Suripto*
| Arif Sugiono | Rifatin Cholidia | Nurul Fikriatus Sholihah
© 2024 The authors. This article is published by IIETA and is licensed under the CC BY 4.0 license (http://creativecommons.org/licenses/by/4.0/).
OPEN ACCESS
This study analyzes the effect of green management on the stock prices of energy companies listed on the Indonesia Stock Exchange from 2020 to 2023 with a sample of 17 energy companies. The results of panel data analysis using Eviews with a fixed effect model show that environmental performance as a proxy for environmentally based company management has a positive effect on stock prices. To obtain accurate prediction results in the study using control variables of profitability, leverage, and company size the results show that only profitability has a positive effect on stock prices. While leverage and company size do not have a significant effect on stock prices. This finding implies that energy companies must implement green management because it will have an impact on increasing stock prices and company value and maintaining environmental sustainability so that companies develop sustainably. These results further prove that information about green management can be a positive signal for investors, and this signal can be used as a basis for making investment decisions in the energy sector.
environmental, performance, profitability, leverage, stock price, investment, fixed effect, signals
Sustainable development issues are very crucial at this time due to the impact of industrialization, especially in industries that depend on the environment, for example, the energy industry. Therefore, cooperation is needed between the government, society and the private sector to overcome the problems of the impact of development. This means that economic growth will have an impact on environmental preservation. The strong relationship between economic growth and the environment is increasingly clear, so there must be an agreement to harmonize economic growth with environmental preservation. This will be very important for the survival of life in the universe. Therefore, research is needed that harmonizes sustainable development with the environment.
Investment is an attempt to obtain future returns. However, the results currently obtained are not balanced without ignoring the environmental impact of a business activity. Investment growth will remain sustainable if we continue to pay attention to the environment. This means that investors when investing not only pay attention to returns but also pay attention to the environmental impact of the business so that the returns obtained are also sustainable or long term. Because business activities or company energy will run out if environmental aspects are destroyed.
Therefore, companies must create policies, strategies and programs that aim at sustainable economic development while paying attention to environmental conservation. This concept is known as the green management concept. Energy industry companies must implement environmentally friendly management to ensure their business aspirations. Likewise, what companies do in implementing green management must be a concern for investors in the capital market. Is this information a positive signal for investors? This will be very important for sustainable economic development.
The concept of green management which is very popular today is in line with the concept of sustainable development (SDG). Green management is a concept that aligns environmental aspects with business goals. Thus, green management is a form of social responsibility for sustainable environmental preservation [1]. This indicates that implementing green management is a social corporate responsibility.
Environmental discussions will be crucial in the energy sector which is always related to environmental conservation. Mining companies are required to implement environmentally friendly management. The green management concept is part of the company's strategy for achieving sustainable goals through achieving environmental performance, which ultimately achieves sustainable development. Energy sector companies that implement green management are generally public companies that become investment media. Thus, the implementation of green management is able to increase company value. Green management research is only linked to company performance [2]. But has not been linked to company value or share prices. This research aims to analyze the influence of green management on company value as proxied by share prices.
According to the statement that performance of companies is simply defined as the manner in which organizations can effectively achieve set goals [3]. It comprises financial metrics such as profitability and revenue growth, as well as non-financial metrics namely customer satisfaction, operational efficiency, and environmental sustainability. According to a previous investigation, the effective improvement of organizational performance is determined by various factors, including the understanding, development, and implementation of sustainable environmental strategies. Sustainable performance, companies must address internal challenges and ensure the preservation of the environment. A previous study supported this assertion, stating that the operational performance of companies can be measured by the corresponding level of environmental performance [4]. From this statement, it can be seen that a relationship exists between the achievement of green management and the attainment of improved operational performance.
Another study found that investors are more likely to value companies with policies aimed at improving environmental performance [5]. This implies that the market generally perceives companies that prioritize environmental sustainability positively. The attainment of environmental performance is expected to have an impact on the overall condition of an organization. Therefore, when there is an information gap between management and investors regarding the conditions of companies, the information provided by management will significantly influence the responses of investors. As previously stated, information about environmental performance can serve as signals for investors, this phenomenon is known as signaling theory.
