Financial decision dynamics: Environmental,social,and governance factors and managerial choices in emerging markets

Abstract

This study examines the linkage between the ESG performance of firms and managerial decision-making. It uses 8 years of ESG performance data of 110 Indian firms collected from the Thomson Reuters database. The study finds that high ESG performance mitigates a firm’s cost of debt more than equity cost. Furthermore, increases in ESG performance are associated with higher capital expenditures, lower investment cash flow sensitivity, higher cash holdings, and lesser payout of increased cash flows to shareholders. The findings are in sync with the Slack resources view, suggesting that the requirement of financial Slack for ESG-related innovations and risk-bearing is large and impacts the major managerial decisions of firms. While the effects of environmental and social performance on these decisions are similar to that of the composite ESG performance, governance performance shows an independent impact on the payout decisions of firms. The Granger Causality test reveals a bi-directional association between debt issues and ESG performance. The main results obtained from the multiple panel regressions are robust to additional tests involving lead-lag analysis. The overall findings of this study highlight the importance of ESG performance screening in the managerial decision-making process of investors who would not like to risk growth potential for a short-term increase in dividends.

Keywords

cash holdings debt issues environmental,social and governance financial decisions liquidity payout

Introduction

Companies increasingly face pressure from regulators to enhance their environmental, social, and governance (ESG) performance and disclosures (Krueger et al., 2021). Any activity aimed at improving the positive impact on the environment and society is categorized as an ESG practice (Chouaibi et al., 2022b). ESG considerations are also becoming increasingly significant in investor decision-making (Birindelli et al., 2015; Hoepner et al., 2016; Humphrey et al., 2012), prompting firms to improve ESG performance and increase ESG disclosures on company websites, annual reports, and business model descriptions (Bini et al., 2018). ESG practices play a critical role in protecting shareholder interests by ensuring the separation between decision management and control within a firm (Chouaibi et al., 2022a). Moreover, ESG disclosures are designed to reduce information asymmetry between companies and stakeholders (Sánchez-Sancho et al., 2024). According to agency theory, ESG can help lower information asymmetry in the market, which may lead to reduced capital costs for firms with high ESG performance (Cheng et al., 2014). Despite these benefits, ESG disclosures by firms, in terms of level and quality, remain inadequate for aiding investment decisions (Krueger et al., 2021).

The academic debate regarding the economic consequences of non-financial disclosures, such as Corporate Social Responsibility (CSR) and ESG, is ongoing. Theories, such as agency theory, resource-based view, and stakeholder legitimacy theory, support the requirement of higher ESG performance, arguing that ESG strengths can provide financial flexibility for efficient financial decisions (Barney, 1991; Thawani and Bhatia, 2024). Non-financial disclosures from firms are essential for providing a complete picture of financial performance (Zimon et al., 2022). Allman and Won (2021) argue that non-financial disclosures are as good as financial disclosures in reducing the adverse selection problems of firms, especially in debt markets. Egginton and McBrayer (2019) report reductions in information asymmetry from ESG performance, enabling firms’ efficient decision-making. Sustainability disclosures reduce default risks, performance risks (Atif and Ali, 2021), and systematic risks of firms (Lueg et al., 2019) while increasing their profits (Atif and Ali, 2021).

Conversely, some studies contend that ESG performance can create negative externalities for firms. For example, in efforts to report superior ESG performance, firms may incur higher costs, potentially reducing shareholder wealth (Ioannou and Serafeim, 2017). Additionally, some firms may engage in “greenwashing” by exaggerating their ESG performance to gain legitimacy, which can increase their risk profile and result in negative economic consequences for investors (Cho et al., 2015; Hemingway and Maclagan, 2004; Michelon et al., 2016).

Given the conflicting theoretical viewpoints and empirical evidence, the role of ESG performance in enhancing the financial flexibility of firms remains unresolved in the existing literature. Although there is substantial empirical evidence in the extant literature suggesting significant economic benefits from increased financial disclosures (Christensen et al., 2019) —such as higher firm value, greater liquidity, lower financing costs, and improved corporate decisions—the economic benefits of non-financial disclosures, like ESG, are less understood and remain at a nascent stage. This study aims to fill this gap by exploring whether high ESG performance increases the financial flexibility of firms. Previous studies have primarily examined the impact of ESG performance on financial performance, but this study uniquely assesses whether ESG performance influences managerial decision-making. This study hypothesizes that firms with high ESG performance are more likely to issue debt for financing, hold less precautionary cash, face lower investment cash flow sensitivity, and enhance their payouts to shareholders. Using panel regressions, the study examines how a firm’s overall ESG performance score and its performance on individual ESG dimensions are associated with its investing, financing, and payout decisions, aiming to gain a nuanced understanding of the role of ESG performance in corporate decisions. The study utilizes ESG performance data from 2014-22 for 110 Indian non-financial firms from the Thomson Reuters database and financial data from the CMIE Prowess database, resulting in a balanced panel comprising 880 firm-year observations.

This study contributes to the literature in three ways. First, it enhances the understanding of the role of ESG performance in corporate managerial decisions. Previous studies suggest that ESG performance can decrease the cost of debt (Eliwa et al., 2019; Hoepner et al., 2016) for firms capable of raising the desired borrowings. However, examining the benefits of ESG solely through the cost of debt is insufficient, as financial constraints include both price (interest rate) and quantity (amount of debt) limitations. This study explores the economic consequences of ESG performance by investigating how it influences corporate decisions regarding the mode of financing, payout increases, and cash reserves. It indirectly examines the role of ESG performance in credit decisions by assessing the firms’ financial flexibility—a topic with limited existing research. Second, this study advances the understanding of how ESG performance is related to a firm’s internal financial decisions and external financial contracting. Third, using a composite ESG performance score may mask the impact of individual ESG dimensions on decisions (Mattingly, 2017). Therefore, the study analyzes the independent effects of each ESG dimension on financial decisions. Finally, the reasons for holding large cash reserves have often intrigued academics, policymakers, and financial economists (Summers, 2015). Recently, shareholders of cash-rich companies have complained to regulators about the non-payment of dividends despite substantial cash reserves, prompting regulators to mandate dividend distribution policies (The Economic Times, 2016). By using ESG performance to explain cash-holding decisions, this study contributes to corporate finance literature.

The ESG reporting landscape in India

Companies should be responsible towards all stakeholders (Salehi et al., 2018). India is one of the countries to mandate CSR for companies. CSR enhances social welfare, transparency, and accountability in business operations (Salehi et al., 2022). Although the National Voluntary Guidelines (NVGs), released in 2011, outlined the Social, Environmental, and Economic Responsibilities of Indian firms, they were concluded in the new Companies Act of 2013. SEBI, tasked with implementing an effective ESG reporting mechanism until 2021, required a Business Responsibility Report (BRR) from the top 500 firms listed by market capitalization in India. In 2021, SEBI replaced BRR reporting requirements with new sustainability-related disclosure requirements termed the Business Responsibility and Sustainability Report (BRSR), applicable to the top 1000 listed firms by market capitalization (SEBI, 2021). The BRSR requirements are a significant step towards aligning Indian sustainability reporting with global reporting standards (Bhatia, 2021). The new BRSR reporting framework is grounded in the nine principles of the “National Guidelines on Responsible Business Conduct,” the RBC Guidelines of the Indian Government. The RBC guidelines take cues from leading international standards such as the Paris Agreement, UN Sustainable Development Goals, UN Guiding Principles on Business and Human Rights, and the International Labor Organization Core Conventions to include a variety of sustainability dimensions involving business ethics, human rights protection, environmental wellbeing, and fair labor practices. Reporting for companies under each principle is segregated into essential and leadership indicators. The Essential indicators are mandatory obligations, while leadership indicators are voluntary. Although companies are encouraged to initiate BRSR early, adoption of the BRSR is mandated from FY 2022-23 to give sufficient time for companies to comply with the new requirements.

ESG targets are increasingly being included in the Key Result Areas for the computation of variable pay of top management by many leading firms in India, such as Marico and all the Tata group companies. Several other developments indicate a growing ESG consciousness among Indian firms. For instance, several Indian companies such as Infosys, Tech Mahindra, and Wipro are part of the Dow Jones Sustainability Index. Reliance Industries and TCS have announced plans for zero greenhouse gas emissions, and Vedanta, a diversified miner, is about to include ESG consideration in all corporate decisions and performance evaluations (Bhatia, 2021). While the interest in higher ESG performance, growing worldwide, is also reflected among Indian companies, most of this interest is driven either by investors and customers or by companies themselves. The role of the Indian regulator so far has been limited (Tyagi, 2021).

