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Audit Report Lag and Cost of Equity Capital


Academic year: 2023

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Audit Report Lag and Cost of Equity Capital

Md. Borhan Uddin Bhuiyan School of Accountancy Massey Business School

Massey University New Zealand

Phone: +6494140800 (ext. 43290) email: [email protected]


Yimei Man1

Department of Accountancy and Finance University of Otago

New Zealand

1 Corresponding author




This research investigates the effect of audit report lag on the cost of equity capital. We argue that an extended audit report lag may perceive questionable accounting practice and unfavorable auditor opinion, which raise a concern on financial reporting quality results in increased cost of equity capital. Using a sample of the listed US companies, we find that firms with higher audit report lag have a higher cost of equity capital. Our findings are consistent with the argument that the lengthy audit report lag raised concerns to the investors' results in higher cost of equity capital.

Keywords: Audit report lag, information, cost of equity capital.



Audit Report Lag and Cost of Equity Capital

1. Introduction

This study examines the relationship between audit report lags (ARL) and the cost of equity capital (CoC). Timeliness is one of the qualitative attributes of financial accounting information and regards as a way of reducing information asymmetry by improving the pricing of securities and helps investors efficient decision making. Al-Ajmi (2008) explains that accounting information loses its economic value in the absence of timeliness. As the audited annual report is the primary source of information for the investor, the more promptly the information delivered to users of financial statements, the more relevant it is to the process of efficient decision-making. Empirical research indicate that ARL is affected by audit and auditor attributes (e.g. auditor affiliation, auditor tenure, non-audit services, going concern opinion, and auditor changes), firm-specific fundamental variables (e.g., the complexity of the audit due to client size, foreign operations or number of subsidiaries), client financial condition (existence of loss and/or distress risk) and organizational risk (e.g., leverage) (Abernathy, Barnes, Stefaniak, & Weisbarth, 2017). However, the empirical research on the consequence of audit report lag is still infancy.

We choose the cost of equity is a natural consequence of audit report timeliness because external stakeholders consider audit report to be a great value, and hence the timing of the release of an audit report became a crucial input for investment decision (Habib, Bhuiyan, Huang, & Miah, 2019). Also, Audit report timeliness viewed as a way of reducing information asymmetry by improving the pricing of securities, and by mitigating insider trading, leaks, and rumors in the market, and reducing the opportunity to spread rumors about the companies’

financial health and performance. Impact of audit report lag has many aspects such as audit



report delay has a likely impact on deferring earnings announcement, reduce earnings informativeness and generate a lower market response to earnings (Bamber, Bamber and Schoderbek, 1993).

A key objective of regulators and standard-setters is to provide useful information to investors so that they can make informed investment decisions (Financial Accounting Standards Board [FASB], 1978). Easley and O’Hara (2004) show that investors rely on information from different sources for investment decision and decide what portfolio of investment will provide them with the desired mix of risk and return. Investors require a higher (lower) return from the risky (less risky) investment, but releasing timely information reduces the uncertainty of the investment, which makes investment decision less risky results at a lower cost. Botosan and Plumlee (2002) evidence that a firm which conducts more voluntary disclosure is in the annual report has a lower cost of equity than firms that have little or no voluntary disclosure. When making investment decisions, investors must make a trade-off between risk and return. To obtain the desired mix of risk and return, investors require a high return from risky investments, whereas a low return form investment with little/no risk. If there is a reward for timely audit report, CoC is relevant.

Regulatory change over the last decade indicates that the Securities Exchange Commission prioritize improving audit report timeliness. In 1970, the Securities Exchange Commission mandated 90 days to release an audited annual report to the stakeholders. In September 2002, SEC adopted new regulation decreasing that time to 75 days for registrants that meet the primary size-based criteria classified as “accelerated” filers. The SEC argued that advancement of information technology and accounting systems should enable firms to file more quickly: an act that would improve capital market efficiency, i.e., more efficient valuation and pricing of securities (Securities & Commission, 2002). However, this decision triggered



controversy with the critics arguing that “…accelerated deadlines would likely lead to an increase in undetected misstatements and negatively impact the quality of financial reports”

(Bryant-Kutcher, Peng, & Weber, 2013, p. 478).

