FINAL EXAM
Impact of Environmental, Social, and Governance (ESG) Disclosure on the Profitability:
Insight from Tobacco Companies Listed on Indonesian Stock Exchange (IDX) 2021- 2022 Period
MM5005-Economic and Business Landscape Analysis
Lecturer:
Ir. Dzikri Firmansyah Hakam, S.T., Pg.Dip., M.Sc., Ph.D.
By:
Andrea Rhegina Putri 29122315 (Young Professional 68 A)
MASTER OF BUSINESS ADMINISTRATION SCHOOL OF BUSINESS AND MANAGEMENT
BANDUNG INSTITUTE OF TECHNOLOGY
2023
Abstract
The environmental, social, and governance (ESG) disclosure is the practice of companiesand organizations sharing information and data about their Environmental, Social, and Governance (ESG) practices and performance in a transparent and systematic approach. It entails delivering detailed reports, metrics, and insights into how the organization addresses and manages various aspects of sustainability and responsible business. ESG disclosure can attract the interest of investors who are concerned about sustainability issues and social responsibility. It can also enhance the company's image in the eyes of customers, suppliers, and the general public. In simpler terms, tobacco companies are not very focused on disclosing their ESG efforts. Nevertheless, based on data, these companies are among the top waste producers, with cigarette butts being a significant environmental concern.The purpose of this study is to determine the impact of environmental, social, and governance on the profitability in tobacco companies listed on the Indonesia Stock Exchange between 2021 and 2022. The population for this study is the tobacco companies listed on the Indonesia Stock Exchange from 2021 to 2022. Purposive sampling is used in this study and obtained eight data samples. In this study, descriptive statistical analysis and panel data analysis were used as analysis techniques.
Keywords
Environmental, Social, and Governance (ESG) Disclosure, Profitability
1. Introduction
The world of finance and investment has undergone a transformation, particularly in its practical approaches. The practice referred to is investment with a focus on sustainability aspects, commonly known as sustainable investing.
Sustainable investing encompasses a variety of practices in which investors seek financial returns while also promoting long-term environmental or social value (Stobierski 2022). The importance of CSR and sustainability reporting is underscored by international regulatory bodies' efforts to harmonize and develop comprehensive global guidelines for sustainability disclosure standards (Ghardallou and Alessa 2022). The recent global emphasis on social responsibility is nothing new. Many countries require companies to disclose information about their environmental, social, and employee impact, as well as their diversity policies (Gutiérrez-Ponce, Chamizo-González, and Arimany-Serrat 2022).
According to Rao et al. (2023), in recent years, environmental, social, and governance (ESG) practices have grown in importance. To address global concerns, corporations have been actively incorporating ESG principles into their operations. ESG, when properly combined, can be used to create a score that can be used to assess the sustainability of companies and investments (Cesarone, Martino, and Carleo 2022). ESG can add value in a variety of ways, one of which is with a strong value proposition, ESG can bring companies to new markets and expand existing markets, boosting the company's level of profitability in running its business (Henisz, Koller, and Nuttall 2019). The combination of comprehensive ESG disclosure and smart use of energy economics can help businesses make more sustainable business decisions, reduce their environmental impact, and improve their long-term performance. It also contributes to the development of a more sustainable energy system and helps to achieve global goals related to climate change and environmental sustainability.
The sustainability aspect has also been addressed by Indonesia through the issuance of the Sustainable Finance Roadmap Phase II by the Financial Services Authority (OJK). One of the objectives of this strategic plan is to prioritize the implementation of Environmental, Social, and Governance (ESG) aspects into all development activities, with a focus on creating a comprehensive sustainable financial ecosystem (Otoritas Jasa Keuangan 2021). There are some companies in industries that are not typically associated with ESG (Environmental, Social, and Governance) concepts, and yet they exhibit strong financial performance and good corporate governance. One example of such a company is a tobacco company (Putra and Adrianto 2020). Tobacco companies are an industry that generates a significant amount of waste in the environment. According to data reported by Annur (2023) on Databoks website, cigarette butts rank second among the most abundant types of waste, reaching 1.13 million units of litter.
