating (significant)
β2 ≠ 0
(significant) β3 ≠i0 Pure Moderating (insignificant)
β2 = 0
(significant) β3 ≠ 0 Source: (Sharma et al., 1981)
The descriptive statistical table succinctly shows the sample data in this study. The most considerable debt ratio value was 94.8%, while the highest foreign sales were 99.2%. The most significant percentage of institutional ownership was 99.6%, while the most significant percentage of managerial ownership was 69.3%. The average managerial ownership is 3.2%, which shows that manufacturing companies' managerial ownership percentage in Indonesia is still deficient. This can also be seen from the average dummy value of OM, which shows a value of 37%, which indicates that only 37% of the sample whose managers own a certain number of shares.
Table 3: Descriptive Statistic
Variable N Mean Min Max Std. Dev
Dependent DARt 405 0,269 0,000
(DVLA)
0,948
(ALMI) 0,179
Independent INTt-1 405 0,176 0,000
(AALI)
0,992
(KKGI) 0,211
Moderating
OCt-1 405 0,532 0,102
(KLBF)
0,996
(MASA) 0,229
OMt-1 405 0,032 0,000 0,693
(LMPI) 0,099
OIt-1 405 0,527 0,000
(INCI)
0,996
(MASA) 0,237 Dummy
Moderating
DUM_OCt-1 405 0,425 0 1 0,495
DUM_OMt-1 405 0,370 0 1 0,484
DUM_OIt-1 405 0,467 0 1 0,500
Control
AGEt 405 42,840 5
(DPUM)
104
(GDYR) 16,568
GRWTt 405 0,069 -0,354
(ALMI)
2,527
(PYFA) 0,226
ROAt-1 405 0,038 -0,375
(CPRO)
0,527
(MLBI) 0,091
SIZEt-1 405 27,072 17,716
(ESTI)
32,726
(INDF) 3,763
TANGt-1 405 0,528 0,165
(RICY)
0,952
(JAWA) 0,186
The results of determining the panel data regression model show that all empirical models of selected research use fixed effect models as appropriate panel data regression models. This is based on the Chow and Hausman tests, which show a probability value of < alpha (0.05).
Table 4: Panel Data Regression Model Determination
Types of Testing Conclusion
(1) (2a) (2b) (3a) (3b) (4a) (4b)
Chow 0,0000 0,0000 0,0000 0,0000 0,0000 0,0000 0,0000
Hausman 0,0001 0,0000 0,0000 0,0000 0,0000 0,0001 0,0128
LM - - - - - - -
Conclusion FEM FEM FEM FEM FEM FEM FEM
The results of classical testing assumptions on the sample data of this study show that all empirical models are not distributed using the Shaprio-Wilk test. However, several studies, such as Altman (1995), Pallant (2007), and Wooldridge (2013), states that data abnormalities are not a serious problem with large sample counts (>30 or 40). The results of the multicollinearity test showed that all independent variables were free from the symptoms of multicollinearity, using both partial correlation and variance inflation factor (VIF) values.
According to Hoechle (2007), the problem of autocorrelation and heteroskedasticity can be solved by performing a regression procedure using the Driscoll-Kraay estimator as a robust standard error. This procedure can be performed using the xtscc command in the STATA program. However, the results of autocorrelation and heteroskedasticity tests show that all regression models experience such symptoms. Therefore, researchers used Driscoll-Kraay's robust standard error estimates to test hypotheses.
Table 5: Regression Results with Driscoll-Kraay Standard Errors
Variable DAR
1 2a 2b 3a 3b 4a 4b
INT 0,2294***
(0,008)
0,2322**
(0,007)
0,2382**
(0,007)
0,2305***
(0,008)
0,2361**
(0,015)
0,2290***
(0,008)
0,2396***
(0,006)
OC 0,0551
(0,235)
0,1130 (0,114)
INT*DUM_OC -0,0922*
(0,093)
OM 0,0731**
(0,011)
0,0739**
(0,015)
INT*DUM_OM -0,0158
(0,646)
OI 0,0181
(0,416)
0,0699**
(0,039)
INT*DUM_OI -0,1187***
(0,002)
AGE -0,0148**
(0,027)
-0,0153**
(0,022)
-0,0153**
(0,022)
-0,0150**
(0,025)
-0,0149**
(0,024)
-0,0149**
(0,027)
-0,0147**
(0,027) GRWT 0,1083***
(0,007)
0,1114***
(0,005)
0,1131***
(0,006)
0,1097**
(0,007)
0,1095***
(0,007)
0,1087***
(0,007)
0,1098***
(0,007)
ROA -0,4021***
(0,007)
-0,4111***
(0,009)
-0,4114**
(0,009)
-0,3978***
(0,008)
-0,3973***
(0,007)
-0,4033***
(0,008)
-0,3895***
(0,008) SIZEc 0,1822***
(0,006)
0,1855***
(0,005)
0,1880***
(0,004)
0,1842***
(0,006)
0,1847***
(0,006)
0,1849***
(0,005)
0,1876***
(0,006)
TANGc 0,0949
(0,182)
0,0900 (0,170)
0,0920 (0,139)
0,0985 (0,174)
0,0975 (0,187)
0,0927 (0,185)
0,0963 (0,149) _cons 0,8703***
(0,008)
0,8641**
(0,009)
0,8361**
(0,010)
0,8756***
(0,007)
0,8732**
(0,007)
0,8674***
(0,008)
0,8317***
(0,008)
N 405 405 405 405 405 405 405
Source: processed data
The above data is the coefficient value of each independent variable The probability value is in parentheses
The *, **, *** signs respectively signify significant at 10%, 5% and 1%
Hypothesis testing is performed using t-tests. The test was performed by comparing probability and alpha values (10%, 5%, and 1%). Suppose the probability value of a variable is less than 0.1. In that case, it can be concluded that the variable has a significant effect. Meanwhile, the variable is said to have a positive or negative effect on the dependent variable depending on the value of the beta coefficient of the variable.
