This study investigates whether, and how, cash dividends impact the reporting of key audit matters (KAMs) in the context of a developed economy, Australia.
The study analyzes 932 firm-year observations spanning 2017–2020 of ASX 300 listed companies by employing panel regression and interpreting the results following the information asymmetry lens of agency, signaling and communication theories. Additionally, the study conducts a series of robustness tests – alongside cross-sectional analyses, mechanism tests and addressing endogeneity concerns – to ensure the consistency and reliability of the findings.
This paper documents a significant, negative association between cash dividends and the number and extent of reported KAMs, which remains robust when considering alternative measures and endogeneity concerns. Cash dividends signal as a tangible indicator of financial strength, reducing information asymmetry and fostering trust, resulting in reduced KAM disclosures. Particularly in cash-rich, financially nondistressed, low-risk firms and pre-COVID-19 periods, the negative association between cash dividends and KAM disclosures is more pronounced due to lower information asymmetry in these firms/periods. We document two potential channels: analyst following and forecast accuracy, through which cash dividends may affect KAM disclosures.
The findings have significant implications for companies, auditors, investors and regulators.
This research pioneers the link between cash dividends and KAMs, enriching both the accounting and finance literature with novel perspectives.
1. Introduction
Amid the ongoing criticism of boilerplate audit reports and mounting demand for more value-relevant information from auditors, the International Auditing and Assurance Standards Board (IAASB) introduced an auditing standard, ISA-701, that requires the auditors to disclose key audit matters (KAMs) in the independent audit reports. The aim of KAMs disclosure is to enhance the communicative value of the audit reports, thereby enhancing the transparency of financial statements (Rahaman and Chand, 2022). KAMs offer impartial and supplementary insights that help stakeholders assess the probability and potential consequences of risks influencing a firm’s financial health and operational outcomes (Maroun et al., 2025). However, while there is ongoing debate regarding the adequacy of the new audit reports, researchers from different jurisdictions find inconsistent results regarding the determinants of KAMs and document no or limited benefits of KAMs (Al-mulla and Bradbury, 2022; Li, 2017; Segal, 2019). Standard-setters, therefore, urge more academic investigations regarding the efficacy of the new reporting model, where KAMs are disclosed as per auditor judgment.
Recent research has extensively explored what determines KAM in the new extended audit reports (Abdullatif and Al‐Rahahleh, 2020; Rahaman and Karim, 2023; Bepari, 2023). While various financial and governance factors have been linked to KAM disclosures, the potential role of dividend policy has received little to no scholarly attention. This gap is surprising given that an increasing number of accounting and finance studies (e.g. Li and Zhao, 2008; Hendijani Zadeh, 2022; Deng et al., 2017) highlight the informational value of dividend payouts from the perspectives of investors, creditors, and other stakeholders. These studies suggest that dividend payouts serve as a credible signal of a firm’s current financial health and management’s confidence in future performance, mitigating information asymmetry between management and external stakeholders. However, its implications for auditors – who are tasked with evaluating risks and uncertainties in financial reporting – remain underexplored. Since KAM disclosures reflect auditors’ professional judgments regarding matters of most significance in the audits, it is reasonable to expect that observable signals such as dividend payouts may influence auditors’ perceptions of audit risk, client financial stability, and managerial intent. Motivated by this theoretical and empirical gap, this study investigates whether and how dividend payouts affect the nature and extent of KAM disclosures. Anchored in the information asymmetry and signaling framework, the study specifically examines whether cash dividend – through its signaling and agency-reducing effects – shapes auditors’ reporting behavior. By doing so, it extends the literature on KAMs’ determinants and contributes to a more nuanced understanding of how corporate payout policies influence auditor judgments.
Audit reports are designed to ensure the reliability of financial statements, but they often fail to effectively communicate between auditors and users (Li, 2017; Moroney et al., 2021). This communication gap is largely due to the standardized language and structure of typical audit reports (Church et al., 2008). Complex language, a neutral tone, and a lack of disclosure about accounting issues or anomalies have led users to overlook these reports (Bédard et al., 2019; Datejarutsri et al., 2019; IAASB, 2012). To address this problem, the IAASB introduced ISA-701 in 2015, which focuses on significant judgmental matters identified during the audit of the current period’s financial statements. Auditors are now required to disclose KAMs in the independent auditor’s reports to enhance transparency of the financial statements and provide users with valuable insights. The reporting of KAMs has been regarded as the most significant reform in audit reporting history (Rahaman and Chand, 2022). While many countries across the world have adopted the new audit reporting model, debate, however, continues regarding the benefits and burdens of the new audit reports. Many argue that the intended goals of transparency and improved communication in the audit report have not been realized yet (Rahaman and Chand, 2022; Bepari, 2023).
Indeed, the success of KAMs’ reporting depends heavily on the level of information asymmetry, auditor judgment, and audit quality (Gambetta et al., 2023; Zeng et al., 2021). Since dividend payouts can signal information asymmetry, altering the auditors’ risk perception and professional skepticism (Hendijani Zadeh, 2022; Li and Zhao, 2008), they may also affect the number and extent of KAM reported by auditors. Auditors, on the one hand, might view dividend distributions as a sign of enhanced information quality, consistent firm performance, and effective governance, which subsequently lowers their perception of risk. As a result, auditors could develop increased confidence in the management and reporting practices of the client, potentially leading to reduced audit efforts. This might lead to the identification of fewer issues classified as KAMs. On the other hand, auditors may critically examine the financial forecasts and projections made by management to justify dividend distributions. If these projections contain overly optimistic assumptions or significant uncertainties, they may influence KAM disclosures. Additionally, large dividend distributions could potentially violate debt covenants. Given that the client companies have issued dividends, auditors might proceed with increased caution and conduct detailed investigations to assess the payments and their sustainability, potentially uncovering more issues to discuss with the board. Moreover, if dividends are distributed from nonrecurring profits or reserves instead of operating income, this may raise auditor concerns about future liquidity or profitability that could manifest in related KAM disclosures (e.g. going concern or capital adequacy). Paying dividends during pandemics such as COVID-19 could also raise concerns regarding the purpose, finance, and sustainability of the payouts. All these can contribute to enhanced professional skepticism, demanding better scrutiny, which in turn may reveal more issues as KAMs. Given the competing theoretical stands and mixed empirical findings, the dynamics between dividend payments and audit outcomes, specifically KAMs disclosure, remain an unresolved puzzle.
Previous studies have explored the impact of cash dividends on audit-related factors such as audit fees, earnings quality, audit quality, and going concern decisions. Lawson and Wang (2016) found that auditors charge lower fees to dividend-paying clients, with discounts ranging from 6.0% to 10.6%. Tong and Miao (2011) and Deng et al. (2017) show that firms paying larger dividends generally exhibit greater earnings quality and persistence. Other research indicates that dividend-paying firms have higher earnings response coefficients (Sivakumar and Waymire, 1993) and lower chances of financial reporting fraud (Caskey and Hanlon, 2013). In these firms, dividend payments mitigate the positive association between earnings manipulation risk and audit fees (Lawson and Wang, 2016). These findings imply that dividends lower audit risk by enhancing the quality of a client’s earnings information. However, this is inconsistent with the traditional signaling hypothesis (John and Williams, 1985; Miller and Rock, 1985) that indicates a link between higher dividends and managerial expropriations. Moreover, standards may not properly function during economic crises, such as COVID-19, challenging the prior findings in the normal economic atmosphere. Therefore, auditors’ risk perception based on dividend policies could be changed, which may also influence how auditors approach audits and report the observations. However, the impact of a firm’s cash dividend on reported KAMs in audit reports has remained underexplored in the literature. Understanding this association is important because it sheds light on how dividend policies might affect the auditor’s risk perception, audit approaches, and the information content of audit reports.
Therefore, the objective of this study is to reduce the ambiguity surrounding the nexus between the information content of cash dividends and KAMs by examining whether auditors incorporate clients’ dividend policy in their risk assessment and risk reporting as reflected in KAM disclosures. Additionally, the study seeks to determine whether this relationship differs based on firm cash holdings, risk levels, and pre- and post-COVID-19 periods. The study examines 932 firm-year observations from ASX 300 listed companies in Australia over the period 2017–2020. The findings reveal a significant negative relationship between cash dividends and KAMs reporting, suggesting that higher cash dividends are associated with fewer and less detailed KAMs. Our subsample analyses indicate that this relationship is particularly strong for cash-rich, low-risk, and nondistressed firms and pre-COVID periods. Furthermore, we find that dividend-paying firms are less likely to have client-specific KAMs (i.e. KAMs that are not industry generic or boilerplate nature) included in the audit reports, reinforcing our baseline evidence that cash dividends reduce the quantity and extent of KAMs reported by auditors. We identify two potential channels of the information environment – analyst following and analyst forecast error – through which the informational content of cash dividends may influence auditors to reduce the extent or number of KAM disclosures. Our results remain robust after addressing potential endogeneity concerns and employing alternative measures of both cash dividends and KAM disclosures.
This study makes several key contributions to the accounting and finance literature, particularly at the intersection of corporate financial policy and audit reporting. First, it is among the first to examine the role of dividend policy in shaping KAM disclosures, an area that has received little scholarly attention. While prior research has explored the impact of dividends on audit quality (Hendijani Zadeh, 2022), audit fees (Lawson and Wang, 2016), and earnings quality (Skinner and Soltes, 2011; Tong and Miao, 2011), this study extends the literature by connecting dividend signaling theory with auditors’ risk assessments, thereby integrating perspectives from both the finance and accounting.
Second, the study adds to the growing body of research that seeks to understand the determinants of KAM disclosures by introducing dividend policy as a previously overlooked explanatory factor. In doing so, it provides a theoretical extension of information asymmetry and signaling frameworks into the domain of extended auditor reporting.
Third, our cross-sectional analysis reveals that the negative association between cash dividends and KAM disclosures is more pronounced in firms that are cash-rich, low-risk, and nondistressed. These firms typically face lower information asymmetry, allowing dividends to serve as a stronger informational signal that reduces the auditor’s perceived need for extensive KAM disclosures. This suggests that dividends function as a complementary governance signal, reducing auditors’ need to bring issues to the boardroom beyond what would be expected from financial condition alone. Furthermore, our mechanism analysis supports this interpretation by demonstrating that the information environment – proxied by the number of analysts following and forecast error – serves as a mediating channel. This evidence reinforces the notion that cash dividends improve transparency and reduce uncertainty, thereby influencing audit reporting behavior and enhancing the informational role of dividend policy (Amiram et al., 2016; Hu et al., 2023; Bilyay-Erdogan et al., 2023).
Finally, the study provides actionable insights for auditors, corporate managers, and policymakers by highlighting how dividend policy may influence auditors’ risk assessments and, consequently, the reporting of KAMs. For auditors, understanding dividend payouts as potential signals of managerial confidence or financial stability can enhance audit planning and risk assessment procedures, particularly when evaluating the likelihood of material misstatements or financial distress. For corporate managers, the findings underscore the broader implications of dividend decisions beyond investor signaling – specifically, how such financial policies may shape external perceptions of risk and transparency, including the extent of scrutiny from auditors. For policymakers and regulators, the study suggests that dividend policy could be considered an indirect indicator of audit risk sensitivity, which may inform efforts to refine disclosure standards, support audit quality monitoring, and strengthen the effectiveness of extended audit reporting frameworks such as KAMs.
The further structure of the paper is as follows: Section 2 discusses the underlying theories used in the study. Section 3 reviews prior research to develop the hypotheses. Section 4 outlines the research methodology. Section 5 presents the findings, including descriptive statistics, correlations, regression analysis, additional analyses, mechanism test, endogeneity issues, and robustness tests. Section 6 concludes the paper with a discussion, recommendations, and suggestions for future research.
2. Theoretical framework
The relationship between cash dividends and KAMs can be well understood through the lens of information asymmetry of agency theory. In a typical agency setting, managers (agents) have superior information about the firm’s operations, risks, and financial condition compared to shareholders (principals), creating a risk that managers may act in their own interests rather than in the interests of stakeholders (Jensen and Meckling, 1976). In such a context, cash dividends serve as a powerful signaling mechanism to reduce the information asymmetry among the stakeholders (Hendijani Zadeh, 2022; Li and Zhao, 2008). Paying dividends is a costly and observable commitment that a firm cannot fake without having actual financial strength. Hence, dividend payouts signal firm earnings quality and managerial confidence, helping to reduce investor uncertainty and mitigate agency costs (Bhattacharya, 1979; Miller and Rock, 1985). On the other hand, KAMs are auditor disclosures that communicate areas of significant risk or complex judgment in the financial statements, aimed at improving transparency and audit quality (IAASB, 2015). However, disclosing multiple or severe KAMs may raise investor concerns about the underlying health of the firm, thereby potentially increasing perceived risk and information asymmetry (Christensen et al., 2014; Maroun et al., 2025). In this context, cash dividends and KAM disclosures interact strategically – while KAM enhances audit transparency, they can also increase perceived uncertainty; dividend payments can offset this by signaling financial stability and reducing information asymmetry triggered by the independent auditors’ reports.
The information asymmetry lens is further reinforced by signaling and communication theories. From a signaling theory perspective, dividend payouts – particularly cash dividends – serve as a credible mechanism for reducing information asymmetry between management and shareholders (Al-Hiyari et al., 2024; Hail et al., 2014; Lin et al., 2017). Cash dividends signal financial health and profitability, providing shareholders with tangible evidence of performance and stability (Chauhan and Pathak, 2021). Regular and sustained dividend payments further indicate earnings persistence and quality, thereby strengthening investor confidence (Skinner and Soltes, 2011; Tong and Miao, 2011). Dividend policies also shape auditors’ perceptions of client risk, as dividend-paying firms are often viewed as financially stable, which in turn influences audit focus and reporting (Hendijani Zadeh, 2022; Lawson and Wang, 2016).
