Corporate environmental, social and governance (ESG) scores and corporate liquidity management (CLM): evidence from Australia

Environmental, social and governance (ESG) scores have emerged as prominent global benchmarks for assessing the sustainability and ethical impact of corporate operations (Abdi et al., 2022). Growing regulatory pressures and increasing expectations from investors and other stakeholders have encouraged firms to integrate ESG considerations into their business strategies and corporate governance practices (Adeneye et al., 2023; Aladwan et al., 2024). Although ESG initiatives were initially driven by environmental concerns, their importance has expanded to broader aspects of corporate performance, including financial stability and liquidity management (Alareeni and Hamdan, 2020; Bianchi and Bigio, 2022; Feng et al., 2020; Issa and Hanaysha, 2023; La Rosa and Bernini, 2022; Sahu et al., 2024).

Recent studies suggest that firms with stronger ESG performance benefit from enhanced stakeholder trust, improved access to financing, lower borrowing costs, and reduced regulatory risk (Ali et al., 2022; Andrieș and Sprincean, 2023; Ben Ali and Chouaibi, 2024). These advantages may strengthen corporate liquidity management (CLM) by improving firms’ ability to meet short-term obligations and maintain financial flexibility. However, the relationship between ESG performance and CLM remains insufficiently understood. While a growing body of literature has examined the association between ESG performance and broader financial outcomes, relatively limited attention has been devoted to understanding how ESG performance relates to key liquidity management measures, including net working capital (NWC), operating cash flow (OCF) and the cash conversion cycle (CCC). Existing evidence remains fragmented and inconclusive, particularly in developed markets such as Australia (Horobeţ et al., 2023; Ben Ali and Chouaibi, 2024; Laghari et al., 2022).

Australia provides a particularly relevant setting for investigating this relationship. The country has a well-developed capital market and has experienced growing regulatory and stakeholder pressure regarding ESG disclosure and corporate sustainability practices. In addition, Australian Securities Exchange (ASX)-listed firms operate within an environment characterised by increasing transparency requirements and heightened investor attention to ESG performance. These features make Australia an appropriate empirical context through which to examine the broader relationship between ESG performance and CLM.

Accordingly, this study examines the association between ESG scores and CLM among ASX-listed firms during the 2010–2023 period. Specifically, the study investigates whether ESG performance is associated with NWC, OCF and the CCC, three widely used measures of CLM. Using a sample of 1,100 firm-year observations, the study employs advanced econometric techniques, including machine learning models, Heckman’s (1979) two-stage procedure and propensity score matching (PSM), to address potential endogeneity and selection bias concerns.

The findings indicate that firms with stronger ESG performance generally exhibit superior liquidity management. Specifically, firms with higher ESG scores tend to maintain more efficient working capital positions and shorter operating and CCCs, suggesting improved cash flow management and lower liquidity risk.

This study contributes to the literature in several ways. Firstly, it addresses a broader theoretical gap by examining the relationship between ESG performance and CLM, an area that has received considerably less attention than the ESG–financial performance relationship. Secondly, it provides comprehensive evidence from Australia, an important but underexplored market in the ESG literature. Thirdly, the study demonstrates how firm-specific characteristics influence the ESG–liquidity relationship, thereby offering a more nuanced understanding of the mechanisms through which ESG performance may affect financial outcomes. Finally, by employing advanced econometric techniques and recent ESG metrics, the study provides robust evidence regarding the financial implications of ESG practices for managers, investors and policymakers.

In seeking a reasonable answer to the question of whether corporate ESG scores have any impact on CLM, this study is grounded in two complementary theoretical perspectives – stakeholder theory and signalling theory – which together provide a robust framework for understanding the ESG–CLM relationship. While stakeholder theory emphasises the role of firm–stakeholder relationships in shaping liquidity outcomes, signalling theory highlights how ESG activities and disclosures convey information to external capital market participants and influence firms’ access to finance and liquidity conditions. Stakeholder theory explains how firms’ relationships with key stakeholder groups influence corporate performance and financial decision-making, including liquidity management (Freeman, 1984). Among its three approaches – descriptive, normative and instrumental – this study adopts the instrumental stakeholder perspective, which views ESG practices as strategic mechanisms that enhance firm value by strengthening stakeholder relationships and improving operational efficiency.

From an instrumental standpoint, strong ESG performance fosters trust and cooperation with employees, suppliers, customers, regulators and capital providers. These improved stakeholder relationships directly affect firms’ working capital dynamics by facilitating favourable trade credit terms, faster receivables collection, and more stable operational processes, thereby shortening the CCC. At the same time, enhanced employee engagement and governance quality improve cash flow predictability and resource allocation efficiency, enabling firms to maintain more stable and optimal levels of NWC.

