Question: Use the data on executive compensation from Compustat in the worksheet execs.xls from the course webpage for this question. This dataset contains data on 2001 compensation for 3595 top executives for a large set of publicly traded firms. It also contains data on each person’s gender, age, job title and their company’s market value.

(a) Run a regression of salary on the gender indicator and report point estimates,

standard errors, and R-squared. Do men and women executives have different

salaries? Does gender explain a large portion of the variation in executives’ salary?

(b) Run a regression of salary on the gender indicator, age, and market value of the firm. Do men and women executives still appear to have different salaries controlling for these firm and individual characteristics?

(c) The column labeled “Job Title” contains a description of the job title held by each of the executives in the sample. Using your best judgment, define 3 or more groups of people that you think have similar job responsibilities, each with at least 30 members. Choose one group to be the base and create 2 or more indicator variables for membership in the remaining groups. Add these 2 or more group indicators to the salary regression along with the gender indicator, age, and market value of the firm. For example, suppose your groups were: anyone with the words “vice president” in their job title, anyone whose title included “CEO”, and all other jobs. You could then use “vice presidents” as the base group and define an indicator for being in the “CEO” group and another indicator for being in the “Other Job” group. Your regression would then be of salary on a constant, “CEO” indicator, “Other Job” indicator, the gender indicator, age, and market value of the firm. Report your group definitions as well as the point estimates and standard errors and R-squared from this regression. What does this regression tell you about the difference in executive salaries for men versus women?

(d) Now replicate part (c) using Total 2001 Compensation as the dependent variable. This measure of total compensation includes salary, bonus, and value of options granted in 2001. Report point estimates, standard errors, and R-square from a regression of total compensation upon a gender indicator, age, firm market value, and your job category indicators. Are your conclusions about gender differences in executives’ earnings altered by using this more inclusive measure of compensation?