Accounting earnings and their components are considered key information used by individuals in decision-making. Investors seek their interests in earnings information. Accounting earnings serve as a signal that influences investors’ beliefs and behaviors. Evidence suggests that accounting earnings are a good indicator of stock returns and a predictor of future cash flows. However, due to the limitations of conservatism and the importance placed on determining accounting earnings, some analysts have concluded that economic earnings are a better indicator for predicting future cash flows.

For reported earnings to assist users in evaluating performance and measuring a company’s profitability, and for stakeholders and investors to estimate their expected returns based on earnings information, the quality of this information must be such that it enables the evaluation of past performance and is effective in measuring profitability and predicting future activities. Therefore, in addition to the reported earnings figure being important to investors and influencing their decisions, the quality of earnings is also a specific dimension of earnings information that attracts investors’ attention.

Consequently, one of the primary objectives of financial reporting is to provide information regarding the performance of a business entity, obtained through the measurement of earnings and their components. A specific interest of financial statement users is to measure the net future cash flows of the business entity to estimate their expected returns Francis et al. [9] Therefore, to enhance the predictive ability of future cash flows, disclosed earnings must be of high quality. The public dissemination of high-quality information by management reduces information asymmetry between management and other users. Based on existing studies, reducing information asymmetry, in turn, leads to a reduction in the cost of capital, a decrease in information risk, an improvement in the ability to predict cash flows, better company valuation, and increased stock liquidity.

On the other hand, the separation of ownership and management, a key characteristic of public joint-stock companies, grants managers and major shareholders exclusive access to certain information. In such a situation, it is said that information asymmetry exists in the economy. Furthermore, shareholders and creditors cannot directly monitor the extent and quality of managers’ efforts in conducting business operations. In such cases, managers may shirk any effort to achieve the business entity’s goals and attribute any performance problems to factors beyond their control. Consequently, serious problems arise for both investors and efficient economic operations [10].

Previous evidence indicates that earnings quality has both positive and negative effects on the cost of debt. Although a negative relationship exists between earnings quality and the cost of debt, Valipour and Moradbeygi [11] demonstrated that this relationship is positive (negative) at low (high) debt levels. Additionally, the theories of Valipour and Moradbeygi [11] and Francis et al. [9] suggest that poor accruals quality is associated with higher debt costs. In contrast, Fung and Goodwin [12] found that short-term debt is positively related to earnings management. Moreover, Rodríguez-Pérez and Van Hemmen [13] concluded that an increase in debt provides managers with incentives to manipulate earnings. Therefore, managers have incentives to obtain information through higher quality, which reduces the cost of debt.

On the other hand, due to conflicts of interest among various stakeholder groups, there is a possibility of biased reporting. In other words, when certain individuals, such as managers and major shareholders, possess more information about the company’s current status and future prospects than other investors, they can exploit this information advantage through various methods to their benefit and to the detriment of other investors. Consequently, doubts regarding the reliability of financial statements have led to a demand for independent oversight in the preparation of financial statements, or in other words, independent audit services.

It is impossible for shareholders and creditors to directly monitor the quantity and quality of managers’ efforts in conducting business operations. In such situations, managers may shirk any effort to achieve the business entity’s goals and attribute any performance problems to factors beyond their control. Consequently, serious problems arise for both investors and efficient economic operations [10]. Therefore, accounting and reporting serve as a mechanism to reduce information asymmetry, thereby ensuring that internal organizational information is reliably transferred to external users.

Furthermore, there is discussion regarding the relationship between audit quality and debt costs. Pittman and Fortin [14] stated that the six largest auditors, by enhancing the credibility of financial statements and reducing debt costs associated with monitoring expenses, are also able to lower the interest rates for young companies. Similarly, Blackwell et al. [15] noted that auditing can reduce bank costs related to debt for privately held companies in the United States. Likewise, Kim et al. [16] demonstrated that the big four auditors can reduce costs associated with borrowing. Causholli and Knechel [17] stated that companies that are young at the time of their IPO pay higher interest rates, and auditors play a crucial role in reducing costs related to financial debt.

