Politically connected independent board and firm performance

Abstract

This research examines the relationship between politically connected independent commissioners and independent directors on firm performance. The sample are all listed companies on the Indonesia Stock Exchange (IDX) from 2010–2017. In this study, we employ the ordinary least squares (OLS) regression model and Heckman’s 2SLS test to handle the problem of endogeneity. We document that politically connected independent commissioners did not affect the firm performance. On the contrary, politically connected independent commissioners had a negative relationship to firm performance; this was due to the appointment of independent commissioners and independent directors not based on expertise and knowledge in the financial and managerial company field, based solely on previous work experience. Moreover, our result is robust to the Heckman 2SLS test. Therefore, the result is expected to give insight for public firms and policy regulators, to avoid misunderstandings in decision-making at company owners and management levels.

Keywords:

• Political connections
• firm performance
• independent board
• independent commissioners
• independent directors

JEL Classification:

• M40
• M41
• M48

Public interest statement

This article analyzes the relationship between independent commissioners and independent directors with political connections that affect the financial performance of public companies in Indonesia. This research is very important because little literature discusses the effectiveness of the positions of independent commissioners and directors who have political links in generating good financial performance. The study results found that politically connected independent commissioners had no relationship with company performance. In contrast, politically connected independent directors are negatively correlated with firm performance. These results provide input to the owners and managers of the company so that in appointing independent commissioners and independent directors, not only look at the work experience and political power owned by independent commissioners and independent directors but also need to consider expertise and knowledge, especially in the field of management and company finance for the company’s sustainability. Furthermore, this study could give insight into the issue of political connection in a firm’s top management, since the political connection is quite common in Indonesia.

1. Introduction

Several previous studies have demonstrated the role of political connections in a business venture. Han et al. (2018) explained that the effect of political connections owned by firms could affect the firm’s value, improve the firm’s performance, and increase the investor’s trust to invest in politically connected firms (Maaloul et al., 2018).

Firm performance describes the firm manager’s achievements in managing the firm’s operational activities by utilizing the firm’s resources (Klapper & Love, 2004). Various factors can influence firm performance, one of which is political connections (Ang et al., 2013; Faccio, 2006; Fan et al., 2014; Fisman, 2001; Wati, 2017).

Politically connected firms tend to generate significant profits and high productivity levels because politics is the most important economic element in firm profitability (Agrawal & Konoeber, 2001). If the firm has political connections, it can satisfy shareholders and, hence, it influences its stock market level (Faccio, 2006). Political connections positively impact firms in countries with high levels of bureaucratic corruption, weak copyright protection, and undemocratic government systems (Faccio, 2006).

A firm is said to have political connections if at least one of the major shareholders (people who have approximately 10% of the total voting rights) or one of the leaders (President, Vice President, CEO, Chairman, or secretary) is a minister, a member of parliament, or a person who is correlating with a politician or political party (Faccio, 2006). This confirms that the directors or commissioners within a firm can be recruited from outside the firm with a record of having political connections. Politically connected boards of directors still contribute to the firm despite being independent directors (Ang et al., 2013).

Looking at the perspective of politically connected independent commissioners and independent directors, this research is conducted because several studies that examined politically connected independent directors have been carried out in several developed countries (such as Korea and China) and described that independent directors who have experience in politics could reduce fraud by firms (Kong et al., 2019). On the other hand, it also reveals that independent directors who have political connections are valuable to minority shareholders even though their interests are often taken over by controlling shareholders (Hu et al., 2020). According to Lei (2018), if a firm loses an independent director who comes from a government official, the value of the company’s shares will decrease by 3.61% in ten trading days. This condition means that investors will react negatively if the firm loses political connections.

However, these studies have not provided overall evidence and benefits of politically connected independent directors. For this reason, this research is fundamental because there is scant research that discussed politically connected independent commissioners and directors on firm outputs (cost of debt, earnings quality, company performance, and research and development), and the object is more specifically in Indonesia.

Indonesia adheres to a two-tier board system consisting of commissioners and the board of directors. The Indonesian Stock Exchange regulates corporate governance so that at least some board members of commissioners and directors come from independent parties. The definition of independent, according to The Financial Services Authority’s Regulation No. 33/POJK.04/2014, is a board member who comes from outside the firm, has no affiliation with the major shareholders, has no relationship with the board of commissioners and directors, has no relationship with the board of commissioners or board of directors in other firms and is not an inside party of the institution or capital market supporting institutions. In Indonesia, political connections have become expected by placing people close to the government in the firm’s organizational structure, both as commissioners and directors. The fulfillment of some commissioners with political connections to the government has been carried out since the regime of President Susilo Bambang Yudhoyono to the era of President Joko Widodo by appointing state-owned commissioners from political parties or volunteers to occupy positions as commissioners.

