Millions of Women Lost Jobs in 2020 — Here’s How They’re Coming Back

March 8, 2021

Photo of smiling woman walking outside

The impact of COVID-19 has been devastating for women in the workforce. Millions lost or left their jobs, and a recent analysis revealed that while men in the United States gained about 16,000 net jobs in December 2020, women lost a net total of 156,000 jobs.

In recognition of International Women’s Day, let’s explore what our data can tell us about COVID’s impact on working women and what companies can do to empower them. “LinkedIn’s data from around the world tells a consistent story,” says Karin Kimbrough, LinkedIn’s chief economist. “Women’s hiring has proven to be more vulnerable than men’s, and COVID-19 has likely had a more damaging impact on women’s careers.” 

Today, we’ll take a closer look at that data to see how the pandemic impacted women in the workplace overall — and how it impacted some women more than others, with some stark disparities across different industries and education levels. Along the way, we’ll consider what it all means for your hiring strategy and how your company can support women every day of the year. 

The gender split of new hires returned to pre-COVID levels, but the recovery still has a long way to go

If you look at the gender split of new hires, you’ll notice the share of women dropped dramatically near the start of the pandemic. “Right away, we saw a dip in the share of women who were being hired,” Karin says.

After that massive decline from March to May, the share of women among new hires surged back almost as quickly as it fell. In fact, the global gender split of new hires in January 2021 was actually about 1% more female than it was in January 2020. 

“The share of women hired has recovered quickly, but that could in part be because so many women lost their jobs and had to find new ones,” Karin explains. “So while we’ve seen some recovery, we still have a ways to go. Companies have work to do to get more women back in the workforce globally.”

Why COVID disproportionately impacts women in the workforce

The disparity we see across genders is almost certainly a reflection of existing inequities. Before the pandemic, women performed 75% of the world’s unpaid domestic labor. That burden only grew heavier when lockdowns forced schools and childcare facilities to close: 32% of unemployed women surveyed in the United States said they weren’t working because COVID disrupted their childcare

“As a working mom, myself,” Karin says, “I think a lot of it was that women were just busy. They suddenly had kids at home, they had childcare or eldercare responsibilities. And so they were definitely pulled out of the workforce a bit.” In fact, women said they faced overwhelming workloads 20% more frequently than men did, according to the latest Employee Well-Being Report from Glint. 

For many women, the decision may also be financial. Economics professor Stefania Albanesi told The New York Times that the preexisting gender wage gap played a big role in COVID’s disproportionate impact on women. 

In two-earner households, she explains, if someone has to step away from work to shoulder extra domestic responsibilities, it's usually the partner making less money.  

With all that in mind, let’s turn to LinkedIn data to see how women are recovering at different speeds across industries and education levels — and what it means for talent professionals. 

Women in the tech industry saw the least disruption, while those in retail and travel faced the most

In retrospect, some industries were clearly better positioned than others to maintain their workforces during a pandemic.

The software industry saw relatively little disruption in the share of women hired — probably in large part because it was relatively easy for many tech workers to work from home. Back in May, 85% of workers in the software industry agreed that they can work from home effectively — more than in any other industry. We also know flexible work arrangements are particularly important to women: Our recent analysis of LinkedIn data revealed that women are 26% more likely to apply to remote jobs than men. 

Workers in the recreation/travel and retail industries were at the very bottom of that same survey, with only 37% and 29% respectively saying their industry could work effectively from home. Not coincidentally, those two sectors saw some of the biggest declines in the share of women hired.

Of course, remote work isn’t always possible for workers, especially in industries like retail or travel. Businesses in these industries were hit particularly hard by COVID, while many tech companies have seen business stay stable or even improve during the pandemic. 

There are likely many women still trying to return to the workforce from jobs they lost in these industries; recruiters shouldn’t dismiss them just because they’re coming from a different sector — less industry-specific experience doesn’t mean fewer skills

The most educated women saw the least impact — and the least educated saw the most impact

Women of all educational backgrounds saw significant declines across their shares of new hires. Still, there are stark and important disparities to highlight.

At the start of the pandemic, women without a bachelor’s degree or equivalent saw their share of hires fall 2x lower than that of women with a master’s degree or higher. 

Less educated women also saw a faster “recovery” in the gender split of new hires — but it’s important to remember that this may be because so many of them lost their jobs in March and April. And given the correlation between educational attainment and income, these women may have faced more financial pressure to quickly return to the workforce than their more educated counterparts.

Recruiters shouldn’t underestimate this talent pool, and adopting skills-based hiring practices can help ensure you don’t overlook them. Less educated doesn’t necessarily mean less capable, especially for nontechnical roles. Consider relaxing or removing requirements from your job descriptions, as women are more likely than men to decide against applying for a role if they fall short of requirements.

Final thoughts 

“While the evidence shows that countries around the world have lost ground on gender equality in the workplace, it also points to steps we can all take to fix that, starting right now,” Karin notes. 

“Employers can help by actively seeking female talent, removing any bias from job descriptions, and by offering more flexibility to allow for a better work-life balance,” she says. “These changes are key to how we recover from the damage caused by the pandemic and build equal workforces and societies.” 

And, of course, that work extends far beyond one day out of the year. 

To continue learning, you can take these select courses from LinkedIn Learning that have been unlocked through all of March 2021 in celebration of International Women’s Day. This is part of LinkedIn’s #ConversationsForChange initiative for International Women’s Day. Follow our comprehensive coverage here.

Methodology

Behavioral insights for this report were generated from the billions of data points created by hundreds of millions of members in over 200 countries on LinkedIn today. Gender identity isn’t binary and we recognize that some LinkedIn members identify beyond the traditional gender constructs of “male” and “female.” If not explicitly self-identified, we have inferred the gender of members included in this analysis by classifying their first names as either male or female or by pronouns used on their LinkedIn profiles. Members whose gender could not be inferred as either male or female were excluded from this analysis. Similarly, members whose industry or education level could not be inferred were also excluded from this analysis.

The share of female hires among new hires is the number of women who started a new job in a given month, divided by the number of men and women who started a new job in a given month. To measure the changes in the female share of new hires, the year-over-year analysis takes the difference in this measure between the given month and the same month of the previous year (e.g., the share of female hires in January 2020 is compared against the share of female hires in January 2019).

This post was co-written by Greg Lewis in collaboration with Insights Analyst Ross Murray and Economic Graph Data Scientist Jenny Ying.

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