Based on the internal control auditing system in China, this paper studies the relationship between internal control audit fees and internal control audit quality. Using the 2011-2016 A-share listed company data test, it is found that under the control of other possible conditions, the higher the internal control audit fee and its proportion, the lower the probability of being issued anon-standard internal control audit opinion, which means that the relatively high internal control audit fee may be paid by companies to purchase more favorable internal control audit opinions. Further, the above result is found to be more significant in non-state-owned, relatively smaller companies, and clients whose total audit fees are higher. In general, from the research conclusions of this paper, the high internal control audit fees can be a form of damage to the independence and quality of internal control audit. The results have certain guiding significance for policy makers to further improve the internal control auditing system and regulate the disclosure of internal control audit fees, and also for the decision-making of auditors and listed companies.
According to the CSRC Accounting [
The available literature indicates that the disclosure of audit fees is considered to help reduce the “low-balling” behavior [
The contributions of this paper to the existing research are as follows. First, it extends the research situation of audit fee information, demonstrating the impact of internal control audit fees on the internal control auditquality, and providing further empirical evidence for the economic consequences of audit fee disclosure. Second, it expands the research on the relationship between abnormal audit fees and auditor independence. In recent years, some studies have begun to pay attention to the impact of abnormal audit fees (that is, the residual items of the audit fee estimation model) on auditor independence or audit quality [
A large amount of research has focused on the relationship between audit fees and non-audit service fees disclosed by companies and audit quality. Among them, some directly use the absolute amount of audit fee or non-audit expense, and its proportion to the total audit expenses as the key explanatory variables. Some further distinguish the nature of audit fees, using the audit pricing model to estimate the normal audit fees, and the difference between the actual audit fees and the normal expenses (the residual items or the abnormal audit fee). In addition, some literature studies the auditor’s economic dependence on specific clients on the audit quality. According to the dominant studies, the audit quality is mostly measured by the degree of discretionary accruals, the probability of being issued modified audit opinions, and the possibility of announcing financial restatement.
As to whether the level of audit fees will affect the quality of audits, the directly related research has not reached an agreed conclusion. Some scholars believe that excessively high audit fees can undermine audit independence and audit quality. When receiving higher audit fees, the auditor may be forced to indulge the opportunistic earnings management behavior of the management under the pressure of the client company. The management may purchase the audit opinion by giving the accounting firm an excessive audit fee, which supports the “audit collusion” hypothesis. The specific empirical results show that higher audit cost is accompanied by lower accrual quality and the probability of being issued a modified audit opinion [
All of the above studies directly examine the relationship between the level of audit fees (or the proportion of audit fees in total costs) and audit quality proxies. In recent years, scholars have further examined the relationship between them from the perspective of abnormal audit fees, and its impact on audit quality or earnings quality, according to its symbol. For positive abnormal audit fees, most empirical findings show that the higher the abnormal audit cost is, the higher the absolute value of the discretionary accruals and the likelihood of meeting or beating analyst forecasts will be [
Most of the domestic research results support that the abnormal audit cost has a negative impact on audit quality. The literature based on the results of the audit opinion shows that the abnormal audit fees are significantly positively correlated with the improvement of the adverse audit opinions of listed companies, and significantly reduce the value relevance of accounting earnings, that is, the listed company successfully purchased the audit opinions by raising the audit fees. The increase in fees has jeopardized the quality of auditing [
In addition, when the proportion of audit fees to the total income of the audit firm is used to measure the economic dependence of auditors on clients, the majority of studies based in China indicate that the independence of auditors is reduced in the face of large clients, which mainly use the discretionary accruals and probability of modified opinions as proxies for audit quality [
In general, the literature in this area reflects the economic bond between the auditor and the client through audit fees, non-audit service fees, abnormal audit fees or client importance, to explore how this bond affects the audit independence or audit quality. Among them, some scholars directly study the relationship between them by using the size of the discretionary accruals and the probability of issuing modified opinions as the proxy variables of audit quality, while the other part pays attention to the perception of audit quality or audit independence from information users (investors, creditors, analysts, etc.).
