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2012 | OriginalPaper | Chapter

What Are Friends for? CEO Networks, Pay and Corporate Governance

Authors : Rayna Brown, Ning Gao, Edward Lee, Konstantinos Stathopoulos

Published in: Corporate Governance

Publisher: Springer Berlin Heidelberg

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Abstract

We investigate the impact of CEO networking on compensation arrangements. Unlike existing studies that are largely based on board interlocks, we use a unique measure that calculates the direct ties the CEO has created during her life. We show that a CEO’s compensation is significantly affected by her power in the managerial labour market. We find that the size of the CEO network is positively related to the level of CEO compensation and inversely related to its pay-performance sensitivity. We interpret our results as direct evidence that managerial power influences compensation. However, in firms where shareholders rights are well protected, the impact of the CEO network over pay arrangements diminishes. This implies that outrage cost and governance reduces managerial power in pay negotiation. Overall, our results are consistent with the predictions of the managerial power approach.

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It is also acknowledged friends and social networks may influence decisions by many of the world’s companies regarding with whom and how they conduct their business (Jackson 2005).

Strong social ties link individuals who are similar and the more similar the individuals the stronger the social ties (Wegener 1991). Weak ties comprise acquaintances with whom we are less likely to be socially acquainted whereas a strong tie implies the individuals are close friends (Granovetter 1983). The issue of strong and weak ties is discussed in more detail in following sections.

See Wellman (1983) for a detailed explanation of the principles of network theory.

If Director “A” sits on a board with “B” and if director “B” sits on a board with “C” then “A” is assumed to know “C” and this link is included to the measure (Larcker et al. 2006). Whether A and C actually know each other, which will allow them to exchange information, know-how etc., is not examined. Larcker et al. (2006) fail to acknowledge this potential bias in their measure.

Recent studies that have also examined the role of social networks in an economics/financial economics context include Fracassi (2009), Burns et al. (2010), Cohen et al. (2010), Nguyen (2012), Battu et al. (2011) and Fracassi and Tate (2012), among others.

For all types of activities, apart from education, BoardEx collects data on the ties developed through board membership. Therefore even for social activities the links for the individual will be counted if she has an active role, e.g. board member of a golf club, trustee of a charitable organization.

One expects older CEOs to be more affected by the strength-of-link issue, since some of their ties might date many years back. In our sample though the mean/median CEO age is only 55 years old, with only 1 % of the observations above 70. In any case, we control in our all analyses for CEO age.

Here we refer to efficiency wages. Firms are willing to offer to specific key employees compensation which is higher than the market rate in order to reduce employee turnover.

Cohen et al. (2009) are the first to use BoardEx data to study the effect of networks in a financial economics context. They find that security analysts gather superior information about firms when they have educational links with the firms’ senior managers.

The transformation into CDFs allows us to control for extreme outliers and also facilitates the subsequent analysis on pay-performance sensitivity by helping us readily interpret the estimated coefficients in an economically meaningful way for the way in which CEO network affects the pay sensitivities at any size of the social network (Milbourn 2003, p. 253).

The g-index is that published for 2004. This variable is updated on a bi-annual basis and hence the 2004 g-index is the appropriate measure to use with 2005 data. A firm’s corporate governance policy is not expected to change substantially on an annual basis.

For example, the first figure in panel D ($18.30) is calculated using the panel B, model 4 coefficients in the following way: 25.13–0.5 × 4.34 + 0.5 × 8.65 + 0.5 × 5.68–0.5 × 3.19–0.5 × 20.46 (we don’t take into account the coefficient for CEO networking since we calculate this figure for the lowest CEO network). The difference between the first and third figure (where we assume maximum CEO networking) stems from the size of coefficient β ₂ (the coefficient of the interacted variable: dollar return × CEO Networking).

We do not use the actual number of current ties because they are bound to be correlated with the networking measure (i.e. they are part of our networking measure).

The correlation coefficient between board size and CEO networks is 21 %. Therefore board size explains 4.4 % (R ² = ρ ² = 0.21²) of the CEO networking variation.

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Title: What Are Friends for? CEO Networks, Pay and Corporate Governance
Authors: Rayna Brown
Ning Gao
Edward Lee
Konstantinos Stathopoulos
Publisher: Springer Berlin Heidelberg
Book: Corporate Governance
Print ISBN: 978-3-642-31578-7

Electronic ISBN: 978-3-642-31579-4

Copyright Year: 2012
DOI: https://doi.org/10.1007/978-3-642-31579-4_12