In the present business landscape, conservation efforts and the responsible use of natural resources, water, and air have become global priorities. Companies that adopt sustainable practices have been observed to not only contribute to environmental preservation but also experience positive impacts on respective financial performance [6]. For instance, under the Green Europe agreement, companies in Europe are required to prioritize environmental considerations. The results of this policy show that companies with superior environmental performance see improvements in accounting-based performance alone, and not in market-based performance [7].
Several studies have been carried out with the primary aim of comprehending the relationship between environmental and financial performance. These investigations yielded different results primarily due to the varied use of moderators across each study [8]. For instance, Di Pillo et al. [9] reported that environmental performance had a positive relationship with financial performance. Therefore, this present study aims to examine the influence of green management on stock prices of companies, particularly those within the energy sector.
To accurately assess the effect of environmental performance on stock prices, this study incorporates control variables such as profitability, leverage, and company size. By adopting these variables, the results provide a more precise model of the causal relationship between environmental performance and stock prices.
2.1 Signaling theory
Investor in making investment decisions in the capital market has always been an interesting discussion in financial studies. The information needed in decision making greatly determines the quality of a decision. This information can come from internal company sources in the form of annual reports, or information from external sources. This information is a signal for investors who are implemented in investment which is reflected in the share price of a company.
The discussion of investor behavior in investing in the capital market is known as signaling theory. Signaling theory elucidates the behavior of individuals with access to varying information by focusing on how one party sends signals and how the other party interprets and responds to those signals [10]. Investors, being external to companies, typically lack detailed knowledge into its condition. The decisions of investors heavily hinge on available information, which is being used to assess the prospects of potential investments. Signaling theory simply elucidates how investors interpret this information to make informed decisions in the capital market.
Investors typically respond to the information provided by companies, including those related to environmental sustainability, and this can significantly impact stock prices. This effect is particularly significant in the mining industry, where environmental practices are closely scrutinized [11]. Accordingly, information asymmetry has been observed to exist between companies and investors, making the information provided crucial signals for market participants.
Signaling theory offers compelling reasons why companies should prioritize environmental concerns. A robust community-company relationship has been observed to ensure the fulfillment of long-term objectives. This relationship is further reinforced by the attainment of economic performance goals, which in turn secure the success of companies.
Another study found that investors are more likely to value companies with policies aimed at improving environmental performance [5]. This implies that the market generally perceives companies that prioritize environmental sustainability positively. The attainment of environmental performance is expected to have an impact on the overall condition of an organization. Therefore, when there is an information gap between management and investors regarding the conditions of companies, the information provided by management will significantly influence the responses of investors. As previously stated, information about environmental performance can serve as signals for investors, this phenomenon is known as signaling theory.
2.2 Green management
Green management is a new perspective in organizational management, where environmental aspects become part of implementing business strategies and operations. This aims to reduce the negative impact of environmental pollution and can improve business performance. Implementations of green management includes the use of environmentally friendly technology, the use of recycling to reduce waste and awareness of the importance of the environment. Companies that imply environmentally friendly management have succeeded in developing policies that pay attention to ongoing environmental aspects [12]. Companies that successfully implement environmentally friendly management are able to improve performance and benefit the interests of stakeholders [13]. Companies that implement green management will be present with other organizations and will adapt to environmental standards and pay attention to environmentally friendly consumers in their business operations [14]. Understanding the importance of awareness of green management will determine success in competition in the era of globalization
In the last decade, there has been much research on the importance of green management in the context of sustainable development. Riyantini and Nusraningrum [2] found that green management influences green performance. This means that environmentally oriented policies are able to improve the performance of environmentally friendly organizations. Green management practices through green marketing and green technology have a significant effect on green performance and financial performance [15]. These findings indicate that green management is also different from increasing company profitability. Improving company performance through improving environmentally friendly management systems is important in the transformation of business management functions [14]. A green management system not only improves financial performance but is able to maintain a sustainable environment.