Ghosh and Pawlewicz [
As to economic consequences, the existing research found that implementing internal control audit can improve the efficiency of financial statement audit and accounting earnings quality, and reduce the cost of equity capital [
Regarding the market response of internal control audit opinions, Wu et al. found that for companies that received “non-clean” opinions only in the internal control audit, investors did not make a significant negative reaction near the information announcement date, indicating that the investors’ response to the “non-clean” internal control audit opinion is not sufficient in China’s stock market at present stage. From the perspective of the creditor’s, Han’s study shows that if the listed company received a “clean” financial statement audit opinion and a “non-clean” internal control audit opinion in the same year, it is often accompanied by a significantly higher risk of financial distress in the current year and the next year, but financial institutions such as banks have not significantly reduced the short-term credit scale of such enterprises.
The literature on internal control audit fees is more limited. For example, Fang et al. studied the influencing factors of internal control audit fees, and found that the size of the company, the complexity of the business, the nature of ownership, the reputation of the accounting firm and the assurance degree of the internal control audit service provided by it are the main influencing factors. Yang Lin’s empirical test found that internal control audit fees are negatively correlated with earnings quality, and board governance has a regulatory role. Tang found that the voluntary disclosure of internal control audit fees increased the independence of internal control audits.
Based on the above literature review, it is obvious that China’s current research on internal control audit fees is quite limited, and the attention on internal control audit fees is also low in practice. The research on internal control audit fees may be a unique area under China’s institutional background. Therefore, this paper intends to further study whether the level of internal control audit fees also affects the quality of internal control audits.
In the current situation where listed companies are required to implement internal control audits, internal control audit fees naturally become a new economic link between auditors and clients. One of the objectives of internal control is to ensure the reliability of financial reporting, and the scope of its current audit is limited to internal controls related to financial reporting. The internal control audit fee is the result of the “bargaining” of the auditor and the audited entity, reflecting both the risk of the internal control system of the audited entity and the cost of the auditor’s internal control audit. Under normal circumstances, when the quality of the internal control of the audited entity is low, the risk of internal control audit is higher, and the auditor needs additional inputs, such as measures to expand the scope of control testing, increase audit procedures, and communicate with clients’ management; and the higher the overall risk level of the clients is, the higher the litigation risk faced by the auditor will be, soaprice premium is required, which leads to higher internal control audit fees. In this case, if the auditor can make accurate professional judgment and maintain its independence, theoretically a modified internal control audit opinion is more likely to be issued. However, there is literature indicating that management can purchase audit opinions by giving audit firms excess audit fees [
According to the above discussion, on the one hand, the high internal control audit fee reflects the auditor’s input to the internal control audit process and the high internal control audit quality. On the other, it may also manifest the economic rent collected by the auditor and the lower internal control audit quality. In view of the fact that most domestic research has found excessive audit fees or positive abnormal audit fees will undermine audit independence, this paper extends its conclusions to the internal control audit situation and proposes the hypothesis:
Hypothesis: Under the same conditions, companies that disclose higher internal control audit fee will have a smaller probability of being issued a modified internal control audit opinion, which means lower quality of internal control audit.
This paper selects all A-share listed companies that have implemented internal control audits from 2011 to 2016 and separately disclosed the internal control audit fees as the original sample, and then excludes the companies that are: 1) in the financial industry, 2) with missing data, 3) listing less than one year, 4) audited by two different firms regarding internal control and financial reporting. In this way 2130 companies remain in the sample. In order to reduce the influence of extreme values, this paper performs Winsorize processing on the continuous variables from 1% to 99% of the quantile level. Among them, the internal control audit fee data is manually collected by the author from the listed companies’ annual reports. The internal control audit opinion and the internal control quality index data are from the DIB Internal Control and Risk Management database1, and the financial and other data are from CSMAR database.
Referring to the previous research on audit opinion, this paper selects internal control audit opinion (ICOP) as the proxy variable for internal control audit independence, namely the dependent variable. The key explanatory variables are the natural logarithm of the amount of internal control audit fees (ICAF) and the proportion of it to total audit fees (ICAF_r). According to the existing literature on audit fee disclosure and internal control audit, this paper includes the following control variables: the internal control audit opinion of the previous year (PRE_ICOP), internal control quality index (ICQ), earnings quality (DA), company size (SIZE), listing years (AGE), asset-liability ratio (LEV), financial status (LOSS), return on assets ( ROA), sales growth rate (GRTH), operating net cash flow level (CFO), inventory level (INVTA), accounts receivable level (RECTA), nature of ownership (SOE), internal control audit firm (ICBIG4) and dummy variables of years and industries. The specific variable definitions are shown in
1The DIB Internal Control and Risk Management database is developed by Shenzhen Dibo Enterprise Risk Management Technology Co., Ltd. It provides enterprises, researchers, regulators and investors with information on the internal control status of listed companies in China through structured data compilation of internal control evaluation status, internal control audit status, internal control defects, and internal control information disclosure index.
