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dc.contributor.authorHallock, Kevin F.
dc.contributor.authorMadalozzo, Regina
dc.contributor.authorReck, Clayton G.
dc.date.accessioned2020-11-25T14:55:42Z
dc.date.available2020-11-25T14:55:42Z
dc.date.issued2008-07-29
dc.identifier.other653698
dc.identifier.urihttps://hdl.handle.net/1813/77373
dc.description.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.
dc.language.isoen_US
dc.subjectExecutive compensation
dc.subjectquantile regression
dc.subjectpay and performance
dc.titleCEO Pay-For-Performance Heterogeneity Using Quantile Regression
dc.typepreprint
dc.description.legacydownloadsWP08_07.pdf: 1673 downloads, before Oct. 1, 2020.
local.authorAffiliationHallock, Kevin F.: kfh7@cornell.edu Cornell University
local.authorAffiliationMadalozzo, Regina: Ibmec Sao Paulo
local.authorAffiliationReck, Clayton G.: CRA International


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