Furthermore, superior ESG performance reduces perceived firm risk and information asymmetry, strengthening stakeholders’ confidence in firms’ long-term viability. This results in improved access to external finance, lower financing costs and greater financial flexibility, which reduces the need for precautionary liquidity buffers and supports more efficient OCF generation. Consistent with this argument, prior empirical evidence shows that firms with higher ESG scores experience enhanced stakeholder trust, reduced risk exposure, and superior liquidity-related outcomes (Ibikunle et al., 2016; Ali et al., 2022; Atif et al., 2022; Andrieș and Sprincean, 2023; Bissoondoyal-Bheenick et al., 2023; Almnadheh et al., 2025). Accordingly, stakeholder theory predicts that stronger ESG performance is associated with more efficient CLM, reflected in higher NWC stability, shorter CCC and improved OCF efficiency. Complementing this stakeholder-based perspective, signalling theory provides an additional market-based explanation by focusing on how ESG information is interpreted by external investors and creditors. Signalling theory explains how ESG performance and disclosure influence CLM through capital market channels (Bergh et al., 2014). High-quality ESG engagement and transparent disclosure act as credible signals of firm quality, effective risk management, and long-term orientation. Such signals reduce information asymmetry, improve investor confidence, and facilitate access to external financing at lower cost, thereby easing liquidity constraints and reducing reliance on precautionary cash holdings. Empirical evidence suggests that proactive ESG disclosure enhances transparency and supports more effective liquidity management, particularly in jurisdictions with strong regulatory frameworks (Drempetic et al., 2020; Oyewo, 2023; Saleh et al., 2025). However, the effectiveness of ESG signalling depends on the credibility, consistency and standardisation of reporting frameworks, as inconsistent metrics and weak alignment with financial strategy can limit the impact of disclosures on liquidity outcomes (Galeone et al., 2024; Horobeț et al., 2023; Agarwala et al., 2024).

Taken together, stakeholder theory and signalling theory provide complementary insights into how ESG performance can shape firms’ liquidity management through both real operational channels and capital market mechanisms.

The relationship between ESG factors and various financial outcomes has been a topic of interest in both academic research and corporate practice for decades. Scholars have explored how ESG performance impacts firm value (Abusharbeh et al., 2023; Aljughaiman et al., 2024; Andrieș and Sprincean, 2023) cost of finance (Giakoumelou et al., 2024; Horobeț et al., 2023); and risk management strategies (Adeneye et al., 2023; De Lucia et al., 2020). A substantial body of research highlights the dual value of ESG, showing that strong ESG performance not only contributes to societal well-being, but also enhances firm performance. For instance, Abdi et al. (2022), Adeneye et al. (2023) and Alareeni and Hamdan (2020) suggest that firms with robust ESG practices tend to achieve greater profitability and improved economic performance. Furthermore, firms with superior ESG scores experience reduced idiosyncratic risk (Ali et al., 2022; Andrieș and Sprincean, 2023); lower equity capital costs (Bissoondoyal-Bheenick et al., 2023; Buallay, 2019; Chen and Xie, 2022); higher payout ratios (De Lucia et al., 2020); and better access to capital (Atif et al., 2022; Dicuonzo et al., 2024; Galeone et al., 2024). These financial advantages underscore the role of ESG scores in enhancing corporate resilience and operational efficiency.

Despite studies conducted on ESG scores and firm operational efficiencies, research specifically examining the link between ESG scores and CLM is scarce. Emerging studies suggest that firms with higher ESG scores tend to have better access to liquidity owing to improved stakeholder trust and reduced perceived risk (Buallay, 2019; Oyewo, 2023). Furthermore, ESG performance appears to influence firms’ ability to secure funding on favourable terms, with this having a positive effect on liquidity management strategies (Almeida et al., 2013; Chen and Xie, 2022). For example, environmentally conscious firms have been found to experience lower capital constraints, indicating that ESG practices enhance both corporate reputation and financial resilience (He et al., 2023; Manita et al., 2018). These insights highlight the growing recognition of ESG dimensions as critical factors in shaping financial decision-making and liquidity management.

Similarly, ESG disclosures are gaining prominence in liquidity management. Firms that provide comprehensive ESG reports tend to attract sustainability-focused investors which strengthens their liquidity positions (Ali et al., 2022). Transparency is enhanced by ESG reporting as it reduces information asymmetry, thus building stakeholder trust, improving access to funding and mitigating liquidity risk (Galeone et al., 2024; Pedersen et al., 2021). However, it is worth noting that the effectiveness of ESG disclosures in predicting liquidity risks depends on the reliability of ESG ratings/scores and consistency in reporting standards (Drempetic et al., 2020).

Empirical evidence shows that firms with higher ESG scores often maintain higher cash reserves and have better access to credit facilities (Ibikunle et al., 2016; Oyewo, 2023). These findings highlight that ESG scores can serve as a signalling mechanism for investors, indicating a firm’s long-term financial stability and resilience (Baker et al., 2020; Friede et al., 2015). However, the relationship between ESG scores and liquidity risk varies across industries and regions. For example, the impact of ESG practices on liquidity risks may be more pronounced in sectors in which sustainability concerns are highly prioritised, such as financial services and manufacturing (Cho et al., 2021; Fang et al., 2018). Furthermore, some studies suggest that the relationship between ESG performance and liquidity risks may follow a non-linear pattern, requiring further exploration to understand its nuances (Luo, 2022; Meng-tao et al., 2023).