Figure 1. Most Types of Garbage Found on Global Coasts in 2021 Source: Annur (2023) on Databoks website
According to the data presented above, ESG disclosure is important for tobacco companies because it allows them to communicate information about their efforts to reduce their environmental footprint. This includes information on waste management practices, resource utilization, and initiatives to reduce pollution and deforestation caused by tobacco production. Furthermore, companies that disclose ESG information and work to reduce their negative environmental impact may attract the interest of more stakeholders, build trust, and improve their corporate image.
International Association for Public Participation (2022) stated that the slow progress of Indonesia in implementing sustainable concepts can be attributed to various challenges that need to be addressed. These challenges include suboptimal understanding, insufficient resources, and the high cost of consultation for managing ESG aspects.
With the disclosure of ESG information and regulations from regulatory bodies, it is expected that public understanding of sustainable investment will continue to grow. From a company's perspective, the disclosure of ESG information can attract investors who are interested in sustainability aspects to invest in the company. ESG disclosure can also support the company's corporate identity, making it more favorable. Improved corporate image and reputation offer opportunities to attract consumers, leading to increased brand loyalty for the company itself.
According to Xu and Liu (2023), ESG disclosure has a positive effect on profitability. However, Lin et al. (2019) discovered that ESG disclosure has no relationship with profitability. Based on the inconsistency of the results of previous studies and the phenomenon that occurs, this study was conducted since there are some companies that are still lacking in disclosing ESG disclosure. Whereas, companies are required to disclose ESG disclosures, so that the asymmetric information does not occur and can be a strategy for companies to increase added values. As a result, this study should be repeated to investigate the factors that influence profitability.
1.1 Objectives
This study has the following objectives:
1. To find out the effect of Environmental, Social, and Governance (ESG) disclosure on the level of profitability of tobacco companies listed on the Indonesian Stock Exchange (IDX) for the 2021-2022 period
2. To find out the effect of Environmental disclosure on the level of profitability of tobacco companies listed on the Indonesian Stock Exchange (IDX) for the 2021-2022 period
3. To find out the effect of Social disclosure on the level of profitability of tobacco companies listed on the Indonesian Stock Exchange (IDX) for the 2021-2022 period
4. To find out the effect of Governance disclosure on the level of profitability of tobacco companies listed on the Indonesian Stock Exchange (IDX) for the 2021-2022 period
2. Literature Review
2.1 Stakeholder TheoryAccording to Donaldson and Preston (1995) stakeholder theory considers all internal and external relationships for organizations and manages all of these relationships that drive the organization to survive, because survival is the most important g of any organization. The descriptive stakeholder theory is concerned with how the corporation responds to various stakeholders. According to instrumental stakeholder theory, if a corporation manages its stakeholder relationships properly, it can improve its financial performance over time. The descriptive stakeholder theory is
concerned with how the corporation responds to various stakeholders. According to instrumental stakeholder theory, if a corporation manages its stakeholder relationships correctly, it can improve its financial performance over time.
As a result, sustainability practices can be motivated by self-interest in order to increase profit and shareholder value.
For example, with improved sustainability performance, a company may be able to attract more resources in order to increase market opportunities and pricing premiums, as well as attract employees. Managing stakeholder relationships may therefore result in advantages in competition (Taha, Al-Omush, and Al-Nimer 2023).
2.2 Profitability
According to Ren, Zeng, and Zhao (2023), the profitability ratio reflects the firm's profitability and is calculated as the ratio of net profit to total assets. A higher indicator indicates that the firm is doing well in terms of increasing revenue and saving money, both of which contribute to the firm's ESG performance. The profitability ratio shows the company capability to generate profits. In this study, the profitability ratio is calculated using the Return on Assets ratio (ROA).
