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Abstract

This research endeavors to investigate the impact of audit firm size on audit quality in Vietnam- a developing country with the expectation of improving audit quality to eliminate financial statement fraud that has been increasing in recent years. Using data from 762 companies listed on HOSE and HNX from 2016 to 2019 and audit quality is proxied by discretionary accruals, this research uses the panel data regression method with POLS, FEM, and REM and then select the appropriate model. The results reveal that discretionary accruals in companies audited by Big4 are lower than in non-Big4 companies. This research significantly contributes to the academic literature on audit quality policies by offering valuable insights into three key aspects. Firstly, it sheds light on the relationship between audit firm size and audit quality within the Vietnamese context, enriching the ongoing scholarly debate with specific empirical evidence. Secondly, the study provides essential evidence to aid government policymakers in formulating relevant policies concerning the approval conditions for audits of public interest entities. Lastly, the research advances the global discussion on audit quality by offering valuable insights that can inform regulatory authorities and policymakers worldwide. In sum, this research paper presents a comprehensive and scholarly approach to proposing policies aimed at enhancing audit quality, making a multifaceted contribution to the field’s ongoing discussions and debates.

Keywords

audit firm size audit quality discretionary accruals earnings management

Introduction

Independent and competent auditors should examine an enterprise’s financial statements to ensure they are reasonably free of material misstatement and to assist users in decision-making (Salehi et al., 2019). To achieve this purpose, the audit needs to be high quality (Tran et al., 2023). The accounting scandals of the early 21st century, starting with Enron and WorldCom, then Parmalat in Europe and many other countries, have raised public concerns about audit quality. Starting from the role of the audit and the reality of the above financial scandals, the topic of audit quality has been a concern for the professionals, authorities, and academic research.

In Vietnam, independent audit activities appeared in 1991 with only two auditing firms, however, until 2018 onwards, there has been a significant increase in the number of auditing firms, which reached over 180 auditing firms, primarily based on small audit firms and micro audit firms. To ensure the audit quality, Decree 84/2016/ND-CP sets out the conditions for auditing listed companies, including conditions related to audit firm size such as capital, number of auditors, and number of audit reports issued. The revision of Circular 183/2013/TT-BTC marks a significant departure from its predecessor, introducing amendments aimed at both streamlining the operations of auditing firms and imposing more stringent criteria for auditors engaged in public company audits. Notable adjustments include a reduction in the maximum allowable number of clients per auditing firm, from 300 to 250, and an extension of the timeframe for client number determination from 9 to 12 months. Furthermore, the updated regulations noticed that auditors must be listed on the audit practice registry and possess a minimum of 24 months of practical audit experience within the Vietnamese jurisdiction. These heightened audit prerequisites have sparked considerable discourse and prompted a pertinent inquiry into whether augmenting the size requirements for auditing firms correlates with an enhancement in audit quality. This inquiry underscores the complexity of the relationship between audit firm dimensions, auditor qualifications, and the efficacy of auditing practices, necessitating further empirical investigation and scholarly analysis to elucidate the nuanced dynamics at play and provide valuable insights for policymakers and regulatory bodies in refining audit oversight frameworks.

In the literature review perspectives, the results of previous studies on the impact of audit firm size on audit quality are not similar; some studies show that the audit firm size has a positive effect on audit quality (Adeniyi & Mieseigha, 2013; Ahmad et al., 2016; Cordoş et al., 2020; Choi et al., 2010; Harris & Williams, 2020; Hegazy et al., 2020; Mokoaleli-Mokoteli & Iatridis, 2017; Rahman et al., 2020). In contrast, the studies of Nichols and Smith (1983), Lam and Chang (1994), Petroni and Beasley (1996), Kim et al. (2003), Jeong and Rho (2004), Othman and Zeghal (2006), Tsipouridou and Spathis (2012), Azibi and Rajhi (2013); did not find evidence of the effect of audit firm size on audit quality. Research by James and Izien (2014) showed a negative influence of size on audit quality. In Vietnam, there are a few studies of the factors affecting audit quality through an exploratory factor analysis model, in which the main factors are: the company characteristics, the size, and the audit fees (Hoang & Phung, 2019; Nguyen et al., 2023; Nguyen & Kend, 2019; Pham et al., 2017). Until now, there has been no research in Vietnam specifically on the effect of the audit firm size on audit quality using secondary data, where discretionary accruals measure quality.

This study posits that examining the relationship between audit firm size and audit quality in an emerging economy like Vietnam, which is essential for developing appropriate regulations and policies aimed at improving audit quality. Accordingly, this study has two primary objectives: (a) To compared the value of discretionary accruals between companies audited by the audit firm with different sizes; (b) To analysis the impact of audit firm size on audit quality. The main contribution of this research is to find empirical evidence in Vietnam on the influence of audit firm size on audit quality. With a positive correlation between audit firm size and audit quality, the results of this study showed that companies audited by Big4 have lower levels of discretionary accruals than other companies. This research has provided compelling evidence underscoring the necessity for government agencies to promulgate regulations and policies of audit firm size, such as capital, number of auditors, and number of audit reports, to enhance audit quality. From this result, we provide policy implications not only for Vietnam SMEs on improving audit quality but also for the Vietnam government to implement regulations and policies to improve the quality and capacity of auditors, support audit firms, especially small audit firm.

The main contents of this research are divided into four key parts. Firstly, the literature review discusses state regulations and synthesis, analyzes previous studies related to firm size and audit quality, and proposes a research hypothesis. Next, the research methodology outlines the methods used, providing a detailed description of the research sample and the techniques for measuring variables within the model. The research results section then presents the analyzed information metrics and key discoveries. Finally, the conclusion summarizes the significant findings, proposes relevant policies, and suggests areas for future research.

