Measuring Audit Quality

Rajgopal, Shivaram; Srinivasan, Suraj; Zheng, Xin

doi:10.2139/ssrn.3504037

Cited by 29 publications

(37 citation statements)

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“…Several proxies of financial reporting quality can be found in the literature: for example, accrual quality (Dechow & Dichev, 2002;Rajgopal & Venkatachalam, 2011); the Dechow and Dichev (2002) measure of earnings quality (McNichols, 2002); the meeting or beating of quarterly earnings forecasts (Rajgopal et al, 2015); and financial statement restatements (Kedia et al, 2015). To avoid the limitations of the different measurements of financial statement quality, this research uses actual violations in financial statements, as reported by the JSC, as a proxy to measure quality.…”

Section: Financial Statement Qualitymentioning

confidence: 99%

“…In examining contagion in earnings management, Rajgopal et al (2015) employed SEC (Securities and Exchange Commission) Accounting and Auditing Enforcement Releases and lawsuits against auditors to reflect how the users of financial statements assess audit performance. Audit deficiencies reported by the SEC and lawsuits may indicate deteriorating reporting quality and violations of auditing standards.…”

Section: Financial Statement Qualitymentioning

confidence: 99%

“…Several empirical studies have found that big audit firms provide better audit quality than small ones (e.g., DeAngelo, 1981;Krishnan & Schauer, 2000;Sundgren & Svanström, 2011). Rajgopal et al (2015) found that the presence of big audit firms is adversely related to the audit deficiencies reported by the SEC and by lawyers.…”

Section: Auditor Sizementioning

confidence: 99%

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The effect of audit fees on disclosure quality in Jordan

Shakhatreh

Alsmadi

Alkhataybeh

2020

Cogent Business & Management

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Disclosure quality is a matter of great importance in the accounting literature. This study examines the effect of audit fees, audit firm size and audit opinion on the quality of disclosures. It focuses on a sample of low-quality financial statements in Jordan that have been reported as breaches by the Jordanian Securities Commission (JSC). Data were collected from the financial statements of the manufacturing and services companies listed on the Amman Stock Exchange (ASE) during the period 2009 to 2016. The logistic regression results suggest that audit fees have a positive significant effect, while audit opinion has a negative significant effect on actual violations. However, audit firm size was found to be insignificant in relation to the level of violations.

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Section: Financial Statement Qualitymentioning

confidence: 99%

Section: Financial Statement Qualitymentioning

confidence: 99%

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The effect of audit fees on disclosure quality in Jordan

Shakhatreh

Alsmadi

Alkhataybeh

2020

Cogent Business & Management

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“…Third, we replace our dependent variable capturing audit quality with a binary variable that measures the tendency to meet or beat an earnings target ( AQS ). Similar to prior literature, we use the last mean analyst forecast of the earnings per share before the annual earnings announcement as a benchmark (e.g., Rajgopal, Srinivasan, & Zheng, 2020; Reichelt & Dechun, 2010). We exclude 111 observations from our sample, as analyst forecasts in Thomson Reuters Eikon Database on earnings per share were not available for these observations.…”

Section: Robustness Checksmentioning

confidence: 99%

“…5 Third, we replace our dependent variable capturing audit quality with a binary variable that measures the tendency to meet or beat an earnings target (AQS). Similar to prior literature, we use the last mean analyst forecast of the earnings per share before the annual earnings announcement as a benchmark (e.g., Rajgopal, Srinivasan, & Zheng, 2020;Reichelt & Dechun, 2010 Fourth, we replace our audit quality proxies using abnormal accrual measures with a variable (lnReportLag) capturing audit effort (audit report lag) (Knechel & Sharma, 2012). The audit report lag is defined as the number of calendar days between the date of the audit report and the company's year-end.…”

Section: Robustness Checksmentioning

confidence: 99%

Codetermination on the audit committee: An analysis of potential effects on audit quality

Hillebrandt¹,

Ratzinger‐Sakel²

2021

Int J Auditing

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This paper empirically investigates the association between codetermination on the audit committee (AC) and audit quality. Using a sample of 655 firm‐year observations related to German CDAX companies, our results indicate that the presence of employee representatives on the AC is negatively associated with audit quality. This negative association can also be observed for the percentage of employee representatives serving on the AC. However, our analyses show that the mentioned findings turn insignificant when employee representatives have accounting expertise. In addition, the type of employee representatives seems to influence audit quality differently: our findings turn insignificant for employee representatives who are classified as company outsiders and, thus, expected to be more independent. These findings highlight the importance of accounting expertise and independence for AC members' monitoring effectiveness. To the best of our knowledge, this study is the first that analyses the impact of codetermination on the AC on audit quality.

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Is artificial intelligence improving the audit process?

Fedyk

Hodson²,

Khimich

et al. 2022

Rev Account Stud

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How does artificial intelligence (AI) impact audit quality and efficiency? We explore this question by leveraging a unique dataset of more than 310,000 detailed individual resumes for the 36 largest audit firms to identify audit firms’ employment of AI workers. We provide a first look into the AI workforce within the auditing sector. AI workers tend to be male and relatively young and hold mostly but not exclusively technical degrees. Importantly, AI is a centralized function within the firm, with workers concentrating in a handful of teams and geographic locations. Our results show that investing in AI helps improve audit quality, reduces fees, and ultimately displaces human auditors, although the effect on labor takes several years to materialize. Specifically, a one-standard-deviation change in recent AI investments is associated with a 5.0% reduction in the likelihood of an audit restatement, a 0.9% drop in audit fees, and a reduction in the number of accounting employees that reaches 3.6% after three years and 7.1% after four years. Our empirical analyses are supported by in-depth interviews with 17 audit partners representing the eight largest U.S. public accounting firms, which show that (1) AI is developed centrally; (2) AI is widely used in audit; and (3) the primary goal for using AI in audit is improved quality, followed by efficiency.

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Measuring Audit Quality

Cited by 29 publications

References 0 publications

The effect of audit fees on disclosure quality in Jordan

The effect of audit fees on disclosure quality in Jordan

Codetermination on the audit committee: An analysis of potential effects on audit quality

Is artificial intelligence improving the audit process?

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