The effect of IFRS adoption on the value relevance of accounting information: evidence from South Korea

  • Received May 19, 2018;
    Accepted April 19, 2019;
    Published May 7, 2019
  • Author(s)
  • DOI
    http://dx.doi.org/10.21511/imfi.16(2).2019.07
  • Article Info
    Volume 16 2019, Issue #2, pp. 78-88
  • TO CITE АНОТАЦІЯ
  • Cited by
    6 articles
  • 1826 Views
  • 296 Downloads

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

This study investigates whether the value relevance of accounting information was changed after IFRS adoption in South Korea. Related prior studies have found mixed empirical evidence depending on research methodologies or research periods. Moreover, the effect of IFRS adoption on value relevance can be different between Korean stock markets (KSE and KOSDAQ) because they have different characteristics. Also, the main financial statements reported by Korean firms had changed from individual financial statements to consolidated financial statements after IFRS adoption. Thus, this study analyzes the effect of IFRS adoption on the value relevance of individual and consolidated accounting numbers expanding research periods (5 years before and after IFRS adoption) and comparing changes in explanatory powers of Ohlson (1995) model on each listing market. The empirical results indicate that the value relevance of Korean listed firms generally decreased after IFRS adoption. However, the value relevance of KSE listed firms decreased, while the value relevance of KOSDAQ listed firms increased after IFRS adoption. In addition, it was found that the effects of IFRS adoption on value relevance of individual and consolidated financial information were different depending on listed markets. This implies that different level of demand for information environment may induce differential effects of IFRS adoption on value relevance.

view full abstract hide full abstract
    • Table 1. Descriptive statistics (n = 14,260)
    • Table 2. Pearson & Spearman Correlation Matrix (n = 14,260)
    • Table 3. Test results of hypothesis using pooled OLS model (Equation (1))
    • Table 4. Test results of hypothesis using fixed industry effect model (Equation (2))
    • Table 5. Annual time-series trends of adjusted R2 by listing market