Using data from companies listed in the USA stock exchange during 2001 to 2015 sample period, we find that firms with higher audit report lag (measured as the number of calendar days from fiscal year-end to the date of the auditor’s report) have a higher cost of capital. Prior research evidence that a lengthy audit report lag is a warning signal as a longer than expected ARL may often suggest the presence of prolonged auditor–client negotiations to settle significant disagreements between the auditor and the clients. Consistent with the previous research, we evidence in support of the prediction that the audit report lag is positively associated with the cost of equity capital.

The remainder of this paper is organized as follows. Section 2 presents the existing literature and develop a hypothesis on the association between audit report lag and cost of equity capital. The research methods and sample selection are described in Section 3.

Descriptive statistics and test results are reported in Section 4. Finally, Section 5 concludes the paper.

2. Literature review and hypothesis development

The timeliness of the information release has been found as an essential factor in affecting the cost of equity (Dechow, Ge, & Schrand, 2010; Francis, LaFond, Olsson, &

Schipper, 2004). Consistently, audit report lag is critically essential attributes of capital market activities. Beaver (1968) posits that investors may postpone their purchases and sales of securities until the earnings report is released. Equally, the investors would probably search for an alternative source of information. The delayed disclosure may encourage individual



investors to acquire costly ‘pre-disclosure’ private information and exploit their private information at the expense of “less informed” investors (Bamber, Bamber, & Schoderbek, 1993).

The stakeholders often interpret a lengthy ARL as a signal of a problem audit (Alan I Blankley, Hurtt, & MacGregor, 2014). ARL reflects the audit efforts, and incremental audit efforts are positively associated with ARL (Knechel & Payne, 2001). As abnormally long ARL associates with uncertainty and risk, the image of the company would be perceived negatively by the market and investors would consider the investment riskier, which would increase CoC.

Prior literature provides evidence that the market generally reacts negatively to delays of information release, which can lead to a higher CoC. Easley and O'hara (2004) show that the cost of capitals is influenced by the impact on the precision and quantity of information available to investors.

Empirical research evidence that firm profitability is highly associated with the audit report timeliness such as less profitable companies tends to have more extended audit reporting lag (Courtis, 1976; Davies & Whittred, 1980; Habib et al., 2019; Owusu-Ansah, 2000).

Companies which experience negative profit, generally have the incentive to delay the announcement of bad news by delaying the commencement date of audit. When firm incurs losses, auditors tend to be more cautious in the auditing process, given that the loss increases the likelihood of financial failure of management fraud (Carslaw & Kaplan, 1991). Good news firms are found to release report earlier than bad news firms, and firms suffer from loss tend to have the longest delay (Haw, Qi, & Wu, 2000). Therefore, losses incurred triggers more substantive tests to confirm if the company is going concern, more time and efforts are invested in the auditing process, hence the delay in the audit report. Extreme changes in profitability can also lead to reporting lags (Davies & Whittred, 1980), as earnings volatility signals risk,



and prompt the auditors to conduct more substantive tests to provide reasonable assurance. For example, in Australia, extreme changes in profitability are found to extend the audit reporting time (Davies & Whittred, 1980). Evidence from a developing country, Zimbabwe, also support a negative relation between profitability and audit reporting lead time (Owusu-Ansah, 2000).

A stream of academic research evidence that audit report timeliness is associated with the business risk. The higher the degree of the financial risks, the more cautious auditors are when proceeding the auditing procedures to reduce any audit risk. There is a higher chance of misreporting and financial failure in financially distressed companies with a high leverage level, which exposes auditors to greater audit risk (Arens, Loebbecke, Elder, Beasley, & American Institute of Certified Public, 2000; Krishnan, 2005). As a result, to react to the additional audit risk associated with the firms in a weaker financial condition, auditors are more sceptical when verifying the reliability of the financial statement of distressed firms, hence end up with longer audit report delays. Also, companies that have abnormal ARL are subject to a higher likelihood of restatement (Alan I Blankley et al., 2014), which exposes investors to risk and increases firm’s cost of equity (Hribar & Jenkins, 2004). Furthermore, inherent risk due to the inherent nature of the client’s industry can pertain to ARL. Firms in the litigious industry, such as innovative firms, are subject to higher inherent risk and also more prone to volatile profit (Bedard & Johnstone, 2004). In order to provide reasonable assurance for firms with higher inherent risk, auditors commonly assign more experienced staff, industry expertise on board and conduct more extensive tests; therefore, more audit work is required, hence extended ARL.