According to the non-linear relationship literature in ESG and financial performance, firms with either very low or very high ESG scores may face higher liquidity risks than those with moderate ESG scores. The rationale behind this pattern lies in the costs associated with implementing ESG practices, which may initially increase liquidity risks before yielding long-term financial benefits (Bose et al., 2021). Firms investing heavily in ESG practices may face short-term cash flow constraints owing to the upfront costs of sustainability initiatives. However, these investments are expected to pay off in the long run by improving stakeholder trust and reducing financing costs (Khalil et al., 2023). This finding highlights the complex trade-offs that firms must navigate when balancing ESG investments with liquidity management.

Despite a growing body of literature on the ESG performance–CLM relationship, significant research gaps remain, particularly regarding the applicability of ESG practices in emerging economies, with limited exploration of how ESG factors influence liquidity management in these regions (Ben Ali and Chouaibi, 2024; Horobeț et al., 2023; Laghari et al., 2022). Most studies have focused on developed markets generally; however, systematic empirical investigation of the ESG–CLM relationship using comprehensive liquidity metrics (NWC, OCF and CCC) and rigorous econometric methods remains limited, including within the Australian context (Ben Ali and Chouaibi, 2024; Horobeț et al., 2023; Laghari et al., 2022). Furthermore, a deeper investigation is needed into how specific ESG dimensions (environmental, social and governance) individually impact liquidity management practices (Adeneye et al., 2023). Addressing these gaps would provide a more comprehensive understanding of how ESG factors shape firms’ financial strategies in diverse regulatory environments.

Empirical evidence highlights the role of regulatory frameworks in shaping ESG practices, particularly in jurisdictions with stricter sustainability reporting requirements. Firms that proactively disclose their ESG performance are more likely to enhance transparency and reduce information asymmetry which can improve their access to financing with better management of their liquidity risk (Drempetic et al., 2020; Oyewo, 2023). However, scholars caution that the effectiveness of ESG disclosures hinges on the standardisation of reporting frameworks and the alignment of ESG practices with firms’ broader financial goals. Without consistent reporting standards, the impact of ESG disclosures on liquidity management may be limited (Galeone et al., 2024; Horobeț et al., 2023).

The relationship between ESG performance and CLM is a critical area of research with significant implications for financial management. While existing studies provide valuable insights, more research is needed to explore the specific mechanisms through which ESG factors influence liquidity management across different contexts and industries (Khalil et al., 2023), with these studies scarce in the context of Australia. Addressing these gaps could help firms to integrate ESG considerations into their liquidity management strategies, ultimately contributing to more sustainable financial practices.

Corporate ESG performance has emerged as an important determinant of firms’ financial health and liquidity management. Firms with higher ESG scores often demonstrate stronger operational efficiency, lower regulatory risk, and enhanced stakeholder trust, all of which contribute to more effective management of working capital. Prior studies show that firms with superior ESG performance tend to achieve better financial outcomes and profitability (Abdi et al., 2022; Adeneye et al., 2023; Alareeni and Hamdan, 2020; Wang et al., 2023). These benefits improve firms’ ability to maintain adequate current assets relative to current liabilities and support efficient liquidity management.

One mechanism through which ESG performance enhances liquidity is the reduction of environmental compliance costs and regulatory risks. Firms that proactively adopt ESG practices are less exposed to penalties and reputational damage, thereby preserving cash resources and improving financial flexibility. Furthermore, ESG-oriented firms often enjoy stronger relationships with investors, creditors and suppliers, leading to improved access to capital and more favourable financing conditions. In addition, growing consumer demand for sustainable products can increase revenues and cash inflows, while operational efficiencies derived from better resource utilisation and waste reduction further strengthen working capital management (Galeone et al., 2024; Giakoumelou et al., 2024).

Although ESG initiatives may require substantial upfront investments and generate short-term liquidity pressures, these temporary costs are generally outweighed by the long-term benefits associated with improved stakeholder confidence, reduced risk, and enhanced operational performance. Therefore, firms with stronger ESG performance are expected to maintain higher levels of NWC:

ESG performance can also influence firms’ OCFs through its impact on operational efficiency, risk management and stakeholder relationships. Firms with strong ESG practices are often better positioned to generate stable cash flows because they benefit from improved resource allocation, lower operational disruptions, and enhanced reputational capital. Ali et al. (2022) and Andrieș and Sprincean (2023) suggest that firms with higher ESG scores experience lower idiosyncratic risk, enabling more predictable financial management and cash flow generation.

Moreover, enhanced stakeholder trust may facilitate access to external financing and reduce financing constraints, allowing firms to operate more efficiently and manage liquidity requirements effectively. While the implementation of ESG initiatives may initially reduce available cash due to investment expenditures, the resulting improvements in operational efficiency and financial stability are expected to strengthen cash flow management over time. Consequently, firms with superior ESG performance are expected to exhibit more efficient OCF management:

The relationship between ESG performance and the CCC reflects the extent to which ESG practices improve firms’ ability to manage inventory, receivables and payables efficiently. Strong ESG performance enhances stakeholder relationships, including those with suppliers, customers and financial institutions, thereby facilitating smoother business operations and more efficient liquidity cycles. Firms with strong ESG credentials are more likely to experience favourable supplier terms, improved customer loyalty, and greater operational coordination, all of which contribute to shorter CCCs.