Furthermore, Karjalainen [18] found that the interest rate on debt for privately held companies is inversely related to the perceived quality of the auditor. Persakis and Iatridis [19] in a study titled “cost of capital, audit quality, and earnings quality under financial crisis”, concluded that the relationship between earnings quality and cost of capital before the financial crisis was negative and significant; additionally, companies with an audit committee have lower debt costs. Karjalainen [18] demonstrated in their research that Big Four auditors and joint audits with more than one responsible auditor are associated with reduced debt costs. Moreover, companies with qualified audit reports and low accruals quality incur higher debt costs.

Chen et al. [20] showed that due to differences in ownership nature, agency relationships, and bankruptcy risks, state-owned enterprises have fewer incentives for earnings management. Therefore, when both state-owned and non-state-owned enterprises hire high-quality auditors, earnings management decreases more significantly in non-state-owned enterprises compared to state-owned ones. Francis et al. [7] examined the relationship between eight earnings quality indicators and the specific cost of debt and common equity. The results indicate that companies with low earnings quality have higher debt costs and common equity costs compared to those with high earnings quality.

Kordestani and Majdi [21] investigated the relationship between five earnings quality characteristics earnings persistence, predictability, relevance to stock value, timeliness, and conservatism and the cost of equity. They found a negative relationship between earnings quality characteristics (persistence, predictability, relevance to stock value, and timeliness) and the cost of common equity. However, no significant relationship was observed between earnings conservatism and the cost of common equity.

Mojtahedzadeh and Babaei [22] stated that as audit quality increases, the cost of equity decreases; in other words, there is a significant negative relationship between these variables. Hajihah and Sobhani [23] demonstrated that the size of the audit firm and the continuity of the relationship between the audit firm and the client have a significant negative relationship with the company’s cost of capital. Therefore, it can be concluded that audit quality reduces the cost of capital for manufacturing companies listed on the Tehran Stock Exchange.

However, Karami et al. [24] investigated the relationship between audit quality components and cost of capital, and their findings indicated no significant relationship between various audit quality components and the cost of capital.

I. Audit quality has a significant impact on the cost of debt.

II. Earnings quality has a significant impact on the cost of debt.

The present research is descriptive-correlational in method and applied in purpose. The statistical population includes all companies listed on the Tehran Stock Exchange that have been continuously active from 2018 to 2024. The data collection method is field-based, using the Tehran Stock Exchange databases as the primary tool. To collect the required data for calculating research variables, the “rahavard novin” and “tadbir pardaz” databases were utilized. The sampling method was purposive and systematic, selecting 148 companies from the total available companies for hypothesis testing.

Based on the aforementioned explanatory variables, the study by Persakis and Iatridis [19] has been utilized:

CODit = β0 + β1Profitabilityit + β2BMit + β3Leverageit + β4Sizeit + β5IntCovit + β6LnNIBEit + β7LnMVEit + β8Collateralit + β9NEGEQit + β10Riskit + β11 − 15AQk, it + εit CODit = β0 + β1Leverageit + β2Sizeit + β3profitabilityit + β4 IntCovit + β5LnNIBEit + β6EPSit + β7ΔEPSit + β8Profitit + β9Incrit + β10CFOit + β11 − 19EQk, it + εit COD is the cost of debt, referring to the effective rate paid by a company on its current liabilities. This term refers to the after-tax cost of debt, but it also refers to the pre-tax cost of debt. The difference between pre-tax and after-tax cost of debt is that, in fact, interest expense is tax-deductible. Nowadays, in financial and accounting research, the cost of debt is calculated by dividing interest expense by interest-bearing debt. In this study, the cost of debt is measured through the ratio of interest expense in year t+1 to the average of unpaid interest-bearing debt during years t and t+1.

Profitability is estimated using return on assets (net income divided by assets); Book-to-Market (BM) is estimated by dividing the book value of equity by the market value of equity; Leverage is calculated by dividing total debt by total assets; Size is estimated using the natural logarithm of total assets; Interest Coverage Ratio (Intcov) is calculated as the ratio of Earnings Before Interest and Taxes (EBIT) to interest expenses; LnNIBE is the natural logarithm of net income before extraordinary items; LnMVE is the natural logarithm of the market value of equity; Collateral refers to the value of collateral or asset structure related to assets, estimated by dividing the ratio of intangible assets to total assets; NEGEQ takes the value of 1 if shareholders’ equity is negative, and 0 otherwise.

