Mandatory internal control audits

and financial reporting quality

Clive Lennox Leventhal School of Accounting, University of Southern California, USA

Xi Wu School of Accountancy, Central University of Finance and Economics, China

August 2018

Acknowledgments: We are grateful for data support from China’s Ministry of Finance.

Mandatory internal control audits

and financial reporting quality

Abstract

Following the accounting scandals of the early 2000s, regulators introduced mandatory internal

control audits (MICAs) for accelerated filers. MICAs were intended to improve financial

reporting quality, but recent evidence suggests this has not happened. We argue that financial

reporting has not improved because, in the presence of a MICA, the auditor is less likely to

discover (and correct) material misstatements in the client’s pre-audit financial statements. We

present three results consistent with this prediction. First, there is an abnormally large drop in

audit adjustments following the introduction of MICAs. Second, accounting misstatements

increase at companies that experience abnormal reductions in audit adjustments following the

introduction of MICAs. Third, accounting misstatements decrease at companies where there is

no abnormal drop in audit adjustments following the introduction of MICAs. Overall, our results

suggest that financial reporting quality has not improved because, when auditors are required to

test and report on clients’ internal controls, they are less likely to detect (and correct) material

misstatements in their clients’ pre-audit financial statements.

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1. Introduction

The Sarbanes-Oxley Act (SOX) of 2002 was enacted to help restore public confidence in the quality

of auditing and financial reporting following several high-profile accounting scandals. One of the

most controversial provisions was Section 404(b), which requires the auditor of an accelerated

filer to opine on the effectiveness of the company’s internal controls. Regulators thought the

mandated internal control audits (MICAs) would improve financial reporting quality in a couple

of ways. First, auditors would conduct more testing of internal controls, which would help

auditors identify weaknesses in financial reporting systems. Second, companies would invest

more resources in their internal controls over financial reporting because they would want to

avoid receiving adverse opinions from their auditors.

The evidence indicates that MICAs have proved very costly (Raghunandan and Rama

2006; Krishnan et al. 2008; Iliev 2010), but recent evidence suggests that MICAs have not helped

to improve financial reporting quality (Bhaskar et al. 2019). In this study, we argue that financial

reporting quality has not improved because the introduction of MICAs has lowered auditors’

discovery of material misstatements in their clients’ pre-audit financial statements. In turn, the

lower rate of discovery has increased the frequency with which material misstatements go

uncorrected during the audit.

Why are auditors less likely to detect material misstatements in the presence of a MICA?

One reason is that the requirement to publicly disclose material weaknesses has changed auditors’

incentives to detect material misstatements. A material misstatement in the pre-audit financial

statements implies a material weakness in internal controls over financial reporting. Prior to the

introduction of MICAs, these weaknesses were not publicly disclosed and the misstatements

could be corrected without any public repercussions for the company’s management. As long as

the corrections were made, the auditor could issue a clean opinion on the audited financial

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statements, and that was the end of the matter. The introduction of MICAs changed this

equilibrium because auditors are now having to publicly disclose material weaknesses in internal

controls. These disclosures are costly to management because they increase the probability of

management being fired (Li et al. 2010; Johnstone et al. 2011), and they are costly to auditors as

well because they increase the probability of the auditor being dismissed from the engagement

(Ettredge et al. 2011; Newton et al. 2016). The auditor’s detection of material misstatements in the

pre-audit financial statements reveals to the auditor that there are material weaknesses in internal

controls which need to be publicly disclosed. We argue that auditors have less incentive to detect

material misstatements in the pre-audit financial statements after MICAs are introduced because

auditors are reticent to publicly disclose the corresponding internal control weaknesses.1

Furthermore, auditors were able to design the optimal balance of internal control testing

and substantive testing for their clients prior to the introduction of MICAs. Requiring auditors to

test internal controls changed this equilibrium because it forced auditors to undertake more

testing of internal controls, which led to large increases in audit fees. Auditors have come under

pressure from clients to limit these fee increases, but it is difficult for them to cut back on control

testing because these tests are required under the new MICA standards. Therefore, the

introduction of MICAs could have triggered reductions in substantive testing (i.e., fewer tests of

individual transactions and balances), which would reduce the ability of auditors to detect (and

correct) material misstatements.

1 An auditor could intentionally misreport by issuing a clean opinion rather than an adverse opinion, even though material misstatements have revealed material weaknesses in internal controls. However, intentional misreporting is a very risky strategy for the engagement auditor because the audit working papers are scrutinized by internal reviewers and external inspectors. Awkward questions are likely to be asked if an engagement partner issues a clean opinion on internal controls when the working papers show that material misstatements were found during the audit. Therefore, when an engagement auditor wishes to issue a clean opinion on internal controls, there is a greater motivation not to discover material misstatements in the pre-audit financial statements.

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In short, we argue that MICAs have failed to improve the quality of financial reporting

because MICAs have resulted in fewer corrections being made to clients’ financial statements

during the audit. We examine this argument by testing three hypotheses. First, we test whether

the introduction of MICAs has led to abnormally large reductions in audit adjustments to clients’

pre-audit financial statements (H1). Second, we test whether the abnormal reductions in audit

adjustments have resulted in worse financial reporting quality following the introduction of

MICAs (H2). Third, we test whether financial reporting quality has improved at companies that

did not experience abnormally large reductions in audit adjustments following the introduction

of MICAs (H3).

The China setting provides several advantages for testing these hypotheses. First, audit

adjustment data are readily available because Chinese audit firms are required to report to the

Ministry of Finance the pre-audit earnings of their public company clients (Lennox et al. 2016;

2018). We use these data to examine how the introduction of MICAs has affected the accounting

corrections that are made to clients’ financial statements during the course of an audit. Second,

China has introduced MICAs on a staggered basis over time (Table 1). The staggered introduction

of MICAs allows us to estimate panel data models (2007-2015) which control for company fixed

effects and year fixed effects as well as the time-varying characteristics of companies and auditors.

Third, there are large differences in financial reporting quality among companies in China, where

the misstatement rate is 17.1% during our sample period. This allows us to provide powerful tests

for the impact of MICAs on accounting misstatements.

Our sample comprises 15,238 audit engagements between 2007 and 2015. We begin by

replicating recent evidence from the U.S. that the introduction of MICAs has not improved

financial reporting in China (Bhaskar et al. 2019). Our remaining tests examine whether financial

reporting has failed to improve because MICAs have led to abnormally large reductions in audit

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adjustments. Consistent with H1, we show that MICAs were followed by abnormally large

reductions in audit adjustments moving from the pre-MICA period to the post-MICA period.

Consistent with H2, we find significant increases in accounting misstatements at companies that

experienced abnormally large reductions in adjustments following the introduction of MICAs

(H2). Consistent with H3, we find significant decreases in accounting misstatements at companies

that did not experience abnormally large reductions in adjustments following the introduction of

MICAs (H3). Thus, the impact of MICAs on financial reporting quality is context specific.

Financial reporting quality has improved at companies where MICAs did not cause abnormal

reductions in audit adjustments, whereas financial reporting quality has deteriorated at

companies where MICAs did cause abnormal reductions in audit adjustments. On a net basis the

two effects cancel out, which is why financial reporting quality has not improved on average.

Our study contributes to a literature examining the consequences of introducing MICAs.

There is a wealth of evidence that MICAs are very costly, but the evidence is mixed as to whether

MICAs have helped to improve financial reporting quality (Raghunandan and Rama 2006;

Krishnan et al. 2008; Iliev 2010; Nagy 2010; Bhaskar et al. 2019). Our study helps explain why

there isn’t stronger evidence of improved financial reporting quality. We show that MICAs have

reduced auditors’ discovery of material misstatements in clients’ pre-audit financial statements

and we show that this explains why financial reporting quality has not improved on average. We

also show that financial reporting quality has improved at companies that did not experience

abnormally large reductions in audit adjustments following the introduction of MICAs.

Although our research is conducted using data from China, we expect our results to

generalize to the U.S. and other countries that have introduced MICAs. We have examined the

generalizability of our findings by testing whether the results from prior U.S. research on internal

control audits generalize to our China setting. This is also important because we use the findings

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from prior U.S. research in our hypothesis development so it is important to show that those

findings also generalize to the China setting. First, consistent with evidence from the U.S. (Bedard

and Graham 2011; Franzel 2015, 2016), we show that auditors are more likely to disclose internal

control weaknesses after they find material misstatements during the audit. This supports a

maintained assumption in our hypothesis development that the discovery of material

misstatements increases the probability that the auditor discloses internal control weaknesses.

Second, we show that auditors are more likely to be removed from the audit engagement after

they disclose internal control weaknesses. Again, this is consistent with prior U.S. research on

auditor switching (Ettredge et al. 2011; Newton et al. 2016) and it supports our maintained

assumption that it is costly for auditors to disclose internal control weaknesses. Third, we show

that the introduction of mandatory internal control audits caused a large and significant increase

in the fees paid to auditors. Again, this is consistent with prior U.S. evidence (Raghunandan and

Rama 2006; Krishnan et al. 2008; Iliev 2010), and supports our assumption that audit firms in

China, as well as in the U.S., were under pressure from their clients to constrain the increases in

audit fees following the introduction of MICAs.

2. Prior literature and hypothesis development

2.1 Prior literature

There is overwhelming evidence that MICAs have proved very costly as there have been

substantial increases in audit fees and other costs, such as consultancy and investments in new

information technology systems. Raghunandan and Rama (2006) report that the mean (median)

audit fee increased by 86% (128%) moving from 2003 to 2004, an increase that is much larger than

the typical annual increment in audit fees. Using a regression discontinuity design, Iliev (2010)

estimates that the introduction of MICAs caused audit fees to increase by 98%. A survey of its

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members by the Financial Executives Institute found that companies spent an average of $4.3

million on higher audit fees, consultancy fees, software costs, and other internal costs (FEI 2005).

Based on a sample of companies that voluntarily disclosed SOX 404 costs between 2003 and 2005,

Krishnan et al. (2008) find the mean (median) total costs of complying with SOX 404 are $2.2

million ($1.2 million). While the costs of mandatory internal control audits are no doubt

substantial, there are potential benefits in terms of improved operating performance and more

timely disclosure of internal control problems. Ge et al. (2017) estimate that these benefits exceed

the costs for small companies that are currently exempt from SOX 404(b).