Complementing this, communication theory emphasizes that effective communication requires clarity, transparency, and reduced information asymmetry (Smith and Smith, 1971). Dividends function as a direct and transparent communication channel, conveying managerial confidence in earnings persistence and financial sustainability (Li and Zhao, 2008; Nguyen et al., 2024). This improved information environment informs auditors’ risk assessments and can affect the scope and depth of KAM disclosures. In strong governance contexts such as Australia, dividends also signal accountability and commitment to shareholder interests, reinforcing trust and legitimacy (Adjaoud and Ben‐Amar, 2010; Habib and Jiang, 2015; Hasan et al., 2022). Overall, dividend policy operates simultaneously as a signaling and communication tool, shaping auditor judgments about client risk and influencing how risks and uncertainties are conveyed through KAM disclosures.
3. Literature and development of hypotheses
3.1 Concurrent studies in KAM disclosures
Recent research explores how auditor, audit firm, and client traits influence KAM disclosures (Abdelfattah et al., 2021; Gambetta et al., 2023; Kuester, 2024). For instance, Kuester (2024) identifies a link between KAM’s length, readability, sentiment, and the nature of KAM topics, client features (such as firm size and losses), and audit firm traits (like audit fees and Big-4 status). Gambetta et al. (2023) also demonstrate that KAM’s readability and types differ among UK audit firms. However, findings from various regions are inconsistent. For example, Abdelfattah et al. (2021) report that female audit partners in the UK produce less readable KAMs, whereas Wuttichindanon and Issarawornrawanich (2020) found improved readability with female external auditors, using the same readability metric. Similarly, while Jiang and Olesen (2022) found no significant link between auditor specialization and account-level or entity-level KAMs in New Zealand, Bepari et al. (2022) discovered a negative correlation with account-level KAMs and a positive one with entity-level KAMs in Australia. Federsel (2025) also found no effect of specialist auditors on the number or changes in KAMs in European audit reports. In emerging markets, Boonlert-U-Thai and Suttipun (2023) found no connection between Big 4 and KAMs reporting, while Suttipun (2022) noted a positive relationship in Thailand. Additionally, current studies offer mixed evidence on the effectiveness of the new audit report. Some indicate enhanced communicative value (Reid et al., 2019; Zeng et al., 2021; Zhai et al., 2021; Seebeck and Kaya, 2022), while others show no effect (Gutierrez et al., 2018; Lennox et al., 2023) or a negative impact (Sirois et al., 2018; Kachelmeier et al., 2020; Abdullatif and Al‐Rahahleh, 2020). Therefore, identifying more firm-level characteristics in various audit contexts could help better assess the efficacy of the new KAM reports.
3.2 Key audit matters and cash dividends
Previous research shows that dividends lower earnings manipulation risk and, therefore, audit risk (Lawson and Wang, 2016). Since earnings manipulation – often associated with accounting fraud – heightens auditors’ litigation risk, firms may adopt dividend policies as a strategic tool to mitigate the likelihood of financial statement fraud (Jensen, 1986; Breeden, 2003). Firms that pay lower cash dividends are often associated with more related-party transactions (Su et al., 2014), while dividend-paying firms are less likely to commit financial statement fraud than nondividend-paying firms (Caskey and Hanlon, 2013). Larger dividend payouts are also linked to smaller discretionary accruals and stronger earnings quality (Tong and Miao, 2011), signaling managerial confidence and a long-term commitment to shareholder returns (Deng et al., 2017). By contrast, managers with abundant free cash flow may prefer lower dividends, channeling resources into projects with negative net present value to serve personal interests such as higher compensation, power, or reputation (Jensen, 1986; Kallapur, 1994). Consistent with this view, firms facing greater information asymmetry between managers and minority shareholders are less likely to distribute dividends (Deshmukh, 2005; Khang and King, 2006; Li and Zhao, 2008). Overall, dividend payouts indicate higher information quality and reduced information asymmetry. Consequently, auditors may perceive dividend-paying firms as less risky in terms of hidden financial problems, leading to lower perceived audit or litigation risk and, in turn, fewer or less extensive KAM disclosures.
Effective communication, as explained by communication theory, involves clarity, transparency, and reducing information asymmetry (Smith and Smith, 1971). Cash dividends serve as a straightforward communication tool, indicating a company’s financial health and profitability to shareholders (Chauhan and Pathak, 2021). Companies distribute larger dividends to convey positive confidential information, resulting in an increased market valuation (Nguyen et al., 2024). Regular dividend payments provide a tangible signal of a company’s performance and earnings growth and persistence, thus decreasing information asymmetry between management and shareholders (Li and Zhao, 2008; Hendijani Zadeh, 2022). This reduction in information asymmetry can influence auditors’ risk assessments, leading to a lower number and extent of KAM disclosures. Furthermore, effective corporate governance promotes transparency and accountability in financial reporting (Habib and Jiang, 2015; Hasan et al., 2022). In environments with strong governance structures, such as Australia, dividend payouts can signal robust governance practices and a commitment to shareholder interests (Adjaoud and Ben‐Amar, 2010). According to communication theory, transparent and accountable communication enhances stakeholder trust, making firms with strong dividend policies have low information asymmetry, resulting in a lower number and extent of KAM.
Nevertheless, according to signaling theory (John and Williams, 1985; Miller and Rock, 1985), better-informed managers may utilize cash dividends as a signal to less-informed market participants that firms are doing well even when they are not. Also, managers may declare and pay dividends during economic crises to reassure investors fearing insiders’ expropriation (Jabbouri, 2016). Previous research indicates an inverse relationship between dividend payouts and managerial compensation, which suggests that dividends diminish the value of managerial stock options (Fenn and Liang, 2001) or that higher dividends are linked to entrenched or lower-quality managers (Bhattacharyya et al., 2008). Executives who are not adequately supervised tend to make imprudent decisions regarding dividends to benefit themselves (Jiraporn et al., 2011; Koo et al., 2017). Morri et al. (2021) documented that information asymmetry has a positive impact on dividend payments. Accordingly, Basiddiq and Hussainey (2012) showed that reduced information asymmetry is associated with lower dividend propensity. Furthermore, Qin et al. (2022) demonstrate that larger dividends are linked with lower social trust. This implies that dividends can also signal managerial opportunism, lower information quality, and increased information asymmetry. Conversely, if a company reduces or halts its dividend payments, it may also indicate underlying problems, increasing information asymmetry. In such cases, auditors may feel the need to provide more comprehensive KAM disclosures to address these issues. If a company’s dividend policy indicates greater risks or uncertainties, auditors are likely to highlight these risks more clearly in their reports. However, companies that distribute adequate cash dividends are likely to have an informational edge in clarifying risk compared to their peers. Any information that clarifies firm risk exposure should influence the audit risk and, consequently, the audit outcome. Based on the above, we argue that client firms’ dividend policy will significantly affect auditors’ risk perception, audit efforts, and, eventually, risk reporting in the form of KAMs reporting in the extended audit reports. Accordingly, the following unidirectional hypothesis is proposed.
There is a significant association between a firm’s cash dividends and the number of key audit matters (KAMs) disclosures.
There is a significant association between a firm’s cash dividends and the extent of key audit matters (KAMs) disclosures.
3.3 Key audit matters, cash dividends and cash holding
Literature shows that firms with limited internal resources might raise funds by selling assets, issuing new equity or debt, or foregoing dividend payments (Keynes, 1936). Large cash reserves can help firms avoid liquidity crises and support dividend payments. A profitable firm without sufficient cash for dividends may need to borrow or liquidate assets. Conversely, paying dividends reduces cash holdings, highlighting the connection between cash reserves and dividend payments. Empirical studies show that in countries with poor investor protection, dividends are valued higher by investors than retained cash due to the risk of expropriation by controlling shareholders (Pinkowitz et al., 2006). Additionally, Al-Najjar and Belghitar (2011) and Houqe et al. (2023) also demonstrate the interrelationship between corporate cash holdings and dividend payouts.
Firms with substantial cash reserves tend to be profitable, generate cash flows from operations, and pursue growth opportunities (Ozkan and Ozkan, 2004; Kim et al., 2013). Cash-rich firms have lower financial risk and higher financial flexibility to distribute dividends while maintaining adequate liquidity for unforeseen circumstances (Ferreira and Vilela, 2004). This financial stability can lower the perceived risk for auditors, potentially leading to fewer KAM being reported. Auditors may consider the strong cash position as an indicator of sound financial management and reduced risk of going concern issues, thereby diminishing the necessity to emphasize numerous KAMs. Furthermore, the ability of cash-rich firms to pay dividends consistently might reinforce the perception of financial stability, leading auditors to focus less on potential risks in their reports. Conversely, cash-poor firms, which may struggle with liquidity (Kim et al., 2013), are likely to be seen as higher risk by auditors. These firms may face greater challenges in sustaining operations and meeting financial obligations, especially during periods of economic uncertainty or downturns. The decision to pay dividends in such firms could strain their already limited resources, raising concerns about their financial sustainability. As a result, auditors might be more cautious and report more KAMs to highlight the risks associated with these firms. Based on this discussion, the following hypotheses can be proposed:
The association between cash dividend payouts and KAMs reporting is more pronounced in cash-rich firms.
3.4 Key audit matters, cash dividends and firm risk
Previous research has suggested that a client’s risk level influences the reporting of KAM in audit reports (Rahaman and Karim, 2023). Audit firms disclose more KAMs for high-risk clients to mitigate litigation risk, as these clients increase the likelihood of legal repercussions for the auditor. Kachelmeier et al. (2017) found that including KAMs makes legal professionals perceive auditors as less liable for false declarations, even when an audit resolution paragraph is present. Brasel et al. (2016) noted that users are less likely to react negatively to overlooked misstatements if a related KAM has been reported. Although nonprofessional investors may not find KAMs particularly informative, professional investors see negative KAM as indicating a more accurate assessment of a firm’s financial condition compared to positive KAM (Backof, 2015; Köhler et al., 2020).
Highly levered firms are generally considered riskier due to the increased financial risk associated with greater leverage. Managers of such firms often adopt cost-saving accounting practices that may increase risks. Additionally, highly levered companies face greater challenges in maintaining lender support, further increasing their risk (Pinto and Morais, 2019). As a result, auditors exercise greater caution when auditing these risky firms to avoid litigation risks and protect their reputation.
Furthermore, information asymmetry is typically higher in high-risk firms compared to low-risk firms (Fosu et al., 2016; Petacchi, 2015). Similarly, financially distressed firms face increased scrutiny due to their precarious financial situations, amplifying information asymmetry. While cash dividends can help reduce information asymmetry by providing a tangible signal of financial health and profitability (Li and Zhao, 2008), highly levered and financially distressed firms remain inherently risky due to factors such as volatile earnings, uncertain market conditions, and potential financial distress. In high-risk firms, the effectiveness of cash dividends in mitigating information asymmetry may be limited by these underlying uncertainties. Additionally, risky and financially distressed firms have going concern issues, which auditors are required to report as KAMs. Therefore, auditors are particularly vigilant in these firms, leading to more detailed and extensive KAM disclosures. This additional scrutiny ensures that all significant risks and issues are transparently communicated to stakeholders, enhancing the overall quality of financial reporting. Based on this discussion, the following hypotheses can be proposed, assuming a positive association between cash dividends and KAM:
The association between cash dividends and KAMs reporting is more pronounced in high-risk firms.
The association between cash dividends and KAMs reporting is more pronounced in financially distressed firms.
However, if the relationship between cash dividends and KAM disclosures is negative, the opposite scenario might hold true for less risky and nondistressed firms. These firms usually demonstrate stable financial performance and lower levels of inherent risk, reducing auditors’ need to report extensive KAMs. The regular issuance of cash dividends in such firms signals their robust financial health, decreasing the necessity for auditors to highlight numerous KAMs in audit reports. Furthermore, nondistressed and low-risk firms tend to have lower information asymmetry than their riskier counterparts (Fosu et al., 2016; Petacchi, 2015), a gap that can be further reduced through the declaration and payment of cash dividends. Thus, the following hypotheses can be proposed as alternatives for H3a and H4a:
The association between cash dividends and KAMs reporting is more pronounced in low-risk firms.
The association between cash dividends and KAMs reporting is more pronounced in nondistressed firms.
3.5 Key audit matters, cash dividends and COVID-19
The COVID-19 pandemic created unprecedented financial uncertainty, disrupting business operations through lockdowns, revenue declines, and liquidity challenges (Karim et al., 2021; Rahaman and Bhuiyan, 2025). It also had significant implications for financial reporting, altering firms’ disclosure practices (Karim et al., 2024). These disruptions are expected to alter the dynamics of the relationship between cash dividends and KAM disclosures. On the one hand, the pandemic could strengthen the association between cash dividends and KAMs. Companies that continue to distribute dividends despite financial strain may face heightened auditor skepticism regarding the sustainability of payouts. In such cases, auditors may respond by increasing the number and scope of KAM disclosures, particularly in relation to liquidity and cash flow risks, to safeguard against investor misinterpretation and mitigate litigation risk (Gold et al., 2020). Dividend inconsistency during the pandemic could further amplify these concerns, as firms that issue dividends in the face of declining revenues may appear to prioritize short-term shareholder appeasement over long-term financial stability. This environment of heightened uncertainty, coupled with remote auditing practices, may therefore intensify the link between dividend policies and auditors’ risk communications through KAMs.