Conversely, poor ESG performance is often associated with operational inefficiencies, higher financing costs, greater regulatory risk and financial instability (Banerjee et al., 2020; Wang and Sarkis, 2017). These factors can lengthen inventory holding periods, delay cash collections, and increase liquidity pressures. Furthermore, misalignment between firms and external capital providers may increase uncertainty regarding future cash flows and financing arrangements, thereby extending liquidity cycles (Bose et al., 2021; Cordova et al., 2021).

Overall, firms with strong ESG performance are expected to manage liquidity cycles more efficiently and convert investments into cash more rapidly than firms with poor ESG performance:

This study investigates companies listed on the ASX. Table 1, Panel A outlines the sample selection process, in which the initial data set consisted of 7,168 firm-year observations from 2010 to 2023. As some companies did not have sufficient environmental and liquidity data, they were removed, with the final sample consisting of 1,100 firm-year observations.

Table 1, Panel B presents a breakdown of the sample by industry and year, highlighting the distribution of observations across various sectors. By excluding years prior to 2010, this study ensured access to a consistent data set that accurately reflected these evolving trends. The 14-year period makes it possible to perform a good longitudinal analysis, allowing our study to examine how ESG scores change over time and how corporate responsibility and financial performance change as is the case with rules and social expectations.

This study explores the factors that influence CLM through a detailed examination of dependent, independent and control variables. To evaluate CLM, this study employs several key metrics. Firstly, NWC represents the difference between a firm’s current assets and its liabilities, providing insight into the firm’s short-term liquidity capacity (Adeneye et al., 2023; Sikveland and Zhang, 2020). Secondly, the CCC measures the time required for a firm to convert its investments in inventory into cash flows from sales, encompassing the inventory conversion period, receivables collection period and payables deferral period (Alareeni and Hamdan, 2020; Bruna et al., 2022). Thirdly, OCF captures the average duration to convert inventory into sales and subsequently into cash, covering both the inventory holding period and the receivables collection period (Buallay, 2019; Drempetic et al., 2020). Together, these metrics – NWC, CCC and OCF – provide a comprehensive view of how a firm manages cash flow and liquidity. By analysing these indicators, this study highlights the interconnections between financial metrics and underscores the importance of efficient asset utilisation and cash flow management (Andrieş and Sprincean, 2023).

This study primarily examines the combined ESG score (ESGC) as the main independent variable, with this serving as a measure of ESG performance. This score encompasses three key dimensions: environmental (ESCORE), social (SSCORE) and governance (GSCORE). The environmental score (ESCORE) assesses a firm’s environmental performance through initiatives such as resource usage, green projects and carbon reduction efforts (Chen and Xie, 2022). The social score (SSCORE) evaluates the firm’s alignment with societal goals, focusing on labour practices, community engagement, customer satisfaction and ethical standards (Manita et al., 2018). The governance score (GSCORE) reflects governance practices, including board transparency, structure, regulatory compliance and shareholder engagement, while highlighting the quality of corporate governance (Liu et al., 2023). Together, these three pillars form the ESG combined score (ESGC), offering a holistic view of the firm’s overall ESG performance (Cheng et al., 2024). This variable is central to the understanding of how sustainability practices influence liquidity management.

This study incorporates several control variables that account for firm-specific characteristics and external factors that may influence liquidity management. Firm size (FS), measured by total assets, reveals a firm’s scale and financial capacity, potentially impacting its ability to invest in sustainability initiatives (Fuadah et al., 2022; Gillan et al., 2021; Yitayaw, 2021; Yu et al., 2018). Leverage (LVG), defined as the ratio of debt to equity, provides insight into a firm’s financial structure and risk profile, with these, in turn, influencing investment decisions (Kretzschmar et al., 2010; Tan et al., 2024). Coverage (COV) calculated as “income before extraordinary items + interest expenses” divided by interest expenses, indicates a firm’s ability to meet its interest obligations (Bruna et al., 2022; Horobeţ et al., 2023).

Furthermore, Beta (⁠$β$⁠), which represents the stock’s systematic risk relative to market volatility based on monthly returns, is included to account for market-related risks (Cheng et al., 2024). Return on assets (ROA), calculated as net income divided by total assets, highlights asset profitability and provides insight into how efficiently a firm utilises its assets (Adeneye et al., 2023). Other control variables include the dividend payout ratio (DPR), which measures the percentage of earnings distributed as dividends, reflecting the firm’s dividend policy (Bruna et al., 2022; Horobeţ et al., 2023). From a resource constraint perspective, firms with higher dividend payouts distribute a greater proportion of earnings to shareholders, which may reduce internally available funds for ESG-related sustainability investments and working capital management. We therefore expect a negative relationship between DPR and liquidity metrics such as NWC, as higher distributions reduce retained earnings and constrain short-term liquidity and board size (BSIZE), which indicates the total number of directors on a firm’s board, with this influencing the governance structure (Gillan et al., 2021). Larger boards provide greater monitoring capacity and broader expertise, facilitating more effective oversight of complex ESG integration strategies and their financial implications, including liquidity management (Manita et al., 2018). We expect a positive relationship between board size and liquidity outcomes, consistent with evidence that governance quality supports ESG adoption and improved financial efficiency. Finally, CEO duality, which highlights whether the Chief Executive Officer (CEO) also serves as the board chair, is considered a potential indicator of the concentration of authority (Alareeni and Hamdan, 2020; Masa’deh et al., 2024). CEO duality may either enhance strategic coherence in ESG integration by enabling faster, unified decision-making, or reduce accountability by weakening board oversight of financial and sustainability practices. Given this mixed evidence, we include CEO duality as a control variable to account for its potential confounding influence on the ESG–CLM relationship. By integrating these control variables, this study comprehensively examines the dynamics of CLM and the impact of ESG scores. Definitions of all variables are provided in  Appendix.