∆EPS represents the change in earnings per share before extraordinary items in year t and t−1; Profit is a dummy variable that takes the value of 1 when a company’s earnings per share before extraordinary items is greater than or equal to 0, and 0 otherwise; Risk is considered credit risk, calculated as the ratio of the standard deviation of operating cash flows to the average total assets over years t−1 and t:

AQ1 is the Audit Quality (1) variable, representing the size of the audit firm. It is a dummy variable that equals 1 if the audit services are performed by the Court of Audit, and 0 otherwise. AQ2 is the Audit Quality (2) variable, calculated through audit fees. AQ3 is the Audit Quality (3) variable, representing auditor change. It equals 1 if the company changes its auditor, and 0 otherwise. AQ4 is the Audit Quality (4) variable, representing an adjusted audit report opinion. It equals 1 if the opinion is qualified, and 0 otherwise. AQ5 is the Audit Quality (5) variable, representing the audit committee. It equals 1 if the company has an audit committee, and 0 otherwise. EQ1 is the earnings Quality (1) model by Basu [1], measured as follows:

Xit = β0 + β1Rit + β2DRit + β3Rit ∗ DRit + εit Pit−1 Xit: earnings per share Pit−1: lagged share price Rit: annual return DRit: dummy variable equal to 1 if return is negative, and 0 otherwise

εit: model residual EQ1: the earnings quality model by Beaver and Ryan [2], used as a conservatism measure, calculated as the ratio of the book value to the market value of shareholders’ equity as follows:

EQ3: the earnings Quality (3) model by Ohlson [3], where the value relevance is estimated through the explanatory power of the following model:

Pit = β0 + β1Eit + β2BVit + εit

Pit: share price Eit: earnings per share BVit: book value per share εit: model residual EQ4: the earnings Quality (4) model by Dechow et al. [4], which uses the residual of the following regression model as a measure of accrual quality:

TAit = β0 + β1 ( ) + β2(∆REVit − ∆RECit) + β3GPPEit + εit Ait−1 TAit: accruals, scaled by lagged total assets. Accruals are calculated as the change in current assets (excluding cash) minus the change in current liabilities (excluding short-term debt and taxes payable), minus depreciation. Ait−1: lagged total assets ΔREVit: change in revenues, measured as the difference between revenues of two consecutive periods divided by total assets at the beginning of the period.

ΔRECit: change in receivables, measured as the difference between receivables of two consecutive periods divided by total assets at the beginning of the period.

GPPEit: net property, plant, and equipment, scaled by total assets.

εit: model residual EQ5 McNichols [5] earnings quality model, which is estimated through the standard deviation of the residuals of the following accruals model:

TCAit CFOit−1 CFOit CFOit+1 = β0 + β1 + β2 + β3 TotalAssetsit−1 TotalAssetsit−1 TotalAssetsit−1 TotalAssetsit−1 ∆REVit PPEit + β4 + β5 .

TotalAssetsit−1 TotalAssetsit−1 TCAit: total accruals. Total accruals are derived from the difference between the annual change in current liabilities and the annual change in current liabilities minus the annual change in cash, plus the change in current liabilities in accruals, plus the change in taxes payable.

Total Assetit: total assets with a lag CFOit: operating cash flow. Operating cash flow is calculated as the difference between net income before extraordinary items and total accruals.

ΔREVit: change in revenues PPEit: property, plant, and Equipment εit: model residual EQ6: Kothari et al. [25] earnings quality model, which is similar to Dechow et al. [4] and is estimated using the following regression residual:

TAit = β0 + β1 ( ) + β2(∆REVit − ∆RECit) + β3GPPEit + β4ROAit−1 + εit Ait−1 ROAit-1: return on assets (lagged) EQ7: Kormendi and Lipe [6] earnings persistence model, which uses the current year’s company earnings relative to past year earnings to estimate the slope coefficient (β1), which is the estimator of earnings persistence:

Earnit Earnit−1 = β0 + β1 + εit TotalAssetsit TotalAssetsit−1

Earnit: net income before extraordinary items.

