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This section provides a general overview of some analytical methods that could be used in a pay gap analysis. Analytical methods are categorized as either exploratory and prescriptive, where exploratory methods may be useful for preliminary, “first round” of analysis. Prescriptive analysis allows the researcher to quantify the degree of gender inequity within a given facet of the pay gap, which may be useful for establishing a monetary remedy.

Descriptive analysis

A thorough descriptive analysis of the administrative data can be an incredibly useful aspect of a pay gap study. While many insights from descriptive analysis could also be gleaned form other analytical techniques, descriptive analysis should not be overlooked. It can help the researcher identify potential mechanisms driving the overall pay gap (both pay and employment inequities), which can inform the planning of subsequent analysis and the specification of regressions. It can also help the researcher identify factors that drive gender pay disparities, allowing the committee to focus its analysis on areas that contribute largely to the pay gap.  

A descriptive analysis could examine counts of faculty, or mean and median salary through cross-tabulation of variables relevant to compensation: gender, rank, discipline/department, years of experience, age, etc. Sub-populations of the faculty can also be examined along a salary distribution, and distributions of men and women can be compared.

Blinder-Oaxaca Decomposition

The method seeks to decompose the difference in average salaries of men and women to identify the drivers of the pay gap.

There are many variations on this method, but the general method requires the researcher to estimate two regressions where salary is regressed onto variables that capture the determinants of salary.12 In one regression, only men are included, and the other uses only salary data of women. The results of the regressions are then compared to determine to what extent the gap is determined by the “explainable” factors, which are included in the regressions, or “unexplainable” factors which suggest the presence of pay inequity.

This method may be useful for understanding the contributors of the overall pay gap and their relative magnitude, allowing the committee to identify areas where potentially large employment inequities exist. A technical description of the method can be found in Brown and Troutt’s paper examining gender pay disparities at the University of Manitoba.13

12 Regression analysis is discussed in the section 2.4.2, “Regression analysis of salaries – pay inequity”.

13 Brown, L.K., Troutt, E.. Sex and Salaries at a Canadian University: The Song Remains the Same or the Times They Are a Changin'? Canadian Public Policy Vol. 3, Issue 3. 2017: Sex and Salaries at a Canadian University: The Song Remains the Same or the Times They Are a Changin'? | Canadian Public Policy (