Early studies provided some evidence of an initial improvement in financial reporting

quality following the introduction of MICAs. Iliev (2010) finds a decrease in discretionary

accruals for accelerated filers in 2004, suggesting that MICAs may have reduced earnings

management. Similarly, Nagy (2010) finds a negative relation between initial MICAs and the

issuance of materially misstated financial statements in 2005-2006. In contrast, a more recent

study by Bhaskar et al. (2019) finds a higher incidence of material misstatements when companies

are subject to MICAs using a longer event window (2007-2013). Their findings suggest that

financial reporting quality is worse rather than better in the presence of a MICA. They suggest

that financial reporting quality became worse because the introduction of MICAs afforded more

opportunities for auditors to exercise judgment, and because PCAOB inspections have shown

that auditors are providing low-quality MICAs to their clients.

Prior research indicates that managers have incentives to avoid receiving adverse internal

control opinions from their auditors because adverse opinions increase the probability of

management turnover (Li et al. 2010; Johnstone et al. 2011). In addition, adverse opinions are

costly to auditors because they increase the probability of auditor dismissal (Ettredge et al. 2011)

and managers shop around audit firms in an attempt to avoid adverse internal control opinions

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(Newton et al. 2016). These findings suggest that adverse opinions are costly to auditors as well

as corporate management.

The evidence also shows that auditors often fail to issue adverse opinions to companies

that have material internal control weaknesses. Using a sample of companies that subsequently

announce material restatements, and which are therefore known to have had material internal

control weaknesses during the reporting period, Rice and Weber (2012) find that only 32.4% of

the companies received adverse opinions from their auditors. DeFond and Lennox (2017) also

find that auditors tend to under-report material weaknesses in internal controls, although the

tendency to under-report has been mitigated by the PCAOB’s increased focus on the quality of

MICAs in its inspections of audit firms.

The systematic under-reporting of internal control weaknesses strongly suggests that

auditors often fail to detect existing material misstatements. Bedard and Graham (2011) find the

decision to disclose material weaknesses is heavily influenced by whether or not the auditor

detected a material misstatement during the audit, as material weaknesses are often identified by

tracing back from a detected misstatement. When an auditor discovers a material misstatement,

it implies that there must be a material weakness in the company’s internal controls and the

auditor is then required to issue an adverse opinion. However, if the auditor fails to detect a

material misstatement during the audit, the auditor is much less likely to conclude that material

internal control weaknesses exist. PCAOB former board member Jeanette Franzel noted this in

her speech to the 2015 AAA annual meeting (Franzel 2015):

“I’ve heard anecdotally that it is difficult for auditors to convince an audit client that a material weakness exists in the absence of a material misstatement. To what extent does this pressure exist and potentially cause underreporting of material weaknesses?”

2.2 Hypothesis development

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Before the introduction of MICAs, material weaknesses in internal controls were not publicly

disclosed which meant that any detected misstatements could be corrected before the results were

released to investors. Consequently, it used to be the case audit corrections to the financial

statements would not cause the company’s management to suffer any public repercussions. As

long as the auditors were satisfied with the corrections, the auditors could conclude that the

audited financial statements were not materially misstated, and so the auditors would issue clean

opinions on the financial statements. This equilibrium changed following the introduction of

MICAs because auditors had to start publicly disclosing material weaknesses even if they were

satisfied that all appropriate adjustments had been made. In other words, the introduction of

MICAs required auditors to disclose material weaknesses even when they concluded that the

audited financial statements were fairly presented.

The discovery of a material misstatement in the pre-audit financial statements reveals the

existence of a material weakness in internal controls over financial reporting. China’s internal

control auditing standard (CICPA 2011, Section 9.2), which is based upon the U.S. Auditing

Standard No. 5 (PCAOB 2007, AS 5, Appendix B, B8), states that:

“In an audit of internal control over financial reporting, the auditor should evaluate the effect of the findings of the substantive auditing procedures performed in the audit of financial statements on the effectiveness of internal control over financial reporting. This evaluation should include, at a minimum ... misstatements detected by substantive procedures. The extent of such misstatements might alter the auditor’s judgment about the effectiveness of controls.”

The link between misstatement discovery and internal control reporting has also been established

in academic research. Using proprietary data on internal control audits from several U.S. audit

firms, Bedard and Graham (2011) find that auditors evaluate internal control deficiencies as being

more severe when a material misstatement has been detected. Therefore, discovering a material

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misstatement increases the probability that the auditor will need to disclose internal control

weaknesses.2

Large audit adjustments are relatively strong indicators of internal control weaknesses

because large adjustments indicate that the errors were not prevented by the company’s own

internal control system but were instead detected by the auditor (Gunn et al. 2018). Disclosing

internal control weaknesses is costly to auditors because these disclosures increase the probability

of the auditor being terminated from the engagement (Ettredge et al. 2011; Newton et al. 2016).

Accordingly, the introduction of the internal control reporting requirement could have had the

unintended consequence of reducing auditors’ incentives to detect material misstatements. In

addition, the introduction of the reporting requirement could have incentivized management to

make it more difficult for auditors to detect material misstatements because management would

know that such misstatements, once detected by the auditor, would likely result in the auditor

disclosing internal control weaknesses. Therefore, the internal control reporting requirement

could motivate management to hamper the auditors’ detection of material misstatements of the

pre-audit financial statements.

Moreover, the introduction of MICAs has changed the way audits are conducted as

auditors are now required to undertake more testing of internal controls. The additional control

testing resulted in large increases in audit fees and auditors have come under pressure from client

management to restrain these fee increases (Raghunandan and Rama 2006; Iliev 2010). Auditors

had to perform the required internal control audits so they may have responded to fee pressures

by reducing their substantive tests, which are designed to identify accounting misstatements. The

2 We confirm that this inference from U.S. research generalizes to our Chinese sample. In particular, Appendix C shows significant positive associations between audit adjustments (LnADJMAG or ABNADJ) and the auditor’s decision to disclose internal control weaknesses (ICMOD).

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increased emphasis on control testing and reduced emphasis on substantive testing could have

impaired auditors’ ability to detect material misstatements in the pre-audit financial statements.

In principle auditors are supposed to expand their substantive testing when tests of controls

reveal material weaknesses but, in practice, the evidence suggests that auditors fail to

appropriately increase their substantive tests in response to identified internal control

weaknesses. Specifically, research has shown that companies with adverse internal control

opinions have worse financial reporting quality than companies with clean opinions, which

suggests that auditors fail to fully compensate for the higher control risks by appropriately

increasing their substantive testing (Doyle et al. 2007; Ashbaugh-Skaife et al. 2008; Hammersley

et al. 2011; Donelson et al. 2017).

In short, we argue that MICAs have reduced auditors’ detection of material

misstatements. We therefore expect a drop in audit adjustments following the introduction of

MICAs. Our first hypothesis is stated in the alternative form:

H1: The introduction of MICAs has led to abnormal reductions in audit adjustments.

Prior research has shown that audit adjustments help to improve the quality of financial

reporting (Lennox et al. 2016; 2018). Therefore, when MICAs cause abnormal reductions in audit

adjustments (as predicted in H1), we would expect a consequent deterioration in financial

reporting quality. In other words, there would be more material misstatements of the audited

financial statements due to the increased failure of auditors to detect (and correct) material

misstatements of the pre-audit financial statements. Our second hypothesis is therefore stated as

follows (in the alternative form):

H2: The introduction of MICAs has led to more accounting misstatements at companies that experienced abnormal reductions in audit adjustments when moving from the pre-MICA period to the post-MICA period.

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If the evidence supports H1 and H2, the implication would be that the introduction of MICAs has

failed to improve financial reporting quality because auditors are now less likely to detect (and

correct) material misstatements of the pre-audit financial statements.

In contrast, we do not expect worse financial reporting quality at the companies that did

not experience abnormal reductions in audit adjustments. Instead, we expect an improvement in

their financial reporting quality because: i) auditors are conducting more tests of internal controls

in the post-MICA period, and ii) companies have incentives to improve their internal controls in

order to avoid receiving adverse opinions. This was the original intention of regulators when they

introduced MICAs. Therefore, our third hypothesis is stated as follows (in the alternative form):

H3: The introduction of MICAs has led to fewer accounting misstatements at companies that did not experience abnormal reductions in audit adjustments when moving from the pre-MICA period to the post-MICA period.

3. Background, sample, and descriptive statistics

3.1 Background

China’s own version of the Sarbanes-Oxley Act of 2002 began in 2008 with the issuance of the ‘Basic

Standard for Enterprise Internal Control’. Like SOX, this standard was intended to improve the quality

of financial reporting by listed companies. China issued three ‘Supplementary Guidelines of

Enterprise Internal Control’ in 2010, which articulate how companies should establish, self-evaluate,

and report on their internal controls, and which show how auditors should conduct internal control

audits. The audit guidelines largely mirror those found in U.S. Auditing Standard No. 5 (AS5). For

instance, auditors are required to focus on internal controls over financial reporting, a material internal

control weakness is defined as “a reasonable possibility that a material misstatement of the company’s

annual or interim financial statements will not be prevented or detected on a timely basis”, and the

auditor is required to publicly disclose internal control weaknesses in an audit report (MOF 2010;

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CICPA 2011). The guideline also requires auditors to cross reference evidence and conclusions

from the internal control audit and the financial statement audit (CICPA 2011, Section 9.2), a

requirement that also exists in the U.S. under the PCAOB (2007, Appendix B, B8).

China’s Ministry of Finance (MOF 2012a; 2012b) introduced mandatory internal control

audits on a staggered basis over time. As shown in Panel A of Table 1, MICAs were introduced

for: cross-listed companies in 2011; state-owned main-board-listed companies in 2012; large non-

state-owned main-board-listed companies in 2013 (i.e., companies with market values of at least

5 billion RMB by December 31, 2011 and average net incomes of 30 million RMB during 2009-

2011); and all other main-board companies in 2014. Companies listed on the small and medium-

sized enterprise board and the Growth Enterprise Market are not required to undergo internal

control audits, with the exception of a few cross-listed companies on the small and medium-sized

enterprise board.

3.2 Sample

Our sample period is from 2007 to 2015 so that we have data for the pre-MICA years as well as

the post-MICA years. Our sample ends in 2015 because this is the last year that audit adjustment

data are available to us. We identify MICAs from the DIB Internal Control and Risk Management

database, with additional validation from other regulatory and public sources. As shown in Panel

B, our initial sample of 19,707 company-year observations is from the Chinese Stock Market and

Accounting Research (CSMAR) database, and comprises 4,811 observations subject to MICAs and

14,896 observations not subject to MICAs.

