Redefining Commerce and Management: New Paradigms for the Digital Age (Volume 1)

By Dr. Gurupada Das

"Redefining Commerce and Management: New Paradigms for the Digital Age" is an edited volume curated by Dr. Gurupada Das, a distinguished Assistant Professor at Trivenidevi Bhalotia College, Raniganj, West Bengal. This book compiles 21 insightful chapters that explore the profound changes and emerging trends in commerce and management brought about by digital advancements. It serves as a comprehensive resource for academics, practitioners, and students keen on understanding the intersection of digital technology and business. This book provides a thorough examination of the changing paradigms in commerce and management due to digital advancements. Each chapter offers unique insights and practical strategies, making this book an essential resource for understanding the opportunities and challenges of the digital age. It serves as a vital resource for understanding the opportunities and challenges in the digital age, making it essential reading for those involved in business and academia.

• Language: English
• Publisher: Authors Click Publishing
• Release date: Jun 14, 2024
• ISBN: 9788119368525

Book preview

CHAPTER - 1

The Effect of Environmental,

Social and Governance Disclosure

Level on the Cost of Equity Capital:

An Empirical Study on Indian Scenario

By

Dr. Chiranjit Ghosh

Assistant Professor

Department of Commerce

Saheed Anurup Chandra Mahavidyalaya

[e-mail]

––––––––

Abstract

Purpose: This research work is conducted from the curiosity what is the effect of Environmental-Social-Governance disclosure (ESG) on the cost of equity capital (COE). Here ESG disclosure level is viewed from two different aspects – current year aspect and lag years aspect. Hence the main aim of this empirical research study is to test what is the effect of current year as well as lag years’ ESG disclosure level on the COE of a firm.

Design/Methodology/Approach: For this empirical study we have made a sample of top 50 Indian companies, listed in NSE. We measure ESG disclosure level through the ESG disclosure index for the study periods 2015-2016 to 2019-20. we have developed and run two regression models to know the effect of ESG disclosure level on the COE.

Findings: The current year as well as lag years’ ESG disclosure level has a negative and statistically significant effect on the current year’s COE. And disclosure level for the lag years has more influence than the current year disclosure level relating to the ESG information. 

Originality/Value: This is the first empirical work that analyses the influence of current year as well as lag years’ ESG disclosure level on the current year’s COE from the view point of Indian companies.

Keywords: Disclosure, ESG disclosure, Cost of Equity Capital, ESG disclosure index, Capital Asset Pricing Model.

1) INTRODUCTION:

We know that a business concern is considered as a social unit because it exists and operates in the society. The prior studies (Carroll,1999; McWilliams & Siegel,2001) argued that business organization should operate their operation in a most lucid, transparent and ethical way so that they also return back to the society where they exist and operate. But businesses often only focus to obtain maximum benefit from the society and environment without inspecting the impact of their activities on society and environment. Moreover, a group of researchers (Newton,2009; Khadjavi,2013; Habib,2017) visualized different disastrous environmental sequels, occurring due to irresponsible social behavior of business organizations. At present environmental issues has turned into a biggest problematic global issue which have to resolve. Moreover the argument of Izzo et al.(2012) acts as the influence like ghee into fire. They argued that the rapid propagation of media in respect of environmental issues, climate change and global warming, business concerns are pressurized to publish their activities in more ethical way regarding to environmental issues.

Hence now a days corporate houses also focus to report environmental, social and governance related information in addition to financial information in order to fulfill the demand of investors or potential investors about the sustainability (Baalouch et.al.,2019). According to the International Financial Reporting Standard (IFRS) the main motive of reporting financial information is to convey how much a business organization is financially strong. This financial strength is considered as a part of sustainability in long run. Businesses, having a harmful impact on environment, can’t survive in long run irrespective of how much they are financially strong. Hence in his study Gray (2006) argued that the non-financial disclosures are also play a crucial role in measuring sustainability. In this context environmental, social & governance (commonly known as ESG) related information are fallen under the category of Non-Financial Disclosure as this information are not measurable in monetary term. Disclosure of ESG related information not only helps to build a bridge between the management and stakeholders (Fuchs et.al.,2011) but also gives valuable information regarding the business activities, policies and sustainability (Virtania and Siregar,2017). Moreover, the Global Reporting Initiative (GRI) gives evidence in support of the concept that with availability of CSR information external related parties are able to realize about the sustainability of firm and firm’s true value.