Equation (1) shows that the INT variable has a significant positive effect on DAR with a coefficient of 0.2294 and a prob value of 0.008, which is less than the alpha value. Thus, the regression of equation (1) shows that the study's results accept the first hypothesis. This is in line with several previous studies that stated that the higher the level of internationalization, the higher the company's debt ratio (Mahendra & Asri, 2020; Nguyen & Almodóvar, 2018;
Maes et al., 2019). An elevated level of foreign sales indicates an increase in the company's income; thus, to protect against income tax, the company will use debt as a source of funding (tax shield effect). In addition, companies with good prospects to maintain the value of shareholders' investments are more likely to use debt than to issue new shares.
Equation (2a) shows that the OC variable has no significant effect with a prob value of 0.235
> alpha. Meanwhile, equation (2b) shows that the interaction variable DUM_OC*INT has a significant negative effect on DAR with a coefficient value of -0.0922 and a prob value of 0.093 < alpha. These results lead the authors to the conclusion that concentrated ownership is a pure moderator variable. Concentrated ownership can significantly weaken the positive influence of internationalization on capital structure. This is in line with Jensen's agency theory which states that ownership structures are an alternative for companies to overcome agency problems and use debt as a source of funding. The greater the percentage of controlling ownership, the more effective it is in monitoring and controlling agents when making decisions to create maximum company value. Thus, based on the results, the second hypothesis is accepted.
Equation (3a) shows that the OM variable shows a significant favorable influence on the DAR variable, with a prob value of 0.011 < alpha and a coefficient value of 0.0731. Meanwhile, equation (3b) shows that the interaction variable DUM_OM*INT has no significant effect on the DAR variable, with a prob value of 0.0646 > alpha. These results lead the authors to conclude that managerial ownership is not a moderating variable because it cannot significantly weaken or strengthen the DAR-dependent variable. Instead, the study results show that managerial ownership is an independent variable. Brailsford et al. (2002) 's research explains that a low percentage of managerial ownership is positively related to the company's debt ratio.
However, the higher the percentage of managerial ownership, the lower the debt ratio.
Brailsford et al. explained that there is a non-linear relationship between managerial ownership and the company's debt ratio. This study can prove this by looking at the statistical description of managerial ownership variables, which shows an average of only about 3%. This low average percentage of managerial ownership indicates that managerial ownership does not influence mitigating agency conflicts, so the company will increase debt to reduce agency problems' potential emergence. Thus, the results of this study reject the third hypothesis Equation (4a) shows that the OI variable has no significant effect on the DAR variable with a prob value of 0.416 > alpha. Meanwhile, equation (4b) shows that the interaction variable DUM_OI*OI has a significant adverse effect on the DAR variable with a prob value of 0.002
< alpha and a coefficient of -0.1187. These results conclude that the institutional ownership variable is a moderating variable that can significantly weaken the positive influence of Internationalization on the company's capital structure. These findings are supported by
previous research by Wahidahwati (2002), David et al. (2015), and Wijayati (2017), which states that institutional ownership negatively affects the company's debt ratio. The higher the ownership percentage, the lower the company's debt ratio. The existence of the institution as a shareholder of the company encourages the institution to more closely monitor the movements of managers to act following the interests of the principal, namely maximizing the company's value and maintaining the value of the investment. Thus, based on the results of this study, the fourth hypothesis that "institutional ownership weakens the positive influence of internationalization on the capital structure" is accepted.
5. Conclusion
Based on the results of the study, data processing, and discussions that have been previously stated, the researcher focuses on testing ownership structure variables in moderating the influence of internationalization on the capital structure of manufacturing companies listed on the IDX in the 2017-2021 period. The researcher concluded that independent internationalization has a significant positive effect on the company's capital structure. The higher the level of foreign sales, the higher the company's debt ratio.
Then, a moderated regression analysis method is conducted to test the influence of moderating variables. The results suggest that the ownership structure represented by concentrated ownership and institutional ownership can weaken the positive influence of internationalization on the company's capital structure. The higher the concentration of ownership, especially institutional ownership, the smaller the influence of foreign sales levels in increasing the debt ratio. This phenomenon can be explained due to the role of investors in monitoring the actions of managers when making decisions. Meanwhile, the ownership structure represented by managerial ownership cannot weaken or strengthen the influence of internationalization on the capital structure. This may be due to the low percentage of managerial ownership that cannot moderating the model.