2.3 ESG Disclosure
ESG refers to a broad set of environmental, social, and corporate governance considerations that may have an impact on a company's ability to execute its business strategy and create value over time. While ESG factors are sometimes referred to as non-financial, how a company manages them has certainly financial consequences (NASDAQ 2019).
Companies are expected to focus not only on profit but also on environmental and social sustainability. The ESG disclosure indicators used in this study are listed in the table below.
Figure 2. Indicator points for assessing ESG disclosure Source: NASDAQ (2019)
According to Baran et al. (2022), the environmental disclosure ratio is calculated based on 10 indicators related to climate change and carbon emissions, use of natural resources, energy and water management, pollution and waste, and ecodesign and innovation. In this research, the specific formula for calculating the environmental disclosure ratio is as follows:
Information:
ENV : Environmental Disclosure Ratio
Σ Item ENV : Total score for Environmental Disclosure Total ENV : Maximum possible score
This formula measures the extent to which a company discloses information related to environmental practices and sustainability based on the given indicators, expressed as a percentage of the maximum achievable score.
ROA = !"# %&'()# *"('&" +,-
+'#,. /00"# X 100%
ENV = 1 2#"3 4!5
+'#,. 4!5 X 100%
In this research, the social disclosure is based on 10 indicators related to workforce health and safety, diversity, and training, customer and product responsibility, and community relations and charitable activities. The social disclosure ratio is calculated using the formula below:
Information:
SOC : Social Disclosure Ratio
Σ Item SOC : Total score for Social Disclosure Total SOC : Maximum possible score
This formula evaluates the extent to which a company discloses information related to social aspects and responsibilities based on the specified indicators. The result is expressed as a percentage of the maximum attainable score, indicating the level of social disclosure by the company.
In this research, the governance disclosure is based on 10 indicators related to shareholder rights, composition of boards of directors (independence and diversity), management compensation policy, and fraud and bribery. The formula used to calculate the governance disclosure ratio is as follows:
Information:
GOV : Governance Disclosure Ratio
Σ Item GOV : Total score for Governance Disclosure Total GOV : Maximum possible score
This formula assesses the level of disclosure by a company concerning its governance practices and adherence to ethical standards based on the given indicators. The result is presented as a percentage of the maximum achievable score, indicating the extent of governance disclosure by the company.
A study by Xu and Liu (2023) and Gholami, Sands, and Rahman (2022) showed that the ESG disclosure has a positive effect on profitability.
H1: ESG Disclosure has positive effect on Profitability
3. Methodology
3.1 Data CollectionThe data is from sustainability report and financial statement by tobacco companies for 2021-2022 which were retrieved from IDX website and the company's official website.
3.2 Research Methods
In this study, the type of study used is A descriptive method is a research method that attempts to describe a current phenomenon, occurrence, or event. The descriptive research method is used to gather information about the current state of affairs. The descriptive method's objective is to find a detailed explanation and description of the research object in a systematic way (Creswell 2012). This study uses quantitative research methods. The definition of quantitative research is a method for testing objective theories by examining the relationship between variables. These variables can then be measured, typically with instruments, and the resulting numbered data can be analyzed statistically (Creswell 2009).This study uses a case study strategy. Case studies focus on gathering information about a particular object that has been found. This study's research object is a group of tobacco companies listed on the Indonesia Stock Exchange for the period 2021-2022. Purposive sampling will be used in this study, so the following criteria will be used:
SOC = 1 2#"3 678
+'#,. 678 X 100%
GOV = 1 2#"3 975
+'#,. 975 X 100%
1. Tobacco companies listed on the Indonesia Stock Exchange (IDX) for the 2021-2022 period
2. Tobacco companies listed on the Indonesia Stock Exchange (IDX) consistently present sustainability reports for the 2021-2022 period
The research background used is the non-contrived setting. The analysis technique in this study uses panel data which combines time series with cross sectional data. The panel data analysis method equations used in this study as follows:
Besides, this study conducted classical and hypothesis tests, which is simultaneous test (F-Test), Determinant Coefficient Test (R2), and Partial Test (T-Test).
