Voluntary Disclosure of Auditor’s Attestation on Internal Control:

Evidence from China

Fang LouQian Sun

Rong YangHongqi Yuan

Motivation• Many studies on IC disclosure– Market reactions to the disclosure of IC weaknesses

(Mammersley et al. 2008; Zhang 2007)– Impact of IC disclosure on the cost of capital (Ashbaugh-

Skaife et al. 2007; Beneish et al. 2008)– Risk factors associated with presence of IC problems (Ge

and Mcvay 2005; Doyle et al. 2007)

• Not many on the incentives for IC disclosure– Mandatory vs. voluntary IC disclosure– Two exceptions: Bronson et al. (2006) and Deumes and

Knechel (2008) address voluntary IC disclosure– Identification problem

Our Contributions• We examine not only why firms would choose

voluntarily to disclose their IC self-assessment reports, but also why some of these firms prefer, in addition, to have an auditor’s attestation on these reports– We use the voluntary disclosure data from SSE during

2006-2010– The uniqueness of the data– We put forward the equity capital refinancing hypothesis– We can address the identification problem to a certain

extent

Theoretical Framework

• Healy and Palepu (2001)– The main purpose for voluntary disclosure of IC

reports is to reduce information asymmetry and agency costs

– Similarly, we argue having an auditor’s attestation on the IC report can make it more convincing, and thus further reduce information asymmetry and agency costs

– Costs and benefits of IC disclosure and the associated auditor’s attestation

The determinants for IC disclosure

• Bronson et al. (2006) and Deumes and Knechel (2008):– Size– Leverage– Institutional Ownership– Growth– ROE – Alternative governance mechanism

Our Hypotheses• H1a: Ceteris paribus, firms controlled by the government

are more likely to issue IC self-assessment reports and to attain an auditor’s attestation.

• H1b: Ceteris paribus, firms controlled by the central government are more likely to issue IC self-assessment reports and to attain an auditor’s attestation than those controlled by local governments.

• H2: Ceteris paribus, firms having more mutual fund shareholdings are more likely to disclose self-assessment on IC and to have an auditor’s attestation.

Our Hypotheses

• H3a: Ceteris paribus, firms having equity-refinancing intentions are more likely to issue IC self -assessment reports and to have an auditor’s attestation on the IC report.

• H3b: When planning to have equity-refinancing in the market, non-government-controlled firms are more likely to issue IC self-assessment reports and to have an auditor’s attestation on the IC report than government-controlled firms.

Research Design• Since there are a few possible choices for a firm’s

disclosure decision over time, we use three pooled Logit regression models to test our hypotheses regarding Chinese firms’ voluntary disclosure of IC self-assessment reports and attaining an auditor’s attestation. The baseline model is specified as follow:

• Logit (ICVDit) = a0 + α1 SEOit + α2FUNDit +α3GOVit + α4CENTRAL* GOVit + a5SEOit* GOVit + a6SIZEit + α7 GROWit + α8ROEit + α9 LEVit + α10 INDIRit + α11CLISTit + α12BIG4it + α13 INVit + α14AGEit + α15IndMBR + YRDummies + εit (1)

Research Design• In Model 1, we set ICVDit to 1 if firm i discloses its IC

self-assessment report at year t no matter whether there is an auditor’s attestation attained or not, and zero otherwise. This is to examine the likelihood to disclose IC self-assessment versus not to disclose.

• In Model 2, we first exclude all firms that do not disclose an IC self-assessment report in year t, then set ICVDit to 1 if firm i attains an auditor’s attestation to its IC self-assessment report, and zero otherwise. This is to examine the likelihood to attain an auditor’s attestation among disclosers.

Research Design• In Model 3, we define a Multinomial Logit variable, MLogit

(ICVDit). Instead of being binary, it is categorized into three groups: ICVD0 represents firms with no IC self-assessment report at all, which serves as the benchmark; ICVD1 represents firms with an IC self-assessment report only; and ICVD2 represents firms with both an IC self-assessment report and an auditor’s attestation.