Internal control that consists of policies and procedures to provide reasonable assurance on the reliability of financial reporting is essential to auditors. The weaker the internal control the client has, the more reliance auditors place on substantive tests. With high control risk, extensive substantive testing which can be much more time consuming than the test of controls



is performed, therefore delays in audit reporting. While with an effective internal control/

reduced control risk, only limited substantive testing is performed. The prior studies provide evidence that internal control weakness is positively associated with ARL. For example, in the U.S., Ettredge, Li, and Sun (2006) find that the presence of material internal control weakness is associated with longer ARL using data from the post-SOX 404 periods of 2003-2004.

Munsif, Raghunandan, and Rama (2012) extend Ettredge et al. (2006) study using data from the period of 2008 and 2009 and find consistent evidence that ARL declines significantly with an effort to remediate material control weakness among accelerated filers. Again, Mitra, Song, and Yang (2015) find that the presence of material internal control weakness significantly increases audit report lag. In Egypt, Khlif and Samaha (2014) find that higher internal control quality contributes significantly to reduce the audit component of ARL. Furthermore, internal control weakness/deficiencies are found to translate to a higher cost of equity. Ogneva, Subramanyam, and Raghunandan (2007) state the reasons to expect higher CoC for firms with internal control weakness include, firstly internal control weakness negatively affect accounting quality, which leads to higher information risk that incurs high CoC; secondly, internal control weakness increases idiosyncratic risk and therefore high CoC. Ashbaugh‐

Skaife, Collins, Kinney Jr, and LaFond (2009) show clear evidence that firms with internal control deficiencies have a significantly higher cost of equity.

Hypothesis development

Audit report lag is a critical factor in the investment decision making as the audited financial statements in the annual report are the only reliable source of information available to investors. Ideally, the audit report contains the auditor's opinion regarding the credibility of the financial statements; therefore, investors generally prefer short ARL. Since longer ARL generally raise concern to the stakeholders; as a result, they would require a higher rate of



returns on their investment to compensate for the perceived risk. The return demanded by investor determines a firm’s cost of capital; therefore, it will be more costly for the firms to raise capital from the capital market. Previous research evidence that longer ARL raises concerns of going concern opinion, restatements and poor quality of earnings, which also could be a potential driving factor to increase the cost of equity capital.

An Audit report contains the auditor’s opinion regarding the credibility of the financial statements. Investors generally prefer short audit report lags; otherwise, it loses some of the economic value (Al-Ajmi, 2008). A longer audit report signals a potential problem in the auditing process (Alan I. Blankley, Hurtt, & MacGregor, 2015). Asthana (2014) argues that abnormal audit delay creates scepticism among investors about earnings quality, and they value the disclosed earnings after discounting for such delay. Empirical research evidence that firms with long audit reporting lags are more likely to have the receipt of non-standard opinions in subsequent periods (Chan, Luo, & Mo, 2016), and are likely to engage in restatement in the following year (Chan, Luo & Mo, 2016; Blankley et al., 2014). A longer than expected ARL (abnormal ARL) may often suggest the presence of prolonged auditor–client negotiations to settle significant disagreements between the auditor and the clients. Longer than expected ARL increases information risk in the market since investors cannot make an investment decision on time. Furthermore, asymmetric information in concert with longer ARL requires investors to demand additional risk premium, thus increasing the cost of capital. Therefore, we develop the following hypothesis:

H1: Audit report lag effects the cost of equity capital.

