UCLA Department of Statistics

Executive Compensation

Methodology: Multinomial logistic regression, generalized linear mixed models, linear regression with random intercept
Client affiliation: Boston University School of Law

Analyzing data from fortune 1500 companies over two recent years for the five top executives within each company. The data includes variables both at the individual executive level and at the company level. The outcome of interest is the proportion of compensation in stock and stock options composed of stock options. We will merge data from two financial databases and fit an appropriate multilevel/repeated measures model for this data.


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