4. Discussion and Analysis
4.1 Numerical Results4.1.1 Descriptive Statistics
Table 1. Results of Descriptive Statistical Tests
Source: Processed Data (2023)
According to the results of descriptive statistical table, which shows the value of each study variable, it shows that:
1. The lowest profitability (ROA) value is 0,03, while the highest ROA value is 0,13 in the descriptive statistics results table. Based on the average ROA of 0,08 and the standard deviation of 0,04, the sample data do not fluctuate with the tendency to group.
2. The lowest environmental disclosure (ENV) value is 0,10 while the highest ENV value is 0,80 in the descriptive statistics results table. Based on the average ENV of 0,53 and the standard deviation of 0,29, the sample data do not fluctuate with the tendency to group.
3. The lowest social disclosure (SOC) value is 0,30, while the highest SOC value is 0,80 in the descriptive statistics results table. Based on the average SOC of 0,59 and the standard deviation of 0,22, the sample data do not fluctuate with the tendency to group.
4. The lowest governance disclosure (GOV) value is 0,03, while the highest GOV value is 0,08 in the descriptive statistics results table. Based on the average GOV of 0,08 and the standard deviation of 0,04, the sample data do not fluctuate with the tendency to group.
4.1.2 Classical Assumption Tests 1. Multicollinearity Test
The multicollinearity test determines whether or not the regression model has a perfect correlation between the independent variables. A regression model is said to have multicollinearity when the correlation coefficient is greater than 0,9, but if it is less than 0,9, there is no problem with multicollinearity.
Table 2. Multicollinearity Test
Source: Processed Data by Eviews 12 (2023)
X1 X2 X3
X1 1.000000 0.218578 0.215101 X2 0.218578 1.000000 -0.207729 X3 0.215101 -0.207729 1.000000
ROA ENV SOC GOV
MAXIMUM 0,13 0,80 0,80 0,80
MINIMUM 0,03 0,10 0,30 0,03
MEAN 0,08 0,53 0,59 0,08
STANDARD DEVIATION 0,04 0,29 0,22 0,04
N 8 8 8 8
Y = α + β:X:+ β;X;+ β<X<+ β<X<+ e
Based on the results, the multicollinearity test reveals a value smaller than 0,9 indicating that there is no multicollinearity.
2. Heteroscedasticity Test
In a regression model, the heteroscedasticity test is used to determine whether or not there is a variance inequality between the residuals of one observation and the residuals of another observation. Heteroscedasticity appears to exist in a regression model if the correlation coefficient is less than 0,05 but not if it is greater than 0,05.
Table 3. Heteroscedasticity Test
Source: Processed Data by Eviews 12 (2023)
According to the test results, the regression model has no heteroskedasticity because the probability value is 0,2854 >
0,05.
4.1.3 Data Panel Regression Model Selection 1. Chow Test
The Chow test is used to determine whether to estimate panel data using a fixed effect or a common effect model. If the F cross-section probability in the Chow test is greater than 0,05, then H0 is accepted, indicating that the common effect model (CEM) is preferable. H0 is rejected if the F cross-section probability is less than 0,05, indicating that the fixed effect model (FEM) is more appropriate.
Table 4. Chow Test Results
Source: Processed Data by Eviews 12 (2023)
Since the probability value of the chi-square cross-section is 0,0000 < 0,05, H0 is rejected, and the fixed effect model (FEM) is chosen in the Chow test.
2. Hausman Test
The Hausman test is used to determine whether to use the fixed effect or random effect model. If the chi-square probability is greater than 0,05, the Hausman test accepts H0, indicating that the random effect model (REM) is more appropriate to use. If the chi-square probability is less than 0,05, H0 is rejected, indicating that the fixed effect model (FEM) is preferable.