3. Sample and Methodology Sample collection



We use several sources to collect relevant data. The data for the board of directors are taken from Board Analytics, covering mostly S&P 500, S&P MidCap 400, and S&P SmallCap 600 between 2000 and 2018. For each firm in a given year, Board Analytics lists the information for board independence, management ownership, CEO duality, board meeting frequencies. Audit and auditor related data are from ‘Audit Analytics’ which includes audit reporting lag and identity of the auditor. Financial data are from the COMPUSTAT annual industrial file. We merge COMPUSTAT, Board Analyst, and Audit Analyst for 2000 to 2015 provides us with a total of 41,348 firm-year observations. We further require non-missing data for firm-level variables in our main regression models, reducing the sample to 27,140 firm- year observations. We exclude a total of 30 firm-year observations, which shows negative ARL.

Finally, we match the proxy for the implied cost of capital. To calculate the implied cost of capital, we collect analyst earnings forecasts, and stock prices used to calculate the implied CoC from the Institutional Brokers’ Estimate System (I/B/E/S). The calculation requires at least one analyst forecast of one-year-ahead and two-year-ahead earnings per share (EPS) and at least one forecast of the long-term growth rate. Further, one of our calculation of implied CoC measures (CoCMPEG) also requires the two-year-ahead forecasted EPS to be higher than the one-year-ahead forecasted EPS causes another 22,313 missing firm-year observations. Our final sample consists of 4,797 firm-year observations from 2000 through 2015. Our sample is based on firm-calendar years rather than firm-fiscal years. To rule out any potential biases from the outliers, all the continuous variables are winsorized top and bottom at 1% level.

Research Design



To examine whether audit report lag is associated with a lower CoC, we estimate the following regression model.

𝐶𝑜𝐶𝑖,𝑡+1 = 𝜕0+ 𝜕1𝐴𝑅𝐿𝑖,𝑡+ 𝜕2𝐵𝑂𝐷𝑆𝐼𝑍𝐸𝑖,𝑡+ 𝜕3𝐼𝑁𝐷𝐷𝐼𝑅𝑖,𝑡+ 𝜕4𝐶𝐸𝑂𝐷𝑈𝐴𝐿𝑖,𝑡 + 𝜕5𝑀𝐺𝑇𝑂𝑊𝑁𝑖,𝑡+ 𝜕6𝐵𝑂𝐷𝑀𝐸𝐸𝑇𝑖,𝑡+ 𝜕7𝐵𝐼𝐺4𝑖,𝑡+ 𝜕8𝐿𝑁𝑆𝐼𝑍𝐸𝑖,𝑡 + 𝜕9𝐿𝐸𝑉𝐸𝑅𝐴𝐺𝐸𝑖,𝑡 + 𝜕10𝑆𝐴𝐿𝐸𝐺𝑅𝑖,𝑡+ 𝜕11𝐵𝑇𝑀𝑖,𝑡+ 𝜕12𝑍𝑆𝐶𝑂𝑅𝐸𝑖,𝑡 + 𝜕13𝐵𝐸𝑇𝐴𝑖,𝑡+ 𝜕14𝑅𝑂𝐴𝑖,𝑡 + 𝜕15𝐿𝑂𝑆𝑆𝑖,𝑡+ 𝐼𝑁𝐷𝑈𝑆𝑇𝑅𝑌 + 𝑌𝐸𝐴𝑅 +𝑖,𝑡+1… . … … … (1)

There is no consensus on which model works best (Botosan & Plumlee, 2005; Easton

& Monahan, 2005). We follow prior studies (e.g., Dhaliwal, Radhakrishnan, Tsang, & Yang, 2012; Hail & Leuz, 2006) and use the average of the individual measures to reduce the idiosyncratic measurement error across models. Also, we measure the CoC using the average of three measures of the implied CoC. Appendix A briefly describes these measures.

Consistent with the previous research findings, we control for several factors related to firm risk including the firm risk (BETA), size (LNSIZE), leverage (LEVERAGE), sale growth (SALEGR), book-to-market ratio (BTM), bankruptcy risk (ZSCORE), firm performance (ROA), and distress risk (LOSS). Also, we include several internal and external corporate governance proxies such as board size (BODSIZE), board independence (INDDIR), CEO duality (CEODUAL), management ownership (MGTOWN), board meeting frequencies (BODMEET) and auditor quality (BIG4).