On the other hand, the pandemic could weaken the association between cash dividends and KAMs. During a period of widespread economic disruption, dividend decisions may no longer serve as reliable signals of firm health, as even strong firms faced external pressures that disrupted normal payout policies (Krieger et al., 2021). Auditors, recognizing the pervasive and systemic nature of COVID-19 risks, may focus less on dividend behavior as a determinant of risk assessment and instead rely on broader firm- and industry-level factors when deciding the content of KAMs. In this context, the information value of dividends diminishes, reducing their explanatory power for KAM disclosures. Moreover, COVID-19 itself represented a significant risk factor that could be reported as a KAM. Consequently, the relationship between dividend policy and audit reporting practices may have been less pronounced during the pandemic.
Taken together, the COVID-19 crisis creates an empirical setting where the dividend–KAMs relationship could either intensify due to heightened uncertainty and skepticism or weaken as dividend signals lose their relevance in an environment dominated by systemic risks. We therefore posit competing hypotheses:
The association between cash dividends and KAMs reporting is more pronounced during COVID-19 periods.
The association between cash dividends and KAMs reporting is less pronounced during COVID-19 periods.
4. Methodology
4.1 Data, sample and research design
This study selected Australia for testing the association between cash dividends and KAM disclosures for several reasons. First, Australia has a well-established and transparent financial reporting and corporate governance framework (ASIC, 2019). The economy of Australia is characterized by high dividend payouts and strong governance (Coulton and Ruddock, 2011; Shamsabadi et al., 2016), making it an ideal context for examining the nuances of audit reporting and dividend policies. Second, Australia’s early adoption of mandatory disclosure requirements for KAMs since 2016 offers a valid reason for studying the impact of cash dividend payouts on KAM disclosures (AuASB, 2015). Third, the Australian Securities Exchange (ASX) is home to a diverse range of companies across various sectors, providing a rich data set that enhances the robustness of the analysis. Further, the country’s relatively stable economic environment and well-regulated financial markets facilitate the generalization of the findings to other developed economies. Furthermore, prior studies have focused on the Austrian context to study KAM disclosures (Bepari et al., 2022; Moroney et al., 2021; Rahaman and Chand, 2022), but no study has yet investigated dividend payouts linking audit outcomes in Australia. These factors collectively justify the selection of Australia as a suitable context for this study.
Our initial sample comprises all companies listed on the ASX 300 from 2017 to 2020, corresponding with the introduction of KAM disclosures in 2016 (reflected in annual reports from 2017) in Australia. The data were collected from these companies’ annual reports, corporate governance reports, and financial statements. The data reliability was assessed using both simple and α coefficients, both of which exceeded the 0.75 threshold recommended by Milne and Adler (1999). Table 1 provides a detailed outline of the sample selection process. Initially, 1200 firms listed on the ASX 300 during 2017–2020 were considered. Exclusions were made due to the unavailability of annual reports (36 firms), nonextractable KAM reports (102 firms), foreign firm status (32 firms), and missing data on control variables (98 firms), resulting in a final sample of 932 observations (77.67% of the initial sample). The breakdown of the sample by industry shows that the materials sector is the largest at 20.17%, followed by consumer discretionary at 16.74%, industrial at 13.41% and real estate at 12.12%. The distribution of sample observations across years is fairly even: 2017 (214), 2018 (229), 2019 (236), and 2020 (253).
Sample selection process
| Description | Observations | % |
|---|---|---|
| Panel A: Sample selection | ||
| Firms listed on the ASX 300 in 2017–2020 | 1,200 | 100.00 |
| Nonavailability of annual reports | (36) | 3.00 |
| Annual reports with nonextractable KAMs report | (102) | 8.50 |
| Observations excluded for foreign firms | (32) | 2.67 |
| Missing data of control variables | (98) | 8.17 |
| Final sample | 932 | 77.67 |
| Panel B: Sample breakdown by industry | ||
| Consumer_Discretionary | 156 | 16.74 |
| Consumer_Staples | 66 | 7.08 |
| Energy | 55 | 5.90 |
| Financials | 47 | 5.04 |
| Health_Care | 68 | 7.30 |
| Industrials | 125 | 13.41 |
| Information_Technology | 67 | 7.19 |
| Materials | 188 | 20.17 |
| Real_Estate | 113 | 12.12 |
| Telecommunication_Services | 29 | 3.11 |
| Utilities | 18 | 1.93 |
| Panel C: Sample breakdown by year | ||
| 2017 | 214 | 22.96 |
| 2018 | 229 | 24.57 |
| 2019 | 236 | 25.32 |
| 2020 | 253 | 27.15 |
| Description | Observations | % |
|---|---|---|
| Panel A: Sample selection | ||
| Firms listed on the | 1,200 | 100.00 |
| Nonavailability of annual reports | (36) | 3.00 |
| Annual reports with nonextractable KAMs report | (102) | 8.50 |
| Observations excluded for foreign firms | (32) | 2.67 |
| Missing data of control variables | (98) | 8.17 |
| Final sample | 932 | 77.67 |
| Panel B: Sample breakdown by industry | ||
| Consumer_Discretionary | 156 | 16.74 |
| Consumer_Staples | 66 | 7.08 |
| Energy | 55 | 5.90 |
| Financials | 47 | 5.04 |
| Health_Care | 68 | 7.30 |
| Industrials | 125 | 13.41 |
| Information_Technology | 67 | 7.19 |
| Materials | 188 | 20.17 |
| Real_Estate | 113 | 12.12 |
| Telecommunication_Services | 29 | 3.11 |
| Utilities | 18 | 1.93 |
| Panel C: Sample breakdown by year | ||
| 2017 | 214 | 22.96 |
| 2018 | 229 | 24.57 |
| 2019 | 236 | 25.32 |
| 2020 | 253 | 27.15 |
4.2 Regression model
We use the following regression specifications to test our hypotheses:
Models 1 and 3 analyze how cash dividends (Cash_Div) influence the quantity and extent of KAM disclosures, respectively. We follow Hendijani Zadeh (2022), Chauhan and Pathak (2021), and Firth et al. (2016) for our measure of cash dividends, calculated as cash dividends paid divided by total assets.[1] Following Bostan et al. (2023), our models 2 and 4 utilize a different metric (lnCash_Div) for cash dividends (the natural logarithm of cash dividends paid) to evaluate its effect on both the number of KAM disclosures and the verbosity used to elucidate them in audit reports. These size-adjusted measures effectively capture the intensity of a firm’s payout relative to its economic scale, offering a firm-level perspective that avoids distortions caused by earnings volatility (Qin et al., 2022). Contemporary studies use both continuous and dummy measures of dividend policy (Tong and Miao, 2011; Su et al., 2014; Hail et al., 2014; Firth et al., 2016; Deng et al., 2017; Qin et al., 2022). Accordingly, for our endogeneity test and robustness tests, we use several dummy measures of dividend payout. We follow recent studies for our measures of KAM disclosures (Pinto and Morais, 2019; Suttipun, 2020; Bepari et al., 2022; Rahaman et al., 2023). For a comprehensive understanding of these variables, their descriptions and measurements are provided in Table 2.
Definition and measurement of the variables
| Dependent variable | Description | Expected sign | Reference |
|---|---|---|---|
| Num_KAM | The natural logarithm of the number of KAMs disclosed | Pinto and Morais, 2019; Rahaman et al., 2023; Velte, 2018 | |
| Word_KAM | The natural logarithm of number of words used to explain KAMs disclosures | Pinto and Morais, 2019; Rahaman et al., 2023; Rahaman and Karim, 2023; Velte, 2018 | |
| Independent variables: | |||
| Cash_Div | Amount of cash divided scaled by total asset | +/- | Qin et al., 2022; Chauhan and Pathak, 2021; Hendijani Zadeh, 2022; Hail et al., 2014; Firth et al., 2016 |
| lnCash_Div | Natural logarithm of (1 + cash dividend) paid by the firms in year t | +/- | Bostan et al., 2023; Green and Kerr, 2022; Hendijani Zadeh, 2022 |
| Cash_Div_Dum | An indicator variable of 1 if the firm paid cash dividend in year t, and 0 otherwise | +/- | Firth, et al., 2016; Hendijani Zadeh, 2022 |
| AF | The number of analysts who issued at least one earnings forecast for firm i in year t | + | Jia, 2017; He et al., 2020 |
| For_Error | Analyst forecast error, computed as the mean estimate of EPS less actual EPS. We standardize the measure by deflating the difference by actual EPS | - | Jia, 2017; He et al., 2020 |
| Control_Variables: | |||
| BOD_Size | Natural logarithm of number of members in corporate board | + | Bepari, 2023; Rahaman and Karim, 2023. |
| AC_FDR | The proportion of female directors on the audit committee | -/+ | Abdelfattah et al., 2021; Bepari, 2023; Rahaman et al., 2023. |
| AC_FE | The ratio of financial experts on the audit committee calculated by dividing the number of financial experts by the total number of committee members | + | Bepari, 2023; Rahaman, and Bhuiyan, 2025. |
| Audit_Fee | Natural logarithm of the amount of audit fee paid | + | Rahaman and Karim, 2023; Velte, 2018; Suttipun, 2022. |
| Audit_Tenure | The number of years current audit firm is auditing the client | +/- | Rahaman, and Bhuiyan, 2025; Rahaman and Karim, 2023; de Ricquebourg and Maroun (2023) |
| Big4 | An indicator variable of 1 if the audit firm is one of the big-4 auditors, and 0 otherwise | + | Pinto and Morais, 2019; Rahaman et al., 2023 |
| Firm_Size | Natural logarithm of total assets of the firm | + | Pinto and Morais, 2019; Rahaman et al., 2023; Velte, 2018 |
| Firm_Age | Natural logarithm of number of years in business from the listing year | + | Rahaman and Karim, 2023 |
| Lev | Leverage measured by debt to total asset ratio | + | Rahaman and Karim, 2023; Bepari, 2023 |
| Loss | An indicator variable 1 if the firm report net loss position in a particular year, and 0 otherwise | - | Rahaman and Karim, 2023; Rahaman, and Bhuiyan, 2025 |
| Current_Ratio | The current ratio calculated as the current assets divided by the current liabilities | +/- | Sierra-García, et al. (2019) |
| COVID19 | An indicator variable 1 if the reporting period ended on or after 25 January 2020 (as the first confirmed case of COVID-19 in Australia was identified on 25 January 2020); 0 otherwise | + | Hategan et al. (2022); Murphy et al., (2025) |
| FiscalYearEnd | An indicator variable coded 1 if the reporting period ended in the month of June; 0 otherwise | + | Rahaman et al., 2023; Rahaman, and Bhuiyan, 2025 |
| Dependent variable | Description | Expected sign | Reference |
|---|---|---|---|
| Num_KAM | The natural logarithm of the number of KAMs disclosed | ||
| Word_KAM | The natural logarithm of number of words used to explain KAMs disclosures | ||
| Independent variables: | |||
| Cash_Div | Amount of cash divided scaled by total asset | +/- | |
| lnCash_Div | Natural logarithm of (1 + cash dividend) paid by the firms in year t | +/- | |
| Cash_Div_Dum | An indicator variable of 1 if the firm paid cash dividend in year t, and 0 otherwise | +/- | |
| The number of analysts who issued at least one earnings forecast for firm i in year t | + | ||
| For_Error | Analyst forecast error, computed as the mean estimate of | - | |
| Control_Variables: | |||
| BOD_Size | Natural logarithm of number of members in corporate board | + | |
| AC_FDR | The proportion of female directors on the audit committee | -/+ | |
| AC_FE | The ratio of financial experts on the audit committee calculated by dividing the number of financial experts by the total number of committee members | + | |
| Audit_Fee | Natural logarithm of the amount of audit fee paid | + | |
| Audit_Tenure | The number of years current audit firm is auditing the client | +/- | |
| Big4 | An indicator variable of 1 if the audit firm is one of the big-4 auditors, and 0 otherwise | + | |
| Firm_Size | Natural logarithm of total assets of the firm | + | |
| Firm_Age | Natural logarithm of number of years in business from the listing year | + | |
| Lev | Leverage measured by debt to total asset ratio | + | |
| Loss | An indicator variable 1 if the firm report net loss position in a particular year, and 0 otherwise | - | |
| Current_Ratio | The current ratio calculated as the current assets divided by the current liabilities | +/- | |
| COVID19 | An indicator variable 1 if the reporting period ended on or after 25 January 2020 (as the first confirmed case of COVID-19 in Australia was identified on 25 January 2020); 0 otherwise | + | |
| FiscalYearEnd | An indicator variable coded 1 if the reporting period ended in the month of June; 0 otherwise | + | |
5. Empirical results and discussion
5.1 Descriptive statistics
Table 3 provides descriptive statistics for the variables used in this study. On average, audit reports from ASX 300 listed companies in Australia reveal 2.68 KAMs, spanning 1000 words. The number of KAMs reported ranges from 1 to 5, while the word count varies between 256 and 2306, underscoring substantial diversity in the depth and detail of KAM disclosures across companies in Australia.