Political connections often occur in developing countries and areas where there is weak property rights protection, including in Indonesia (Fisman, 2001). Firms are categorized as having political connections if at least one of the main shareholders or one of the firm’s leaders is a minister, a member of parliament, and has a relationship with politicians or political parties (Faccio, 2006). Firms whose directors are politically connected to the government have a positive and more stable impact on the firm performance than firms whose family members have political connections (Wong & Hooy, 2018).

If one of the firm managers (commissioners or directors) is appointed to the cabinet of ministers or becomes a member of the people’s representative council, then the value of the firm’s shares will increase significantly (Faccio, 2006). However, Kang and Zhang (2018) explained that directors from the government tend to have problems attending board of directors meetings rather than directors from non-government.

Based on the previous explanation, the research question is whether politically connected independent commissioners and independent directors have a relationship with the firm performance. This research contributes to public firms and regulators of policies in managing a firm. It is hoped that there will be no misunderstanding in decision-making at both the firm owner level and the firm management level. This research is divided into five parts. The first part contains the background of the study. The second part is about literature review and hypothesis development. The third part discusses research methods. Results and discussion are in the fourth section, and finally conclusions are presented in the fifth part.

2. Literature Review and Hypotheses Development

The agency theory explains that managers must be responsible for the tasks mandated by the firm owner to improve the firm performance. However, in carrying out firm management activities, one cannot avoid various obstacles or problems that occur both from within and outside the firm, which, in turn, cause problems between firm owners (principals) and managers (agents; Jensen & Meckling, 1976). This theoretical explanation expects good corporate governance because good and strong corporate governance can minimize conflicts between firm owners and managers. Moreover, it also has impact on increasing the firm performance (Dwaikat et al., 2021; Gallego-Álvarez et al., 2010).

Firm performance describes the firm’s state in a whole period, which explains the success and achievements that the firm has achieved through operational activities carried out by utilizing its resources. Firm performance is a measure to see how far the achievements made by the firm are in good condition at a certain time (Margaretha & Afriyanti, 2016). On the other hand, firm performance is a picture of the firm’s achievements to gain the trust of outsiders (Memon et al., 2012).

Firm performance results from works done by managers, both individually and in groups, in carrying out their respective duties to achieve the firm’s goals legally and following the applicable regulations (Iswati, 2007). The firm’s performance will run well and provide positive values if sustainable firm performance also provides positive growth (Rahman et al., 2013).

One of the factors that can affect a firm is the firm’s political connections (Ang et al., 2013; Faccio, 2006; Fan et al., 2014; Fisman, 2001; Wati, 2017). Political connections can have an impact on both sides of the firm and can increase or decrease its performance. Firms connected to politics often get privileges such as getting a loan from the bank to finance the firms’ projects even though the project does not provide a profit (Pranoto & Widagdo, 2016; Zhang et al., 2012). If politically related directors are removed, the firm value will decrease by 3.61% (Lei, 2018). The stability of politically connected firms positively affects the firm’s performance compared to not politically connected firms (Wong & Hooy, 2018). Political connections can also be see from visits by government officials to firms; research by Wang et al. (2018) provides evidence that having government officials visit firms can improve the firm performance, improve governance systems and reduce information asymmetry.

However, other studies show a contradiction to the previous research and provide evidence that firms with politically connected CEOs have a lower performance of about 37% than firms that do not have political connections when measured on the firm’s stock returns after three years since the IPO (Fan et al., 2014). The investment efficiency of state-owned companies in China will decrease if the firm has an executive board from the government (Chen et al., 2011). The political connections built by the firm can have a bad effect on the firm performance compared to firms that are not politically connected (Saeed et al., 2016). With the inconsistency of the research results above, a more in-depth study is needed on political connections within the company.

Political connections occur in developed countries and developing countries such as Indonesia (Fisman, 2001). Indonesia adheres to a two-tier system of corporate governance, where the two boards consist of a board of commissioners and a board of directors. In each board, there is an independent commissioner and an independent director. The Financial Services Authority regulates the meaning of independent in regulation no. 33/POJK.04/2014 as a board member from outside the firm, has no affiliation with the major shareholders, has no relationship with the board of commissioners and directors, and has no relationship with the board of commissioners or the board of directors in other firms.