Background & hypotheses development

Background to the research problem

One of the major challenges for investors and firms in communicating sustainability performance information is the absence of comprehensive standards (Salehi and Arianpoor, 2021). Several studies (Ahmed and Uddin, 2018; Baldini et al., 2018) report that both ESG performance and the market incentivization of such disclosures differ across countries due to differences in institutional settings. They suggest that the economic rewards from ESG performance will be higher in country settings characterized by stakeholder orientation. Companies disclose ESG and other non-financial information to let the public understand the impact corporate operations are creating, which also strengthens communication with stakeholders (Kao et al., 2024). Chauhan & Kumar (2018) argue that motivation for firms to disclose non-financial data, such as CSR and ESG, is low due to higher reporting costs in emerging countries characterized by low levels of corporate governance. Environmental legislation requiring additional disclosures to regulatory bodies increases the firms’ costs (Choi et al., 2021). For several reasons, the Indian market, one of the fastest emerging markets, is an interesting case to examine the association between ESG performance and corporate financial decisions. There has been a sharp increase in shareholder activism on ESG issues in India (Mukherjee, 2021; Varottil, 2021). Governance is in focus, and the boards and top management of Indian firms are increasingly finding it hard to push agendas that do not cater to the broad interests of all stakeholders. Typically, 20-25 BSE 500 Indian companies see their resolutions defeated in the AGMs (Varottil, 2021). The number of such cases has significantly increased in recent years due to the increased voicing of concerns by institutional investors, increased shareholder activism, and the economic environment and related uncertainties. Public shareholders have successfully pushed back resolutions on matters such as managerial remuneration, related party transactions, and the reappointment of directors at some leading Indian firms such as Zee Entertainment, Eicher, Hero MotoCorp, and Balaji Telemilfm (Varottil, 2021).

There are mandates by regulators such as SEBI (Securities and Exchange Board of India), IRDA (Insurance Regulatory and Development Authority), and PFRDA (Pension Fund Regulatory and Development Authority) for implementation of the Stewardship Code by Indian institutional investors. If the financial investors value ESG performance, high ESG-performing firms will have financial flexibility. It would, therefore, be of interest to empirically explore the existence of market rewards for higher ESG performance in the Indian market. Several related studies have attributed variations in empirical results to cumulative sustainability measures such as the ESG score. This study includes tests of the independent impact of the ESG dimensions of the firms on their financial decisions.

ESG performance: Constraining or enabling efficient corporate financial decisions

The role of ESG performance in the financial decision-making of firms is still unclear in the extant literature. Contrasting viewpoints exist on the association between ESG performance disclosures and the financial flexibility of firms. Agency Theory, Stewardship Theory, Stakeholder Theory, and Resource-based Theory (Barney, 1991) suggest that the ESG performance of firms provides non-financial performance data that investors need, causing their increased financial flexibility. Harrison and St John (1996) argue that the most significant benefit of the stakeholder approach to corporate decisions is that it creates and preserves organizational flexibility that the firms require for adequately responding to changes in their business environment. Due to a growing realization among stakeholders that business firms are also accountable for environmental and societal issues, the ESG non-performance of firms today can add immensely to their business risks. ESG reduces information asymmetry and the consequent agency costs for the company (Egginton and McBrayer, 2019). Maintaining transparency in non-financial sustainability information provides in-depth knowledge to investors (Arianpoor et al., 2023; Rossi et al., 2021). Firms that incorporate ESG considerations in their business activities are considered stewards of stakeholder interests. The increased attention to the environment has led the firms to improve the quality of environmental disclosure (Chouaibi et al., 2021). Therefore, ESG strengths can benefit the company by increasing its brand value (Lee et al., 2022), moral capital, profitability, and lowering its risks (Luo and Bhattacharya, 2006).

The alternate viewpoint considers ESG activities as mere eyewash activities designed to manage the goodwill of firms. Implementing ESG activities increases monetary costs in return for long-term non-pecuniary gains (Niu et al., 2022), costs of compliance leading to profit erosion (Ioannou and Serafeim, 2017), and can lead to suboptimal business decisions (Christensen et al., 2019). ESG investments, thus, contradict the shareholder wealth maximization goal as propagated by the traditional corporate finance theories (Levitt, 1958). Investors are wary of investing in the debt and equity of companies with poor ESG performance to avoid being perceived as supporters of firms that do not comply with sustainability standards (Caragnano et al., 2020; Jung et al., 2018). Such pressures from investors are causing firms to artificially project themselves as ESG-conscious (Cho et al., 2015; Michelon et al., 2016). Consequently, firms that are low on ESG performance or are indulging in some wrongdoings are the ones that use rigged ESG performance disclosures to manage investor perception for legitimacy (Hemingway and Maclagan, 2004). Therefore, higher ESG performance disclosures indicate risks that will eventually constrain the firms financially.

Figure 1 depicts the conceptual framework for the association between ESG performance and corporate financial decisions. Extant literature remains inconclusive about whether firms use ESG performance to window-dress their performance or genuinely reduce asymmetric information and increase transparency (Lueg et al., 2019). ESG reporting frameworks are still evolving. Since most ESG reporting is voluntary for firms (Cotter and Najjah, 2012), it is of academic and practical interest to explore whether high-performance scores predict economic benefits for firms. This analysis will also create some knowledge about whether or not investors consider the performance disclosures as true revelations of firms’ ESG performance.

Figure 1.

Conceptual framework for the association between ESG performance and managerial decisions. Source: Authors’ construction.

Empirical evidence & hypotheses development

ESG performance & cash holdings

The most prominent theoretical explanation for corporate cash holdings is the precautionary motive, explaining them as protection for firms against market uncertainties (Almeida et al., 2004; Harford et al., 2014). Consistent with the preserving liquidity motive, firms holding higher proportions of cash to total assets have riskier cash flows and limited access to external financing (Harford et al., 2014). From an investment viewpoint, firms with higher levels of information asymmetry save more cash to avoid incurring high costs on external financing (Bigelli and Sanchez-Vidal, 2012). ESG performance reduces information asymmetry and agency conflicts (Cormier et al., 2011). It increases investor trust and loyalty and reduces the default risks of firms to increase their access to external funds at lower costs (Cheng et al., 2014). Recent empirical findings report meaningful reductions in default risks (Atif and Ali, 2021) and improvements in credit ratings (Feng and Wu, 2021) of firms with high ESG performance and lesser cash holdings by firms having lower reputational risks (higher ESG performance) (Hasan et al., 2021). Firms that consider ESG get benefits in terms of reduced borrowing cost and risk levels and maximized shareholder value (Khan and Iqbal, 2024)

The opposing viewpoint on the ESG-cash holdings relation also exists in the extant literature. Wee et al. (2020), for example, in the Korean market, found that high ESG performance levels constrain net cash flows, and unlike in the U.S. markets, low ESG levels lead to higher net cash flows. Although ESG investments can help firms acquire unique and valuable resources, creating a sustainable competitive advantage, firms would need financial slack to invest and undertake innovation activities pointed out by the slack resources theory (Nohria and Gulati 1996). Since innovation and experimentation involve risks of failures and losses, financial slack would be a cushion of protection for firms engaging in high ESG activities (Bowen, 2002). ESG performance will be positively associated with cash holdings and negatively with the cost of withholding cash. It is because shareholders view ESG investments of firms as mitigation of agency conflicts between shareholders and other stakeholders and also protection from managerial expropriation to assign a higher value to the cash holdings of high ESG over low ESG firms (Arouri and Pijourlet, 2017; Perez-de-Toledo & Bocatto, 2019). Therefore, whether ESG performance creates sufficient financial flexibility for firms to help them sustain themselves with low cash holdings is an open question in the extant literature. The following hypotheses are formulated to test the association between ESG performance and the cash-holding decisions of firms:

H1: Higher environmental, social, and governance performance are related to lesser cash holdings of firms

H2: Higher environmental, social, and governance performance are related to a lesser propensity of firms to save cash

ESG performance & investment-cash flow sensitivity

High ESG performance facilitates continuous and stable cash flows for firms. Extant studies find lesser cash flow sensitivity to adverse events for socially responsible investments (Renneboog et al., 2011). Also, improved access to capital markets from high ESG performance protects firms from variations and market uncertainty, decreasing their propensity to save for precautionary motives (Favara et al., 2021). Allman and Won (2021) find that non-financial disclosure can mitigate adverse selection problems for underinvesting firms. Investment decisions of firms with high ESG performance will be based on the availability of profitable opportunities because financing will not be a problem for these firms. The investment-cashflow sensitivity, thus, will be lower in these firms (Favara et al., 2021). The following hypothesis is constructed to test the role of ESG performance in the firms’ investing decisions:

