Benchmarking executive compensations: exploring fresh perspectives on chief executive officer (CEO) compensation drivers in major US corporations

Document Type

Article

Version Deposited

None (link only)

Open Access Funding Source

Other

Publication Date

Summer 6-2024

Publication Title

Benchmarking: An International Journal

DOI

https://doi.org/10.1108/BIJ-03-2024-0208

Abstract

Purpose

This study aims to contribute to the ongoing assessment of executive compensation by investigating the nexus between managerial entrenchment factors, adopting a multifaceted perspective encompassing both economic and non-economic dimensions.

Design/methodology/approach

This research employs pooled cross-sectional Ordinary Least Squares (OLS) regression and Least Squares with Dummy Variables (LSDV) models with fixed effects to examine the determinants of Chief Executive Officer (CEO) compensation.

Findings

This research identifies firm size, performance (via ROA and Tobin’s Q), and CEO characteristics (age, tenure, stock ownership, MBA degree) as significant determinants of executive compensation at the 0.05 level. In contrast, the prestige of educational institutions, doctoral degrees, and the MBA’s relevance to short-term performance, along with CEO tenure, do not significantly affect pay. Additionally, the study highlights the significance of industry type (manufacturing vs technology) in shaping compensation, emphasizing the role of firm metrics and CEO credentials in designing executive pay packages.

Originality/value

This research introduces an innovative approach to controlling unobserved heterogeneity and adjusting for the dynamic nature of CEO compensation attributes across diverse CEO characteristics. By integrating both pooled Ordinary Least Squares (OLS) and Least Squares Dummy Variable (LSDV) models, the study addresses the challenges posed by time-invariant variables and unobservable heterogeneity. Such issues have historically skewed the accuracy of traditional OLS models in identifying the comprehensive array of factors—both economic and non-economic—that influence CEO compensation. This novel methodological framework significantly advances the examination of unobservable variables that may vary not only across the firms selected for analysis but also over time periods, thereby offering a more detailed understanding of the determinants of CEO pay.

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