4. Empirical Result Descriptive Statistics

Table 2 presents descriptive statistics for the variables used in the regression variables.

The mean value of ARL is 54 days with a standard deviation of 19 days. The average (standard deviation) cost of equity capital is 0.15 (0.10). The sample firm has an average of sales growth 6% and the mean (standard deviation) leverage is 0.23 (0.13). The average return on assets



(ROA) is 0.11. A total of 87 per cent of sample firms are audited by BIG4 audit firms. The average board size of the sample firms are approximately 6 directors (6.47) and 47 percent of the board members are represented by the independent directors. Also, the average meeting frequencies of the sample firms are approximately four times (4.75), and the average management ownership is 7 per cent of the total outstanding shareholdings.

Correlation Analysis

Table 3 presents the Pearson correlation among all the variables included in this study.

The main variable of interest ARL and CoC proxies (all the four measures Ke; PEG; MPEG;

and AVGCOE) are positive and statistically significant at 1% level. Firms which has CEO- duality, higher managerial ownership, and negative profit earners have a higher cost of equity capitals (all the four measures Ke; PEG; MPEG; and AVGCOE). Profit-making firms and firms which have higher sales growth shows negative correlation indicating a lower cost of equity capital. Firms which has a higher proportion of independent directors shows a negative cost of equity capital. Also, the cost of equity shows a negative correlation with the firms, which has higher meeting frequencies. Above-mentioned discussed findings are statistically significant at 1% level.

Regression Analysis

We now turn our attention to the multivariate regression analysis. Table 4 reports the results for the Equations (1). Our dependent variable is CoC, which has four different proxies such as Ke; PEG; MPEG; and AVGCOE. Also, we have two different proxies for audit report timeliness such as ARL and LOG(ARL). We include one independent variable at a time in testing Equation (1) and report the results in Table 4 Columns (1)–(8). We find that audit report lag (both ARL and LOG(ARL)) has a positive association with all the proxies of cost of equity capital which indicates that firms with the lengthy audit report lag have a higher cost of equity



capital. These findings are consistent with the argument that a lengthy audit report lag causes more uncertainty and risk on the unreleased accounting information results in a higher cost of equity capital. Thus, hypothesis 1 is supported. As mentioned in the section of sample selection, the continuous variables are winsorized at the top and bottom 1 per cent of this distribution to control any outlier effect. Also, I calculate the variable inflation factor (VIF), and the variable range from 1.04 to 2.10 indicates that the multivariate regression equation is not biased due to multicollinearity. In respect to heteroscedasticity, I perform the Breuch-Pegan test, which fails to null homoscedasticity, suggesting that heteroscedasticity has not inferred with the regression model. Overall, the control variables show consistent evidence compare to the previous findings. The adjusted R2 of the multivariate regression models ranges from 18 to 33 per cent.

5. Conclusion

This research examines the effect of audit report lag on the cost of equity capital.

Following the stream of accounting research on information asymmetry, business risk and cost of equity capital, we argue that an extended audit report lag raise concerns on questionable accounting practice and unfavourable auditor opinion, which results in increased cost of equity capital. Using a sample of the listed US companies, we find that firms with higher audit report lag have a higher cost of equity capital. Our findings are consistent with the argument that the lengthy audit report lag raised concerns to the investors' results in higher cost of equity capital.




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Table 1: Sample Selection

Details # of firm # of firm

Matching sample with Audit Analytics (AA), Board Analyst (BA) and Compustat

41, 348 Less: Missing sample

After excluding missing sample between AA, BA and Compustat 27,140

Less: Excluded inconsistent negative ARL 30

After excluding negative ARL 27,110

Less: Missing sample from IBES which attributes CoC sample 22,313

Final Sample 4,797

Table 2: Descriptive Statistics

(1) (2) (3) (4) (5)