This research examines the existence of politically connected independent commissioners and independent directors. Independent commissioners and independent directors who are considered agents by the principal must undoubtedly contribute more to improving the firm’s performance because they are parties from outside the firm who do not have a relationship, either directly or indirectly, with the firm owner or the firm management (Utomo et al., 2018) The independent commissioner is tasked with the audit committee to monitor the performance of the director and, at the same time, as a representative of the firm’s minority shareholders, while the independent director is in charge of monitoring the work of the executive board as well as minimizing conflicts of interest between managers and firm owners (Tanjung, 2020).

Independent commissioners are one of the applications of good governance practices in public firms and are often associated with firm performance (Gati et al., 2020). Nawawi et al. (2020) reveal that independent commissioners can positively and significantly influence the firm’s stock performance. Firms that have a large proportion of independent commissioners can produce high performance (Abidin et al., 2009). However, on the other hand, the presence of independent commissioners in the firm does not affect the firm performance (Basyith et al., 2015; Chi et al., 2017; Wati, 2017). Thus, the hypothesis proposed in this research is as follows..

Hypothesis 1: Politically connected independent commissioners positively affect the firm’s performance.

The existence of an independent director in the firm can provide a positive or negative direction in the firm performance (Samara & Berbegal-Mirabent, 2018). Mishra (2020) and Wei and Muratova (2020) provide evidence that the proportion of independent directors has a negative impact on firm performance. Firms whose directors have political connections with the government provide a positive and more stable relationship with the firm performance than firms whose entrepreneurs or family members have political connections (Wong & Hooy, 2018). The firm value will be negative if the firm loses independent directors who have political connections (Yanyu et al., 2020). Based on the previous studies, the second hypothesis in this research is:

Hypothesis 2: Politically connected independent directors have a negative relationship with firm performance.

3. Methods of Research

3.1. Sample and Data Sources

The samples in this study are all listed companies on the Indonesia Stock Exchange (IDX) from 2010–2017, with a total observational data of 2,821 companies. The research data sources were taken from the company’s annual report and the ORBIS database. This research used univariate and multivariate analysis techniques with an ordinary least squares (OLS) regression model. The software used in this research is Stata version 16.0. This research used the Heckman two-stage least squares (2SLS) test to overcome selection bias and endogeneity. In the Heckman 2SLS model, there are two stages. The first stage is to determine the instrumental variables by following the research of Harymawan and Nowland (2016), in which the instrumental variables are formed from the presentation of politically connected firms based on the standard industrial classification (SIC). This value will look for the percentage of independent commissioners and independent directors of politically connected companies based on SIC from 2010–2017. The instrumental variables are named: PROBCON_KI and PROBCON_DI. The second stage of the Heckman 2SLS test re-tests H1 and H2 by entering the Inverse Mills Ratio (IMR) value as an independent variable. IMR is the result of regression in the first stage of the Heckman 2SLS test and is an additional variable used to explain the presence or absence of potential self-selection bias. If the IMR coefficient value is not significant statistically, it indicates no self-selection bias (Habib & Muhammadi, 2018; Harymawan, 2018). The IMRs are named: MIILS_BOCI and MIILS_BODI.

3.2. Variable Identification

The independent variables of this research are politically connected independent commissioners and independent directors. In this research, the criteria for independent commissioners and independent directors who have political connections are (1) former government agency officials; (2) former judges or prosecutors; (3) former members of the legislative council; (4) Ex-military or police; (5) members of political parties (Shin et al., 2018). In this research, politically connected independent commissioners and directors are measured using a dummy variable, where the value is 1 if the independent commissioner and independent director of the firm are politically connected and 0 otherwise.

The dependent variable of this research is firm performance, which is the firm’s management achievement in managing the firm’s operational activities by using the firm’s resources. In this research, the firm performance was measured using Return on Assets (ROA), which will show the quality of the accounting and the earnings generated to increase the investor’s trust more (Bhagat & Bolton, 2008; Cordeiro et al., 2013; Peng et al., 2015). To facilitate understanding in reading the results of this research, the authors present a table for the naming of research variables.

4. Results and Discussions

4.1. Distribution of Variables

This section will present the distribution of the value of politically connected independent commissioners and independent directors from 2010–2017 in the table below.

From Table 2 above, it can be see that during 2010–2017, 1,481 independent commissioners were politically connected and 1,340 independent commissioners who were not politically connected, with the percentage of politically connected independent commissioners 52.50%.

From Table 3 above, it is explain that from the distribution based on the industrial firm group, 1,481 independent commissioners were politically connected and 1,340 independent commissioners who were not politically connected, with the percentage of independent commissioners who were politically connected of 52.50%.