[INSERT TABLE 1 HERE]

Next, we derive our final sample using the steps shown in Panel A of Table 2. Starting

with the 19,707 observations from the CSMAR database, we drop 166 observations where the

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internal control audit and the financial statement audit are undertaken by different audit firms.

We drop these non-integrated audits because the internal control audit is nearly always

integrated with the financial statement audit (the two audits are always integrated in the United

States).3 Next, we merge the CSMAR database with the Ministry of Finance database to obtain

each company’s pre-audit earnings (EPRE), which we compare to audited earnings (EAUD) in order

to quantify the size of the audit adjustment to reported earnings. Merging these two databases

results in the loss of 2,650 observations. We lose 547 observations where data are missing for the

control variables, and we lose another 1,106 observations where the value of audited earnings

(EAUD) is different in the CSMAR database compared to the Ministry of Finance database.4 The

final sample consists of 15,238 firm-year observations.5 Panel B of Table 2 presents the yearly

distribution of the sample.

[INSERT TABLE 2 HERE]

3.3 Descriptive statistics

Table 3 reports descriptive statistics for the sample. We identify misstatements of the audited

financial statements using information from subsequent restatement announcements (DIB

database) and regulatory sanctions (CSMAR database). We include restatements that impact

financial statement items and exclude those that are due to typographical errors. We exclude

3 China is the only country that does not require the internal control audit to be integrated with the financial statement audit. Gunn et al. (2018) compare audit quality and audit costs for integrated versus non-integrated audits using data from China. Their results suggest that non-integrated auditors provide higher quality MICAs than do integrated auditors. Moreover, companies pay lower fees and experience shorter audit delays when they employ non-integrated auditors rather than integrated auditors. 4 Consistent with Lennox et al. (2018), we define their reported values of audited earnings as being consistent with each other when the difference is less than ±1%. 5 Among our sample, nearly all observations with MICAs (99.6%) are assigned the same one or two signing audit partners for both the financial statement audit and the internal control audit, with only 14 exceptions (0.4%) where two different audit teams are assigned. Dropping the 14 different-team audits from the sample does not alter any of our main results.

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regulatory sanctions for issues unrelated to financial misreporting such as insider trading,

inappropriate stock trading, stock pricing manipulation, or violation of laws other than disclosure

regulations. We use the misstating years in the DIB and CSMAR databases to identify when a

company issued misstated financial statements to investors. We focus on misstatements rather

than other measures of financial reporting quality such as abnormal accruals because a

misstatement is a more direct indication of a breakdown in a company’s internal controls over

financial reporting. Moreover, misstatements suit our purposes because auditors use detected

misstatements in their decision to disclose internal control weaknesses (Bedard and Graham 2011;

Franzel 2015, 2016). We collect data on restatements and regulatory sanctions up to June 2018 to

allow a reasonable ex post window for misstatements to be uncovered and revealed. As shown in

Table 3, the misstatement frequency is 17.1% in our sample. This is about three times higher than

the United States, which reflects that there are more companies in China that have low financial

reporting quality.

For each audit engagement, we measure the absolute magnitude of the audit adjustment

to earnings by scaling the raw adjustment by the absolute value of pre-audit earnings (i.e.,

ADJMAG = │EPRE - EAUD│/│EPRE│). This audit adjustment variable captures the percentage

change to earnings moving from the pre-audit accounts to the audited accounts. For example, if

an audit adjustment reduces reported earnings from $10 million to $9 million, the value of

ADJMAG is 10%. Table 3 shows that the median value of ADJMAG is 0.8%, whereas the 99th

percentile value is 291.8% and the maximum value is 945,929.2%. These numbers reflect that there

are large outliers in ADJMAG because some companies’ pre-audit earnings (EPRE) are close to

zero. We address these outliers by taking a log transformation of ADJMAG and winsorizing this

variable at the 99th percentile (LnADJMAG). As shown in Table 3, this largely takes care of the

outliers.

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[INSERT TABLE 3 HERE]

Table 3 provides descriptive statistics for the control variables: company size (LnTA),

leverage (LEV), profitability (ROA), audit complexity (measured by the log of the number of

subsidiaries, LnSUBS), an indicator variable for state-owned enterprises (SOE), an indicator for

companies not listed on the main board (NONMB), an indicator for the Top Ten audit firms in

China (BIG10), and the length of tenure between the company and its audit firm (in years,

TENURE). These descriptive statistics are similar to those found in prior China studies. Formal

definitions for the variables are provided in Appendix A.

Table 4 reports a pair-wise correlation matrix, where correlations that are significant at

the 5% level or better are highlighted in bold. None of the correlations exceed 0.5 and in

untabulated tests we find that none of the variance-inflation-factors exceed 10.0 in our

regressions, indicating that multicollinearity is not an issue. Consistent with H1, we find that

mandatory internal control audits (MICA) are significantly and negatively correlated with the

size of audit adjustments (LnADJMAG). In other words, companies have smaller adjustments to

earnings when they are subject to mandatory internal control audits.6

[INSERT TABLE 4 HERE]

4. Main results

4.1 Univariate tests of H1

We begin in Table 5 by providing univariate tests for the changes in audit adjustments and the

changes in material accounting misstatements when moving from the pre-MICA period to the

6 Our tests of H2 and H3 require measures of the abnormal reductions in audit adjustments, moving from the pre-MICA period to the post-MICA period. These abnormal adjustment measures will be constructed using the audit adjustment model reported in Col. (2) of Table 7.

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post-MICA period. Cols. (1) and (2) present the mean values of LnADJMAG and MISSTATE for

the pre-periods and the post-periods of companies that become subject to mandatory internal

control audits. Col. (3) presents the mean values of these variables for companies that do not

receive MICAs at any time during the sample period.

[INSERT TABLE 5 HERE]

Table 5 shows a large decrease in audit adjustments when moving from the pre-MICA

period to the post-MICA period. The mean values of LnADJMAG are 0.103 in the pre-MICA

period compared with 0.055 in the post-MICA period and this difference is highly significant (t-

stat. = −11.71). This is consistent with our prediction in H1 that there are large decreases in audit

adjustments following the introduction of MICAs. In contrast, Table 5 shows a small and

statistically insignificant decrease in the frequency of accounting misstatements (from 17.0% to

16.3%) when moving from the pre-MICA period to the post-MICA period (t-stat. = −0.87). This is

inconsistent with an average improvement in financial reporting quality following the

introduction of MICAs. Overall, then, the univariate results indicate a large drop in audit

adjustments following the introduction of MICAs, while there is no significant drop in the

incidence of material accounting misstatements. However, it’s important to note that the

univariate tests in Table 5 fail to control for other potential confounds such as company fixed

effects, year fixed effects, and other time-varying characteristics of companies and audit firms.

4.2 The effect of mandatory internal control audits on accounting misstatements

We begin our regression analysis by testing the impact of MICAs on accounting misstatements.

Prior U.S. research has found mixed results for this association. Nagy (2010) finds a negative

association between MICAs and accounting misstatements, whereas Bhaskar et al. (2019) find a

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positive association. Our univariate analysis in Table 5 fails to find any significant association but

we now examine the regression-based evidence.

Our model of accounting misstatements is shown in eq. (1):

Pr (MISSTATE = 1) = F [α1 + α2 MICA + FE + CONTROLS + u] (1)

The dependent variable (MISSTATE) equals one if the audited financial statements are materially

misstated, and zero otherwise. The MICA variable equals one if the company is subject to a

mandatory internal control audit, and zero otherwise. If MICAs lead to improved (worse)

financial reporting quality, we would expect a negative (positive) coefficient on MICA.

The results are reported in Table 6. Col. (1) is estimated for the full sample with year and

industry fixed effects, while Col. (2) is estimated with year and company fixed effects. The sample

size is reduced in Col. (2) (from 15,238 observations to 7,642) because some companies do not

have any variation over time in the MISSTATE dependent variable. Cols. (1) and (2) show that

the coefficients on MICA are negative, but they are not statistically significant (z-stats. = −0.50,

−0.49). Therefore, consistent with the univariate tests in Table 5, we do not find a significant

reduction in accounting misstatements following the introduction of MICAs. Thus, it appears

that financial reporting quality does not significantly improve, at least not on average.

[INSERT TABLE 6 HERE]

The remainder of our analyses seeks to explain why MICAs do not lead to improved

financial reporting quality. Specifically, we test whether: (1) MICAs result in abnormal reductions

in audit adjustments (H1); (2) financial quality becomes worse for companies that experience

abnormal reductions in audit adjustments following the introduction of MICAs (H2); and (3)

financial quality improves for companies that do not experience abnormal reductions in audit

adjustments following the introduction of MICAs (H3).

18

4.3 The effect of mandatory internal control audits on audit adjustments (H1)

We test H1 by estimating the following model of audit adjustments:7

LnADJMAG = β1 + β2 MICA + FE + CONTROLS + u (2) Under H1, we expect significant reductions in audit adjustments following the introduction of

mandatory internal control audits. We therefore predict negative coefficients on MICA in eq. (2);

i.e., β2 < 0. Again, we control for year fixed effects, company fixed effects, and other time-varying

control variables. 8 Including company fixed effects is important because this allows us to

compare how audit adjustments change over time within the same company when moving from the

company’s pre-MICA period to its post-MICA period.

The results for eq. (2) are reported in Col. (1) of Table 7. We find a significant negative

coefficient on MICA (t-stat. = −2.98). This translates to an average decrease of −1.8%in unlogged

adjustments (ADJMAG) when moving from the pre-MICA period to the post-MICA period. This

drop in audit adjustment size is large relative to the sample median value of ADJMAG (0.8%).

Therefore, consistent with H1, there is an abnormally large reduction in audit adjustments

following the introduction of mandatory internal control audits. Results for the control variables

show that audit adjustments are larger for: companies that are less profitable (ROA), companies

with more subsidiaries (LnSUBS), companies audited by large accounting firms (BIG10), and

companies with longer audit firm tenure (TENURE).

[INSERT TABLE 7 HERE]

7 Our dependent variables are the continuous measures of audit adjustments rather than dummy variables because we need to use the residuals from the models of audit adjustments to construct our measures of abnormal adjustments. If the dependent variables in our adjustment models were dummy variables we would not be able to construct the residuals because the dependent variable in a logit or probit model is an unobserved latent variable, which means the residuals from the logit and probit models are unobserved (Gourieroux et al. 1987). 8 The NONMB variable is a time-invariant company characteristic so this variable does not appear in the models that control for company fixed effects.