To explore the real-world implications of our study’s hypotheses, we examine whether ESG scores impact the CLM of companies listed on the ASX. For this purpose, we use panel regression analysis (Baltagi, 2008; Belotti et al., 2017). Initially, we perform ordinary least squares (OLS) regression to assess the baseline ESG scores–CLM relationship. The OLS results provide a first insight into the strength and direction of the association between ESG scores and liquidity metrics. Then, to account for potential selection bias, we employ Heckman’s (1979) two-stage model analysis, and to assess the causal impact on CLM of ESG, we use PSM analysis. These techniques help to isolate the effect of ESG from confounding factors and ensure that the observed relationships are not driven by firm characteristics unrelated to ESG performance. Firm fixed-effects models are also utilised to ensure that results are not affected by unobservable firm-level differences. By controlling firm-specific unobserved heterogeneity, fixed-effects models improve the internal validity of our estimates. In addition, to address potential endogeneity concerns and to ensure robustness and consistency of our results, we implement a two-stage least squares (2SLS) model and test alternative measurements. The 2SLS method allows us to account for reverse causality and omitted variable bias, providing more reliable estimates of the effect of ESG scores on liquidity. Finally, an ESG dimension analysis is conducted to examine how specific ESG dimensions (environmental, social and governance) individually influence corporate liquidity. This allows us to identify which aspects of ESG contribute most to liquidity management outcomes.

We evaluate the impact of ESG scores on CLM variables using the following baseline model for these analyses:

where CLM (i.e. NWC, OCF and CCC) a CLM indicator; $ESGit$ denotes ESG score; and $Controlsit$ the vector of firm-specific control variables. Terms i and t account for individual and temporal effects, respectively, while $ε it$ captures the error term. This model framework allows us to quantify the relationship between ESG performance and liquidity, while controlling other factors that may influence liquidity outcomes.

Table 2 presents the descriptive statistics for all variables used in this study, along with the univariate analysis. Panel A shows the mean, standard deviation, minimum, 25th percentile, median, 75th percentile and maximum values for the full sample, across various financial and governance variables. The mean and median values are 46.323 and 44.877, respectively, with a range of 2.497–95.565. The NWC measure of financial liquidity has a mean value of 0.880 and a median value of 0.437, with values ranging from −1.076 to 8.005. OCF shows a mean of 8.769 and a median of 8.456, whereas CCC has a mean value of 4.508 and a median value of 4.064. The mean (median) value of FS is 9.284 (9.307) months. Beta (⁠$β$⁠) captures market risk with a mean value of 1.089 and a median value of 0.979. The LVG measure records a mean value of 0.486, whereas the DPR has an average value of 0.533. Governance characteristics, such as BSIZE, exhibit a mean of 7.139 members, while CEODual is present in 10.3% of firms. The average COV is 29.454.

To provide further insight, Table 2, Panel B compares the mean and median values of the key variables between firms with low ESG scores and firms with high ESG scores. Following Al Rabab’a et al. (2023), the industry median of ESG scores is used to separate the two sub-samples. The last two columns report the results of the t-test and the Mann–Whitney test, respectively, to examine the differences between the two groups. The mean NWC value for low ESG firms is 0.863, compared to 0.897 for high ESG firms, but this difference is not statistically significant. In contrast, operational measures, such as OCF and CCC, show significant differences between the two groups. Firms with low ESG scores show a higher mean OCF (9.182) and a higher mean CCC (5.157) than high ESG firms, which have mean values of 8.353 and 3.854, respectively. These differences are statistically significant at the 1% level. The results also indicate that high ESG firms tend to be larger, with a mean FS of 9.495, compared to a mean FS of 9.075 for low ESG firms. Similarly, high ESG firms exhibit higher market risk, as indicated by a mean Beta (β) of 1.154, compared to 1.025 for low ESG firms. Governance differences are also evident, with high ESG firms having a larger average BSIZE of 7.540, compared to 6.741 for low ESG firms. In addition, CEO duality is more prevalent among high ESG firms, with a mean CEODual value of 0.122, compared to 0.083 for low ESG firms, with the difference being significant at the 5% level. These findings suggest that firms with high ESG generally have stronger governance structures, more efficient operational processes and fewer CCCs. These results support the hypothesis that higher ESG performance is associated with improved financial and operational metrics across firms.