Literature review and Hypothesis Development

Audit Firm Size

Firm size is considered a set of indicators related to the condition and characteristics of a business. Typically, for ease of management, state agencies classify enterprise size based on industry, capital, revenue, and workforce. Based on this framework, Arens et al. (2012) and Colbert and Murray (1998) identified firm size through total revenue, number of partners, number of professional staff, and number of offices. Firm size can also be measured by the value of assets or total revenue (Ali et al., 2020; Yasar, 2013; Yousaf et al., 2019). In the field of auditing, some authors argue that the size of an audit firm can also be measured by its reputation. Following this perspective, El Guindy and Trabelsi (2020), Ernstberger et al. (2020), Salehi et al. (2019), Sawan and Alsaqqa (2013), Suryani et al. (2023), Yasar (2013), and Wang et al. (2014) categorized audit firm size into Big 4/Big 5/Big 6 and Non-Big 4. This research classified audit firm size according to the reputation of the audit firm (Big 4 and Non-Big 4).

Audit Quality

Audit quality is not directly observable like other services (DeAngelo, 1981), so different approaches must be used. Quality can be directly assessed through inputs, processes, and outputs (DeFond & Zhang, 2014) or indirectly through the quality of financial statements, profit management, and misstatement. The results of some previous studies show that audit quality will reduce the level of earnings management (Becker et al., 1998; Francis et al., 1999). Earnings management is usually determined based on discretionary accruals, and the audit firm size is often considered whether the accounting firm is a Big4 or not. Big4 are often considered large-size audit firms in terms of revenue, number of auditors, and capital.

Agency Theory

Shapiro (2005) in her study on agency theory argued that this theory originated from economic theory, was formed in the 70s, then was widely used by scholars in many fields such as accounting, economics, finance,… (Eisenhardt, 1989). Agency theory is concerned with solving problems that may arise in agency relationships. Jensen and Meckling (1976) argued that an agency relationship is a contract under which one or more persons (the principals) hire another person (the agent) to perform some services on their behalf and due to the separation between ownership and control rights of managers in joint-stock companies, there is a conflict of interest between these two subjects. The manager is the person who runs the company - holds more information of the company than the shareholders - so it may be in self-interest, will provide information in a way that benefits them so that they can receive more wages and rewards (Fields et al., 2001). One way to protect the investors is to get an audit from a qualified, independent auditor (Pham et al., 2023). However, audit firms are also profit companies, that may accept customers even though they are not qualified in order to increase revenue and the audit firms may sacrifice audit quality (Lennox & Wu, 2018). If the audit firm does not have enough human and other resources, the audit quality will not be achieved as expected (Lin et al., 2014).

Audit Firm Size and Audit Quality

The connection between the size of an audit firm and the quality of its audits remains an area of active investigation within the auditing profession. Academic researchers have examined this relationship from multiple perspectives. From one standpoint, scholars have demonstrated that there is a meaningful correlation between the size of an audit firm and the caliber of its auditing services. Research by Moizer (1997) concluded that for entities who change their audit firm from Big5 to non-Big5, the capital market reacted negatively immediately and vice versa. Also, the author concluded that large audit firms have more power (higher quality). Becker et al. (1998) examined the relationship between audit quality and earnings management and confirmed that companies that were not audited by Big6 companies often have a higher level of earnings management. The authors’ results are consistent with the notion that larger audit firms, such as those in the Big6 at the time, could provide higher quality audits that constrain earnings management to a greater degree than smaller audit firms. Steveny and Vanstraelen (2006) examined the effect of audit firm size on earnings management (through discretionary accruals) of listed companies in France, Germany and the UK. That research results showed that companies’ earnings management levels in the studied countries were not similar, and the quality audit would reduce earnings management. Several authors such as Adeniyi and Mieseigha (2013), Choi et al. (2010), Davidson and Neu (1993), argued that large audit firms provide better quality because (a) large audit firms are more independent than small firms due to the separation of audit and non-audit services, and (b) more than one customer influences the revenue of the audit firm, so it is less dependent on the customer, (c) the large audit firm has stronger resources and the ability to serve customers. Large audit firms increase the probability of detecting errors more than small audits (d) large audits are very reputable, so they don’t trade off quality for benefits. Moreover, the research of Cameran et al. (2015) showed that companies audited by Big4 have lower earnings management through discretionary accruals. Many previous studies have measured the audit firm size on the criterion of Big4 or non-Big4 audit firms, such as research from Ahmad et al. (2016) in Indonesia, Mokoaleli-Mokoteli and Iatridis (2017) in South Africa, Rahman et al. (2020) in Malaysia, Abid et al. (2018) in Pakistan both showed that the company audited by Big 4 have lower discretionary accruals compare with non-big 4 audit firms.

High-quality audits ensure compliance with regulatory standards and improve stakeholder confidence, thereby facilitating economic decisions and maintaining market integrity (Tiron-Tudor et al., 2018). The larger size audit firms allow them to conduct more thorough and rigorous audits, which can lead to higher audit quality. Additionally, the reputation and brand name of large audit firms provide an incentive to maintain high quality, as a loss of reputation could be very costly. Regulatory oversight and inspection processes also tend to be more stringent for larger audit firms (Hegazy et al., 2020). As Cordoş et al. (2020) highlighted, robust audit practices not only increase accountability and detect irregularities but also foster investor trust and efficient resource allocation in the economy. Therefore, the ongoing enhancement of auditing standards is vital for the effectiveness of corporate governance and financial reporting systems. Consistently, audit firm size has proved to have a positive impact on audit quality, as larger firms are better equipped to ensure the availability, competence, and focus of audit professionals (Harris & Williams, 2020). For research in Vietnam, based on a sample of 192 manufacturing companies from the period 2006 to 2014, a study by Pham et al. (2017) found that Big 4 audit firms provide higher audit quality compared to Non-Big 4 firms. Nevertheless, several other studies conducted by Nguyen and Kend (2019) and Nguyen et al. (2023) revealed that there are still business risks for foreign companies operating in Vietnam, especially when non-Big 4 audit firms are involved in the audit function, as in some cases, the independence of auditors is most likely to be compromised.