19

4.4 Tests of H2 and H3

In order to test H2 and H3, it is necessary to identify which companies experience abnormally

large reductions in audit adjustments following the introduction of MICAs. The negative

coefficient on MICA in Col. (1) of Table 7 shows there are abnormally large reductions on average,

but this does not tell us which companies experience (do not experience) abnormal reductions in

audit adjustments. To identify these two groups of companies, we re-estimate eq. (2) without the

MICA variable and compute the residuals. The residuals from Col. (2) of Table 7 are the abnormal

adjustments (which we label ABNADJ). The next step is to identify which companies experience

(or do not experience) abnormal reductions in audit adjustments following the introduction of

MICAs. We identify these companies by comparing their abnormal residuals in the post-MICA

period and the pre-MICA period. The CHABNADJ variable equals a company’s average value of

ABNADJ in years with a mandatory internal control audit (i.e., MICA = 1) minus the same

company’s average value of ABNADJ in years without a mandatory internal control audit (i.e.,

MICA = 0). The abnormal reduction in audit adjustments is measured as ABNADJDECR, which

equals the absolute value of CHABNADJ if CHABNADJ < 0, and zero otherwise.

We test H2 and H3 using the following model of accounting misstatements:

Pr (MISSTATE = 1) = F [γ1 + γ2 MICA × ABNADJDECR + γ3 MICA + γ4 ABNADJDECR + FE + CONTROLS + u] (3)

The misstatement model in eq. (3) is the same as eq. (1) except that we have added the variable

for abnormal adjustment decreases (ABNADJDECR), along with the interaction MICA ×

ABNADJDECR. The interaction allows us to compare how misstatements change following the

introduction of mandatory internal control audits for companies that experience abnormal

reductions in audit adjustments when moving from the pre-MICA period to the post-MICA

20

period. Under H2, we expect an increase in accounting misstatements following the introduction

of MICAs when companies experience larger abnormal reductions in audit adjustments.

Therefore, we predict that γ2 > 0. This would mean that there is a deterioration in financial

reporting quality when companies have larger abnormal reductions in audit adjustments

following the introduction of MICAs. (Note that the ABNADJDECR variable is a time-invariant

company characteristic so this variable drops out of the specification that controls for company

fixed effects.)

The MICA coefficient in eq. (3) captures the change in accounting misstatements for

companies that do not experience an abnormal reduction in audit adjustments following the

introduction of mandatory internal control audits (i.e., the coefficient on MICA captures the

impact of mandatory internal control audits when the ABNADJDECR variable is set equal to zero).

Under H3, we expect a reduction in accounting misstatements following the introduction of

MICAs for companies that do not experience abnormal reductions in audit adjustments.

Therefore, we predict that γ3 < 0. This would indicate an improvement in financial reporting

quality at companies where the introduction of MICAs does not cause an abnormal reduction in

audit adjustments.

Before estimating eq. (3) we first report univariate difference-in-difference tests. We

partition companies that are subject to mandatory internal control audits into two groups: the

first group experiences large abnormal reductions in audit adjustments (ABNADJDECR_H equals

one if ABNADJDECR is larger than the mean value of ABNADJDECR), and the second group does

not (ABNADJDECR_H = 0 if ABNADJDECR is smaller than the mean value of ABNADJDECR).

The results are shown in Panel A of Table 8. Col. (1) contains the companies that

experience large abnormal reductions in audit adjustments following the introduction of MICAs,

while Col. (2) contains the companies that do not experience large abnormal reductions in audit

21

adjustments following the introduction of MICAs. Moving from the pre-MICA period to the post-

MICA period we find a significant increase in accounting misstatements from 20.0% to 25.2% for

the companies that experience large abnormal reductions in audit adjustments following the

introduction of MICAs (Col. (1): t-stat. = 2.84). In other words, financial reporting quality

deteriorates for these companies following the introduction of MICAs. In contrast, we find that

financial reporting quality goes in the other direction for other companies. Moving from the pre-

MICA period to the post-MICA period we find a significant decrease in accounting misstatements

from 16.0% to 13.6% for the companies that do not experience large abnormal reductions in audit

adjustments following the introduction of MICAs (Col. (2): t-stat. = −2.74). In other words,

financial reporting quality improves for these companies following the introduction of MICAs.

As expected, the difference-in-differences test is also statistically significant (t-stat. = 4.08). In

other words, the different misstatement rates between the two groups increase when moving

from the pre-MICA period to the post-MICA period. These univariate findings provide

preliminary support to H2 and H3 that financial reporting quality deteriorates (improves) for

companies that experience (do not experience) large abnormal reductions in audit adjustments

following the introduction of mandatory internal control audits.

[INSERT TABLE 8 HERE]

The regression results for eq. (3) are shown in Panel B of Table 8. Col. (1) reports the results

for the full sample (N = 15,238). Col. (2) reports results for the sub-sample of companies that

become subject to mandatory internal control audits at some time during the sample period (N =

9,414).9 Col. (3) reports results after controlling for year and company fixed effects. The sample

9 The sample in Col. (2) is the same one used for the univariate tests in Panel A of Table 8.

22

size is reduced in Col. (3) because some companies do not have any variation over time in the

MISSTATE dependent variable (N = 5,026).

In all three columns we find significant positive coefficients on the interaction variable

MICA × ABNADJDECR (z-stats. = 4.29, 4.02, 4.39). Consistent with H2, this means there is an

increase in accounting misstatements following the introduction of MICAs when companies

experience large abnormal reductions in audit adjustments as they move from the pre-MICA

period to the post-MICA period. In other words, there is a deterioration in financial reporting

quality when companies experience abnormally large reductions in audit adjustments after

MICAs are introduced. These results are also economically significant. For instance, in the full

sample (N = 15,238), the average misstatement rate under mandatory internal control audits is

14.46% at companies without abnormal reductions in adjustments, whereas it is 17.99% at

companies with a 10% abnormal reduction in adjustments.

We also find significant negative coefficients on MICA in all three columns (z-stats. = −2.17,

−3.13, -2.75). Consistent with H3, this means the introduction of MICAs is followed by a

significant reduction in accounting misstatements for companies that do not experience abnormal

reductions in audit adjustments as they move from the pre-MICA period to the post-MICA period.

This suggests there is an improvement in financial reporting quality for these companies.

Moreover, these results are economically significant. The average misstatement rate at companies

without abnormal reductions in audit adjustments is 17.22% during the pre-MICA period and

this falls to 14.46% during the post-MICA period.

5. Additional analyses

5.1 The immediate and later impact of introducing mandatory internal control audits

23

Nagy (2010) finds an initial decrease in misstatements following the introduction of MICAs,

whereas Bhaskar et al. (2019) find a positive association between MICAs and misstatements in

the period from 2007 onwards. We therefore look into the immediate and later effects of

introducing MICAs. We split the MICA variable into MICA_FIRST (equal to one in the first year

the mandatory internal control audit is introduced, and zero otherwise) and MICA_LATER (equal

to one in subsequent mandatory internal control audits, and zero otherwise). We re-run the

models in Table 8 after replacing the MICA variable with MICA_FIRST and MICA_LATER, and

replacing the MICA × ABNADJDECR variable with MICA_FIRST × ABNADJDECR and

MICA_LATER × ABNADJDECR.

Table 9 presents the regression results. (For the sake of brevity, we do not tabulate the

control variables). The coefficients on MICA_FIRST × ABNADJDECR in Cols. (1) to (3) are

significantly positive (z-stats. = 4.09, 3.83, 3.72), and the coefficients on MICA_LATER ×

ABNADJDECR are also significantly positive (z-stats. = 3.42, 3.18, 3.47). Moreover, there is no

significant difference between the coefficients on these two interaction variables (Chi2 = 0.52, 0.56,

1.05). These results mean that there is an immediate and sustained increase in accounting

misstatements for companies that experience abnormally large reductions in audit adjustments

as they move from the pre-MICA period to the post-MICA period. Thus, our H2 results hold for

both initial and later mandatory internal control audits.

We find that the coefficients on MICA_FIRST are significantly negative (z-stats. = −2.45,

−2.87, −2.72), and the coefficients on MICA_LATER are also significantly negative (z-stats. = −2.90,

−2.35 in Cols. (2) and (3)). Moreover, in all three columns, we find no significant difference in the

coefficients on MICA_FIRST and MICA_LATER (Chi2 = 0.83, 0.63, 0.00). These results mean there

is an immediate and sustained decrease in accounting misstatements at companies that do not

experience abnormal reductions in audit adjustments as they move from the pre-MICA period to

24

the post-MICA period. Thus, our H3 results hold for both initial and later mandatory internal

control audits.

[INSERT TABLE 9 HERE]

5.2 Audit adjustments and internal control opinions

In our hypothesis development, we assumed that auditors are more likely to disclose internal

control weaknesses when they detect abnormally large misstatements in the pre-audit financial

statements. This assumption is necessary for our argument that auditors are less motivated to

discover material misstatements following the introduction of MICAs because such

misstatements necessitate the disclosure of internal control weaknesses. This assumption was

based on evidence from the U.S. (Bedard and Graham 2011; Franzel 2015, 2016) but we are using

Chinese data, so it is important to verify that the assumption holds in China as well. We therefore

examine how audit adjustments affect the auditor’s decision to disclose internal control

weaknesses.

For this analysis we restrict the sample to the 3,418 observations with mandatory internal

control audits because we require data on the internal control audit opinions. Following Ge et al.

(2018) we select only the internal control weaknesses that pertain to financial reporting.10 As

shown in Appendix B, weaknesses in internal controls over financial reporting (ICMOD = 1) are

disclosed in 133 internal control reports (25 reports are adverse and 108 are modified).11 The

remaining 3,285 reports do not disclose internal control weaknesses over financial reporting

10 In China, auditors sometimes issue modified opinions even when there are no weaknesses in internal controls over financial reporting. 11 In China, auditors have to publicly disclose any ‘significant’ weaknesses (using modified opinions) as well as ‘material’ weaknesses (using adverse opinions).

25

(ICMOD = 0). We test the impact of audit adjustments on internal control reporting using the

following model:

Pr (ICMOD = 1) = F [δ1 + δ2 LnADJMAG + FE + CONTROLS + u] (4a) Pr (ICMOD = 1) = F [δ1 + δ2 ABNADJ + FE + CONTROLS + u] (4b)

We expect auditors are more likely to disclose internal control weaknesses when they require

larger corrections to earnings (δ2 > 0). We use the raw values and residual values of audit

adjustments in eqs. (4a) and (4b), respectively. The results are shown in Appendix C. The

coefficients on audit adjustments (LnADJMAG and ABNADJ) are significantly positive (z-stats. =

3.99, 3.11, 2.83, 2.83 in Cols. (1) to (4)). These results are consistent with our assumption that

auditors report internal control weaknesses when they detect larger misstatements in the pre-

audit financial statements.

