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CEO pay slice and firm value: evidence from UK panel data

Valentina V. Tarkovska (Accounting and Finance, Dublin Institute of Technology, Dublin, Ireland)

Review of Behavioral Finance

ISSN: 1940-5979

Article publication date: 10 April 2017



The purpose of this paper is to examine the relationship between CEO pay slice (CPS) – the fraction of the top five executive directors’ total compensation that is captured by the chief executive officer (CEO) – and the value of firms in the UK. Specifically, this paper examines whether CPS alters the effectiveness of board performance by influencing cooperation and cohesiveness among its members.


This paper analyses a large sample of non-financial companies listed on the London Stock Exchange from 1997 to 2010. The empirical methodology includes the analysis of panel data by using a dynamic generalized method of moments estimator.


The evidence supports social comparison theory and demonstrates that high CPS is likely to impact negatively on executive team’s spirit and motivation. However, the tournament argument is supported when a subsample of companies with CEOs close to retirement age has been analysed. In addition, the findings suggest that companies perform better after the introduction of non-binding say on pay law in the UK in 2002.

Practical implications

The results have major implications for the on-going debate on how to reform executive remuneration, and highlight the importance of considering remuneration issues at the board level, supporting the principles of UK Corporate Governance Code (Financial Reporting Council, 2010).


The results indicate that CPS can provide a useful tool for research on firm performance, and that its relation with the value of firms is an important issue to be considered in the UK context. The findings also highlight the importance of considering board-wide remuneration issues without narrowing them down simply to the details of CEO compensation.



Tarkovska, V.V. (2017), "CEO pay slice and firm value: evidence from UK panel data", Review of Behavioral Finance, Vol. 9 No. 1, pp. 43-62.



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