Regulators worldwide are considering expanding current audit reporting model to include key audit matters (KAM). Proponents argue that current audit reports are standardized and uninformative to financial statement users. Auditors in current reporting regime can choose to add explanatory notes in audit reports, however, few current studies have investigated the information content of these explanatory notes. This thesis conducts a textual analysis of explanatory notes in auditor reports and examines the predictability of auditors’ explanatory notes consisting of both unqualified and qualified opinions in determining the incidence of subsequent restatements. I hand collect material accounting restatements disclosed by the public companies in China from 2003 to 2017 and obtain modified audit reports from the CSMAR database during the period between 2003 and 2015. Based on a sample of 22,850 firm-years from 2003 to 2015 in China, I find that modified audit opinions, in general, can communicate financial misstatement risks, and the probability of such risks increases when the type of audit opinion is more severe. I also find that compared with unmodified audit opinion, modified ones containing explanatory notes have a higher possibility of subsequently being restated. Further, the predictive power is not the same across different types of explanatory notes. I have shown that explanatory notes including notes emphasizing contingencies and uncertainties and those relating to audit scope limitations have greater predictive power in explaining subsequent accounting restatements. My findings are robust with a set of additional tests. The findings of this thesis indicate that auditors do communicate financial misstatement risks in modified audit opinions (MAOs). Moreover, the findings are consistent with and provide evidence to support policy changes in developing new enhanced auditor reports introduced by the standard setters in China.
| Identifer | oai:union.ndltd.org:ln.edu.hk/oai:commons.ln.edu.hk:otd-1031 |
| Date | 31 August 2018 |
| Creators | YEUNG, Hau Yi |
| Publisher | Digital Commons @ Lingnan University |
| Source Sets | Lingnan University |
| Language | English |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | All Open Access Theses and Dissertations |
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