Using a logitstic regression, the model (1) below tests whether the internal control audit fee and its proportion of the total audit fee are correlated to the probability that the enterprise is issued the modified internal control audit opinion. If the assumption of this paper is true, β1 is expected to be significantly negative.
ICOP = β 0 + β 1 ICAF ( ICAF_r ) + β 2 ICQ + β 3 Pre_ICOP + β 4 DA + β 5 SIZE + β 6 AGE + β 7 LEV + β 8 ROA + β 9 LEV + β 10 CFO + β 11 GRTH + β 12 INVTA + β 13 RECTA + β 14 SOE + β 15 ICBIG 10 + YEAR + INDUS + ε (1)
After removing the sample of companies in the financial industry, with missing
Variable type | Variable name | Variable Definition | |
---|---|---|---|
Dependent Variable | ICOP | Internal control audit opinion. 1 for modified opinion, 0 otherwise | |
Explanatory Variables | ICAF | Internal control audit fees, expressed in natural logarithm | |
ICAF_r | The proportion of internal control audit fees to total audit fees | ||
Pre_ICOP | Internal control audit opinion of the previous year | ||
ICQ | The natural logarithm of DIB internal control quality index | ||
DA | Absolute value of discretionary accruals | ||
AGE | Years of listing | ||
SIZE | Natural logarithm of total assets | ||
ROA | Profitability, measured by company’s return on total assets | ||
LEV | Financial leverage, measured by asset-liability ratio | ||
Control Variables | LOSS | Equals 1 when the net income is negative, 0 otherwise | |
CFO | Operating net cash flow divided by total assets | ||
GRTH | Operating income growth rate | ||
INVTA | Inventory divided by total assets | ||
RECTA | Account receivable divided by total assets | ||
SOE | Equals 1 if the company is state-owned, 0 otherwise | ||
ICBIG10 | Equals 1 when the internal control audit firm is “big ten” | ||
INDUS | Dummy variables of the industries | ||
YEAR | Dummy variables of the years |
data and listing for less than one year, a total of 6257 original observations were obtained. Among them, as shown in
As shown in
Year | 2011 | 2012 | 2013 | 2014 | 2015 | 2016 | Total |
---|---|---|---|---|---|---|---|
Total Obs. | 164 | 786 | 967 | 1228 | 1567 | 1563 | 6275 |
Obs. of disclosure group | 29 | 521 | 660 | 871 | 943 | 988 | 4012 |
The proportion of disclosure group | 17.68% | 66.28% | 68.25% | 70.93% | 60.18% | 63.21% | 63.94% |
Variable | Obs. | Mean | Std. Dev. | Min. | Median | Max. |
---|---|---|---|---|---|---|
ICOP | 4012 | 0.03 | 0.17 | 0 | 0 | 1 |
pre_ICOP | 3422 | 0.034 | 0.182 | 0 | 0 | 1 |
ICAF | 4012 | 12.698 | 0.638 | 11.29 | 12.612 | 14.732 |
ICAF_r | 4012 | 0.273 | 0.085 | 0.068 | 0.273 | 0.529 |
ICQ | 4012 | 6.482 | 0.144 | 5.809 | 6.504 | 6.836 |
DA | 4012 | 0.066 | 0.084 | 0.001 | 0.042 | 0.748 |
ICBIG10 | 4012 | 0.598 | 0.49 | 0 | 1 | 1 |
AGE | 4012 | 14.081 | 6.031 | 1 | 15 | 26 |
LOSS | 4012 | 0.1 | 0.3 | 0 | 0 | 1 |
SIZE | 4012 | 22.645 | 1.378 | 19.212 | 22.537 | 27.148 |
LEV | 4012 | 0.501 | 0.206 | 0.046 | 0.508 | 0.935 |
ROA | 4012 | 0.032 | 0.046 | -0.16 | 0.027 | 0.199 |
CFO | 4012 | 0.043 | 0.072 | −0.212 | 0.043 | 0.259 |
