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 Bemidji 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 $5,729 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	49815	84	10433
M	55544	125	11801
Total	53241	209	11592

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 Instructor, Assistant Professor, Associate Professor and Professor ranks, male salaries are on average $5, $764, $1,422, and $2,973 respectively, above the female averages.

Table 2. Average 2002 Salary by Gender and Rank

rank	M/F	Mean	N	Std. Dev
professor	F	62271	24	6279
	M	65244	57	8467

associate professor	F	44916	36	4558
	M	46338	32	5334

assistant professor	F	34253	10	2498
	M	35017	8	2684

instructor	F	52177	14	4446
	M	52182	28	4546

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 White females earn less on average than the average for White males. However, the Asian and Hispanic males earn more on average.

Table 3. Average 2002 Salary by Ethnicity-Gender

ethnicity-gender	Mean	N	Std. Dev
White female	49810	82	10520
African amer female	*	1
Hispanic female	*	1
White male	55574	114	11773
Asian male	*	4
Native amer male	55690	5	17240
unknown	*	2
Total	53241	209	11592

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

B. Promotion to Academic Rank

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.

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 Bemidji in 2002 there were 28 White male Assistant Professors and 27 White male Associate Professors, with corresponding odds of 27/28 (= 0.964) of moving from Assistant to Associate rank. For White females there are 35 Assistants and 13 Associates, with corresponding odds of 13/35 (=0.371) of being Associates. The “odds ratio” of White females to White males getting promoted from Assistant to Associate is then (0.371/0.964) = 0.385; that is, White female odds of moving to Associate are only 38.5% 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 additional variables were entered into the Multinomial Regression model below, for example, the odds ratio for White females improved slightly, to 0.541 from 0.385.)

Two minority dummy variables –White females and All Minorities – 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 had to be combined as separate category.

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

		Sig.	Exp(b)=Odds Ratio
assistant to associate	White female to White male	0.180	0.541
assistant to associate	All minorities to White male	0.295	0.249

associate to professor	White female to White male	0.561	1.347
associate to professor	All minorities to White male	0.806	1.376

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 Highest Degree variable. That is, holding a doctorate completely predicts this promotion step in this data.

White females and All minorities have lower odds of promotion from Assistant to Associate than the corresponding White category, although neither of these coefficients is statistically significant. Associate to Professor shows White females and Under-represented males having better odds than the White male category, although neither coefficient is statistically significant.

In general, at least two of the control variables of Doctorate, Total MnSCU years, and Years since Highest Degree were highly significant in the equations examined here.

Since none of the promotion odds coefficients for protected classes are statistically significant, there is no statistically significant evidence from this analysis to indicate that the Academic Rank variable is “tainted.” This issue is examined further below in the regression analysis that omits the Rank variable.

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=209). 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 Native American males (N=5) to conduct an analyses using this variable, this category was entered into the model as a separate variable. The remaining African American female, Hispanic female, and 4 Asian Pacific Island males were collapsed into an Under-represented minorities category (N=6). There are sufficient White females (N=82) for a separate variable. The two (2) Unknown faculty were entered as a separate dummy variable simply to ensure that the reference category consisted of only 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 “White male” category (coded as 0) to the “White female” category (coded as 1) would be expected to have an increase (positive coefficient) in annual salary of $247, all other variables in the regression model being equal. For continuous variables, such as Years since Highest Degree, the corresponding unstandardized coefficient ($64) indicates how much each additional unit (here, a year) is worth, on average.

Table 5. Total Population Model with Ethnicity-Gender Variables.
	Unstandardized		Standardized	t	Sig.	Collinearity
	B	Std. Error	Beta	t	Sig.	Tolerance	VIF
(Constant)	57168	1205		47.430	0.000

ACCTG	8295	1848	0.120	4.488	0.000	0.644	1.553
ARTFI	1675	1847	0.031	0.907	0.366	0.395	2.533
BIOLO	1011	1434	0.020	0.705	0.482	0.551	1.814
BUSAD	4057	1666	0.067	2.435	0.016	0.600	1.666
CHEMS	853	1627

I. Executive Summary