Contrary to the results of the above studies, a few studies did not find evidence of the effect of size on audit quality. The reason is that in countries where the risk of litigation is low, oversight functions and penalties for auditors are low, which will not promote a high-quality audit. Thus, auditors may not restrict the earnings management of client firms, then Big4 firms may not necessarily provide higher quality than non-Big4 audit firms. Louis (2004) examined the relationship between audit quality and audit size; the research results showed that large audit firms do not always provide better quality services than small ones. According to Jeong and Rho (2004), it is examined whether Big6 provides higher quality than non-Big6 in Korea, where institutional incentives did not motivate auditors to provide higher audit quality. The research results showed no difference in audit quality between Big6 and non-Big6. Studies in countries such as France, Belgium, Greece, and Tehran have shown that there were no significant differences in earnings management between Big4 and non-Big4 firms (Bauwhede & Willekens, 2004; Moradi et al., 2011; Othman & Zeghal, 2006; Tsipouridou & Spathis, 2012). Similarly, Big4 firms in Turkey did not reduce their discretionary accruals compared with non-Big4 firms in developed countries (Yasar, 2013). Research of Sari et al. (2019) showed that both Big and Non-big 4 audit firms focused on improving quality to attract customers. Audit firm size has no significant impact on the audit quality, showing that Non-big 4 audit firms have made significant progress in improving the quality of their service delivery. In other words, the size of the audit firm is no longer considered the main consideration when deciding to choose an audit firm. Similarly, Nasuci et al. (2020) concluded that there was no statistically significant relationship between audit firms’ size and audit quality. Research by James and Izien (2014) showed that the results of audit firm size negatively affect audit quality. According to James and Izien (2014), it is believed that: (a) Small audit firms provide high-quality audit services to maintain their clients due to their small number of clients; (b) The number of customers is small, so there are better conditions to perform the audit so that the quality will be higher.

However, the results of studies examining the influence of audit firm size on audit quality have been inconsistent. Some research has shown a positive impact of audit firm size on audit quality. Conversely, other studies have found that audit firm size either does not affect or negatively affects audit quality. Additionally, some research has indicated that audit firm size does not influence audit quality in countries with low litigation risk. Regarding studies conducted in Vietnam, although previous research by Nguyen and Kend (2019), Nguyen et al. (2023), and Pham et al. (2017) have demonstrated a positive relationship between audit firm size and audit quality, with the explanation being a lack of compliance with standards and a compromise of auditor independence in small auditing firms, the results of these studies have only been validated through multiple regression models (Pham et al., 2017) or expert interviews (Nguyen & Kend, 2019) and surveys of auditors’ perceptions (Nguyen et al., 2023). Therefore, there is still a lack of research using secondary data and panel data regression to increase the reliability of the relationship between audit firm size and audit quality. In Vietnam, following the Law on Enterprises, in Article 138 (paragraph 1), the General Meeting of Shareholders has the right to approve an independent auditing company based on the list proposed by the Board of Directors. Based on the above arguments, practice in Vietnam shows that companies with poor corporate governance and lack of independence will tend to choose small audit firms to expect to reduce the adjustment of financial statements and vice versa. Based on Vietnam’s regulations on auditing conditions for entities with the public interest as well as an overview of previous studies, the hypothesis is put forward as follows:

H1: Audit firm size positively affects audit quality

Research Methodology

Research Models

Audit quality is difficult to measure directly (DeFond & Zhang, 2014), so it is often measured through many indirect ways. Audit quality can be measured through various representative variables such as discretionary accruals, going-concern modified audit opinions (Carey & Simnett, 2006), firms just beating or missing earnings benchmarks, and accounting restatements (Garcia-Blandon et al., 2020). In our study, audit quality was measured through discretionary accruals.

Based on the results of previous research (Abid et al., 2018; Ahmad et al., 2016) on the influence of audit firm size on audit quality, this study designed a research model (1) to test the effect of companies listed on the Vietnam stock market:

$\begin{matrix} DACDit = α + β 1 BIGit + β 2 OPINIONit + β 3 SIZEit \\ + β 4 AGEit + β 5 LEVit + β 6 PERFORMit \\ + β 7 CFFOit + β 8 GROWTHit + Firm - fixed effects \end{matrix}$ (1)

Research model (1) includes the dependent variable, which is audit quality as measured through absolute values of discretionary accruals (DACD) determined according to the adjusted Dechow et al. (1995) as shown in the equation (2). This research performs the following regression for each industry each year and requires at least five observations for each regression.

$\begin{matrix} \frac{DAC D_{t}}{A_{t - 1}} = \frac{T A_{t}}{A_{t - 1}} - a_{1} * (\frac{1}{A_{t - 1}}) - a_{2} * (\frac{Δ RE V_{t} - Δ RE C_{t}}{A_{t - 1}}) \\ - a_{3} * (\frac{PP E_{t}}{A_{t - 1}}) \end{matrix}$ (2)

In there: At-1: Total assets at the end of year t-1; TAt: Total accrual income (Net income excluding other income - operating cash flow); ΔREVt: Change in net sales in year t; ΔRECt: Change in accounts receivable in year t; PPEt : Original cost of tangible fixed assets in year t; a1, a2, a3: estimated parameters = OLS of a1, a2, a3 in the model: TAt/At-1 = a1/At-1 + a2(ΔREVt - ΔRECt)/At-1 + a3PPEt/At-1 +εt.

