The Importance of Partner Narcissism to Audit Quality: Evidence from Taiwan

2021 ◽  
Author(s):  
Ting-Kai Chou ◽  
Jeffrey Pittman ◽  
Zili Zhuang
Keyword(s):  
Audit Quality ◽  
Auditor Independence ◽  
Type I ◽  
Type Ii ◽  
Type Ii Error ◽  
Negatively Associated ◽  
Client Pressure ◽  
Audit Reports ◽  
The Impact ◽  
Quality Evidence

Relying on the size of partner signatures in audit reports in Taiwan to measure their narcissism, we find that audit quality rises with partner narcissism. Our analysis also implies that changes in audit quality are positively associated with changes in partner narcissism stemming from mandatory partner rotation. We also find that the impact of partner narcissism on audit quality only manifests when auditor independence is more likely to be compromised, although it does not vary with engagement complexity. These results suggest that partner narcissism improves audit quality mainly through increased auditor independence, rather than auditor competence. Additionally, we document that although partner narcissism has no perceptible impact on the incidence of Type I going concern reporting errors, it is negatively associated with the probability of making a Type II error, implying that more narcissistic partners are less likely to succumb to client pressure to issue opportunistic reports.

scholarly journals The Effect of Independence and Integrity on Audit Quality: Is There A Moderating Role for E-Audit?

2021 ◽  
Vol 23 (3) ◽  
Author(s):  
Diza Dianeke Budi Prabowo ◽  
Dwi Suhartini
Keyword(s):  
Industrial Revolution ◽  
Audit Quality ◽  
Practical Implication ◽  
Financial Statements ◽  
Auditor Independence ◽  
Audit Process ◽  
Accounting Firms ◽  
Audit Reports ◽  
The Impact

The financial statements must be reliable and become a benchmark in considering an audit decision on the financial statements. In order for this to be achieved, independence and integrity is required in carrying out the audit process. E-Audit helps overcome challenges in the industrial revolution 4.0 and prevent fraud. This research aims of testing and analyzing the role of e-audit in moderating the impact of auditor independence and integrity on audit quality. The data was collected through a questionnaire distributed to auditors at Public Accounting Firms in Surabaya. There are 36 respondents involved. The data were analyzed using SmartPLS. The results showed that auditor independence positively effect audit quality, auditor integrity positively effect audit quality; e-audit does non moderate the effect of auditor independence on audit quality; ande-Audit negatively moderates the effect of auditor integrity on audit quality. The practical implication of this research is that when determining high audit quality, independent auditors should at least increase their independence and integrity so that the resulting audit reports are of high quality and can be a reference for decision makers.

Consequences of Going-Concern Opinion Inaccuracy at the Audit Office Level

2020 ◽  
Vol 39 (3) ◽  
pp. 185-208
Author(s):  
Qiao Xu ◽  
Rachana Kalelkar
Keyword(s):  
Market Share ◽  
Audit Quality ◽  
Type I ◽  
Type I Errors ◽  
Negatively Associated ◽  
Going Concern ◽  
Big 4 ◽  
Office Market ◽  
Going Concern Opinion ◽  
Office Level

SUMMARY This paper examines whether inaccurate going-concern opinions negatively affect the audit office's reputation. Assuming that clients perceive the incidence of going-concern opinion errors as a systematic audit quality concern within the entire audit office, we expect these inaccuracies to impact the audit office market share and dismissal rate. We find that going-concern opinion inaccuracy is negatively associated with the audit office market share and is positively associated with the audit office dismissal rate. Furthermore, we find that the decline in market share and the increase in dismissal rate are primarily associated with Type I errors. Additional analyses reveal that the negative consequence of going-concern opinion inaccuracy is lower for Big 4 audit offices. Finally, we find that the decrease in the audit office market share is explained by the distressed clients' reactions to Type I errors and audit offices' lack of ability to attract new clients.