INVTA | 4012 | 0.167 | 0.172 | 0 | 0.115 | 0.749 |
RECTA | 4012 | 0.089 | 0.097 | 0 | 0.055 | 0.454 |
GRTH | 4012 | 0.143 | 0.537 | −0.624 | 0.056 | 4.33 |
SOE | 4012 | 0.665 | 0.472 | 0 | 1 | 1 |
ICOP | ||||
---|---|---|---|---|
Coef. | Z-value | Coef. | Z-value | |
ICAF | −0.640** | (−2.387) | ||
ICAF_r | −4.149** | (−2.163) | ||
ICQ | −4.437*** | (−7.339) | −4.370*** | (−7.294) |
DA | −0.095 | (−0.069) | −0.268 | (−0.198) |
pre_ICOP | 2.401*** | (7.716) | 2.339*** | (7.369) |
AGE | 0.034 | (1.419) | 0.033 | (1.400) |
LOSS | 0.608 | (1.387) | 0.615 | (1.386) |
SIZE | 0.294** | (2.226) | 0.045 | (0.383) |
LEV | −0.688 | (−0.823) | −0.699 | (−0.838) |
ROA | −4.168 | (−1.374) | −4.019 | (−1.348) |
---|---|---|---|---|
CFO | 0.409 | (0.233) | 0.273 | (0.153) |
INVTA | −1.342 | (−1.252) | −1.304 | (−1.191) |
RECTA | 1.892 | (1.634) | 1.874 | (1.562) |
GRTH | 0.476*** | (3.470) | 0.485*** | (3.584) |
SOE | −0.365 | (−1.436) | −0.301 | (−1.171) |
ICBIG10 | 0.223 | (0.947) | 0.090 | (0.363) |
_cons | 26.347*** | (5.170) | 24.648*** | (4.989) |
Industry & Year | Control | Control | ||
N | 3273 | 3273 | ||
Pseudo R2 | 0.245 | 0.246 | ||
Wald chi2 | 224.369 | 231.191 |
Notes: 1) Significance (two-tailed) at: *0.10, **0.05 and ***0.01 levels, respectively; 2) 149 observations are automatically omitted because the industry dummy variables fully predict the dependent variable.
reflect the auditor’s collection of economic rents to compromise with the management, and thus the quality of internal control audits is relatively low.
Based on China’s institutional background, most scholars further distinguish the nature of ownership and find the research results differ between state-owned and private enterprises. On the one hand, state-owned companies generally have special agency problems, with the main body of their owners being absent. The actual owner entrusts the management personnel to perform the relevant control functions, which increases the length of the company’s agent chain. In this case the complicated agency problem exacerbates the difficulty of internal control construction. Moreover, most of the delegated managers have a political background, which may trigger the risk that the management is above its internal control, inhibiting the normal function of internal control system. In order to alleviate agency conflicts and establish a good corporate image, state-owned companies are more inclined to choose highly reputed audit firms. On the other hand, state-owned companies generally face more stringent risk management requirements, preferring to hire large-scale and high-quality accounting firms to deliver a positive signal to the stakeholders. In addition, compared with private enterprises, state-owned enterprises have less incentive to cater for security regulatory policies, and the risk of material misstatement in financial statement audits is significantly lower than that of private enterprises. Therefore most state-owned enterprises do not need to pay high audit fees to auditors, who tend to be independent.