This research also estimates discretionary accruals according to the Jones model (Jones, 1991) (DACJ) and the model of Kothari et al. (2005) (DACK). In primary regression, we present the results with DACD estimated by the model of Dechow et al. (1995). In the sensitivity test, we present the results with DACJ estimated by Jones’ model 1991 and DACK estimated by Kothari et al.’s model 2005.

Discretionary accruals (DACJ) are estimated according to the Jones model 1991 as follows:

$\frac{DAC J_{t}}{A_{t - 1}} = \frac{T A_{t}}{A_{t - 1}} - a_{1} * (\frac{1}{A_{t - 1}}) - a_{2} * (\frac{Δ RE V_{t}}{A_{t - 1}}) - a_{3} * (\frac{PP E_{t}}{A_{t - 1}})$ (3)

The discretionary accruals (DACK) are estimated according to the model Kothari et al. (2005) as follows:

$\begin{matrix} \frac{DAC K_{t}}{A_{t - 1}} = \frac{T A_{t}}{A_{t - 1}} - a_{1} * (\frac{1}{A_{t - 1}}) - a_{2} * (\frac{Δ RE V_{t} - Δ RE C_{t}}{A_{t - 1}}) \\ - a_{3} * (\frac{PP E_{t}}{A_{t - 1}}) - a 4 * RO A_{t - 1} \end{matrix}$ (4)

Where ROAt-1: Return on assets of year t-1.

The independent variables are the size of the audit firm (BIG) is measured by 1 if the firm is Big4 and = 0 other cases (Abid et al., 2018; Becker et al., 1998; Francis et al., 1999).

In addition, this study also includes control variables in the model based on previous research results, including:

- Variable OPINION: Qualitative variable, expressing audit opinion, measured by 1 if the client company receives a qualified opinion and = 0 other cases. The OPINION variable is based on Carey and Simnett (2006), Garcia-Blandon and Argiles-Bosch (2017), Garcia-Blandon et al. (2020). According to Carey and Simnett (2006), firms generally accept audit opinions as they provide an independent and credible assessment of their financial statements, which enhances transparency and investor confidence. However, they tend to avoid higher discretionary accruals, which are adjustments to earnings based on management’s judgment, because these accruals can be perceived as manipulative and may raise concerns about earnings quality and financial integrity. Therefore, this research expects the variable OPINION to have a positive effect on audit quality.

- Variable SIZE: Quantitative variable, representing the size of customers, measured by Logarithm of total assets at the end of the year. The SIZE variable is based on research by Abid et al. (2018), Carey and Simnett (2006), Rahman et al. (2020). Larger companies tend to be less involved in managing earnings through discretionary accruals than smaller companies. We expect the variable SIZE to have a positive effect on audit quality.

- Variable AGE: Quantitative variable, representing the age of customers, measured by Logarithm of the number of years the company is listed. The AGE variable is based on the study of Carey and Simnett (2006), Myers et al. (2003). Firm age influences audit quality as older firms have better-established controls, experienced reporting, and history with audit processes, leading to reliable financial statements and effective auditor communication. Younger firms, with evolving systems and less audit experience, may face challenges that compromise audit quality. Thus, the maturity and stability of a firm’s operations over time enhance audit outcomes.

- Variable LEV: Quantitative variable, representing the leverage of customers, calculated as liabilities over total assets. The LEV variable is based on research by Abid et al. (2018), Ahmad et al. (2016). Firms with more debt are likely to be more involved in income management to avoid violating debt covenants. We expect the variable LEV to have a negative effect on audit quality.

- Variable PERFORM: Quantitative variable, showing the performance of the company, calculated by profit after tax on total assets at the end of the year. The PERFORM variable is based on the study of Rahman et al. (2020). The management of income through discretionary accruals may be affected by the company’s operating performance. We expect the variable PERFORM to have a negative effect on audit quality.

- Variable CFFO: Quantitative variable, showing net cash flow from operating activities, calculated as net cash flow from operating activities over total assets at the end of the year. The CFFO variable is based on the study of Abid et al. (2018). Net cash flow from operating activities is inversely correlated with discretionary accruals. We expect the variable CFFO to have a positive effect on audit quality.

- Variable GROWTH: Quantitative variable, representing the growth of customers, calculated as net sales at the end of the year minus net sales at the beginning of the year over net sales at the beginning of the year. The GROWTH variable is based on the study of Rahman et al. (2020). We expect the variable GROWTH to have a positive effect on audit quality. It can be explained that firms focused on customer growth rates tend to avoid discretionary accruals to maintain credibility and support sustainable expansion.

- AFE variable: The quantitative variable, which represents the financial expertise of the Audit Committee, is calculated as the ratio of members of the Audit Committee with financial and accounting expertise to the total number of members of the Audit Committee. Variable AFE is based on research by Ghafran and O’Sullivan (2017), Ha (2022). This research expects the AFE variable to have a positive impact on audit quality.

- IND variable: The quantitative variable, which represents the independence of the audit committee, is calculated as the ratio of members of the independent non-executive audit committee to the total number of members of the audit committee. Variable IND is based on research by Ghafran and O’Sullivan (2017), Ha (2022), Khudhair et al. (2019). This research expects the IND variable to have a positive impact on audit quality.

- In equation (1), this research also uses the company-specific fixed effect to control for variables that are invariant over time. The method to measure the variables in the model is summarized in Table A1.

Research Sample

Research data is collected from the financial statements, annual reports, management reports, websites of listed companies, and website cafef.vn. The preliminary sample includes 762 companies listed on the Ho Chi Minh Stock Exchange and the Hanoi Stock Exchange with a total of 2,934 observations between 2016 and 2019. Excluding observations related to credit institutions and observations with insufficient data, the final sample consisted of 362 listed companies, corresponding to 1,448 observations.

