Placing a gender lens on the economic impacts of the pandemic

The COVID-19 pandemic spotlighted the importance of applying a 'gender lens' when it comes to the analysis of economic impacts and the design of economic policy.

In a recent paper, co-authored with Dr Angela Jackson and published in the Australian Journal of Labour Economics, we analyse the workforce impacts of the pandemic through a gender lens.

Here's a snapshot of our key findings and takeaways lessons.

Several factors raised concerns that the pandemic would exacerbate gender gaps in economic outcomes

Many of the industries that were most affected by the pandemic containment measures were female-dominated or large employers of women.

The shift to home-schooling and working-from-home brought the risk of reinforcing traditional household roles, with women predominantly taking on the unpaid domestic work and carer roles and men prioritising their breadwinner role.

Government policy responses predominantly supported male-dominated sectors.

Many of the occupations that experienced intensified work pressures during the pandemic – such as nurses, aged care, mental health and education – are female-dominated. This presented a higher risk of mental health distress, burnout and attrition among the female workforce.

These factors meant that the pandemic poses the risk of stalling – or even unravelling – progress in closing existing gender gaps in Australia’s workforce.

Women were over-represented in job losses

By May 2020, around 472 000 fewer women and 371 000 fewer men were in employment in the Australian workforce, compared to pre-pandemic numbers. The gender differential was particularly stark in Victoria.

Summing up total losses employment over the first year of the pandemic, the pandemic saw 2,003,373 lost months of employment among women, compared to 1,708,022 lost months of employment among men. Relative to their 47% share of the Australian workforce before the pandemic, women were over-represented among these employment losses.

By far, it was younger women (aged 15 to 24 years) who shouldered the largest employment losses.

Placing a gender lens on some of the hardest-hit sectors and cohorts:

• Retail trade is the fourth-largest industry of employment for women, and is fairly gender-balanced in composition. Three months into the pandemic, there were 73,000 fewer women employed in retail compared to pre-pandemic levels, yet only 11,300 fewer men.
• Accommodation and food services is the fifth-largest employer of women and is also fairly gender-balanced in composition. But by November 2020, there were 65,800 fewer women employed in accommodation and food services, compared to pre-pandemic levels, while men’s jobs had fallen by only 33,500.
• Among Professionals, there were 47,000 fewer women in employment by the end of the May 2020, compared to only 7,500 fewer men.
• Job losses were largest among women with lower educational qualifications. By May 2020, women with no post-school qualifications had experienced a net loss in employment of 258,000 jobs, compared to 147,700 lost jobs among men.

Women were more likely than men to absorb the economic shock of the pandemic by withdrawing from the labour force completely, moreso than moving into unemployment. Women made up 64% of the cumulative fall in labour force participation numbers throughout the first year of the pandemic.

This reflected the additional caring, housework and home-schooling responsibilities that the pandemic created for households, and the power of gender norms in determining which members of the household were expected to respond to these needs.

But haven't women's employment numbers now recovered?

Assuming that these economic impacts are no longer a concern because employment has climbed back to pre-pandemic levels ignores the reality that any interruptions to a person's workforce attachment can have longer-term repercussions.

Any time spent out of the workforce brings a depletion of skills, a loss of social connections and networks, and weaker future job prospects. Interruptions to employment are not just about a loss of earnings, but the psychological costs of economic insecurity and a higher likelihood of mental health distress.

For many women who lost employment or stepped out of the workforce during the pandemic, it's not guaranteed that they will step back into new jobs that match their previous earnings and skills levels. Experiencing a break in employment can also mean losing the continuity of service required for eligibility for certain employment entitlements such as parental leave.

All these factors add up to disproportionately more women than men facing setbacks and stalled progress in their economic opportunities and outcomes.

We also need to be cautious about measuring economic recovery simply in terms of employment numbers. Under-employment rates – having a job but insufficient hours – are persistently higher among women. Pay rates, working conditions, job security, and safe and respectful workplaces, are all important markers of economic progress.

Applying a gender lens makes for better policymaking?

The process of assessing the ways that an economic shock or policy proposal can have different economic implications for men and women makes for more robust policymaking. Using the insights of gender impact analysis to inform policy design is a best practice approach recognised internationally as Gender Responsive Budgeting.

It's a way that governments can instil the principle of gender equity into the policymaking process, and ensure that investments in gender equality initiatives are not being undone by other policies elsewhere in the government's budget.

In the paper, we compare the policy responses of the Victorian Government and Australian Government in terms of the extent to which their policies responded to the gender-patterned impacts of the pandemic.

To understand the impacts of other demographic characteristics, we need better data

Due to the compounding factors of disadvantage and discrimination, the economic impacts of the pandemic are expected to have been more severe among single parents, Aboriginal and Torres Strait Islander women, women living with a disability, LGBTIQ women, migrant women, women from culturally and linguistically diverse backgrounds, and women in lower socioeconomic circumstances.

Gender-patterned impacts need to be further analysed through an intersectional lens to account for the influence of these other important demographic and socioeconomic characteristics. However, the lack of the systematic and comprehensive collection of data further disaggregated according to these dimensions is a barrier to more responsive policymaking. This is an area in need of further attention and action.

Our full paper is freely available as an open-access article from the Australian Journal of Labour Economics - here's the direct link to paper.