H3: Investment-cash flow sensitivity is low in firms with high environmental, social, and governance performance

ESG performance & financing decisions

ESG performance may increase firm valuation because investors are concerned about corporate externalities (Bonnefon et al., 2019). Nowadays, firms voluntarily report ESG-related information to gain stakeholder approval (Paolone et al., 2024). Non-financial disclosures such as ESG may assure many financial benefits to firms and improve their access to finance by fulfilling the information requirements of investors (Kleimeier and Viehs, 2018). Companies are promoting innovation in products/services, which requires external financing (Shafeeq Nimr Al-Maliki et al., 2023). Raimo et al. (2021) demonstrate that firms with higher ESG performance benefit from their increased ability to access third-party financing at better terms. There is unanimous empirical evidence of the negative effect of ESG on both the cost of debt (Eliwa et al., 2019; Raimo et al., 2021) and the cost of equity (Ferris et al., 2017). The reductions in debt and equity costs are because of mitigations in the information asymmetry problems and agency costs from ESG disclosures (Bryl and Fijałkowska, 2020; La Rosa et al., 2018). ESG disclosures reduce systematic risk (Lueg et al., 2019) and facilitate lenders in assessing the default risk of firms (Eliwa et al., 2019; Gerwanski, 2020). Not many studies have analyzed the association between the ESG dimensions and the cost of financing. Concerning the cost of debt, Hamrouni et al. (2019) find that the environmental dimension reduces, and social performance unexpectedly increases, while governance has no significant effect on the cost of debt.

Studies to indicate whether the reductions in asymmetric information of debt and equity investors are comparable are missing in the literature. Allman and Won (2021) report increased ability of firms from their ESG reporting for raising new debt, but not new equity. This study contends that if ESG increases the financial flexibility of firms, it will predict debt issues for the external financing needs of the firms more than equity, as the former is inherently cheaper than the latter for external financing. The following hypothesis is constructed to test the association between ESG performance and the financing decisions of firms:

H4: Firms with high environmental, social, and governance performance issue debt for external financing

ESG performance & payout decisions

Dividend decision, which impacts several other financial decisions, such as investment decisions, cash holdings, financing decisions, and management compensation, has been a focus of a large no. Of studies in the finance literature (Hasan and Habib, 2020). However, the association of sustainability performance with dividend decisions is not adequately examined in the existing literature (Verga Matos et al., 2020; Zadeh, 2020). Recent studies report a positive association between dividends and ESG or sustainability performance. For instance, high CSR firms exhibit higher payouts (Benlemlih, 2019; Cheung et al., 2018) and a stable dividend policy (Samet and Jarboui, 2017). Verga Matos et al. (2020) report the use of stable dividend policy by firms with high performance on ESG, including on the individual dimensions of ESG. These findings are consistent with the propositions of the Agency theory, Signaling Theory, and Stakeholder Theory (Yu et al., 2018). Consistent with the stakeholder theory, high ESG-performing firms look at dividend decisions from the viewpoint of ethics of profit distribution to pay high dividends in the interest of all of their shareholders (Yu et al., 2018). ESG performance satisfies the information needs of different stakeholders, and dividend policy restricts the managerial discretionary use of free cash flows or managerial tendency to overinvest in ESG activities or corporate philanthropy for personal benefits, causing non-value maximizing outcomes for the shareholders (Barnea, 2010). Higher ESG performance enhances the dividend-increasing ability of firms by increasing their income generation ability (Yu et al., 2018).

On the contrary, the slack resources theory suggests that dividend payments would reduce ESG activities by lowering financial slack in the firm (Barnea and Rubin, 2010). Increased payouts might get other stakeholders worried about the decrease in the ability of firms to serve their interests or meet their requirements (Shapiro, 1990). Since increased dividends would reduce cash, it may reduce the ability of firms to implement ESG policies. The following hypothesis is constructed to test the association between ESG performance and payout decisions of the firms:

H5: Dividend changes in firms with high environmental, social, and governance performance are more positively related to the prior cash changes

Data and methodology

Data

A sample of 110 firms was obtained after removing banks, financial firms, and firms with missing data, for which complete ESG data from 2014-22 were available on the Thomson Reuters database. The study examined a balanced panel comprising 880 firm-year observations. The financial data of the firms were collected from the CMIE Prowess database. For empirical analysis, the study performed panel regressions, using Hausman tests to decide between random effects (RE) and fixed effects (FE) models for all the decisions analyzed (Faysal et al., 2021). The regression models included industry and time effects.

Table 1 reports the descriptive statistics of independent, dependent, and control variables. The mean ESG performance is 53.5, close to the median value. Similarly, the mean and median values of ENV (environmental), SOC (social), and GOV (governance) performance are also very close, implying low skewness in the data. On average, firms hold 3.8% of the market value of assets (hereafter MVA) in cash. The mean change in cash balance is also small. Most of the firms in the sample are dividend-paying and maintain stable cash holdings as a percentage of MVA, as inferred from the low mean cash flow volatility value. The mean value of ΔDebt/MVA is 2.1%, depicting that firms largely maintain target debt levels in the capital structure or do not increase debt significantly over time.

Table 1.

Descriptive statistics.

Variables	Mean	Standard deviation	Q1	Median	Q3
ESG	53.500	16.277	42.445	53.739	64.117
ENV	45.689	23.461	26.662	45.518	64.728
SOC	59.111	19.274	45.744	59.693	75.335
GOV	50.219	22.084	30.965	49.251	68.258
BM	0.6958	0.8020	0.252	0.493	0.964
ΔDebt/MVA	0.021	0.072	−0.004	0.001	0.044
D/EISSUE	0.227	0.419	0.000	0.000	0.000
Cash	0.038	0.215	0.003	0.010	0.031
CF	0.099	0.066	0.056	0.103	0.142
NWC	0.111	0.255	−0.059	0.050	0.191
CAPEX	0.002	0.005	0.000	0.000	0.001
ACQ	0.002	0.017	0.000	0.000	0.000
CFVOL	0.022	0.024	0.008	0.015	0.026
DIVD	0.928	0.259	1.000	1.000	1.000
FCF	0.147	2.629	0.001	0.018	0.041
PPE	0.350	2.190	0.030	0.103	0.284
OI	0.234	2.808	0.046	0.076	0.110
R&D	0.004	0.010	0.000	0.000	0.003
LY OI/MVA	0.191	0.119	0.107	0.175	0.248
OIVOL	0.027	0.025	0.011	0.020	0.035
LEV	0.180	0.252	0.002	0.044	0.292
RET	−0.052	0.152	−0.125	−0.015	0.055
MVA (in crores)	115096.000	193252.931	32324.730	59721.090	117326.900
ΔCash	0.005	0.082	−0.003	0.000	0.006
LEV-predicted LVA	0.000	0.186	−0.118	−0.033	0.069
RETVOL	0.089	0.037	0.063	0.081	0.105
NOL	0.014	0.084	0.000	0.008	0.012
CFSI	2.8909	10.8041	0.5029	0.2103	1.1578
CFSIDUMMY	0.9392	0.2392	1.0000	1.0000	1.0000
ΔPayout	0.0012	1.2290	0.0000	−0.0013	0.0022
STD	0.0107	0.0145	0.0052	0.0078	0.0095
Ke	0.1314	0.0408	0.1270	0.1030	0.1553
Kd	0.0391	0.0214	0.0404	0.0204	0.0584

Source: Authors’ own work.

Empirical models

This section elucidates the empirical models used to test the hypotheses. To examine the impact of ESG performance on various managerial decisions—such as corporate liquidity decisions, investment-cash-flow sensitivity, financing decisions, and payout decisions—panel data analysis is conducted. For each decision, different models are employed, which are explained in the sub-sections. Additionally, the study posits that firms’ ESG performance influences their financial decisions, but it is also possible that financial decisions impact firms' ESG performance. The Granger Causality test is used to examine the possibility of a bidirectional association between firms’ ESG performance and financial decisions.

ESG performance & corporate liquidity decisions

For testing Hypothesis 1, the study first estimates whether ESG performance in the previous year determine the corporate cash holdings. It uses the cash-holding model by Bates et al. (2009). The model uses cash as the dependent variable, lagged ESG disclosure score as an independent variable, and controls for the other contemporaneous financial variables.