Descriptive statistics
| Variable | Observations | Mean | SD | Minimum | Maximum |
|---|---|---|---|---|---|
| Num_KAM | 932 | 2.68 | 1.01 | 1.00 | 5.00 |
| lnNum_KAM | 932 | 0.90 | 0.43 | 0.00 | 1.61 |
| Word_KAM | 932 | 1,000.52 | 419.76 | 256.00 | 2,306.00 |
| lnWord_KAM | 932 | 6.81 | 0.46 | 5.55 | 7.74 |
| Cash_Div | 932 | 0.04 | 0.04 | 0.00 | 0.25 |
| lnCash_Div | 932 | 14.92 | 7.02 | 0.00 | 22.17 |
| Cash_Div_Dum | 932 | 0.82 | 0.38 | 0.00 | 1.00 |
| BOD_Size | 932 | 1.91 | 0.24 | 1.10 | 2.48 |
| AC_FDR | 932 | 0.30 | 0.23 | 0.00 | 1.00 |
| AC_FE | 932 | 0.39 | 0.21 | 0.00 | 1.00 |
| Audit_Fee | 932 | 13.49 | 1.07 | 11.01 | 16.86 |
| Audit_Tenure | 932 | 1.85 | 0.74 | 0.00 | 2.64 |
| Big4 | 932 | 0.93 | 0.26 | 0.00 | 1.00 |
| Firm_Size | 932 | 21.32 | 1.40 | 17.45 | 25.59 |
| Firm_Age | 932 | 2.65 | 0.85 | 0.05 | 4.12 |
| Lev | 932 | 0.24 | 0.16 | 0.00 | 0.87 |
| Loss | 932 | 0.18 | 0.38 | 0.00 | 1.00 |
| Current_Ratio | 932 | 2.10 | 1.94 | 0.08 | 14.17 |
| COVID19 | 932 | 0.27 | 0.44 | 0.00 | 1.00 |
| FiscalYearEnd | 932 | 0.78 | 0.41 | 0.00 | 1.00 |
| AF | 932 | 9.13 | 4.73 | 1.00 | 22.00 |
| lnAF | 932 | 2.03 | 0.68 | 0.00 | 3.09 |
| For_Error | 932 | 0.05 | 0.36 | −3.86 | 4.62 |
| Variable | Observations | Mean | Minimum | Maximum | |
|---|---|---|---|---|---|
| Num_KAM | 932 | 2.68 | 1.01 | 1.00 | 5.00 |
| lnNum_KAM | 932 | 0.90 | 0.43 | 0.00 | 1.61 |
| Word_KAM | 932 | 1,000.52 | 419.76 | 256.00 | 2,306.00 |
| lnWord_KAM | 932 | 6.81 | 0.46 | 5.55 | 7.74 |
| Cash_Div | 932 | 0.04 | 0.04 | 0.00 | 0.25 |
| lnCash_Div | 932 | 14.92 | 7.02 | 0.00 | 22.17 |
| Cash_Div_Dum | 932 | 0.82 | 0.38 | 0.00 | 1.00 |
| BOD_Size | 932 | 1.91 | 0.24 | 1.10 | 2.48 |
| AC_FDR | 932 | 0.30 | 0.23 | 0.00 | 1.00 |
| AC_FE | 932 | 0.39 | 0.21 | 0.00 | 1.00 |
| Audit_Fee | 932 | 13.49 | 1.07 | 11.01 | 16.86 |
| Audit_Tenure | 932 | 1.85 | 0.74 | 0.00 | 2.64 |
| Big4 | 932 | 0.93 | 0.26 | 0.00 | 1.00 |
| Firm_Size | 932 | 21.32 | 1.40 | 17.45 | 25.59 |
| Firm_Age | 932 | 2.65 | 0.85 | 0.05 | 4.12 |
| Lev | 932 | 0.24 | 0.16 | 0.00 | 0.87 |
| Loss | 932 | 0.18 | 0.38 | 0.00 | 1.00 |
| Current_Ratio | 932 | 2.10 | 1.94 | 0.08 | 14.17 |
| COVID19 | 932 | 0.27 | 0.44 | 0.00 | 1.00 |
| FiscalYearEnd | 932 | 0.78 | 0.41 | 0.00 | 1.00 |
| 932 | 9.13 | 4.73 | 1.00 | 22.00 | |
| lnAF | 932 | 2.03 | 0.68 | 0.00 | 3.09 |
| For_Error | 932 | 0.05 | 0.36 | −3.86 | 4.62 |
This table presents the key descriptive statistics used in this study. Variable definitions are provided in Table 2
Regarding cash dividends, the findings indicate that, on average, firms in Australia pay $0.04 per dollar of assets as a cash dividend, ranging from $0.00 to $0.25. Additionally, the mean value of the logarithm of cash dividends paid is 14.92, with a minimum value of 0.00 and a maximum value of 22.17. Furthermore, the cash dividends dummy indicates that 82% of ASX 300 companies in Australia pay dividends. These statistics underscore the diverse dividend policies among firms in Australia, which could significantly influence auditing processes and the disclosure of KAMs.
The study incorporates several control variables drawn from prior literature to account for factors that may influence cash dividend payouts and KAM disclosures. Firm size and age, with an average of 21.32 and 2.65, respectively, and a standard deviation of 1.40 and 0.93, respectively, indicate a diverse sample of companies in terms of size and age levels. Leverage, another crucial variable, averages 0.24 with a standard deviation of 0.16, spanning a wide range from 0.001 to 0.87, further highlighting the diversity within the sample. About 18% of the firms in the sample report a net loss, reflecting varying financial performance. The current ratio, with an average of 2.10 and a standard deviation of 1.94, illustrates liquidity differences across the firms. The binary variable for COVID-19, averaging 0.27, captures the pandemic’s significant impact during the study period. The mean of the dummy variable for fiscal year-end in June is 0.78, reflecting seasonal variations in reporting.
Board size averages 1.91 with a standard deviation of 0.24, indicating differences in board composition, while the female director ratio of 0.30 reflects gender diversity in audit committees within Australian corporate boards. The average audit committee size with accounting and finance expertise is 2.51, with a range from 0.00 to 8.00, showcasing the variability in financial literacy among board members. Audit fees have a mean of 13.49 and a standard deviation of 1.07, indicating differences in auditing costs. Auditor tenure (in natural logarithm) averages 1.85 (ranging from 0.00 to 2.64). Notably, the presence of Big4 auditors is high, with an average of 0.93, indicating that most firms in the sample are audited by these major firms. These descriptive statistics highlight the extensive variability in the sample, which is essential for a comprehensive analysis of the factors influencing KAM disclosures.
5.2 Correlation analysis
Table 4 illustrates the pairwise correlations among various variables, highlighting significant relationships with KAMs. Cash dividends show a negative correlation with both the number of KAM (−0.06) and the words used in KAMs (−0.11), indicating that higher cash dividends are associated with fewer and less extensive KAM disclosures. The alternative measure of cash dividends also negatively correlates with the number and word counts of KAMs, suggesting a similar trend when dividends are log-transformed. Additionally, board, auditor, and firm characteristics are mostly positively associated with the number and extent of KAM disclosures. Furthermore, among the control variables, none of the correlation coefficients exceeds the minimum threshold (i.e. 0.70), thus indicating no multicollinearity problem among the variables.
Pairwise correlations
| Variables | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 | 12 | 13 | 14 | 15 | 16 | 17 | 18 | 19 | 20 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| (1) Num_KAM | 1 | |||||||||||||||||||
| (2) Word_KAM | 0.76*** | 1 | ||||||||||||||||||
| (3) lnCash_Div | −0.06** | −0.11*** | 1 | |||||||||||||||||
| (4) Cash_Div | −0.08** | −0.10*** | 0.49*** | 1 | ||||||||||||||||
| (5) AF | 0.14*** | 0.22*** | 0.35*** | 0.17*** | 1 | |||||||||||||||
| (6) For_Error | 0.08** | 0.12*** | −0.25*** | −0.15*** | −0.05 | 1 | ||||||||||||||
| (7) BOD_Size | 0.26*** | 0.30*** | 0.34*** | 0.08** | 0.44*** | −0.09** | 1 | |||||||||||||
| (8) AC_FDR | 0.09*** | 0.18*** | 0.21*** | −0.01 | 0.25*** | 0.02 | 0.25*** | 1 | ||||||||||||
| (9) AC_FE | 0.17*** | 0.15*** | 0.23*** | 0.13*** | 0.25*** | −0.08** | 0.31*** | 0.11*** | 1 | |||||||||||
| (10) Audit_Fee | 0.39*** | 0.47*** | 0.39*** | 0.04 | 0.47*** | −0.04 | 0.60*** | 0.33*** | 0.30*** | 1 | ||||||||||
| (11) Audit_Tenure | 0.08** | 0.14*** | 0.18*** | 0.15*** | 0.28*** | −0.05 | 0.21*** | 0.12*** | 0.15*** | 0.25*** | 1 | |||||||||
| (12) Big4 | −0.03 | 0.16*** | 0 | −0.01 | 0.20*** | 0.02 | 0.17*** | 0.16*** | 0.14*** | 0.28*** | 0.13*** | 1 | ||||||||
| (13) Auditor_Gender | −0.05* | −0.06* | 0.08** | 0.08** | 0 | −0.03 | 0.09*** | 0.01 | 0.09*** | 0.08** | 0.03 | 0.07** | 1 | |||||||
| (14) Firm_Size | 0.29*** | 0.41*** | 0.49*** | −0.04 | 0.53*** | −0.06* | 0.63*** | 0.33*** | 0.31*** | 0.73*** | 0.27*** | 0.21*** | −0.01 | 1 | ||||||
| (15) Firm_Age | 0.16*** | 0.14*** | 0.15*** | 0.07** | 0.22*** | −0.04 | 0.28*** | 0.01 | 0.15*** | 0.27*** | 0.42*** | −0.09*** | 0 | 0.32*** | 1 | |||||
| (16) Lev | 0.06* | 0.12*** | 0.10*** | −0.01 | 0.06* | 0.03 | 0.11*** | 0.07** | 0.08** | 0.13*** | 0.04 | 0.09*** | 0.06* | 0.23*** | −0.09*** | 1 | ||||
| (17) Loss | 0.03 | 0.10*** | −0.42*** | −0.31*** | −0.04 | 0.19*** | −0.03 | 0.01 | −0.02 | −0.03 | −0.03 | 0.08** | −0.03 | −0.08** | −0.02 | 0.10*** | 1 | |||
| (18) Current_Ratio | −0.07** | −0.16*** | −0.26*** | −0.08** | −0.15*** | −0.03 | −0.22*** | −0.14*** | −0.11*** | −0.24*** | −0.03 | −0.20*** | −0.03 | −0.29*** | 0.03 | −0.17*** | 0.11*** | 1 | ||
| (19) COVID19 | −0.07** | 0.03 | −0.07** | −0.03 | 0.01 | 0.16*** | −0.02 | 0.09*** | 0 | 0.05 | 0.14*** | 0.01 | 0.02 | 0.02 | 0.10*** | 0.09*** | 0.13*** | 0.01 | 1 | |
| (20) FiscalYearEnd | −0.03 | 0.03 | 0 | −0.02 | 0.10*** | 0.04 | 0.05* | 0.07** | 0.05 | 0.04 | 0.08** | 0.05* | 0.03 | 0.10*** | 0.15*** | 0.04 | 0.08** | 0.02 | 0.03 | 1 |
| Variables | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 | 12 | 13 | 14 | 15 | 16 | 17 | 18 | 19 | 20 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| (1) Num_KAM | 1 | |||||||||||||||||||
| (2) Word_KAM | 0.76 | 1 | ||||||||||||||||||
| (3) lnCash_Div | −0.06 | −0.11 | 1 | |||||||||||||||||
| (4) Cash_Div | −0.08 | −0.10 | 0.49 | 1 | ||||||||||||||||
| (5) | 0.14 | 0.22 | 0.35 | 0.17 | 1 | |||||||||||||||
| (6) For_Error | 0.08 | 0.12 | −0.25 | −0.15 | −0.05 | 1 | ||||||||||||||
| (7) BOD_Size | 0.26 | 0.30 | 0.34 | 0.08 | 0.44 | −0.09 | 1 | |||||||||||||
| (8) AC_FDR | 0.09 | 0.18 | 0.21 | −0.01 | 0.25 | 0.02 | 0.25 | 1 | ||||||||||||
| (9) AC_FE | 0.17 | 0.15 | 0.23 | 0.13 | 0.25 | −0.08 | 0.31 | 0.11 | 1 | |||||||||||
| (10) Audit_Fee | 0.39 | 0.47 | 0.39 | 0.04 | 0.47 | −0.04 | 0.60 | 0.33 | 0.30 | 1 | ||||||||||
| (11) Audit_Tenure | 0.08 | 0.14 | 0.18 | 0.15 | 0.28 | −0.05 | 0.21 | 0.12 | 0.15 | 0.25 | 1 | |||||||||
| (12) Big4 | −0.03 | 0.16 | 0 | −0.01 | 0.20 | 0.02 | 0.17 | 0.16 | 0.14 | 0.28 | 0.13 | 1 | ||||||||
| (13) Auditor_Gender | −0.05 | −0.06 | 0.08 | 0.08 | 0 | −0.03 | 0.09 | 0.01 | 0.09 | 0.08 | 0.03 | 0.07 | 1 | |||||||
| (14) Firm_Size | 0.29 | 0.41 | 0.49 | −0.04 | 0.53 | −0.06 | 0.63 | 0.33 | 0.31 | 0.73 | 0.27 | 0.21 | −0.01 | 1 | ||||||
| (15) Firm_Age | 0.16 | 0.14 | 0.15 | 0.07 | 0.22 | −0.04 | 0.28 | 0.01 | 0.15 | 0.27 | 0.42 | −0.09 | 0 | 0.32 | 1 | |||||
| (16) Lev | 0.06 | 0.12 | 0.10 | −0.01 | 0.06 | 0.03 | 0.11 | 0.07 | 0.08 | 0.13 | 0.04 | 0.09 | 0.06 | 0.23 | −0.09 | 1 | ||||
| (17) Loss | 0.03 | 0.10 | −0.42 | −0.31 | −0.04 | 0.19 | −0.03 | 0.01 | −0.02 | −0.03 | −0.03 | 0.08 | −0.03 | −0.08 | −0.02 | 0.10 | 1 | |||
| (18) Current_Ratio | −0.07 | −0.16 | −0.26 | −0.08 | −0.15 | −0.03 | −0.22 | −0.14 | −0.11 | −0.24 | −0.03 | −0.20 | −0.03 | −0.29 | 0.03 | −0.17 | 0.11 | 1 | ||
| (19) COVID19 | −0.07 | 0.03 | −0.07 | −0.03 | 0.01 | 0.16 | −0.02 | 0.09 | 0 | 0.05 | 0.14 | 0.01 | 0.02 | 0.02 | 0.10 | 0.09 | 0.13 | 0.01 | 1 | |
| (20) FiscalYearEnd | −0.03 | 0.03 | 0 | −0.02 | 0.10 | 0.04 | 0.05 | 0.07 | 0.05 | 0.04 | 0.08 | 0.05 | 0.03 | 0.10 | 0.15 | 0.04 | 0.08 | 0.02 | 0.03 | 1 |
This table presents the correlation coefficient among the variables used in this study. Variable definitions are provided in Table 2, and all continuous variables are winsorized at the 99th percentile to mitigate the influence of outliers. ***, ** and * denote statistical significance at the 1, 5 and 10% levels, respectively
5.3 Regression results
Table 5 presents the results from our econometric models using ordinary least squares (OLS). Models 1 and 2 test H1a, focusing on the number of reported KAMs as the dependent variable. Model 1 uses cash dividends scaled by total assets, while Model 2 employs the natural logarithm of cash dividends as an alternative measure. Models 3 and 4 examine H1b, investigating the impact of cash dividends on the extent of KAM, measured as the natural logarithm of words used to explain KAMs. Model 3 utilizes the primary measure of cash dividends, whereas Model 4 uses the alternative measure.