From Table 4 above, it is visible that during 2010–2017, 145 independent directors were politically connected and 2,672 independent directors who were not politically connected, with a percentage of independent directors who were politically connected as large as 5.28%.

From Table 5 above, it can be explain that from the data distribution based on the industrial firm group, 145 independent directors were politically connected and 2,672 independent directors who were not politically connected with the percentage of politically connected independent directors 5.28%.

4.2. Descriptive Statistics

Table 6 shows that the average value of politically connected independent commissioners is 0.525 and politically connected independent directors is 0.053, while the average value of firm performance as seen from ROA is 4.115%, the average value of growth (GROWTH) is 141.179%, the number of commissioners (COMSIZE) is 4.277%, and the average number of boards of directors in a firm (DIRSIZE) is 4.727%. The percentage of independent commissioners in the board of commissioners is 37.031%, and independent directors are 11.286%.

4.3. Pearson Correlation

This section presents the results of the Pearson correlation of politically connected independent commissioners and independent directors on the firm’s performance. Table 7 shows the Pearson correlation of the politically connected independent commissioner variable (PCON_BOCI) and the politically connected independent director variable (PCON_BODI) has a significant positive (negative) effect on the firm performance (ROA) with a significance level at 1%. In contrast, the control variable shows LEVERAGE, LN_TASSET, COMSIZE, DIRSIZE, CI_PERCEN, and DI_PERCEN have a significant effect on ROA, with a significance level at 1%. Meanwhile, the control variable GROWTH has no statistically significant effect on ROA.

p-values in parentheses * p <0.1, ** p <0.05, *** p <0.01

4.4. Independent T-Test

This section presents the results of the independent t-test and PCON_BODI PCON_BOCI variables

Table 8 above explains that, from the firm performance (ROA), there is a significant difference between the average ROA value of independent commissioners who are politically connected and independent commissioners who are not. This result is evidenced by the ROA coefficient value of −1.438 (t = —3.018), with a significance at the level of 1%.

Table 9 explains that the average value of ROA between independent directors who are politically connected and independent directors who are not is different. The average ROA of politically connected independent directors is lower than non-politically connected independent directors (Non_PCON_BOCI). This is evidenced by the coefficient value of 4.008 (t = 3.771) with a significance at the level of 1%.

4.5. OLS Regression Results

In this section, the OLS regression results will be explained as evidence of the hypothesis presented in this research.

Based on Table 10 above, it is explained that the relationship between politically connected independent commissioners and the firm performance is statistically insignificant (model 1). In contrast, politically connected independent directors have a significant negative effect on the firm performance with a coefficient value of −3.62 and a 1%significance level (model 2). This explains that the presence of politically connected independent directors gives a more significant effect than the presence of politically connected independent commissioners on public firms.

The insignificant results of independent commissioners who are politically connected in this research are in line with research by Basyith et al. (2015). The presence of independent commissioners cannot have a strong influence on the firm performance because the appointment of independent commissioners is not based on expertise, especially in the financial sector. It is only based on their previous job experience. Other studies also provide evidence that firms whose boards of commissioners come from central government officials and legislators have low accounting and stock performance (Chi et al., 2017). Similar results are also explained in Wati’s (2017) research that independent commissioners who come from conglomerates and politically connected groups don’t significantly impact the market accounting performance. This result explains that H1 in this research is rejected.

In contrast, the regression results of politically connected independent directors on the firm performance show that PCON_BODI has a negative and significant relationship at the 1% level on ROA. This result is in line with research by Cao et al. (2017), Reguera-Alvarado and Bravo (2017), and Mishra (2020), who examined the relationship between the characteristics of independent directors and the firm performance of which the results show that, in absolute terms, independent directors gave a significant negative effect on the firm performance. These results are also consistent with Ha et al. (2020), who suggested that the value of a firm will decrease if politics is integrated with the firm compared to firms that are not integrating with politics. This can mean that, when there are politically connected independent directors within a firm, the firm performance will experience a significant decline. The negative results on firm performance in this research were due to the lack of knowledge of independent directors in managing the firm, as the findings by Firth et al. (2007) explained that firm performance would decline due to politically connected independent directors who lacked experience and knowledge in the managerial field of the firm. The average number of directors in the firm is 5.2 directors with one independent director who is politically connected. Although the number of politically connected independent directors is small, it can provide better value for private companies than state-owned companies (Yanyu et al., 2020). Based on this explanation, H2 in this research is accepted.