• Since ICVD0 is used as the benchmark, we replace ICVD with ICVD1 and set it equal to 1 if firm i is in the category of ICVD1 in year t, and zero otherwise. Similarly, we replace ICVD with ICVD2 and set it equal to 1 if firm i is in the category of ICVD2 in year t, and zero otherwise.

Research Design• The dependent variable, Logit(ICVDit), measures

the likelihood of firm i having ICVD1 and ICVD2 in year t. Hence, there are two simultaneously estimated equations in the Multinomial Logit regression model:

• one examines whether a firm discloses its IC self-assessment report only without attaining an auditor’s attestation

• the other examines whether a firm has both a self-assessment disclosure and an auditor’s attestation

Table 1 Sample Distribution

Panel A: Frequency of the whole sample

Year 

Firms with no disclosure

Firms with disclosure on self-assessment, but no

auditor’s attestation

Firms with both self-assessment reports and

auditors’ reports Total number of observations

2006748 10 37 795

       

2007648 8 129 785

       

2008473 161 159 793

       

2009468 168 175 811

       

2010459 160 191 810

       

Total2,796 507 691 3,994

       

Panel B: Distribution of firms with IC weaknesses during 2009 and 2010

Year  

(1)  Number of firms with IC

weakness

(2)(1) As a

percentage of total

number of firms

  

(3)Firms with IC

weakness and self-assessment

disclosure, but no auditor’s attestation

(4) (3) As a percent of total

number of firms that disclose both self-

assessment and auditor’s attestation

(5) Number of firms with IC weakness, but that

disclose both self-assessment and auditor’s

attestation

(6)(5) As a percent of total

number of firms that disclose both self-

assessment and auditor’s attestation

2009 53 6.72 7 4.12 7 3.93

2010 100

 12.41

 25 

15.52 

12 

6.06 

Total or Average153

 9.57

 32 

9.82 

19 

5.00 

Variable Name Description

ICVD =

ICVD in Model 1 is set 1 if a firm discloses the IC self-assessment report, and zero otherwise. In Model 2 all non-disclosures are deleted. Then ICVD is set to 1 if a firm attains an auditor’s attestation on the IC self-assessment report, and zero otherwise. ICVD in Model 3 is categorized into three groups: ICVD0 represents firms with no IC self-assessment report at all, which serves as the benchmark; ICVD1 represents firms with only an IC self-assessment report; and ICVD2 represents firms with both an IC self-assessment report and the auditor’s attestation. Since ICVD0 is used as the benchmark, we replace ICVD with ICVD1 and set it equal to 1 if the firm is in the category of ICVD1, and zero otherwise. Similarly, we replace ICVD with ICVD2 and set it equal to 1 if the firm is in the category of ICVD2.

SEO= 

A dummy variable, which is equal to 1 if a firm makes seasoned equity offerings in the next fiscal year, and zero otherwise.

FUND= 

The number of tradable shares held by mutual-fund institutions among the ten largest shareholders, divided by total tradable shares at the end of year t.

GOV= 

A dummy variable, which is equal to 1 if the largest shareholder is the government (including both central government and local governments), and zero otherwise.

CENTRAL= 

A dummy variable, which is equal to 1 if the largest shareholder is the central government, and zero otherwise. 

SIZE= The natural logarithm of total assets at the end of year t.

GROW= The change in operating revenue from year t-1 to year t divided by operating revenue at year t-1.

ROE= Return on equity for year t.

LEV=  Total liability divided by total assets.

INDIR=  The ratio of the number of independent outside directors to total number of directors.

CLIST=

A dummy variable, which is equal to 1 if a firm’s shares are cross-listed in the US in addition to SSE, and zero otherwise.