Table 5. Hausman Test Results
Source: Processed Data by Eviews 12 (2023) Heteroskedasticity Test: Breusch-Pagan-Godfrey
Null hypothesis: Homoskedasticity
F-statistic 1.198284 Prob. F(3,4) 0.4171
Obs*R-squared 3.786620 Prob. Chi-Square(3) 0.2854 Scaled explained SS 0.669606 Prob. Chi-Square(3) 0.8803
Test Equation:
Dependent Variable: RESID^2 Method: Least Squares Date: 07/19/23 Time: 19:07 Sample: 1 8
Included observations: 8
Variable Coefficient Std. Error t-Statistic Prob.
C -0.396841 0.272463 -1.456493 0.2190
SOCIAL 0.010830 0.111559 0.097082 0.9273
GOVERNANCE 0.527183 0.376627 1.399751 0.2342 PROFITABILITY 0.812884 0.590390 1.376859 0.2406 R-squared 0.473327 Mean dependent var 0.049191 Adjusted R-squared 0.078323 S.D. dependent var 0.062548 S.E. of regression 0.060048 Akaike info criterion -2.480484 Sum squared resid 0.014423 Schwarz criterion -2.440764 Log likelihood 13.92194 Hannan-Quinn criter. -2.748385 F-statistic 1.198284 Durbin-Watson stat 1.646275 Prob(F-statistic) 0.417095
Redundant Fixed Effects Tests Equation: MODEL_FEM Test cross-section fixed effects
Effects Test Statistic d.f. Prob.
Cross-section F 95.318024 (3,1) 0.0751
Cross-section Chi-square 45.274577 3 0.0000
Cross-section fixed effects test equation:
Dependent Variable: Y Method: Panel Least Squares Date: 07/19/23 Time: 18:25 Sample: 2021 2022
Periods included: 2 Cross-sections included: 4
Total panel (balanced) observations: 8
Variable Coefficient Std. Error t-Statistic Prob.
C 1.148238 1.423200 0.806800 0.4650
X1 0.672426 0.582725 1.153934 0.3128
X2 -1.044522 1.967292 -0.530944 0.6236
X3 -3.478227 3.083876 -1.127875 0.3224
R-squared 0.338608 Mean dependent var 0.525000 Adjusted R-squared -0.157437 S.D. dependent var 0.291548 S.E. of regression 0.313659 Akaike info criterion 0.825834 Sum squared resid 0.393528 Schwarz criterion 0.865554 Log likelihood 0.696665 Hannan-Quinn criter. 0.557933 F-statistic 0.682616 Durbin-Watson stat 0.651483 Prob(F-statistic) 0.607487
Correlated Random Effects - Hausman Test Equation: MODEL_REM
Test cross-section random effects
Test Summary Chi-Sq. Statistic Chi-Sq. d.f. Prob.
Cross-section random 285.954072 3 0.0000
Cross-section random effects test comparisons:
Variable Fixed Random Var(Diff.) Prob.
X1 -0.726432 0.672426 0.044610 0.0000
X2 1.161220 -1.044522 0.139218 0.0000
X3 -5.978480 -3.478227 2.789144 0.1344
Cross-section random effects test equation:
Dependent Variable: Y Method: Panel Least Squares Date: 07/19/23 Time: 18:27 Sample: 2021 2022
Periods included: 2 Cross-sections included: 4
Total panel (balanced) observations: 8
Variable Coefficient Std. Error t-Statistic Prob.