Table 10 also shows the results of the control variables that leverage in the three models has a negative and significant relationship at the 1% level on firm performance. This means that the greater the firm’s debt ratio is it will have a greater impact on the firm’s performance decline. Firms that always increase the value of debt can decrease their value (Ang et al., 2013; Chi et al., 2017). We also find that size of the board of commissioners and the size of the director have a positive relationship with the firm performance, and this relationship is significant at the 1% level. These results indicate that the more members of the board of commissioners and the board of directors in the firms will increase the firm performance. However, too few members on the board of directors and the board of commissioners in the firms will cause problems. Bank Indonesia has set a minimum number of three commissioners and directors (Lukas & Basuki, 2015).

Furthermore, in the third model, the regression results are jointly from politically connected independent commissioners and politically connected independent directors. The results found are in line with the statistical results in model 1 and model 2 and show the insignificant effect of politically connected independent commissioners on the firm performance and the significant effect of politically connected independent directors on the firm performance.

4.6. Self-Selection Bias

Research which has variables that contain elements of choosing a policy cannot be separated from endogeneity. In this research, the possibility of endogeneity occurs where unobserved variables correlate with politically connected board and firm performance. To overcome this problem, we used Heckman’s 2SLS model, as in the previous studies from Kim and Zhang (2016) and Harymawan (2018).

In the first stage, we look for corporate factors that are politically connected by using the formula below

(1) $PCON\mathrm{\_}BOCI=\beta 1+\beta 2Contro{l}_{it}+\hspace{0.17em}\beta 3Y_{it}+\hspace{0.17em}Industry+Year\hspace{0.17em}+\epsilon$(1)

(2) $PCON\mathrm{\_}BODI=\beta 1+\beta 2Contro{l}_{it}+\hspace{0.17em}\beta 3Y_{it}+\hspace{0.17em}Industry+Year\hspace{0.17em}+\epsilon$(2)

The formula above means that PCON_BOCI and PCON_BODI are dummy variables, as proxies for the political connections of the independent commissioner and independent director, Controlit is the control variable of this first regression. Yit is the instrument variable, where the instrument variable in this research is see from the factors of the politically connected independent commissioner and the independent director. However, these variables do not affect the firm performance. To determine this, we follow research from Harymawan and Nowland (2016) and Kim and Zhang (2016), where the instrument variable is formed from the presentation of politically connected firms based on the SIC (standard industry classifications), because politically connected companies, both on the board of commissioners and on the board of directors, exist in each industry (Agrawal & Konoeber, 2001; Harymawan & Nowland, 2016). The instrument variables are named: PROBCON_BOCI and PROBCON_BODI. The regression results from the two formulas above can be seen in appendix Table 1 and 2.

Table 1. Variable definition

Variables	Names of Variables	Definitions	Data Sources
Politically connected independent commissioner	PCON_BOCI	Independent commissioners who are politically connected are measured using a dummy variable, and the value is 1 if there is a politically connected independent commissioner within the firm and 0 otherwise	Annual report
Politically connected independent directors	PCON_BODI	Independent directors who are politically connected are measured using a dummy variable, and the value is 1 if there is a politically connected independent director within the firm and 0 otherwise.	Annual report
ROA	ROA	The firm’s ability to generate profit from its asset	OSIRIS
Leverage	LEVERAGE	The firm’s ability to finance its resources obtained through debt	OSIRIS
Firm size	LN_TASSET	the number of assets owned by the firm	OSIRIS
Growth	GROWTH	Percentage of change in sales	OSIRIS
Total commissioners	COMSIZE	Total number of commissioners	Annual report
total membership director	DIRSIZE	Number of the board of directors	Annual report
Percentage of independent commissioners	CI_PERSEN	Percentage of an independent commissioner	Annual report
Percentage of independent directors	DI_PERSEN	Percentage of an independent commissioner	Annual report
Political connections of independent commissioners-based on industries	PROBCON_BOCI	Percentage of politically connected independent commissioners of each industrial firm each year	Annual report
Political connections of independent directors based on industries	PROBCON_BODI	Percentage of politically connected independent directors of each industrial firm each year	Annual report

Table 2. Distribution of politically connected independent commissioners

YEAR	PCON_BOCI		Total	% PCON_BOCI
	Connect	N_Connect
2010	148	132	280	52.86
2011	158	158	316	50.00
2012	174	166	340	51.18
2013	196	179	375	52.27
2014	202	183	385	52.47
2015	202	175	377	53.58
2016	202	171	373	54.16
2017	199	176	375	53.07
Total	1,481	1,340	2,821	52.50

Table 3. Distribution of politically connected independent commissioners by industrial firm group (SIC)