5.3 Internal control opinions and auditor switching

In our hypothesis development, we argued that auditors have less incentive to detect material

misstatements following the introduction of MICAs because auditors are more likely to be

dismissed when they disclose internal control weaknesses. This assumption was based on

evidence from prior U.S. research (Ettredge et al. 2011; Newton et al. 2016), but we are using

Chinese data, so it is important to verify that the assumption holds in China as well. We therefore

follow these studies by examining the association between internal control audit opinions and

subsequent auditor switching.

We test the effect of internal control opinions on auditor switching by estimating the

following model:

Pr (AUDCHt+1 = 1) = F [θ1 + θ2 MICA_MODt + θ3 MICA_CLEANt + FE + CONTROLS + u] (5)

26

In eq. (5), the dependent variable (AUDCHt+1) equals one if the audit firm is removed in the

following year, and zero otherwise. The MICA_MODt (MICA_CLEANt) variable equals one if the

company is subject to a mandatory internal control audit and receives a modified (clean) internal

control audit opinion in year t, and zero otherwise. We expect auditors are more likely to be

removed after they disclose internal control weaknesses (i.e., θ2 > θ3). The results are shown in

Appendix D. We find the coefficients on MICA_MOD are significantly positive (z-stats. = 3.00,

2.90), and they are significantly more positive than the coefficients on MICA_CLEAN (Chi2 = 9.49,

4.49). These findings confirm that auditors are more likely to be dismissed from the audit

engagement after they disclose internal control weaknesses.

5.4 Mandatory internal control audits and audit fees

The introduction of mandatory internal control audits caused a large and significant increase in

audit fees in the United States (Raghunandan and Rama 2006; Krishnan et al. 2008; Iliev 2010). In

this section, we examine whether the same finding generalizes to China. We test the effect of

mandatory internal control audits on audit fees by estimating the following model:

LnAF = λ1 + λ2 MICA + FE + CONTROLS + u (6) The dependent variable (LnAF) equals the natural log of the audit fee paid to the auditor. We

expect a significant increase in audit fees following the introduction of mandatory internal control

audits (i.e., λ2 > 0). We continue to control for company fixed effects and year fixed effects so that

our variables of interest capture the change in fees within the same company when moving from

the pre-MICA period to the post-MICA period.

The results are shown in Appendix E. As expected, we find a significant increase in audit

fees following the introduction of MICAs. The average fee increase is economically large (26.7%)

27

as well as statistically significant (t-stat. = 19.73 in Col. (1)).12 Col. (2) finds that the impact on audit

fees is significantly larger in the initial year that MICAs are introduced. Moreover, Col. (3) shows

that the fee increase is larger when auditors disclose internal control weaknesses compared to

when they issue clean internal control opinions, although this difference is not statistically

significant.

5.5 Voluntary internal control audits

Our focus has been on mandatory internal control audits. However, some of the companies in our

sample were already purchasing internal control audits on a voluntary basis before they were

mandated to do so. In our sample, there are 3,418 observations where companies are subject to

mandatory internal control audits (MICA = 1). In 2,358 of these observations the company was

not purchasing a voluntary internal control audit in the year before the rule was introduced, and

in 1,060 observations the company was purchasing a voluntary internal control audit in the year

before MICAs were introduced. We expect the reduction in audit adjustments (H1) to be driven

by the companies that were not voluntarily purchasing internal control audits. In other words,

we expect a stronger result for H1 when companies switch from no internal control audit to a

mandatory internal control audit, compared to when companies switch from a voluntary internal

control audit to a mandatory internal control audit.

To test this, we construct two additional variables: MICA_NOPREVOL equals one if the

company is subject to a mandatory internal control audit and the company did not purchase an

12 Prior studies document an even larger fee increase in the United States (Raghunandan and Rama 2006; Krishnan et al. 2008; Iliev 2010). However, they examine the introduction of MICAs under the PCAOB’s more stringent Auditing Standard 2 (AS2). Krishnan et al. (2011) find the switch from AS2 to AS5 has helped to reduce the positive impact of MICAs on audit fees. China’s standards on internal control audits are very similar to AS5, which likely explains why we find a smaller increase in audit fees following the introduction of MICAs in China.

28

internal control audit in the year immediately before its first MICA (zero otherwise);

MICA_PREVOL equals one if the company is subject to a mandatory internal control audit and

the company voluntarily purchased an internal control audit in the year immediately before its

first MICA (zero otherwise). We re-test H1 by estimating our model of audit adjustments (Table

7) using MICA_NOPREVOL and MICA_PREVOL instead of MICA. (The PREVOL variable is a

time-invariant company-specific characteristic, which is subsumed by the inclusion of company

fixed effects in Table 7.)

In this untabulated test, we find a significant negative coefficient on MICA_NOPREVOL

(t-stat. = −3.49). This confirms that there is a significant drop in audit adjustments following the

introduction of MICAs for the companies that did not voluntarily purchase internal control audits

before they had to do so. In contrast, we find a small and statistically insignificant coefficient on

MICA_PREVOL (t-stat. = −0.77), which means there is no significant drop in audit adjustments

for companies that were already purchasing internal control audits on a voluntary basis.

Furthermore, we find that the MICA_NOPREVOL coefficient is significantly more negative than

the MICA_PREVOL coefficient. Therefore, the drop in audit adjustments following the

introduction of MICAs is significantly larger for companies that were not voluntarily purchasing

internal control audits. These results reinforce our inference from H1 that the abnormal drop in

audit adjustments is attributable to the introduction of internal control audits.

Next, we re-estimate our models of accounting misstatements (Table 8) using

MICA_NOPREVOL, MICA_PREVOL, MICA_NOPREVOL × ABNADJDECR and MICA_PREVOL

× ABNADJDECR, which replace the MICA and MICA × ABNADJDECR variables. In these

untabulated tests, we find significant positive coefficients on MICA_NOPREVOL ×

ABNADJDECR (z-stats. = 4.17, 3.97, 4.58). This means there is a significant increase in accounting

misstatements following the introduction of MICAs for companies that experienced large

29

abnormal drops in audit adjustments moving from the pre-MICA period to the post-MICA period

where those companies did not purchase voluntary internal control audits before their first

MICA. In contrast, we find insignificant coefficients on MICA_PREVOL × ABNADJDECR (z-stats.

= 0.85, 0.64, 0.28). Therefore, our results for H2 are primarily driven by the companies that did

not previously purchase internal control audits on a voluntary basis.

Finally, we find negative coefficients for MICA_NOPREVOL (z-stats. = −1.32, −2.51, −2.88)

and MICA_PREVOL (z-stats. = −2.68, −3.27, −1.42). This means that our H3 result holds for both

the voluntary purchasers and the companies that did not purchase a voluntary internal control

audit before their first MICA. In both groups, financial reporting quality improves following the

introduction of MICAs as long as they do not experience abnormally large drops in audit

adjustments moving from the pre-MICA period to the post-MICA period.

5.6 Outlier issues

We previously documented (in Table 3) that the raw value of audit adjustments (ADJMAG) has

some outliers which is why we used a log transformation (with winsorization). While this is a

conventional way to deal with outliers, we also follow Kane and Meade (1998) by using a rank-

transformation for audit adjustments (Rank(ADJMAG)). Specifically, when ADJMAG has N non-

zero observations in year t, we replace each observation with its corresponding rank (from j = 1,

..., N in ascending order) and the rank j assigned to each observation is then divided by N+1. This

ensures that the rank-transformed variable is distributed between zero and one. When ADJMAG

equals zero (i.e., no audit adjustment), we code Rank(ADJMAG) as zero.

We then re-run our regressions in Table 7 using the Rank(ADJMAG) variable. In these

untabulated tests, we continue to find a significant negative coefficient on MICA (z-stat. = −5.89).

This confirms that there are large reductions in audit adjustments following the introduction of

30

MICAs (H1). Next, we use the residuals to compute the abnormal reductions in ranked

adjustments moving from the pre-MICA period to the post-MICA period. We then re-run our

regressions in Table 8 using these alternative abnormal reductions in audit adjustments. We

continue to find significant positive coefficients on MICA × ABNADJDECR (z-stats. = 2.74, 2.47,

2.56 in Cols. (1) to (3)), which indicates a significant increase in accounting misstatements for

companies that experience abnormally large reductions in audit adjustments (H2). We also find

significant negative coefficients on MICA (z-stats. = −1.76, −2.81, −2.41), suggesting a significant

decrease in accounting misstatements for companies that do not experience abnormally large

reductions in audit adjustments (H3).

6. Conclusion

Regulators around the world have introduced mandatory internal control audits in the hope that

these audits would help to improve the quality of financial reporting. However, prior research

has found mixed evidence that the introduction of MICAs has achieved this intended goal (Nagy

2010; Iliev 2010; Bhaskar et al. 2019). We argue that there has not been a clear improvement in

financial reporting quality because the introduction of mandatory internal control audits altered

the previous equilibrium in unintended ways.

Before MICAs were introduced, material misstatements of the pre-audit financial

statements were corrected during the audit without any public repercussions for the company’s

management. As long as the corrections were made before the audited financial statements were

released to investors, the auditor could issue a clean opinion and managers would not suffer from

unfavorable audit reports. The introduction of MICAs changed this equilibrium because auditors

are now required to publicly disclose material weaknesses even when corrections are made to the

pre-audit financial statements. These unfavorable disclosures are costly to auditors as well as

31

managers because they increase the likelihood of the auditor being dismissed from the

engagement. This means that auditors now have less incentive to detect material misstatements

during the course of an audit. Furthermore, auditors have come under pressure to constrain

increased audit costs following the introduction of MICAs. Auditors were unable to cut back on

their tests of internal controls so they could have responded to the audit fee pressures by cutting

back on their substantive testing. This would also increase the risk of an auditor failing to detect

an existing material misstatement. Accordingly, we predict that the introduction of MICAs has

resulted in significant reductions in audit adjustments (H1).

Further, we argue that this change in audit adjustments explains the evidence on financial

reporting quality. We predict a decline in financial reporting quality for companies that

experience abnormally large reductions in audit adjustments following the introduction of

MICAs (H2). In contrast, we predict an increase in financial reporting quality for companies that

do not experience abnormally large reductions in audit adjustments following the introduction

of MICAs (H3).