Research Results

Descriptive Statistics and Correlations

Table 1 below presents descriptive statistics of the variables in the research model. The DACD has mean 0.15, lowest 0.000 and highest 0.9. This means that the average accruals (profit adjusted) is 0.15, the lowest profit adjustment is 0.00 and the highest is 0.9; BIG has an average value of 0.27, the lowest is 0 and the highest is 1. This means that the average Big four audit firm ratio is 27%; OPINION has a mean value of 0.04, which means that the average percentage of the auditor opinion that is a modified opinion is 4%; SIZE has an average value of 27.12, the lowest is 23.44 and the highest is 31.77. This means that the average logarithm of total assets at the end of the year is 27.12, the logarithm of the lowest total assets at the end of the year is 23.44 and the highest is 31.77; AGE has an average value of 2.17, the highest is 2.9. This means that the average logarithm of the number of years the company listed is 2.17, the logarithm of the highest number of years the company listed is 2.9; LEV has an average value of 0.46, the lowest is 0.01 and the highest is 0.97. This means that the average debt-to-assets ratio is 0.46, the lowest ratio is 0.01. and the highest is 0.97; PERFORM has an average value of 0.07, the lowest is −0.3 and the highest is 0.6. This means that the ratio of profit after tax to total assets at the end of the year is 0.07, the lowest is −0.3 and the highest is 0.6; OCF has an average value of 0.07, the lowest is −0.45 and the highest is 0.69. This means that the ratio of net operating cash flow to total assets at the end of the year on average is 0.07, the lowest ratio is −0.45 and the highest is 0.69; GROWTH has an average value of 0.14, the lowest is −0.89 and the highest is 7.82. This means the average net sales growth is 0.14, the lowest growth is −0.89 and the highest is 7.82. The AFE has a mean value of 0.68, the lowest is 0.33 and the highest is 1. This means that the ratio of members of the Audit Committee with financial and accounting expertise to the total number of members of the Audit Committee averages 0.68, the lowest is 0.33 and the highest is 1. IND has a mean value of 0.52, the lowest is 0.25 and the highest is 1. This means that the average non-executive independent audit committee membership ratio is 0.68, with the lowest being 0.25 and the highest being 1.

Table 1.

Descriptive Statistics.

Variable	Obs	M	SD	Min	Max
DACD	1,448	0.153	0.127	000	0.9
BIG	1,448	0.267	0.442	0	1
OPINION	1,448	0.040	0.196	0	1
SIZE	1,448	27.118	1.426	23.440	31.768
AGE	1,448	2.166	0.348	0	2.944
LEV	1,448	0.462	0.221	0.012	0.966
PERFORM	1,448	0.069	0.079	−0.297	0.600
CFFO	1,448	0.070	0.126	−0.446	0.691
GROWTH	1,448	0.143	0.670	−0.893	7.820
AFE	1,448	0.675	0.130	0.333	1
IND	1,448	0.522	0.136	0.25	1

Table 2 presents descriptive statistics on the absolute value of discretionary accruals (DACD) according to the audit firm size, including the mean value of the DACD for the group of audit firm as Big4 (BIG4) and the mean value of the DACD for those not Big4 (NONBIG4). The results show that there is a difference in discretionary accruals between companies audited by the Big4 and non-Big4 firms. The t-test (Table A2) also shows the difference in discretionary accruals between these two groups. The companies audited by Big4 companies had an average of 0.1077 accruals, the other group was 0.1724.

Table 2.

Descriptive Statistics of DACD by the Scale of Audit Firm.

Variable	Obs	M	SD	Min	Max
DAC (BIG4)	387	0.100	0.073	0.000	0.247
DAC (NONBIG4)	1061	0.172	0.137	0.014	0.9

Source. Authors’ compilation based on analysis.

The Pearson correlation of chosen variables is shown in Table 3. The findings indicate a negative correlation between BIG and DACD, giving early evidence of a positive link between audit firm size and audit quality. OPINION, LEV, FFO, and GROWTH and IND are inversely connected with DACD, whereas LEV, AFE and PERFORM are favorably correlated with DACD, as shown in Table 3. Furthermore, the majority of correlation coefficients among the independent variables are minor, and the variance inflation factors (VIF) vary from 1.01 to 1.54, showing that multicollinearity is not an issue in this research.

Table 3.

Pearson Correlations.

Variables	(1)	(2)	(3)	(4)	(5)	(6)	(7)	(8)	(9)	(10)	(11)	VIF
(1) DACD	1.000
(2) BIG	−0.249*	1.000										1.18
(3) OPINION	−0.205*	0.171*	1.000									1.04
(4) SIZE	−0.026	0.346*	−0.001	1.000								1.30
(5) AGE	−0.034	0.037	0.044	0.068*	1.000							1.01
(6) LEV	0.048	0.082*	0.017	0.310*	0.006	1.000						1.39
(7) PERFORM	0.074*	−0.021	−0.066*	0.009	−0.023	−0.421*	1.000					1.54
(8) CFFO	−0.290*	0.047	0.024	−0.014	0.018	−0.217*	0.434*	1.000				1.26
(9) GROWTH	−0.083*	−0.003	−0.020	0.020	−0.021	−0.016	0.158*	−0.031	1.000			1.04
(10) AFE	0.109*	−0.144*	−0.156*	0.028	0.015	0.002	0.054*	0.017	−0.003	1.000		1.05
(11) IND	−0.116*	0.072*	0.050	0.041	−0.001	−0.007	−0.020	−0.001	−0.040	−0.058*	1.000	1.01

Source. Authors’ compilation based on analysis.

Shows significance at the .05 level.