{C a s h}_{t} = α_{0} + a_{1} {E S G}_{t - 1} + {Σ C o n t r o l s}_{t} + ɛ_{t}

(1A)

All variables in equation (1A) are deflated by the MVA to eliminate heteroskedasticity. The book-to-market (BM) ratio and research and development (R&D) expenditure are proxies for investment opportunities used as controls because firms with growth opportunities keep higher cash holdings. Firm size (SIZE) is a proxy of economies of scale related to the transaction motive of cash holdings. Firms with better performance usually gather more cash (Bates et al., 2009). Cash flows (CF) and returns (RET) (Orazayeva and Arslan, 2024) are controls for firm performance. Net working capital (NWC) is the control variable for assets that are alternatives for cash. Firms with higher tangibility have fewer cash holdings. Capital expenditure (CAPEX) and acquisition expenditure (ACQ) are included as proxies for asset tangibility and cash outflows, respectively. Another control variable is financial leverage (LEV) because cash is needed to repay debt. Cash flow volatility (CFVOL) is used to control cash flow risk in the model, and returns volatility (RETVOL) is the control for other unsystematic risks that encourage precautionary cash holdings (Bates et al., 2009) by firms. A control variable for dividend-paying firms (DIVD) is also included in the model, as firms that distribute dividends are less risky and, thus, have lower cash holdings. Finally, dummy variables for industry and year are added to the model as additional controls. Explanations of primary and control variables are provided in the Appendix.

If the ESG performance increases (decreases) a firm’s financial flexibility, firms with high (low) ESG performance will have less (more) cash holdings. Therefore, $a_{1}$ in equation (1A) shall be less (more) than zero. The cash variable is regressed on ENV, SOC, and GOV individually in Equations (1B)–(1D), respectively, to assess the independent impact of ESG dimensions on corporate cash holdings.

{C a s h}_{t} = β_{0} + β_{1} {E N V}_{t - 1} + {Σ C o n t r o l s}_{t} + ɛ_{t}

(1B)

ENV in equation (1B) is the Environmental performance score of firms. This score depicts the performance of firms related to reductions in the use of materials, energy, and water (resource use), reductions in environmental emission (emission), and the generation of newer opportunities by introducing environment-friendly products (innovation). All control variables are the same as those appearing in equation (1A).

{C a s h}_{t} = δ_{0} + δ_{1} {S O C}_{t - 1} + {Σ C o n t r o l s}_{t} + ɛ_{t}

(1C)

The social performance score (SOC) in equation (1C) is the performance of firms on 63 factors related to their effectiveness in maintaining employee job satisfaction, creating equal opportunities for employees, keeping the workplace healthy and safe (workforce), respecting human rights, taking appropriate care of public health, following business ethics (community), and creating quality products (product responsibility). All control variables have already been defined and are the same as those in equation (1A).

{C a s h}_{t} = λ_{0} + λ_{1} {G O V}_{t - 1} + {Σ C o n t r o l s}_{t} + ɛ_{t}

(1D)

The governance performance score (GOV) in equation (1D) is the performance of firms on 54 factors related to their endorsement of the best corporate governance practices (management), equal treatment of shareholders (shareholders), and integration of social and environmental parameters into their day-to-day decision-making process (CSR Strategy). All control variables have already been defined and are the same as those in equation (1A).

Following the work of Lee (2010) in examining the ESG-liquidity relationship, the study also tests whether ESG is associated with a firm’s propensity to save cash. The cash flow retention model (Equation (2A)) proposed by Almeida et al. (2004) is used to test Hypothesis 2.

{Δ C a s h}_{t} = Ω_{0} + Ω_{1} {F C F}_{t} + Ω_{2} {E S G}_{t - 1} + Ω_{3} {F C F}_{t} * {E S G}_{t - 1} + {Σ C o n t r o l s}_{t} + ɛ_{t}

(2A)

{Δ C a s h}_{t} = ϝ_{0} + ϝ_{1} {F C F}_{t} + ϝ_{2} {E N V}_{t - 1} + ϝ_{3} {F C F}_{t} * {E N V}_{t - 1} + {Σ C o n t r o l s}_{t} + ɛ_{t}

(2B)

{Δ C a s h}_{t} = ρ_{0} + ρ_{1} {F C F}_{t} + ρ_{2} {S O C}_{t - 1} + ρ_{3} {F C F}_{t} * {S O C}_{t - 1} + {Σ C o n t r o l s}_{t} + ɛ_{t}

(2C)

{Δ C a s h}_{t} = с_{0} + с_{1} {F C F}_{t} + с_{2} {G O V}_{t - 1} + с_{3} {F C F}_{t} * {G O V}_{t - 1} + {Σ C o n t r o l s}_{t} + ɛ_{t}

(2D)

FCF is a firm’s free cash flow determined as operating profit before depreciation and after interest, taxes, dividends, and other uses of cash. Control variables included in equation (2A) are BM, SIZE, CAPEX, ACQ, ΔNWC, and Δshort-term debt, along with the industry and year dummies. All financial variables are deflated by the MVA. Explanation of the primary and control variables of Equations (2A)–(2D) are provided in the Appendix.

If ESG performance increases (decreases) a firm’s financial flexibility, firms with higher (lower) ESG performance should save lesser (more) cash flows. Therefore, the coefficient on the interaction variables between FCF and lagged ESG scores (of composite and individual ESG dimensions) shall be less (more) than zero.

ESG performance and investment-cash-flow sensitivity

{C F S I}_{t} = ʂ_{0} + ʂ_{1} {E S G}_{t - 1} + {Σ C o n t r o l s}_{t} + ɛ_{t}

(3A)

Investment-cashflow sensitivity (CFSI) is determined using equation (3A) proposed by Hovakimian and Hovakimian (2009). PPE is included as a control because firms with more assets have better access to financial markets and have less investment-cashflow sensitivity. RET is a proxy for firm performance, as performance is inversely related to investment constraints. BM and R&D are proxies for growth opportunities. SIZE and DIVD are included as controls, respectively, for big-size and dividend-paying firms. LEV, OIVOL, and RETVOL are also included as controls because firms with a higher level of leverage, high cash-flow risk, and idiosyncratic risks may have more sensitivity in cash flows. The model variables are deflated by MVA. Industry and year dummies are also the control variables in the model.

{C F S I D U M}_{t} = ҟ_{0} + ҟ_{1} {E S G}_{t - 1} + {Σ C o n t r o l s}_{t} + ɛ_{t}

(3B)

{C A P E X}_{t} = һ_{0} + һ_{1} {E S G}_{t - 1} + {Σ C o n t r o l s}_{t} + ɛ_{t}

(3C)

In equation (3B), CFSIDUM is a dummy variable with a value of 1 if the CFSI value exceeds 5%, else 0. In equation (3C), CAPEX is the dependent variable. All other variables in Equations (3A) and (3B) are the same as those in equation (3A). Explanation of the primary and control variables of Equations (3A)–(3C) are provided in the Appendix. If ESG performance increases (decreases) firms’ financial flexibility, firms with higher (lower) ESG performance will have lower (higher) investment-cashflow sensitivity. Therefore, the coefficienton

{E S G}_{t - 1}

shall be less (more) than zero in Equations (3A) and (3B) and more (less) than zero in equation (3C).

ESG performance & financing decisions

The study tests whether ESG performance (Hypothesis 4) predicts firms’ choice of debt financing using equation (4A).

{D / E I s s u e}_{t} = ψ_{0} + ψ_{1} {E S G}_{t - 1} + ψ ({L e v e r a g e}_{t} - {L e v e r a g e}_{t - 1}) + {Σ C o n t r o l s}_{t} + ɛ_{t}

(4A)

D/EIssue is a binary variable that takes a value of 1 or 0. In estimating equation (4A), the model considers debt and equity issuances (D/EIssue) of more than 5% of MVA. The difference between leverage and target leverage is added as a control because firms with less (more) leverage have higher chances of raising debt (equity). The leverage used in equation (4A) is estimated using equation (4B). The target leverage is predicted using equation (4B) and its residual value is considered as the difference between actual and target leverage. PPE is a proxy for asset tangibility, which increases the firm’s ability to carry debt. OI and RET are controls of firm performance, and R&D is the control for product/service uniqueness. Firms carry forward net operating losses (NOL) that minimize their tax and reduce their tax advantage on interest. NOL is included as a control variable. Because firms with volatile operations opt for less debt in capital structure, OIVOL is added as a control. Similarly, RETVOL is included to proxy for idiosyncratic risk because firms with high risk rely less on leverage. ILEV is another control since firms are inclined to tune their capital structure to approach industry median leverage (Hovakimian et al., 2001).