Consistent with H1, we show that the introduction of MICAs has led to an abnormally

large drop in audit adjustments. This means that auditors are detecting (and correcting) fewer

material misstatements of the pre-audit financial statements in the presence of a MICA. This

reduction in audit adjustments does not signify an improvement in the quality of companies’ pre-

audit financial statements. To the contrary, we find a significant increase in material

misstatements when there are abnormally large reductions in audit adjustments following the

introduction of MICAs (H2). The deterioration in financial reporting quality among these

companies explains why financial reporting quality has not improved on average. Further, we

find a significant decrease in material misstatements among companies that do not experience

abnormally large reductions in audit adjustments following the introduction of MICAs (H3). That

32

is, the introduction of MICAs is followed by improved financial reporting quality when auditors

do not reduce their audit adjustments.

We acknowledge the limitation that our results are confined to a single country (China)

and may not generalize elsewhere. We have tried to address this limitation by replicating prior

evidence from the United States on SOX 404(b) audits. Consistent with U.S. research, we show

that auditors are more likely to disclose internal control weaknesses when they require larger

adjustments to their clients’ pre-audit financial statements. We also show that auditors are more

likely to be removed from the audit engagement after they disclose internal control weaknesses.

Together, these two results are consistent with auditors having less incentive to find material

misstatements following the introduction of MICAs (H1). Moreover, we replicate prior evidence

from the U.S. that the introduction of MICAs has caused large increases in audit fees. The

consistency between these results for the U.S. and Chinese settings give us some comfort that our

conclusions for H1, H2, and H3 are unlikely to be specific to China. Nevertheless, we

acknowledge that we are unable to test H1, H2, and H3 in the U.S. setting because we do not have

the necessary audit adjustment data.

33

References Ashbaugh-Skaife, H., D. Collins, W. Kinney, and R. Lafond. 2008. The effect of SOX internal

control deficiencies and their remediation on accrual quality. The Accounting Review 83: 217-50.

Bedard, J., and L. Graham. 2011. Detection and severity classifications of Sarbanes-Oxley Section

404 internal control deficiencies. The Accounting Review 86: 825–855. Bhaskar, L., Schroeder, J., Shepardson, M., 2019. Integration of internal control and financial

statements audits: Are two audits better than one? The Accounting Review, forthcoming. Bronson, S. N., C. E. Hogan, M. F. Johnson, and K. Ramesh. 2011. The unintended consequences

of PCAOB Auditing Standard Nos. 2 and 3 on the reliability of preliminary earnings releases. Journal of Accounting and Economics 51: 95-114.

China’s Ministry of Finance (MOF). 2010. The Guidance on Internal Control Audit of Business

Enterprises. April 15, Beijing: China’s MOF. China’s Ministry of Finance (MOF). 2012a. Interpretation of issues arising from implementing internal

control regulations No. 1. Feb. 23, Beijing: China’s MOF. China’s Ministry of Finance (MOF). 2012b. On the schedule for main-board listed companies to

implement internal control regulations. Aug. 14, Beijing: China’s MOF. Chinese Institute of Certified Public Accountants (CICPA). 2011. On Implementing the Guidance on

Internal Control Audit of Business Enterprises. October 11, Beijing: CICPA. DeFond, M.L., and C. Lennox. 2017. Do PCAOB inspections improve the quality of internal

control audits? Journal of Accounting Research 55 (3): 591-627. Donelson, D. C., M. S. Ege, and J. M. McInnis. 2017. Internal control weaknesses and financial

reporting fraud. Auditing: A Journal of Practice & Theory 36: 45-69. Doyle, J., W. Ge, and S. McVay. 2007. Accruals quality and internal control over financial

reporting. The Accounting Review 82: 1141-1170. Ettredge, M., Heintz, J., Li, C., Scholz, S., 2011. Auditor realignments accompanying

implementation of SOX 404 ICFR reporting requirements. Accounting Horizons 25 (1): 17-39. Financial Executives Institute (FEI), 2005. Comments of the Committee on Corporate Reporting.

Submitted to the SEC Roundtable on Implementation of Internal Control Reporting Provisions. Washington, D.C.: SEC. Available at: https://www.sec.gov/spotlight/soxcomp/soxcomp-brod.pdf.

Franzel, J. M. 2015. Current issues, trends, and open questions in audits of internal control over

34

financial reporting. In American Accounting Association Annual Meeting, Chicago, IL. Available at: https://pcaobus.org/News/Speech/Pages/08102015_Franzel.aspx.

Franzel, J. M. 2016. Update on trends and issues in audits of internal control over financial

reporting. In American Accounting Association Annual Meeting, New York, NY. Available at: https://pcaobus.org/News/Speech/Pages/Franzel-speech-internal-control-over-financial-reporting-AAA-08-06-2016.aspx.

Ge, W., A. Koester, and S. McVay. 2017. Benefits and costs of Sarbanes-Oxley Section 404(b)

exemption: Evidence from small firms’ internal control disclosures. Journal of Accounting and Economics 63 (2-3): 358-384.

Ge, W., Li, Z., Liu, Q., McVay, S., 2018. When does internal control over financial reporting curb

resource extraction? Evidence from China. Working paper. Gourieroux, C., Monfort, A., Renault, E., and A. Trognon. 1987. Simulated residuals. Journal of

Econometrics 34(1-2): 201-252. Gunn, J., Li, C., Liao, L., Zhou, S., 2018. Is it better to kill two birds with one stone? Internal control

audit quality and audit costs for integrated versus non-integrated audits. Working paper. Hammersley, J., Johnstone, K., Kadous, K., 2011. How do audit seniors respond to heightened

fraud risk? Auditing: A Journal of Practice and Theory 30 (3): 81-101. Hammersley, J., Myers, L., Shakespeare, C., 2008. Market reactions to the disclosure of internal

control weaknesses and to the characteristics of those weaknesses under Section 302 of the Sarbanes Oxley Act of 2002. Review of Accounting Studies 13(1): 141-165.

Iliev, P., 2010. The effect of SOX Section 404: Costs, earnings quality, and stock prices. The Journal

of Finance 65(3): 1163-1196. Johnstone, K., Li, C., Rupley, K. H., 2011. Changes in corporate governance associated with the

revelation of internal control material weaknesses and their subsequent remediation. Contemporary Accounting Research 28(1): 331-383.

Kane, G. D., Meade, N. L. 1998. Ratio analysis using rank transformation. Review of Quantitative

Finance and Accounting 10 (1): 59–74. Krishnan, J., Rama, D., Zhang, Y., 2008. Costs to comply with SOX Section 404. Auditing: A Journal

of Practice & Theory 27 (1): 169-186. Krishnan, J., Krishnan, J., Song., H., 2011. The effect of Auditing Standard No. 5 on audit fees.

Auditing: A Journal of Practice & Theory 30 (4): 1-27. Lennox, C., Wu, X., Zhang, T. 2016. How do audit adjustments affect earnings quality? Evidence

from China. Journal of Accounting and Economics 61 (2-3): 545-562.

35

Lennox, C., Wang, Z., Wu, X. 2018. Earnings management, audit adjustments, and the financing of corporate acquisitions: Evidence from China. Journal of Accounting and Economics 65 (1): 21-40.

Li, C., Sun, L., Ettredge, M., 2010. Financial executive qualifications, financial executive turnover,

and adverse SOX 404 opinions. Journal of Accounting and Economics 50: 93-110. Nagy, A. 2010. Section 404 compliance and financial reporting quality. Accounting Horizons 24 (3):

441-454. Newton, N. J., Persellin, J. S., Wang, D., Wilkins, M. S., 2016. Internal control opinion shopping

and audit market competition. The Accounting Review 91(2): 603-623. Public Company Accounting Oversight Board (PCAOB). 2007. An Audit of Internal Control Over

Reporting That Is Integrated with Audit of Financial Statements and Related Independence Rule and Conforming Amendments. Release No. 2007-005A. Washington, DC: PCAOB.

Raghunandan, K., and D. Rama. 2006. SOX Section 404 material weakness disclosures and audit

fees. Auditing: A Journal of Practice & Theory 25: 99-114. Rice, S., and D. Weber. 2012. How effective is internal control reporting under SOX 404?

Determinants of the (non-) disclosure of existing material weaknesses. Journal of Accounting Research 50: 811–843.

Schroeder, J., and M. Shepardson. 2016. Do SOX 404 control audits and management assessments

improve overall internal control system quality? The Accounting Review 91: 1513-41.

36

APPENDIX A Variable Definitions

Audit adjustment and misstatement variables

EPRE Pre-audit earnings. EAUD Audited earnings. ADJMAG The absolute magnitude of the audit adjustment (i.e., │EPRE - EAUD│/│EPRE│). LnADJMAG Natural log of (one plus) ADJMAG. ABNADJ The residuals from the following model of audit adjustments:

LnADJMAG = a + FE + CONTROLS + u, where FE are company fixed effects and year fixed effects and CONTROLS is a set of control variables. The residuals are estimated from the audit adjustment model reported in Col. (2) of Table 7.

CHABNADJ A company’s average value of ABNADJ in years with a mandatory internal control audit (i.e., MICA = 1) minus the same company’s average value of ABNADJ in years without a mandatory internal control audit (i.e., MICA = 0).

ABNADJDECR The absolute value of CHABNADJ if CHABNADJ < 0, and zero otherwise. For companies that never receive a mandatory internal control audit, the value of CHABNADJ is set at zero.

ABNADJDECR_H Indicator variable equal to one if ABNADJDECR is larger than the mean value of ABNADJDECR, and zero otherwise.

MISSTATE Indicator variable equal to one if there is a misstatement that results in a subsequent restatement or regulatory sanction, and zero otherwise.

Internal control audit variables MICA Indicator variable equal to one if the company undergoes a mandatory internal

control audit, and zero otherwise. MICA_FIRST Indicator variable equal to one in the first year that the mandatory internal

control audit is introduced for the company, and zero otherwise. MICA_LATER Indicator variable equal to one for subsequent years in which the company is

subject to mandatory internal control audits, and zero otherwise. ICMOD Indicator variable equal to one if the company receives a modified or adverse

internal control audit opinion due to weaknesses in internal controls over financial reporting, and zero otherwise.

MICA_MOD Indicator variable equal to one if the company undergoes a mandatory internal control audit and receives a modified or adverse internal control audit opinion due to weaknesses in internal controls over financial reporting, and zero otherwise.

MICA_CLEAN Indicator variable equal to one if the company undergoes a mandatory internal control audit and receives a clean unmodified internal control audit opinion, and zero otherwise.