KE 4,797 0.13 0.12 0.00 0.62

PEG 4,797 0.15 0.11 0.02 0.62

MPEG 4,797 0.15 0.17 -0.17 4.15

AVGCOE 4,797 0.15 0.10 0.01 1.68

ARL 4,797 54.61 19.21 4.00 235.00

LOGARL 4,797 1.71 0.15 0.60 2.37

LNARL 4,797 3.94 0.35 1.39 5.46

SALEGR 4,797 0.06 0.26 -0.84 8.65

LNSIZE 4,797 7.82 2.09 0.79 12.91

BTM 4,797 0.54 0.61 -11.18 16.79

LEVERAGE 4,797 0.23 0.13 0.00 1.00

ZSCORE 4,797 7.44 33.07 -13.18 2,240.73

ROA_EBIT 4,797 0.11 0.24 -2.76 7.72

ROA_NI 4,797 0.07 0.24 -2.28 7.72

LOSS_EBIT 4,797 0.05 0.22 0.00 1.00

LOSS_NI 4,797 0.11 0.31 0.00 1.00

BIG4 4,797 0.87 0.34 0.00 1.00

BETA 4,797 0.88 0.59 -1.43 5.40

MGTOWN 4,797 0.07 0.15 0.00 1.00

BODMEET 4,797 4.75 4.39 0.00 36.00

CEODUAL 4,797 0.37 0.48 0.00 1.00

DIRECTORSOUTSIDE 4,797 4.82 4.08 0.00 16.00

BODSIZE 4,797 6.47 5.13 0.00 17.00

INDDIR 4,797 0.47 0.38 0.00 0.94


Table 3: Correlation Analysis

Variables (1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) (13) (14) (15) (16) (17) (18)

(1) KE 1.000

(2) PEG 0.005 1.000

(3) MPEG 0.012 0.782* 1.000

(4) AVGCOE 0.430* 0.827* 0.879* 1.000

(5) ARL 0.083* 0.122* 0.100* 0.138* 1.000

(6) LOGARL 0.099* 0.113* 0.089* 0.135* 0.918* 1.000

(7) LNARL 0.099* 0.113* 0.089* 0.135* 0.918* 1.000* 1.000

(8) BODSIZE 0.077* -0.114* -0.087* -0.060* 0.026 0.136* 0.135* 1.000

(9) INDDIR -0.069* -0.105* -0.078* -0.055* 0.042* 0.154* 0.154* 0.908* 1.000

(10) CEODUAL 0.103* 0.051* 0.035* 0.042* 0.054* 0.143* 0.143* 0.522* 0.546* 1.000

(11) MGTOWN 0.009 0.031 0.028 0.031 0.134* 0.165* 0.165* 0.232* 0.177* 0.202* 1.000

(12) BODMEET -0.074* -0.057* -0.044* -0.036* 0.060* 0.158* 0.158* 0.772* 0.777* 0.449* 0.150* 1.000

(13) BIG4 0.001 -0.064* -0.056* -0.056* -0.150* -0.116* -0.116* 0.314* 0.287* 0.134* -0.006 0.237* 1.000

(14) LNSIZE 0.124* -0.088* -0.052* -0.011 -0.184* -0.167* -0.167* 0.425* 0.356* 0.197* -0.093* 0.349* 0.479* 1.000

(15) LEVERAGE 0.011 -0.017 0.007 0.003 -0.009 -0.046* -0.046* -0.055* -0.056* -0.081* -0.049* -0.087* 0.034 0.027 1.000

(16) SALEGR -0.053* -0.094* -0.078* -0.103* -0.020 -0.023 -0.023 -0.007 -0.024 -0.058* -0.023 -0.004 -0.002 -0.002 0.027 1.000

(17) BTM -0.044* 0.354* 0.482* 0.394* 0.087* 0.095* 0.094* -0.105* -0.097* -0.050* 0.036 -0.077* -0.118* -0.142* -0.141* -0.080* 1.000

(18) ZSCORE 0.036 -0.051* -0.047* -0.031 0.003 0.004 0.004 -0.035 -0.031 -0.013 0.004 -0.032 -0.028 -0.103* -0.046* 0.057* -0.049* 1.000 (19) BETA 0.038* 0.186* 0.155* 0.176* 0.080* 0.116* 0.116* 0.192* 0.223* 0.206* 0.075* 0.191* 0.089* 0.078* -0.024 -0.089* 0.076* -0.028 (20) ROA_NI -0.092* -0.115* -0.126* -0.078* -0.032 -0.027 -0.027 -0.045* -0.046* -0.024 -0.020 -0.054* -0.105* -0.145* 0.231* 0.073* -0.113* 0.222*

