Overview and Summary Findings of the Gender Equity Salary Study May 2nd, 2018

Historical Faculty Salary Equity Analysis at UB The University of Buffalo has continually monitored their internal salary structure for evidence of inequitable treatment, particularly among gender groups of faculty members. 2009 & 2011 – it was persistent in both studies that average received salaries were comparable between male and female faculty members after taking into account work-related factors. 2017 – the university again undertook an internal salary equity study to address possible presence of inequities associated with gender. A unique shared-governance approach was adopted in which both faculty and professional staff undertook the study together. Prior studies were undertaken only by professional staff without faculty input. GESS 2018

Committee Charge The Gender Equity Salary Study (GESS) Committee was jointly appointed by the University Provost and the Chair of the Faculty Senate to assess whether there is statistically significant inequity in ladder faculty salaries by gender at the University at Buffalo. Gender equity in salaries is a reasonable expectation of everyone at the University at Buffalo. Factors that should be considered in order to assess salary equity should be factors that may be expected to impact salary differences. GESS 2018

GESS Committee Co-Chairs Craig Abbey – Associate Vice President and Director of Institutional Analysis Glenna Bett – Chair of the Faculty Senate Committee on Equity and Inclusion, Associate Professor, Obstetrics and Gynecology, Jacobs School of Medicine and Biomedical Sciences Peter Elkin – Chair of the Faculty Senate Committee on Budget Priorities, Professor and Chair, Biomedical Informatics, Professor of Internal Medicine, Jacobs School of Medicine and Biomedical Sciences Sharon Nolan-Weiss – Director, Office of Equity, Diversity and Inclusion, Title IX and ADA Coordinator GESS 2018

GESS Committee Members Sharmista Bagchi-Sen – Professor, Geography Rajan Batta, – Associate Dean for Faculty Affairs, Human Resources & Diversity, School of Engineering and Applied Sciences Lucinda Finley – Professor, Law Brenda Moore – Associate Professor, Sociology Neel Rao – Assistant Professor, Economics Gregory Wilding – Professor, Chair, Biostatistics GESS 2018

Specific Aims The focus of the internal equity study was twofold: Determine if there is a statistically significant difference in the pay of tenured and tenure-track faculty (ladder) by gender when controlling for academic rank, time in rank, rank at hire and department affiliation. Determine if there is a statistically significant difference in the pay of tenured and tenure-track faculty (ladder) by gender when controlling for academic rank, time in rank, rank at hire and market factor discipline when comparing the salaries to a national database of academic salaries by discipline. GESS 2018

Statistical Methods A Hierarchical Linear Model and Regression analysis were the statistical procedures used in this study and are most often used by researchers in the field to measure unexplained wage differences for gender. Regression analysis provides information about the average percent difference in salaries between male and female faculty members and whether this change is significantly different from a zero percent (0%) difference. A 5% significance level was used for this study. This is considered a standard significance level for this type of study. GESS 2018

Statistical Models Model 1 – Departmental Salary Comparison This model tests for gender differences in ladder faculty pay conditional on Current academic rank Initial rank Time in rank Department affiliation Model 2 – Discipline Salary Comparison Discipline-specific salary market factor GESS 2018

Stakeholder Input October 19th, 2017 was held on South Campus It was important to the Committee to provide the UB Community with an opportunity to review the proposed methodology, ask questions, and provide suggestions and feedback. The method was presented to the Faculty Senate Executive committee then the full Faculty Senate where feedback was obtained. Faculty were invited to attend either of two Town Hall meetings where the GESS study was discussed. October 19th, 2017 was held on South Campus October 23rd, 2017 was held on North Campus Faculty were also invited to provide feedback by email. A Frequently Asked Questions (FAQ) has been created to address commonly asked questions pertaining to UB’s Gender Equity Salary Study. GESS 2018

Dataset – Study Group Inclusion Criteria All ladder faculty including full professors, associate professors and assistant professors Primary unqualified appointments with FTE of 1.0 State faculty title and annualized base state salary only Exclusion Criteria Faculty with qualified title (e.g. clinical, research, visiting) All Geographic Full-Time (GFT) faculty All Educational Opportunity Center (EOC) faculty All librarians Tenured faculty serving in an administrative capacity GESS 2018

Data Collection University at Buffalo - Human Resources Data Collection All human resources data was collected from Payroll 17 of the 2016-2017 academic year. Market Factor Data Collection The 2016-2017 Oklahoma State University Salary Study by Discipline, a national sample of average faculty salaries by discipline, was used to assign corresponding market factors based on discipline and rank. GESS 2018

Faculty Demographics Gender and Rank Distributions Rank Female Male Total Assistant 94 165 259 Associate 144 214 358 Professor 105 320 425 343 699 1042 Ethnicity/Race Distributions American Indian/Alaskan Native 5 Asian 238 Black or African American 23 Hispanic 34 Multiple Races 8 White 734 Total 1042 GESS 2018

Unadjusted Gender Pay Gap Comparison Gender Pay Gap is the difference in the average man's and average woman's remuneration without accounting for other differences. Group Male Female Gap ($) Gap (%) Overall All Public Doctoral $102,331 $81,174 -$21,157 -21% University at Buffalo $122,774 $105,144 -$17,630 -14% Full Professors $133,468 $119,761 -$13,707 -10% $151,809 $139,037 -$12,772 -8% Associate $91,354 $84,997 -$6,357 -7% $103,259 $94,700 -$8,559 Assistant $80,858 $73,741 -$7,117 -9% $91,774 $83,283 -$8,491 Source: All Public Doctoral from Academe March/April 2015, UB from human resource data.