Some previous group of researchers like Asemah et al.,2013 and Kang & Hustvedt,2014 opinioned through their studies that by contributing in society and involving in social activates firms are able to build a mutual interaction and confidence with the society where they are operate and that mutual confidence acts as the foundation of good reputation and loyalty. Moreover the available information manifests that peoples are ready to pay more for socially responsible products (Gamerschlag et al.,2011; Smith,2003). Because good socially responsible products come from good socially responsible operation and good socially responsible operation come from ethical behavior of employees, management process. Therefore this will leads to act from the perspective of corporate social responsibilities (Menz,2010) and this will also eventually influence in making firm’s reputation (Cacioppe et al.,2008). 

In other words, with a continuous communication among human, environment and natural resources, corporations are not only able to maintain a sustainable growth but also enjoy a competitive advantages like lower cost of equity capital (Healy & Palepu,2001). The authors also opinioned that publication of more information can mitigate agency problem by minimizing information asymmetry thereby diminishing the uncertainty and risk which consequently leads to lower equity capital cost. Alternatively, it can be said that in the availability or presence of adequate information investors are capable to differentiate good investments from bad ones that raises the demand of respective securities in the stock market and this higher demand indicates higher liquidity in the market and decreases the cost of equity. 

By forward moving of the boundary of financial disclosure our study carries out a systematic inquiry to add different dimension in the literature by focusing a light on the non-financial disclosure specifically on ESG issues. Because environmental disclosure has also much broader scope, it is associated with firm’s long term development, growth strategies and performances sustainability (Dhaliwal et al.,2011). This study is unlike the study, conducted by Richardson and Walker (2001). They analyze the impact of social as well as financial disclosure on the equity cost in the perspective of Canadian firms. Where Dhaliwal et al. (2011) conduct an experiment on the relationship between non-financial disclosure relating to the CSR issues and cost of equity capital in respect of United States’ firms. But here we confine our research work within the Indian firms. India differs notably than U.S. and Canada in respect of rules and regulations regarding making non-financial disclosure. In India it is still in the nature of willful as there is lack of strict or mandatory policies regarding non-financial disclosure. If we consider the strict policies and related litigation risk, we can observe different relations between disclosure and cost of equity capital in these three countries (Dhaliwal et al.,2011). With such regard this study undertakes the initiative to explore the influence of voluntary ESG information on the cost of equity capital from the perspective of Indian companies.

For our study we select top 50 Indian companies, listed in National Stock Exchange (NSE). We also limit the time frame of my study within the 5 years – from 2015-26 to 2019-20. Moreover we measure the ESG disclosure level through the self-generated ESG disclosure index based on previous studies (Plumlee et al.,2008; Clarkson et al.,2008&2013) by the content analysis method of annual report of the sample companies. A multiple theoretical framework: Agency Theory, Legitimacy Theory, Signaling Theory, Stakeholder Theory is considered because ESG reporting is so elaborate and complex phenomenon that is not possible to explain with the help of a single theory (Tagesson et al.,2009; Gray & Handley,2015). The current year as well as lag years’ ESG disclosure level has a negative and statistically significant effect on the current year’s COE. And disclosure level for the lag years has more influence than the current year disclosure level relating to the ESG information.   

The residual portion of this paper is framed as follows. In the next section we survey the pertinent theories and empirical literatures to develop or establish our hypothesis. The 3rd segment associates with the research methodology. The section followed by the 3rd section, present the empirical findings of our study. And finally the last section cover up with discussion and conclusion. 

––––––––

2) LITERTURE REVIEW AND HYPOTHESIS DEVELOPMENT:

Despite the absent of any mandatory regulation regarding the environmental and social activities and disclosure, firms come with these activities and disclose these activities in an increasing attitude. In his study Perez (2015) argued that by making availability of information relating to different activities regarding social welfare, environmental protection, governance policies towards the development of environment firms are able to establish and maintain a good corporate image and reputation by legitimizing its conduct through interaction with its stakeholders.

