Association between Earning Management and Audit Quality: Evidence from Chinese Manufacturing Companies

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Abstract

In recent years, it is common that many listed companies utilize earnings management to manipulate the financial statement for the purpose of maximizing private gain. However, excessive earnings management can mislead the public due to materially misstated information provided. The study will examine the relationship between earnings management and audit opinion using OLS regression model. The earning management can be measured by discretionary accruals. Auditors’ size and auditor specialization are the proxies of audit quality. In this research, I assume that the audit quality and earnings management have a negative correlation, and select 6725 observations sample size to make empirical analysis.

1. Introduction

It is common that companies engage in the earning management in context business environment, Following the Healy and Wahlen(1999),earning management occurs when administrators alter the financial report by using their judgments to mislead the stakeholders about the economic performance of the company. Under the situation, auditors play a important role in the earning management.

In Western countries, such as the UK, all companies which have a turnover of 1 million or more are generally required to prepare an annual audit carried out by independent external auditors. However, In China, the main organizations that are required to be audited are as follows: limited liability companies, stock companies, public companies and foreign-invested enterprises. Whatever the size of their sales or assets, these companies are required to be audited. Therefore, we cannot ensure every clients are audited by these auditors who have high audit quality. People also attach more importance to relations between audit quality and earning management.

Previous studies have do some investigations about the association. Beckel et al (1998) assume the clients of Big Six auditors increasing income by discretionary accrual is lower than the clients of Non-Big Six auditors. Finally, through an empirical evidence of econometric model, they find hypothesis is valid. Nevertheless. Tsipouridu and Spathis(2012) draw a different conclusion, finding the size of audit firm does not affect the earning management level and the audit opinion is not relevant o management’s opportunistic behavior.

Based on these analysis of the literatures. In this research, I will make a research about the link between earning management and audit quality, which will take the Chinese manufacturing companies as the evidence. In the progress, Modified Jones model and OLS regression will be used.

By descriptive statistics and multivariate analysis to verify hypothesis.

2. Literature Review

2.1 Earning management

Prior studies have given many definitions of earning management. Healy and Wahlen(1999) define the earning management happens when the manager wants to utilize its right in financial statement and in structuring transactions to interfere and change financial reports so as to misinform some stakeholders about the potential economic performance of the firm or to influence contractual outcomes which depend on the report numbers. Sayari et al(2013) point out “because managers can look over arrangement strategies (for example, GAAP), it is normal to expect that they will pick approaches to argument their own particular utility and/or the market share”. Thus, this shows that it is legal that managers use earning management to achieve some goals for the company in permission scope. Dechow and Skinner(2000) report that it is possible for managers to implement earning management by alterations in shipment schedules, acceleration of sales and delaying of research and development expenses as well as maintenance expense .

According to Healy and Wahlen(1999), the incentives for earning management arise from capital market motivations. contracting motivations and Anti-trust and other regulations. Dechow and Skinner (2000) indicate managers can manipulate cash flow by delaying sales, accelerating research and development expenditure, as well as advertising expenditures. 

Because earning management is difficult to measure, so prior studies contribute to choosing a proxy to represent. Healy(1985) ever detects earning management by using mean total accruals, he thinks earning management occurs in every period, and the mean total accruals in the estimated period can measure the nondiscretionary accruals. DeAngelo’s model(1981) can be treated as a special case of Healy, restricting the estimated period is the last year’s observations. Both models assume the nondiscretionary is constant and ignore it may change with the situation of economics. Jones (1991) puts forward a model that tries to control the effect of economics, and she points nondiscretionary will varies with the  sales growth and plant, property and equipment(PPE),working capital accruals such as inventory and accounts payables changes with sales ,and the calculation of depreciation depends on the value of PPE. Therefore, she regresses that total accruals(ACC) on the change in sales and gross PPE, all variables are scaled by total assets:

ACCt = α + β1jΔREVt + β2PPE t + Єt.

Jones model confirms that a correlation between firm performance and accruals, finding the explanatory power of the model is low.R2 around 12%,the reason for the low R2 is that managers are prudent over the accrual process and cover up their fundamental performance.

In order to improve the power of Jones model, Dechow et al (1995) modifies the Jones model to adjust for growth in credit sales because credit sales can be manipulated, which reflects revenue manipulation better

As opposed to Jones model , Kothari et al (2005) suggest using “performance matched”  discretionary measures. This approach tries to match firm year observation with another firm from the same industry which have the closest level of return on assets(ROA) and deduct control firm’s discretionary accruals from the sample firm to generate performance matched residuals.it can be applied when correlated performance is an important issue.