Other variables

LnTA Natural log of the company’s total assets. LEV Ratio of total liabilities to total assets. ROA Ratio of net income to total assets. LnSUBS Natural log of (one plus) the number of subsidiaries. SOE Indicator variable equal to one if the company’s ultimate owner is the

government or a state-owned entity, and zero otherwise. NONMB Indicator variable equal to one if the company is not listed on the main board,

and zero otherwise.

37

BIG10 Indicator variable equal to one if the audit firm ranks top 10 (based on the sum of clients’ total assets), and zero otherwise.

TENURE Length of tenure between the audit firm and client (measured in years). AUDCHt+1 Indicator variable equal to one if the company switches to a different audit firm

in the following year, and zero otherwise. LnAF The natural log of the total audit fees paid to the auditor.

38

APPENDIX B Modified internal control audit opinions in China

Appendix B presents the internal control audit opinions for 3,418 sample observations with mandatory internal control audits.

Audit reports disclosing internal control weaknesses over financial reporting (ICMOD = 1) Adverse 25 Modified with emphasis of matter 108 Subtotal 133 Audit reports not disclosing internal control weaknesses over financial reporting (ICMOD = 0) Unmodified 3,263 Modified with emphasis of matter a 21 Disclaimer b 1 Subtotal 3,285 Total observations with mandatory internal control audits 3,418

a In these 21 observations the internal control audit reports mention audit scope exemptions due to current-period mergers and acquisitions, where such exemptions are officially approved by the CSRC, but they do not mention any weaknesses in internal controls over financial reporting. b In this single observation the internal control audit report mentions audit scope limitations without mentioning any weaknesses in internal controls over financial reporting.

39

APPENDIX C Effect of audit adjustments on internal control audit opinions

Appendix C tests the effect of audit adjustments on internal control audit opinions. Cols. (1) to (4) are estimated using binary logit models for companies that are subject to mandatory internal control audits (MICA = 1). Cols. (1) and (2) are estimated without controlling for company fixed effects. Cols. (3) and (4) are estimated after controlling for company fixed effects. The sample size is reduced in Cols. (3) and (4) because the fixed effects specification drops any company that has no variation in the dependent variable (ICMOD) during the sample period. All variables are defined in Appendix A. ***, ** and * denote significance at the 1%, 5% and 10% levels (two-tailed), respectively. Dependent variable = ICMOD (1) (2) (3) (4) Coeff. Coeff. Coeff. Coeff. (z-stat.) (z-stat.) (z-stat.) (z-stat.)

LnADJMAG 1.274 *** 3.861 *** (3.99) (2.83) ABNADJ 1.212 *** 3.861 *** (3.11) (2.83) LnTA -0.318 *** -0.337 *** 0.478 0.456 (-2.80) (-3.00) (0.93) (0.89) LEV 1.884 *** 1.914 *** 1.485 1.598 (2.98) (2.99) (0.81) (0.87) ROA -7.210 *** -7.773 *** -4.585 * -6.316 ** (-3.53) (-3.70) (-1.92) (-2.51) LnSUBS -0.067 -0.066 -0.617 -0.579 (-0.43) (-0.43) (-1.18) (-1.11) SOE -0.461 * -0.499 ** 2.457 * 2.370 * (-1.88) (-2.00) (1.91) (1.86) BIG10 -0.077 -0.060 0.473 0.533 (-0.32) (-0.25) (0.52) (0.58) TENURE -0.004 -0.002 -0.003 0.007 (-0.24) (-0.10) (-0.03) (0.08) Year fixed effects? Yes Yes Yes Yes Industry fixed effects? Yes Yes - - Company fixed effects? No No Yes Yes Observations 3,418 3,418 235 235 Unique companies 1,308 1,308 79 79 Observations with ICMOD = 1 133 133 95 95 Model Chi2 174.5 *** 169.5 *** 33.7 *** 33.7 *** Pseudo R2 0.171 0.167 0.198 0.198

40

APPENDIX D Modified internal control opinions and next-period auditor switching

Appendix D tests the impact of modified internal control audit opinions on next-period auditor switching. Col. (1) is estimated without controlling for company fixed effects. Col. (2) is estimated after controlling for company fixed effects. The sample size is reduced in Col. (2) because the fixed effects specification drops any company that has no variation in the dependent variable (AUDCHt+1) during the sample period. All variables are defined in Appendix A. ***, ** and * denote significance at the 1%, 5% and 10% levels (two-tailed), respectively. Dependent variable = AUDCHt+1 (1) (2) Coeff. Coeff. (z-stat.) (z-stat.)

MICA_MODt 0.710 *** 0.957 *** (3.00) (2.90) MICA_CLEANt -0.004 0.284 * (-0.03) (1.94) LnTAt -0.120 *** -0.293 *** (-4.13) (-3.48) LEVt 0.360 ** 0.012 (2.36) (0.04) ROAt -3.332 *** -2.256 *** (-6.05) (-3.40) LnSUBSt -0.008 -0.189 * (-0.21) (-1.94) SOEt 0.386 *** -0.076 (5.33) (-0.35) NONMB -0.147 (-1.49) BIG10t -0.237 *** -0.608 *** (-3.65) (-5.67) TENUREt -0.034 *** 0.441 *** (-4.83) (21.12) Year fixed effects? Yes Yes Industry fixed effects? Yes - Company fixed effects? No Yes Observations 15,238 6,322 Unique companies 2,478 946 Observations with AUDCHt+1 = 1 1,208 1,204 Model Chi2 381.7 *** 946.4 *** Pseudo R2 0.041 0.235 Chi2 Chi2 Testing MICA_MODt = MICA_CLEANt 9.49 *** 4.49* *

41

APPENDIX E Mandatory internal control audits and audit fees

Appendix E tests the impact of mandatory internal control audits on fees. All variables are defined in Appendix A. ***, **, and * denote significance at the 1%, 5%, and 10% levels (two-tailed), respectively. (1) (2) (3)

Dependent variable = LnAF LnAF LnAF

Coeff. Coeff. Coeff. (t-stat.) (t-stat.) (t-stat.)

MICA 0.237 *** (19.73) MICA_FIRST 0.249 *** (21.71) MICA_LATER 0.226 *** (15.87) MICA_MOD 0.269 *** (8.77) MICA_CLEAN 0.236 *** (19.48) LnTA 0.194 *** 0.194 *** 0.195 *** (13.11) (13.10) (13.09) LEV 0.106 ** 0.104 ** 0.105 ** (2.52) (2.48) (2.52) ROA 0.052 0.049 0.055 (0.71) (0.67) (0.75) LnSUBS 0.066 *** 0.065 *** 0.066 *** (6.23) (6.15) (6.24) SOE 0.012 0.012 0.012 (0.47) (0.47) (0.45) BIG10 0.021 * 0.020 * 0.020 * (1.81) (1.77) (1.79) TENURE -0.002 -0.002 -0.002 (-1.01) (-1.06) (-1.00) Year fixed effects? Yes Yes Yes Company fixed effects? Yes Yes Yes Observations 13,301 13,301 13,301 Unique companies 2,466 2,466 2,466 Model F-stat. 302.8 *** 293.7 *** 285.4 *** Adjusted R2 0.581 0.581 0.581 F-stat. F-stat. Testing MICA_FIRST = MICA_LATER 5.00 ** Testing MICA_MOD = MICA_CLEAN 1.26

42

Table 1 The staggered introduction of mandatory internal control audits in China Panel A: Regulatory requirements Effective years Companies subject to mandatory internal control audits

2011 onwards Cross-listed companies. 2012 onwards State-owned main-board listed companies. 2013 onwards Non-state-owned main-board listed companies whose market value by December

31, 2011 is no less than 5 billion RMB and whose average net income during 2009-2011 is above 30 million RMB.

2014 onwards All remaining main-board listed companies.

Panel B: Companies subject (not subject) to mandatory internal control audits

Year

Number of companies that are subject to mandatory

internal control audits

Number of companies that are not subject to mandatory

internal control audits

Total number of Chinese listed companies in the

CSMAR database

2007 0 1,549 1,549 2008 0 1,624 1,624 2009 0 1,715 1,715 2010 0 2,062 2,062 2011 67 2,272 2,339 2012 852 1,638 2,490 2013 1,031 1,458 2,489 2014 1,414 1,198 2,612 2015 1,447 1,380 2,827 Total 4,811 14,896 19,707

43

Table 2 The sample

Panel A: Sample selection (2007-2015)

Observations CSMAR database. 19,707 Less: Non-integrated audits. (166) Less: Observations with missing data from the Ministry of Finance database. (2,650) Less: Observations with missing data for the control variables. (547) Less: Observations where there are inconsistencies between the CSMAR and Ministry of Finance databases.

(1,106)

Final sample 15,238

Panel B: Distribution by year

Year Observations % of sample

2007 1,334 8.8% 2008 1,431 9.4% 2009 1,548 10.2% 2010 1,877 12.3% 2011 1,753 11.5% 2012 2,001 13.1% 2013 1,845 12.1% 2014 1,521 10.0% 2015 1,928 12.7% Total 15,238 100.0%

44

Table 3 Descriptive statistics. The sample consists of company-year observations from 2007 to 2015 (N = 15,238). The variables are defined in Appendix A. We winsorize the LnADJMAG, LEV, and ROA variables at the 1st and 99th percentiles to mitigate outliers in the raw values of these variables. Mean Min P1 P25 P50 P75 P99 Max

MISSTATE 0.171 0.000 0.000 0.000 0.000 0.000 1.000 1.000 ADJMAG 1.447 0.000 0.000 0.000 0.008 0.061 2.918 9459.292 LnADJMAG 0.078 0.000 0.000 0.000 0.008 0.059 1.356 1.356 MICA 0.224 0.000 0.000 0.000 0.000 0.000 1.000 1.000 LnTA 12.625 1.632 9.614 11.684 12.446 13.344 17.497 21.521 LEV 0.471 0.045 0.045 0.288 0.464 0.636 1.319 1.319 ROA 0.037 -0.247 -0.247 0.013 0.036 0.066 0.219 0.219 LnSUBS 2.166 0.000 0.000 1.609 2.197 2.773 4.554 6.356 SOE 0.460 0.000 0.000 0.000 0.000 1.000 1.000 1.000 NONMB 0.341 0.000 0.000 0.000 0.000 1.000 1.000 1.000 BIG10 0.479 0.000 0.000 0.000 0.000 1.000 1.000 1.000 TENURE 6.401 1.000 1.000 3.000 5.000 9.000 20.000 24.000

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Table 4 Pair-wise correlation matrix

The sample consists of company-year observations from 2007 to 2015 (N = 15,238). The variables are

defined in Appendix A. Correlation coefficients are shown in bold if they are statistically significant

at the 5% level or better (two-tailed).

