Voluntary IFRS adoption and accounting quality: Evidence from Japan
| Autor: | Junjian Gu |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
Expectancy theory
Economics and Econometrics conditional conservatism business.industry media_common.quotation_subject income smoothing Economic growth development planning Accounting Conditional conservatism expectancy theory voluntary IFRS adoption Japan japan International Financial Reporting Standards voluntary ifrs adoption Regional economics. Space in economics Turnover HT388 HD72-88 Asian country Quality (business) Business media_common |
| Zdroj: | Ekonomska Istraživanja, Vol 34, Iss 1, Pp 1985-2012 (2021) Economic research-Ekonomska istraživanja Volume 34 Issue 1 |
| ISSN: | 1848-9664 1331-677X |
| DOI: | 10.1080/1331677x.2020.1860793 |
| Popis: | Accounting scholars have discussed the determinants of International Financial Reporting Standards (IFRS) adoption and its outcomes. However, little research focuses on the Asian countries that voluntarily adopted IFRS on a limited basis. In this study, we focus on a specific country, Japan, the largest nation worldwide that allows voluntary IFRS adoption. According to expectancy theory, we predict that voluntary IFRS adoption with motivation similar to that of the International Accounting Standards Board can improve accounting quality by enhancing motivation to adhere to the IFRS guidelines, which increases financial reporting comparability. We find that voluntary IFRS adoption by Japanese firms with positive motivation reduces income smoothing and enhances the extent of conditional conservatism. Additionally, we find that these associations primarily exist in firms with higher leverage, banker investors, a higher degree of tax avoidance and in regions with strong outside investor rights. Our main findings are robust to several sensitivity tests. This study fills a gap in the existing literature on IFRS adoption by investigating the effect of voluntary IFRS adoption on accounting quality from an adoption motivation perspective. |
| Databáze: | OpenAIRE |
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