The argument of Perez (2015) can be explained by signaling theory. Firms having higher social, environmental activities and good governance are willing to publish more information to provide a signal to their shareholders, stakeholders and other related parties about their superior performance which not only improve the transparency level but also reduce business uncertainties and also enhance the faith in respect of long term performance and risk management via reducing information asymmetry (Connelly,2011; Dhaliwal,2011). Alternatively, this should enhance firm’s renown, boost brand loyalty and make stakeholders to realize firm’s real value (Clarkson,2008). Hence this theory states that better social, environmental performance and good corporate governance have a positive effect on the firm’s value (Voerman,2018) and hence reduce the cost of equity capital.

On the other hand, the assumption of legitimacy theory also justifies the assumption of signaling theory. According to legitimacy theory business organizations should operate their operation within legitimate of social as well as environment otherwise they can’t subsist in long run. A group of researchers like Lanis & Richardson, 2012; Fernando & Lawrence, 2014; Hummel & Schlick, 2016 argued that firms with comparatively low performer, more harmful towards environment hide their bad performance to distract or mislead the investors and try to earn a good reputation. Often firms disclose wrong information or overstated information or manipulated information to make a legitimacy image about their business conduct to the investors and other stakeholders by pulling down a curtain to their poor performances (Voerman,2018; Cho & Patten, 2007).

The fundamental supposition of agency theory is associated with the human nature. According to his nature, human is more concern to his self-interest. Human always endeavor to maximize their self-interest whenever they get opportunities. That leads to a conflict between the principal (shareholder/investors) and agent (management) (Habib,2017) as business executives or management are appointed as the representatives of the shareholders or investors in operating business operations. Hence it is expected to perform their duties for the best interests of the principal without regard for self-interest. But in practice management may not entirely perform in the best interests of the principal (Watson et al,2002). Beside this in many times management would also intentionally retain valuable information privately and would not share with others to maximize their self-interest. Consequently investors, other stakeholders have to incur additional cost as well as additional time for monitoring and assuring the behavior of the management (An et al.,2011). According to Watson et al.(2002) management may reveal or disclose more information in order to attain low cost of equity capital by eliminating the barrier of information asymmetry though management is guided by an impetus of self interest.

A group of researchers like Izzo & Magnanelli, 2012; Du et al., 2010; Galbreath, 2008; Asemah et al., 2013 argued that firms with disclosing social-environmental activities, performances and good governance enjoy a competitive advantage by improving reputation and brand loyalty, by maintaining and acquiring faith and confidence, by minimizing cost and risk via reducing information asymmetry. As per the opinion of Habib (2017) one of the primary objectives of environmental disclosure is to minimize the equity cost. In this ground publication of social-environmental issues give more information to the market that leads to better transparency level and reduce estimation risk which in return enhances market liquidities and hence reduce the cost of equity capital (Plumlee et al.,2015).

Resent researcher EI Ghol et al. (2011) explained that publication of information relating to social issues and environmental issues minimize information gap or diminish information asymmetry problem between the firms and related parties that would be advantageous to the investors or potential investors in measuring future performance more accurately and firm’s true value which leads to a lower equity capital cost. The same result has also been verified by Dhaliwal et al. (2011) after investigating 31 countries. As per Dhaliwal et al. (2011) behind the disclosure of environmental information firm intend to acquire more equity capital at a lower cost through attracting more devoted investors and more analysts. By staying on the same line Revert (2012) also suggest that social-environmental disclosure gives more and better information to the investors so that they can forecast future earnings capability and ascertain firm’s value precisely. The author also consider that the publication of information is the only way of communicating with stakeholders and investors to minimize information gap which thereby increases investors base and confident, influence investors to invest, these are all indicate to a minimum cost of equity capital.

From the above discussion it is revealed that there is a gap in the field of empirical research in respect of social, environmental and governance (ESG) disclosure level and cost of equity capital (COE) from the aspect of Indian companies. That is why we take an initiative to fill this gap by undertaking this empirical research.

To fulfill our purpose, we develop the below mention hypothesis:

H1: The ESG disclosure level and COE are inversely associated with each other.

