Determinants influencing audit delay: The case of Vietnam

 in income before interest and taxes (EBIT). According to 
Mckinnie (2016), leverage ratio is the company's ability to meet its liability. If the company has a high leverage ratio, the risk 
of loss will increase. Therefore, to gain confidence in the company's financial statements, the auditor will increase his prudence 
so that the audit report lag span will be longer. 
Besides, it has been argued that increasing the amount of debt a firm uses, will put pressure on the firm to provide its creditors 
with audited financial reports more quickly (Abdulla, 1996). 
3. Research methodology 
The aim of this research is to investigate the effects of firm size, sign of income, leverage, audit opinion, and auditor firm on 
audit delay for FDI firms in Vietnam. Based on Hair et al. (2006), the sample size is at least 100. We chose our sample consists 
T.T.T. Lai et al. /Accounting 6 (2020) 5
of 142 FDI firms that are convenient to collect data. The data for each of the 142 sample firms were taken from their annual 
reports. 
To better understand how FDI firms respond to the timely reporting requirements, it is necessary to relate their timely reporting 
practices to certain factors. This study investigates some of these factors that are relevant to the socio-economic conditions in 
Vietnam and for which data were available. The factors include the company size (SIZE), the audit firm (AUDITOR), audit 
opinion (OPINION), sign of income (INCOME), and debt to equity ratio (LEVERAGE). Therefore, the hypotheses of this study 
are drawn below: 
H1: Audit delay is a function of a firm size. 
H2: Audit delay is a function of an auditor. 
H3: Audit delay is a function of sign of income. 
H4: Audit delay is a function of audit opinion. 
H5: Audit delay is a function of debt to leverage. 
As in prior studies, we define “audit lag” as the number of days between a company’s financial year-end and the day of the audit 
report. If a firm releases its financial statements within regulatory deadline, then, it cannot be said that the company has delayed 
in releasing its financial statements. Therefore, we describe the number of days that elapses between a company’s financial year-
end and the date of audit report as its audit lag. We computed the audit delay for each company by counting the number of days 
that elapsed between its financial year-end and the date of the audit report. To investigate the influence of the selected factors 
on audit lag in our sample, we estimated the following cross-sectional regression model. Table 1 shows the explanation of the 
explanatory independent variables. 
AUDITLAG = b0 + b1×SIZE + b2×AUDITOR + b3×INCOME + b4×OPINION + b5×LEVERAGE + e 
Table 1 
Definitions of independent variables 
Independent 
Variables 
Explanations 
SIZE Total assets of an entity 
AUDITOR Type of audit firm represented by a dummy variable: “Big 4 audit firms” assigned a 0, otherwise 1. 
INCOME Sign of current year income represented by a dummy variable: firms with “positive net income” 
assigned a 0, otherwise 1. 
OPINION Type of audit opinion represented by a dummy variable: “standard opinion” assigned a 0, otherwise 1. 
LEVERAGE Total debt / Equity 
4. Results and discussion 
Table 2 presents summary statistics of the variables used in this study. As is evident, it takes FDI firms approximately 63 days, 
on average, to report to the public after the end of their financial year. The standard deviation for the AUDITLAG variable is 
13 days, suggesting considerable variability in timely reporting by the firms. It is found that 50.7% of the sample was audited 
by big four audit firms and 76.01% of the firms audit report was standard. 66.2% of the firms report net income for the year 
2017. 
Table 2 
Summary statistics 
Variables Mean Standard Deviation Percentage (*) 
AUDITLAG 62.62 4.305 
SIZE 193.82 142.690 
AUDITOR 50.7 
INCOME 66.2 
OPINION 76.1 
LEVERAGE 34.3449 13.67493 
(*) % of firms whose dummy variable was coded as 0 
Table 3 shows the results from comparison of means between the dichotomous variables. From the table, it can be seen that on 
average, the audit delay increases with the presence of a loss, qualified audit opinion and by small audit firms. As for AUDITOR, 
the mean delay for small audit firms is higher by about 1 day than those for big 4 audit firms with a mean delay of only 62 days. 
 6
Regarding INCOME, firms suffering from losses seem to have a longer mean delay than those gaining a positive net income. 
Firms receiving a qualified audit opinion also seem to take on average of 5 days more than those receiving a clean audit report. 
Table 3 
Mean differences for dichotomous variables 
AUDITLAG Independent Variables 
AUDITLAG 
Mean 
Standard Deviation 
Big 4 Audit Firms 
62 
4.302 
Non-Big 4 Audit Firms 
63 
4.334 
AUDITLAG 
Mean 
Standard Deviation 
Standard Opinion 
62 
3.789 
Others 
67 
3.586 
AUDITLAG 
Mean 
Standard Deviation 
Net Income 
61 
3.776 
Loss 
66 
3.324 
Table 4, 5, 6 present the multiple regression results for the sample. 
