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CEO Pay-For-Performance Heterogeneity Using Quantile Regression
CAHRS Working Paper Series
  • Kevin F. Hallock, Cornell University
  • Regina Madalozzo, Ibmec Sao Paulo
  • Clayton G. Reck, CRA International
Publication Date
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.
Suggested Citation
Hallock, K. F., Madalozzo, R., & Reck, C. G. (2008). CEO pay-for-performance heterogeneity using quantile regression (CAHRS Working Paper #08-07). Ithaca, NY: Cornell University, School of Industrial and Labor Relations, Center for Advanced Human Resource Studies.
Citation Information
Kevin F. Hallock, Regina Madalozzo and Clayton G. Reck. "CEO Pay-For-Performance Heterogeneity Using Quantile Regression" (2008)
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