To address concerns regarding multicollinearity, our study first examines the correlation matrix of the key variables. Table 3 reports Pearson’s correlation coefficients between the variables in the regression analysis. As shown in the table, the correlations between independent and control variables are generally low, suggesting that multicollinearity is unlikely to affect our regression results. Specifically, ESG-related variables, such as ESCORE, SSCORE and GSCORE, exhibit relatively strong positive correlations with each other, with ESCORE and SSCORE having a correlation of 0.72, and GSCORE and ESGC having a correlation of 0.68. However, to avoid the potential multicollinearity issue, these variables are included separately in the model rather than being used together. Furthermore, the correlations between ESG scores and liquidity measures, such as NWC, OCF and CCC, align with our study’s hypotheses. Specifically, ESG scores are positively correlated with NWC, while they are negatively correlated with OCF and CCC. To further investigate the potential multicollinearity issue, we use the variance inflation factor (VIF) values when estimating the regression models. The VIF values are all below 6, indicating that multicollinearity is not present (Liu et al., 2023). As a VIF value above 10 signals significant multicollinearity, our study’s results confirm that this is not the case. This analysis confirms that multicollinearity does not pose a significant threat to the validity of this study’s regression results.

This section discusses the relationship between ESG scores and liquidity measures, specifically NWC, OCF and CCC, after controlling for firm specificity. We regress liquidity measures on ESG scores and a set of control variables with year and industry fixed effects to account for changes in the economy and sector-specific factors (see Table 4). The regression results from 1,100 firm-year observations show that ESGC has a significantly positive relationship with NWC (0.013) at the 10% level, indicating that higher ESG scores are associated with improved working capital management. However, ESGC also has a significantly negative relationship with both OCF (−0.034) and CCC (−0.041) at the 1% significance level, suggesting that firms with higher ESG scores tend to experience lower OCF and lower CCCs. These findings support our hypotheses that ESG performance is positively (negatively) related to NWC (CCC and OCF).

Furthermore, our regression models show that control variables, such as ROA, LVG and BSIZE, play a significant role in liquidity management, with the results largely aligned with our expectations and findings from prior studies. For instance, the relationships observed between ROA, LVG and liquidity measures are consistent with findings in studies by Atif et al. (2022), Uyar et al. (2023) and Yu et al. (2018), while the positive association between board size and liquidity supports the arguments made by Manita et al. (2018). However, it is worth noting that some studies, such as Buallay (2019), suggest that factors other than sustainability reporting may also influence liquidity dynamics, highlighting the complexity of these relationships.

Our study provides evidence that ESG performance is an important factor influencing liquidity management. Higher ESG scores tend to improve working capital management but may lead to lower OCFs and slower CCCs.

The robustness of the link between the ESG scores and cash flow management of ASX-listed companies is confirmed in this study after addressing sample selection bias, endogeneity, heterogeneity and simultaneous causality. Higher ESG scores correlate with optimised NWC, improved OCF and a reduced CCC. This finding demonstrates that strong ESG performance enhances financial efficiency, enabling better inventory, receivables and payables management. The findings affirm ESG’s role in driving operational resilience and sustainable cash flow practices.

One of the key issues in this study is the potential for sample selection bias which arises when the focal outcome is observed only for a non-randomly selected sample. This could occur when firms with high ESG scores have unobserved traits that affect their liquidity outcomes, with these traits changing the representativeness of the sample. To address this concern, this study follows Heckman’s (1979) approach and employs a two-stage model, as outlined in Table 5. In the first stage (Column 1), a probit regression model is applied as a selection equation, in which the dependent variable (ESG_DUM) is a dummy variable equal to 1 if the firm’s ESG score is available and 0 otherwise. The key determinants of a firm’s propensity to engage in ESG initiatives are included, thus incorporating two instrumental variables – Median-ESG (IV1) and First-ESG (IV2) – alongside the control variables used in our baseline model. Subsequently, the inverse Mills ratio (IMR) is calculated from the first stage and included as an additional control variable in the second stage. In the second stage, baseline regression models are estimated for the liquidity outcomes (i.e. NWC, OCF and CCC). All regressions are estimated with clustered robust standard errors by firm and include year and industry fixed effects. The results show that the coefficient of IMR is significantly positive, suggesting the presence of sample selection bias. The estimates in the second stage show that our baseline results are slightly more positive after considering sample selection bias. Thus, the main findings remain robust after accounting for potential sample selection bias.

To address this concern, we use PSM, as outlined by Rosenbaum and Rubin (1983), to match firms with high ESG scores (treated group) and those with low ESG scores (control group) within the same industry and year. The first stage uses a logit model to perform nearest-neighbour matching within a 1% calliper with no replacement, as shown in Table 6. The second stage uses OLS regressions on the matched sample based on propensity scores to understand whether ESGC affects CLM measurements (NWC, OCF and CCC). The results show that ESGC has a statistically significant negative effect on both OCF and CCC after the second stage. The coefficients, respectively, are −0.039 (significant at the 1% level) and −0.029 (significant at the 5% level). Moreover, ESGC also has a marginally positive effect on NWC, with a coefficient of 0.013, which is significant at the 10% level. These findings suggest that ESG performance is positively associated with improved CLM. To validate the matching procedure, no significant differences are shown in Panel B between the treated and control groups in terms of the key firm characteristics, confirming the robustness of the matching algorithm.

