Income and Wage Gaps: How Occupational Segregation Fuels Gender Pay Disparities

Two people work the same hours, in the same city, with similar qualifications. At the end of the month, one takes home noticeably less than the other. The single most consistent predictor of who earns less is gender. The wage gap is not a quirk of individual contracts but a structural pattern shaped by where women are funnelled in the labour market, what their work is considered to be worth, and which doors quietly stay closed. Understanding this requires looking at occupational segregation, the crowding hypothesis, and how India compares with the rest of the world.

What the wage gap actually measures
Decomposing the gap
Occupational segregation: the engine of inequality
Why segregation happens
The crowding hypothesis explained
Crowding in the Indian labour market
Devaluation: the second layer
Global wage comparisons
Where India stands
What closing the gap would require

What the wage gap actually measures

The gender wage gap is the difference between what men and women earn, usually expressed as a percentage of male earnings. It can be calculated as a raw (unadjusted) gap or as an adjusted gap that controls for education, experience, hours and industry. Both numbers matter. The raw gap shows the lived reality of household incomes, while the adjusted gap isolates what cannot be explained by observable characteristics, a portion economists often attribute to direct discrimination.

In India, the Periodic Labour Force Survey is the primary source of wage and employment data. According to PLFS 2023-24, the female labour force participation rate rose to 41.7 percent, up from 23.3 percent in 2017-18, while male participation stood at 78.8 percent. Participation is improving, but earnings have not caught up. The World Economic Forum’s Global Gender Gap Report 2024 ranks India 129th out of 146 countries overall, with the economic participation and opportunity sub-index particularly weak.

Decomposing the gap

Economists typically split the wage gap into two components. The first is the explained portion, attributable to differences in education, work experience, hours and the type of industry workers are in. The second is the unexplained portion, which captures discrimination and unobserved factors. A study using NSSO data applied the Blinder-Oaxaca decomposition method and found that a substantial part of the Indian wage gap is driven by occupational segregation combined with direct discrimination, with employer-controlled factors like industry assignment producing the largest unexplained component.

Occupational segregation: the engine of inequality

Occupational segregation refers to the uneven distribution of men and women across jobs and sectors. It has two faces. Horizontal segregation is when women dominate certain sectors (teaching, nursing, garment work, domestic help) and men dominate others (construction, transport, engineering, finance). Vertical segregation is when women cluster at the lower rungs of an organisation even within the same sector, blocked from senior or leadership positions by what is often called the glass ceiling, with a sticky floor trapping low-wage women in the most precarious roles.

In India, this layering is sharp. Women remain underrepresented in higher-paying domains like technology, engineering and finance, and concentrated in lower-paying caregiving and administrative roles. Even within information technology, an industry considered modern and meritocratic, women make up only a small fraction of senior positions. The pattern repeats across sectors: women enter, but mostly at the bottom.

Why segregation happens

Segregation is rarely the result of free choice. It builds up through interlocking pressures. Social norms assign caregiving and domestic responsibilities primarily to women, pushing them towards jobs perceived as flexible or “feminine.” Educational tracking nudges girls away from STEM and trades. Employer bias, both conscious and unconscious, favours men for roles considered demanding or technical. Safety concerns, transport limitations and the absence of childcare make many workplaces effectively inaccessible. The result is that women cluster in a narrow band of occupations long before any wage is negotiated.

The informal sector deepens the divide. A large share of Indian working women are in informal or precarious employment, where labour laws are weakly enforced and wages remain low. As PLFS data has repeatedly shown, the rise in female workforce participation has been driven largely by rural women entering self-employment, agriculture and own-account work, none of which guarantee steady wages or social protection.

The crowding hypothesis explained

The crowding hypothesis is a foundational idea in feminist economics, developed most influentially by economist Barbara Bergmann in the early 1970s. Originally applied to racial discrimination in the United States in a 1971 paper, Bergmann extended it in 1974 to gender. The model is elegant: if women are systematically excluded from a wide range of occupations and pushed into a narrow subset of “female” jobs, the labour supply in those few occupations swells. Standard supply-and-demand logic then does the rest. With more workers competing for the same crowded roles, wages in those occupations fall. Meanwhile, in the occupations from which women are excluded, the labour supply is artificially restricted and wages stay elevated.