Baseline Regression Results

With panel data, we estimate equation (1) with POLS, FEM, and REM and then select the appropriate model. F-test is performed to choose between POLS and FEM estimates with the hypothesis H0: The appropriate model is POLS. The results (Table A3) show that Prob > F = 0.000 < significance level α = .01, so H0 is rejected and the conclusion is that the FEM model is more appropriate than POLS (Wooldridge, 2010). The Hausman test is performed to choose between FEM and REM estimates. The Hausman test results (Table A3) show that Prob>chi2 = 0.000 is less than 0.01, so the hypothesis H0: there is no correlation between the explanatory variables and the random components, which means H1 is accepted and the conclusion is that the FEM model is selected (Wooldridge, 2010). To handle the phenomenon of heteroscedasticity in FEM, the FEM model with Cluster - Robust estimation is appropriate. The results show that BIG has β1 = −.086 and is statistically significant (P>|t| = .000). This shows that audit firm size has a negative effect on the discretionary accruals (DACD) or audit firm size has a positive effect on the audit quality. Turning to control variables including OPINION (Coef. = −0.06, P>|t| = .000), AGE (Coef. = −0.05, P>|t| = .03), CFFO (Coef. = −0.49, P>|t| = .000, IND (Coef. = −0.039, P>|t| = .047) has a positive influence on audit quality. PERFORM (Coef. = 0.34, P>|t| = .05) has a negative influence on audit quality. Our findings are consistent with existing studies that the larger the scale of the audit, the higher increases in both capital standards, number of auditors, experience, and number of reports issued, which lead to higher audit quality (Abid et al., 2018; Ahmad et al., 2016; Alsmairat et al., 2019; Ayu et al., 2019; Mokoaleli-Mokoteli & Iatridis, 2017; Salehi et al., 2019; Sawan & Alsaqqa, 2013). This result is the basis for us to propose recommendations to help the authorities in Vietnam to improve audit quality.

Cross-sectional Tests - CEO-chairperson Duality

This section examines whether CEO-chairperson duality (CEO also serves as board chair) influences the connection between audit firm size and discretionary accruals. When the CEO has the role of chairman of the board of directors, he has considerable influence over the other organization’s directors (Dunn, 2004). Under some circumstances, the board of directors’ capacity to preserve the credibility of the firm’s financial statements, including monitoring the auditors’ work and independence from the company, is more likely to suffer when the CEO has significant influence within the board. Several studies have shown that CEO-chairperson duality affects audit quality (Hudaib & Cooke, 2005; Sarhan et al., 2019). In Vietnam, the provision on the Chairman of the Board of Directors not to concurrently hold the title of Director is implemented after 3 years from the effective date of Decree No. 71/2017/ND-CP. Consequently, we hypothesize that the association between discretionary accruals and audit firm size is more pronounced in companies with a dual CEO-chairperson duality. To test the hypothesis, this study defines an indicator variable whose value is one if the CEO is the chairman and zero otherwise. We analyze the main regression using subsamples of companies with CEO-chairperson duality (CEO = 1) and companies without CEO-chairperson duality (CEO = 0). According to Table 4, the coefficient on BIG for the subsample with CEO-chairperson duality is not significantly different from the coefficient for the subsample without CEO-chairperson duality (column 2). Moreover, the coefficient on BIG is negative and statistically significant in columns 1 and 2. Overall, the result does not support our hypothesis that the association between audit firm size and discretionary accruals is stronger in companies with a dual CEO-chairperson structure. Overall, this section’s data implies that weak corporate governance does not mediate the connection between audit firm size and discretionary accruals.

Table 4.

Cross-sectional Tests - CEO-chairperson Duality.

	CEO = 1	CEO = 0
Variables	[1]	[2]
BIG	−0.081***	−0.085***
OPINION	−0.064***	−0.069***
SIZE	0.054	−0.013
AGE	−0.051	−0.057***
LEV	−0.057	−0.009
PERFORM	0.143	0.276
CFFO	−0.407***	−0.504***
GROWTH	−0.009	−0.006
AFE	0.039	0.031
IND	−0.065	−0.029
_cons	−1.127	0.668
F	8.70	36.18
Prob > F	0.000	0.000
Observations	297	1.151
Adjusted R2	0.215	0.377

Source. Authors’ compilation based on analysis.

***

denote statistical significance for p < .01.

Additional Analyses

Propensity score matching: To control for any confounding factors related to both audit firm size and audit quality, researchers used the propensity score matching (PSM) method (Shipman et al., 2017). In the first step, our sample is divided into a treatment group (observations with BIG = 1) and a control group (observations with BIG = 0). Next, a probit regression is conducted between BIG and control variables, including OPINION, SIZE, AGE, LEV, PERFORM, CFFO, AFE, IND, and GROWTH, in order to calculate the chance of having a Big4 business. Using a caliper of 0.001 and no replacement, we match each treatment with one control based on the odd ratios of the Big4 company. A sample size of 682 observations is included in the PSM sample. Following the suggestions of Shipman et al. (2017), we conduct two tests to ensure the reliability of the PSM matching process. In the first stage, we repeat the probit regression using the PSM sample and find that the importance of control variables vanishes in the PSM sample. In the second phase, we run t-tests to determine if the mean changes in company characteristics between treatment and control firms in the PSM sample are statistically significant. The main regression is then repeated using the PSM sample. We then rerun the primary regression using the PSM sample. Table 5 reports the findings of equation (1) using the PSM sample. This research reports results for the DACD main dependency variable in column [1], the DACJ replacement dependent variable in column [2], and the DACK replacement dependent variable in column [3]. Overall, the evidence is consistent with our baseline results.

Table 5.

Propensity Score Matching.

	DACD	DACJ	DACK
Variables	[1]	[2]	[3]
BIG	−0.065***	−0.070***	−0.065***
OPINION	−0.097*	−0.102	−0.096
SIZE	0.002	0.001	0.001
AGE	−0.025*	−0.026	−0.025
LEV	−0.054	−0.055	−0.055
PERFORM	0.140**	0.152*	0.138
CFFO	−0.204**	−0.221*	−0.209*
GROWTH	−0.003	−0.004	−0.003
AFE	0.059	0.061	0.058
IND	−0.072	−0.072	−0.074
_cons	0.207	0.230	0.213
F	18.30	18.19	18.20
Prob>F	0.000	0.000	0.000
R-squared	0.218	0.213	0.214

Source. Authors’ compilation based on analysis.