Dechow and Dichev(2002) proposes a new model based on the relation between accruals and cash flows. It defines the working capital accruals (∆WC) as a function of past, present and future cash flows(CFO) because accruals are related to the future cash collection/payments and previous cash in accruals is received/paid :

∆WC=α + β1CFO t-1 + β2CFOt +β3CFOt+1 +Єt.

The biggest limitation for the model is that it focus on short term accruals and cannot identify long term errors because impairments of PPE and goodwill is important to reflect earning management. Many researchers use the model as a measure of earning management not just detect earning management. For instance, Doyle et al (2007) use this measure to capture “both biased “ discretionary” accruals and unintentionally poorly estimated accruals, which we predict will be the result of an internal control system with weaknesses”. Compared to Jones model, Dechow-Dichev is not widely applied in auditing literature because its limitation..               

2.2 Audit quality

In order to understand what audit quality is, I will adopt some definition in the literature firstly. According to DeAngelo (1981), Audit quality is defined as the market-assessed joint probability that an auditor discovers the misstatements and disclose them. Titman and Trueman (1986) defines audit quality is the accuracy of information supplied by auditors to investors; or represents the auditors’ ability to detect and eliminate misstatements and manipulations in financial statements(Palmrose,1988)

Audit quality is difficult to measure, so some proxies are designed to infer audit quality.In prior researches, DeAngelo (1981) states that audit firm size is relevant to the audit quality. For some big companies with a large number of clients, these audit firms may suffer more loss when they do not discover and report the misstatement in the financial statement because they have a greater investment in reputation capital. Moreover, St. Pierre and Anderson (1984) find a lower incidence of litigation among Big Six auditors compared with non-Big Six auditors because larger accounting firms may be more sensitive to loss than are smaller firms.

In addition to that, auditor specialization can affect the audit quality (Hogan and Jeter, 1999).Industry specialists are identified as the largest supplier in the industry, and the second and third suppliers which can be observed difference easily compared to remaining suppliers. Prior literature has proved that there is a positive relationship between industry specialization and audit quality, indicating industry specialists provide high audit quality than non-specialists. ( Balsam, Krishnan, and Yang, 2003).A proxy for specialization is auditors’ expertise, auditors can get it from the training and practical experience from auditing in the specific industry. (Gramling and Stone, 2001). Balsam et al. (2003) suggest that the expertise will improve when auditors have a large number of clients in an industry, which also leads to higher audit quality. Because it is difficult to observe the expertise directly, so previous study use market share as a proxy. Gramling and Stone (2001) suggest that market shares of auditor firm i is measured as the total audit fees earned by auditor firm I in industry k divided by the total audit fees generated by all the clients in the industry k. In addition to that, some researchers also use the client size or the number of clients as a method to calculate industry market share. However, Minutti-Meza(2013) finds using industry market share to measure the industry specialization is not a reliable indicator of audit quality.

2.3 The link between audit quality and earning management

Auditor size and earning management

Numerous studies suggest big six auditors (now considered as BIG 4 Auditors)provide higher audit quality than non-big six auditors. Beckel et al(1998) compare the discretionary accruals of a sample of firms with non-Big Six auditors to those of a sample of firms with Big Six auditor and conclude that big audit firm is more reliable in reporting the misstatements. DeAngelo(1981) argues audit size is dependent of the audit quality, large audit firms with more clients means the percentage of quasi-rents dependent on any one client is low, auditors will have fewer incentives to behave opportunistically, and more likely to detect and reveal the accounting error. Francis et al (1999) and Krishnan (2003) demonstrate that Big4 auditors are better at constraining client earnings management compared to non-Big4 auditors; they find that clients of non-Big4 auditors have higher levels of discretionary accruals. Moreover, Chen et al (2005) find that Big 4 auditors associate with less earnings management in the firms. However, some studies show an opposite view. Tsipouridu and Spathis (2012) find discretionary accruals are not associated with the size of the audit firm. Moreover, St. Pierre and Anderson (1984) find a lower incidence of litigation among Big Six auditors compared with non-Big Six auditors.

Auditor Industry Specialization and Earnings Management

When it comes to the auditor specialization or expertise, we mention above that good auditor specialization can improve the audit quality.

prior studies find that client firms with industry specialists are associated with higher quality of financial reporting ,thus it illustrates audit specialist can help detect earning management better. Higher quality of audits by

industry specialists is also attributed to the fact that they invest heavily in technologies, physical facilities, personnel, and organizational control systems that enable them to detect irregularities and misrepresentations more easily (Simunic and Stein, 1987),Maletta and Wright(1996) suggest that auditors who have a professional understanding of an industry’s characteristics and operations will audit more effectively than those without industry knowledge. According to Balsam et al (2003) studies, finding that clients audited by industry specialists have lower discretionary accruals and higher earnings response coefficient than clients of non-specialist auditors, suggesting that auditor industry specialization improves earnings quality.