BIG 4=

 A dummy variable, which is equal to 1 if a firm’s auditor is one of the big four accounting firms, and zero otherwise. 

INV= Book value of inventory divided by total assets.

AGE= A firm’s age is measured as the number of years since it was listed on the SSE.

IndustryMBR= The median of market-to-book ratio for each industry.

Table 2 Description of Variables

  Mean Q1 MEDIAN Q3 Std. Dev.

SEO 0.106 0 0 0 0.308

FUND 0.030 0 0.006 0.044 0.047

GOV 0.668 0 1 1 0.471

CENTRAL 0.172 0 0 0 0.377

SIZEa 3,231 1,362 2,709 6,474 3,666

GROW 0.338 -0.017 0.139 0.326 3.047

ROE 0.066 0.025 0.072 0.128 2.607

LEV 0.602 0.397 0.541 0.672 1.161

INDIR 0.359 0.333 0.333 0.375 0.050

CLIST 0.013 0 0 0 0.111

BIG4 0.070 0 0 0 0.255

INV 0.177 0.062 0.138 0.237 0.161

AGE 9.349 6 9 13 4.023

IndustryMBR 3.227 1.958 3.114 4.330 1.356

Table 3 Descriptive Statistics for Independent VariablesPanel A: Descriptive statistics for full sample during the period of 2006-10

Panel B: Descriptive statistics of test variables for firms with IC weakness during the period of 2009-10

  Firms with IC weakness  

(n=153)Mean Median

Firms with IC weakness, but which disclose self-assessment (no

auditor’s attestation)(n=321)

Mean Median

Firms with IC weakness, but which disclose both self-assessment and

auditor’s attestation(n=19)

Mean Median

SEO 0.072 0 0.059 0 0.157 0

FUND 0.032 0.004 0.053 0.021 0.051 0.018

GOV 0.653 1 0.667 1 0.789 1

CENTRAL 0.183 0 0.294 0 0.421 0

a SIZE in Table 2 (both panels A and B) is the total assets (in million RMB) at year-end.

  SEO FUND GOV

CEN-TRAL SIZE GROW ROE LEV INDIR CLIST BIG4 INV AGE

SEO                          

FUND 0.10                        

GOV -0.01 0.01                      

CENTRAL 0.02 0.01 0.32                    

SIZE 0.05 0.17 0.29 0.22                  

GROW -0.003 0.03 -0.002 -0.02 0.02                

ROE -0.01 0.02 0.01 0.03 0.01 0.003              

LEV -0.001 -0.05 -0.07 -0.02 -0.15 -0.01 0.001            

INDIR 0.002 0.03 -0.04 0.03 0.06 0.003 -0.01 -0.001          

CLIST -0.01 -0.04 0.08 0.18 0.29 -0.004 0.001 -0.01 0.02        

BIG4 0.002 -0.02 0.13 0.15 0.45 0.01 0.005 -0.02 0.09 0.34      

INV -0.01 0.03 -0.08 -0.06 0.02 0.09 -0.001 -0.01 0.04 -0.06 -0.10    

AGE -0.07 -0.06 -0.01 -0.11 -0.05 -0.01 0.002 0.07 0.005 -0.05 -0.08 0.06  

IndustryMBR -0.04 0.13 -0.03 -0.01 -0.04 0.03 -0.003 -0.01 0.02 -0.01 -0.03 0.01 0.09

Table 4 Pearson Correlation Matrix

This presents the Pearson correlation coefficients between all independent variables defined in Table 2.

The bold number represents that two-tailed p-value is significant at the 10% level or better.

