Audit firm tenure and qualified opinions: New evidence from Spain

Blandón, Josep García; Bosch, Josep Maria Argilés i

doi:10.1016/j.rcsar.2013.02.001

Cited by 17 publications

(7 citation statements)

References 25 publications

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“…Given the relatively high frequency of qualified audit opinions in Serbia (32.6%) compared to elsewhere in Europe, e.g. 16% in Spain, 2% in Germany, 0.5% in Austria, 3.7% in Switzerland, 1.3% in France, and 0.5% in the United Kingdom (Blandón and Bosch, 2013;Gassen and Skaife, 2009), and other parts of the world, e.g. 13% in the US and 11% in China (Abad et al, 2017;Dhaliwal et al, 2014), the results of the study may only be generalized to a smaller number of countries with unusually high frequencies of qualified audit opinions.…”

Section: Discussionmentioning

confidence: 99%

Predicting the type of auditor opinion: Statistics, machine learning, or a combination of the two?

Stanišić¹,

Radojević²,

Stanić³

2019

EurJ Appl Econ

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The goal of this study is to overcome the identified methodological limitations of prior studies aimed at predicting the type of auditor opinion and draw definite conclusions on the relative predictive performance of different predictive methods for this particular task. Predictive performance of twelve candidate models from the realms of statistics and machine learning is assessed separately for the two common real-life scenarios: a) when prior information on the client (i.e. types of audit opinion received in the past) is available and can be used in prediction, and b) when such information is not available (e.g. new companies). The results show that, in the first scenario, several methods from both realms achieve comparable predictive performance of around 0.89, as measured by the Area under the curve (AUC). In the second scenario, however, machine learning algorithms, particularly tree-based ones, such as random forest, perform significantly better, achieving the AUC of up to 0.79. Finally, we develop and assess the predictive performance of two hybrid models aimed at combining the strong points of both statistical (i.e. interpretability of results) and machine learning (i.e. handling a large number of predictors and improved accuracy) approaches. The complete procedure is demonstrated in a reproducible manner, using the largest empirical data set ever used in this stream of research, comprising 13,561 pairs of annual financial statements and the corresponding audit reports. The procedures described in this study allow audit and finance professionals around the globe to develop and test predictive models that will aid their procedures of audit planning and risk assessment.

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Section: Discussionmentioning

confidence: 99%

Predicting the type of auditor opinion: Statistics, machine learning, or a combination of the two?

Stanišić¹,

Radojević²,

Stanić³

2019

EurJ Appl Econ

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“…Although auditors are highly influenced by the legal regulation in the resolution of ethical conflicts the relatively low importance attached by auditors to the possibility of being punished or discovered results in this factor being less influential than the firm and loss of reputation. An explanation for the relatively low importance attached to being punished or discovered may be found in the low litigation risk perceived by the Spanish audit market (Cano Rodriguez, 2007;Carmona Ibáñez & Momparler Pechuán, 2011;García Blandón & Argilés Bosch, 2013;Ruiz Barbadillo, Gómez Aguilar, & Biedma López, 2005).…”

Section: Resolution Of Conflicts Of Interestmentioning

confidence: 99%

An exploratory study of the pressures and ethical dilemmas in the audit conflict

Espinosa-Pike

Barrainkua

2016

Revista de Contabilidad

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“…The dependent variable (IA) is a dummy variable that equals 1 when the company receives a qualified audit opinion, and zero otherwise. Some other papers have used audit opinion as a proxy for financial reporting quality (Bartov et al, 2000;Butler et al, 2004;Chen et al, 2001;Farihna & Viana, 2009;García Blandón & Argilés Bosch, 2013;Pucheta-Martínez & de Fuentes, 2007).…”

Section: Variablesmentioning

confidence: 99%

Institutional Investors on Boards and Audit Committees and Their Effects on Financial Reporting Quality

Pucheta‐Martínez¹,

García‐Meca²

2014

Corporate Governance

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Manuscript Type Empirical Research Question/Issue This study examines how the presence of representatives of institutional investors as directors on boards or on audit committees enhances financial reporting quality, reducing the probability that the firm receives qualified audit reports. We focus on directors who maintain business relations with the firm on whose board or committee they sit (pressure‐sensitive directors). We also investigate the specific role of bank directors and examine their effects on financial reporting quality when they act as shareholders and directors. Research Findings/Insights Our results suggest that institutional directors are effective monitors, which leads to higher quality financial reporting and, therefore, a lower likelihood that the firm receives a qualified audit report. Consistent with the relevant role of business relations with the firm, we find that directors appointed to both boards and audit committees by pressure‐sensitive investors have a larger effect on financial reporting quality as it is more likely that the auditor issues an unqualified audit opinion. Nevertheless, when analyzed separately, only savings bank representatives on the board increase financial reporting quality. Theoretical/Academic Implications The results confirm that board characteristics have an important influence on financial reporting quality, in line with the views that have been expressed by several international bodies. The findings also suggest that both researchers and policy makers should no longer consider institutional investors as a whole, given than directors appointed by different types of institutional investors have various implications on financial reporting quality, measured by the type of audit opinion. Practitioner/Policy Implications This study makes its core contribution by empirically showing that directors appointed by different types of institutional investors have diverse implications on financial reporting quality. This evidence can be potentially helpful in providing a basis for regulatory actions, namely those aiming to influence the structure of the board of directors. The results have important implications for supervisors and regulators, who will benefit from an understanding of how the presence of directors on boards of savings and commercial banks in nonfinancial firms affects financial reporting quality in a bank‐based system.

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Audit firm tenure and qualified opinions: New evidence from Spain

Cited by 17 publications

References 25 publications

Predicting the type of auditor opinion: Statistics, machine learning, or a combination of the two?

Predicting the type of auditor opinion: Statistics, machine learning, or a combination of the two?

An exploratory study of the pressures and ethical dilemmas in the audit conflict

Institutional Investors on Boards and Audit Committees and Their Effects on Financial Reporting Quality

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