Issue |
E3S Web Conf.
Volume 214, 2020
2020 International Conference on Energy Big Data and Low-carbon Development Management (EBLDM 2020)
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Article Number | 02022 | |
Number of page(s) | 9 | |
Section | Machine Learning and Energy Industry Structure Forecast Analysis | |
DOI | https://doi.org/10.1051/e3sconf/202021402022 | |
Published online | 07 December 2020 |
Fair Value Hierarchy and Audit Fees: An Empirical Analysis based on the Listed Banks in China
College of finance and accounting, Henan University of Animal Husbandry and Economy, Zhengzhou, Henan, China
a e-mail: 1103498281@qq.com
The key to the criticism of fair value lies in the lack of measurement in the active market quotation, while the fair value hierarchy hopes to make up for the reliability of fair value information by increasing disclosure. Using listed commercial bank data from 2007 through 2016, this paper documents that the assets and liabilities measured by fair value are significantly positively associated with audit fees. The positive association between audit fees and the fair value obtained via Level 2 or Level 3 inputs is greater than that Level 1.These results indicate that when the fair value needs to be estimated, the auditor needs to increase audit effort with resulting in higher audit fees. Moreover, the balance of assets and liabilities that fair-valued using Level 2 inputs is the largest and accounts for the highest proportion, which leads to more substantial changes in audit expenses. This result is consistent with the scale determinism of audit expenses. At the same time, due to the impact of professional judgment on the fair value hierarchy and the absence of corresponding supervision, the management has the motivation to use hierarchy for earnings management. The assets and liabilities that fair-valued using Level 2 inputs may represent the characteristics of fair value earnings management, audit risk is higher.
© The Authors, published by EDP Sciences, 2020
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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