Keywords

Company Value, Dividend Policy, Debt Policy, Capital Structure, Liquidity.

Introduction

Management of a large, small, private or state-owned enterprise is constantly building a strategy that is supposed to ensure financial security and profits for the owners (Zimon, 2020). The development of the manufacturing industry in Indonesia is proliferating in the current industrial era. It can be seen from the increasing number of manufacturing companies listed on the IDX from year to year. These two elements of financial liquidity and profitability are one of the most important measures of the company’s position in the market (Zimon, 2020). Competition in today's business world requires every company to improve its performance further to achieve its goals. The better the company's performance, the more attractive it is to investors (Driver, 2020). Many investors are currently looking at manufacturing companies in Indonesia because the growth rate in this sector is proliferating from year to year (Mesrawati et al., 2021). Firm value is an investor's perception of the company's level of success which is often associated with stock prices (Sumani, 2020). High stock prices make the company's value also high and increase market confidence in the company's current performance and the company's prospects in the future (Nguyen, 2020;  Zimon, 2018). Potential investors will consider poor financial performance because this will affect the value of the company (Kumar, 2020). If the company's condition is terrible, investors lose confidence in its business prospects and choose to withdraw their funds (Dewi et al., 2021). The existence of value creation and the creation of welfare for shareholders, and market valuation are the most critical problems the company faces (Zimon & Zimon, 2019). Financial statements that explain book value do not describe the actual financial condition of the company (Renneboog, 2020). Thus the estimated value has a vital role in the company's environment.

The level of dividends distributed by the company can affect stock prices because investors prefer returns from dividends compared to capital gains. The higher the dividend payment, the higher the stock price so that the company's value is also high. However, if a small company pays the dividend, then the company's stock price is also low (Purwaningtyas & Abbas, 2021; Setiawan et al., 2021). The results of research conducted by (Dewi et al., 2021; Masri Erma, 2014; Mesrawati et al., 2021; Miranti et al., 2021) stated that dividend policy positively affects firm value. If the dividend policy increases, the value of the company also increases. However, the results of this study are not in line with research conducted by (Abbas, 2019; Apriani et al., 2021; Syamsuhidjar Ar et al., 2020), which states that dividend policy does not affect firm value. The increase in the dividend payout ratio is only a detail and does not affect the level of shareholder welfare. Based on the explanation of the existing research gap, it raises a question in this study, namely about whether dividend policy affects the value of manufacturing companies in the primary and chemical industry sub-sectors in Indonesia.

Another factor that influences firm value is debt policy. Debt is an instrument that is very sensitive to changes in the value of the company (Tahir, 2020). The results of research conducted by (Apriliyanti et al., 2019) stated that debt policy positively affects firm value. Increasing debt at the optimal point will increase the value of the company. Research conducted by (Alvita & Khairunnisa, 2019; Apriani et al., 2021; Nainggolan & Listiadi, 2014) states that debt policy hurts firm value. These results indicate that the higher the debt, the lower the firm value, and the lower the debt, the higher the firm value. These results are not in line with research conducted by (Apriani et al., 2021; Azis, 2017; Dewi et al., 2021; Jones Xaverius Pontoh, 2019; Masri Erma, 2014; Syamsuhidjar Ar et al., 2020), which shows that debt policy does not affect firm value. The high and low debt ratio does not have implications for the high and low value of the company. Based on the explanation of the existing research gap, it raises a question in this study, namely, whether debt policy affects the value of manufacturing companies in the primary and chemical industry sub-sectors in Indonesia.

To achieve the company's goal is maximizing the company's value can not be separated from the problem of how much the company can meet funding needs (Demirgüç-Kunt, 2020). Capital structure can be an important problem for the company because the good or lousy capital structure will directly affect the company's financial position (Mubeen, 2020). Financial managers must be able to raise funds efficiently. The results of research conducted by (Febriana et al., 2016) stated that capital structure positively affects firm value. The use of debt in the capital structure can control the excessive use of free cash flow. So that management does not get involved in unprofitable investment projects. The results of research conducted by (Gustini, 2017; Purwaningtyas & Abbas, 2021; Sri et al., 2013) stated that capital structure hurts firm value. Determination of capital structure by using debt at a certain level as a source of funding can increase the company's value. However, the results of this study are not in line with (Chasanah, 2019; Febriani, 2017; Setiawan et al., 2021; Syamsuhidjar Ar et al., 2020), which state that capital structure does not affect firm value. Based on the explanation of the existing research gap, it raises a question in this study, namely about whether the capital structure affects the value of manufacturing companies in the primary and chemical industry sub-sectors in Indonesia.