Similarly, PWC( 2002) argue that audit quality depends on numerous

factors including an auditor’s knowledge and understanding of the company being audited and the industry in which it operates. These arguments thus suggest that auditors with industry expertise are more

likely to detect misrepresentations and irregularities than auditors without industry expertise.

In addition to audit size and industry specialization, Tsipouridou and Spathis(2015) research the association between audit opinions and earning management, and divided audit opinion into qualified for the going-concern uncertainty as well as qualified for other reasons. The results suggest the going-concern qualification decision is not related to the level of discretionary accruals

Hypotheses Development

Prior literatures focus on detect the earning management from the firm or auditor’s perspective .In addition, fewer sample selected from Chinese enterprise. In the context of Chinese environment, More and more companies try to control their earnings for maximize companies benefit due to a rapid development in economic. Therefore, I will investigate the companies of Chinese manufacturing industry and identify whether there is a relationship between audit quality and earning management.

Prior studies have proved that using Big 4/non-Big 4 audit variable to capture audit quality differences audit quality. DeAngelo(1981) use the auditor's "reputational bond" to show that larger auditors provide better quality because an inaccurate report may have more to loss in terms of clients and audit fees in case of an audit failure. Besides, audit industry specialization. However, some empirical research documents suggest that audit quality indeed differs across different legal environments. For example, Francis and Wang (2003) report that Big 4 auditors are not equally conservative in different audit environments regarding to constraining earnings management. In Chinese market, Lixian and Nielijie (2006) find the number of Chinese companies hiring the top ten accounting firms for auditing is low, indicating there is a big gap between top ten and Big 4 in terms of the auditing income, the number of employees and the customers. Therefore, as far as the size of the firm is concerned, it cannot achieve the same monopoly position as the foreign big companies. However, in terms of the Chinese market, the top ten accounting firms occupy 20% of the market share with a ratio of 0.22%.(LiXian and Nie Lijie,2006). Therefore, it has research value as a substitution variable of audit quality.

3. Research Methodology

3.1 Data

Selecting manufacturing china listed firms as the research target. There are two reasons for choosing manufacturing industry as the sample. On one hand, manufacturing is a traditional industry for China and national policy have little impact on this industry, thus it can reduce the impact of industrial policies on corporate earnings. On the other hand, selecting the companies which are from same industry can reduce the impact of industry differences to some extent. Based on the two points, the sample selected in this study involves all Chinese manufacturing listed companies of 2359 which are based on CSRC Industry classification 2012 edition in CSMAR.. In order to improve the objectivity and accuracy of results, it will cover 4 years from 2014 to 2017.In order to calculate discretionary accruals, my initial sample is selected in years from 2013 to 2017 yielded 9202 firm-years .After getting DA, I  exclude all the records of the year 2013 and missing value, that reduces the overall sample to 6937 firm-years .From the remaining samples, I calculate required numerical variables. Afterward, I extract the 7313 records for dependent variables. Finally, I merge the two sets of data and get ultimate 6725 records.

3.2 Dependent variable

In order to measure the earning management, discretionary accruals are used to proxy as the dependent variable. The research will apply the modified Jones model to calculate the discretionary accruals.

In modified Jones model, the change in revenue and receivables are involved because changes in total accruals depending on changes in revenue. Property, plant, and equipment is used to control for total accruals because it relates to non-discretionary depreciation expense. Those accruals which cannot be explained by normal operating activities is discretionary accruals. Following that, the model for discretionary accruals is estimated by three steps:

Step 1: Calculate the total accruals as follow:

TACCt= ∆CAt- ∆Cash- ∆CLt+ ∆DCLt- DEPt

(Eq. 1)

Where:

TACCt is total accruals in year t; ∆CAt is change in current assets in year t;

∆Cash is change in cash and cash equivalents in year t; ∆CLt is change in current liabilities in year t; ∆DCLt is change in short term debt included in current liabilities in year t;DEPt is depreciation and amortization expense in year t

Step 2: Estimate the Modified Jones Model, which is defined below:

TACCtAt-1=α11At-1+ α2(∆REVt-∆RECt )At-1 + α3PPEt At-1+εt

(Eq. 2)

Where:

∆RECt is net receivables in year t less net receivables in year t – 1; ∆ REVt is revenues in year t less revenues in year t – 1; PPEt is gross property plant and equipment in year t; At-1 is total assets in year t – 1; α1, α2,α3 are estimated parameters; εt is residuals in year t; other variables are same as the meaning of those in eq.1

 

Step 3: Calculate the discretionary accruals

DACCt=TACCt-NDACCt

(Eq. 3)

NDACCtAt-1=α̂11At-1+ α̂2(∆REVt-∆RECt )At-1 + α̂3PPEt At-1

(Eq. 4)

The non-discretionary accruals can be calculated with the next formula:

3.3 Independent variable

In regard to independent variable,because there is no uniform measure for the construction of audit quality, it is measured using two different measures as follows.

