CEO Pay-For-Performance Heterogeneity Using Quantile Regression

We provide some examples of how quantile regression can be used to investigate heterogeneity in pay‐firm size and pay‐performance relationships for U.S. CEOs. For example, do conditionally (predicted) high‐wage managers have a stronger relationship between pay and performance than conditionally low‐...

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Bibliographic Details
Published in:The Financial review (Buffalo, N.Y.) N.Y.), 2010-02, Vol.45 (1), p.1-19
Main Authors: Hallock, Kevin F., Madalozzo, Regina, Reck, Clayton G.
Format: Article
Language:English
Subjects:
Chief executive officers
Executive compensation
J33
M52
pay and performance
Pay for performance
quantile regression
Regression analysis
Studies
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Summary:We provide some examples of how quantile regression can be used to investigate heterogeneity in pay‐firm size and pay‐performance relationships for U.S. CEOs. For example, do conditionally (predicted) high‐wage managers have a stronger relationship between pay and performance than conditionally low‐wage managers? Our results using data over a decade show, for some standard specifications, there is considerable heterogeneity in the returns‐to‐firm performance across the conditional distribution of wages. Quantile regression adds substantially to our understanding of the pay‐performance relationship. This heterogeneity is masked when using more standard empirical techniques.
ISSN:0732-8516
1540-6288
DOI:10.1111/j.1540-6288.2009.00235.x