Every company, both large and small, must pay attention to liquidity. By maintaining its liquidity, the company can gain the trust of internal and external parties (Pattiruhu, 2020). One of the causes of the company's inability to fulfill its obligations is the negligence of the company's management in running its business. The results of research conducted (Putra & Lestari, 2016) stated that liquidity positively affects firm value. The research results conducted by (Andrianti et al., 2021; G. Zimon, 2020) stated that liquidity hurts firm value. That can be realized because when an enterprise and by ordering goods and services is able to sell them faster and receive payment than is the time of payment for these goods, materials to suppliers (G. Zimon, 2020). These results are not in line with research conducted by (Abbas et al., 2020; Humairah et al., 2021; Purwaningtyas & Abbas, 2021; Septiana et al., 2021), which states that liquidity does not affect firm value.

Signal theory explains the reasons for companies to provide financial statement information to external parties related to the existence of information asymmetry between the company's management and outside parties (Jensen & Meckling, 1976). The company management has more information and knows the company's prospects in the future. The information can be in financial reports, company policy information, or other information that is carried out voluntarily by the company's management. Signal theory suggests how a company should provide signals to users of financial statements. This signal is in the form of information about what management has done to realize the wishes of the owner company (Jensen & Meckling, 1976). Companies can increase the company's value by reducing information asymmetry; one way is by giving signals to outsiders in the form of reliable financial information to reduce uncertainty about the company's prospects in the future.

The theoretical benefit of this research is as a means of information about how the interaction of dividend policy, debt policy, capital structure, and liquidity on firm value in primary and chemical industries in Indonesia. The practical benefits of this research are expected to be used as material for consideration and reference so that in investing, investors choose companies that are transparent in disclosing information and company performance that can be accounted it. And, it can provide a discourse about the importance of the company in making decisions on the policies issued by the company, which of course, can affect its value. In addition, it is also expected to motivate the company so that the company can continue to grow and develop so that it can continue to compete in local and international markets.

Methodology

The approach in this study is quantitative because this research is presented with numbers. Quantitative research is research whose data is quantitative so that it is in the form of numbers or quantitative data that is numbered (Abbas et al., 2018). Meanwhile, Eksandy & Heriyanto (2017) stated that the quantitative research method is a research method based on the philosophy of positivism, used to examine the population in a particular sample; the sampling technique in this study uses purposive sampling based on specific considerations. According to the level of explanation, this research is classified as associative research. According to (Dirvi et al., 2020), associative research aims to find whether there is a relationship between two or more variables. The associative research analysis technique uses quantitative (statistical) analysis techniques. In this study, researchers used four independent variables and one dependent variable. The operational definition of research variables explains each variable used in research on the indicators that make it up. The operational definition of this research can be seen in the following Table 1:

Table 1 Operational Variables
No	Variable	Proxy	Measure Scale
1.	Firm Value		Ratio
2.	Dividen Policy		Ratio
3.	Debt Policy		Ratio
4.	Structure Capital		Ratio
5.	Liquidity		Ratio

This study takes a sample of Basic and Chemical Industry companies listed on the Indonesia Stock Exchange during 2015 - 2019. The data used in this study is secondary data obtained from the official website of the Indonesian Stock Exchange (IDX). Sampling in this study using a purposive sampling technique, namely sampling based on specific criteria. Data found the number of primary and chemical industrial companies listed on the Indonesia Stock Exchange (IDX) in 2015–2019 to be 80 companies. However, 25 companies do not issue annual financial reports, 13 companies that provide complete information in foreign currencies, and 34 companies that do not distribute dividends in a row in 2015–2019. So that the sample data that sample can use are 40 (8 companies x 5 years).

Results

The next stage of data testing aims to find a suitable analytical model so that the model can later be used in the next stage of regression analysis. In testing to find the type of regression model that is suitable for use, the result must pass through the model testing stage, which is as follows:

Based on observations from Table 2, the result can conclude that the model is Random Effect more suitable to analyze the relationship between factors in exogenous and endogenous variables. After finding a suitable model for use, the next stage is classical assumption testing, but this test cannot be applied to all model results that will be used after going through the testing stage. Classical assumption testing is only used for regression models with the OLS approach to estimate (Abbas & Hidayat, 2021). The analytical model that has the nature of the approach Ordinary Least Square (OLS)in the regression model is the Common Effect Model (CEM) and Fixed Effect Model (FEM). Therefore, based on the results of the regression model test, the model obtained that the Random Effect Model (CEM) model was feasible to use. That way, the model will not test the regression in this study for classical assumptions.

