The Gender Pay Gap: Normalized vs Adjusted

Pave Data Lab
September 30, 2024
3
min read

What is the gender pay gap?

The gender pay gap refers to the difference in earnings between men and women in the workforce. However, when we talk about gender pay gaps, are we really getting the full picture? Two weeks ago, I posted about the differences between the "raw" and "normalized" gender pay gap in the USA tech sector. Let's dive deeper into this crucial topic.

What is the raw gender pay gap?

The raw gender pay gap measures the overall median salary of men versus women. This is the metric you usually read about in the news and is also the basis of the EU's DEI reporting requirements. For instance, in the USA, the "raw" salary gap for women as a proportion of men's compensation is 78.06%.

What is the normalized gender pay gap?

The normalized gender pay gap accounts for job level and function, providing a more nuanced view of pay disparities. In the USA, the "normalized" salary gap is 95.24%.

How is the normalized gender pay gap calculated?

The normalized gender pay gap is calculated by comparing salaries of men and women in similar positions, with similar experience and qualifications. This method aims to isolate the impact of gender on pay, controlling for other variables.

Raw vs normalized pay gap, which one should you use?

Both metrics offer valuable insights. The raw pay gap provides an overall picture of earnings disparities, while the normalized gap helps identify potential discrimination within specific roles. It's crucial to consider both when analyzing gender pay inequalities.

European DEI Requirements

European Union regulations often focus on the raw gender pay gap for reporting purposes. However, a comprehensive approach should consider both raw and normalized figures for a more accurate assessment.

Why is there a large discrepancy between raw and normalized pay gap?

The significant difference between raw and normalized pay gaps is largely due to lower representation of women in higher-paying jobs, such as executive positions and technical R&D roles. This representation issue plays a crucial role in dragging down the "raw" pay gaps.

Gender Pay Gap by Country: Women vs Men

Let's compare the "raw" vs. "normalized" salary pay gaps around the world and investigate how dramatic the "representation" rate gaps are for women in leadership and technical positions.

Observations from around the world:

  1. Poland: Poland has a massive gap between the "raw" (53%) and "normalized" (92%) pay gap. Why? Representation plays a large hand. Only 9% of M5+ (Director+) leaders in Poland are women, and only 11% of Polish engineers are women.
  2. Brazil: Brazil stands out due to its 48% "raw" gap and 80% "normalized" gap. The normalized gap is the lowest in our study, meaning that representation is likely only one part of the problem. Interestingly, 28% of M5+ Brazilian leaders are women (much higher than Poland), but only 8% of Brazilian engineers are women – the lowest women engineering representation rate in our study.
  3. USA: The USA, while not perfect, generally shows better gender gap numbers than most countries in our study (aside from perhaps Singapore). This applies to both the normalized pay gap (95%) and women representation rates in M5+ (35%) and software engineering (19%) roles. However, there's still significant room for improvement, as a 19% women representation rate among all American software engineers remains a stark statistic.

In conclusion, focusing solely on the surface-level "raw" gender pay gap provides an oversimplified view of the gender pay gap issue. 

Representation is likely the most vital underlying cause of the gap. To address this complex issue effectively, we must consider both raw and normalized pay gaps, as well as representation rates in leadership and technical roles.

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Matthew Schulman
CEO & Founder
Matt Schulman is CEO and founder of Pave, the complete platform for Total Rewards professionals. Prior to Pave, he was a software engineer at Facebook focusing on user-centric mobile experiences. A self-proclaimed "comp nerd," Matt is known for sharing data-driven thought leadership around all things compensation and personal finance.

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