UCI Pay Equity Study Update, 1998-99

Methodology

The 1998-99 pay equity study at UCI was conducted for general campus ladder rank faculty based on October 1998 Payroll/Personnel data combined with data from the Office of Academic Personnel. This study applied the pay equity model recommended by the American Association of UniversityProfessors (AAUP) to identify women and minority faculty members who appear to be underpaid. The Payroll/Personnel System snapshot used for this analys is included only ladder rank faculty members whowere on active pay status as of the end of October 1998. The only individuals excluded from the analysis were faculty administrators who were compensated on a fiscal-year basis instead of an academic-year basis.

The pay equity model used was assessed for its reliability inSpring 1997 by an ad hoc committee on pay equity methodology. With membership from across the campus and including representatives from the Office of Academic Affairs, the Committee on Academic Personnel, and the Faculty Women's Association, this committee determined that the model being used could be recommended as a screening device --although not as the only screening device -- for an assessment of equity in compensation at UCI.

The model is based on a least squares analysis (multivariatelinear regression) that estimates the adjusted academic-year(nine-month) salary for regular rank faculty members. The estimation equation describes the linear relationship between the predictors(independent variables) and the salaries (the dependent variable) forwhite male faculty members.

The estimation equation is included underneath each school's graph. Because the regression analysiswas conducted by academic unit, each unit's equation uses different values to calculate estimated salaries. At UCI, we used the following predictors or independent variables:

• degree indicator: an indicator of the highest degree (0 = Baccalaureate or lower; 1 = Masters; 2 = Doctorate)
• degree year: the last two digits of the year the highest degree was awarded (e.g., 87)
• year of hire: the last two digits of the year the faculty member was hired at UCI (e.g., 90)
• year of birth: the last two digits of the year of birth (e.g., 60)

The next step in applying the AAUP model was to calculate theresidual for women and minority faculty members,with residual defined as the difference between actual salary and salary predicted by the regression equation. A negative residual indicates that the salary is lower than the salaries of white males in the same academic unit who have the sameattributes.

Graphs 1-11 display the negative andpositive residuals for women and minorities from each of the academicunits, as well as those for females and minorities for the general campus. Graph 12 displays thedistribution of residuals for white males, calculated separately foreach academic unit by comparing actual salaries with predictedsalaries for all ladder rank faculty -- white males, females, andminorities.

On each graph, the X-axis indicates the size of the residual. TheY-axis indicates the number of individuals. The "-" area indicates negative residuals and the "+" area positive ones. The standard error for each academic unit, in the footnote at the bottom of each page, may be used as a measure of the significance of the residual.

Please direct questions or comments about the content of this page to Associate Executive ViceChancellor Killackey.