Baseline regression results (H1a and H1b)
| Variables | (1) Num_KAM | (2) Word_KAM | (3) Num_KAM | (4) Word_KAM |
|---|---|---|---|---|
| Cash_Div | −1.603*** (−3.763) | −1.013** (−2.323) | ||
| lnCash_Div | −0.009*** (−3.261) | −0.005** (−2.147) | ||
| BOD_Size | 0.044 (0.532) | 0.007 (0.075) | 0.030 (0.363) | −0.004 (−0.044) |
| AC_FDR | −0.062 (−0.951) | 0.037 (0.543) | −0.040 (−0.600) | 0.049 (0.705) |
| AC_FE | −0.024*** (−3.167) | −0.019** (−0.593) | −0.025*** (−3.198) | −0.018** (−0.538) |
| Audit_Fee | 0.159*** (7.126) | 0.159*** (6.779) | 0.161*** (7.176) | 0.159*** (6.759) |
| Audit_Tenure | −0.005 (−0.249) | 0.008 (0.354) | −0.012 (−0.549) | 0.004 (0.155) |
| Big4 | −0.251*** (−4.052) | 0.024 (0.366) | −0.284*** (−4.524) | 0.007 (0.109) |
| Firm_Size | 0.004 (0.200) | 0.025 (1.181) | 0.030 (1.448) | 0.039* (1.837) |
| Firm_Age | 0.026 (1.364) | 0.003 (0.145) | 0.022 (1.169) | 0.000 (0.021) |
| LEV | 0.060 (0.604) | 0.131 (1.249) | 0.062 (0.616) | 0.134 (1.275) |
| Loss | 0.038 (0.930) | 0.097** (2.300) | 0.025 (0.582) | 0.097** (2.196) |
| Current_Ratio | 0.011 (1.283) | −0.004 (−0.420) | 0.009 (1.080) | −0.004 (−0.490) |
| COVID19 | −0.148*** (−3.707) | 0.005 (0.117) | −0.144*** (−3.605) | 0.008 (0.185) |
| FiscalYearEnd | 0.027 (0.765) | −0.033 (−0.906) | 0.022 (0.615) | −0.035 (−0.957) |
| Constant | −1.085*** (−4.039) | 4.122*** (14.645) | −1.487*** (−5.489) | 3.893*** (13.715) |
| Year_FE | Yes | Yes | Yes | Yes |
| Industry_FE | Yes | Yes | Yes | Yes |
| Observations | 932 | 932 | 932 | 932 |
| Adjusted_R2 | 0.228 | 0.236 | 0.225 | 0.233 |
| Variables | (1) Num_KAM | (2) Word_KAM | (3) Num_KAM | (4) Word_KAM |
|---|---|---|---|---|
| Cash_Div | −1.603 | −1.013 | ||
| lnCash_Div | −0.009 | −0.005 | ||
| BOD_Size | 0.044 (0.532) | 0.007 (0.075) | 0.030 (0.363) | −0.004 (−0.044) |
| AC_FDR | −0.062 (−0.951) | 0.037 (0.543) | −0.040 (−0.600) | 0.049 (0.705) |
| AC_FE | −0.024 | −0.019 | −0.025 | −0.018 |
| Audit_Fee | 0.159 | 0.159 | 0.161 | 0.159 |
| Audit_Tenure | −0.005 (−0.249) | 0.008 (0.354) | −0.012 (−0.549) | 0.004 (0.155) |
| Big4 | −0.251 | 0.024 (0.366) | −0.284 | 0.007 (0.109) |
| Firm_Size | 0.004 (0.200) | 0.025 (1.181) | 0.030 (1.448) | 0.039 |
| Firm_Age | 0.026 (1.364) | 0.003 (0.145) | 0.022 (1.169) | 0.000 (0.021) |
| 0.060 (0.604) | 0.131 (1.249) | 0.062 (0.616) | 0.134 (1.275) | |
| Loss | 0.038 (0.930) | 0.097 | 0.025 (0.582) | 0.097 |
| Current_Ratio | 0.011 (1.283) | −0.004 (−0.420) | 0.009 (1.080) | −0.004 (−0.490) |
| COVID19 | −0.148 | 0.005 (0.117) | −0.144 | 0.008 (0.185) |
| FiscalYearEnd | 0.027 (0.765) | −0.033 (−0.906) | 0.022 (0.615) | −0.035 (−0.957) |
| Constant | −1.085 | 4.122 | −1.487 | 3.893 |
| Year_FE | Yes | Yes | Yes | Yes |
| Industry_FE | Yes | Yes | Yes | Yes |
| Observations | 932 | 932 | 932 | 932 |
| Adjusted_R2 | 0.228 | 0.236 | 0.225 | 0.233 |
This table presents the baseline regression results examining the impact of cash dividends on Key Audit Matters (KAMs). Reported coefficients are accompanied by t-statistics in parentheses. Variable definitions are provided in Table 2, and all continuous variables are winsorized at the 99th percentile. ***, ** and * denote statistical significance at the 1, 5 and 10% levels, respectively
However, Columns 1 and 2 show that the coefficient on Cash_Div is −1.603 and −1.013, respectively, both of which are statistically significant at 1% level. The findings indicate a significant and negative association between cash dividends and both the number and extent of KAMs reported. This suggests that auditors tend to report fewer KAMs and provide less detailed explanations for firms that declare and pay higher cash dividends. These results are statistically significant at the 1% level for models 1 and 3, and at 5% for models 2 and 4, underscoring the robustness of the findings. These outcomes are consistent with previous studies that provide evidence of lower information asymmetry in firms that distribute larger dividends (e.g. Hail et al., 2014; Lawson and Wang, 2016; Lin et al., 2017; Li and Zhao, 2008). According to agency theory, there exists information asymmetry among the stakeholders in the firms (Jensen and Meckling, 1976). Research indicates that dividend payouts function as a credible signaling and communication tool to convey private information about firm performance, and firms with higher cash dividends exhibit lower information asymmetry (Al-Hiyari et al., 2024; Li and Zhao, 2008; Hail et al., 2014), potentially reducing the necessity for extensive KAM disclosures in audit reports. Moreover, higher dividends signal positively regarding a firm’s financial health and prospects, leading auditors to perceive the client as less risky, resulting in fewer and less detailed KAM disclosures.
The coefficient of −1.603 on Cash_Div indicates that a one percentage-point increase in dividend payout relative to assets is associated with a 1.6% reduction in the number of KAMs disclosed. Given the standard deviation of Cash_Div is 0.04, a one standard deviation increase implies a 6.4% (i.e. e−0.064 −1) decline in KAMs, which indicates approximately 0.17 fewer KAMs than the mean KAM of 2.68. On the other hand, the coefficient on Cash_Div (−1.013, p < 0.01) for words in KAMs implies that a one standard-deviation increase in dividend payout (0.04) is associated with a 3.9% (i.e. e−0.04 −1) reduction in the length of KAM disclosures, equivalent to about 39 fewer words given the sample mean of 1000 words. These results suggest that the effect is not only statistically significant but also economically meaningful.
Among the control variables, audit fees exhibit a significant positive correlation with KAM disclosures across all models at the 1% level, suggesting that higher audit fees are associated with more extensive KAM disclosures. In contrast, engagement by Big 4 firms is negatively linked to the number of KAMs, indicating potential underreporting by these firms. However, the financial expertise of the audit committee is positively associated with the number of KAMs only, indicating that audit committees with greater financial acumen may be more inclined to identify and highlight complex issues in the audit report. Additionally, firm age is positively and significantly associated with just the number of KAMs, as aged firms have more issues to report compared to their counterparts.
Furthermore, loss position shows a significant positive association solely with the extent of KAM disclosures. Moreover, the COVID-19 pandemic exhibits a significant negative association with the number of KAM, reflecting its impact on audit processes. However, board size, audit committee female director ratio, audit tenure, leverage, and the current ratio do not emerge as significant determinants of KAM disclosures. The adjusted R-squared values and the statistical significance of the F tests (at the 1% level) confirm the overall fitness of the models. These statistics indicate that our prediction of the association between cash dividends and KAMs reporting is reliable.
5.4 Cross-sectional analyses
For the cross-sectional analyses, we run baseline regressions on various subsamples to examine potential heterogeneity in the relationship between dividend policy and KAM disclosures. Specifically, we analyze firms based on their financial and contextual characteristics: cash-rich versus cash-poor firms, low-risk versus high-risk firms, distressed versus nondistressed firms, and pre-COVID-19 versus COVID-19 periods. Firms are classified as cash-rich if their cash and equivalents ratio (CER) is above the sample median, and as cash-poor if the CER is at or below the median. Similarly, we divide firms into low-risk and high-risk categories using leverage, with firms below the median leverage considered low-risk and those at or above the median as high-risk. To identify financial distress, we use the ratio of free cash flow to current liabilities (FCF_CL), classifying firms with FCF_CL above the median as nondistressed and those at or below as distressed firms. For the COVID-19 classification, firm-years with reporting periods ending on or after 25 January 2020 are treated as the COVID-19 period, while those prior to this date are considered pre-COVID-19. The results of these subsample analyses are discussed in the following section.
5.4.1 Cash-rich vs cash-poor firms.
Table 6 presents the results of the regression analysis comparing cash-rich and cash-poor firms, focusing on the impact of cash dividends on KAM disclosures across different cash-holding levels (H2). For cash-rich firms (as in Columns 1 and 2), the findings indicate a statistically significant negative relationship between cash dividends and KAMs (both in terms of number and words) at the 1% significance level. The robustness models (as in Columns 5 and 6) show similar results, significant at 5% level. In contrast, for cash-poor firms, the relationship is weaker and less consistent. While Column 3 shows a significant negative association (significant at 5%) between cash dividends and the number of KAMs, the relationship is not significant in the other models. Thus, these results support hypothesis H2, indicating that the negative relationship between cash dividends and KAM disclosures is more pronounced in cash-rich firms. These findings are in line with the conclusions of previous studies by Houqe et al. (2023), Ozkan and Ozkan (2004), and Kim et al. (2013), among others. Cash-rich firms typically have lower liquidity risk and more financial stability to pay dividends, which leads to fewer KAMs being reported by auditors. Additionally, these firms experience lower levels of information asymmetry by reducing cash flow shocks and increasing stock price (Aono and Hori, 2023; Drobetz et al., 2010). Dividends payments by cash-rich firms further mitigate information asymmetry compared to their counterparts. Therefore, cash dividends are associated with reduced KAM disclosures in cash-rich firms relative to cash-poor firms.
