SOEs CORPORATE PERFORMANCE ON IDX AND SOME INFLUENCED FACTORS

: State-owned enterprises are government-owned businesses that have been priva-tized and can be close to politicians from political parties. They are also notorious for being poorly managed. The purpose of this research is to examine how political connections, institutional ownership, cash holdings, company size, and leverage affect the performance of state-owned enterprises on the Indonesia Stock Exchange. The data for this study comes from the annual reports of 20 state-owned enterprises (SOEs) listed on the IDX from 2014 to 2018. This research model is a panel regression model that tests the common, fixed-effect, and random effect models. Based on the Chow test and Hausman test, the best model in this study is the random effect model. The results found that political connections, institutional ownership, and cash holding are significant factors affecting the performance of state-owned companies. Another finding was that companies with stronger political connections affect the performance of state-owned companies. On the other hand, this study did not find companies having political connections affect the performance of state-owned companies. This finding is expected to benefit investors to consider SOEs companies to invest.

In many countries, stateowned enterprises (SOEs) are no longer state-owned companies but have become companies owned by the private sector and public. This can be proven from several companies that have been listed in the country's capital market. In principle, whether going to public or not, SOEs all play an essential role in advancing the Indonesian economy. In the context of Indonesia, data from the Ministry of SOEs showed that in the last four years of the previous 2015-2018 period, Indonesian SOEs gained profits that tended to fluctuate in 2015, reaching 150 trillion rupiahs, Rp 176 trillion 2016, Rp 186 trillion 2017 and Rp 188 trillion 2018. The data highlights that the profits of SOE compa-nies experienced a significant frisk (Tri, 2019). On the contrary, SOE companies also experienced a significant increase in debt levels. Data from the Ministry of SOEs reveals that the debt level of stateowned companies has reached 2,140 trillion as of the 3 rd quarter of 2020 (Saputra, 2021). The high level of debt is driven by non-financial SOEs rather than finance SOEs.
On the other hand, SOEs companies cannot be separated from their connections with politicians from various political parties. Petriella (2015) revealed that several administrators or members of a political party served as commissioners in several state-owned enterprises. Even Transparency International Indonesia (2021) said that in SOEs, not only members/political parties with a background in the company's board, even presidential volunteers, have been appointed as commissioners of SOEs. Syaifuddin and Putri (2016) said that the appointment of commissioners related to certain political parties is part of taking advantage of SOEs for the benefit of political parties. Savitri (2021) stated that connection with politics is part of achieving profits by building its reputation. However, Shleifer and Vishny (1994) suggested that government companies close to politicians can be poorly managed from a theoretical perspective.
Based on the phenomenon mentioned above, the data highlights that state-owned companies are carried to two sides that can be said to be performing well and leading to a good performance. Good performance certainly shows a state-owned company that can manage all company resources efficiently. On the other hand, companies that do not have good contributions tend to be unable to manage their asset sources efficiently (Matar and Eneizan, 2018).
Many indicators can be used to measure company performance. Profitability is a pivotal milestone for companies to operate in the short term and even in the long term (Roni et al., 2018). One of the indicators used in analyzing the company's performance is the company's ability to earn profits which are return on assets (Kangarluei et al., 2012).
Political connection is a hidden political relationship between senior management and government officials (Hill, 2009). Meanwhile, Purwoto (2011) states that politically connected companies have political ties or seek closeness with politicians or the government in specific ways. According to Habib et al. (2017), companies owned by the government are also politically connected. In this case, the company owned by the government is a company in the form of SOEs or regional ownership enterprises. Institutional ownership is a condition where the institution owns shares in a company. These institutions can be government, private, domestic, or foreign (Widarjono, 2010). According to Widiastuti et al. (2013), institutional ownership is shared ownership by external institutions. In comparison, Handayani and Nuraina (2012) institutional ownership is the percentage of company shares owned by institutions or institutions.
Cash holding is a term for holding cash or cash in the company. According to Gill and Shah (2012), cash holding is cash held by the company or ready to invest in fixed assets and distribute to investors. Research conducted by Abushammala and Sulaiman (2014) focuses on cash ownership decisions and their important role in improving the company's financial performance and ensuring the required funds in time. Company size is a scale that can classify the size of a company seen from the amount of the assets owned by a company (Dewi, 2010). Accord-DECEMBER 2021 Zainuddin Iba , Yudi Syahputram Ghazali Syamni, Mahdawi ing to Brigham and Houston (2010), company size measures the size of a company indicated or assessed by total assets, total sales, total profits, tax expenses, and others. According to Harahap (2013), leverage is a ratio that describes the relationship between the company's debts to capital. This ratio can oversee how far the company is financed by debt or external parties with the company's ability described by capital. Meanwhile, according to Fahmi (2012), leverage is a measure used in analyzing financial statements to show the amount of collateral available to creditors.
Several previous studies have revealed inconsistent results regarding the performance or profitability of state-owned companies. Maaloul et al. (2018), researching 32 companies in Tunisia, found that political connections affect the company's profitability. Meanwhile, Wulandari and Raharja (2013), who researched 171 companies in Indonesia, found that political connections negatively affect company profitability. Furthermore, Lin and Fu (2017), who conducted a study of 2465 companies in China, found that institutional ownership positively affects a company's performance and is strong to consider for deregulation, current market conditions, and faulty market boards. Research conducted by Doan (2020) using data from 186 Vietnamese companies found a statistically positive and significant effect of state ownership on company performance. Vijayakumaran and Atchyuthan (2017), based on their research in Sri Lanka, explained that cash holding follows the theory that supports a positive effect on company performance. Meanwhile, Iftikhar (2017) also revealed a relationship between cash holding and company performance. The results of this study provide a reliable basis for financial managers to make appropriate cash holding decisions to improve company performance. Research analyzing the performance of companies in Indonesia also found various results. Anggarsari and Aji (2018) documented that company size has an effect on company performance while leverage does not. Linggasari and Adnantara (2020) stated that company size positively affects company performance. Kartikasari and Merianti (2016), who examined 100 quality manufacturing companies on the IDX, found that leverage has a positive effect while firm size has a negative impact on company profitability.
Based on the previous description, it shows the inconsistency of the research results. In addition, the use of the political connection variable in this study is separated at the level of strong and weak, which is then interacted with the political connection but as a model in this study. Therefore, this study is one of the studies using strong and weak political connections in examining the factors that affect the performance of SOEs in Indonesia.
Furthermore, the results of this study are expected to provide benefits for policymakers, company management, investors, or other stakeholders when entering or investing in the capital market. In other words, we can understand the role of political connections in SOEs companies as an important factor, in addition to other factors. This study was conducted to examine several factors that affect the performance of SOEs companies, including political connection, institutional ownership, cash holding, and company size. In addition, it also conducts testing by interacting the level of strong and weak political connections on the performance of SOEs companies.