Moreover, most of the prior researchers conduct their research work based on the current year only. That means they test the relation of the current year’s ESG disclosure level with the current year’s COE. But it is more logical and pragmatic that the effect of ESG disclosure level of preceding year or years has more effect than the current year’s ESG disclosure level on the firm’s future value creation process because the current year’s ESG disclosure is published through the annual report in the middle of the current year. This leads to the following hypothesis:

H2: Current year’s as well as lag year or years’ ESG disclosure level has a negative effect on the current year’s COE.

3) RESEARCH METHODOLOGY:

The primary objective of this research work is to analyze whether the COE is affected or not by the ESG disclosure. For this purpose, we have taken into account two types of comparisons viz. current year ESG disclosure with current year COE and preceding year or years ESG disclosure with current year COE. In this regard, the selection of samples, sources of collecting data, use and measurement of different variables are discussed below.

3.1) SAMPLE SELECTION AND DATA SOURCES:

For this empirical study we create a group of top 50 companies (based on their market capitalization as on 31st March,2020) which are registered in India’s one of the leading stock exchanges namely National Stock Exchange (NSE) as our sample companies. Here NSE is considered due to its vast area of incorporation that include almost all sectors of the Indian economy. Moreover, it can also be used as a benchmark for fund portfolios, index-based derivatives and index. This empirical research is conducted based on secondary data which are collected from the annual reports of those sample companies for the study period from 2015-2016 to 2019-2020. Many researchers Lang & Lundholm, 1993; Niemark, 1995 are taken the annual report as their main source of data. According to authors annual report is an important tool by which business firm communicate with outside world. Similarly the authors Guthrie et al. (2004) produce the evidence about the annual report most used by financial analyst for analyzing firm’s performances.

3.2) VARIABLE DESCRIPTION:

3.2.1) INDEPENDENT VARIABLE (ESG DISCLOSURE LEVEL):

In this present study we have considered the ESG disclosure level as our independent variable. Here the extent of ESG disclosure level is ascertained through the ESG disclosure index. For that purpose, we also construct an ESG disclosure checklist based on previous researchers like, Plumlee et al.,2008; Clarkson et al.,2008&2013; Zahller et al.,2015. Thereafter we assign a numerical value against each item of this ESG disclosure checklist to measure the amount of ESG disclosure level numerically. Though earlier researchers like Farooque et al.2014; Poignant & Stensio,2014; Habib, 2017 assign ‘0’ and ‘1’ against ESG items, but in this research work we assign a value range 0 to 3 on the basis of disclosing pattern of ESG items in the annual reports through the content analysis technique, taken as very significant approach for textual inspection (Baalouch et al.,2019; Michelon et al.,2015). Here a value of 0 is put if the item is not disclosure; a value of 1 is assign if the item is presented in descriptive form only. If the item is disclosed in a numerically, a value of 2 is assigned and alternatively a value of 3 is also assigned if the item is presented in both way – descriptively and numerically. After that the ESG disclosure index is computed by dividing the sum of score which is actually given for each item by the maximum score of all items, included in the disclosure checklist. Here the maximum score is also calculated by multiplying the maximum score value with the total numbers of items in the checklist. 

3.2.2) DEPENDENT VARIABLE (COST OF EQUITY CAPITAL):

Keeping in mind about the main aim of this empirical study we have fixed the cost of equity capital (COE) as our dependent variable. COE may be explained as the minimum required rate of return that investors can presume from their investment (Botosan, 2006). Alternatively, we can say that COE is the minimum rate of return, demanded by the shareholders to equate the present value of the expected dividends with the current market value of the share. Hence COE is not only an important matter towards corporate houses but investors also.

In spite of this importance there is no specific method of computing COE. COE may be computed by applying capital assets pricing model (CAPM), earning-price growth model, dividend growth model and bond yield plus risk premium model, but for this research work we have selected the CAPM model as other models are based on unrealistic and subjective assumptions. In bond yield plus risk premium model the risk premium is determined based on judgment rather than any objective methods. On the other hand, it is very uncountable in real life and unrealistic that earnings are expected to remain constant, dividend are paid off every year, dividend will grow at a fixed rate. Therefore, the other models should also not be used uniformly/indiscriminately in the measuring COE. The CAPM is very useful approach of understanding the risk-return relationship in computing COE. Under the CAPM model return of a security is calculated after taking into account the associated risk and this reckon with risk makes this model more scientific. Moreover, the computation of this risk makes the CAPM model more realistic because here risk is measured by the volatility of security’s return with market return. Hence it gives better result of measuring the cost of a security.