Regression results for cash-rich vs cash-poor firms (H2)
| Variables | Main model | Robustness test | ||||||
|---|---|---|---|---|---|---|---|---|
| (1) Cash-rich Firms NumKAM | (2) Cash-rich Firms WordKAM | (3) Cash-poor Firms NumKAM | (4) Cash-poor Firms WordKAM | (5) Cash-rich Firms NumKAM | (6) Cash-rich Firms WordKAM | (7) Cash-poor Firms NumKAM | (8) Cash-poor Firms WordKAM | |
| Cash_Div | −1.93*** (−3.20) | −1.90*** (−3.06) | −1.55** (−1.95) | −0.87 (−1.03) | ||||
| lnCash_Div | −0.062** (−2.168) | −0.06** (−2.11) | −0.067* (−1.90) | −0.041 (−1.09) | ||||
| Constant | −0.41 (0.85) | 5.46*** (9.067) | −2.94*** (−4.991) | 3.14*** (5.021) | −0.53 (−0.938) | 4.92*** (8.656) | −3.16*** (−5.310) | 3.01*** (4.774) |
| Controls | Yes | Yes | Yes | Yes | Yes | Yes | Yes | Yes |
| Year FE | Yes | Yes | Yes | Yes | Yes | Yes | Yes | Yes |
| Industry FE | Yes | Yes | Yes | Yes | Yes | Yes | Yes | Yes |
| Observations | 466 | 466 | 466 | 466 | 466 | 466 | 466 | 466 |
| Adjusted R2 | 0.231 | 0.336 | 0.324 | 0.293 | 0.173 | 0.249 | 0.384 | 0.271 |
| Variables | Main model | Robustness test | ||||||
|---|---|---|---|---|---|---|---|---|
| (1) Cash-rich Firms NumKAM | (2) Cash-rich Firms WordKAM | (3) Cash-poor Firms NumKAM | (4) Cash-poor Firms WordKAM | (5) Cash-rich Firms NumKAM | (6) Cash-rich Firms WordKAM | (7) Cash-poor Firms NumKAM | (8) Cash-poor Firms WordKAM | |
| Cash_Div | −1.93 | −1.90 | −1.55 | −0.87 (−1.03) | ||||
| lnCash_Div | −0.062 | −0.06 | −0.067 | −0.041 (−1.09) | ||||
| Constant | −0.41 (0.85) | 5.46 | −2.94 | 3.14 | −0.53 (−0.938) | 4.92 | −3.16 | 3.01 |
| Controls | Yes | Yes | Yes | Yes | Yes | Yes | Yes | Yes |
| Year | Yes | Yes | Yes | Yes | Yes | Yes | Yes | Yes |
| Industry | Yes | Yes | Yes | Yes | Yes | Yes | Yes | Yes |
| Observations | 466 | 466 | 466 | 466 | 466 | 466 | 466 | 466 |
| Adjusted R2 | 0.231 | 0.336 | 0.324 | 0.293 | 0.173 | 0.249 | 0.384 | 0.271 |
This table presents the subsample regression results in cash rich vs cash poor firms using the main and alternative measures of cash dividend. Reported coefficients are accompanied by t-statistics in parentheses. Variable definitions are provided in Table 2, and all continuous variables are winsorized at the 99th percentile. ***, ** and * denote statistical significance at the 1, 5 and 10% levels, respectively
5.4.2 Low vs. high-risk firms.
Table 7 presents regression results examining the relationship between cash dividends and KAM disclosures in high-risk and low-risk firms. The analysis is divided into main models and robustness tests, with separate models for the number of KAM and the word count of KAMs. However, for low-risk firms, the results show a significant negative association between cash dividends and KAM disclosures. Specifically, as in Columns 1 and 2, cash dividends are negatively associated with both the number and word count of KAMs, with coefficients significant at the 1% level. This suggests that in low-risk firms, higher cash dividends correspond to fewer and less detailed KAM disclosures. The robustness tests with an alternative measure of dividend payouts (as in Columns 5 and 6) confirm this negative relationship, though with a slightly lower significance level for the number of words. In contrast, for high-risk firms, the relationship between cash dividends and KAM disclosures is weaker or not statistically significant. The coefficient for cash dividends is significant at 5% for the number of KAMs (as in Columns 3 and 7) but insignificant for words in KAMs (as in Columns 4 and 8), indicating that cash dividends have a relatively weaker impact on KAM disclosures in high-risk firms. The main model and the robustness tests consistently support our supposition in H3.
Regression results for high-risk vs low-risk firms (H3)
| Variables | Main model | Robustness test | ||||||
|---|---|---|---|---|---|---|---|---|
| (1) Low-Risk Num_KAM | (2) Low-Risk Word_KAM | (3) High-Risk Num_KAM | (4) High-Risk Word_KAM | (5) Low-Risk Num_KAM | (6) Low-Risk Word_KAM | (7) High-Risk Num_KAM | (8) High-Risk Num_KAM | |
| Cash_Div | −1.66*** (−2.64) | −1.53*** (−2.46) | −1.01** (−1.20) | −0.45 (−0.51) | ||||
| lnCash_Div | −0.056*** (−1.77) | −0.063** (−2.02) | −0.028** (−0.76) | −0.001 (−0.02) | ||||
| Constant | −1.16* (−1.95) | 3.11*** (5.30) | −1.69*** (−2.61) | 4.33*** (6.33) | −1.51** (−2.59) | 2.78*** (4.84) | −1.91*** (−3.11) | 4.22*** (6.51) |
| Controls | Yes | Yes | Yes | Yes | Yes | Yes | Yes | Yes |
| Year_FE | Yes | Yes | Yes | Yes | Yes | Yes | Yes | Yes |
| Industry_FE | Yes | Yes | Yes | Yes | Yes | Yes | Yes | Yes |
| Observations | 466 | 466 | 466 | 466 | 466 | 466 | 466 | 466 |
| Adjusted R2 | 0.195 | 0.262 | 0.332 | 0.258 | 0.184 | 0.257 | 0.328 | 0.257 |
| Variables | Main model | Robustness test | ||||||
|---|---|---|---|---|---|---|---|---|
| (1) Low-Risk Num_KAM | (2) Low-Risk Word_KAM | (3) High-Risk Num_KAM | (4) High-Risk Word_KAM | (5) Low-Risk Num_KAM | (6) Low-Risk Word_KAM | (7) High-Risk Num_KAM | (8) High-Risk Num_KAM | |
| Cash_Div | −1.66 | −1.53 | −1.01 | −0.45 (−0.51) | ||||
| lnCash_Div | −0.056 | −0.063 | −0.028 | −0.001 (−0.02) | ||||
| Constant | −1.16 | 3.11 | −1.69 | 4.33 | −1.51 | 2.78 | −1.91 | 4.22 |
| Controls | Yes | Yes | Yes | Yes | Yes | Yes | Yes | Yes |
| Year_FE | Yes | Yes | Yes | Yes | Yes | Yes | Yes | Yes |
| Industry_FE | Yes | Yes | Yes | Yes | Yes | Yes | Yes | Yes |
| Observations | 466 | 466 | 466 | 466 | 466 | 466 | 466 | 466 |
| Adjusted R2 | 0.195 | 0.262 | 0.332 | 0.258 | 0.184 | 0.257 | 0.328 | 0.257 |
This table presents the subsample regression results in low-risk vs high-risk firms using the main and alternative measures of cash dividend. Reported coefficients are accompanied by t-statistics in parentheses. Variable definitions are provided in Table 2, and all continuous variables are winsorized at the 99th percentile. ***, ** and * denote statistical significance at the 1, 5 and 10% levels, respectively
These findings align with previous research (Rahaman et al., 2023; Rahaman and Karim, 2023), which indicates that low-risk firms experience less information asymmetry (Fosu et al., 2016; Petacchi, 2015). Cash dividends signal reduced information asymmetry to auditors, leading to fewer KAM disclosures, as there are fewer judgmental issues to report. According to agency theory, clear and transparent communication reduces information asymmetry and builds trust between a firm and its stakeholders. By paying cash dividends, low-risk firms signal reduced information gaps and strong financial health to shareholders (Fosu et al., 2016), reducing uncertainty about their financial situation. Consequently, auditors respond by decreasing the extent of audit procedures and KAM disclosures.
5.4.3 Distressed vs. nondistressed firms.
Table 8 shows the regression analysis results on the impact of cash dividend payouts on KAM disclosures for financially nondistressed vis-à-vis distressed firms (H4). For nondistressed firms, the results indicate a significant negative relationship between cash dividends and KAM disclosures. As reported in Columns 1 and 2, cash dividends are significantly associated with a reduction in both the number and word count of KAM, with coefficients significant at the 5% level with similar findings in robustness test as reported in Columns 5 and 6. In contrast, for distressed firms, the relationship between cash dividends and KAM disclosures is weaker and not statistically significant. The coefficient for cash dividend is negative and marginally significant in the regression model for number of KAMs (as reported in Column 3), but it is statistically insignificant in the model for number of words (as shown in Column 4), indicating that cash dividends do not have a substantial impact on KAM disclosures in distressed firms. The robustness tests (as reported in Columns 7 and 8) confirm these findings, showing no significant relationship between cash dividends and KAM in distressed firms.
Regression results for distressed and nondistressed firms (H4)
| Variables | Main_Model | Robustness_Test | |||||||
|---|---|---|---|---|---|---|---|---|---|
| (1) Nondistressed Firms Num_KAM | (2) Nondistressed Firms Word_KAM | (3) Distressed Firms Num_KAM | (4) Distressed Firms Word_KAM | (5) Nondistressed FirmsNum_KAM | (6) Nondistressed Firms Word_KAM | (7) Distressed Firms Num_KAM | (8) Distressed Firms Word_KAM | ||
| Cash_Div | −1.60** (−2.36) | −1.43** (−2.24) | −1.25* (−1.93) | −0.64 (−0.77) | |||||
| lnCash_Div | −0.07* (−1.81) | −0.07** (−2.28) | −0.02* (−0.50) | −0.02 (−0.55) | |||||
| Constant | −1.31*** (−2.73) | 3.84*** (8.47) | −1.39*** (−3.36) | 4.37*** (9.63) | −1.55** (−2.54) | 3.28*** (5.79) | −1.46** (−2.36) | 4.30*** (6.23) | |
| Controls | Yes | Yes | Yes | Yes | Yes | Yes | Yes | Yes | |
| Year_FE | Yes | Yes | Yes | Yes | Yes | Yes | Yes | Yes | |
| Industry_FE | Yes | Yes | Yes | Yes | Yes | Yes | Yes | Yes | |
| Observations | 466 | 466 | 466 | 466 | 466 | 466 | 466 | 466 | |
| Adjusted_R2 | 0.245 | 0.282 | 0.218 | 0.228 | 0.234 | 0.291 | 0.246 | 0.211 | |
| Variables | Main_Model | Robustness_Test | |||||||
|---|---|---|---|---|---|---|---|---|---|
| (1) Nondistressed Firms Num_KAM | (2) Nondistressed Firms Word_KAM | (3) Distressed Firms Num_KAM | (4) Distressed Firms Word_KAM | (5) Nondistressed FirmsNum_KAM | (6) Nondistressed Firms Word_KAM | (7) Distressed Firms Num_KAM | (8) Distressed Firms Word_KAM | ||
| Cash_Div | −1.60 | −1.43 | −1.25 | −0.64 (−0.77) | |||||
| lnCash_Div | −0.07 | −0.07 | −0.02 | −0.02 (−0.55) | |||||
| Constant | −1.31 | 3.84 | −1.39 | 4.37 | −1.55 | 3.28 | −1.46 | 4.30 | |
| Controls | Yes | Yes | Yes | Yes | Yes | Yes | Yes | Yes | |
| Year_FE | Yes | Yes | Yes | Yes | Yes | Yes | Yes | Yes | |
| Industry_FE | Yes | Yes | Yes | Yes | Yes | Yes | Yes | Yes | |
| Observations | 466 | 466 | 466 | 466 | 466 | 466 | 466 | 466 | |
| Adjusted_R2 | 0.245 | 0.282 | 0.218 | 0.228 | 0.234 | 0.291 | 0.246 | 0.211 | |
This table presents the subsample regression results in nondistressed vs distressed firms using the main and alternative measures of cash dividend. Reported coefficients are accompanied by t-statistics in parentheses. Variable definitions are provided in Table 2, and all continuous variables are winsorized at the 99th percentile. ***, ** and * denote statistical significance at the 1, 5 and 10% levels, respectively
This finding aligns with previous research (Lee et al., 2010; Rahaman et al., 2023). Nondistressed firms are less risky and have lower information asymmetry than distressed firms (Lee et al., 2010; Karim et al., 2021). Cash dividends reduce information asymmetry for auditors, leaving fewer judgmental issues to report as KAMs. Nondistressed firms also lack going concern problems, which are often reported as KAMs in distressed firms. According to agency theory, cash dividends reduce information asymmetry and build trust with stakeholders. By paying cash dividends, nondistressed firms signal financial stability, reducing uncertainty and perceived risks. Auditors respond by disclosing fewer KAMs, making the negative association between cash dividends and KAM disclosures more pronounced in nondistressed firms.
5.4.4 Pre-COVID-19 vs. COVID-19 periods.
Table 9 presents the regression results for pre-COVID vis-à-vis COVID-19 periods. The results show that coefficients for cash dividends are negative and statistically significant for both the number of KAMs (significant at 1%) and words in KAM (significant at 5%) in the pre-COVID-19 sample. However, for the COVID-19 sample, the coefficients on cash dividend are negative but statistically insignificant. The findings support our prediction that the association between dividend payouts and KAM disclosures is less pronounced during the COVID-19 period (H5b). The results in the robustness models are also consistent with the main models. Auditors seemed to have less confidence and did not heavily depend on dividend payouts as indicators of a company’s stable performance, especially during times of economic uncertainty. Additionally, the elevated uncertainty during COVID-19 May have contributed to an increase in auditor judgment and caution, resulting in a greater number and complexity of issues being disclosed as KAMs. Consequently, they issued a higher number of KAMs during the COVID-19 period compared to the time before COVID-19, specifically for firms that paid dividends.