Table 5 Multinomial Regression Results for 2006-2010  Separate logistic Regressions Multinomial logistic regressions (Model 3)

  Model 1  Discloser versus non-disclosers

Model 2Self-assessment report only

versusSelf-assessment report with

auditor’s attestation

(1) Self-assessment report

only versus non-disclosers(ICVD1)

(2) Self-assessment report with auditor’s attestation versus

non-disclosers(ICVD2)

(3) Diff

Between (1) & (2)

Chi-squared

SEO 0.75*** 0.54 0.28 1.05***  

  (3.40) (1.52) (0.90) (4.29) 5.33**

FUND 4.63*** 5.12*** 1.80 5.94***  

  (3.84) (2.67) (1.12) (4.29) 5.58**

GOV 0.22 0.47* -0.05 0.42**  

  (1.45) (1.91) (-0.24) (2.10) 3.54*

GOV*CENTRL 0.41** 0.93*** -0.22 0.69***  

  (2.25) (3.60) (-0.85) (3.53) 11.69***

GOV*SEO -0.35 -0.50 0.14 -0.66**  

  (-1.28) (-1.16) (0.36) (-2.19) 3.85**

SIZE 0.55*** -0.03 0.62*** 0.53***  

  (8.57) (-0.36) (7.29) (7.17)  

GROW 0.01 0.08 -0.16 0.01  

  (0.26) (0.88) (-1.64) (0.74)  

ROE -0.01 0.14 -0.01 -0.01  

  (-0.55) (0.72) (-0.48) (-0.44)  

LEV -1.49*** 0.37 -1.72*** -1.32***  

  (-4.27) (0.68) (-3.52) (-3.33)  

INDIR 0.71 1.23 0.01 1.44  

  (0.61) (0.78) (0.01) (1.00)  

CLIST 1.36** 0.37 1.42** 1.75**  

  (2.11) (0.47) (1.97) 2.43)  

BIG4 0.19 -1.95*** 1.01*** -0.75**  

  (0.82) (-5.14) (3.41) (-2.38)  

INV 0.90** -0.06 0.86* 0.90**  

  (2.53) (-0.09) (1.82) (2.01)  

AGE -0.07*** -0.11*** -0.01 -0.11***  

  (-4.21) (-4.20) (-0.77) (-5.48)  

Industry MBR 0.03 0.08 -0.33 0.04  

  (0.37) (0.68) (-0.31) (0.80)  

           

# of Obs. 3,994 1,198 3,994    

Pseudo R2 23.26% 17.67% 21.99%    

  Separate logistic Regressions Multinomial logistic regressions (Model 3)  Model 1

 Discloser versus non-disclosers

Model 2 Self-assessment report only

versusSelf-assessment report with

auditor’s attestation

(1)Self-assessment report only

versus non-disclosers(ICVD1)

(2) Self-assessment report with auditor’s

attestation versusnon-disclosers

(ICVD2)

(3)Diff

Between (1) & (2)Chi-square

SEO 0.41 0.39 0.11 0.68**  

  (1.47) (0.86) (0.29) (2.09) 1.73

FUND 3.61** 6.47*** 0.16 6.26***  

  (2.22) (2.77) (0.08) (3.32) 8.23***

GOV 0.21 0.42 -0.12 0.43*  

  (1.15) (1.58) (-0.05) (1.89) 2.78*

GOV*CENTRL 0.30 1.03*** -0.29 0.67***  

  (1.38) (3.64) (-0.97) (2.83) 11.16**

GOV*SEO -0.24 -0.58 0.21 -0.62  

  (-0.67) (-1.06) (0.44) (-1.49) 2.42

SIZE 0.67*** -0.05 0.71*** 0.65***  

  (8.25) (-0.50) (7.33) (7.14)  

GROW -0.11* 0.11 -0.21 -0.08  

  (-1.76) (0.99) (-0.44) (-1.59)  

ROE -0.01 0.57 -0.22 0.02  

  (-0.24) (1.43) (-0.65) (0.48)  

LEV -1.80*** 0.82 -2.13*** -1.43***  

  (-4.06) (1.33) (-3.90) (-2.81)  

INDIR 0.57 0.51 0.33 1.02  

  (0.42) (0.31) (0.22) (0.62)  