The environmental performance assessment program as a form of responsibility in environmental management is known as PROPER (Public Disclosure Program for Environmental Compliance). PROPER is the result of an evaluation carried out by the Indonesian Ministry of Environment on companies in managing the environment. PROPER is a Public Disclosure Program for Environmental Compliance. PROPER is a form of accordance with what has been stipulated in statutory regulations. The implementation of this instrument is an effort by the State Ministry of the Environment to apply some of the principles of good governance (transparency, fairness, accountability and community involvement) in environmental management [16]. Thus, the PROPER assessment can be used as a proxy for the assessment environmental performance. PROPER as a result of the implementation of environmental management has a significant positive effect on stock prices. Thus, the better the PROPER value, the higher the stock price will be [17]. Environmental performance is the result of a management process that implements company strategies by paying attention to the environment. Achieving environmental performance which is the result of the company's green management strategy will provide a signal to external parties or investors. This signal will be responded to by investors in making investment decisions in the stock market.
The application of signal theory in the context of this study is to help explain market behavior in transactions. The basic concept of signal theory is how market players interact between sellers and buyers, where both have different information in making decisions [18]. Price agreement between sellers and buyers when there is the same information so that a mutually beneficial price will be obtained. The results of the implementation of the green management strategy which is the achievement of environmental performance known as PROPER is information that must be conveyed to market players. This information is referred to as a signal of what has been done by the company will be responded to by investors as market players according to the content of the information. PROPER information indicates that the company has implemented green management. PROPER content will be used as a basis or information in making decisions to buy shares. Thus, the application of signaling theory in explaining the transaction process between companies and investors is very relevant. The relationship between the content of PROPER information and stock prices is directly proportional or positive. When the value is good, market demand will increase so that the price will increase.
3.1 Green management
Management is a company strategy with an environmental conservation approach. This approach requires companies to pay attention to environmental conservation principles in operating their business. The assessment of this strategy is an environmental performance assessment known as PROPER. Thus, the measurement of green management can use the PROPER value as a form of implementation of the green management concept. The PROPER value can be used as a signal for investors in the stock market to what extent the company cares about the environment. This indicates that the more concerned about the environment, the company has the prospect of achieving sustainable goals. So with this, the research hypothesis can be formulated:
H1: There is a positive relationship between Green Management and stock prices.
3.2 Profitability
Profitability is the company's ability to generate profits with all its assets. Profitability is fundamental information in measuring financial performance. This performance can be used as a dominant signal for stock market players. High profitability indicates efficient and effective company management which ultimately provides benefits in the form of dividends for shareholders. Thus, the research hypothesis can be formulated:
H2: There is a positive relationship between Profitability and stock prices.
3.3 Leverage
Leverage is a concept that measures the comparison of total debt to total assets. This concept is known as the concept of funding policy. The purpose of this ratio is to measure how much company capital is financed by debt. When the company's prospects have good prospects, the use of debt can be used as a lever for company performance. This leverage can be used as a positive signal that the company has good performance. So, we can formulate a research hypothesis:
H3: There is a positive relationship between Leverage and stock prices.
3.4 Size of the firms
The scale of the company's financial performance achievement is very dependent on the size of the company. The larger the company as measured by total assets, the greater its performance, because the capital operated is also large so that it will have an impact on performance achievement. Thus, the size of the company can be used as a signal that the company has a profitable performance which ultimately provides stock returns for investors in the market. So, we can formulate a research hypothesis:
H4: There is a positive relationship between Size of the Firms and stock prices.
This research aims to analyze the influence of green management on stock prices in the energy sector. To obtain valid results, control variables will be added, namely profitability, company size and leverage using the panel data method. Therefore, this present study aims to examine the influence of green management on stock prices of companies, particularly those within the energy sector. To accurately assess the effect of green management on stock prices, this study incorporates control variables such as profitability, leverage, and company size. By adopting these variables, the results provide a more precise model of the causal relationship between green management and stock prices.