Table 4 
The summary of the statistics associated with the regression estimate 
Model R R Square Adjusted R Square Std. Error of the 
Estimate 
Durbin-Watson 
1 .729a .531 .514 3.001 1.198 
a. Predictors: (Constant), SIZE, LEVARAGE, AUDITOR, INCOME, OPINION 
b. Dependent Variable: AUDITLAG 
Table 5 
The results of ANOVA test 
Model Sum of Squares df Mean Square F Sig. 
1 
Regression 1388.431 5 277.686 30.828 .000b 
Residual 1225.034 136 9.008 
Total 2613.465 141 
a. Dependent Variable: AUDITLAG 
b. Predictors: (Constant), SIZE, LEVARAGE, AUDITOR, INCOME, OPINION 
Table 6 
The results of regression estimate 
Model Unstandardized Coefficients Standardized Coefficients t Sig. 
B Std. Error Beta 
1 
(Constant) 63.069 .894 70.531 .000 
AUDITOR .230 .508 .027 .452 .652 
INCOME 2.845 .591 .314 4.815 .000 
OPINION 2.578 .655 .256 3.933 .000 
LEVARAGE .003 .019 .009 .153 .879 
SIZE -.012 .002 -.383 -5.682 .000 
a. Dependent Variable: AUDITLAG 
From the above results, it can be seen that: 
Multi-collinearity testing: The VIF of all independent variables is less than 10, so the multi-collinearity in the model is 
considered not to be serious. 
The Durbin Watson Test is a measure of autocorrelation (also called serial correlation) in residuals from regression analysis. 
The Durbin-Watson value is 1.198 (between 1 and 3). Model does not have autocorrelation. 
Result of ANOVA test with Sig. = 0.000 shows that the linear regression model was constructed in accordance with the dataset 
and was usable. 
T.T.T. Lai et al. /Accounting 6 (2020) 7
The R2 (R Square) = 0.531 indicates that 53.1% of the variation in AUDITLAG of financial statements of FDI firms in Vietnam 
will be explained by factors with independent variables in the research model. 
The coefficient estimates for SIZE, INCOME, OPINION are all statistically significant (Sig. <5%). Audit delay was positively 
associated with OPINION, INCOME and negatively associated with SIZE. This means that audit lag decreases with the presence 
of income and standard audit report. Thus, the research hypotheses H1, H3, H4 are accepted. On the other hand, the AUDITOR 
coefficient and LEVERAGE coefficient are statistically not significant (Sig. >5%). Therefore, the research hypotheses H2, H5 
are rejected. 
It was also found that firms receiving a qualified audit opinion seem to suffer from a longer audit lag than those receiving a 
standard (clean) audit report. Logically, it can be argued that auditors need to spend considerable amount of time and effort in 
pursuing audit procedures to confirm the qualification or maybe possibly to avoid such qualification. The other finding of this 
study is that firms that report net income for the period publish their financial statement 5 days earlier than other firms that 
report loss for the period. 
In addition, it is found that firms that have standard audit reports publish their financial statements 5 days earlier than other 
firms that have qualified or adverse opinions. 
In short, this paper has investigated the effects of factors such as company size, sign of income, leverage, audit opinion, and 
auditor firm on timely financial reporting practices in a developing country, Vietnam. For this objective, financial statements 
and audit reports of 142 FDI firms were analyzed. According to empirical results; 53.1% of the variation in the audit lag in our 
model is explained by variations in company size, auditor firm, sign of income, audit opinion, and leverage. The coefficient 
estimates for INCOME, OPINION and SIZE are all found statistically significant. Besides, the coefficient estimates for 
LEVERAGE and AUDITOR coefficient are found statistically not significant. 
Timeliness is an important and useful characteristic of accounting information. Thereby, it is of great interest to different 
regulatory bodies and standard setters. However the timeliness of financial reporting is directly affected by the length of auditing. 
Our data indicate that the average audit delay in Vietnam FDI firms is 63 days. The aim of this study was to analyse the effect 
of several FDI company and audit related variables on audit delay in Vietnam. Our findings indicate that audit lag decreases 
with the presence of income and standard audit report, while audit lag increases in the smaller firms. The results of this paper 
could be of interest not only to academics but also to standard setters and regulators in the process of improvement of the quality 
of financial reporting. However, potential limitations of our study are related to a small sample size, sample selection bias and 
the problem of omitted variables (namely variables that explain different corporate governance aspects, institutional setting, 
audit firm and audit technology characteristics). These limitations can also be used as suggestions for future research. 
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