CLIST 16.02*** 0.34 14.92*** 15.27***  

  (28.46) (0.46) (23.86) (24.06)  

BIG4 0.35 -1.77*** 0.93** -0.71  

  (1.02) (-4.11) (2.65) (-1.62)  

INV 0.98** -0.15 1.00* 0.95*  

  (2.24) (-0.22) (1.88) (1.74)  

AGE -0.07*** -0.12*** -0.02 -0.13***  

  (-3.61) (-4.31) (-0.83) (-5.42)  

Industry MBR -0.03 0.11 -0.07 0.01  

  (-0.34) (0.91) (-0.71) (0.11)  

           

# of Obs. 1,621 694 1,621    

Pseudo R2 17.28% 11.96% 15.47%    

Table 6 Multinomial Regressions Results for 2009-2010

  Separate logistic Regressions Multinomial logistic regressions (Model 3)

  Model 1 Discloser versus

non-disclosers

Model 2Self-assessment report only

versusSelf-assessment report with

auditor’s attestation

(1) Self-assessment report only

versus non-disclosers(ICVD1)

(2) Self-assessment report with auditor’s

attestation versusnon-disclosers

(ICVD2)

(3)Diff

Between (1) & (2)Chi-square

SEO -14.86*** 0.07 -16.72*** -14.54***  

  (-15.82) (0.08) (-14.62) (10.77) 2.68

FUND 10.97** -4.12 14.73*** 11.40  

  (2.21) (-0.49) (2.86) (1.60) 0.31

GOV -0.81 1.07 -0.85 0.10  

  (-1.35) (0.71) (-1.47) (0.08) 0.58

GOV*CENTRL 0.77 1.16 0.68 1.39  

  (1.17) (0.93) (1.00) (1.57) 0.61

GOV*SEO 14.91***   -0.36 15.31***  

  (12.32)   (-0.24) (10.61) 128.26***

SIZE 1.01*** 0.16 0.87*** 0.97**  

  (3.23) (0.35) (2.64) (2.57)  

GROW -0.67* 0.31 -0.82* -0.98**  

  (-1.65) (0.52) (-1.87) (-2.08)  

ROE 1.27 -2.53 2.27 1.80  

  (0.67) (-0.61) (0.87) (0.45)  

LEV -0.25 2.68 -0.67 -1.78  

  (-0.18) (0.64) (-0.46) (-0.66)  

INDIR -5.14 -2.94 -2.62 0.28  

  (-1.02) (-0.29) (-0.51) (0.03)  

CLIST 13.58*** -0.01 15.66*** 13.27***  

  (7.82) (-0.01) (8.23) (4.65)  

BIG4 1.15 -17.56*** 0.24 -16.51***  

  (1.06) (-9.27) (0.02) (-7.80)  

INV 1.11 -0.73 0.66 2.02  

  (0.81) (-0.17) (0.48) (0.74)  

AGE -0.22*** -0.39*** -0.12 -0.45***  

  (-2.91) (-2.99) (-1.62) (-3.61)  

Industry MBR 0.17 -0.20 -0.11 -0.34  

  (0.69) (-0.33) (-0.34) (-0.68)  

# of Obs. 153 51 153    

Pseudo R2 30.50% 33.91% 32.20%    

Table 7 Multinomial Regressions Results for Firms with IC Weaknesses (2009-10)

Robustness Check• Use SEO scale in place of SEO dummy• Poor credibility as an incentive to have an

audit attestation on IC report– Previous penalty by CSRC or SSE– Non-clean auditor opinion

• Lead-lag relationship between Fund and Disclosure

Conclusion• We hypothesize and find supporting evidence

that a firm with the government, especially the central government, as its largest shareholder, with more mutual fund shareholdings, and with an equity refinancing plan in the near future, is more likely to disclose an IC self-assessment report and to attain an auditor’s attestation on the report.

• We have also addressed the identification issue to a certain extent.