4.1 Study sample
This quantitative study aimed to analyze companies in the energy subsector listed on the Indonesia Stock Exchange from 2020 to 2023. The selection of research samples is very relevant to environmental issues because energy companies are businesses that exploit natural resources that will have an impact on environmental conservation. Likewise, the selection of 2020-2023 is very appropriate because in that period there was still a Covid pandemic that had an impact on the operations of energy companies. The energy sector is the sector most affected by the pandemic. The restrictions on public mobility will affect energy use. Thus, this period is very important to study.
4.2 Study variables
The variables considered in this study include: Green management: This variable was measured using the Ministry of Environment's PROPER ranking, which assigns scores as follows, Gold (5), Green (4), Blue (3), Red (2), and Black (1). Returns on Asset (ROA): Includes the comparison of operating profit with total assets. Company Size (Size) proxied by total Assets.
Leverage (Debt Assets ratio -DAR): This variable comprises the comparison of total debt with total assets. Stock Price: refers to the closing stock price at the end of the year.
4.3 Data analysis: Panel data model
Regression analysis is typically conducted with the aim of measuring the strength and direction of the relationship between two or more variables. This analysis shows how the dependent variable is influenced by the independent variables.
Y=α+β1Proper+β2ROA+β3Size+β4DAR+e (1)
where, Y: Stock Prices; α: Constant; β1: Green management Coefficient; β2: ROA Coefficient; β3: Size Coefficient; β4: DAR Coefficient; e: Error term.
To estimate panel data parameters, several methods can be adopted, including:
4.3.1 Pooled least square
This method combines cross-sectional and time series data, treating both as a single observation to estimate the model. By pooling the data, the regression results tend to be more robust compared to using either cross-sectional or time series data alone. The estimation formula for PLS is as follows:
$\mathrm{Y}_{\mathrm{it}}=\beta_1+\beta_2+\beta_3 \mathrm{X}_{3 \mathrm{it}}+\ldots+\beta_n X_{n i t}+\mu_{\mathrm{it}}$ (2)
4.3.2 Fixed effect model
This model incorporates additional variables not explicitly stated in the equation by permitting a variable intercept that can vary for each individual and over time. Unlike the ordinary least squares method, which assumes constant intercepts and slopes, the fixed effect model includes dummy variables to capture differences in parameter values across cross-sectional units. The equation formula for this model is:
Yit=α1+α2D2+…+αnDn+β2X2it+…+βnXnit+μit (3)
4.3.3 Random effect model
In this model, differences between individuals are reflected through the error term rather than the intercept. Specifically, the random effects model assumes that these differences are random and may be correlated across time series and cross-sections. The model is formulated as follows:
Yit=β1+β2X2it+…+βnXnit+εit+μit (4)
4.4 Model selection
In this study, several tests were conducted to select the appropriate model, including the Hausman test and the Fixed Effect Test (or Chow test). The Hausman test determines whether to use a fixed-effect or random-effect model, while the fixed-effect test (or Chow test) decides between a common model and a fixed-effect model.
4.4.1 Chow-test (common vs fixed effect)
The Chow test is used to determine the common or fixed effect to be used in an estimate. The Chow test formula includes:
$C H O W=\frac{(R R S S-U R S S) /(N-1)}{U R S S /(N T-N-K)} .8$ (5)
The basis for decision-making using the Chow test is as follows:
a) If the Chow statistical value Fcount>Ftable=H0 is rejected, then the Fixed Effect model is used, after which the Hausman Test should be conducted.
b) If the value of Chow statistics Fcount<Ftable=H0 is accepted, then use the Pooled Least Square model.
