CEO Pay-For-Performance Heterogeneity Using Quantile RegressionCAHRS Working Paper Series
AbstractWe 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.
Citation InformationKevin F. Hallock, Regina Madalozzo and Clayton G. Reck. "CEO Pay-For-Performance Heterogeneity Using Quantile Regression" (2008)
Available at: http://works.bepress.com/kevin_hallock/1/