Deeper data analysis key to fixing gender gap

By Killian Plastow
 — 1 minute read

Government policy makers need to explore retirement income data in more depth and look beyond superannuation balances when trying to fix the gender gap in retirement income adequacy, according to Willis Towers Watson.

Drawing on the Department of Social Services’ Household, Income and Labour Dynamics Australia (HILDA) data, Willis Towers Watson noted marital status impacted the adequacy of retirement income of individuals aged 25 to 64 based on the Association of Superannuation Funds Australia (ASFA) retirement standards, particularly for women.

Speaking to InvestorDaily, Willis Towers Watson senior consultant Jackie Downham said households comprised of couples, including married, de facto and same-sex relationships, were more likely to reach the ASFA ‘comfortable’ standard than their single peers.


“When we look at males and females who are part of a couple compared to singles, then their combined median projected retirement income is about 2 per cent above the ‘comfortable’ ASFA standard,” she said.

The ASFA comfortable retirement standard for those aged around 65 at the June quarter 2016 was an annual household income of $43,062 for singles, and $59,160 for couples.

Median projected retirement income was 15 per cent below this standard for single men and 23 per cent below for women, Ms Downham said.

“We thought it was important to really look at the gender gap based on marital status as opposed to just looking at males and females in isolation, because that sort of indicates that females who are a part of a couple are on track to achieve a comfortable retirement standard,” she said.

Ms Downham explained that while Willis Towers Watson weren’t advocating for changes to policy, this research highlighted the importance of exploring data in more depth to identify and understand where gaps in retirement income adequacy exist.

“By actually looking a bit deeper in to the data rather than just saying ‘superannuation account balances for females are significantly below that of males’ tells you a different story,” she said.

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Deeper data analysis key to fixing gender gap
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