How Labor Market Segmentation Affects Women Workers

Labor market segmentation is a quiet but powerful force shaping the working lives of millions of women. It divides the economy into distinct compartments, where some workers enjoy stable salaries, benefits, and growth, while others remain stuck in low-paying, insecure, and often invisible jobs. Women, in particular, are concentrated in the lower tier, and this is not by accident. Social norms, unpaid care responsibilities, weaker bargaining power, and gendered hiring patterns push them into specific kinds of work. The consequences are far-reaching, touching everything from daily wages to long-term economic security.

Understanding how segmentation shapes women’s work
Low wages and persistent earning gaps
Why the gap persists
Job vulnerability and the “first out” pattern
The fallback problem
Locked out of advanced technologies
Why skilling alone is not enough
Higher unemployment and economic vulnerability
The compounding effect on households
The policy response and the road ahead

Understanding how segmentation shapes women’s work

A segmented labor market is essentially a divided one. On one side sits the “primary” segment, with formal contracts, regular pay, social security, and a clear path for promotion. On the other side lies the “secondary” segment, marked by informality, irregular hours, low wages, and almost no protection. Most women in India find themselves in the second category. Research drawing on the Periodic Labour Force Survey shows that women’s work participation rate stands at only 22% compared to 54% for men, and even among those who work, the majority are clustered in low-paying segments.

This division does not exist in a vacuum. It is reinforced by deeply rooted social expectations that view women’s earnings as supplementary to a household rather than essential, and by the assumption that women will take time off for childbirth or caregiving. Employers often respond to these assumptions by offering women narrower roles, fewer training opportunities, and lower pay. The effect is a workforce where the doors to the better-paying segment quietly close, one by one.

Low wages and persistent earning gaps

The most visible effect of segmentation is the wage penalty. Women working similar hours and performing comparable tasks consistently take home less than men. The Self Employed Women’s Association found that the average wage of women workers was around Rs. 1,815 against Rs. 3,842 for men, a gap of more than 50%. Even in modern sectors that are often celebrated for being meritocratic, the difference is stark. Reports indicate that in the IT and software industry, women earn only 40% of what men earn, and in finance and banking, that figure is roughly 50%.

Why the gap persists

Several forces keep women’s wages depressed. First, occupational segregation funnels women into roles like domestic work, garment stitching, care services, and small-scale farming, all of which sit at the lower end of the pay scale. Second, the informal nature of these jobs means there is no contract, no minimum wage enforcement, and no collective bargaining power. The wage disparity is particularly striking in casual labour, and the earnings gap has been widening for casual workers between 2011-12 and 2017-18, a worrying sign that segmentation is hardening rather than loosening.

Third, even when women have the same qualifications as men, they are routinely paid less. Studies suggest that a significant chunk of the wage gap simply cannot be explained by education, experience, or productivity, leaving discrimination as the most plausible explanation.

Job vulnerability and the “first out” pattern

Segmentation does not just keep women’s wages low; it also makes their jobs disposable. Because women are concentrated in informal and contact-intensive industries like textiles, retail, hospitality, and domestic work, they are usually the first to be let go when the economy stumbles. The COVID-19 pandemic exposed this with brutal clarity.

According to high-frequency data analyzed by economists, 37.1% of women lost their jobs in April 2020 compared with 27.7% of men, and women made up 73% of all job losses in April 2021. A separate study tracking workers through the pandemic found that at the peak of the lockdown, nearly 53% of women lost their jobs compared with only 16% of men. By the time men’s employment had returned to almost 90% of pre-pandemic levels, women’s recovery was significantly slower.

The fallback problem

Rosa Abraham, an economist at Azim Premji University who tracked over 20,000 workers during the pandemic, captured the issue plainly. She found that when men face a major economic shock they have fallback options and can navigate into different kinds of work, but women lack that flexibility and cannot negotiate the labor market as effectively. Segmentation walls off the rest of the economy. A woman who has spent years as a tailor or a domestic worker cannot suddenly switch to delivery driving or factory machine operation, both because of skill barriers and because of social restrictions on mobility.