Market Reactions to a High-Quality Auditor and Managerial Preference for Audit Quality

2019 ◽  
Vol 38 (4) ◽  
pp. 131-149 ◽  
Author(s):  
Patrick J. Hurley ◽  
Brian W. Mayhew
Keyword(s):  
Loss Aversion ◽  
Audit Quality ◽  
Data Availability ◽  
Quality Competition ◽  
High Quality ◽  
Market Reactions ◽  
Comprehensive Theory ◽  
Audit Reports ◽  
The Impact ◽  
Quality Theory

SUMMARY We insert an automated high-quality (HQ) auditor into established experimental audit markets to test the impact of high-quality competition on other auditors' supply of and managers' demand for audit quality. Theory predicts that managers will demand high levels of audit quality to avoid investors' price-protecting behavior. This demand should result in the HQ auditor dominating the market and increase other auditors' audit quality provision to compete with the HQ auditor. However, we find that the HQ auditor does not dominate the market—despite holding audit costs constant and investors placing a premium on HQ auditor reports. We also find that adding an HQ auditor results in other auditors lowering audit quality. Additional analyses indicate some managers demand lower audit quality to avoid negative audit reports, consistent with loss aversion as a potential explanation. Our findings indicate a need to develop a more comprehensive theory of the demand for auditing. Data Availability: The laboratory market data used in this study are available from the authors upon request.

Modeling Endoleaks and Collateral Reperfusion following Endovascular AAA Exclusion

2003 ◽  
Vol 10 (3) ◽  
pp. 424-432 ◽  
Author(s):  
Chuh K. Chong ◽  
Thien V. How ◽  
Geoffrey L. Gilling-Smith ◽  
Peter L. Harris
Keyword(s):  
Stent Graft ◽  
Aortic Pressure ◽  
Type I ◽  
Type Ii ◽  
Pump System ◽  
Type Ii Endoleak ◽  
Type I Endoleak ◽  
The Impact ◽  
Mean Aortic Pressure

Purpose: To investigate the effect on intrasac pressure of stent-graft deployment within a life-size silicone rubber model of an abdominal aortic aneurysm (AAA) maintained under physiological conditions of pressure and flow. Methods: A commercial bifurcated device with the polyester fabric preclotted with gelatin was deployed in the AAA model. A pump system generated physiological flow. Mean and pulse aortic and intrasac pressures were measured simultaneously using pressure transducers. To simulate a type I endoleak, plastic tubing was placed between the aortic wall and the stent-graft at the proximal anchoring site. Type II endoleak was simulated by means of side branches with set inflow and outflow pressures and perfusion rates. Type IV endoleak was replicated by removal of gelatin from the graft fabric. Results: With no endoleak, the coated graft reduced the mean and pulse sac pressures to negligible values. When a type I endoleak was present, mean sac pressure reached a value similar to mean aortic pressure. When net flow through the sac due to a type II endoleak was present, mean sac pressure was a function of the inlet pressure, while pulse pressure in the sac was dependent on both inlet and outlet pressures. As perfusion rates increased, both mean and pulse sac pressures decreased. When there was no outflow, mean sac pressure was similar to mean aortic pressure. In the presence of both type I and type II endoleaks, mean sac pressure reached mean aortic pressure when the net perfusion rate was low. Conclusions: In vitro studies are useful in gaining an understanding of the impact of different types of endoleaks, in isolation and in combination, on intrasac pressure after aortic stent-graft deployment.

Type I and type II error rates for quantitative trait loci (QTL) mapping studies using recombinant inbred mouse strains

1996 ◽  
Vol 26 (2) ◽  
pp. 149-160 ◽  
Author(s):  
J. K. Belknap ◽  
S. R. Mitchell ◽  
L. A. O'Toole ◽  
M. L. Helms ◽  
J. C. Crabbe
Keyword(s):  
Quantitative Trait ◽  
Recombinant Inbred ◽  
Inbred Mouse ◽  
Error Rates ◽  
Mouse Strains ◽  
Type I ◽  
Inbred Mouse Strains ◽  
Type Ii ◽  
Type Ii Error ◽  
Recombinant Inbred Mouse

scholarly journals Reliability and Accuracy of Alternative Default Prediction Models: Evidence from Slovakia