Endogeneity arises when a two-way relationship is present between independent and dependent variables, potentially leading to biased estimates. In this study, endogeneity concerns stem from the possibility that ESG scores and liquidity management practices simultaneously influence each other. To address this, a 2SLS model is used to examine the link between ESG scores and liquidity management, while accounting for endogeneity (Semykina and Wooldridge, 2010). Two instrumental variables are employed: Median-ESG (IV1), representing the industry-year median of ESG scores, and First-ESG (IV2), corresponding to the ESG score when a firm first entered the sample. In the first stage, both instruments are highly significant, with positive coefficients of 0.580 and 0.501 (both at 1% level of significance), respectively, confirming their predictive power for ESG scores. In the second stage, ESG scores are found to positively impact NWC (0.016), while negatively affecting OCF (−0.038) and CCC (−0.040) (all at 1% level of significance), indicating that higher ESG scores enhance liquidity management efficiency.

The validity of the instrumental variables is assessed using Hansen’s J statistic (Hansen, 1994), while an endogeneity test examines whether endogeneity is present. Hansen’s J statistic, which tests the null hypothesis that the instrumental variables are valid and uncorrelated with the error term, yields values of 0.140, 0.165 and 0.014 across the three models (i.e. NWC, OCF and CCC). These small and statistically insignificant values indicate that the instruments Median-ESG (IV1) and First-ESG (IV2) are appropriately selected and do not suffer from overidentification issues. In addition, the endogeneity test, which examines whether the endogenous regressor (ESGC) can be treated as exogenous, produces p-values of 0.326, 0.500 and 0.915, respectively. These high p-values suggest that ESGC does not exhibit significant endogeneity concerns, implying that the observed relationship between ESG performance and liquidity management is unlikely to be driven by reverse endogeneity. The result of the 2SLS is shown in Table 7.

To ensure the robustness of our study’s findings, we re-estimate the baseline regression model using three alternative measures of CLM: the current ratio (CR), average payment period (APP) and average collection period (ACP) (Habib and Dalwai, 2024). These measures capture various aspects of liquidity management, providing a different assessment of how firms handle their cash flows. We regress these liquidity measures on ESG scores and a set of control variables, employing robust standard errors clustered by firm and including year and industry fixed effects. Table 8 presents the OLS regression results for a sample of 1,100 firm-year observations for CR and, for APP and ACP, for a sample of 1,032 firm-year observations. A positive relationship is found between the ESG scores and CR, with a coefficient of 0.005 (t-statistic = 2.35; at a 5% level of significance). This means that higher ESG scores are linked more to current assets than to current debt. The ESG scores have a negative relationship with the average collection period (t-statistic = −1.71). Thus, a higher ESG score is linked to a firm having shorter periods in which to collect payments from its customers. In contrast, ESG scores have a positive effect on average payment period (APP), with a coefficient of 0.018 (t-statistic = 1.99, at a 5% level of significance), suggesting better liquidity management when a firm has a higher ESG score.

In a further robustness check, our study uses firm fixed-effects models to control for unobserved heterogeneity. Table 9 reveals that higher ESG scores are positively associated with NWC, with a significant coefficient of 0.014 (t-statistic = 4.59), indicating that firms excelling in ESG practices tend to maintain higher levels of working capital. We also find that, in relation to OCF and CCC, ESG scores are negatively and statistically significant. These findings reinforce our study’s main findings and ensure their robustness after addressing another model specification. This outcome may occur as firms with strong ESG performance prioritise sustainable investments and risk mitigation which could lead to having increased working capital as a buffer against uncertainty.

Table 10 presents the OLS regression results for 1,100 firm-year observations, focusing on the individual dimensions of ESG scores – environmental (ESCORE), social (SSCORE) and governance (GSCORE) – to explore their distinct impacts on NWC, OCF and CCC, that is, the liquidity management metrics. This analysis is essential for understanding how each ESG dimension contributes to financial efficiency and working capital management. The findings reveal a positive and significant relationship between ESCORE and NWC at the 1% level of significance, indicating that stronger environmental practices enhance working capital. However, in terms of OCF and CCC, ESCORE shows a negative and significant relationship, suggesting potential short-term cash flow inefficiency due to sustainability-related investment. Similarly, SSCORE exhibits a positive but marginally significant (10% level) relationship with NWC, reflecting the trade-offs of social responsibility initiatives that may boost reputation and stakeholder satisfaction but at the cost of reduced cash flow efficiency. In contrast, GSCORE demonstrates a positive yet insignificant relationship with liquidity metrics, implying that governance improvements have a weaker direct impact on liquidity than environmental or social factors. Overall, this dimension-level analysis reinforces our study’s main results, highlighting that, while individual ESG dimensions contribute to improved NWC, they may also lead to trade-offs in cash flow efficiency. These findings underscore the complexity of balancing sustainability efforts with financial performance and align with the broader trends observed in our study.