(21) LOSS_NI 0.023 0.399* 0.366* 0.371* 0.077* 0.068* 0.068* -0.125* -0.118* -0.075* -0.001 -0.076* -0.029 -0.063* -0.013 -0.181* 0.225* -0.035

* shows significance at the .01 level


Table 4: Regression Analysis

𝐶𝑂𝐶𝑖,𝑡+1= 𝜕0+ 𝜕1𝐴𝑅𝐿𝑖,𝑡+ 𝜕2𝐵𝑂𝐷𝑆𝐼𝑍𝐸𝑖,𝑡+ 𝜕3𝐼𝑁𝐷𝐷𝐼𝑅𝑖,𝑡+ 𝜕4𝐶𝐸𝑂𝐷𝑈𝐴𝐿𝑖,𝑡+ 𝜕5𝑀𝐺𝑇𝑂𝑊𝑁𝑖,𝑡+ 𝜕6𝐵𝑂𝐷𝑀𝐸𝐸𝑇𝑖,𝑡+ 𝜕7𝐵𝐼𝐺4𝑖,𝑡+ 𝜕8𝐿𝑁𝑆𝐼𝑍𝐸𝑖,𝑡 + 𝜕9𝐿𝐸𝑉𝐸𝑅𝐴𝐺𝐸𝑖,𝑡+ 𝜕10𝑆𝐴𝐿𝐸𝐺𝑅𝑖,𝑡 + 𝜕11𝐵𝑇𝑀𝑖,𝑡+ 𝜕12𝑍𝑆𝐶𝑂𝑅𝐸𝑖,𝑡+ 𝜕13𝐵𝐸𝑇𝐴𝑖,𝑡+ 𝜕14𝑅𝑂𝐴𝑖,𝑡+ 𝜕15𝐿𝑂𝑆𝑆𝑖,𝑡+ 𝐼𝑁𝐷𝑈𝑆𝑇𝑅𝑌 + 𝑌𝐸𝐴𝑅 +𝑖,𝑡+1… . … … … (1)

(1) (2) (3) (4) (5) (6) (7) (8)


Constant 0.0405* 0.0744*** -0.00399 0.0370* -0.0165 0.00593 -0.0750* -0.0285

(1.96) (4.68) (-0.16) (2.56) (-0.54) (0.25) (-2.05) (-1.33)

ARL 0.000375*** 0.000411*** 0.000481*** 0.000422*** - - - -

(3.80) (5.40) (4.08) (6.10)

LOG(ARL) - - - - 0.0473*** 0.0553*** 0.0595*** 0.0540***

(3.51) (5.32) (3.69) (5.72)

BODSIZE -0.000195 -0.000345 -0.000585 -0.000375 -0.000250 -0.000400 -0.000657 -0.000436

(-0.21) (-0.49) (-0.54) (-0.59) (-0.27) (-0.57) (-0.60) (-0.68)

INDDIR -0.0271* -0.0231* -0.0154 -0.0219* -0.0274* -0.0233* -0.0158 -0.0222*

(-2.21) (-2.44) (-1.05) (-2.54) (-2.23) (-2.46) (-1.08) (-2.58)

CEODUAL 0.00414 -0.00689 0.000494 -0.000753 0.00403 -0.00698 0.000337 -0.000872

(0.83) (-1.80) (0.08) (-0.22) (0.81) (-1.82) (0.06) (-0.25)

MGTOWN -0.00284 0.0116 0.0172 0.00865 -0.00243 0.0119 0.0178 0.00907

(-0.24) (1.25) (1.19) (1.03) (-0.20) (1.28) (1.24) (1.08)

BODMEET -0.000557 0.00139** 0.00160* 0.000811 -0.000562 0.00138** 0.00160* 0.000804

(-0.86) (2.77) (2.07) (1.78) (-0.87) (2.75) (2.06) (1.77)

