Detecting Managed Earnings With CEO Profiles

Earnings management is the use of managerial discretion to apply accounting standards or construct business transactions in a way that alters reports on the financial health of an organisation [1]. Earnings management can include both legitimate and illegitimate methods “to smooth earnings over accounting periods or to achieve a forecasted result.” [2] For example, in periods of good financial performance, managers may increase provisions for bad debts or for obsolete inventory to create reserves for future use. Alternatively, in periods of poor financial performance, managers may reduce or reverse those provisions to inflate reported earnings. Similarly, managers might also construct business transactions to affect reported earnings in various ways. Managers might also increase production beyond market demand (overproduction). Because fixed costs can be spread over more products, overproduction results in lower unit cost, which in turn leads to lower cost of goods sold and higher profit.

Because senior managers engage in earnings management, the academic and practitioner literature has looked at the possible influence of personal characteristics on the decision to engage in earnings management. For example, in a 2015 Wall Street Journal interview, Professor Ashiq Ali of the University of Texas at Dallas observed that new chief executive officers (CEOs) tend to manipulate earnings during the first three years in office to favorably influence the market’s perception of their abilities [3]. Another study (Francis et al.2008) [4] found that CEOs with good reputations are less likely to manage earnings, because they often have more to lose in the way of compensation, career opportunities and the like.

As stories of suspect financial behavior like earnings management proliferate, it would be interesting to see what personal characteristics seem to be associated with it. Our research builds on the existing evidence by focusing on the effect of a combination of CEO characteristics on financial reporting practices associated with earnings management. We offer the PSCORE, a composite grouping of individual characteristics linked with a higher likelihood of earnings management by prior research. We identified nine individual variables or signals from existing research to develop the PSCORE. These signals or variables can be sorted into four categories: financial expertise, personal reputation, internal power, and age. We used finance-related working experience and qualifications as the signals for financial expertise. The length and performance of a CEO’s tenure as well as how often the media mentioned the CEO were used as signals for personal reputation. The signals for internal power included information about other significant positions a CEO held in a company (e.g. chairman, founder). Age was captured from curricula vitae in the public domain disclosing the actual age and distance from retirement of a CEO.

The sample we used to test the efficacy of the PSCORE included all CEOs working for listed companies in the UK from 2005 to 2012. The findings of our analysis substantiated the predictive power of the PSCORE and suggested that personal characteristics of the CEOs were indeed significantly associated with earnings management. Specifically, we found a significant relationship between PSCORE and discretionary accruals, a measure of accrual earnings management widely used in existing research to capture the extent of discretion over flexible accounting methods and estimations to influence earnings. We also found that the PSCORE was associated with the extent to which CEOs would exercise their preferences on real business decisions to influence reported earnings, such as changing sales policy, production volume, and level of research and development expenses and so on. We measured the manipulation of business transactions by estimating abnormal cash flows, abnormal production costs, and abnormal discretionary expenses and found that the PSCORE was associated with all of these earnings management practices. We also found that the marginal effects of PSCORE were higher on real earnings management than on accrual earnings management. Anomalous accounting numbers as stipulated by Benford’s Law [5] were also associated with the PSCORE.

Based on our findings, we suggest that the PSCORE could be a useful risk indicator of CEO tendencies to engage in earnings management. The PSCORE also highlights the need to take into account the possible associations between individual difference variables and CEOs’ earnings management decision making. While the scope of our research did not permit a granular analysis of the type of influence exerted by individual differences, it has served to flag the existence of statistically significant associations between personal characteristics of CEOs and earnings management practices.

In addition, as the data used to construct PSCORE was obtained from the curricula vitae of CEOs available in the public domain, the data collection was fairly straightforward. If the PSCORE is used as a risk indicator, the users can use the simple checklist of signals provided by the PSCORE to identify the risk-related signals and suggest flag that the reported earnings on financial statements might need further scrutiny. The PSCORE therefore could be a useful risk indicator for investment professionals, boards of directors, auditors, regulators, and others who need a simple way to identify risks of earnings management. It also has potential as an even more nuanced and sophisticated tool that can identify and regulate earnings management risks.


[1] Healy, P. M., and Wahlen, J. M. (1999). A Review of The Earnings Management Literature and Its Implications for Standard Setting. Accounting Horizons, 13(4), 365-383.

[2] See the post by Ira Millstein, Financial Times, May 26th 2005. Available at:

[3] See the post by Toddi Gutner, Wall Street Journal, February 22nd 2015. Available at:

[4] Francis, J., Huang, A. H., Rajgopal, S., & Zang, A. Y. (2008). CEO Reputation and Earnings Quality. Contemporary Accounting Research, 25(1), 109-147.

[5] See the post by Derryck Coleman, Audit Analytics, October 20th 2014. Available at:

This post comes to us from Tri Nguyen, a PhD candidate and teaching assistant at the University of East London’s Royal Docks School of Business and Law, Dr. Chau Duong, a senior lecturer at the Royal Docks School of Business and Law, and Professor Sunitha Narendran, the director of research at the Royal Docks School of Business and Law. The post is based on their article, “Using The Profile of CEOs to Detect Earnings Management,” available here.