Regression results for pre-COVID-19 and COVID-19 periods (H5)
| Variables | Main_Model | Robustness_Test | ||||||
|---|---|---|---|---|---|---|---|---|
| (1) Pre-COVID Num_KAM | (2) Pre-COVID Word_KAM | (3) COVID-19 Num_KAM | (4) COVID-19 Word_KAM | (5) Pre-COVID Num_KAM | (6) Pre-COVID Word_KAM | (7) COVID-19 Num_KAM | (8) COVID-19 Word_KAM | |
| Cash_Div | −2.704*** (−3.597) | −1.977** (−2.542) | −0.992 (−1.521) | −0.755 (−1.088) | ||||
| lnCash_Div | −0.010*** (−2.834) | −0.006** (−1.433) | −0.011* (−1.926) | −0.003 (−0.444) | ||||
| Constant | −1.078* (−1.664) | 4.192*** (6.251) | −1.330** (−2.240) | 3.868*** (6.123) | −1.828*** (−3.661) | 3.514*** (6.641) | −1.551* (−1.805) | 4.491*** (5.068) |
| Controls | Yes | Yes | Yes | Yes | Yes | Yes | Yes | Yes |
| Year_FE | Yes | Yes | Yes | Yes | Yes | Yes | Yes | Yes |
| Industry_FE | Yes | Yes | Yes | Yes | Yes | Yes | Yes | Yes |
| Observations | 679 | 679 | 253 | 253 | 679 | 679 | 253 | 253 |
| Adjusted_R2 | 0.206 | 0.203 | 0.226 | 0.252 | 0.207 | 0.205 | 0.233 | 0.235 |
| Variables | Main_Model | Robustness_Test | ||||||
|---|---|---|---|---|---|---|---|---|
| (1) Pre-COVID Num_KAM | (2) Pre-COVID Word_KAM | (3) COVID-19 Num_KAM | (4) COVID-19 Word_KAM | (5) Pre-COVID Num_KAM | (6) Pre-COVID Word_KAM | (7) COVID-19 Num_KAM | (8) COVID-19 Word_KAM | |
| Cash_Div | −2.704 | −1.977 | −0.992 (−1.521) | −0.755 (−1.088) | ||||
| lnCash_Div | −0.010 | −0.006 | −0.011 | −0.003 (−0.444) | ||||
| Constant | −1.078 | 4.192 | −1.330 | 3.868 | −1.828 | 3.514 | −1.551 | 4.491 |
| Controls | Yes | Yes | Yes | Yes | Yes | Yes | Yes | Yes |
| Year_FE | Yes | Yes | Yes | Yes | Yes | Yes | Yes | Yes |
| Industry_FE | Yes | Yes | Yes | Yes | Yes | Yes | Yes | Yes |
| Observations | 679 | 679 | 253 | 253 | 679 | 679 | 253 | 253 |
| Adjusted_R2 | 0.206 | 0.203 | 0.226 | 0.252 | 0.207 | 0.205 | 0.233 | 0.235 |
This table presents the subsample regression results in pre-COVID-19 vs COVID-19 periods using the main and alternative measures of cash dividend. Reported coefficients are accompanied by t-statistics in parentheses. Variable definitions are provided in Table 2, and all continuous variables are winsorized at the 99th percentile. ***, ** and * denote statistical significance at the 1, 5 and 10% levels, respectively
5.5 Mechanism test
We examine two possible channels through which cash dividends might influence KAM disclosures, focusing particularly on the role of analyst coverage and forecast accuracy. Cash dividends act as a signal to the market by reducing information asymmetry, as indicated by proxies such as analyst following and forecast accuracy (Amiram et al., 2016; Hu et al., 2023). Table 10 presents the results of the channel analysis, inspired by the methodology of Bilyay-Erdogan et al. (2023), where analyst following and forecast error are employed as measures of information asymmetry. The findings reveal that cash dividends significantly enhance analyst coverage (coefficient = 3.828, p < 0.01), indicating a positive association with reduced information asymmetry. Conversely, cash dividends are negatively linked to forecast error (coefficient = −3.962, p < 0.10), further demonstrating their role in improving forecast accuracy and mitigating information gaps in the market. Then the results show that the analyst following (forecast error) negatively (positively) impacts the number and length of KAM disclosures. These results underscore the signaling and informational role of cash dividends in improving market transparency and reducing uncertainty, which ultimately reduces the number and extent of KAM disclosures.
Mechanism test
| Variables | Analyst following | Forecast_Error | ||||
|---|---|---|---|---|---|---|
| AF | NumKAM | WordKAM | For_Error | NumKAM | WordKAM | |
| Cash_Div | 3.828*** (6.712) | −3.962* (−1.892) | ||||
| AF | −0.009** (−2.284) | −0.053* (−1.577) | ||||
| For_Error | 0.025*** (3.379) | 0.029*** (3.901) | ||||
| Constant | −3.237*** (−6.492) | −1.874*** (−4.877) | 3.610*** (9.251) | −0.442 (−0.237) | −1.720*** (−4.503) | 3.807*** (9.932) |
| Controls | Yes | Yes | Yes | Yes | Yes | Yes |
| Year FE | Yes | Yes | Yes | Yes | Yes | Yes |
| Industry FE | Yes | Yes | Yes | Yes | Yes | Yes |
| Observations | 932 | 932 | 932 | 932 | 932 | 932 |
| Adjusted R2 | 0.439 | 0.223 | 0.244 | 0.094 | 0.227 | 0.249 |
| Variables | Analyst following | Forecast_Error | ||||
|---|---|---|---|---|---|---|
| NumKAM | WordKAM | For_Error | NumKAM | WordKAM | ||
| Cash_Div | 3.828 | −3.962 | ||||
| −0.009 | −0.053 | |||||
| For_Error | 0.025 | 0.029 | ||||
| Constant | −3.237 | −1.874 | 3.610 | −0.442 (−0.237) | −1.720 | 3.807 |
| Controls | Yes | Yes | Yes | Yes | Yes | Yes |
| Year | Yes | Yes | Yes | Yes | Yes | Yes |
| Industry | Yes | Yes | Yes | Yes | Yes | Yes |
| Observations | 932 | 932 | 932 | 932 | 932 | 932 |
| Adjusted R2 | 0.439 | 0.223 | 0.244 | 0.094 | 0.227 | 0.249 |
This table presents regression results for mechanism test using the number of analysts following (AF) and analyst forecast error (For_Error) as the channels. Reported coefficients are accompanied by t-statistics in parentheses. Variable definitions are provided in Table 2, and all continuous variables are winsorized at the 99th percentile. ***, ** and * denote statistical significance at the 1, 5 and 10% levels, respectively
5.6 Endogeneity test
Our findings may be influenced by concerns related to endogeneity because firms independently determine their dividend policies and select auditors, who subsequently make decisions regarding KAM disclosures. To mitigate these potential endogeneity issues, we employ entropy balancing and propensity score matching (PSM) techniques. In entropy balancing, the dividend dummy variable allows for a more accurate balancing of covariates between treated (dividend-paying) and control (nondividend-paying) firms, ensuring that any observed differences in KAMs can be more confidently attributed to the treatment effect of dividend payments rather than to confounding factors. In PSM, the cash dividend dummy is used to match firms with similar characteristics, except for their dividend payment status. This helps to isolate the impact of dividend payments on KAM by comparing firms that are otherwise similar, thereby reducing the potential bias from endogeneity and making the causal interpretation of the results more robust. In our study, we used 1:1 nearest-neighbour matching for PSM.
Table 11 presents the regression outcomes for the cash dividend dummy using entropy balancing and PSM, where a dummy variable for cash dividends serves as the treatment indicator. Firms are categorized with a dummy variable of 1 if they pay cash dividends, and 0 otherwise. The coefficients for dividends are significant at the 1% or 5% level, indicating that firms paying dividends tend to disclose fewer and less detailed KAMs. These regression results consistently reinforce our main findings. Although the detailed statistics for the covariates before and after the matching are not provided here for conciseness, these supplementary analyses support our initial findings. Overall, our primary inferences remain robust after addressing potential endogeneity issues.
Entropy balancing and propensity score matching results (PSM)
| Variables | Entropy balancing | PSM | ||
|---|---|---|---|---|
| NumKAM | WordKAM | NumKAM | WordKAM | |
| Cash_Div_dum | −0.121*** (−2.020) | −0.180** (−2.824) | −0.217** (−2.018) | −0.132** (−5.603) |
| Constant | −0.400* (0.792) | 4.312*** (8.641) | 1.511*** (0.951) | 4.605*** (2.472) |
| Controls | Yes | Yes | Yes | Yes |
| Year FE | Yes | Yes | Yes | Yes |
| Industry FE | Yes | Yes | Yes | Yes |
| Observations | 932 | 932 | 112 | 112 |
| Adjusted R2 | 0.480 | 0.413 | 0.613 | 0.602 |
| Variables | Entropy balancing | |||
|---|---|---|---|---|
| NumKAM | WordKAM | NumKAM | WordKAM | |
| Cash_Div_dum | −0.121 | −0.180 | −0.217 | −0.132 |
| Constant | −0.400 | 4.312 | 1.511 | 4.605 |
| Controls | Yes | Yes | Yes | Yes |
| Year | Yes | Yes | Yes | Yes |
| Industry | Yes | Yes | Yes | Yes |
| Observations | 932 | 932 | 112 | 112 |
| Adjusted R2 | 0.480 | 0.413 | 0.613 | 0.602 |
This table presents regression results under entropy balancing and propensity score matched sample. Reported coefficients are accompanied by t-statistics in parentheses. Variable definitions are provided in Table 2, and all continuous variables are winsorized at the 99th percentile. ***, ** and * denote statistical significance at the 1, 5 and 10% levels, respectively
5.7 Robustness tests
To ensure the robustness of our findings, we conduct a battery of tests using alternative measures of both cash dividends and KAM disclosures. As presented in Table 12, we use four different proxies for cash dividends to capture various dimensions of dividend behavior. First, we include a cash dividend dummy, coded as 1 for dividend-paying firm-years and 0 otherwise. Second, we use dividend per share (DPS), calculated as total cash dividends divided by the number of shares outstanding. Third, we introduce a change in dividend status variable, coded as 1 for firm-years that issued dividends in the current year but not in the previous year (dividend initiation), 0 for no change, and −1 for firm-years that did not issue dividends in the current year but did so in the previous year (dividend omission). Finally, we use an increase in dividend variable, coded as 1 if there was an increase in dividend compared to the prior year, and 0 otherwise. Previous studies have utilized these measures of cash dividends, which are widely accepted as credible signals of reduced information asymmetry. The act of paying dividends is viewed as an observable commitment to shareholder returns (Bhattacharya, 1979; Miller and Rock, 1985). Additionally, dividends per share (DPS) reflect the actual cash distributed to each shareholder and closely align with the investor-focused signaling theory (Lintner, 1956; Long, 1978).
Robustness test (alternative measures of cash dividend)
| Variables | (1) NumKAM | (2) WordKAM | (3) NumKAM | (4) WordKAM | (5) NumKAM | (6) WordKAM | (7) NumKAM | (8) WordKAM |
|---|---|---|---|---|---|---|---|---|
| Cash_Div_Dum | −0.165*** (−3.589) | −0.082* (−1.725) | ||||||
| DPS | −0.101* (−1.749) | −0.162*** (−2.713) | ||||||
| Change_Div_Status | −0.099* (−1.325) | −0.141* (−1.804) | ||||||
| Increase_Div | −0.056* (−1.673) | −0.028 (−0.809) | ||||||
| Constant | −1.036*** (−4.093) | 4.052*** (15.379) | −1.335*** (−4.640) | 3.800*** (12.725) | −1.037*** (−3.549) | 3.965*** (12.989) | −0.944*** (−3.725) | 4.099*** (15.630) |
| Controls | Yes | Yes | Yes | Yes | Yes | Yes | Yes | Yes |
| Year FE | Yes | Yes | Yes | Yes | Yes | Yes | Yes | Yes |
| Industry FE | Yes | Yes | Yes | Yes | Yes | Yes | Yes | Yes |
| Observations | 932 | 932 | 777 | 777 | 679 | 679 | 679 | 679 |
| Adjusted R-squared | 0.231 | 0.241 | 0.238 | 0.243 | 0.226 | 0.258 | 0.221 | 0.238 |
| Variables | (1) NumKAM | (2) WordKAM | (3) NumKAM | (4) WordKAM | (5) NumKAM | (6) WordKAM | (7) NumKAM | (8) WordKAM |
|---|---|---|---|---|---|---|---|---|
| Cash_Div_Dum | −0.165 | −0.082 | ||||||
| −0.101 | −0.162 | |||||||
| Change_Div_Status | −0.099 | −0.141 | ||||||
| Increase_Div | −0.056 | −0.028 (−0.809) | ||||||
| Constant | −1.036 | 4.052 | −1.335 | 3.800 | −1.037 | 3.965 | −0.944 | 4.099 |
| Controls | Yes | Yes | Yes | Yes | Yes | Yes | Yes | Yes |
| Year | Yes | Yes | Yes | Yes | Yes | Yes | Yes | Yes |
| Industry | Yes | Yes | Yes | Yes | Yes | Yes | Yes | Yes |
| Observations | 932 | 932 | 777 | 777 | 679 | 679 | 679 | 679 |
| Adjusted R-squared | 0.231 | 0.241 | 0.238 | 0.243 | 0.226 | 0.258 | 0.221 | 0.238 |
This table presents the robustness test results using four alternative measures of cash dividends: (i) Cash_Div_Dum, a binary variable equal to 1 if the firm pays a dividend and 0 otherwise; (ii) DPS (Dividend Per Share), calculated as cash dividends divided by the number of shares outstanding; (iii) Change_Div_Status, coded as 1 if a firm initiates a dividend, 0 if there is no change, and −1 if the firm ceases to pay dividends compared to the prior year; and (iv) Increase_Div, a binary variable equal to 1 if there is an increase in DPS compared to the previous year, and 0 otherwise. Reported coefficients are accompanied by t-statistics in parentheses. Variable definitions are provided in Table 2, and all continuous variables are winsorized at the 99th percentile. ***, ** and* denote statistical significance at the 1, 5 and 10% levels, respectively
Table 12 reports results for robustness tests using alternative measures of cash dividends, including a dividend dummy, dividend per share (DPS), change in dividend status, and increase in dividends. Across all specifications, the coefficients remain negative and statistically significant (except for the coefficient on increase in dividend with the extent of KAMs, as in Column 8), indicating that cash dividends are associated with fewer and less extensive KAM disclosures. These findings reinforce our main results and confirm that various forms of dividend signaling are consistently linked to lower perceived audit risk.