METHOD Data
The data used in this study is the documentation data of 20 SOEs companies that go public on the IDX accessed from the website www.idx.co.id. From the 20 state-owned companies, there are 16 non-financial companies and four financial companies. The data period used in this study is from 2014 to 2018. So the number of observations is 100 observations.

Research Variable
In this study, the dependent variable is the company's performance as a proxy for return on assets (ROA). Meanwhile, the independent variables used are the level of debt, cash holding, institutional ownership, and company size. The symbols and relationships between the variables can be seen in Table 1 below:

SOEs Corporate Performance on IDX and Some Influenced Factors
The given Table 1 depicts one dependent variable and five independent variables. Each dependent variable is ROA, independent is PC, KI, CASH, Size, and Lev. Apart from this, this research adds a dummy variable to the political connection D_PCON. The addition of the connection political dummy variable is because each company has a different political relationship, meaning that there are less than <3 grouped into the category of not strong (weak) connections and given a value of 0. While those with a value  3 are grouped into the category of strong connections and given a value of 1.

Research Model
This study uses static panel data by testing the common effect model, fixed-effect model, and random effect model. The selected model or the best model is done using the Chow test and Hausman test. So, based on the variables described above, this study uses two models. The first model tests directly or overall, and the second model is a moderation model. Those models can be seen as below:

Data Descriptive
The description of the data is done to explain the level of normality of the data by analyzing the mean and standard deviation, maximum, minimum, and observation. The description of the data can be seen in Table 2  In Table 2, Panel A Overall, the average value of ROA, lower than the standard deviation, explains that the data are not normally distributed. At the same time, the average values of PCON, KI, CASH, SIZE, and LEV are higher than the standard deviation. That indicates that the data are generally distributed with 100 observations. In panel B, with 38 observations, companies that are not connected to politics have the same result. The average value of ROA and KI is lower than the standard deviation. The highlights are that the data are not normally distributed.
Furthermore, CASH, SIZE, and LEV have a mean value higher than the standard deviation. That explains that the data is a good representation of the overall data. In Panel C, with 62 observations, the category of politically connected companies has similar results. The average value of ROA, which is lower than the standard deviation, explains that the data are not normally distributed. While mean values of KI, CASH, SIZE, and LEV are higher than the standard deviation. That indicates that the data are normally distributed.