This is what economists mean when they say the wage gap is structural rather than purely individual. As later analyses of Bergmann’s work explain, occupational segregation by sex came to be seen as a major determinant of the gender disparity in wages because crowding benefits some groups by reducing competition for the most desirable occupations.

Crowding in the Indian labour market

The crowding logic helps explain why teachers, nurses, anganwadi workers, ASHA workers, garment stitchers and domestic helpers in India earn so little despite the social importance of their work. These occupations are not low-paid because the work is easy or unskilled; they are low-paid because they have been historically coded as women’s work, and the supply of women funnelled into them is large relative to demand. Sex-typing of jobs creates a self-reinforcing cycle: jobs done by women are paid less, which signals they are less valuable, which discourages men from entering, which keeps the supply of women high.

Public health workers offer a stark example. ASHA workers, who form the backbone of rural healthcare delivery, are overwhelmingly women and are paid honorariums rather than salaries. Their work is essential, the demand for it is enormous, and yet pay remains modest because the role is structured as “voluntary” care work.

Devaluation: the second layer

Crowding alone is not the full story. There is also the devaluation hypothesis, the idea that work itself is valued less simply because women do it. Historical examples make this visible. Secretarial work, bank clerking and elementary school teaching were once male-dominated and relatively well-paid. As women entered these fields in large numbers, wages stagnated and prestige declined. The skills did not change; the gender composition did.

Global wage comparisons

Globally, no country has closed the gender gap entirely. The 2024 Global Gender Gap Report estimates that at current rates of progress it will take 134 years to reach full parity, with the economic participation gap alone requiring an estimated 152 years to close. Iceland leads the rankings, with 93.5 percent of its overall gender gap closed, followed by Finland, Norway, Sweden and Germany. South Korea, despite being a high-income economy, has one of the widest pay gaps in the OECD.

The patterns are remarkably consistent across countries even when levels differ. UN analyses point out that men earn more than women in most countries and nearly all industries because of persisting occupational segregation, disruptions to women’s careers due to motherhood, unequal sharing of family responsibilities and lower pay in female-dominated sectors. The same drivers appear in Stockholm and in Siliguri, just with different magnitudes.

Where India stands

India’s economic participation gap is wider than that of most peer economies. The World Economic Forum has ranked India poorly on economic opportunity for several consecutive years. Cross-country research finds that crowding of women into particular occupations also reduces the overall labour share of income from GDP growth, meaning workers as a whole share less in economic expansion when segregation is high. Closing the gap is therefore not just a gender justice question but a macroeconomic one.

Policy responses exist on paper. The Equal Remuneration Act of 1976 and the Code on Wages of 2019 mandate equal pay for equal work. MGNREGA prescribes equal wages for men and women in public works. But enforcement is uneven, particularly in the informal economy where most working women are employed. As the WEF notes, only about one in five economies that legislate equal pay have also implemented mechanisms to actually redress the gap.

What closing the gap would require

Reducing occupational segregation demands intervention on several fronts at once. Skilling programmes need to actively push women into non-traditional, higher-paying sectors rather than reinforcing care and craft tracks. Childcare infrastructure has to be treated as economic policy, not welfare. Workplace safety laws need genuine enforcement so that distance and timing stop functioning as exclusion mechanisms. Pay transparency, already mandated in parts of the European Union, gives workers the information to challenge unequal pay. And the social devaluation of care work must be addressed directly, through both wages and public recognition.

None of this is quick. But the data is now clear enough that the question is no longer whether occupational segregation drives the wage gap. It is how long societies are willing to wait before treating that finding as a basis for action.

What do you think? If wages in female-dominated occupations like nursing or teaching were raised significantly, would that reduce the wage gap or simply shift the segregation pattern? And in your own field of study or work, where do you see the early signs of crowding beginning to shape who ends up earning what?

References

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Income and Wage Gaps: How Occupational Segregation Fuels Gender Pay Disparities

Table of Contents

What the wage gap actually measures 🔗

Decomposing the gap 🔗

Occupational segregation: the engine of inequality 🔗

Why segregation happens 🔗

The crowding hypothesis explained 🔗

Crowding in the Indian labour market 🔗

Devaluation: the second layer 🔗

Global wage comparisons 🔗

Where India stands 🔗

What closing the gap would require 🔗