, **, and *** denote statistical significance for p < .1, p < .05, and p < .01.

Positive and negative abnormal accruals: Our data indicate a negative correlation between audit firm size and discretionary accruals in Table 6. The data indicate that income decline when a company is a Big 4. This supplementary test examines how corporations use income-increasing accruals (positive values of discretionary accruals) and income-decreasing accruals (negative values of discretionary accruals). Table 7 displays the results of equation (1), where the dependent variable is the positive values of DACD (column 1) or the absolute values of negative DACD values (column 2). In column 1, the coefficient on BIG is negative and statistically significant (coef. = −0.056 and P>|t| = .000). The evidence suggests that when the firm is Big4, the levels of income-increasing discretionary accruals decrease. In contrast, with a significance level of 10%, in column 2, the coefficient on BIG is positive and statistically significant (coef. = 0.029 and P>|t| = .069). This evidence suggests that when the company is Big4, the level of discretionary accruals that reduce earnings increases.

Table 6.

FEM Model Results With Cluster – Robust.

	Dependent variable
Variables	DACD
BIG	−0.081*** (−7.47)
OPINION	−0.062*** (−4.70)
SIZE	−0.009 (−0.36)
AGE	−0.045** (−2.13)
LEV	0.025 (0.29)
PERFORM	0.347** (1.89)
CFFO	−0.492*** (−10.60)
GROWTH	−0.001 (−0.19)
AFE	0.030 (1.61)
IND	−0.039** (−1.98)
_cons	0.521 (0.80)
Firm-fixed effects	Yes
F	38.33
Prob>F	0.000
Observations	1,448
R-squared	0.3288
	FEM with Cluster - Robust

Source. Authors’ compilation based on analysis.

Figures in parentheses are t-statistics.

and *** denote statistical significance for p < .05, and p < .01.

Table 7.

Regressions With Positive and Negative Abnormal Accruals.

	Positive DACD	Negative DACD
Variables	[1]	[2]
BIG	−0.056***	0.029*
OPINION	−0.085***	−0.049
SIZE	−0.006	−0.004**
AGE	−0.010*	0.003
LEV	−0.034	0.007
PERFORM	0.517***	0.488**
CFFO	−0.563***	−0.422***
GROWTH	−0.005	−0.023***
AFE	0.042*	0.071*
IND	−0.090***	−0.025
_cons	0.067	−0.060**
F	48.58	12.8
Prob > F	0.000	0.000
Observations	1179	269
Adjusted R2	0.293	0.331

Source. Authors’ compilation based on analysis.

, **, and *** denote statistical significance for p < .1, p < .05, and p < .01.

- Alternative measurements discretionary accruals:

In the primary tests, this research used discretionary accruals (DACD) estimated by Dechow et al.’s (1995) model. In this test, this research runs regressions with anomalous accruals calculated according to the Jones model (Jones, 1991) (DACJ) and the model of Kothari et al. (2005) (DACK). As reported in Table 8, this research shows that audit firm size is positively associated with alternative measurements of discretionary accruals. The relationships were all statistically significant at 5%. Overall, the findings are insensitive to measurement options.

Table 8.

Regression With Alternative Measurements for Unusual Accruals.

	FEM with cluster - Robust
	DACJ	DACK
Variables	[1]	[2]
BIG	−0.087*** (−7.56)	−0.081*** (−7.44)
OPINION	−0.063*** (−4.51)	−0.060*** (−4.55)
SIZE	−0.007 (−0.28)	−0.009 (−0.36)
AGE	−0.050** (−2.23)	−0.045** (−2.04)
LEV	0.020 (0.24)	0.027 (0.30)
PERFORM	0.368** (1.76)	0.362* (1.79)
CFFO	−0.528*** (−10.66)	−0.492*** (−10.45)
GROWTH	−0.002 (−0.31)	−0.001 (−0.06)
AFE	0.038 (1.47)	0.039 (1.59)
IND	−0.036** (−1.97)	−0.039** (−2.00)
_cons	0.489 (0.73)	0.532 (0.79)
Firm-fixed effects	Yes
F	38.19	37.76
Prob > F	0.000	0.000
R-squared	0.315	0.312
Observations	1448

Source. Authors’ compilation based on analysis.

, **, and *** denote statistical significance for p < .1, p < .05, and p < .01.

Conclusion, Policy Implications, and Limitations of the Study

Our main research objective is to examine the impact of audit firm size on the audit quality of listed companies in Vietnam. Audit quality is measured through discretionary accruals estimated according to the adjusted Jones model of Dechow et al. (1995).

For the first research objectives, this research proved that the discretionary accruals of the companies audited by Big 4 are lower than the remaining companies. This result aligns with (Viana et al., 2022) that the rigorous oversight provided by Big Four auditors can effectively constrain earnings manipulation practices, thereby enhancing the integrity of financial reporting in contexts where such practices are prevalent. It can be anticipated that Big Four audit firms will exercise greater scrutiny over financial reports, particularly in firms that have stronger incentives to engage in earnings management.

