Corporate tax noncompliance is a serious problem in many developed and developing countries. My PhD thesis is composed of two essays to investigate various factors that mitigate corporate tax noncompliance by listed Chinese firms.
The first essay examines whether a firm’s corporate tax noncompliance can be constrained by auditor quality. Past studies have shown that high-quality auditors are effective in reducing earnings management, which mainly involves overstatements of earnings. In this essay, I find that high-quality auditors are associated with better overall tax compliance by their client firms. In particular, high-quality auditors are effective in constraining book-tax-conforming noncompliance, which mainly involves understatements of both book and taxable income.
The second essay examines the tax noncompliance behavior of firms since the adoption of International Financial Reporting Standards (IFRS) in China, taking into account the influences of lower tax rates and more stringent tax enforcement. In recent years, many countries have moved away from tax-based accounting and toward adopting IFRS which increase tax noncompliance. At the same time, there has been a general reduction of corporate income tax rates as a means to increase tax competitiveness. Lower tax rates should be associated with decreases in tax noncompliance. Similarly, firms should be more tax compliant under a more stringent tax enforcement regime. In this essay, I find that the negative effect of book-tax delinking on tax noncompliance is significantly attenuated for firms that are subject to lower tax rates or more stringent tax enforcement measures. This essay also provides evidence that the effects of tax rates and of tax enforcement measures are more pronounced in the lower book-tax conformity period.
| Identifer | oai:union.ndltd.org:ln.edu.hk/oai:commons.ln.edu.hk:acct_etd-1020 |
| Date | 13 July 2015 |
| Creators | LUO, Kim Wan, Rebecca |
| Publisher | Digital Commons @ Lingnan University |
| Source Sets | Lingnan University |
| Language | English |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | Theses & Dissertations |
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