SIC	PCON_BOCI		Total	% PCON_BOCI
	Connect	N_Connect
0	66	36	102	64.71
1	257	127	384	66.93
2	308	382	690	44.64
3	179	289	468	38.25
4	250	139	389	64.27
5	122	139	261	46.74
6	170	112	282	60.28
7	104	107	211	49.29
8	25	9	34	73.53
Total	1,481	1,340	2,821	52.50

Table 4. Distribution of politically connected independent directors (PCON_BODI)

YEAR	PCON_BODI		Total	PCON_BODI
	Connect	N_Connect
2010	9	271	280	3.21
2011	9	307	316	2.85
2012	9	331	340	2.65
2013	15	360	375	4.00
2014	25	360	385	6.49
2015	30	347	377	7.96
2016	28	345	373	7.51
2017	24	351	375	6.40
Total	149	2,672	2,821	5.28

Table 5. Distribution of politically connected independent directors based on industrial firm group (SIC)

SIC	PCON_BODI		Total	% PCON_BODI
	Connect	N_Connect
0	11	91	102	10.78
1	45	339	384	11.72
2	15	675	690	2.17
3	31	437	468	6.62
4	32	357	389	8.23
5	5	256	261	1.92
6	3	279	282	1.06
7	6	205	211	2.84
8	1	33	34	2.94
Total	149	2,672	2.821	5.28

Table 6. Descriptive statistics

	Mean	Median	Standard Deviation	Minimum	Maximum
ROA	4.115	3.290	12.657	−130.820	209.230
PCON_BOCI	0.525	1.000	0.499	0.000	1.000
PCON_BODI	0.053	0.000	0.224	0.000	1.000
LEVERAGE	0.552	0.498	0.689	0.000	20.714
LN_TASSET	21.471	21.481	1.723	15.019	26.413
GROWTH	141.179	8.626	3354.806	−1694.476	138,462.570
COMSIZE	4.277	4.000	1.937	1.000	22.000
DIRSIZE	4.727	4.000	1.938	2.000	16.000
CI_PERCEN	37.031	33.333	15.938	0.000	300.000
DI_PERCEN	11.286	0.000	14.189	0.000	100.000

Table 7. Pearson correlation

From Variable Number [1] to Number [5]
		[1]	[2]	[3]	[4]	[5]
[1]	ROA	1.000
[2]	PCON_BOCI	0.057***	1.000
		(0.003)
[3]	PCON_BODI	−0.071***	0.120***	1.000
		(0.000)	(0.000)
[4]	LEVERAGE	−0.268***	0.013	−0.001	1.000
		(0.000)	(0.474)	(0.970)
[5]	LN_TASSET	0.102***	0.392***	0.052***	−0.076***	1.000
		(0.000)	(0.000)	(0.006)	(0.000)
From Variable Number [6] to Number [10]
[6]	GROWTH	1.000
[7]	COMSIZE	−0.011	1.000
		(0.557)
[8]	DIRSIZE	−0.010	0.478***	1.000
		(0.602)	(0.000)
[9]	CI_PERCEN	−0.000	−0.002	0.020	1.000
		(0.982)	(0.911)	(0.283)
[10]	DI_PERCEN	−0.002	−0.132***	−0.191***	0.134***	1.000
		(0.905)	(0.000)	(0.000)	(0.000)

Table 8. T-Test of independent variables PCON_BOCI

PCON_BOCI
	Mean PCON	Mean Non_PCON	Coef	t-value
ROA	4.798	3.360	−1.438***	−3.018
LEVERAGE	0.561	0.542	−0.019	−0.715
LN_TASSET	22.114	20.760	−1.354***	−22.656
GROWTH	91.536	196.047	104.511	0.826
COMSIZE	4.899	3.589	−1.311***	−19.062
DIRSIZE	5.199	4.205	−0.993***	−14.061
CI_PERCEN	37.939	36.028	−1.911***	−3.186
DI_PERCEN	10.640	12.000	1.360**	2.544

Table 9. T-Test of independent variables PCON_BODI

	PCON_BODI
	Mean PCON	Mean Non_PCON	Coef	t-value
ROA	0.318	4.326	4.008***	3.771
LEVERAGE	0.550	0.552	0.002	0.038
LN_TASSET	21.848	21.450	−0.398***	−2.751
GROWTH	8.854	148.558	139.705	0.495
COMSIZE	4.503	4.264	−0.239	−1.467
DIRSIZE	5.248	4.698	−0.551***	−3.382
CI_PERCEN	40.778	36.822	−3.956***	−2.953
DI_PERCEN	18.904	10.861	−8.043***	−6.788