This research shows that the size of audit firms have a positive effect on audit quality. The results are aligned with several academic scholars such as Abid et al. (2018), Ahmad et al. (2016), Alsmairat et al. (2019), Ayu et al. (2019), Mokoaleli-Mokoteli and Iatridis (2017), Rahman et al. (2020), Sawan and Alsaqqa (2013), Salehi et al. (2019). It is can be explained that larger audit firms possess significant incentives to enhance and maintain high levels of audit quality. These incentives arise from various factors, including maintain their reputation, mitigate litigation risks, and attract a diverse client base. Research on non-Big Four auditors reveals challenges related to auditor independence and quality. These firms often encounter internal pressures that may lead to compromised compliance with audit reforms, primarily because they operate under less regulatory scrutiny than their larger counterparts (Salehi et al., 2019). Thus, while the Big Four are positioned as leaders in maintaining high audit standards, non-Big Four firms may struggle to achieve similar outcomes due to their inherent limitations in resources and oversight. During the COVID-19 pandemic, smaller audit firms in Vietnam faced significant pressure to reduce their audit fees as a means of retaining clients in a challenging economic environment (Nguyen et al., 2023). Smaller firms typically operate with tighter margins and less flexibility, making it difficult for them to absorb the costs associated with maintaining high-quality audit practices during such economic downturns. In contrast, larger firms, particularly the Big Four audit firms, were able to lower their fees strategically without compromising audit quality (Nguyen et al., 2023). These audit firms possess greater resources, including advanced technology and highly skilled audit experts, which allows them to maintain rigorous audit standards even while adjusting their pricing structures to retain clients. The ability of larger audit firms to adapt their pricing strategies while sustaining quality is indicative of their operational resilience and robust infrastructure. Moreover, the pandemic has underscored the importance of high-quality audits as a mechanism for corporate governance and transparency. As such, the large audit firms’ commitment to maintaining high audit quality not only reinforces their market position but also enhances trust among investors and clients.

In theoretical perspective, our research has provided additional evidence supporting the argument that as the scale of auditing increases, audit quality improves due to standards related to capital, number of auditors, experience, and the volume of issued reports. Although the relationship between audit firm size and audit quality in Vietnam has been previously explored in studies by Nguyen et al. (2023), Pham et al. (2017) and, Nguyen and Kend (2019) earlier research in Vietnam was conducted solely through multiple regression models or surveys of auditors’ perceptions. Therefore, by utilizing panel data regression, this research has significantly contribute to affirming the impact of audit firm size on audit quality in Vietnam, a developing country aiming to enhance audit quality to attract investment. Furthermore, our study was conducted with a total of 2,934 observations between 2016 and 2019, a period during which significant accounting and auditing regulations were enacted and implemented in Vietnam. Thus, our research has addressed potential biases compared to previous studies.

For practical implications, our research results support the government regulation that it must have conditions to audit public interest companies by finding evidence of the difference between discretionary accruals in companies audited by Big4 and not Big4. However, to enhance audit quality, a higher standard is required for audit firms for public interest companies with large market capitalization, banks, and credit institutions. Because these organizations greatly influence society, specifically, it is necessary to enhance further the requirements about the capital, the number of auditors, and the number of issued reports for auditing the above group. The reason is that: if an audit firm with only 10 auditors (belonging to the group of micro companies) has modest human resources, it will be difficult to implement strict quality control. In addition, to audit for the group of companies mentioned above, the auditor needs more experience to measure the accuracy of audit reports. That means the number of issued reports needs to be higher than the prescribed number (200 reports) in the regulations.

From a corporate governance perspective, the research findings can also assist audit firms in determining their development strategies. To achieve higher levels of growth, audit firms need to have adequate capital and high-quality human resources. Hence, audit firms must regularly conduct training and implement policies to retain capable auditors. The research results also impact the maintenance of investor confidence. If investors understand that the companies they invest in are audited by firms with sufficient capital and human resources, it will help strengthen their trust in the financial reports, enabling them to make appropriate investment decisions.

This research has several limitations that should be acknowledged. First, the research sample is limited because there is a lack of listed companies with full data in Vietnam. The availability of data is restricted due to sensitive information, and the data collection is cross-sectional leading to generalized issues. Second, the effect on audit size and audit quality may change over time due to changes in legal requirements, information technology advances, or market conditions. Addressing these limitations and leveraging policy implications can foster a deeper understanding of how audit size affects audit quality, which in turn contributes to ongoing discussions on regulatory reform and enhancing professional practice. Third, several other factors that have not been included in the model significantly affect audit quality, such as audit fees, and level of specialization, because this information is unavailable in public reports.

To further understand the relationship between audit firm size and audit quality, future research should explore alternative measures of audit quality and incorporate additional control variables. First, researchers could utilize other proxies for audit quality beyond the traditional measures, such as auditors’ propensity to issue qualified going concern opinions, the perceived quality of audit reports, the timeliness of error detection, the prevalence of errors in audited financial statements, and the presence of discretionary accruals, accounting restatements, and differences between earnings benchmarks and reported earnings. Second, the relationship between audit firm size and audit quality could be further explored by incorporating control variables related to (1) technological advancements, such as artificial intelligence (AI), data analysis, and blockchain; (2) differences in legal environments and corporate governance structures; (3) client-specific factors, including size, market complexity, industry characteristics, capital, ownership structure; and (4) the impact of regulatory reforms, such as changes in audit firm rotation requirements, mandatory audit firm rotations, or enhanced audit reporting requirements. By pursuing these research directions, scholars can gain a more comprehensive understanding of the factors influencing audit quality, which can inform the development of regulations, professional practices, and academic discourse in the field of auditing.

Footnotes

ORCID iDs

Quoc Thuan Pham

Thi Thao Hien Bui

Funding

The author(s) disclosed receipt of the following financial support for the research,authorship,and/or publication of this article: This research is funded by University of Economics and Law,Vietnam National University Ho Chi Minh City,Vietnam;University of Economics Ho Chi Minh City (UEH),Ho Chi Minh City,Vietnam and University of Finance and Accountancy,Quang Ngai City,Vietnam.

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research,authorship,and/or publication of this article.

Data Availability Statement

Data sharing not applicable to this article as no datasets were generated or analyzed during the current study.

Animals Welfare

This research project does not involve human participants,animals,or any identifiable personal information

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