BIG4 -0.0144* -0.000724 -0.00754 -0.00757 -0.0151* -0.00135 -0.00837 -0.00826*

(-2.45) (-0.16) (-1.07) (-1.83) (-2.56) (-0.30) (-1.19) (-2.00)

LNSIZE 0.0109*** -0.000770 0.00261* 0.00424*** 0.0110*** -0.000632 0.00272* 0.00435***

(10.29) (-0.94) (2.07) (5.72) (10.33) (-0.77) (2.14) (5.85)

LEVERAGE 0.00265 0.0241* 0.104*** 0.0435*** 0.00402 0.0255* 0.105*** 0.0450***

(0.18) (2.17) (6.03) (4.31) (0.28) (2.30) (6.14) (4.46)

SALEGR -0.0153* -0.000255 0.00644 -0.00304 -0.0156* -0.000561 0.00618 -0.00331

(-2.23) (-0.05) (0.78) (-0.63) (-2.26) (-0.11) (0.75) (-0.68)

BTM -0.00647* 0.0424*** 0.117*** 0.0508*** -0.00661* 0.0422*** 0.116*** 0.0507***

(-2.15) (18.25) (32.42) (24.10) (-2.19) (18.15) (32.34) (23.99)

ZSCORE 0.000110* -0.0000737 -0.0000185 0.00000587 0.000110* -0.0000737 -0.0000182 0.00000608

(2.07) (-1.80) (-0.29) (0.16) (2.07) (-1.79) (-0.29) (0.16)

BETA -0.00771* 0.0250*** 0.0313*** 0.0162*** -0.00752* 0.0253*** 0.0316*** 0.0164***

(-2.42) (10.18) (8.23) (7.27) (-2.36) (10.27) (8.29) (7.35)

ROA 0.0573*** -0.00778 -0.0232* 0.00879 0.0569*** -0.00809 -0.0237** 0.00838



(7.46) (-1.31) (-2.52) (1.63) (7.41) (-1.36) (-2.58) (1.56)

LOSS 0.0261*** 0.0989*** 0.132*** 0.0856*** 0.0260*** 0.0987*** 0.132*** 0.0854***

(4.37) (21.47) (18.46) (20.45) (4.35) (21.41) (18.43) (20.40)

YEAR Controlled Controlled Controlled Controlled Controlled Controlled Controlled Controlled INDUSTRY Controlled Controlled Controlled Controlled Controlled Controlled Controlled Controlled

N 4,797 4,797 4,797 4,797 4,797 4,797 4,797 4,797

F-statistics 25.23 58.84 74.64 60.21 25.15 58.81 74.50 60.01

Adj R-squared 18.67 27.85 32.95 28.32 18.63 27.83 32.91 28.25

t statistics in parentheses

* p < 0.05, ** p < 0.01, *** p < 0.001


Appendix A

Acronym Variable description

KE Cost of equity calculated based on Gordon growth model.

PEG The ratio of price-to-forecasted (next-year) earnings per share divided by the expected short-term earnings growth rate

MPEG The modified PEG-ratio where the modification is the inclusion of expected dividends via the Ohlson and Juettner-Nauroth (2000) growth variable AVGCOE Cost of equity calculated based on capital asset pricing model

ARL Audit report lag

LOGARL Base 10 logarithm of audit report lag

LNARL Base e logarithm of audit report lag

SALEGR Sale growth

LNSIZE Frim size

BTM Book to market ratio

LEVERAGE Leverage, debt to asset ratio

ZSCORE Bankruptcy risk

ROA_EBIT Earnings before interest and tax on asset

ROA_NI Net income on asset

LOSS_EBIT Distress risk (loss calculated using Earnings before interest and tax) LOSS_NI Distress risk (net income calculated using Earnings before interest and tax)

BIG4 Auditor quality

BETA Firm risk

MGTOWN Management ownership

BODMEET Board meeting frequencies


DIRECTORSOUTSIDE Director independence (outside directors)

BODSIZE Board size

INDDIR Board independence


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