{L e v e r a g e}_{t} = Ґ_{0} + Ґ_{1} {P P E}_{t} + Ґ_{2} {O I}_{t} + Ґ_{3} {R E T}_{t} + Ґ_{4} {B M}_{t} + Ґ_{5} {R & D}_{t} + Ґ_{6} {S I Z E}_{t} + Ґ_{7} {D I V D}_{t} + Ґ_{8} {N O L}_{t} + Ґ_{9} {O I V O L}_{t} + Ґ_{10} {R E T V O L}_{t} + Ґ_{11} {I L E V}_{t} + Ґ_{12} {IDummy}_{t} + ɛ_{t}

(4B)

If ESG performance increases (decreases) firms’ financial flexibility, firms with higher (lower) ESG performance are more likely to issue debt for external financing. Therefore, the coefficient on ESGt-1 shall be more (less) than zero in equation (4A). The debt issue of firms is regressed on ENV, SOC, and GOV individually in Equations (4C)–(4E), respectively, to assess the independent impact of ESG dimensions on financing decisions.

{D / E I s s u e}_{t} = ˠ_{0} + ˠ_{1} {E N V}_{t - 1} + ˠ_{2} ({L e v e r a g e}_{t} - {L e v e r a g e}_{t - 1}) + {Σ C o n t r o l s}_{t} + ɛ_{t}

(4C)

{D / E I s s u e}_{t} = ϛ_{0} + ϛ_{1} {S O C}_{t - 1} + ϛ_{2} ({L e v e r a g e}_{t} - {L e v e r a g e}_{t - 1}) + {Σ C o n t r o l s}_{t} + ɛ_{t}

(4D)

{D / E I s s u e}_{t} = Ҁ_{0} + Ҁ_{1} {G O V}_{t - 1} + Ҁ_{2} ({L e v e r a g e}_{t} - {L e v e r a g e}_{t - 1}) + {Σ C o n t r o l s}_{t} + ɛ_{t}

(4E)

Control variables in Equations (4C)–(4E) are the same as those in equation (4A). A detailed explanation of the primary and control variables of Equations (4A)–(4E) is in the Appendix.

ESG performance & payout decisions

{Δ P A Y O U T}_{t + 1} = ϫ_{0} + ϫ_{1} {Δ C A S H}_{t} + {ϫ_{2} C A S H}_{t} + {ϫ_{3} E S G}_{t - 1} + ϫ_{4} {Δ C A S H}_{t} * {E S G}_{t - 1} + {Σ C o n t r o l s}_{t} + ɛ_{t}

(5A)

If ESG performance increases (decreases) the firms’ financial flexibility, high ESG firms having an increase (decrease) in cash will be more capable of increasing (decreasing) payout. Therefore, the coefficient on $ϫ_{4} {Δ C A S H}_{t} * {E S G}_{t - 1}$ shall be more (less) than zero in equation (5A). Control variables of Equation (1A) and Equation (5A) are the same because the liquidity of the firm impacts both its cash changes and changes in payouts. The ΔPAYOUT_t+1 is regressed on ENV, SOC, and GOV individually in Equations (5B)–(5D), respectively, to assess the independent impact of ESG dimensions on payout decisions.

{Δ P A Y O U T}_{t + 1} = Ϯ_{0} + Ϯ_{1} {Δ C A S H}_{t} + {Ϯ_{2} C A S H}_{t} + Ϯ_{3} {E N V}_{t - 1} + Ϯ_{4} {Δ C A S H}_{t} * {E N V}_{t - 1} + {Σ C o n t r o l s}_{t} + ɛ_{t}

(5B)

{Δ P A Y O U T}_{t + 1} = ӻ_{0} + ӻ_{1} {Δ C A S H}_{t} + {ӻ_{2} C A S H}_{t} + ӻ_{3} {S O C}_{t - 1} + ӻ_{4} {Δ C A S H}_{t} * {S O C}_{t - 1} + {Σ C o n t r o l s}_{t} + ɛ_{t}

(5C)

{Δ P A Y O U T}_{t + 1} = Ԏ_{0} + Ԏ_{1} {Δ C A S H}_{t} + {Ԏ_{2} C A S H}_{t} + Ԏ_{3} {G O V}_{t - 1} + Ԏ_{4} {Δ C A S H}_{t} * {G O V}_{t - 1} + {Σ C o n t r o l s}_{t} + ɛ_{t}

(5D)

Control variables of equations 5B, 5C, and 5D have already been defined and are the same as those in equation (1A). Table 2 shows the correlations among the variables of this study.

Table 2.

Correlation matrix.

Variables	Size	Ke	Kd	BM	D/EISSUE	Cash	R&D	NWC	Capex	ACQ	CF	CFVOL	DIVD	FCF	PPE	R&D	OI	LY OI/TA	OIVOL	DIVDCHG	LEV	RET	MVA	LEV-Prediceted LVA	RETVOL
Size	1.000
Ke	0.135	1.000
Kd	−0.105	−0.344	1.000
BM	0.107	0.388	−0.206	1.000
D/EISSUE	0.162	0.067	−0.001	−0.008	1.000
Cash	0.044	0.463	−0.277	0.848	−0.149	1.000
R&D	−0.049	−0.177	0.135	0.011	−0.218	−0.021	1.000
NWC	0.059	0.101	0.133	0.045	0.278	−0.078	0.132	1.000
Capex	−0.046	−0.017	−0.043	−0.050	−0.132	−0.056	0.525	0.023	1.000
ACQ	−0.064	0.181	−0.054	0.087	0.096	0.091	0.095	0.010	0.076	1.000
CF	−0.353	−0.412	0.074	−0.370	−0.217	−0.315	0.238	−0.131	0.092	−0.106	1.000
CFVOL	−0.012	−0.240	0.079	−0.135	−0.110	−0.158	−0.137	−0.272	−0.165	−0.370	0.037	1.000
DIVD	0.509	−0.014	0.068	−0.475	0.087	−0.324	−0.038	−0.016	0.027	−0.042	0.046	−0.026	1.000
FCF	−0.106	0.194	−0.150	0.188	−0.497	0.341	0.139	−0.437	0.056	0.038	0.175	−0.061	−0.072	1.000
PPE	0.151	0.057	−0.298	0.368	0.247	0.240	−0.062	−0.337	0.026	0.132	−0.140	−0.051	−0.063	0.112	1.000
R&D	0.029	0.181	−0.054	0.655	−0.126	0.568	0.698	0.111	0.331	0.106	−0.092	−0.167	−0.301	0.181	0.192	1.000
OI/MVA	−0.117	−0.419	0.204	−0.359	−0.211	−0.343	−0.008	−0.136	0.005	−0.395	0.492	0.512	0.123	−0.013	−0.367	−0.227	1.000
LY OI/MVA	−0.079	−0.413	0.208	−0.304	−0.128	−0.303	0.010	−0.158	0.039	−0.443	0.330	0.542	0.112	−0.034	−0.271	−0.175	0.930	1.000
OIVOL	0.190	−0.132	0.083	−0.063	−0.041	−0.095	0.015	−0.223	−0.026	−0.331	−0.059	0.602	0.098	0.013	0.087	0.003	0.439	0.572	1.000
DIVDCHG	0.070	0.004	−0.225	−0.170	−0.101	−0.083	0.002	−0.038	0.163	−0.061	−0.124	0.078	0.219	−0.009	−0.099	−0.124	−0.048	−0.121	−0.197	1.000
LEV	0.253	0.338	−0.087	0.333	0.603	0.028	−0.239	0.388	−0.134	0.119	−0.450	−0.180	−0.076	−0.345	0.461	0.033	−0.432	−0.347	−0.097	−0.187	1.000
RET	0.094	−0.174	0.198	−0.155	0.002	−0.117	−0.018	0.046	−0.127	0.016	0.034	−0.198	0.175	−0.105	−0.146	−0.163	0.043	−0.013	−0.224	−0.073	−0.163	1.000
MVA	0.348	−0.107	0.056	−0.108	0.434	−0.276	−0.246	0.131	−0.161	−0.178	−0.194	0.298	0.141	−0.498	0.246	−0.280	0.128	0.196	0.339	−0.120	0.432	0.063	1.000
LEV-prediceted LVA	0.092	−0.022	0.276	−0.080	0.434	−0.214	0.102	0.351	0.103	0.145	−0.134	−0.198	0.239	−0.361	0.147	0.053	−0.227	−0.133	−0.033	−0.165	0.538	−0.099	0.034	1.000
RETVOL	0.101	0.546	−0.343	0.264	0.057	0.172	−0.163	0.173	−0.035	0.093	−0.328	−0.168	−0.084	0.180	0.143	0.096	−0.397	−0.396	−0.084	0.008	0.419	−0.355	−0.089	−0.160	1.000

Source: Authors’ own work.