In the CAPM model COE (denoted by Ke) is calculated by the combination of risk free rate (Rf) and risk premium [β(Rm-Rf)].  Where risk premium is obtained by multiplying the market premium (Rm-Rf) by beta (β), indicating the degree of risk (Botosan,2006). And market premium is the excess of market return than the risk-free rate [Ke = Rf + β (Rm-Rf)].

In this regards the rate of 10 years Government Securities is considered as the risk-free rate.

3.2.3) CONTROL VARIABLE:

In order to enhance the reliability of the influence of ESG disclosure on COE, in this study we have also use some control variables to control the influence of additional determinants on COE. Following the former researchers (Reverte,2012; Liao et al.,2014; Voerman,2018; Baalouch et al.,2019; Mohamed & Faouzi,2014; Habib,2017) we consider different firm characteristics such as firm’s size (SIZE), market to book value (MBR), unlevered or adjusted beta (BETAu), financial leverage (LEV) and profitability (Prfty) as the control variables. The author Farooque et al.(2014) argued that firm’s size positively affect all aspect of corporate disclosure that leads to minimize information asymmetry and resulting reduction in agency cost. Hence, we anticipate an antipathy association between firm’s size and COE (Reverte,2012; Botosan&Plumlee,2005). We measure the SIZE through simple logarithm of total assets of the firm (Voerman,2018). Alternatively, Ghoul et al.,2011; Baalouch et.al.,2019 suggested that the financial leverage is positively related to the COE. Firms with higher leverage are associated with higher risk (Mohamed & Faouzi,2014). LEV is measured as long-term debts to equity share capital ratio (Duccasy & Montandrau,2015). The concept of profitability is connected with the signaling theory (Burgwal & Vieira,2014). Superior profitability carries information about the competitive advantage. In this respect by publishing more environmental information firms provide a signal to its investors regarding their intangible assets, potentiality of future growth which will help investors to protect their future earnings (Surroca & Tribo,2008). The return on equity is considered as the basis of profitability (Prfty) measurement (Voerman,2018). The ratio of book value to the market value of equity ratio of a firm is taken as the proxy measure of market-to-book value (MBR) (Reverte,2012). This market to book value conveys the availability of favorable opportunities (Khurana & Raman,2004). Previous researcher Bushman & Smith (2001) opinion that the voluntary disclosure of corporate environmental information act as a leaver to diminish firm’s cost of equity to back growth opportunities. Hence, we also predict that there is an inverse association between the market to book value and the COE (Botosan & Plumlee, 2005; Orens et al.,2009). On the other hand, beta is positively correlated with the COE (Reverte,2012; Habib,2017; Salvi et.al.,2020). Beta represents the volatility risk associated with the security. Higher the beta indicates a risky security and resulting high equity cost (Botosan & Plumlee, 2005). Here we use the unlevered beta in order to separate the leverage risk from the model (Botosan et al.,2011). This implies that the model is only related with the market risk. BETAu is measured as the ratio of beta (calculating by individual security’s volatility with market volatility) and one plus debt-equity ratio (Bu=Beta/1+Debt-Equity Ratio) (Salvi et.al.,2020).

3.3) RESEARCH MODEL:

To test our hypothesizes we construct two regression equations based on Habib,2017. The first model focuses on the influence of present year’s ESG disclosure level on the present year’s COE. Whereas the second model deal with the influence of lagged or previous years’ ESG disclosure level on the present year’s COE. Hence the two regression equations are as follows:

COE = β0 + β1ESG + β2PRFTY + β3SIZE + β4MBR + β5LEV + β6BETAu + ε  ........... (1)

COE = β0 + β1ESGt-1 + β2ESGt-2 + β3ESGt-3 + β4ESGt-4 + β5PRFTY + β6SIZE + 

β7MBR + β8LEV + β9BETAu + ε  ........................ (2)

COE = Cost of Equity Capital

ESG = ESG Disclosure Level of last 5 preceding years starting from 2019-2020.