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

(1) MISSTATE 1.00

(2) LnADJMAG 0.07 1.00

(3) MICA -0.01 -0.07 1.00

(4) LnTA -0.08 -0.14 0.33 1.00

(5) LEV 0.07 0.10 0.16 0.30 1.00

(6) ROA -0.10 -0.21 -0.10 0.04 -0.38 1.00

(7) LnSUBS -0.02 -0.03 0.23 0.49 0.21 0.03 1.00

(8) SOE -0.05 -0.03 0.28 0.29 0.24 -0.11 0.10 1.00

(9) NONMB 0.00 -0.07 -0.38 -0.27 -0.43 0.16 -0.20 -0.47 1.00

(10) BIG10 -0.05 -0.05 0.16 0.22 -0.02 0.02 0.13 0.02 0.06 1.00

(11) TENURE -0.02 0.04 0.24 0.12 0.15 -0.07 0.20 0.18 -0.41 -0.05 1.00

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Table 5 Univariate analyses

Cols. (1) and (2) present the mean values of MISSTATE and LnADJMAG for the pre-MICA period and the post-MICA period of companies that become subject to mandatory internal control audits during the sample period. To maintain comparability between the pre- and post-MICA periods, we require the availability of audit adjustment data in both periods, which reduces the pre-MICA sample from 6,581 to 6,019, and reduces the post-MICA sample from 3,418 to 3,395. Col. (3) presents the mean values of MISSTATE and LnADJMAG for companies that are not required to undergo mandatory internal control audits at any time during the sample period. All variables are defined in Appendix A. *** denotes significance at the 1% level (two-tailed).

(1) (2) (3)

Before the introduction of

mandatory internal control audits

After the introduction of

mandatory internal control audits

Companies that are never required to undergo mandatory

internal control audits during the sample period

(N = 6,019) (N = 3,395) (N = 5,239)

MISSTATE 0.170 0.163 0.173 LnADJMAG 0.103 0.055 0.062 (1) vs. (2) MISSTATE LnADJMAG t-stat. −0.87 −11.71***

47

Table 6 Misstatements and mandatory internal control audits. The misstatement models are estimated using logit because the dependent variable (MISSTATE) is binary. Col. (1) is estimated without controlling for company fixed effects. Col. (2) is estimated after controlling for company fixed effects. The sample size is reduced in Col. (2) because some companies do not have any variation over time in the MISSTATE dependent variable. All variables are defined in Appendix A. ***, **, and * denote significance at the 1%, 5%, and 10% levels (two-tailed), respectively.

(1) (2) Dependent variable = MISSTATE MISSTATE

Coeff. Coeff. (z-stat.) (z-stat.)

MICA -0.046 -0.050 (-0.50) (-0.49) LnTA -0.134 *** 0.104 * (-4.07) (1.70) LEV 0.828 *** -0.011 (5.48) (-0.05) ROA -2.592 *** -1.159 ** (-6.02) (-2.34) LnSUBS 0.047 0.012 (1.14) (0.16) SOE -0.278 *** -0.134 (-3.42) (-0.86) NONMB -0.099 (-0.91) BIG10 -0.192 *** -0.059 (-3.12) (-0.70) TENURE -0.020 *** 0.003 (-2.63) (0.26) Year fixed effects? Yes Yes Industry fixed effects? Yes - Company fixed effects? No Yes Observations 15,238 7,642 Unique companies 2,478 1,152 Observations with MISSTATE = 1 2,612 2,402 Model Chi2 266.9 *** 83.1 *** Pseudo R2 0.034 0.014

48

Table 7 Audit adjustments and mandatory internal control audits This table presents fixed effects models of audit adjustments. Col. (1) is estimated with the MICA variable, whereas Col. (2) is estimated without the MICA variable. The results in Col. (2) are used to construct the ABNADJ and ABNADJDECR variables. All variables are defined in Appendix A. ***, **, and * denote significance at the 1%, 5%, and 10% levels (two-tailed), respectively.

(1) (2) Dependent variable = LnADJMAG LnADJMAG

Coeff. Coeff. (t-stat.) (t-stat.)

MICA H1 (-) -0.018 *** (-2.98) LnTA -0.005 -0.006 (-0.88) (-0.93) LEV 0.026 0.029 (1.23) (1.37) ROA -0.450 *** -0.448 *** (-7.87) (-7.85) LnSUBS 0.008 * 0.010 ** (1.68) (1.99) SOE -0.022 -0.023 (-1.56) (-1.58) BIG10 0.015 ** 0.016 *** (2.49) (2.66) TENURE 0.002 *** 0.003 *** (2.85) (3.09) Year fixed effects? Yes Yes Company fixed effects? Yes Yes Observations 15,238 15,238 Unique companies 2,478 2,478 Model F-stat. 13.5 *** 13.6 *** Adjusted R2 0.038 0.037

49

Table 8 Misstatements and mandatory internal control audits - the interaction effect of abnormal reductions in audit adjustments following the introduction of mandatory internal control audits. Panel A presents the univariate difference-in-differences results for companies that become subject to mandatory internal control audits during the sample period. Panel B presents logit regression results, where Cols. (1) and (2) are estimated without controlling for company fixed effects, and Col. (3) is estimated with company fixed effects. Col. (1) is estimated using the full sample, whereas Cols. (2) and (3) are estimated using the sub-sample of companies that become subject to mandatory internal control audits during the sample period. The sample size is reduced in Col. (3) because some companies do not have any variation over time in the MISSTATE dependent variable. All variables are defined in Appendix A. ***, **, and * denote significance at the 1%, 5%, and 10% levels (two-tailed), respectively. Panel A: Univariate analysis

(1) (2) (1) vs. (2) Companies that experience a

large abnormal reduction in audit adjustments after the introduction of mandatory

internal control audits (ABNADJDECR_H = 1)

Companies that do not experience a large abnormal

reduction in audit adjustments after the

introduction of mandatory internal control audits (ABNADJDECR_H = 0)

Before the introduction of mandatory internal control audits (MICA = 0; the pre-period) (N = 1,607) (N = 4,412) MISSTATE 0.200 0.160 After the introduction of mandatory internal control audits (MICA = 1; the post-period) (N = 809) (N = 2,586) MISSTATE 0.252 0.136

Difference (t-stat.)

Difference (t-stat.) Difference in differences

Pre- vs. Post-period 0.052 (2.84***) −0.024 (−2.74***) 0.076 (4.08***)

50

Panel B: Regression results

(1) (2) (3) Dependent variable: MISSTATE MISSTATE MISSTATE

Coeff. Coeff. Coeff. (z-stat.) (z-stat.) (z-stat.)

MICA × ABNADJDECR H2 (+) 2.550 *** 2.378 *** 2.625 *** (4.29) (4.02) (4.39) MICA H3 (-) -0.214 ** -0.400 *** -0.420 *** (-2.17) (-3.13) (-2.75) ABNADJDECR 0.138 0.299 (0.29) (0.62) LnTA -0.120 *** -0.131 *** 0.090 (-3.63) (-3.35) (1.30) LEV 0.815 *** 0.701 *** 0.034 (5.42) (3.83) (0.13) ROA -2.509 *** -1.659 *** -1.039 * (-5.84) (-3.46) (-1.77) LnSUBS 0.048 0.026 0.026 (1.18) (0.50) (0.29) SOE -0.289 *** -0.316 *** -0.048 (-3.53) (-3.35) (-0.28) NONMB -0.092 0.629 (-0.82) (1.18) BIG10 -0.188 *** -0.174 ** 0.005 (-3.06) (-2.09) (0.05) TENURE -0.020 *** -0.019 ** 0.010 (-2.66) (-2.29) (0.82) Year fixed effects? Yes Yes Yes Industry fixed effects? Yes Yes - Company fixed effects? No No Yes Observations 15,238 9,414 5,026 Unique companies 2,478 1,300 676 Observations with MISSTATE = 1 2,612 1,581 1,485 Model Chi2 315.9 *** 214.5 *** 67.0 *** Pseudo R2 0.037 0.043 0.018

51

Table 9 Misstatements and the timing of mandatory internal control audits. The misstatement models are estimated using logit because the dependent variable (MISSTATE) is binary. Cols. (1) and (2) are estimated without controlling for company fixed effects, and Col. (3) is estimated with company fixed effects. Col. (1) is estimated using the full sample, whereas Cols. (2) and (3) are estimated using the sub-sample of companies that become subject to mandatory internal control audits during the sample period. The sample size is reduced for the fixed effects model in Col. (3) because some companies do not have any variation over time in the MISSTATE dependent variable. Control variables are the same as those used in Table 8 but are untabulated for the sake of brevity. All variables are defined in Appendix A. ***, **, and * denote significance at the 1%, 5%, and 10% levels (two-tailed), respectively.

(1) (2) (3)

Dependent variable: MISSTATE MISSTATE MISSTATE

Coeff. Coeff. Coeff. (z-stat.) (z-stat.) (z-stat.) MICA_FIRST -0.283 ** -0.374 *** -0.447 *** (-2.45) (-2.87) (-2.72) MICA_FIRST × ABNADJDECR 2.941 *** 2.770 *** 3.287 *** (4.09) (3.83) (3.72) MICA_LATER -0.172 -0.488 *** -0.456 ** (-1.48) (-2.90) (-2.35) MICA_LATER × ABNADJDECR 2.371 *** 2.184 *** 2.315 *** (3.42) (3.18) (3.47) ABNADJDECR 0.137 0.302 (0.29) (0.63) Control variables? Yes Yes Yes Year fixed effects? Yes Yes Yes Industry fixed effects? Yes Yes - Company fixed effects? No No Yes Observations 15,238 9,414 5,026 Unique companies 2,478 1,300 676 Observations with MISSTATE = 1 2,612 1,581 1,485 Observations with MICA_FIRST = 1 1,052 1,046 560 Observations with MICA_LATER = 1 2,366 2,349 1,225 Model Chi2 316.5 *** 217.5 *** 68.3 *** Pseudo R2 0.037 0.043 0.018 Chi2 Chi2 Chi2 Testing MICA_FIRST × ABNADJDECR =

MICA_LATER × ABNADJDECR 0.52 0.56 1.05

Testing MICA_FIRST = MICA_LATER 0.83 0.63 0.00