This research is expected to support pre-existing theories and empirical evidence and provide a new view of the company's optimal capital structure. As a suggestion for future research, a company's capital structure could be represented by other proxies, such as long-term debt to asset (LTD) or short-term debt to asset (STD), to see a unique perspective. Other proxies, such as foreign assets to total assets, can also represent internationalization variables. Recent research is expected to conduct research with different industrial populations or indices to produce a broader and new picture.
Reference
Central Bureau of Statistics. (2021). Indonesian Oil and Gas and Non-Oil and Gas Export Volume (Net Weight: Thousand Tons), 1990-2019. Bps.Go.Id. https://doi.org/10.1055/s- 2008-1040325
Bernandhi, A. M. R. (2014). The effect of managerial ownership, Institutional ownership, Dividend policy, Leverage, and company size on the company's value. Diponegoro Journal of Accounting, 3(1), 177–191.
Brailsford, T. J., Oliver, B. R., & Pua, S. L. H. (2002). On the relation between ownership structure and capital structure. Accounting and Finance, 42(1), 1–26.
https://doi.org/10.1111/1467-629X.00001
Brigham, E. F., & Ehrhardt, M. C. (2019). Financial management: Theory & practice.
Cengage Learning.
David, A., Nangoy, S., & Saerang, I. (2015). The effect of managerial and institutional ownership on debt policy in non-manufacturing companies in Bei. Scientific Periodical Journal of Efficiency, 15(05), 690–702.
Hadianto, B. (2017). Effect of Asset Structure, Company Size, and Profitability on the Capital Structure of Telecommunications Sector Issuers for the 2000-2006 Period. Maranatha Journal of Management, 7(2), 14–29.
Hostile, D. (2007). Robust Standard Errors for Panel Regressions with Cross-Sectional Dependence. The Stata Journal: Promoting Communications on Statistics and Stata, 7(3), 281–312. https://doi.org/10.1177/1536867X0700700301
EBTKE Public Relations. (2020). Directorate General of EBTKE - Ministry of Energy and
Mineral Resources. In Press Releases (pp. 1–4).
https://ebtke.esdm.go.id/post/2020/06/18/2560/jadi.satu-
satunya.negara.asean.di.g20.indonesia.komitmen.wujudkan.pembangunan.ekonomi.ber k elanjutan
Jensen, M. C. (1996). Agency costs of free cash flow, corporate finance, and takeovers. In Corporate Bankruptcy (Vol. 76, Issue 2, pp. 11–16). Cambridge University Press.
https://doi.org/10.1017/CBO9780511609435.005
Joliet, R., & Muller, A. (2013). Capital structure effects of international expansion. Journal of Multinational Financial Management, 23(5), 375–393.
https://doi.org/10.1016/j.mulfin.2013.08.002
MFA. (2015). ASEAN Economic Community AEC. In Kemenlu.co.id.
https://kemlu.go.id/portal/id/read/113/halaman_list_lainnya/masyarakat-ekonomi- asean- mea
Kuncoro, M. (2009). Research methods for business & economics, third edition. In PT.
Primary Script Gelora.
Maes, E., Dewaelheyns, N., Fuss, C., & Van Hulle, C. (2019). The impact of exporting on financial debt choices of SMEs. Journal of Business Research, 102, 56–73.
https://doi.org/10.1016/J.JBUSRES.2019.05.008
Mahendra, C., & Asri, M. (2020). THE INFLUENCE OF THE LEVEL OF INTERNATIONALIZATION ON THE CAPITAL STRUCTURE. Gadjah Mada
University.
Moh'd, M. A., Perry, L. G., & Rimbey, J. N. (1998). The Impact of Ownership Structure On Corporate Debt Policy: a Time-Series Cross-Sectional Analysis. The Financial Review, 33(3), 85–98. https://doi.org/10.1111/j.1540-6288.1998.tb01384.x
Shapiro, A. C. (2013). Multinational Financial Management. In John Wiley & Sons.
Sharma, S., Durand, R. M., & Gur-Arie, O. (1981). Identification and Analysis of Moderator Variables. Journal of Marketing Research, 18(3), 291. https://doi.org/10.2307/3150970 Sjahrial, D. (2008). Financial management. Media Discourse Partners.
Wahidahwati. (2002). The Effect of Managerial Ownership and Institutional Ownership on Corporate Debt Policy: An Agency Theory Perspective. The Indonesian Journal of Accounting Research, 5(1). https://doi.org/http://doi.org/10.33312/ijar.67
Wijaya, T. (2020). Advanced linear regression (Issue IX, pp. 1–12).
Wijayati, F. L. (2017). Analysis of the Effect of Managerial Ownership, Institutional Ownership, Board of Directors Size, and Board of Commissioners Size on Agency Costs.
EBBANK Journal, 6(2), 1–16.
Wooldridge, J. M. (2013). Introductory econometrics: A modern approach 5th ed. OH: South- Western Cengage Learning.