Auditors’ size(TEN10)

Regarding the significance of auditor size, DeAngelo (1981) states that audit firm size is related to audit quality, and large public accounting firms usually supply a high-quality audit. Craswell et al (1995) suggest that the large audit firms generally have brand-name reputation, charge higher audit fees, and/or behave qualitatively than smaller audit firms. These studies suggest that audit quality is likely to be positively related to auditors’ size. so I set auditor size equal 1 if the company audited by TEN10, otherwise, 0.

Auditor Industry specialization

Regarding the Auditor Industry specialization, prior studies has used some proxies to measure . Craswell et al (1995) and Ferguson and Stokes(2002) utilize the ratio of the income of accounting firms to the income of all firms as a proxy for professional auditing, and to measure whether the auditors of the firms have professional auditing qualifications. They believe that a firm have a 10% market share can be treated as industry specialization.Because audit fee can be acquired and therefore I set a dummy variable, 1 if the market share is greater than 10%, otherwise, 0.

Auditor industry market share was defined as the proportion of industry revenue audited by an individual accounting firm relative to the total industry revenue for all companies in that industry audited by all public accounting firms

.MSik=∑j=1JikSALESijk∑i=1Ik∑j=1JikSALESijk

Where:

SALESijk = total sales of client firm j in industry k audit by auditor I.

i=1, 2,..., I = an index for audit firms.

j=1, 2,..., J = an index for client firms.

k=1, 2,..., K = an index for client industry.

Ik = the number of audit firms i in industry k.

Jik = the number of clients served by audit firm i in industry k.

When auditor j’s market share is greater than 10 percent in Industry k, the auditor j is treated as an industry specialist.

3.4 Control variable

The research contains three control variables which help to control discretionary accruals.

Firm size

The effect of firm size on earnings management is controversial (Kouki et al, 2011). Klein (2002) claims that there is a negative relation between firm size and discretionary accruals because large companies has more sophisticated internal control systems and are able to avoid earning management. Myers and Skinner (2000) hold the opposite view because larger companies with more capital market pressure, are more likely to manage earnings than small companies. Therefore, firm size can be used to control the impact to discretionary accruals, which is measured by natural log of firm’s total assets

Leverage

Leverage is used to control for earnings management, as previous studies show that firms with a higher debt to equity percentage are more likely to have an incentive to manipulate earnings management to increase earnings. (Healy and Palepu, 1990).Consistent with Becker et al(1998) Leverage as the ratio of total debt to total assets is related to discretionary accruals(DA)

Operating Cash Flows(OCF)

Consistent with Becker et al (1988),there is a difference in operating cash flows in two sections ,so operating cash flows are included.

Rate of return of asset (ROA)

Kothari etal (2005) found a negative association between earning management and ROA, indicating that the lower the performance of the firm, the higher the possibility for the firms’ incentive to engage in earning management. Thus, ROA is included in this study.

Warfield, Wild, and Wild (1995) indicate that the absolute value of discretionary accruals is a good proxy for earning management.Thus, the research will employ the multi regression model for the test of hypotheses in this study as below:

absDACCt=β01TEN10+β2SPEC+β3LEVERAGE+β4OCF+β5SIZE+β6ROA+e

In which:

DACCt refers to discretionary accruals, as a proxy of earning management;TEN10 is dummy variable,1 if the audit firm is TEN 10,0 otherwise; SIZE is natural log of firm’s total assets. SPEC is auditor industry specialization, dummy variable,1 if market share>10%,ortherwise 0;LEVERAGE is ratio of total debt to total asset; OCF is operating cash flow divided by total assets. ROA is return of asset, which is calculated by dividing the net income by the total assets. e refers to the error term

4. Results and discussion

4.1 Descriptive statistics

In order to characterize the sample, this part will analyse the results by descriptive statistics, which can identify the general nature of data Table 1 shows the summary of descriptive statistics of audit quality and earning management variables. To ensure the relative accuracy of the results,I use the 6697 observations N=6697. From the table, we can acquire some important information:

Absolute discretionary accruals(absDACC) of the Chinese manufactured listed companies ranged between 0-2.4467 the distribution of the values shows that the mean value of absolute discretionary accruals 0.1016, and the standard deviation is 0.3450.