Empirical analysis

ESG performance & corporate liquidity decisions

Table 3 reports the results of Equations (1A)–(1D) used to explore the relationship between ESG performance and liquidity decisions of the firms. Panel A results show that high ESG performance is related to high cash holdings (coefficient = 0.0033, t-statistic = 2.159), which is inconsistent with H1. The firm performance on Environmental (coefficient 0.0024; p-value <0.01) and Social (coefficient 0.0014; p-value <0.01) dimensions are also positively related to corporate cash holdings. The governance performance is negatively related to corporate cash holdings, but the coefficient is statistically insignificant.

Table 3.

ESG performances and liquidity decisions.

Panel A: Liquidity Model
	Model 1A	Model 1B	Model 1C	Model 1D
Variables	Cash	Cash	Cash	Cash
Intercept	0.166*** (3.778)	0.184*** (4.198)	0.181*** (4.093)	0.183*** (4.003)
ESG	0.003** (2.159)
E		0.0024*** (3.623)
S			0.0014*** (2.655)
G				−0.0001 (−1.232)
BM	−0.003*** (−56.989)	−0.003*** (−58.179)	−0.003*** (−56.876)	−0.003*** (−57.372)
R&D	0.029** (2.008)	0.028** (2.003)	0.029** (2.102)	0.024** (2.001)
SIZE	−0.011*** (−3.266)	−0.008** (−2.331)	−0.012*** (−3.524)	−0.009*** (−2.717)
CF	−0.122** (−2.414)	−0.125** (−2.545)	−0.124** (−2.468)	−0.141*** (−2.786)
RET	−0.015 (−0.755)	−0.011 (−0.583)	−0.014 (−0.691)	−0.016 (−0.818)
NWC	−0.029** (−2.246)	−0.024^* (−1.908)	−0.029** (−2.328)	−0.033*** (−2.732)
CAPEX	−0.103** (−2.180)	−0.554*** (−2.982)	−0.177** (−2.311)	−0.241*** (−2.818)
ACQ	−0.138 (−0.882)	−0.234 (−1.519)	−0.131 (−0.842)	−0.107 (0.681)
LEV	−0.012** (−2.141)	−0.015** (−2.344)	−0.0017** (−2.046)	−0.0016** (−2.373)
CFVOL	0.282** (2.370)	0.329*** (2.806)	0.309*** (2.954)	0.279** (2.330)
RETVOL	−0.002** (−2.019)	−0.001** (−2.012)	−0.003** (−2.026)	−0.004** (−2.045)
DIVD	−0.004 (−0.364)	−0.010 (−0.817)	−0.005 (−0.435)	−0.011 (−0.852)
Industry and year	YES	YES	YES	YES
R-squared	0.445	0.447	0.446	0.395
F Sig	0	0	0	0
F value	41.951	42.161	42.106	38.952
Panel B: Cash retention model
	Model 2A	Model 2B	Model 2C	Model 2D
Variables	ΔCash	ΔCash	ΔCash	ΔCash
Intercept	−0.0027 (−0.171)	−0.0087 (−0.556)	−0.0034 (−0.219)	−0.0034 (−0.213)
FCF	0.070^* (1.665)	0.071^* (1.667)	0.107^* (1.693)	0.081^* (1.756)
ESG	0.0035^* (1.738)
E		0.0012** (2.209)
S			0.0004^* (1.902)
G				0.0003 (0.530)
FCF^*ESG	0.0068^* (1.723)
FCF^*E		0.0018^* (1.664)
FCF^*S			0.0012^* (1.732)
FCF^*G				0.000 (1.069)
BM	−0.0018^* (−1.926)	−0.0011** (−2.356)	−0.003^* (−1.763)	−0.002*** (−2.685)
Size	−0.0060** (−2.430)	−0.0051*** (−2.807)	−0.006** (−2.468)	−0.003*** (−3.228)
ΔNWC	−0.0431*** (−3.052)	−0.037*** (−2.830)	−0.042*** (−3.220)	−0.045*** (−3.093)
CAPEX	−0.155 (−0.626)	−0.167 (−0.678)	0.145 (0.586)	0.121 (0.486)
ACQ	−0.019 (−0.267)	−0.0138 (−0.198)	−0.015 (−0.222)	−0.012 (−0.176)
ΔSTD	0.002 (0.597)	0.0025 (0.612)	0.003 (0.908)	0.002 (0.4410)
Industry and year	Yes	Yes	Yes	Yes
R-squared	0.553	0.592	0.583	0.599
F sig	0	0	0	0
F value	97.604	99.250	98.951	99.681

^*, **, *** represent significance at 10%, 5% and 1% respectively; values in parenthesis are t-values.

Source: Authors’ own work.

The results of Equations (2A)–(2D) which examine the association between ESG performance and firms’ propensity to save are in Panel B of Table 3. With an ESG coefficient significant at 10%, the high ESG performance of firms depicts their greater propensity to save cash. Environmental (0.0012 p-values <0.05) and Social (0.0004; p-value <0.10) dimensions predict higher cash retention of firms, but Governance (GOV) performance does not indicate the firms’ cash saving tendency. These results reject H2 and suggest that ESG performance is a positive predictor of cash retention by firms. The results of most of the control variables of Equations (1A)–(1D) and (2A)–(2D) are consistent with the findings in the prior literature.

ESG performance & investment-cashflows sensitivity (CFSI)

The test results of Equations (3A)–(3C) are reported in Table 4. The equation (3C) result indicates that high ESG firms incur more capital expenditures. Model 3 A result shows high ESG performing firms have lesser investment-cashflows sensitivity (coefficient = −0.008; p-value <0.05). Establishing the robustness of the equation (3A) results, using 0.05 as the threshold CFSI, when CFSIDUM is estimated as a binary variable with a value of 1 for CFSI>0.05 and 0 otherwise and use it as the dependent variable in logit regression equation (3B), the test result does not change. Results of Equations (3A)–(3C) are consistent with Hypothesis H3, which suggests that an increase in ESG performance increases the financial flexibility of firms by reducing their dependence on internal cash flows for investing in profitable opportunities. The results of the control variables in equation (3A)–(3C) are similar to findings in the popular literature. Size (SIZE), dividend payments (DIVD), asset tangibility (PPE), and profitability (OI) are negatively associated, whereas leverage (LEV) and business risks (OIVOL) are positively associated with the investment-cashflows sensitivity of firms.

Table 4.

ESG performance and cash flow sensitivity of investment.

Cash-flow sensitivity of investment	Model 3A	Model 3B	Model 3C
Variables	CFSI	CFSIDUM	CAPEX
Intercept	0.006** (1.997)	0.006^* (1.887)	−0.007^* (−1.698)
ESG	−0.008** (−2.053)	−0.009** (−2.091)	0.006^* (1.816)
BM	−0.0025^* (−1.818)	−0.0039^* (−1.798)	−0.012^* (−1.698)
R&D	−0.0003 (0.987)	−0.0004 (0.898)	0.0008*** (3.289)
Size	−0.0047^* (−1.724)	−0.0038^* (−1.716)	−0.0042^* (−1.773)
RET	−0.0004 (−0.834)	−0.0004 (−0.838)	−0.0011 (−1.113)
LEV	0.0009^* (1.764)	0.0008^* (1.668)	0.0011** (1.995)
OI	−0.321^* (−1.702)	−0.334^* (−1.721)	0.412** (1.987)
PPE	−0.0081** (−2.001)	−0.0084** (−2.114)	−0.091** (−2.013)
OIVOL	0.0084** (1.921)	0.0095*** (2.721)	0.0078^* (1.842)
RETVOL	0.0021 (0.812)	0.0037 (0.912)	0.0098 (0.721)
DIVD	−0.0065^* (−1.731)	−0.0069^* (−1.801)	0.0012 (1.102)
Industry and year	YES	YES	YES
R-squared	0.218	0.293	0.342

^*, **, *** represent significance at 10%, 5% and 1% respectively; values in parenthesis are t-values.

Source: Authors’ own work.

