Impact of factors on fair value accounting: empirical study in Vietnam

  • Received April 10, 2020;
    Accepted July 24, 2020;
    Published August 7, 2020
  • Author(s)
  • DOI
    http://dx.doi.org/10.21511/imfi.17(3).2020.02
  • Article Info
    Volume 17 2020, Issue #3, pp. 10-26
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Due to the ongoing process of globalization, enterprises need to provide financial statements in accordance with international practices, in which information about assets and liabilities should be presented at fair values rather than at original prices. Fair value is supported by the International Accounting Standards Board and the Financial Accounting Standards Board. The purpose of this study is to evaluate the adoption of fair value accounting in Vietnam and the impact of factors on the adoption of fair value. The paper used the analytical framework of previous studies to identify factors affecting the adoption of fair value. Additionally, this study applied quantitative research methods and collected data by sending questionnaires to 127 accountants and directors of listed companies. Particularly, binary logistic regression was conducted to investigate the extent of the impact of each factor on the adoption of fair value. The results have shown that human resources have the strongest and positive impact on the adoption of fair value, and this is followed by the benefits of fair value. Difficulties and markets negatively affect the use of fair value. Furthermore, the control variables that affect the use of fair value are sector, size and length of operation with different levels of impact. The accuracy rate of the overall predictive model is 85.8%. The findings provide guidance of the application of fair value accounting in companies and give recommendations to policy makers in establishing a legal accounting framework in Vietnam.

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    • Figure 1. Conceptual framework
    • Table 1. Group statistics
    • Table 2. Independent sample test
    • Table 3. Test of homogeneity of variances
    • Table 4. KMO and Bartlett’s Test
    • Table 5. Total variance explained
    • Table 6. Rotated component matrix
    • Table 7. Omnibus tests of model coefficients
    • Table 8. Classification table
    • Table 9. Variables in the equation
    • Table A1. Measurement scales
    • Table A2. Descriptive statistics
    • Table A3. Item-total statistics
    • Table A4. Correlations
    • Conceptualization
      Bui Thi Ngoc
    • Data curation
      Bui Thi Ngoc
    • Formal Analysis
      Bui Thi Ngoc
    • Funding acquisition
      Bui Thi Ngoc
    • Investigation
      Bui Thi Ngoc
    • Methodology
      Bui Thi Ngoc
    • Project administration
      Bui Thi Ngoc
    • Resources
      Bui Thi Ngoc
    • Software
      Bui Thi Ngoc
    • Supervision
      Bui Thi Ngoc
    • Validation
      Bui Thi Ngoc
    • Visualization
      Bui Thi Ngoc
    • Writing – original draft
      Bui Thi Ngoc
    • Writing – review & editing
      Bui Thi Ngoc