SIZE = Firms’ Size; LEV = Financial Leverage; PRFTY = Profitability; MBR = Market to Book Value;

BETAu = Unlevered Beta

––––––––

4) RESULT SUMMARY:

4.1) DESCRIPTIVE STATISTICS & CORRELATION ANALYSIS:

This section is concerned with the statistical results of all the variables. Firstly, we start with the descriptive statistical result, followed by the Pearson Correlation matrix and lastly the regression results. Here, ESG represent the ESG disclosure level for the year 2019-20, whereas ESGt-1 represents the same disclosure level for the year 2018-19 and likewise ESGt-2, ESGt-3, ESGt-4 represent the same disclosure level for the year 2017-18, 2016-17 and 2015-16 respectively. And other variables having no subscript represent the respective variable for the year 2019-20.

Table-1 shows the results of descriptive statistics.  Table-1 depicts the five consecutive mean values of ESG disclosures which are 0.4398, 0.3914, 0.3398, 0.3198 and 0.2832 respectively. If we closely observe the mean values, we can see that there is an increasing trend which also reflects an enhancement in the disclosure level of ESG in perspective of Indian companies. But at the same time, it can be seen that the maximum mean value is 0.4398 which also implies that the disclosure level is still moderate as compared to the disclosure level of other countries (Habib,2017; Reverte,2012).

The main motive of this empirical work is to investigate the nexus between the ESG disclosure level and COE. Therefore, we go through the Pearson Correlation between these two main variables for the earlier mentioned two-research models. As the results of correlation table shows that the COE is negatively and statistically significant related with the ESG disclosure level for all the study periods except for the year 2016-17. Hence the COE and ESG disclosure level are negatively connected with each other. And other control variables are also correlated with COE according to their hypothetical sign.

4.2) CLLINEARTY & AUTO-CORRELATION ANALYSIS:

In Table-1 the highest correlation value is 0.769 between COE and BETAu. Therefore, we can say that all variables are free from the multicollinearity issues. Field (2009) and Habib (2017) argued that this does not hold a problem of multicollinarity as it stays below the maximum threshold limit of 0.80. In this case we ignore the correlation values among the variables of ESG disclosure itself. As most of the companies publish their ESG related information in the same pattern for every year. Further, we also test the multicollinearity issues using variance inflation factors (VIFs) in respect of the two regression models as represented in table 3(i) and table 3(ii). After running our two multiple regressions in SPSS we can see that the maximum VIFs value is 1.869 for the first regression model and 2.885 for the second regression model which are below 10, indicating the two regression models have no multicollinearity problem. As a VIF value of 10 is considered as a thumb rule for measuring the collinearity issues relating to a variable (Hail & Leuz,2006). The Durbin-Watson values of two models are 1.759 [from table-3(i)] & 1.847 [from table-3(ii)] respectively which are fallen within 1-4 that implies there is no autocorrelation among under considered variables. 

4.3) REGRESSION ANALYSIS:

Here, ‘*’ and ‘**’ represent at 1% and 5% significance level respectively. But ‘***’ indicate 10% significance level.

In order to fulfill our research objectives, we already construct two regression models for all the variables. The table-3(i) represents the regression results for the first model i.e. for the nexus between current year COE and ESG disclosure level and table-3(ii) shows the regression results for second model i.e. for the current year COE and 4 years lag ESG disclosure level in respect of the year 2019-20. The Adj.R² values for the two models are 0.675 and 0.749 respectively that implies the two models can explain approximately 67% & 75% variance in the dependent variable i.e. COE for the predictor variable i.e. ESG disclosure. The F-stat values are 22.223 and 31.444 respectively at 1% significance level which indicate both the models are good fitted models.

The regression results of table-3(i) reveals that current year ESG disclosure level has a statistically proved negative coefficient (-0.006) with current year COE. Hence, we can say that there exit an inverse association between current year ESG disclosure level and COE. Alternatively, we can say that lower is the COE with the increases of the ESG disclosure level. This finding confirms our first hypothesis that the current year ESG disclosure level and COE are inversely associated with each other.