4.4.2 Hausman test (fixed effect vs random effect)
The Hausman test is used to choose between a random-effect or fixed-effect model. The test statistic follows a Chi-Square distribution with k degrees of freedom, where k is the number of independent variables. If the Hausman test statistic is greater than the critical value, the fixed-effect model can be considered appropriate. Conversely, if the test statistic is smaller than the critical value, the random-effect model is appropriate. The formula for the Hausman test is as follows:
W=X2 [K]=(b-)[var(b)-var( ))]-1(b-) (6)
Please use the SI set of units as much as possible. Wherever the application domain uses a different set of units widely, please minimize the use of non-standard units or non-standard symbols for those units.
5.1 Descriptive statistical analysis results
Descriptive statistical results are a description of a research variable (Tables 1-4):
5.1.1 Descriptive statistics of stock prices
The share price is the closing share price at the end of the year. Based on Table 1, the average is IDR. 3,931 with quite large standard deviation and kurtosis values. This means that the distribution of stock price data is not normally distributed. This is because there are differences in share prices between large companies.
5.1.2 Descriptive statistics of PROPER
PROPER is a proxy for green management, a ranking criterion for assessing a company's environmental performance. Based on Table 1, the average PROPER value is 4. This means it is good at handling environmental conservation. Meanwhile, a kurtosis value of 2 means that the data has a normal distribution. Thus, the implementation of green management is very successful in all energy companies or the results are relatively the same.
5.1.3 Descriptive statistics of Return on Assets (ROA)
Return on Assets is a proxy for profitability which is a description of the company's financial performance. Profitability is measured by comparing operating profit to total assets. Based on Table 3, the average ROA value is 13 percent. This shows that the company is able to generate profits of 13 percent of total assets. Meanwhile, a kurtosis value of more than 2 indicates that there is quite a large difference in the profitability value between companies. This means that the data distribution is less than normal.
5.1.4 Descriptive statistics of size of the firms
The size of this research is to measure the size of the company by the total asset value. Table 1 shows the average value of total assets of 30 billion. Meanwhile, the average kurtosis value is 2.9, indicating relatively normal data. This shows that the total asset value of the company is relatively the same or the size of the company is relatively the same.
5.1.5 Descriptive statistics of leverage
Leverage is a variable that measures funding policy. This variable measures the comparison between total debt and total assets. The leverage value in Table 3 is 48 percent. This means that the company's debt composition is 48 percent of total assets. This condition indicates that the company's debt policy aspect is quite good. Meanwhile, the correlation value is almost the same as 2, meaning the data is normally distributed. This shows that the debt policies of energy companies are relatively good.
Table 1. Descriptive statistical of variable
|
|
STOCK_PRICES |
PROPER |
ROA |
SIZE |
DAR |
|
Mean |
3931.544 |
3.867647 |
0.130885 |
30.54098 |
0.485007 |
|
Median |
1553.500 |
4.000000 |
0.075853 |
30.53389 |
0.510590 |
|
Maximum |
39025.00 |
5.000000 |
0.617597 |
32.76456 |
0.961314 |
|
Minimum |
50.00000 |
3.000000 |
-0.098975 |
27.49350 |
0.023752 |
|
Std. Dev. |
6970.069 |
0.731068 |
0.164771 |
1.247414 |
0.218340 |
|
Skewness |
3.027791 |
0.206880 |
1.505079 |
-0.486506 |
0.106118 |
|
Kurtosis |
12.93594 |
1.912375 |
4.461145 |
2.986028 |
2.243369 |
|
Jarque-Bera |
383.6133 |
3.836688 |
31.72199 |
2.683016 |
1.749680 |
|
Probability |
0.000000 |
0.146850 |
0.000000 |
0.261451 |
0.416929 |
|
Sum |
267345.0 |
263.0000 |
8.900159 |
2076.787 |
32.98050 |
|
Sum Sq. Dev. |
3.25E+09 |
35.80882 |
1.819021 |
104.2547 |
3.194034 |
|
Observations |
68 |
68 |
68 |
68 |
68 |
Data processing was carried out on the panel data using three alternative methods, namely pooled least square/common effect, fixed effect, and random effect methods. First, a Chow test was conducted to determine between pooled least square and fixed effect.