Additionally, we conduct robustness tests using alternative measures of KAM disclosures, focusing on client-specific KAM – those uniquely tailored to the audited firm and not boilerplate industry-generic KAM – to better capture the auditor’s judgment about firm-specific risks. We follow Rahaman and Chand (2022) to classify reported KAM into 25 categories. We then identify the five most reported KAMs (industry-generic) in each of the sampled industries. We borrow the idea of Zeng et al. (2021) to identify client-specific KAM, i.e. a KAM that is not an industry-generic KAM. Client-specific KAM is a dummy equal to 1 if a client firm has a client-specific KAM (where a client-specific KAM is one that is not one of the five commonly reported KAM in an industry) and 0 otherwise. We run a logistic regression where the dependent variable is the presence of client-specific KAM, and the key independent variables are the alternative measures of cash dividends: Cash_Div_Dum, Change_Div_Status and Increase_Div. In addition to the binary measure, we also use a count variable representing the number of client-specific KAMs to capture the extent of firm-specific audit disclosures. To address potential selection bias, we apply a propensity score matching (PSM) technique to compare dividend-paying firms with nondividend-paying firms. We implement 1:1 nearest-neighbor matching with replacement to reduce covariate imbalance and ensure comparability between the treatment and control groups.
Table 13 shows results for the robustness tests using alternative measures of KAM disclosures, focusing on client-specific KAM as a binary variable and as a count. The results indicate a negative and significant association (mostly at 1% and 5% level) between cash dividend measures (Cash_Div_Dum, Change_Div_Status, Increase_Div) and client-specific KAM disclosures. This suggests that dividend-paying firms tend to have fewer client-specific KAMs, reinforcing the idea that dividends signal lower audit risk or information asymmetry.
Robustness test (alternative measure of KAMs)
| Variables | (1) Client_Specific KAM | (2) Count Client_Specific KAM | (3) Client_Specific KAM | (4) Count Client_Specific KAM | (5) Client_Specific KAM | (6) Count Client_Specific KAM |
|---|---|---|---|---|---|---|
| Cash_Div_dum | −0.463** (−1.380) | −0.274** (−1.641) | ||||
| Change_Div_Status | −0.191*** (−0.054) | −0.153* (−0.091) | ||||
| Increase_Div | −1.053** (−0.513) | −0.161** (2.023) | ||||
| Constant | −12.438* (2.091) | −1.941*** (1.341) | 0.212* (0.617) | −3.588 (1.012) | −7.032* (6.121) | −4.411*** (3.761) |
| Controls | Yes | Yes | Yes | Yes | Yes | Yes |
| Year_FE | Yes | Yes | Yes | Yes | Yes | Yes |
| Industry_FE | Yes | Yes | Yes | Yes | Yes | Yes |
| Observations | 602 | 602 | 377 | 377 | 692 | 692 |
| Pseudo/Adjusted R2 | 0.475 | 0.281 | 0.323 | 0.452 | 0.196 | 0.201 |
| Variables | (1) Client_Specific | (2) Count Client_Specific | (3) Client_Specific | (4) Count Client_Specific | (5) Client_Specific | (6) Count Client_Specific |
|---|---|---|---|---|---|---|
| Cash_Div_dum | −0.463 | −0.274 | ||||
| Change_Div_Status | −0.191 | −0.153 | ||||
| Increase_Div | −1.053 | −0.161 | ||||
| Constant | −12.438 | −1.941 | 0.212 | −3.588 (1.012) | −7.032 | −4.411 |
| Controls | Yes | Yes | Yes | Yes | Yes | Yes |
| Year_FE | Yes | Yes | Yes | Yes | Yes | Yes |
| Industry_FE | Yes | Yes | Yes | Yes | Yes | Yes |
| Observations | 602 | 602 | 377 | 377 | 692 | 692 |
| Pseudo/Adjusted R2 | 0.475 | 0.281 | 0.323 | 0.452 | 0.196 | 0.201 |
This table presents the robustness test results using alternative measure of KAM (client specific KAM). Reported coefficients are accompanied by t-statistics in parentheses. Variable definitions are provided in Table 2, and all continuous variables are winsorized at the 99th percentile. ***, ** and * denote statistical significance at the 1, 5 and 10% levels, respectively
Furthermore, we argue that dividends signal higher financial prospects and lower information asymmetry when they are paid from operating profits rather than reserves or nonoperating income. To examine this, we constructed a dummy variable identifying firms that pay dividends despite reporting negative operating income – serving as a proxy for dividends potentially funded through nonrecurring profits or reserves rather than sustainable core earnings. We incorporated this variable into our baseline regression models, with both the number and extent of KAM disclosures as dependent variables. The results, shown in Table 14, reveal that dividend paid by loss-making firms (Div_Dummy_Loss) is not significantly associated with either measure of KAM disclosures. We interpret this finding as evidence that while dividend payments may be intended to signal financial strength despite poor operating performance, persistent information asymmetry and a lack of alignment with sustainable earnings exist in these firms, compared to their counterparts. Consequently, auditors may not view these dividends as credible signals of financial health, resulting in no significant reduction in the number or extent of KAM disclosures. This finding reinforces our baseline conclusion that dividends paid from operating income are more effective in signaling financial transparency and lower audit risk, thereby resulting in fewer and less extensive KAMs disclosed by auditors.
Impact of dividend payments despite operating losses on KAM disclosures
| Variables | NumKAM | WordKAM |
|---|---|---|
| Div_Dummy_Loss | −0.077 (−0.073) | 0.028 (0.076) |
| Constant | −1.283*** (0.376) | 3,832*** (0.390) |
| Controls | Yes | Yes |
| Year_FE | Yes | Yes |
| Industry_FE | Yes | Yes |
| Observations | 932 | 932 |
| Adjusted R2 | 0.220 | 0.237 |
| Variables | NumKAM | WordKAM |
|---|---|---|
| Div_Dummy_Loss | −0.077 (−0.073) | 0.028 (0.076) |
| Constant | −1.283 | 3,832 |
| Controls | Yes | Yes |
| Year_FE | Yes | Yes |
| Industry_FE | Yes | Yes |
| Observations | 932 | 932 |
| Adjusted R2 | 0.220 | 0.237 |
This table presents the results of regression analyses examining the association between dividend payments made by firms reporting operating losses and KAM disclosures. Reported coefficients are accompanied by t-statistics in parentheses. Variable definitions are provided in Table 2, and all continuous variables are winsorized at the 99th percentile. ***, ** and * denote statistical significance at the 1, 5 and 10% levels, respectively
6. Conclusion and recommendations
This study contributes to the accounting and finance literature by examining mandatory KAMs reporting and cash dividend payouts in ASX 300 firms in Australia. Despite KAMs’ importance in meeting investor information needs, questions remain about their effectiveness and influencing factors. This research investigates how cash dividends influence KAM disclosures, filling a notable gap in the literature, particularly in a developed economic setting such as Australia. While previous studies have explored various factors affecting KAMs reporting, dividend policy remains relatively underexplored. This study addresses this gap by analyzing how firms’ cash dividend policy is associated with auditors’ risk disclosures, specifically the quantity and the extent of KAM disclosures, offering insights into audit reporting dynamics in diverse economic settings.
Triangulating agency, signaling, and communication theories framework, this study examines and interprets how cash dividends impact KAMs reporting. Drawing on a data set of 932 annual reports from ASX 300 listed firms spanning from 2017 to 2020, our findings indicate a significant negative relationship between cash dividends and both the number and extent of KAMs reported by auditors in their audit reports. These results are robust across alternative measures for KAM and cash dividends. Cash dividends, rooted in agency and signaling theories, reduce information asymmetry by signaling and communicating financial stability and strengths to the shareholders and other market participants. This transparency (i.e. lower information asymmetry) enhances trust between auditors and their clients. Auditors perceive dividend-paying firms as less risky and thus report fewer and less detailed KAMs in these firms.
Furthermore, our study highlights that the association between cash dividends and KAM disclosures is more pronounced in cash-rich, low-risk, and financially nondistressed firms. These firms, due to their cash reserve, simpler operations, and lower risk profiles, typically face fewer challenges with information asymmetry. Cash dividends in these contexts serve as signals of financial health and stability, helping to mitigate perceived risks. Auditors, interpreting these signals, tend to report fewer KAMs with less description as the need for highlighting significant concerns diminishes in these firms. In addition, the negative association between dividend payouts and KAM disclosures is more pronounced during the pre-COVID-19 periods, likely due to the heightened uncertainty and increased auditor judgment during the COVID-19 period, which may have weakened the signaling effect of dividend payments.
Moreover, this study adopts multiple techniques to address potential endogeneity concerns. First, industry and year fixed effects are incorporated into the baseline regression models to control for unobserved heterogeneity that could bias the results. Additionally, alternative measures of both cash dividends and KAM disclosures are used to test the robustness of the findings, ensuring that the results are not sensitive to the specific definitions or metrics employed. Finally, the study employs entropy balancing and propensity score matching (PSM). These approaches specifically mitigate endogeneity issues that may arise from reverse causality, sample selection bias, or omitted variable bias. By balancing covariates and matching treatment observations with control observations, these methods help to mitigate the influence of endogenous factors, thereby providing more reliable estimates of the relationship between cash dividends and KAM disclosures.
This study stands out for its originality across several dimensions, including its innovative concept, rigorous research methodology, and significant findings. To our knowledge, no prior research has explored the relationship between KAMs and cash dividends, making this study unique in its approach. The application of agency, communication, and signaling theories within the KAMs literature represents a novel aspect of this research. The robust models and methodologies employed to test hypotheses provide compelling insights. By bridging the finance (e.g. cash dividends) and accounting literature (e.g. KAMs), this study enriches the understanding of both fields. The implications extend to auditors, companies, investors, and regulators, offering insights into audit strategy refinement, corporate governance alignment, investment decisions, and regulatory policy enhancement. Auditors of dividend-paying firms may interpret cash dividend payments as a signal of lower information asymmetry, strong financial prospects, and managerial credibility. These signals can influence the auditor’s assessment of client risk and shape audit planning decisions. Specifically, consistent dividend payouts – particularly those funded through sustainable operating income – may indicate that the firm is financially stable, transparent in its reporting practices, and less likely to engage in earnings manipulation. As a result, such firms are generally perceived as lower-risk audit clients, which may lead auditors to exercise less intensive scrutiny and report fewer KAMs. For companies, this highlights the strategic value of dividend policy as a mechanism for influencing external perceptions, not just among investors but also among auditors. Firms that maintain transparent and sustainable dividend practices may benefit from more favorable audit assessments, which can improve their credibility in capital markets. For investors, the findings underscore the importance of critically evaluating the source and sustainability of dividend payments. While dividends may signal financial health, the absence of a clear link to operating income – particularly during periods of heightened uncertainty – may diminish their informational value. Investors should therefore consider dividends alongside other performance and governance indicators when assessing firm quality and audit risks. This knowledge enables them to make more informed choices when assessing KAMs in their investment evaluations. For regulators and standard setters, these results suggest that dividend policy can carry unintended signaling consequences in the audit process. During periods of economic instability, such as the COVID-19 crisis, the diminished effectiveness of dividends as a signal underscores the need for enhanced audit disclosure practices and clearer guidelines on how auditors evaluate firms’ financial behavior. Regulators might also consider developing frameworks that help distinguish between dividends as a genuine performance signal and those driven by reputational or impression management motives. Additionally, regulators can consider establishing guidelines or frameworks that encourage more detailed and client-specific KAM disclosures by firms.
Nevertheless, this study acknowledges its limitations. It primarily focuses on testing hypotheses within a developed economy context. Future research could expand these findings by examining emerging economies and cross-country settings for broader applicability. The findings from a developed economy like Australia may not directly apply to emerging markets due to differences in market structure, regulatory environments, and investor behavior. In emerging markets, factors such as higher information asymmetry, less stringent regulatory oversight, and varying investor expectations could influence the relationship between dividends and KAM disclosures differently. Additionally, the study exclusively considers cash dividends, while dividends can take other forms, such as stock dividends or combinations thereof. Exploring different forms of dividend measurement could yield alternative implications. If a firm opts for stock dividends, auditors may need to address KAMs related to valuation, market perception, and potential impacts on cash flow, which may not be as critical in the context of cash dividends. Furthermore, future studies could explore how dividend policy interacts with corporate governance characteristics to provide a more comprehensive understanding of its impact on KAMs’ reporting.
Acknowledgements
The authors are grateful to the Editor and Associate Editor of Meditari Accountancy Research for their constructive guidance throughout the review process. Authors also sincerely acknowledge the valuable comments and suggestions provided by the two anonymous reviewers, which substantially improved the quality and clarity of this paper.
Note
Alternatively, if we use dividend per share (DPS), our baseline results remain the same. We present robustness tests using alternative measures of cash dividend, including DPS, change dividend status, increase dividend, and dividend dummy variable in Table 12.

