This blog is the first in a series that will explore different variables that should be part of any pay equity analysis. The technique for pay equity analysis is regression (see this blog for more details about the methods). The way that regression works is you put in variables that you believe/want to explain the outcome variable. For pay equity analyses, the outcome variable is pay. The variable you do not want to explain pay differences is gender; because if gender explains pay differences, then you have discriminatory pay practices.
Every variable you put into the regression analysis should be something you believe can explain pay differences. And it is good to express that belief as a hypothesis.
I hypothesize that if you compare the pay of two employees – one who has been in their current job for years and one who has just started in that job – that the employee that has been in their current job longer will have higher pay. This is an example of a variable that could explain why two employees with the same role have pay differences.
There are other variables that can explain pay differences. Stay tuned for the next variable in a future blog.