5.2 Results of inferential statistical analysis
The results of this analysis are to test the hypothesis of green management variables environmental performance, profitability, company size and leverage on share prices.
Table 2. Chow test result
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Redundant Fixed Effects Tests |
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Equation: Untitled |
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Test cross-section fixed effects |
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Effects Test |
Statistic |
d.f. |
Prob. |
|
|
Cross-section F |
13.136007 |
(16,47) |
0.0000 |
|
|
Cross-section Chi-square |
115.573721 |
16 |
0.0000 |
|
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Cross-section fixed effects test equation: |
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Dependent Variable: STOCK_PRICES |
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Method: Panel Least Squares |
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Date: 07/24/23 Time: 17:30 |
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Sample: 2019 2022 |
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Periods included: 4 |
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Cross-sections included: 17 |
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Total panel (balanced) observations: 68 |
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|
Variable |
Coefficient |
Std. Error |
t-Statistic |
Prob. |
|
C |
-57749.99 |
18569.56 |
-3.109927 |
0.0028 |
|
PROPER |
-1440.487 |
1094.069 |
-1.316633 |
0.1927 |
|
ROA |
22480.43 |
4487.938 |
5.009079 |
0.0000 |
|
SIZE |
2243.677 |
690.3484 |
3.250065 |
0.0019 |
|
DAR |
-8687.720 |
3618.823 |
-2.400703 |
0.0193 |
|
Root MSE |
5155.201 |
R-squared |
0.444798 |
|
|
Mean dependent var |
3931.544 |
Adjusted R-squared |
0.409547 |
|
|
S.D. dependent var |
6970.069 |
S.E. of regression |
5355.867 |
|
|
Akaike info criterion |
20.08046 |
Sum squared resid |
1.81E+09 |
|
|
Schwarz criterion |
20.24366 |
Log-likelihood |
-677.7356 |
|
|
Hannan-Quinn criteria |
20.14512 |
F-statistic |
12.61805 |
|
|
Durbin-Watson stat |
0.485307 |
Prob(F-statistic) |
0.000000 |
|
Table 3 shows that the F test and Chi-square are significant (p-values 0.0000 and 0.0000 less than 5%), hence, H0 was rejected. Based on these results, the fixed-effect model was considered the appropriate model to be used. Subsequently, the Hausman test was carried out.
Table 3. Hausman test results
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Correlated Random Effects - Hausman Test |
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Equation: Untitled |
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Test cross-section random effects |
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Test Summary |
Chi-Sq. Statistic |
Chi-Sq. d.f. |
Prob. |
|
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Cross-section random |
18.632166 |
4 |
0.0009 |
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Cross-section random effects test comparisons: |
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|
Variable |
Fixed |
Random |
Var(Diff.) |
Prob. |
|
PROPER |
4351.165740 |
2150.572384 |
639953.053639 |
0.0059 |
|
ROA |
7789.815193 |
13237.425034 |
6531275.178592 |
0.0330 |
|
SIZE |
3007.036336 |
943.575013 |
2159682.333889 |
0.1603 |
|
DAR |
-5866.554388 |
-6303.573350 |
3610449.517516 |
0.8181 |
|
Correlated Random Effects - Hausman Test |
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Pool: Untitled |
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Test Summary |
Chi-Sq. Statistic |
Chi-Sq. d.f. |
Prob. |
|
|
Cross-section random |
6.862456 |
5 |
0.2311 |
|
The obtained p-value, which was 0.000, is smaller than 0.05, hence H0 is rejected. Based on the results of the F test it can be concluded that the fixed effect is most suitable for use in the panel data analysis.
Based on the values in Table 4, the fixed-effect model uses the principle of ordinary least squares to produce a constant intercept from each data set and accommodate differences in data intercepts. This estimation model type is often called the Least Squares Dummy Variable technique. Thus, the method used in this study uses the panel least squares, which is a fixed-effect model.