Within the sample, it is found that 56.80 percent of the selected manufacturing companies are audited by Ten 10 firms, and 40.42 percent of the clients are audited by the specialist auditors.

As shown in Table I the mean value of ratio of total debt to total assets

Is 0.6986, illustrating that about 70 percent of total assets of Iranian listed firms are financed by debt, this is consequently suggests that Iranian listed firms operate with high level.

The table shows the mean of log of the firm’s total assets is around 22 and the standard deviation in the variable is 1.185 which is the largest within all the variables.

The range of operating cash flow divided total asset is from -1.9377 to 1.1273. The standard deviation is 0.0819

Descriptive Statistics

 

N

Minimum

Maximum

Mean

Std. Deviation

DACC

6697

-2.2227

2.4467

-.006567

.1724357

absDACC

6697

.0000

2.4467

.101595

.1394781

SPEC

6697

.0000

1.0000

.404211

.4907753

TEN10

6697

.0000

1.0000

.568016

.4953893

LEV

6697

.0131

14.5448

.698630

.6534927

SIZE

6697

17.2770

27.3074

22.064016

1.1847882

ROA

6697

.0045

8.8249

.715680

.5400409

OCF

6697

-1.6863

.6612

.042433

.0769250

Valid N (listwise)

6697

       

Notes: DACC-Discretionary Accruals estimated using Modified-Jones Model; absDACC-absolute Discretionary Accruals TEN10-dummy variable, 1 if the firm is audited by the top 10 Chinese audit firms, 0 otherwise; SPEC-dummy variable, 1 if MS > 10 percent, and 0 otherwise; LEV-ratio of total debt to total assets. SIZE-firm size defined as natural log of firm’s total assets; ROA- net income divided by the total assets. OCF -operating cash flow divided by total assets.

4.2 Multivariate analysis

In this section, multivariate analysis will be used to explore the association between the audit quality proxies and the earning management. According to that, the hypothesis can be accepted or rejected.

Model Summaryb

Model

R

R Square

Adjusted R Square

Std. Error of the Estimate

Durbin-Watson

1

.322a

.104

.103

.1321131

1.873

a. Predictors: (Constant), OCF, TEN10, LEV, ROA, SIZE, SPEC

b. Dependent Variable: absDACC

ANOVAa

Model

Sum of Squares

df

Mean Square

F

Sig.

1

Regression

13.498

6

2.250

128.897

.000b

Residual

116.766

6690

.017

   

Total

130.265

6696

     

a. Dependent Variable: absDACC

b. Predictors: (Constant), OCF, TEN10, LEV, ROA, SIZE, SPEC

Coefficientsa

Model

Unstandardized Coefficients

Standardized Coefficients

t

Sig.

Collinearity Statistics

B

Std. Error

Beta

Tolerance

VIF

1

(Constant)

.613

.031

 

19.911

.000

   

SPEC

-.011

.005

-.037

-2.246

.025

.481

2.079

TEN10

.002

.005

.007

.401

.689

.481

2.077

LEV

.014

.003

.066

5.511

.000

.939

1.064

SIZE

-.025

.001

-.215

-17.823

.000

.920

1.087

ROA

.067

.003

.261

22.168

.000

.966

1.035

OCF

-.168

.021

-.093

-7.885

.000

.971

1.030

a. Dependent Variable: absDACC

5. Conclusion

The objective of this research is to examine the association between audit quality and earning management. In order to test it, I investigate some listed companies from the Chinese manufacturing industry in 2017 and 2018. In this research, I use a sample of 6725 firm-year observations as the basic data. Following the prior studies, discretionary accruals are used to measure the earning management level; Audit size and Auditor Industry specialization as the proxies to measure the audit quality. Based on that, I use the discretionary accruals as the dependent variable and auditors’ size auditor Industry specialization. For constructing the correlation of these variables. In the first step, The modified Jones model is applied to calculate the discretionary accruals. Next, estimating a regression model within these variables regarding the earning management and audit quality.

Once empirical results can be obtained, it will provide a proof for us to decide whether to accept this hypothesis: there is a positive link between audit quality and earning management before testing.

However, there are some limitations in the research. Firstly, this research only focus on one industry . Secondly, some economic factors are not considered, such as inflation. These limitations could be taken into consideration as opportunities for future research .Therefore, I suggest future research can cover these factors that might affect the empirical results

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