C 0.595482 0.208638 2.854146 0.2145
X1 -0.726432 0.222133 -3.270258 0.1889
X2 1.161220 0.439508 2.642093 0.2303
X3 -5.978480 1.709302 -3.497615 0.1773
Effects Specification Cross-section fixed (dummy variables)
R-squared 0.997695 Mean dependent var 0.525000 Adjusted R-squared 0.983866 S.D. dependent var 0.291548 S.E. of regression 0.037032 Akaike info criterion -4.083488 Sum squared resid 0.001371 Schwarz criterion -4.013977 Log likelihood 23.33395 Hannan-Quinn criter. -4.552315 F-statistic 72.14393 Durbin-Watson stat 3.200000 Prob(F-statistic) 0.089879
As shown, the probability value of a random cross-section is 0,0029 < 0,05, so H0 is rejected, and the fixed effect model (FEM) is chosen in the Hausman test
4.1.4 Results of Panel Data Regression Analysis
Table 6. Fixed Effect Model Results
Source: Processed Data by Eviews 12 (2023)
Y = 0,595482 – 0,726432 X1 + 1,161220 X2 – 5,978480 X3 + e Information:
Y : Profitability
X1 : Environmental Disclosure X2 : Social Disclosure
X3 : Governance Disclosure e : Error term
4.1.5 Coefficient of Determination Test
Table 7. Coefficient of Determination Test (R2) Results
Source: Processed Data by Eviews 12 (2023)
Table 7 shows that adjusted R-squared was 0,983866, which meant that the independent variables were able to explain the profitability by 98,38% and the remaining 1,62% was explained by other factors outside the study.
4.1.6 Simultaneous Hypothesis Testing (F Test)
Based on the probability value (f-statistic) of 0,089879 > 0,05, H1 is rejected and H0 is accepted. Environmental, Social, and Governance Disclosure the independent variables of this study, simultaneously not affected the dependent variable, namely profitability on tobacco companies listed on the IDX for the 2021-2022 period.
Dependent Variable: Y Method: Panel Least Squares Date: 07/19/23 Time: 18:24 Sample: 2021 2022 Periods included: 2 Cross-sections included: 4
Total panel (balanced) observations: 8
Variable Coefficient Std. Error t-Statistic Prob.
C 0.595482 0.208638 2.854146 0.2145
X1 -0.726432 0.222133 -3.270258 0.1889
X2 1.161220 0.439508 2.642093 0.2303
X3 -5.978480 1.709302 -3.497615 0.1773
Effects Specification Cross-section fixed (dummy variables)
R-squared 0.997695 Mean dependent var 0.525000 Adjusted R-squared 0.983866 S.D. dependent var 0.291548 S.E. of regression 0.037032 Akaike info criterion -4.083488 Sum squared resid 0.001371 Schwarz criterion -4.013977 Log likelihood 23.33395 Hannan-Quinn criter. -4.552315 F-statistic 72.14393 Durbin-Watson stat 3.200000 Prob(F-statistic) 0.089879
Dependent Variable: Y Method: Panel Least Squares Date: 07/19/23 Time: 18:24 Sample: 2021 2022 Periods included: 2 Cross-sections included: 4
Total panel (balanced) observations: 8
Variable Coefficient Std. Error t-Statistic Prob.
C 0.595482 0.208638 2.854146 0.2145
X1 -0.726432 0.222133 -3.270258 0.1889
X2 1.161220 0.439508 2.642093 0.2303
X3 -5.978480 1.709302 -3.497615 0.1773
Effects Specification Cross-section fixed (dummy variables)
R-squared 0.997695 Mean dependent var 0.525000 Adjusted R-squared 0.983866 S.D. dependent var 0.291548 S.E. of regression 0.037032 Akaike info criterion -4.083488 Sum squared resid 0.001371 Schwarz criterion -4.013977 Log likelihood 23.33395 Hannan-Quinn criter. -4.552315 F-statistic 72.14393 Durbin-Watson stat 3.200000 Prob(F-statistic) 0.089879
4.1.7 Partial Hypothesis Testing (T Test)
Table 8. Partial Hypothesis Testing (T Test) Results
Source: Processed Data by Eviews 12 (2023) Partial hypothesis testing results table shows that:
1. Environmental disclosure has a probability value of 0,1889 > 0,05 and a coefficient of -0,726432, this indicates that there is a negative relationship with the company's profitability, but it is not statistically significant.