ESG performance & financing decisions

Table 5 reports the results of Equations (4A)–(4E), used to estimate whether ESG performance influences the financing decisions of firms. Results suggest that firms rated high on ESG performance are more inclined to raise external finance via debt than equity. Analysis of ESG dimensions reveals ENV and GOV dimensions have independent positive effects on debt issues of firms, significant at 1% and 10%, respectively. The SOC dimension does not affect the debt-issuing decisions. While the result for the impact of ENV on debt financing is similar to Hamrouni et al. (2019), results for GOV and SOC dimensions are different. While the authors report a positive effect of SOC and no effect of GOV, the study documents no effect of SOC and a positive effect of GOV on the debt financing decisions of firms. Since empirical evidence of the mitigating impact of ESG performance on the cost of equity is heavy, this study additionally analyzes the effect of ESG performance on the cost of debt and equity of debt-issuing firms using the following equations given by Goh et al. (2017):

{K d}_{i, t} = δ_{0} + {δ_{1} E S G}_{i, t} + δ_{2} {D / EIssue}_{i, t} + δ_{3} {E S G * D / EIssue}_{i, t} + I N D + Y e a r + e_{\begin{array}{l} i, t \end{array}}

(6a)

{K e}_{i, t} = δ_{0} + {δ_{1} E S G}_{i, t} + δ_{2} {D / EIssue}_{i, t} + δ_{3} {E S G * D / EIssue}_{i, t} + I N D + Y e a r + e_{\begin{array}{l} i, t \end{array}}

(6b)

Table 5.

ESG performance and financing decisions.

	Model 4A	Model 4C	Model 4D	Model 4E
Variables	Debt/Equity issue	Debt/Equity issue	Debt/Equity issue	Debt/Equity issue
Intercept	−1.139*** (−4.458)	−1.167*** (−4.52)	−1.184*** (−4.593)	−1.011*** (−3.783)
ESG	0.0015** (2.536)
ENV		0.0016*** (2.714)
SOC			0.001 (1.228)
GOV				0.0013^* (1.664)
LEV-predicted LEV	0.870*** (9.704)	0.879*** (9.686)	0.883*** (9.940)	0.870*** (9.734)
PPE	−0.037 (−0.832)	−0.040 (−0.896)	−0.044 (−0.976)	−0.031 (−0.686)
OI	1.204*** (5.242)	1.235*** (5.274)	1.245*** (5.360)	1.068*** (4.378)
OIVOL	−1.304^* (−1.960)	−1.256^* (−1.883)	−1.196^* (−1.803)	−1.320** (−1.985)
R&D	0.038 (0.023)	−0.328 (−0.200)	−0.237 (−0.145)	0.119 (0.072)
BM	0.048*** (5.336)	0.049*** (5.343)	0.049*** (5.437)	0.042*** (4.469)
Size	0.130*** (6.810)	0.125*** (6.565)	0.130*** (6.606)	0.120*** (6.583)
DIVD	−0.206*** (−2.917)	−0.198*** (−2.805)	−0.204*** (−2.887)	−0.206*** (−2.918)
NOL	−0.692*** (−3.892)	−0.583*** (−2.943)	−0.434 (−1.243)	−0.712** (−2.032)
RETVOL	1.751*** (3.275)	1.757*** (3.266)	1.798*** (3.362)	1.702*** (3.171)
Industry and year	Yes	Yes	Yes	Yes
R-squared	0.407	0.405	0.407	0.409
F Sig	0	0	0	0
F value	23.612	23.322	23.479	23.678

^*, **, *** represent significance at 10%, 5% and 1% respectively; values in parenthesis are t-values.

Source: Authors’ own work.

The results from Equations (4F) and (4G) are in Table 6. It is seen that the coefficient on ESG is significant and negative for both the cost of equity and the cost of debt, suggesting that both equity and debt issuers benefit from ESG performance in mitigating their cost of capital. The coefficient on the interaction term between ESG and D/EIssue (Coefficient = −0.0003; t-value −2.294) is negative and significant for the cost of debt but not for the cost of equity, suggesting that the mitigation in the equity cost from ESG performance is similar for debt issuers and equity issuers but, the reduction in the debt cost is significantly more for debt issuers than equity issuers. The results in Table 6 support the main results reported in Table 5 and help to explain why high ESG-performing firms are more likely to use debt for external financing. The findings on the association between ESG performance and the financing decision of firms are consistent with Allman and Won (2021), who report an increased debt-raising ability of firms from their high ESG performance but no such impact on their ability to raise new equity. The results in Tables 5 and 6 support Hypothesis 4. Consistent with the findings in the popular literature, analysis of the control variables also finds that big (SIZE), profitable (OI), and underleveraged firms (LEV-Predicted LEV) are more likely to issue debt, whereas dividend-paying (DIVD), loss-making (NOL), and high risk (OIVOL) firms are more likely to issue equity for external financing.

Table 6.

ESG performance and cost of financing.

	Model 4F	Model 4G
	Cost of debt $K d$	Cost of equity $K e$
Variables	Co-efficient (t-stat)	Co-efficient (t-stat)
Intercept	0.0386*** (6.244)	0.0156*** (11.62)
ESG	−0.0006*** (−3.246)	−0.0002*** (−2.900)
D/EIssue	0.0034 (0.0489)	−0.0149 (1.013)
ESG^*D/EIssue	−0.0003** (−2.294)	0.0003 (1.434)
Industry	Yes	Yes
Year	Yes	Yes
R-square	0.1891	0.0239
ESG + ESG^* D/EIssue	−0.0003 (0.952)	0.0001 (1.466)

^*, **, *** represent significance at 10%, 5% and 1% respectively; values in parenthesis are t-values.

Source: Authors’ own work.

ESG performance and payout decision

Table 7 reports the results from Equations (5A)–(5D) to examine the association between ESG performance and payout decisions of the firms. The study finds that an increase in cash flows causes increased payouts, but in high ESG-performing firms, an increase in payouts following an increase in cash flows is low (ΔCash*ESG = −0.032; p-value <0.01). Results, thus, reject Hypothesis 5. Although coefficients on Environmental and Social dimensions are small, they are statistically significant in Equations (5B) and (5C). The governance dimension has an insignificant coefficient for influencing payouts, but the interaction variable between change in cash and governance is significant at 1%. The Table 7 results reject an increase in the dividend-paying ability of high ESG-performing firms following an increase in their cash flows, as postulated in H5. The results are in contrast to Benlemlih (2019) and Cheung et al. (2018), who report increased payouts from increasing ESG performance but are similar to findings of stable dividend payments by ESG-performing firms suggested by Samet and Jarboui (2017), and Verga Matos et al. (2020). The results of the control variables of equation (5A)–(5D) are similar to findings in the popular literature.

Table 7.

ESG performance and payout decisions.

	Model 5A	Model 5B	Model 5C	Model 5D
Variables	Δpayout	Δpayout	Δpayout	Δpayout
Intercept	−0.012 (−0.193)	−0.077 (−1.053)	−0.008 (−0.135)	−0.029 (−0.334)
Cash	0.473*** (6.165)	0.578*** (6.308)	0.504*** (7.012)	0.081*** (7.756)
ΔCash	0.886*** (37.812)	0.632*** (30.432)	0.267*** (40.698)	0.488*** (34.504)
ESG	−0.0026** (−2.408)
ΔCash^*ESG	−0.032*** (−3.569)
ENV		−0.0007*** (−3.250)
ΔCash^*ENV		−0.090*** (−14.263)
SOC			−0.0003^* (−1.720)
ΔCash^*SOC			−0.020*** (−3.290)
GOV				0.0005 (1.069)
ΔCash^*GOV				0.0017*** (2.685)
BM	−0.0015^* (−1.856)	−0.002^* (−1.836)	−0.0012^* (−1.822)	−0.0016** (−2.191)
R&D	−0.0001 (−0.532)	−0.0002 (−0.518)	−0.0001 (−0.530)	−0.0001 (−0.530)
Size	−0.001 (−0.253)	−0.0041 (−0.715)	−0.0002 (−0.046)	−0.0007 (−0.109)
CF	−0.065^* (−1.930)	−0.117^* (−1.912)	−0.095^* (−1.939)	−0.089^* (−1.938)
RET	0.025^* (1.913)	0.036^* (1.912)	0.021^* (1.820)	0.040** (1.979)
NWC	0.005 (0.303)	0.0058 (0.383)	0.006 (0.364)	0.0059 (0.347)
CAPEX	−0.123 (−0.156)	−0.556 (0.597)	−0.376 (−0.510)	−0.463 (−0.433)
ACQ	−0.062 (−0.289)	−0.102 (−0.400)	−0.033 (−0.163)	−0.040 (−0.138)
LEV	−0.0005** (−2.024)	−0.009** (−2.237)	−0.019*** (−2.931)	−0.006** (−2.200)
CFVOL	−0.117 (−0.708)	−0.122 (−0.624)	−0.177 (−1.138)	−0.061 (−0.274)
RETVOL	−0.068 (−0.495)	−0.364 (−0.273)	−0.060 (−0.470)	−0.262 (−1.420)
DIVD	0.013 (0.786)	0.0003 (0.014)	0.013 (0.827)	0.025 (1.100)
Industry and year	Yes	Yes	Yes	Yes
R-squared	0.698	0.616	0.671	0.585
F Sig	0	0	0	0
F value	38.974	36.714	36.243	29.789

^*, **, *** represent significance at 10%, 5% and 1% respectively; values in parenthesis are t-values.

