Real earnings management trends in the context of the COVID-19 pandemic: The case of non-financial listed companies in Vietnam

  • Received May 27, 2023;
    Accepted June 27, 2023;
    Published June 30, 2023
  • Author(s)
  • DOI
    http://dx.doi.org/10.21511/imfi.20(2).2023.25
  • Article Info
    Volume 20 2023, Issue #2, pp. 295-306
  • TO CITE АНОТАЦІЯ
  • Cited by
    2 articles
  • 460 Views
  • 219 Downloads

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

Real earnings management comprises the intervention by managers intending to change business strategies or policies to achieve specific goals. The paper aims to examine trends and levels of real earnings management in the context of the COVID-19 pandemic in Vietnam. The study uses time series data, and the sample includes 1,800 observations from 2016 to 2021. The methods of the study are regression analyses of the real earnings management model. The results indicate that the COVID-19 pandemic positively and significantly affected real earnings management of companies listed on the Vietnamese stock exchange. The trends and levels of real earnings management in the context of the COVID-19 pandemic increase depending on the severity of the pandemic. In terms of applications, the study provides evidence that the quality of financial reporting is lower during the pandemic. Listed enterprises in Vietnam are using high financial leverage, leading to a higher vulnerability to shocks such as the pandemic. Therefore, the real earnings management technique mainly used by managers is operating cash flow adjustment by using income maximization strategies to increase the ability to borrow capital to maintain business operations. The study suggests that the choice of income maximization or income minimization strategy depends mainly on commitments with the capital provider (credit institutions), specific contexts, and economic factors.

view full abstract hide full abstract
    • Table 1. The definition of variables and methods to measure the level of REM
    • Table 2. Descriptive statistics of the variables in the model
    • Table 3. Two-sample t-tests
    • Table 4. Pearson’s correlation coefficient
    • Table 5. Regression results according to each proxy of REM
    • Table 6. REM measures result
    • Table 7. REM regression results by year during the pandemic
    • Conceptualization
      Dang Anh Tuan, Nguyen Ngoc Khanh Dung, Bui Thi Thu Thao
    • Data curation
      Dang Anh Tuan, Nguyen Ngoc Khanh Dung
    • Formal Analysis
      Dang Anh Tuan, Bui Thi Thu Thao
    • Investigation
      Dang Anh Tuan, Nguyen Ngoc Khanh Dung, Bui Thi Thu Thao
    • Methodology
      Dang Anh Tuan, Nguyen Ngoc Khanh Dung
    • Project administration
      Dang Anh Tuan
    • Resources
      Dang Anh Tuan, Nguyen Ngoc Khanh Dung
    • Software
      Dang Anh Tuan, Nguyen Ngoc Khanh Dung, Bui Thi Thu Thao
    • Supervision
      Dang Anh Tuan
    • Validation
      Dang Anh Tuan, Nguyen Ngoc Khanh Dung, Bui Thi Thu Thao
    • Visualization
      Dang Anh Tuan
    • Writing – original draft
      Dang Anh Tuan, Nguyen Ngoc Khanh Dung
    • Writing – review & editing
      Dang Anh Tuan, Nguyen Ngoc Khanh Dung, Bui Thi Thu Thao