Using the Profile of CEOs to Detect Earnings Management

60 Pages Posted: 12 Dec 2016 Last revised: 12 Jan 2017

Tri Nguyen

University of East London - Royal Docks Business School

Chau Duong

University of East London - Royal Docks Business School

Suneetha Narendran

University of East London - Royal Docks Business School

Date Written: December 10, 2016

Abstract

Most widely-used models to detect earnings management rely on firms’ characteristics, but they fail to consider the profile of top managers such as chief executive officers. Since chief executive officers have overall responsibilities for the performance of firms, they possibly influence financial statements which present the financial performance, financial position and cash flows of their firms. Based on empirical evidence, this research constructs a composite score, namely PSCORE, to signal the presence of earnings management. PSCORE requires data mostly collected from the curriculum vitae of CEOs, therefore it could be advantageous compared to other empirical measures of earnings management. PSCORE has nine factors which cover the financial expertise, reputation, internal power and age of CEOs. We find that PSCORE is positively correlated with discretionary accruals, abnormal cash flows, abnormal production costs, abnormal discretionary expenditures, and deviations of the first digits of figures reported in financial statements from what are expected by Benford’s Law. The associations between PSCORE and the other established proxies remain statistically significant after controlling for key determinants of earnings management such as equity issuance, corporate governance factors and firm characteristics. The findings have some implications for practitioners, especially external auditors and board of directors.

Keywords: Earnings Management Detection Models, Benford's Law, Chief Executive Officers, Reputation, Financial Expertise

Suggested Citation

Nguyen, Tri and Duong, Chau and Narendran, Suneetha, Using the Profile of CEOs to Detect Earnings Management (December 10, 2016). Available at SSRN: https://ssrn.com/abstract=2883503 or http://dx.doi.org/10.2139/ssrn.2883503

Tri Nguyen (Contact Author)

University of East London - Royal Docks Business School ( email )

4-6 University Way
London, E16 2RD
United Kingdom

Chau Duong

University of East London - Royal Docks Business School ( email )

4-6 University Way
London, E16 2RD
United Kingdom

Suneetha Narendran

University of East London - Royal Docks Business School ( email )

4-6 University Way
London, E16 2RD
United Kingdom

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