Table 4. Fixed effect results
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Dependent Variable: STOCK_PRICES |
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Method: Panel Least Squares |
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Date: 07/24/23 Time: 17:29 |
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Sample: 2019 2022 |
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Periods included: 4 |
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Cross-sections included: 17 |
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Total panel (balanced) observations: 68 |
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Variable |
Coefficient |
Std. Error |
t-Statistic |
Prob. |
|
C |
-102909.3 |
50898.48 |
-2.021855 |
0.0489 |
|
PROPER |
4351.166 |
1327.179 |
3.278507 |
0.0020 |
|
ROA |
7789.815 |
3897.325 |
1.998759 |
0.0514 |
|
SIZE |
3007.036 |
1672.257 |
1.798190 |
0.0786 |
|
DAR |
-5866.554 |
3690.519 |
-1.589629 |
0.1186 |
|
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Effects Specification |
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Cross-section fixed (dummy variables) |
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Root MSE |
2203.836 |
R-squared |
0.898535 |
|
|
Mean dependent var |
3931.544 |
Adjusted R-squared |
0.855358 |
|
|
S.D. dependent var |
6970.069 |
S.E. of regression |
2650.847 |
|
|
Akaike info criterion |
18.85143 |
Sum squared resid |
3.30E+08 |
|
|
Schwarz criterion |
19.53687 |
Log-likelihood |
-619.9487 |
|
|
Hannan-Quinn criteria |
19.12302 |
F-statistic |
20.81059 |
|
|
Durbin-Watson stat |
2.152335 |
Prob(F-statistic) |
0.000000 |
|
5.3 Partial regression testing (t-Test)
This analysis is used to measure the strength of the influence and direction of the relationship between independent variables and dependent variables. The formula for multiple linear regression in general is:
Y=102909+4351.166 X1+7789.815 X2+3007.036 X3-5866.554 X4+e (6)
5.3.1 Testing of variable X1
Based on the results of the data calculation. The results obtained are that the significance value is 0.000. This means that green management has a significant effect on stock prices with a positive relationship direction. Thus, the better the implementation of green management will increase the company's stock price. The Green Management strategy is able to provide a positive signal for stock market players. The regression coefficient of X1 is 4351.166, which means that every 1% increase in X1 will increase Y by 4351.166% assuming other variables are constant, and vice versa.
5.3.2 Testing of variable X2
Based on the calculation results, the results were obtained with a significance value of 0.051. This means that profitability has a significant effect and a positive relationship direction on stock prices. The greater the profit obtained, the more it increases the company's stock price. This indicates the profitability variable as a positive signal for investors. The regression coefficient of X2 is 7789.815, which means that every 1% increase in X2 will decrease Y by 7789.815% assuming other variables are constant, and vice versa.
5.3.3 Testing of variable X3
The results of data calculations using the Eview program obtained results with a significance value of 0.0786. This means that company size has an insignificant positive effect on stock prices. This finding indicates that company size is not used as a source of information in buying shares. The regression coefficient X2 is 3007.036.
5.3.4 Testing of variable X4
Based on the results of data processing, the significance value is 0.1186. This means that Leverage has an insignificant negative effect on stock prices. This means that information on the amount of leverage is not a signal for investors so that it is not used as a basis for buying shares. The regression coefficient X2 is X3 - 5866.554.
5.3.5 Multiple determination coefficients
The value of the multiple determination coefficients can be seen that the R-Square is 0.898535, which means that the dependent variable in the model can explain the independent variable by 90%. While the rest is explained by other variables outside the model that are not studied. While the adjusted R Square value means the R Square value that has been corrected by the standard error value. Adjuster R Square is 0.855 with a standard error value of the regression model of while the standard error value of the regression model is 2.030858 indicated by the label S.E of regression. This standard error value is smaller than the standard deviation value of the independent variable which is assigned with the label "S.D. dependent var" which is 6970.069 which means that the regression model is valid as a dependent variable model.