Correlation Matrix
The purpose of correlation analysis is to determine how big the correlation or relationship between the independent variables and the dependent variable is. The Correlation Matrix can be seen in the Tables below.
Overall, the correlation between the independent variables and the dependent variable portrays that political connections (PCON) have a significant positive relationship to company performance (ROA) at the 1% level, as well as cash holding (CASH), which has a significant positive relationship to company performance (ROA) at the level of 1%. Meanwhile, firm size (SIZE) and leverage (LEV) have a significant negative relationship at the level of 5% and 1%, respectively. Then, institutional ownership has an insignificant positive connection with company performance (ROA).
In Table 3. 2 Panel B, the correlation between the independent variable and the dependent variable for D_PCON=0 (does not have political connections) found that cash holding (CASH) has a   Description: ROA (company performance), KI (Institutional Ownership), CASH (Cash Holding), SIZE (Company Size), LEV (Leverage). The significance of 1%, 5%, 10% is expressed in the sign *** ** * significant positive relationship on company performance (ROA) at the level of 1%. Furthermore, institutional ownership (KI) has a positive relationship, firm size (SIZE) has a positive relationship, and leverage (LEV) has an insignificantly negative relationship on company performance (ROA) for the three variables. Table 3. 3 Panel C, the correlation between independent variables and dependent variable for D_PCON=1 (having political connections) found that institutional ownership (KI) has a positive and significant relationship at the level of 1%. In con-trast, cash holding (CASH) has a positive and significant relationship at the level of 5%. Furthermore, firm size (SIZE) and leverage (LEV) have a negative and significant relationship at the level of 1%, respectively.
In terms of heteroscedasticity, this study found that some variables still indicated heteroscedasticity because there was a significant value at the level of 5%. On the autocorrelation side, this study did not find autocorrelation. In addition, as this study researched using panel data, it does not need to test the classical assumptions (Gujarati and Porter, 2009   Based on Table 4 using the regression results with the Random Effect Model, it can be explained as follows: 1. SIZE, SIZE*(D_DM=0), and SIZE*(D_KM=1) show probability values with a significance level over 10%. That means that the company's size does not affect the company's performance. 2. KI and KI*(D_KM=0) show the probability value with a significance level of over 10 percent. So it has no significant effect on company performance. But KI*(D_KM=1) indicates a significant probability of 10%, meaning that there is an influence on company performance. 3. Political Connections directly affect the company's performance with a significance level of 1%. 4. The cash holding level affects the company's performance, which can be seen from CASH, CASH*(D_PCON=0) with a significance level of 1%. While CASH*(D_PCON=1) does not affect the company's performance as shown by the non-significant profitability value of 10 percent, 5. LEV and LEV*(D_PCON=1) affect the company's performance which is shown from the significant probability values of 10% and 1%. Meanwhile, LEV*(D_PCON=0) has no effect on the company's performance, indicated by a significant value of over 10%. 6. The results of the F test show that PCON, KI, CASH, SIZE, and LEV have a significant effect on return on assets in state-owned com-panies in Indonesia. That can be seen from the significance level of 1%. 7. This finding shows that all independent variables' ability to explain the company's performance is weak. That can be seen from the coefficient of determination (R 2 ) at the 20-39.9% level. That means that many other variables are affecting the company's performance.

The effect of political connections on company performance
The study results (Table 4) reveal that political connections affect company performance in SOEs companies on the Indonesia Stock Exchange. The significant probability value indicates this at the level of 1% (Table 4). The results of this study are in line with previous research conducted by Maaloul et al. (2018) that political connections have a significant positive effect on company performance in which they use all companies on the Tunisian Exchange except the financial sector. Meanwhile, this research focuses on all SOEs companies. However, other studies say that political connections have a negative effect on company performance, such as research by Wulandari (2018), which focuses on manufacturing companies, found that political connections negatively affect company performance.
Political connections are considered an intangible resource that enables firms to gain government support, and therefore the companies gain competitive advantage and result in higher performance. The positive effect of political connections on a company's performance may reflect that po- (2) Therefore, the best model in this study is the random effect model. However, this study found that it does not affect its performance when a company has no political connection. When there is a political connection, it makes SOEs with institutional ownership (government) affect its performance. Besides that, this study found that companies having political connections will make cash holding no effect on a company's performance. This finding indicates that companies with political connections have no impact on the company's motives for cash holding. Each company has its cash plan according to the company's needs. There are political connections or not; companies should still plan their cash for their long-term plans.