2. Social disclosure has a probability value of 0,2303 > 0,05 and a coefficient of 1,161220, this indicates that there is a positive relationship with the company's profitability, but it is not statistically significant.
3. Governance disclosure has a probability value of 0,1773 > 0,05 and a coefficient value of -5,978480, this indicates that there is a negative relationship with the company's profitability, but it is not statistically significant.
5. Validation, Conclusions and Recommendation
5.1 ValidationBased on the data above, the environmental, social, and governance disclosures each have a probability value bigger than the significant level of 0,05. Indicating that environmental, social, and governance (ESG) disclosure has no effect on profitability. The results are not in line with the hypothesis built by previous researches. Although, this research are in line with Du and Vieira (2012) who stated that because of the high costs associated with social and environmental activities, there is a perceived negative relationship between corporate social responsibility and company performance. These expenses have the potential to decrease the company's competitive advantage and profitability. Furthermore, some empirical studies have provided evidence of negative results, emphasizing that investments in CSR incur additional costs and expenses, which have a negative impact on firm performance (Lin et al. 2019; Hirigoyen, and Poulain-Rehm 2015; Makni, Francoeur, and Bellavance 2009).
5.2 Conclusions
The result and discussion of this study, lead the following conclusions.
1. The independent variables, namely environmental, social, and governance disclosure simultaneously not affected on profitability of tobacco companies listed on the Indonesia Stock Exchange (IDX) in 2021-2022.
2. Environmental disclosure has a negative relationship with the profitability of tobacco companies listed on the Indonesia Stock Exchange (IDX) in 2021-2022, but it is not statistically significant.
3. Social disclosure has a positive relationship with the profitability of tobacco companies listed on the Indonesia Stock Exchange (IDX) in 2021-2022, but it is not statistically significant.
4. Governance disclosure has a negative relationship with the profitability of tobacco companies listed on the Indonesia Stock Exchange (IDX) in 2021-2022, but it is not statistically significant.
5.3 Recommendation
Companies from any sector should engage in ESG disclosure. ESG disclosure is a practice that is increasingly recognized and expected by various stakeholders, including investors, customers, employees, government, society, and financial institutions. There are several benefits for companies that undertake ESG disclosure:
1. ESG disclosure allows companies to be more transparent about how they manage environmental, social, and governance issues in their operations. This fosters trust and accountability among stakeholders.
2. Positive ESG disclosure can improve the company's reputation in the eyes of customers, suppliers, and the general public.
3. Investors are increasingly interested in companies that consider ESG aspects in their businesses.
4. ESG disclosure helps companies identify and manage environmental and social risks more effectively.
5. ESG disclosure can assist companies in complying with government regulations and policies related to sustainability. It also reaffirms the company's responsibility in managing its impact on the environment and society.
Dependent Variable: Y Method: Panel Least Squares Date: 07/19/23 Time: 18:24 Sample: 2021 2022 Periods included: 2 Cross-sections included: 4
Total panel (balanced) observations: 8
Variable Coefficient Std. Error t-Statistic Prob.
C 0.595482 0.208638 2.854146 0.2145
X1 -0.726432 0.222133 -3.270258 0.1889
X2 1.161220 0.439508 2.642093 0.2303
X3 -5.978480 1.709302 -3.497615 0.1773
Effects Specification Cross-section fixed (dummy variables)
R-squared 0.997695 Mean dependent var 0.525000 Adjusted R-squared 0.983866 S.D. dependent var 0.291548 S.E. of regression 0.037032 Akaike info criterion -4.083488 Sum squared resid 0.001371 Schwarz criterion -4.013977 Log likelihood 23.33395 Hannan-Quinn criter. -4.552315 F-statistic 72.14393 Durbin-Watson stat 3.200000 Prob(F-statistic) 0.089879
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