Based on the above analysis, this paper further explores whether the relationship between internal control audit fees and internal control audit quality will vary among clients with different ownership. The results in
Smaller-scale enterprises are mostly in the early stage of development and their internal control system construction started relatively late, which results in lower internal control quality weaker ability to withstand risk. In addition, smaller companies may not give adequate attention to internal control audit, so they are more inclined to purchase audit opinions. Thus, this paper speculates that companies with relatively small scale in the same industry are more likely to pay higher internal control audit fees to obtain internal control audit opinions favorable to them. Grouping the full sample by the industry mean of total assets, the test results listed in
ICOP | ||||
---|---|---|---|---|
State-owned | Non-state-owned | |||
ICAF | −0.462 | −1.072** | ||
(−1.250) | (−2.475) | |||
ICAF_r | −2.508 | −6.951** | ||
(−0.956) | (−2.550) | |||
ICQ | −4.479*** | −4.406*** | −5.042*** | −5.080*** |
(−5.821) | (−5.752) | (−5.033) | (−5.279) | |
DA | −1.563 | −1.795 | 0.101 | −0.024 |
(−0.722) | (−0.820) | (0.062) | (−0.015) | |
pre_ICOP | 2.842*** | 2.806*** | 1.480*** | 1.438*** |
(7.757) | (7.524) | (2.708) | (2.591) | |
AGE | 0.066* | 0.067* | −0.005 | −0.002 |
(1.755) | (1.759) | (−0.150) | (−0.067) | |
LOSS | 0.887* | 0.901* | 0.147 | 0.178 |
(1.667) | (1.662) | (0.205) | (0.253) | |
SIZE | 0.323* | 0.129 | 0.077 | −0.225 |
(1.884) | (0.893) | (0.345) | (−1.133) | |
LEV | 0.233 | 0.291 | −0.365 | −0.620 |
(0.205) | (0.257) | (−0.318) | (−0.508) | |
---|---|---|---|---|
ROA | −0.173 | −0.210 | −6.101 | −5.280 |
(−0.036) | (−0.044) | (−1.411) | (−1.271) | |
CFO | 3.506 | 3.590 | −2.095 | −2.437 |
(1.240) | (1.252) | (−0.925) | (−1.106) | |
INVTA | −0.115 | −0.062 | −1.976 | −2.095 |
(−0.082) | (−0.044) | (−1.398) | (−1.419) | |
RECTA | 2.273 | 2.307 | 0.405 | 0.526 |
(1.463) | (1.429) | (0.249) | (0.315) | |
GRTH | 0.495** | 0.513** | 0.573*** | 0.565*** |
(2.128) | (2.219) | (3.037) | (3.079) | |
ICBIG10 | 0.223 | 0.145 | 0.131 | −0.056 |
(0.709) | (0.429) | (0.335) | (−0.148) | |
_cons | 22.366*** | 21.038*** | 42.956*** | 38.905*** |
(3.718) | (3.577) | (4.623) | (4.559) | |
Industry & Year | Control | Control | ||
N | 2208 | 901 | ||
Pseudo R2 | 0.257 | 0.256 | 0.279 | 0.281 |
Wald chi2 | 196.476 | 194.082 | 88.949 | 94.512 |
Notes: 1) Significance (two-tailed) at: *0.10, **0.05 and ***0.01 levels, respectively; 2) 313 observations are automatically omitted because the industry dummy variables fully predict the dependent variable.
ICOP | ||||
---|---|---|---|---|
Big client | Small client | |||
ICAF | −0.303 | −1.375*** | ||
(−0.994) | (−3.219) | |||
ICAF_r | −1.176 | −10.465*** | ||
(−0.529) | (−3.638) | |||
ICQ | −4.603*** | −4.526*** | −4.936*** | −5.107*** |
(−5.670) | (−5.695) | (−4.554) | (−5.109) | |
DA | −4.106 | −3.991 | 0.041 | 0.644 |
(−1.561) | (−1.544) | (0.023) | (0.445) | |
pre_ICOP | 2.254*** | 2.305*** | 2.466*** | 2.454*** |
(5.233) | (5.248) | (5.192) | (5.217) | |
AGE | 0.003 | 0.004 | 0.037 | 0.053 |
(0.102) | (0.151) | (1.001) | (1.375) | |
LOSS | 0.573 | 0.598 | 0.160 | 0.257 |
(0.959) | (0.985) | (0.277) | (0.449) | |
---|---|---|---|---|
SIZE | 0.292 | 0.037 | −1.015 | −1.369 |
(0.264) | (0.035) | (−0.988) | (−1.270) | |
LEV | −3.284 | −3.576 | −7.360* | −7.272* |
(−0.723) | (−0.784) | (−1.800) | (−1.716) | |
ROA | 4.731 | 4.648 | −2.269 | −2.695 |
(1.382) | (1.355) | (−0.923) | (−1.153) | |
CFO | −1.627 | −1.505 | −1.111 | −1.574 |
(−0.966) | (−0.873) | (−0.921) | (−1.115) | |
INVTA | 2.282 | 2.421 | 0.317 | 1.060 |
(1.539) | (1.626) | (0.171) | (0.509) | |
RECTA | 0.715*** | 0.705*** | 0.320 | 0.313* |
(3.460) | (3.472) | (1.617) | (1.698) | |
GRTH | 0.112 | 0.079 | −0.916** | −0.760* |
(0.304) | (0.211) | (−2.179) | (−1.788) | |
ICBIG10 | 0.551 | 0.484 | −0.263 | −0.571 |
(1.340) | (1.174) | (−0.702) | (−1.417) | |
_cons | 30.626*** | 26.737*** | 45.299*** | 31.593*** |
(4.236) | (4.783) | (4.791) | (4.809) | |
Industry & Year | Control | Control | ||
N | 1711 | 1385 | ||
Pseudo R2 | 0.220 | 0.218 | 0.335 | 0.353 |
Wald chi2 | 142.671 | 146.564 | 123.075 | 120.404 |
Notes: 1) Significance (two-tailed) at: *0.10, **0.05 and ***0.01 levels, respectively; 2) 326 observations are automatically omitted because the industry dummy variables fully predict the dependent variable.