The results of the panel data analysis conducted using the fixed effect model show that the PROPER variable, serving as a proxy for green management, significantly influenced the stock prices of energy companies listed on the Indonesia Stock Exchange. In line with previous studies, the analysis showed that environmental performance has a significant and positive effect on stock prices [19-27].
Environmental performance or PROPER is the result of the process of implementing green management of energy companies and this information for investors is a signal that the company cares about environmental preservation. Thus, green management is expected to have an impact on the achievement of the company's overall performance. This positive signal will be responded to by stock market players by buying shares of energy companies. This means that the movement of energy company stock prices is positively related to the achievement of environmental performance (green management). This phenomenon is known as Signaling Theory. This condition is very reasonable because energy companies are closely related to environmental issues. Energy companies that care about the environment will have an impact on the achievement of sustainable performance. This condition indicates that the application of signaling theory in financial management has been shown to increase the tendency of investors to allocate their capital [28]. This means that investors in the stock market tend to apply signaling theory in making decisions to buy shares. Investor behavior reflects the information obtained in making decisions.
According to a previous observation, stock price volatility would remain relatively stable even during a pandemic, provided environmental performance is strong [29]. This suggests that initiatives carried out by companies with a focus on environmental sustainability typically send positive signals to investors, showing expectations of strong future performance. Environmental considerations have been observed to play a significant role in shaping the perceptions of investors and this can impact the sustainability of companies. The extent to which companies effectively manage environmental performance proportionally reflects long-term sustainability [30]. Consequently, the capital market often interprets these efforts as positive signals, prompting favorable investor responses to achievements in environmental performance [22, 31]. Meanwhile, research examining environmental performance using PROPER values influences share prices in the energy sector, supported by previous studies [32, 33]. This research is not in line with the results which found that environmental performance does not determine stock prices [34]. These findings indicate that environmental performance, which is an implementation of green management, can have a significant effect on share prices or company value. Likewise, implementing strategies based on green management is also able to determine organizational sustainability or organizational performance [35, 36]. Thus, green management is very important in ensuring the sustainability of a company and is able to provide a positive signal to external parties or investors that the company is aligning the interests of environmental preservation and profits. This information is very useful for investors in making investment decisions in the capital market.
Investors base decisions on the information or signals provided by companies. This is in line with signaling theory, which addresses the information asymmetry between companies and investors. Typically, management communicates information about the environmental achievements of respective organizations, and investors analyze and make informed decisions using these signals. However, it is important to establish that this result is not consistent where investors do not respond to environmental performance or use the factor as a basis for making investment decisions.
According to the results of the fixed effect test, the Return on Assets (ROA) variable significantly impacted stock prices, in line with the observations of the previous study [7]. This suggests that profitability plays a crucial role in investors' decisions when purchasing shares in the energy sector. However, factors such as the sizes of companies and leverage are observed to not significantly influence stock prices. This result is consistent with the results where it was stated that information regarding these variables did not serve as a signal for investors. Rather, investors focus solely on environmental performance and profitability when making investment decisions in the energy sector capital market. This finding encourages the government to create policies supporting policies and operations in improving environmental performance, ultimately improving sustainable financial performance [37]. Thus, the implementation of green management has an impact on improving sustainable performance [38]. The results of this study indicate that the implementation of green management has an impact on improving financial performance, sustainable performance, and increasing company value through rising share prices.
In conclusion, based on the results of the panel data analysis, it can be seen that green management had a significant effect on the stock prices of companies in the energy sector listed on the Indonesia Stock Exchange. The results from this study showed that information about environmental management served as a positive signal for investors regarding the prospects of companies. In addition, profitability was also found to significantly influence stock prices. This simply implies that profitability as a control variable influences the impact of environmental performance on stock prices. However, company size and leverage, which were also control variables, did not significantly contribute to the model. This result shows that the government's policy on environmental performance assessment, conducted by the Ministry of Environment, is highly credible to capital market players.
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