Quirks of the raw Gender Pay Gap

Published March 2026

 

Your raw Gender Pay Gap is 0% - time to celebrate? Sometimes you want your figures to show a 'zero' value. For instance, an inbox without unread messages may inspire a sigh heavy with relief. However, the e-mail reminder about the upcoming mandatory corporate-training deadline might have been read – and then quickly forgotten. Just like deceptively empty inboxes, the 0% raw Gender Pay Gap figure can mask underlying troubles.

 

The raw Gender Pay Gap ("rGPG") reflects pay differences across genders and allows for statements such as “On average, for every 1€ a male employee receives, a female employee receives [XX] cents”. Importantly, the rGPG is strongly influenced by pay distribution and workforce composition. This can lead to counterintuitive outcomes.

 

Consider the following example:

 

 

Gender

Employee Count

Average Pay

rGPG

Department A

Male

7

€20

10%

Female

5

€18

Department B

Male

3

€40

15%

Female

5

€34

Group

Male

10

€26

0%

Female

10

€26

 

Notes regarding the table:

  • The rGPG is calculated as
    (average pay men – average pay women) / average pay men = rGPG
  • In Department A, each male employee receives an hourly pay of €20 and
    each female employee receives an hourly pay of €18.
  • In Department B, each male employee receives an hourly pay of €40 and
    each female employee receives an hourly pay of €34.
  • The group average is calculated across the combined employee population of Departments A and B.
    The average pay for male employees is calculated on an individual-level basis across departments:
    ((7x€20) + (3x€40))/10=€26.
    The average pay for female employees is calculated on an individual-level basis across departments:
    ((5x€18) + (5x€34))/10=€26.

 

 

These results illustrate Simpson’s paradox, a specific form of aggregation bias: a zero overall rGPG (at the group-level) can mask department-level gaps due to employee distribution effects.

 

 

This does not mean the rGPG lacks value. It remains an important diagnostic indicator. However, it is a high-level metric and should never be interpreted in isolation. Robust Gender Pay analysis requires deeper segmentation, structural review, and contextual interpretation.

 

Further examples of how rGPG figures can mask structural differences are explored in my book The Equal Pay Guide – a practical framework for understanding, explaining, and managing Gender Pay, Equal Pay, Pay Equity & Pay Transparency”.

 

If you would like to conduct rigorous Gender Pay analyses and translate insights into impactful actions, you can find more information here - link to The Equal Pay Guide (available on multiple Amazon marketplaces)