Earnit-1: lagged net income before extraordinary items.

εit: model residual.

EQ8: Francis et al. [7] earnings predictability model, calculated as the square root of the variance of the error term from the Kormendi and Lipe [6] model:

√σ2(ε ̂it) EQ9: Leuz et al. [8] earnings smoothing model, derived from the following relationship:

σ(CFOit⁄TotalAssetsit−1) σ(Earnit⁄TotalAssetsit−1)

Stationarity of research variables means that the mean and variance of the variables, as well as the covariance between variables across different years, remain constant over time. Consequently, using these variables in the model does not lead to spurious regression . Based on the Fisher Chi-Square test results (Table 2), since the P-value for all variables is less than 0.05, the research variables are stationary throughout the study period.

The first model of the study indicates that audit quality has an impact on the cost of debt. After testing the regression assumptions and confirming their validity, the results of fitting the aforementioned regression equation are presented in Table 3. The F-statistic value (4.94) also indicates the significance of the overall regression model. As shown in the lower part of Table 3, the R-squared and adjusted R-squared of the model are 58% and 46%, respectively. Therefore, it can be concluded that in the aforementioned regression equation, only about 58% of the cost of debt under study is explained by the independent and control variables. Among the five audit quality indicators, the indicators (AQ5, AQ4, AQ2, AQ1), which respectively represent audit firm size, audit fees, modified audit opinion, and audit committee, have a significant negative impact on the cost of debt.

Furthermore, the second model of the study indicates whether earnings quality has an impact on the cost of debt. After testing the regression assumptions and confirming their validity, the results of fitting the aforementioned regression equation are presented in Table 4. The F-statistic value (4.7) also indicates the significance of the overall regression model. As shown in the lower part of the table, the R-squared and adjusted R-squared of the model are 57% and 45%, respectively. Therefore, it can be concluded that in the aforementioned regression equation, only about 57% of the cost of debt under study is explained by the aforementioned independent and control variables. According to Table 4, among all earnings quality indicators, the indicators (EQ1, EQ2, EQ3, EQ4, EQ6, EQ7), which respectively represent the Basu earnings quality model, Beaver and Ryan [2] Dechow et al. [4], Kothari et al. [25], and Kormendi and Lipe [6], have a significant positive impact on the cost of debt.

This study examined the impact of audit quality and earnings quality on the cost of debt. The results indicate that among the five audit quality indicators, four showed a significant negative impact on the cost of debt. Furthermore, among the nine earnings quality models, six demonstrated a significant positive impact on the cost of debt. Based on these findings, it can be argued that as audit quality increases, the cost of debt increases. This result is attributed to the fact that although the financing system in Iran is primarily channeled through banks and other financial institutions via credit, lenders do not place much importance on the manner and quality of reports and information disclosed by companies; they may focus solely on the quality of reported earnings. The results of this study align with expectations. The outcome of the first hypothesis is consistent with the findings of Karjalainen [18], while it contradicts the results of Patsakis and Latridis [26].

Since companies must disclose high-quality earnings to enhance their ability to predict future cash flows, the public dissemination of high-quality information by management reduces information asymmetry between management and other users, including lenders. Lenders are considered a key source of corporate financing. To mitigate lending risks, they examine the financial information of companies applying for loans. Consequently, they require reliable information to analyze financial statements and determine the loan amount and cost of debt.

Comparison with Previous Studies: the results of this study align with expectations. The outcome of the second hypothesis is consistent with the findings of Francis et al. [7], and Patsakis and Latridis [26].

The author would like to express sincere appreciation to all individuals and institutions who contributed to the completion of this research through their valuable guidance, support, and cooperation

This research received no external funding.

The data supporting the findings of this study are available from the corresponding author upon reasonable request. No publicly archived datasets were generated during the current study.

The author declares no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript; or in the decision to publish the results.