This study empirically investigates the relationship between corporate ESG scores and CLM. Specifically, we examine the impact of ESG performance on key liquidity metrics, such as NWC, the CCC and OCF, using a data set of 1,100 ASX-listed companies’ firm-year observations spanning 2010–2023. We find that higher ESG scores are positively associated with higher NWC (H1) but negatively associated with the CCC (H2) and OCF (H3). Our study began by conducting univariate analysis and then proceeded to multivariate analysis using OLS regression models, while controlling for a set of firm-level variables. To address potential concerns, such as sample selection bias, heterogeneity and endogeneity, we used several alternative model specifications: Heckman’s (1979) two-stage approach; PSM analysis; 2SLS regression analysis; and firm fixed-effects models. Our study’s main results are found to be robust to these concerns and continue to hold across alternative specifications and various tests.

This study’s findings offer significant insights into how firms’ ESG performance can impact liquidity management, with notable implications for financial management, policy makers, creditors and investors. The results suggest that firms with higher ESG scores may leverage an enhanced reputation to achieve better liquidity management which helps to reduce operational inefficiency. This challenges the notion that ESG practices are merely a cost or a burden for firms. Therefore, firms can improve their liquidity by enhancing their ESG practices which, in turn, may improve their firm value. Our study contributes to the broader discourse on corporate governance and ESG practices. This finding provides additional insights for policy makers at the firm level with its suggestion that encouraging firms to engage in ESG activities could lead to both direct and indirect benefits, including improved financial management practices. Firms that actively address ESG concerns are likely to experience a reduction in operational costs and a more stable cash flow, thus contributing to their overall financial resilience. Therefore, fostering ESG initiatives could help to secure firms’ financial stability, while also contributing to broader environmental and social goals.

Comparing our results with studies from other countries, we find consistency with previous research. For instance, European firms with higher ESG scores were found to maintain better liquidity and reduce cash flow risks, as reported by Saleh et al. (2025). Similarly, studies in China (Chen and Xie, 2022) and India (Mondal and Sahu, 2025) indicate that strong ESG performance positively influences NWC and operational efficiency, aligning with our findings. However, some studies in emerging economies, such as those by Oyewo (2023) in African markets, show that while ESG improves stakeholder trust, liquidity outcomes may be more sensitive to institutional frameworks, suggesting regional differences in ESG–CLM effectiveness. Overall, our results corroborate the international evidence that ESG practices enhance liquidity management, while also highlighting contextual variations across different regulatory and economic environments.

This study empirically examined the relationship between corporate ESG scores and CLM using a sample of 1,100 ASX-listed firm-year observations spanning 2010–2023. The findings demonstrate that higher ESG scores are positively associated with NWC and negatively associated with the CCC and OCF, supporting all three hypotheses. These results remain robust across multiple econometric specifications addressing selection bias, endogeneity and heterogeneity. Beyond the financial and theoretical implications discussed in Section 6, the findings carry important societal implications that warrant explicit recognition. Firms that maintain sound liquidity through responsible ESG practices are better positioned to honour their social licence to operate during periods of economic stress. This social licence – conferred informally by the broader community, employees and stakeholders – depends critically on a firm’s ability to sustain operations, preserve employment and fulfil contractual obligations to suppliers and creditors even during adverse conditions. By maintaining adequate liquidity through strong ESG performance, firms reduce the risk of abrupt operational failures that impose negative externalities on employees (through job losses), local communities (through economic disruption) and supply chain partners (through payment delays or contract terminations). ESG-driven liquidity management should therefore be recognised as a proactive measure to mitigate negative social externalities, aligning a firm’s financial health with broader stakeholder interests. In the Australian context, where mandatory climate-related financial disclosure requirements now apply to ASX-listed firms, firms that proactively align their financial health with stakeholder interests through ESG practices contribute to the broader goals of sustainable economic development and social stability, in line with the United Nations Sustainable Development Goals (SDGs), particularly SDG 8 (Decent Work and Economic Growth) and SDG 17 (Partnerships for the Goals).

This study presents important theoretical implications for understanding the determinants of CLM. Firstly, the results are consistent with stakeholder theory, which suggests that firms that effectively manage relationships with key stakeholders – such as employees, customers, suppliers, regulators and capital providers – are more likely to achieve superior operational and financial outcomes. Strong ESG performance enhances stakeholder trust and cooperation, which improves working capital efficiency and, in turn, has a positive effect on NWC, OCF and CCC.

Secondly, the findings provide empirical support for signalling theory by showing that ESG performance and disclosure act as credible signals of firm quality, transparency and effective risk management. These signals reduce information asymmetry between firms and external stakeholders, particularly investors and creditors, thereby improving access to external finance and lowering financing costs. As a result, firms with stronger ESG performance face fewer liquidity constraints and are able to manage liquidity more efficiently, rather than relying on excessive precautionary cash holdings. Despite these valuable contributions, this study had several limitations. Our data are restricted to firms within the ASX index; therefore, the findings may not be generalisable to firms outside this region or those operating in different institutional contexts. In addition, some ESG metrics used in this study may have limitations in terms of their ability to fully capture the breadth of ESG factors that could impact liquidity. Future research may benefit from using more granular or industry-specific ESG data to further refine these measurements.

Future research should also focus on developing standardised ESG metrics and on examining the long-term effects of ESG practices on liquidity risk (Pedersen et al., 2021). As ESG metrics continue to evolve, they will play an increasingly important role in shaping firms’ financial strategies and risk management practices.