Table 10. OLS regression results

	(1)	(2)	(3)
	ROA	ROA	ROA
PCON_BOCI	0.335		0.528
	(0.66)		(1.05)
PCON_BODI		−3.626***	−3.740***
		(−3.53)	(−3.62)
LEVERAGE	−4.678***	−4.677***	−4.693***
	(−14.11)	(−14.15)	(−14.19)
LN_TASSET	−0.067	−0.051	−0.093
	(−0.38)	(−0.29)	(−0.52)
GROWTH	0.000	0.000	0.000
	(0.69)	(0.63)	(0.65)
COMSIZE	0.589***	0.601***	0.576***
	(4.14)	(4.30)	(4.06)
DIRSIZE	0.751***	0.794***	0.793***
	(5.05)	(5.34)	(5.33)
CI_PERCEN	−0.021	−0.019	−0.019
	(−1.45)	(−1.30)	(−1.34)
DI_PERCEN	−0.012	−0.005	−0.004
	(−0.67)	(−0.25)	(−0.24)
Industry	Included	Included	Included
Year	Included	Included	Included
_cons	4.697	4.513	5.251
	(1.28)	(1.25)	(1.43)
r2	0.126	0.130	0.130
N	2821	2821	2821

Table 11. Second-Stage regression: Heckman

	(1)	(2)	(3)
	ROA	ROA	ROA
PCON_BOCI	0.267		0.459
	(0.56)		(0.98)
PCON_BODI		−3.664***	−3.760***
		(−3.21)	(−3.30)
LEVERAGE	−4.799***	−4.816***	−4.819***
	(−4.22)	(−4.25)	(−4.24)
LN_TASSET	−0.440	−0.478	−0.484
	(−1.16)	(−1.26)	(−1.28)
GROWTH	0.000	0.000	0.000
	(0.77)	(0.75)	(0.75)
COMSIZE	0.397**	0.381**	0.375**
	(2.16)	(2.06)	(2.03)
DIRSIZE	0.727***	0.767***	0.768***
	(5.24)	(5.53)	(5.54)
CI_PERCEN	−0.025	−0.024	−0.024
	(−1.58)	(−1.50)	(−1.51)
DI_PERCEN	−0.012	−0.004	−0.004
	(−0.54)	(−0.18)	(−0.17)
MILLS_BOCI	−2.605		−2.725
	(−1.30)		(−1.36)
MILLS_BODI		−2.938	0.000
		(−1.46)	(.)
_cons	15.585*	16.901*	16.645*
	(1.70)	(1.84)	(1.82)
Year FE	Yes	Yes	Yes
Industry FE	Yes	Yes	Yes
r2_p
r2_a	0.119	0.123	0.123
N	2821	2821	2821

t statistics in parentheses * p < 0.1, ** p < 0.05, *** p < 0.01

Appendix 1 shows the results of the first-stage regression of formula 1, where we entered PROBCON_BOCI as the instrumental variable. As a result, we found that PROBCON_BOCI, LEVERAGE, LN_TASSET, COMSIZE & CI_PERSEN affected PCON_BOCI, although GROWTH, DIRSIZE, and DI_PERSEN did not. This shows that the political connections built by firms by having politically connected independent commissioners are more than by having politically connected independent commissioners, as well as having large asset and debt values.

Appendix 2 shows the results of the first-stage regression of formula 2, where we entered PROBCON_BODI as the instrumental variable. As a result, we found that PROBCON_BODI, DIRSIZE & DI_PERSEN affect PCON_BODI. This shows that the firm builds its political connections by recruiting independent directors with more than one political connection. Even though it has been regulated in The Financial Services Authority’s regulations, public firms must have at least one director on the independent director board.

Furthermore, we have re-tested H1 and H2 by entering the inverse mills ratio of politically connected independent commissioners and politically connected independent directors, calculated from the previous first-stage regression.

Table 11 shows that the first model tested the first hypothesis, and we found that politically connected independent commissioners have no effect on the firm performance. This is evidenced by the coefficient value of 0.267 and the t statistical value of 0.56, which are not significant at the levels of 1%, 5%, and 10%. The second model is a test of the second hypothesis. The results show that politically connected independent directors influence firm performance. This result is evidenced by the significant coefficient of −3.664 at the level of 1% with a t-value of −3.21.

Meanwhile, the third model results from joint regression of the two independent variables on the firm’s performance. The results are similar to the first model and the second model that politically connected independent commissioners do not influence the firm performance. Furthermore, vice versa, politically connected independent directors significantly impact the firm’s performance. This regression result reinforces the previous regression results, showing that only firms with politically connected independent directors can affect the firm’s performance.