Source: Authors’ own work.

Granger causality test & control for endogeneity

Panel A and B results of Table 8 confirm a unidirectional causal association between ESG performance and liquidity decisions and between ESG performance and payout decisions, respectively. Results of Table 8C show that ESG performance and debt financing have a bi-directional causal association even though individual ESG dimensions show a unidirectional effect on the debt issues of the firms. To overcome the reverse causality problem in the association between ESG performance and debt issue decisions of firms, this study re-estimated equation (4A) using 2-year lagged values of ESG performance scores. Results (untabulated) were consistent with the main findings but with lower statistical significance levels.

Table 8.

Granger causality test results.

Discussions

The findings from this study support the slack resources theory suggesting enhanced engagement in ESG activities requires financial slack. A positive association of cash holdings with environmental and social performance indicates that high ESG-performing firms need to preserve cash for ESG performance-boosting activities such as innovations for minimizing ESG risks, creating quality products, enhancing social performance, and adhering to safety norms for the public and workforce. Higher employment of cash in ESG activities may increase the social and environmental performance of the firms but may cause them a financial loss or muted financial returns. Wee et al. (2020) find that high ESG levels are associated with lesser cash flows, which explains the study’s result of higher cash holdings by high ESG-performing firms. Since the markets value cash holdings of high ESG-performing firms more than the other firms (Perez-de-Toledo & Bocatto, 2019), their cost of withholding cash is lower. Arouri and Pijourlet (2017) argue that the reductions in the cash holding costs of high ESG firms are only in countries with proper governance structures and adequate shareholder protection. Since governance structures in the Indian market are still underdeveloped, withholding cash to invest in ESG innovations and protect against the risks of failures would cause a higher cost, indicating ESG activities as financially constraining for Indian firms. The finding of higher capital expenditures by high ESG firms is consistent with the result on the ESG-cash holdings association. The study finds high capital expenditures but low investment-cashflow sensitivity in high ESG-performing firms. Findings of high cash holdings, greater use of low-cost debt financing, and no increase in dividends despite positive cash flow changes in high ESG-performing firms explain their lesser investment-cashflow sensitivity. Saeed (2021) documents that social initiatives are valued but cause firms to decide on low payouts to preserve cash for future investment needs. The overall results indicate financial benefits for firms from their ESG performance through reductions in their cost of capital. It also suggests a higher resource requirement for making ESG investments and bearing related risks.

Examination of the individual dimensions of ESG reveals that the effects of ENV and SOC performance on the financial decisions of firms are generally consistent with that of the composite ESG performance. Environmental performance significantly affects all the financial decisions that this study investigates. Governance is the only dimension that, barring the case of financing decisions, shows results opposite to composite ESG performance. In contrast to composite ESG and other ESG dimensions, GOV is linked with the increased dividend-paying ability of firms following an increase in cash flows, indicating its independent effect on the payout decision of firms. While the study finds ESG, ENV, and SOC performance to be financially more constraining than enabling for firms, GOV performance is more likely to increase the financial flexibility of firms in emerging markets like India.

This study answers whether firms with higher ESG performance are more likely to increase dividends and issue debt and be less likely to withhold cash and face investment-cashflows sensitivity. It, therefore, informs the current debate around the role of ESG performance in a firm’s financial decisions. The findings from this study have implications for theory and practice.

Implications

Theoretical implications

This study significantly contributes to the literature on ESG performance and corporate financial decision-making by offering several key insights. First, it demonstrates that both composite ESG performance and its dimensions—environmental, social, and governance—are linked to lower costs of debt and equity and reduced investment-cash flow sensitivity, suggesting that strong ESG performance provides financial benefits like lower borrowing costs and increased investment efficiency. It aligns with calls in the literature for more evidence of the economic advantages of ESG activities (Egginton and McBrayer, 2019; Eliwa et al., 2019). Second, the study provides a more nuanced perspective on financial flexibility by showing that while high ESG performance can reduce borrowing costs and investment cash flow sensitivity, it requires firms to maintain financial slack due to the resource-intensive nature of ESG-related innovations and risk management. This finding refines the slack resources view by highlighting the need for careful financial management to balance ESG commitments with liquidity. Third, it identifies the distinct impact of governance performance on financial decisions, particularly payout policies, unlike environmental and social performance, which align more closely with overall ESG scores. It adds depth to understanding how different aspects of ESG influence corporate strategy. Lastly, consistent with Lueg et al. (2019), the study shows that firms are more likely to increase ESG disclosures when issuing debt, emphasizing ESG’s role in enhancing transparency and shaping debt-related financial strategies.

Managerial implications

This study has several important implications for managers, investors, and regulatory agencies. For corporate managers, understanding the costs and benefits associated with ESG activities is crucial when deciding on ESG investments. This study is the first to provide empirical evidence on how both composite and individual dimensions of ESG performance affect firms’ financial decisions. The findings indicate that higher ESG performance can reduce investment cash flow sensitivity and lower the cost of debt. Therefore, managers should be encouraged to enhance ESG performance, as it can provide these financial advantages.

For investors, the study aligns with Patel et al. (2021), who found that investors may expect lower short-term growth potential in firms engaging in ESG investments and innovations. However, findings from this study show a positive association of ESG performance with stable profit sharing, increased capital expenditures, and higher cash holdings. It suggests that high ESG performance signals a better alignment of long-term interests between shareholders and other stakeholders, which is particularly important for investors prioritizing sustainable growth over short-term gains.

Finally, for regulatory agencies, the results underscore the importance of promoting ESG reporting among firms. Regulatory bodies should consider measures that encourage more transparent and comprehensive ESG disclosures, as this could improve market efficiency and investor decision-making by providing insights into a firm’s long-term strategy and risk management.

Conclusions & limitations

This study provides new insights into the complex relationship between ESG performance and corporate financial decision-making. The study analyzes a balanced panel dataset of 110 non-financial firms from 2014 to 2022 to examine the impact of ESG practices on corporate liquidity, investment cash-flow sensitivity, financing, and payout decisions. The empirical approach involves using panel regressions, as indicated by Hausman tests, to identify causal associations and Granger causality tests to explore both uni-directional and bi-directional effects. Additional tests, using 2-year lagged values to control for reverse causality, confirmed the robustness of the results.

The analysis reveals several key findings. High ESG performance reduces the cost of debt more than equity. Furthermore, strong ESG performance causes increased capital expenditures, lower investment cash-flow sensitivity, higher cash holdings, and reduced payouts of excess cash flows to shareholders. These results are consistent with the slack resources theory, suggesting that ESG-related innovations and risk-taking require significant financial slack, affecting financial decisions. The effects of performance on environmental and social dimensions are similar to the effects of overall ESG performance on corporate decisions, while governance performance uniquely impacts payout decisions.

The findings have important implications for practitioners and policymakers. For managers, the results underscore the strategic value of integrating ESG considerations into financial decision-making processes. For investors, the study highlights the importance of including ESG performance in their investment criteria, as firms with strong ESG scores tend to demonstrate greater financial resilience and lower risk, making them attractive investment targets. Additionally, the study underscores the need for policymakers to promote ESG disclosures and reporting standards to ensure transparency and encourage sustainable practices among firms. By fostering an environment that rewards strong ESG performance, regulators can drive corporate behavior toward greater sustainability and long-term value creation.

Despite the robustness of the analysis, this study has several limitations. The reliance on ESG performance data from Thomson Reuters may not align with the data commonly used by investors, potentially affecting the results if different data sources are employed. Future research should address this by utilizing a variety of ESG metrics and rating systems to assess their impact on this study’s findings. Additionally, the findings may be specific to a context and not generalizable to other markets. Replicating the study in different countries with varying institutional settings would be valuable for understanding the impact of diverse regulatory and governance frameworks on the findings on the association between ESG performance and financial decisions. Also, this study has overlooked qualitative aspects such as organizational culture and leadership attitudes. Future research could include in-depth case studies of firms with varying levels of ESG performance to explore how these qualitative factors influence managerial decision-making. Longitudinal studies could also examine how changes in ESG performance over time affect managerial decisions and organizational outcomes, providing insights into the evolution of long-term ESG strategies and their impact on management practices.

Footnotes

Acknowledgments

The infrastructural support provided by the FORE School of Management, New Delhi, in completing this paper is gratefully acknowledged.

Declaration of conflicting interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

ORCID iDs

Pratibha Wasan

Kalyani Mulchandani

Appendix

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