2021 ◽  
Vol 9 (4) ◽  
pp. 65
Author(s):  
Daniela Rybárová ◽  
Helena Majdúchová ◽  
Peter Štetka ◽  
Darina Luščíková
Keyword(s):  
Prediction Models ◽  
Slovak Republic ◽  
Type I ◽  
Type Ii ◽  
Type Ii Error ◽  
Z Score ◽  
Local Conditions ◽  
Default Prediction ◽  
Statistical Hypotheses ◽  
Subsequent Comparison

The aim of this paper is to assess the reliability of alternative default prediction models in local conditions, with subsequent comparison with other generally known and globally disseminated default prediction models, such as Altman’s Z-score, Quick Test, Creditworthiness Index, and Taffler’s Model. The comparison was carried out on a sample of 90 companies operating in the Slovak Republic over a period of 3 years (2016, 2017, and 2018) with a narrower focus on three sectors: construction, retail, and tourism, using alternative default prediction models, such as CH-index, G-index, Binkert’s Model, HGN2 Model, M-model, Gulka’s Model, Hurtošová’s Model, Model of Delina and Packová, and Binkert’s Model. To verify the reliability of these models, tests of the significance of statistical hypotheses were used, such as type I and type II error. According to research results, the highest reliability and accuracy was achieved by an alternative local Model of Delina and Packová. The least reliable results within the list of models were reported by the most globally disseminated model, Altman’s Z-score. Significant differences between sectors were identified.

scholarly journals BANKRUPTCY PREDICTION MODEL WITH ZETAc OPTIMAL CUT-OFF SCORE TO CORRECT TYPE I ERRORS

2005 ◽  
Vol 7 (1) ◽  
pp. 41 ◽  
Author(s):  
Mohamad Iwan
Keyword(s):  
Type I Error ◽  
Bankruptcy Prediction ◽  
Type I ◽  
Type Ii ◽  
Type Ii Error ◽  
Prior Probabilities ◽  
Prediction Result ◽  
Optimum Cutting ◽  
Classification Errors ◽  
One Year

This research examines financial ratios that distinguish between bankrupt and non-bankrupt companies and make use of those distinguishing ratios to build a one-year prior to bankruptcy prediction model. This research also calculates how many times the type I error is more costly compared to the type II error. The costs of type I and type II errors (cost of misclassification errors) in conjunction to the calculation of prior probabilities of bankruptcy and non-bankruptcy are used in the calculation of the ZETAc optimal cut-off score. The bankruptcy prediction result using ZETAc optimal cut-off score is compared to the bankruptcy prediction result using a cut-off score which does not consider neither cost of classification errors nor prior probabilities as stated by Hair et al. (1998), and for later purposes will be referred to Hair et al. optimum cutting score. Comparison between the prediction results of both cut-off scores is purported to determine the better cut-off score between the two, so that the prediction result is more conservative and minimizes expected costs, which may occur from classification errors.  This is the first research in Indonesia that incorporates type I and II errors and prior probabilities of bankruptcy and non-bankruptcy in the computation of the cut-off score used in performing bankruptcy prediction. Earlier researches gave the same weight between type I and II errors and prior probabilities of bankruptcy and non-bankruptcy, while this research gives a greater weigh on type I error than that on type II error and prior probability of non-bankruptcy than that on prior probability of bankruptcy.This research has successfully attained the following results: (1) type I error is in fact 59,83 times more costly compared to type II error, (2) 22 ratios distinguish between bankrupt and non-bankrupt groups, (3) 2 financial ratios proved to be effective in predicting bankruptcy, (4) prediction using ZETAc optimal cut-off score predicts more companies filing for bankruptcy within one year compared to prediction using Hair et al. optimum cutting score, (5) Although prediction using Hair et al. optimum cutting score is more accurate, prediction using ZETAc optimal cut-off score proved to be able to minimize cost incurred from classification errors.

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