The insignificant inverse mills (MILLS_BOCI and MILLS_BODI) ratios were formed from PROBCON_BOCI and PROBCON_BODI. The insignificant MILLS_BOCI and MILLS_BODI mean that these instrumental variables are appropriate to explain the relationship between politically connected independent commissioners and independent directors and the firm performance.

5. Conclusion

Evidence of the role of political connections in public firms has been widely discussed and it has been explained that the existence of politically connected members of firm management can increase the firm stability, reduce fraud that occurs in the firms, and give value in front of the minority shareholders (Hu et al., 2020; Kong et al., 2019; Wu et al., 2018). This study examines the influence of politically connected independent commissioners and independent directors on the firm performance of listed companies on the Indonesian stock exchange in the 2010–2017 period. This research found that politically connected independent commissioners have no relationship with firm performance (ROA). On the contrary, politically connected independent directors are negatively related to firm performance (ROA). This is because the appointment of independent commissioners and independent directors is not based on expertise and knowledge in the financial and managerial fields of the form but only based on their previous position experience. Our research contributes to firms and policy makers in managing the firm, especially in the appointment of the firm management’s members who have political backgrounds.

We realize that this research has several limitations, thus becoming the basis for further research. First, the educational background of the independent commissioners and independent directors needs to be analyzed further. Even though they have political connections, it is also necessary to have an education, especially in economics, management, and finance, to manage and monitor firms properly. Second, it is necessary to review the criteria for political connections which are influential based on (1) former government agency officials; (2) former judge or prosecutor; (3) former members of the legislative council; (4) ex-military or police; (5) members of political parties.

Acknowledgment

We express gratitude to Ministry of Education, Culture, Research, and Technology of Republic of ‎Indonesia for the grant given to fund this research.‎

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

The author(s) reported there isfunding associated with the work featured in this article from the Ministry of Education, Culture, Research, and Technology of Republic of Indonesia

Notes on contributors

Onong Junus

Onong Junus is a doctoral student in the accounting doctoral program at Universitas Airlangga and a lecturer at the economics faculty of the University of Gorontalo.

Mohammad Nasih

Mohammad Nasih is a professor of accounting at the accounting department, Faculty of Economics and Business, Universitas Airlangga. He holds a doctorate from Airlangga University and a master’s degree from Airlangga University. Research interest: financial accounting

Muslich Anshori

Muslich Anshori is a professor in accounting, at the accounting department of the Faculty of Economics and Business, Universitas Airlangga. He holds a doctorate from Airlangga University and a master’s degree from the Bandung Institute of Technology. Interested research: Accounting, Management, and Islamic Accounting.

Iman Harymawan

Iman Harymawan is a chief of Airlangga Global Engagement and a lecturer of accounting in Universitas Airlangga, Indonesia. He obtained his Ph.D. from The City University of Hong Kong and obtained MBA from National Chen Kung University. Research Interest: political and military connections in business.

Appendix 1.

First-Stage Regression Result: Determinant of Political Connected Commissioner

Table

	(1)
	PCON_BOCI
PCON_BOCI
PROBCON_BOCI	0.029***
	(4.52)
LEVERAGE	0.085*
	(1.92)
LN_TASSET	0.225***
	(10.46)
GROWTH	−0.000
	(−0.83)
COMSIZE	0.187***
	(8.63)
DIRSIZE	0.001
	(0.09)
CI_PERCEN	0.003*
	(1.83)
DI_PERCEN	−0.000
	(−0.08)
_cons	−7.373***
	(−11.87)
Year FE	Yes
Industry FE	Yes
r2_p	0.176
N	2821

t statistics in parentheses * p < 0.1, ** p < 0.05, *** p < 0.01

Appendix 2.

First-Stage Regression Result: Determining FactorDeterminant Of Political Connected Director

Table

	(1)
	PCON_BODI
PCON_BODI
PROBCON_BODI	0.080***
	(5.24)
LEVERAGE	−0.030
	(−0.89)
LN_TASSET	−0.025
	(−0.71)
GROWTH	−0.001
	(−1.49)
COMSIZE	0.008
	(0.37)
DIRSIZE	0.138***
	(5.48)
CI_PERCEN	0.006**
	(2.37)
DI_PERCEN	0.026***
	(7.24)
_cons	−2.660***
	(−3.45)
Year FE	Yes
Industry FE	Yes
r2_p	0.167
N	2821

t statistics in parentheses * p < 0.1, ** p < 0.05, *** p < 0.01