Faculty Salary Distribution

Faculty Salaries Before Regression Analysis 25th Percentile, Median, 75th Percentile Assistant Professor Associate Professor Professor 25th Percentile Median 75th Percentile Female $66,865 $72,792 $92,825 $80,046 $87,558 $104,561 $111,716 $127,430 $155,972 Male $71,398 $91,270 $94,911 $83,536 $94,926 $116,943 $120,065 $142,743 $177,185 GESS 2018

Contribution of Variables to Base Differences in Salaries Variables Considered Remaining Difference in Salaries by Gender Female – Male Salaries Difference Amount Accounted For Gender - $17,630 Departments - $8,393 $9,237 Current Rank - $3,498 $4,895 Rank at Hire - $1,407 $2,091 Time in Rank + $119 $1,526 Underrepresented Minority Status + $60 - $59

Contribution of Variables to Total Explained Variance R-squared is statistical measure of how close the data fits the model. It can be interpreted as the percentage of explained variance. In general, the higher the R-squared value the better the model fits the data. But the R-square will generally increase as additional predictors are added to the model even by chance, so an adjusted R-squared value is generally preferred. The adjusted R-square value is adjusted for the number of predictors in the model. It will increase only if new predictors improve the model fit.

Gender + Component R-squared   Base Salary Ln Base Salary Model Variables Adjusted R2 Gender 0.036 0.042 Gender + Market Factor 0.596 0.694 Departments 0.444 0.452 Current Rank 0.388 0.448 Rank at Hire 0.323 0.314 Time in Rank 0.173 0.201 URM Status 0.037 0.043

Overall Results – Market Factor Model Base Salary Unstandardized Coefficients p-value Ln Base Salary Gender -1,951.04 0.273 -0.012 0.322 Market Factor 0.816 <0.001 0.857 Is Professor 2016 -5,436.58 0.069 -0.071 0.001 Is Associate 2016 -658.62 0.762 -0.009 0.555 Rank at Hire Professor 36,016.84 0.217 Rank at Hire Associate 4,031.68 0.074 0.040 0.010 Time in Rank 452.37 0.004 URM Status -129.81 0.976 -0.005 0.866 Gender x URM Status 2,798.04 0.654 0.028 0.518   Adjusted R2 0.670 0.745 N 1042

Unstandardized Coefficients Overall Results – Department Model Model Base Salary Unstandardized Coefficients p-value Ln Base Salary Gender 60.56 0.970 -0.001 0.933 Departmental Effects 85 Departments   Is Professor 2016 44,023.72 <0.001 0.404 Is Associate 2016 12,956.68 0.146 Rank at Hire Professor 30,641.73 0.192 Rank at Hire Associate 5,858.36 0.005 0.056 Time in Rank 594.91 URM Status 6,553.35 0.081 0.049 Gender x URM Status 441.21 0.934 0.001 0.969 Adjusted R2 0.770 0.828 N 1042

Model Fit Results – Market Factor Model Base Salary Ln Base Salary Model Variables   Adjusted R2 Δ Adjusted R2 1 Gender 0.036 - - 0.410 2 0.595 0.559 0.693 0.652 Market Factor 3 0.600 0.005 0.694 0.001 Current Rank 4 0.664 0.064 0.735 0.041 Rank at Hire 5 0.670 0.006 0.745 0.010 Time in Rank 6 <0.001 URM Status

Model Fit Results – Department Model Base Salary Ln Base Salary Model Variables   Adjusted R2 Δ Adjusted R2 1 Gender 0.036 - - 0.041 2 0.394 0.358 0.403 0.362 Department 3 0.715 0.321 0.782 0.379 Current Rank 4 0.759 0.044 0.814 0.032 Rank at Hire 5 0.769 0.010 0.827 0.013 Time in Rank 6 0.771 0.002 0.828 0.001 URM Status

Outlier Analysis In order to assess the impact of faculty salaries considered outliers at each end of the salary range, a residual analysis was done. In each model, a total of 17 faculty members were identified as outliers with 7 faculty members considered outliers within both regression models. Each model was re-run excluding the outliers and the results did not change. There was no statistically significant effect for gender. GESS 2018

Discussion After controlling for the effects of current academic rank, time in current rank, rank at hire, departmental affiliations, or discipline market factors, the unexplained wage gap between male and female faculty members varied between 0.1% and 1.3% and was not statistically significantly different (p=0.933 departmental model and p=0.322 salary market factor model). Likewise, there was no evidence of a systemic pay bias against faculty in underrepresented race/ethnicity categories relative to non-underrepresented faculty. Work-related factors such as rank, experience, and discipline have an effect on pay and were statistically significant. GESS 2018

Limitations Study did not analyze salaries of non-tenure track, EOC, GFT and librarian faculty Study does not address differences in promotion and tenure rates between men and women Study did not consider research productivity and professional achievement other than academic rank Study considered only state base salary, therefore excluding compensation from Also Receives, the Research Foundation, UB Foundation or other sources. The study did not address any differences in rank at hire between men and women Individual cases of gender bias may not show up in population-based statistics GESS 2018

How UB Addresses Individual Cases UB’s Office of Equity, Diversity and Inclusion will address individual reports of salary inequity under UB’s Discrimination and Harassment Policy. Contact info: (716) 645-2266 (phone), diversity@buffalo.edu (email) In addition to gender and race/national origin, EDI will investigate salary disparities on any basis covered by law (ex. age, disability, sexual orientation) Process Confidential meeting with EDI representative Data review analyzing the salaries of similarly-situated colleagues Follow-up meeting with reporting party to review the data If the reporting party decides to move forward, EDI will meet with the chair/dean for an explanation of any salary differentials Resolution or an explanation of why a resolution is not supported by the evidence.

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