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CEO Pay‐For‐Performance Heterogeneity Using Quantile Regression
Author(s) -
Hallock Kevin F.,
Madalozzo Regina,
Reck Clayton G.
Publication year - 2010
Publication title -
financial review
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.621
H-Index - 47
eISSN - 1540-6288
pISSN - 0732-8516
DOI - 10.1111/j.1540-6288.2009.00235.x
Subject(s) - quantile regression , econometrics , wage , quantile , economics , distribution (mathematics) , regression , regression analysis , statistics , labour economics , mathematics , mathematical analysis
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.