The Effect of Institutional Ownership on Company Performance
The study results found that institutional ownership does not affect the performance of stateowned companies on the Indonesia Stock Exchange. That can be seen in Table 4 above, where the probability value is not significant at the level of 10%. The findings of this study are consistent with the research conducted by Sianipar et al. (2018), who examined plantation sector companies on the Indonesia Stock Exchange, which found that institutional ownership does not affect company performance. Meanwhile, this study used data on SOEs companies whose ownership is mainly the government.
However, this result is in line with the research by Lin and Fu (2017), who stated that institutional ownership has a positive effect on company performance. This finding indicates that state-owned companies, whose majority of shareholders are owned by the government, receive preferential treatment from the government, such as deregulation, current market conditions, easy access to capital loans, and low risk during tax audits.

The Effect of Cash Holding on Company Performance
The study results (Table 4) found that cash holding has a significant positive effect on the performance of state-owned companies on the Indo-nesia Stock Exchange. That is indicated in a significant probability value of one percent. This finding is in line with Iftikhar (2017) and Vijayakumaran and Atchyuthan (2017) Sri Lanka. They focus on Pakistan companies and state that cash holding has a significant positive effect on company performance. Iftikhar (2017) uses non-financial companies on the Pakistan Stock Exchange. That indicates that the company is increasing its cash holdings due to uncertain cash flows and future business opportunities.

The Effect of Company Size on Company Performance
The results of the study (Table 4) found that company size has no significant effect on the performance of SOEs companies on the Indonesia Stock Exchange. That can be seen in Table 4 above, where the probability value is not significant. This finding is consistent with Maaloul et al. (2018), who found that company size has no effect on company performance at all non-financial companies in Tunisian Exchange. However, this research is not in line with Wulandari (2018), who focuses on the mining sector, finding that company size positively affects company performance. Kartikasari and Merianti (2016), who focus on manufacturing companies on the IDX, found that firm size has a negative effect on company profitability. This finding indicates that a large number of assets is not a guarantee if it does not provide maximum benefits from the results of its operational activities and can reduce its performance. Large assets incur high maintenance costs and cause high fixed costs where when there is a decrease in demand, the company's profits will decrease.

The Effect of Leverage on Company Performance
The study results (Table 4) found that leverage has a significant negative effect on the performance of SOEs companies on the Indonesia Stock Exchange. This finding is consistent with Maaloul et al. (2018), who focus on all non-financial companies in Tunisia found that leverage has a significant negative effect on company performance. This find-ing indicates that state-owned companies are highly dependent on government funds. The use of debt that is not optimal in the capital structure will not affect the company's performance. That is because funding through debt results in the company having to pay its obligations and interest, which usually comes from its profits.

CONCLUSIONS
Based on the analysis and discussion results above, this study concludes that political connection, cash holding, and leverage affect SOEs corporate performance. Meanwhile, two other variables, such as institutional ownership and firm size, do not affect the performance of SOEs. In addition, this study found that institutional ownership and leverage in companies with strong political connection potential affect the financial performance of SOEs companies. On the other hand, cash holding in SOEs companies with political potential tends to have a weak effect on company performance.

LIMITATIONS
This research has limitations because it only uses the issue of weak and strong political connections. Therefore it is necessary to consider including political connections during certain government periods. Future research is expected to identify not only the state-owned enterprises listed on the stock market but also state-owned companies that are not listed on the stock market or companies owned by officials involved in the administration

IMPLICATIONS
Based on the research results presented above, the theoretical and practical implications can be expressed. The theoretical implications provide knowledge about separating the potential for strong and weak political connections in a company. So that it can determine which companies with weak political potential do not affect company performance, on the other hand, companies that tend to have strong connections affect their company's performance. Meanwhile, the practical implications of this research can be used as information input for investors (potential), especially those who invest in SOEs companies, to consider companies with potential political connections. That is because the company's performance tends to perform well.