Audit opinion and earnings management: Empirical evidence from Vietnam

  • Received September 10, 2021;
    Accepted October 19, 2021;
    Published October 27, 2021
  • Author(s)
  • DOI
  • Article Info
    Volume 18 2021, Issue #4, pp. 131-140
  • Cited by
    2 articles

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License

This paper aims to explore the interaction between earnings management and audit opinions in the context of Vietnam – an emerging country. For this purpose, two regressions were developed with sample consists of 1,294 firm-years in the period from 2018 to 2020. The first regression model uses Audit Opinion as dependent variable, Discretionary Accruals (DA) as independent variable, and other 8 controlling variables. The results demonstrate that the Discretionary Accruals influence audit opinion, significantly at 0.1 level in the study year. This means the auditor’s probability of issuing modified opinion is positively associated with earnings management and with the attendance of a Big 4 audit companies. Another regression model tests influence of auditor size (measured by Opinion of Auditor) on the interaction between management of earnings and audit opinion (measured by Discretionary Accruals) as independent variable, and other 10 controlling variables. Surprisingly, this model is not statistically significant and this confirms that the appearance of a Big 4 audit companies does not significantly affect the nexus between profit management and audit opinion in the case of Vietnamese listed companies. The results suggest that Big 4 audit firms tend to have higher requirements for the true-and-fair information on the client’s financial statements and often have a tendency to issue modified opinions when the financial statements have material errors, or it is impossible to collect sufficient audit evidence. This finding may enhance the decision-making process of users in various circumstances.

This paper is funded by the National Economics University (NEU), Vietnam. The authors thank anonymous reviewers for their contributions and the NEU for supporting this study.

view full abstract hide full abstract
    • Table 1. Descriptive statistics for continuous variables
    • Table 2. Descriptive statistics for binary variables
    • Table 3. Pearson correlations analysis
    • Table 4. Logistic regression results without BIGN variable
    • Table 5. Logistic regression results with the moderator variable (BIGN)
    • Conceptualization
      Thanh Nga Doan, Duc Cuong Pham
    • Funding acquisition
      Thanh Nga Doan, Thu Trang Ta, La Soa Nguyen
    • Methodology
      Thanh Nga Doan, Thu Trang Ta
    • Project administration
      Thanh Nga Doan, Thu Trang Ta, La Soa Nguyen
    • Writing – original draft
      Thanh Nga Doan
    • Resources
      Thu Trang Ta, La Soa Nguyen
    • Writing – review & editing
      Thu Trang Ta, Duc Cuong Pham
    • Formal Analysis
      Duc Cuong Pham, Hoai Nam Tran
    • Investigation
      Duc Cuong Pham
    • Supervision
      Duc Cuong Pham
    • Visualization
      Duc Cuong Pham, Hoai Nam Tran
    • Validation
      La Soa Nguyen
    • Data curation
      Hoai Nam Tran
    • Software
      Hoai Nam Tran