Locked out of advanced technologies

One of the most damaging long-term effects of segmentation is technological exclusion. When women are confined to labor-intensive, low-skill work, they miss out on the chance to learn the tools that drive productivity and higher wages. Across factories, farms, and offices, the technologies that boost output are often introduced in male-dominated parts of the workplace first, leaving women with the manual, repetitive tasks.

This pattern is visible in India’s much-celebrated tech sector. A recent industry report shows that while women make up 35-38% of the overall IT workforce, they hold only 14-16% of niche technical roles in artificial intelligence, cybersecurity, cloud computing, and programming, with a 20-25% gap in job readiness for specialised positions. The pipeline narrows at every stage. Women begin as roughly 43% of STEM graduates but their share keeps dropping as the technical demand of the job grows.

Why skilling alone is not enough

Government skilling missions have tried to plug this gap, but the structure of segmentation tends to undo the gains. Rural women’s vocational training is often limited to a narrow set of female-dominated areas like tailoring, beauty work, and food processing. Such training improves immediate economic options but reinforces traditional roles and keeps women away from non-traditional professions like information and communication technology. When training itself is segmented, the workforce that emerges from it is segmented too.

There is also a deeper digital divide at play. Women often have lower access to smartphones, the internet, and digital literacy programs. When the economy shifts towards digital platforms, fintech, e-commerce, and AI-driven services, this gap translates directly into fewer job opportunities and lower pay for women. The transition that should be a chance to leapfrog inequality instead deepens it.

Higher unemployment and economic vulnerability

The combined weight of low wages, job insecurity, and skill exclusion shows up most painfully in unemployment data. Women in India face higher unemployment rates than men in nearly every category, and the gap widens during economic downturns. Even when overall labour market indicators improve, female youth unemployment has continued to rise in recent surveys, indicating persistent gender-specific challenges.

What makes this especially worrying is the phenomenon of women dropping out of the labor force entirely. When women lose jobs in a segmented market, the next available job is often worse than the one they lost, so many simply stop looking. In March 2021, a year after the lockdown, 74% of unemployed men were actively looking for jobs compared with only 42% of unemployed women. This withdrawal from the workforce does not mean women have stopped contributing economically; rather, the unpaid work of caregiving and household labor expands to absorb their time.

The compounding effect on households

When women face higher unemployment and lower wages, the impact ripples through families. Household incomes shrink, savings dwindle, and girls in poor families are often the first to be pulled out of school when money is tight. This sets up the next generation of women for the same segmented entry into the labor market. The cycle becomes self-perpetuating, with each generation inheriting the disadvantages of the last.

From a macroeconomic perspective, the cost is enormous. Women in India represent 48% of the population but contribute only around 17% of GDP, compared with 40% in China. Closing the gender employment gap could add trillions of dollars to the economy and lift millions of households out of vulnerability.

The policy response and the road ahead

Recent legislative efforts try to address some of these issues. The Code on Wages (2019) reinforces the principle of equal pay for equal work and universalizes minimum wage coverage across both organized and unorganized sectors, which is significant for women in informal occupations. Similarly, the Occupational Safety and Health Code aims to extend protections to a wider set of workers.

However, laws alone cannot dismantle segmentation. The structures that channel women into low-paying, vulnerable, and labor-intensive work include childcare gaps, unpaid domestic burdens, mobility restrictions, and biased hiring practices. Policy needs to address these alongside wage reform. Expanding affordable childcare, training women in emerging technologies, enforcing wage protections in the informal sector, and supporting women-led enterprises are all part of the puzzle. Without coordinated action, segmentation will continue to quietly determine who earns, who learns, and who loses out when the economy shifts.

What do you think? If labor market segmentation reflects social norms as much as economic forces, can wage laws alone close the gap, or do we need to rethink how care work and skill-building are distributed across genders? And when the next economic downturn arrives, what would it take to make sure women are not, once again, the first to lose their jobs?

References

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How Labor Market Segmentation Affects Women Workers

Table of Contents

Understanding how segmentation shapes women’s work 🔗

Low wages and persistent earning gaps 🔗

Why the gap persists 🔗

Job vulnerability and the “first out” pattern 🔗

The fallback problem 🔗

Locked out of advanced technologies 🔗

Why skilling alone is not enough 🔗

Higher unemployment and economic vulnerability 🔗

The compounding effect on households 🔗

The policy response and the road ahead 🔗