Table 2 Model Estimation Test Results
Effect Test	Prob > F	Best Model
		Determining Test	(Prob>F) / (Prob>Chibar2) / (Prob>Chi2)	Description
Ordinary Least Square (OLS)	0.0000	Chow test (OLS vs FE)	0.0001	Fixed Effect
Fixed Effect (FE)	0.0000	Hausman test (FE vs RE)	0.3442	Random Effect
Random Effect (RE)	0.0000	LM test(OLS vs RE)	0.0000	Random Effect

Table 3 above describes all variables in this study, including the minimum, maximum, mean (average), and standard deviation values. The explanation above provides an overview of the data descriptive statistics, which is expected to provide an initial picture of the problem under study. Where descriptive statistics are more focused on the highest value, lowest value, average and standard deviation of each variable studied, amounting to 8 Basic and Chemical Industry companies in 2015 to 2019, both independent variables consisting of Dividend Policy, Debt Policy, Capital Structure, and Liquidity, as well as the dependent variable Firm Value.

Table 3 Analysis Statistic Descriptive Result
	Q	DPR	DAR	DER	CR
Mean	1.812525	0.725650	0.418075	1.047350	2.316800
Median	1.732000	0.440000	0.367500	0.559000	2.118000
Maximum	4.584000	5.615000	0.820000	4.547000	4.887000
Minimum	0.673000	-0.099000	0.133000	0.154000	0.993000
Std. Dev.	0.979164	0.978662	0.193006	1.127034	1.167535
Skewness	0.805732	3.453023	0.614542	1.871122	0.546896
Kurtosis	3.003491	16.85295	2.518507	5.472948	2.150964
Observations	40	40	40	40	40

a. Firm Value

Table 3 above shows the number of data on the value of the company or Tobin's Q. The largest (maximum) is 4.584000, and the smallest value (minimum) is 0.673000. The mean (mean) of Tobin's Q is 1.812525, and the standard deviation is 0.979164. The standard deviation value, which is smaller than the average value, indicates that the firm value of the sample firms during the study period experienced changes that were not too volatile.

b. Dividen Policy

Table 3 above shows the largest (maximum) amount of dividend policy data or Dividend Payout Ratio (DPR) is 5.615000, and the smallest (minimum) value is 0.099000. The average (mean) of the DPR is 0.725650, and the standard deviation is 0.978662. The standard deviation value that exceeds the average value indicates that the condition of the dividend policy in the sample companies during the study period experienced fluctuating changes.

c. Debt Policy

Table 3 above shows the most significant (maximum) amount of debt policy data or Debt to Asset Ratio (DAR) is 0.820000, and the smallest (minimum) value is 0.133000. The mean (mean) of DAR is 0.418075, and the standard deviation value is 0.193006. The standard deviation value, which is smaller than the average value, indicates that the condition of debt policy in the sample companies during the study period experienced changes that were not too volatile.

d. Capital Structure

Table 3 above shows the most significant amount of capital structure data or Debt to Equity Ratio (DER) (maximum) is 4.547000, and the smallest (minimum) value is 0.154000. The mean (mean) DER is 1.047350, and the standard deviation value is 1.127034. The standard deviation value that exceeds the average value indicates that the condition of the capital structure of the sample companies during the study period experienced fluctuating changes.

e. Liquidity

Table 3 above shows the most significant amount of liquidity data or Current Ratio (CR) is 4.887000, and the smallest value (minimum) is 0.993000. The mean (mean) of CR is 2.316800, and the standard deviation is 1.167535. The standard deviation value is smaller than the average value, indicating that the liquidity conditions in the sample companies during the study period experienced changes that were not too volatile.

Based on the observations in Table 4, it can be seen that the F-table with the criteria df1 = 4 and df2 = 35 with a level of = 5%, then the value is Ftable 2.64. So when compared to Fstatistic (36.9547) > F-table (2.95), it appears that F-statistic is higher than F-table, so it means that the selected regression model is feasible. The exogenous variables in this study were able to explain the variation of high/low endogenous variables by 25.8%, while 74.1% was influenced by exogenous variables that were not present in this study.