It has been shown in the literature that integrated audit can significantly reduce total audit fees, which is mainly due to the enhanced efficiency of audit brought by scaling synergy [
ICOP | ||||
---|---|---|---|---|
High audit fee | Low audit fee | |||
ICAF | −0.453 | −1.336*** | ||
(−0.982) | (−3.458) | |||
ICAF_r | 1.144 | −7.511*** | ||
(0.328) | (−3.025) | |||
ICQ | −4.688*** | −4.633*** | −4.244*** | −4.211*** |
(−5.432) | (−5.394) | (−4.574) | (−4.668) | |
DA | −6.518* | −6.711** | 0.958 | 0.858 |
(−1.945) | (−2.048) | (0.634) | (0.615) | |
pre_ICOP | 1.507** | 1.457** | 2.740*** | 2.617*** |
(2.516) | (2.482) | (7.120) | (6.775) | |
AGE | 0.033 | 0.034 | 0.021 | 0.022 |
(0.834) | (0.875) | (0.625) | (0.680) | |
LOSS | 0.297 | 0.279 | 0.865 | 0.864 |
(0.393) | (0.370) | (1.506) | (1.519) | |
SIZE | 0.014 | −0.050 | 0.304 | 0.031 |
(0.059) | (−0.193) | (1.645) | (0.161) | |
LEV | −0.156 | −0.357 | −1.115 | −1.152 |
(−0.109) | (−0.247) | (−1.099) | (−1.099) | |
ROA | −7.794 | −7.885 | −4.068 | −3.519 |
(−1.160) | (−1.132) | (−1.179) | (−1.018) | |
CFO | 2.950 | 3.279 | −0.762 | −0.755 |
(0.692) | (0.772) | (−0.374) | (−0.388) | |
INVTA | 0.717 | 0.746 | −2.005 | −1.971 |
(0.428) | (0.432) | (−1.573) | (−1.493) | |
RECTA | 1.491 | 1.919 | 2.442 | 2.606 |
(0.736) | (0.941) | (1.531) | (1.581) | |
GRTH | 0.905*** | 0.903*** | 0.406** | 0.429*** |
(3.745) | (3.833) | (2.401) | (2.614) | |
---|---|---|---|---|
ICBIG10 | 0.747 | 0.791 | −0.185 | −0.341 |
(1.508) | (1.524) | (−0.660) | (−1.219) | |
_cons | 32.470*** | 27.483*** | 33.350*** | 24.789*** |
(3.300) | (3.504) | (4.419) | (3.373) | |
Industry & Year | Control | Control | ||
N | 998 | 2099 | ||
Pseudo R2 | 0.238 | 0.235 | 0.295 | 0.298 |
Wald chi2 | 108.914 | 109.476 | 168.436 | 170.551 |
Notes: 1) Significance (two-tailed) at: *0.10, **0.05 and ***0.01 levels, respectively; 2) 325 observations are automatically omitted because the industry dummy variables fully predict the dependent variable.
The following robustness checks were conducted to test the relative stability of the main hypothetical results. Due to space limitations, the specific statistical results are not included in the text.
Since the higher internal control audit fees may include the normal part of the auditor’s increased input and effort, this paper further distinguishes the internal control audit fees with reference to the literature on abnormal audit fees. Referring to the internal control audit fee model established by Fang et al., this paper first used the pricing model to obtain the predicted value of internal control audit fee for each observation, and then compared it with the actual internal control audit fee disclosed. The difference between the two values is considered to be the abnormal audit fee (AB_ICAF), which cannot be accounted for by known explanatory variables. In the meantime, the sign of AB_ICAF is distinguished. Finally, this paper added the positive or negative AB_ICAF to model (1) to replace the IACF for regression. The results show that the positive abnormal internal control audit fee is negatively correlated with the probability of issuing modified internal control audit opinion. Although the result is not significant, it supports the main hypothesis to some extent.
