I. Faculty Salary Equity Analysis

A. Brief Description of Average Faculty Salary Differentials by Gender and Ethnicity

The first three tables reported in this section are intended to provide a very brief indication of the variation in average 2002 yearly salaries across ethnic and gender groupings of Mankato State faculty. Explaining as much of this variation in salary as possible, using additional background factors such as academic rank and length of service, is the focus of this report.

1. Faculty Salary By Gender

Table 1 shows a $9,182 shortfall in average annual salary for female relative to male faculty. Several factors that account for much of this difference will be discussed below.

Table 1. Average 2002 Salary by Gender

M/F	Mean	N	Std. Dev
F	49605	239	10990
M	58787	316	13320
Total	54833	555	13171

2. Faculty Salary By Gender and Rank

One major factor that affects faculty salary differences is Academic Rank. Table 2 reports average annual salaries broken out by Gender and Rank. At the Assistant Professor, Associate Professor, and Professor ranks, male salaries are on average $3,503, $2,253, and $5,210, respectively, above the female averages. Female Instructors earn on average $2,364 than Male Instructors.

Table 2. Average Salary by Rank and Gender

Rank	M/F	Mean	N	Std. Dev
Professor	F	63195	45	7125
	M	68405	141	8413

associate professor	F	56848	52	7844
	M	59101	69	9359

assistant professor	F	45352	105	4410
	M	48855	86	7399

Instructor	F	34964	37	3664
	M	32600	20	2514

3. Faculty Salary By Gender and Ethnicity

Table 3 reports average salary differences broken out by a combination of Gender and Ethnicity. Again, this table shows substantial salary differences in average salaries across these groupings. Comparing the average salary for White males to the other averages reveals that they earn more on average than all other categories except Asian Pacific Island males.

Table 3. Average Salary by Ethnicity-Gender

ethnicity-gender	Mean	N	Std. Dev
white female	49485	221	11066
african amer female	*	3
asian female	55530	8	12745
hispanic female	*	3
native amer female	*	3
white male	58732	276	13238
african amer male	*	3
asian male	62911	26	11692
hispanic male	55603	8	13679
Unknown	*	4
Total	54833	555	13171

* Data are omitted if less than five faculty members within a grouping.

B. Promotion to Academic Rank

We note that this analysis uses current data patterns within campus to assess odds ratios for promotion. This analysis did NOT examine actual rates of promotion acceptance and rejection within a campus, as this data were not available for analysis. That is, we analyzed only the current distribution of faculty within ranks, broken out by ethnicity-gender. For example, at Mankato there are 71 White male Assistant Professors and 60 White male Associate Professors, with corresponding odds of 60/71 (=0.845) of moving from Assistant to Associate rank. For White females there are 94 Assistants and 45 Associates, with corresponding odds of 45/94 (=0.479) of moving to Associate. The “odds ratio” of White females to White males getting promoted from Assistant to Associate is then (0.479/0.845) = 0.566; that is, White female odds of moving to Associate are only 56.6 % of the White male odds. The multinomial Logistic regression model adjusts these odds ratios to take into account the effects of other variables that might factor into promotion decisions, such as highest degree, previous experience, length of service, etc. When these variables were added to the Multinomial Logistic regression model, the White female to White male odds changed slightly, from 0.566 to 0.531 (see Table 4 below).

Table 4 shows the estimated odds ratios of promotion from Assistant Professor to Associate Professor and from Associate Professor to Professor obtained using the Multinomial Logistic Regression model. The odds ratios were calculated after controlling for Highest Degree, Years of Prior Experience, and Length of Service. Odds ratios greater than 1.0 indicate a correspondingly greater likelihood for individuals in the indicated category in obtaining promotion to the next category. Conversely, odds less than 1.0 indicate less likelihood.

Three to five protected class dummy variables – Asian females, White females, Asian males, Under-represented females, and Under-represented males – were included in predicting odds of promotion to higher rank. Because categorical modeling cannot handle groupings with very low frequency for combinations of attributes (e.g. African American + female + associate professor), all minority groupings are combined as separate category.

Table 4. Odds of Promotion to Higher Rank by Gender and Ethnicity

		Sig.	Exp(b)=Odds Ratio
assistant to associate	Asian Female to White male	0.551	1.599
assistant to associate	White female to White male	0.020	0.531
	Asian male to White male	0.523	1.461
	Under-rep female to White male	0.965	1.036
	Under-rep male to White male	0.879	0.872

associate to professor	White female to White male	0.018	0.513
associate to professor	Asian male to White male	0.978	1.015
	Under-rep male to White male	0.858	1.201

Table 4 shows the odds of promotion and associated statistical significance levels for protected classes as compared to White males. There is no analysis for promotion from Instructor to Assistant Professor since there is “complete separation” on the Doctorate variable: that is, holding a doctorate completely predicts this promotion. Assistant to Associate and Associate to Professor promotions show White females have lower odds ratios than the corresponding White male reference category, and both odds ratios are very statistically significant.

In general, one or more of the control variables –Total MnSCU years, Doctoral Degree, and Prior Experience --were statistically significant in each equation examined here.

The promotion odds coefficients for White females for both the Assistant to Associate and Associate to Professor steps indicate that the Academic Rank variable may be “tainted.” This finding will be examined below, where the Total Population Model is re-estimated after dropping the Rank variables.

C. Controlling Salary For Structural Factors: Multiple Regression Analysis

1. Total Population Salary Analysis – with and without the Academic Rank variable.

Table 5 reports the estimated regression equation and auxiliary statistics for the Total Population Analysis (N=555). In this model, the dependent variable is 2002 Annual Salary, and the predictor variables are all of the structural variables plus a set of dummy variables corresponding to ethnic minority and gender status. Since there are sufficient numbers of Asian males (N=26) and females (N=8) to conduct an analyses using these variables, these categories were entered into the model as separate variables. The African American and Hispanic males were collapsed into an Under-represented male category (N=11). The Hispanic, Native American, and African American females were collapsed into an Under-represented females category (N=9). There are sufficient White females (N=221) for a separate variable. There are 4 unknowns. The reference category is thus White males.

The first column of Table 5 shows the labels of each of the variables entered into the regression model. The first term (constant) can be ignored. Each of the other terms in the first column corresponds to either a “structural” variable or one of the ethnicity-gender variables.

The second column in Table 5 shows the “unstandardized coefficient” B associated with each variable, which indicates the average amount by which each faculty member’s salary increases (or decreases) for a one unit change in the corresponding variable, all of the other variables in the equation being held constant. In the case of a dummy variable, the one unit change is from the omitted reference category (coded as 0) to the corresponding category (coded as 1). So, for example, the coefficient for White females in the second column indicates that an individual moving from the reference “White male” category (coded as 0) to the “White female” category (coded as 1) would be expected to have a decrease (negative coefficient) in annual salary of $590, all other variables in the regression model being constant. For continuous variables, such as Years in current rank of Professor, the corresponding unstandardized coefficient ($700) indicates how much each additional unit (here, a year) is worth, on average.

Table 5. Total Population Model With Ethnicity-Gender Variable.


	Unstandardized		Standardized	t	Sig.	Collinearity
	B	Std. Error	Beta	t	Sig.	Tolerance	VIF
(Constant)	58986	1033		57.113	0.000

I. Executive Summary