Table 4 Summary of Research Hypotheses
Hyp	Hypothesis Statement	Coef. Value	P >|z|	Model
1	Are dividend policy have positive affected to Firm Value	t-statistic -0.438900 Prob. 0.6634	Hypothesis Denied	Q = 5,167007 − 0,044863DPR− 5,881408DAR + 0,209065DER − 0,467033CR + ε
2	Are debt policy have negative affected to Firm Value	t-statistic -2.332744 Prob. 0.0255	Hypothesis accepted
3	Are capital structure have positive affected to Firm Value	t-statistic 0.583914 Prob. 0.5630	Hypothesis Denied
4	Are liquidity have positive affected to Firm Value	t-statistic -2.266896 Prob. 0.0297	Hypothesis accepted
F Statistic = 36.9547		F tabel = 2.64
R-Square = 0,258352

Discussion

Dividend Policy Not Increasing Firm Value

The dividend policy variable partially does not affect firm value. These results indicate that the high and low dividend ratio distributed to shareholders is not related to the high or low firm value. It is due to the increase in the dividend payout ratio only details and does not affect the level of welfare of shareholders. The results of this study are by research conducted by (Apriani et al., 2021; Apriliyanti et al., 2019; Syamsuhidjar Ar et al., 2020), which states that dividend policy does not affect firm value. The value of the company is only influenced by the company's ability to generate the desired profit. However, the research results are not in line with (Dewi et al., 2021; Ferina & Tjandrakirana, 2015; Masri Erma, 2014; Mesrawati et al., 2021; Miranti et al., 2021; Putra & Lestari, 2016) results, which state that dividend policy has a positive effect on firm value.

Debt Policy Increasing Firm Value

The debt policy variable partially affects the firm value. The negative results support the regression coefficient value of the DAR variable of -6.193462, which illustrates that debt policy hurts firm value. It is because debt is one source of financing that has a high level of risk. This risk is related to the risk of interest payments, which the company cannot cover. The greater the debt, the higher the probability of bankruptcy because the company cannot pay interest and principal. The lower the debt ratio value, the better because it means the company can run its business without debt burden and minimize the risk of bankruptcy. The negative results in this study support the results of research conducted by (Alvita & Khairunnisa, 2019; Apriani et al., 2021; Masri Erma, 2014; Nainggolan & Listiadi, 2014), which states that debt policy hurts firm value. The Apriliyanti research (2019) results stated that debt policy has a positive effect on firm value. However, research conducted by (Ferina & Tjandrakirana, 2015; Setiawan et al., 2021; Syamsuhidjar Ar et al., 2020) states that debt policy does not affect firm value.

Capital Structure Not Increasing Firm Value

The capital structure variable partially does not affect firm value. The bigger the company uses debt, the greater the benefits of using debt from tax savings. It will impact the company's agency costs to external or creditors so that the capital structure of a company is only part of its financial structure. It is shown that profitable companies will use large debts for company funding but can pay their debts from the profits earned. Companies with a low-profit level will not use debt with a high ratio because it will cause the risk of default and bankruptcy. The results of this study are supported by (Chasanah, 2019; Febriani, 2017; Setiawan et al., 2021; Syamsuhidjar Ar et al., 2020) which state that capital structure does not affect firm value. However, the results of this study are not in line with (Febriana et al., 2016; Gustini, 2017; Purwaningtyas & Abbas, 2021), which states that capital structure has a positive effect on firm value.

Liquidity Increasing Firm Value

The liquidity variable partially affects the firm value. The negative results support the CR variable regression coefficient of -0.546159, which illustrates that liquidity hurts firm value. The higher the liquidity, the company's value will decrease because of the large number of idle funds resulting in the company not utilizing its current assets optimally. It is considered by investors and becomes a negative signal because the company must bear the risk in capital costs. The results of this study are supported by (Andrianti et al., 2021; Sri et al., 2013) which states that liquidity hurts firm value. However, the results of this study are not in line with  (Abbas et al., 2020; Chasanah, 2019; Febriani, 2017; Humairah et al., 2021; Purwaningtyas & Abbas, 2021; Septiana et al., 2021), which state that liquidity does not affect firm value.

Conclusion

This study analyzes the effect of Dividend Policy, Debt Policy, Capital Structure, and Liquidity on Firm Value. The sample used is eight companies in the Basic and Chemical Industry sector listed on the Indonesia Stock Exchange from 2015 to 2019. Based on the results of the tests carried out, it can be concluded several things, namely. Dividend policy and capital structure in this study do not affect firm value. Debt policy in this study affects firm value. The debt policy regression coefficient (DAR) value is 5.881408, which illustrates that debt policy hurts firm value. Likewise, the liquidity variable in this study affects firm value. The liquidity regression coefficient (CR) value is -0.546159, which illustrates that liquidity hurts firm value. This study has limitations. Namely, the Adjusted R-Square value in this study is 0.258352 on the variables of Dividend Policy, Debt Policy, Capital Structure, and Liquidity in explaining its influence on the Firm Value variable which is still limited at only 25.83%. The remaining 74.17% is explained by other variables not examined in this study, and this study only took a sample of 40 financial statements from 8 Basic and Chemical Industry Sector Companies listed on the Indonesia Stock Exchange for the 2015–2019 period.

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