In order to alleviate the endogenous problems caused by missing variables, this paper added the audit opinion of the previous year’s financial statements (pre_Auditop) as one of the control variables by referring to the study of Tang and Zhang. The results are still consistent.
Referring to the previous literature, the internal governance of the company also has an impact on the audit opinion. Therefore, this paper added a series of common corporate governance variables as control variables, such as “whether the chairman and CEO are the same person” (Dual), the proportion of independent directors to total directors (Indpdt), the size of the supervisory board (Supervise), the separation of two powers. The results did not change.
Based on the internal control auditing system, this paper studies the relationship between internal control audit fees and internal control audit quality. The research results are as follows: 1) under the control of other possible conditions, the higher the internal control audit fee and its proportion, the lower the probability of being issued a modified internal control audit opinion, which means that the relatively high internal control audit fee may be paid by companies to purchase more favorable internal control audit opinions; 2) the above result is found to be more significant in non-state-owned, relatively smaller companies, and clients whose total audit fees are higher. Overall, from the research conclusions of this paper, higher internal control audit fee damages the quality of internal control audit.
The study also has certain enlightenments in practice. On the one hand, although there are documents that require listed companies to disclose the payment to the accounting firms, there is no exact requirement regarding how detailed the disclosure of audit fees should be. Furthermore, there is no corresponding penalty mechanism for companies that do not disclose audit fees. In this case, enterprises have considerable arbitrariness in the disclosure of audit fees. At the same time, no clear pricing mechanism for internal control audits has been implemented so far in China, so the rent-seeking behavior between client companies and auditors is difficult to avoid. On the other hand, the results of this paper indirectly reflect that when China’s internal control auditing system is still in its early stage, the information content of internal control auditing opinions is minimal, supporting the conclusions of Wu et al. and Han.
Given the above, this paper proposes the following policy recommendations. 1) Standardizing the information disclosure related to internal control audit. The regulatory body should strengthen the enforcement of the audit fee disclosure system, and force the listed company to separately disclose the internal control audit fees and the financial report audit fees, standardizing the relevant formats for the disclosure of audit fees to facilitate the use of accounting information and protect the relevant interests of investors. Moreover, certain penalties could be imposed on companies which do not disclose audit fees. 2) Establishing specific standards for internal control audit fees. The regulatory body should also promote the establishment of a pricing model for internal control audits and establish reasonable charging standards, such as the reasonable scope and gradient of internal control audit fees based on the characteristics of listed companies such as asset size and business complexity. It helps control the internal control audit fees within a reasonable proportion to reduce the possibility of listed companies using internal control audit fees for audit opinion purchases. 3) Improving the internal control audit system. Relevant departments should strengthen the enforcement of internal control audits, update and improve relevant laws and regulations to further specify and standardize the audit procedures. It can also help guide and constrain the behavior of certified public accountants, making internal control audits fully exert its due value and escort the development of the enterprise and the order of the market.
This paper is subject to some possible limitations. 1) The data on internal control audit fees in this paper are collected manually, so errors may exist, which could affect the test results. 2) Before 2014, non-state-owned companies listed in the main board had not been required to implement internal control audits; and even until now SME board and GEM companies are still in the stage of voluntary internal control audit. This inevitably leads to sample self-selection bias. For companies that do not separately disclose internal control audit fees, we cannot observe the relationship between their internal control audit fees and internal control audit quality. Although certain measures have been taken to mitigate the endogeneity problem, the bias cannot be eliminated. 3) At present, there is no specific proxy variable used to measure the quality of internal control audit. The measurement of explanatory variable in this paper is relatively simple.
This paper only examines the impact of internal control audit fees on internal control audit opinions from the results of the disclosure, yet the incentives for listed companies to disclose internal control audit fees and the influencing factors of internal control audit fees may themselves affect the internal control audit results. These can be further explored in the future studies.
The author declares no conflicts of interest regarding the publication of this paper.
Chen, R.S. (2019) Internal Control Audit Fee and Internal Control Audit Quality―Evidence from Integrated Audits. Open Journal of Business and Management, 7, 292-311. https://doi.org/10.4236/ojbm.2019.71020