The table-3(ii) shows that the regression coefficient between ESG disclosure level for the year 2018-19, 2017-18, 2016-17 & 2015-16 and COE are -0.156, -0.221, -0.098 & -0.058 respectively and all are statistically significance except 2015-16 disclosure level at 1% & 5% level. Therefore, the COE is negatively and statistically linked with all the previous years’ ESG disclosure level. From these results we can interpret that lag years’ ESG disclosure level has an adverse effect on the current year’s COE. Availability of ESG information for the pervious years minimizes the finance cost by maximizing investors’ confidence level, market liquidity and firm value.

In this regards, if we analyze the Adj.R² values for the two models, we observe that model-2 (approx.75%) have more explanatory power than model-1 (approx.67%). Generally current year’s information is published at the middle of current year through the annual reports, but lag years’ information already exists in the market. Therefore, market participants easily can collect related information from the previous years. Hence it is more pragmatic and logical that lag years’ ESG disclosure level has more effect than the current year’s ESG disclosure level. 

Moreover, in order to analyze the lag year effect in depth additionally we also examine the influence of the previous years’ of ESG disclosure level against the COE in respect of 2018-19, 2017-18 and 2016-17 respectively out of our study periods. Consequently, below mentioned three additional regression models are run:

COEt-1 = β0 + β1ESGt-2 + β2ESGt-3 + β3ESGt-4 + β4PRFTYt-1 + β5SIZEt-1 + 

β6MBRt-1 + β7LEVt-1 + β8BETAut-1 + ε  ........................ (2a)

COEt-2 = β0 + β1ESGt-3 + β2ESGt-4 + β3PRFTYt-2 + β4SIZEt-2 + 

β5MBRt-2 + β6LEVt-2 + β7BETAut-2 + ε  ....................... (2b)

COEt-3 = β0 + β1ESGt-4 + β2PRFTYt-3 + β3SIZEt-3 + 

β4MBRt-3 + β5LEVt-3 + β6BETAut-3 + ε  ........................ (2c)

––––––––

The regression results are as follows:

Here, ‘*’ and ‘**’ represent at 1% and 5% significance level respectively. But ‘***’ indicate 10% significance level.

Above mentioned three tables [3(ii)(a), 3(ii)(b) & 3(ii)(c)] reveal that the regression coefficients for all lag years’ ESG disclosure with respective current year’s COE are negatively and statistically associated with each other. Hence, it is clearer that lag years’ ESG disclosure level has more effect than the current year ESG disclosure level. 

In relation with our control variables, most of the cases control variables maintain their hypothetical sign in the regression with COE. From all the earlier mentioned tables we can say that profitability negatively and statistically regresses with COE (-0.287, -0.328, -0.053, -0.016 & -0.024). That means higher profitability leads to higher opportunity, higher investors’ confidence, higher demand and lower COE. Likewise profitability, firms’ size and market-to-book ration also inversely connect with COE (-0.069, -0.051, -0.043, -0.096 & -0.068 and -0.044, -.310, -0.026, -0.050 & -0.075 respectively) - higher firms size, better financial condition, having more capability of disclosing higher level of information, leads to lower information asymmetry, higher transparency level and lower finance cost. Firms having a higher market value than book value secure higher MBR and higher MBR indicates greater opportunity, higher earning capability and lower equity cost. But financial leverage and unlevered beta positively and statistically regresses with COE (0.301, 0.541,0.149, 0.415 & 0.152 and 0.768, 1.039, 0.951, 0.789 & 0.913 respectively) – higher the financial leverage, higher the associated risk and higher the COE. 

5) DISCUSSION & CONCLUSION:

This section relates with the discussion of results of the analysis, represented in previous section, by dividing three parts. In the first part we summarize the findings, there after we consult the research models with our hypothesis and lastly we discuss about the relevance of our research work and drawn conclusion.

The findings of this present study, concerning to investigate the effect of ESG disclosure level on the COE, can be summarized in the following way. The current year’s as well lag years’ ESG disclosure level is negatively with statistical significantly attached with the current year COE from the perspective of Indian scenario. Thus our two hypothesizes are proved (EI Ghol et