Female Education And Workforce Participation (PLFS 2017–18 To 2023–24): Evidence From The U-Shaped Worker Population Ratio In India

Policy Update

Shruti Sethi

Background

Since the introduction of Periodic Labour Force Survey (PLFS) by the Ministry of Statistics and Programme Implementation (MoSPI), India’s female labour force participation rate (LFPR) has risen sharply from 23.3 per cent in 2017-18 to 41.7 per cent by 2023-24. LFPR counts women who are either working or actively looking for work. This article looks at a related but different number: the Worker Population Ratio (WPR), which counts only women who are actually employed. WPR is the number PLFS publishes broken down by education level, and it answers the question that matters most for policy, not whether a woman is looking for work, but whether she has found it.

A common assumption is that more schooling should simply mean more women working. The data tells a different story. When female WPR is broken down by education level, it does not rise in a straight line. It is high among women with little or no schooling, falls through middle and secondary school, hits its lowest point among women who finished higher secondary school, and then climbs again among graduates and postgraduates. This is a U-shaped curve, and it says something important: a woman’s education does not simply predict whether she works. It predicts what kind of work is available to her at each stage of schooling.

This pattern is well known in the literature on Indian labour markets. Goldin (1994) first identified a version of it as a general feature of how women’s work changes as economies develop, and later studies confirmed it for India specifically. What has been less clear is whether the pattern holds up year after year, or whether it was a feature of a particular time period. This article uses the complete education-wise female WPR series from all seven PLFS annual reports, from 2017-18 through 2023-24, to answer that question directly.

The Theoretical Foundation: From Development Economics to the Indian Case

Goldin (1994) proposed that the relationship between economic development and female labour force participation follows a U-shape at the level of whole economies: participation is high in poor, agrarian societies where women work out of necessity on family land, falls as economies industrialise and production moves into factories where female wage work carries social stigma, and rises again only once economies reach a level of development where white-collar and service-sector jobs which are considered socially acceptable for women, become widely available. This account was central to Goldin being awarded the 2023 Nobel Prize in Economic Sciences “for having advanced our understanding of women’s labour market outcomes” (Royal Swedish Academy of Sciences, 2023).

Key Stages of the U-shaped curve

Stage 1: Agrarian Economy. Female participation starts high. Women work extensively in family farming and unpaid agricultural labour, driven by economic necessity rather than choice. Because home and workplace are not clearly separated in an agrarian household, this work carries little social stigma.

Stage 2: Industrialisation. Participation falls. Production moves out of the home and into factories, and rising household income (as men’s industrial wages grow) reduces the economic need for women to work. At the same time, wage work outside the home, particularly in low-status factory or manual jobs, carries social stigma for women in many households, especially those seeking to signal rising status.

Stage 3: Service Economy. Participation rises again. White-collar, clerical and professional jobs become available and are considered socially acceptable for educated women, drawing them back into paid work. As the Indian evidence in this article shows, however, this recovery is not automatic: it depends on the formal, salaried job market actually growing fast enough to absorb educated women, which is precisely where the PLFS data suggest India is falling short.

Figure 1: A conceptual illustration of Goldin’s theoretical U-curve, showing the mechanism at each stage of economic development.

Source: Author’s construction, illustrating the theoretical framework described in Goldin (1994).

Applied within a single country to individual women rather than across economies, the same logic produces an education-specific version of the curve. Klasen and Pieters (2015), using decades of Indian survey data through 2009-10, found that urban Indian women with little or no education participate at relatively high rates driven by economic necessity, that participation falls through middle and secondary schooling as rising household income removes the need to work while the social respectability of available jobs remains low and that participation recovers only among graduates who gain access to salaried, white-collar employment.

Both studies relied on data ending around 2009-10 or shortly after. The PLFS series, running from 2017-18 to 2023-24, offers a chance to ask whether the pattern they identified has persisted, weakened or changed shape over the past decade and a half, including through a period of rapid overall growth in female WPR and a pandemic-driven disruption to the urban labour market.

The Evidence: Seven Years, The Same U-shaped Curve

Table 1 presents female Worker Population Ratio by highest level of education completed, for persons aged 15 years and above, across all seven PLFS annual reports (from 2017-18 to 2023-24). The pattern is not an artefact of any single year. In every one of the seven rounds, WPR falls in an unbroken sequence from Not Literate through Higher Secondary, and rises in an unbroken sequence from Higher Secondary through Post-Graduation. Higher Secondary is the trough in every year without exception.

Table 1: Female Worker Population Ratio (%) by education level, usual status (ps+ss), persons aged 15 and above, all-India.

Level of Education Completed	2017-18	2018-19	2019-20	2020-21	2021-22	2022-23	2023-24
Not Literate	27.7	29.1	36.8	40.3	40.4	44.6	50.4
Literate & Upto Primary	24.9	27.3	32.8	37.9	39.2	42.1	50.2
Middle	16.9	19.3	24.4	27.8	27.3	33	37.8
Secondary	13.7	14.5	18	20	19.9	25.4	28.5
Higher Secondary	11.4	12	15.8	16.9	18.2	21.3	23.9
Graduation	21.2	21.3	24.1	23.5	25.8	28.1	30.5
Post-graduation	34.5	35.5	38.1	37.3	36.8	40.5	39.6

Source: Author’s Compilation of Data from PLFS Annual Reports, 2017-18 to 2023-24, Ministry of Statistics and Programme Implementation, Government of India

Figure 2: The U-shape repeats every year while shifting upward. The trough at Higher Secondary holds its position across all seven rounds even as the overall curve rises.

Source: Author’s construction, based on data from PLFS Annual Reports 2017-18 to 2023-24, Ministry of Statistics and Programme Implementation, Government of India.

Beyond confirming that the U-shape is structural rather than incidental, the full time series makes visible two dynamics that a single cross-section cannot show.

First, the absolute gap between the least-educated and the most-constrained group is widening even as both groups’ participation rises. The distance between Not Literate and Higher Secondary WPR was 16.3 percentage points in 2017-18; by 2023-24 it had grown to 26.5 points. In relative terms, however, the gap has narrowed slightly. Not Literate WPR was 2.43 times Higher Secondary WPR in 2017-18, falling to 2.11 times by 2023-24. Every education tier is gaining, but the least-educated tier is gaining somewhat faster in relative terms, even as it pulls further ahead in absolute percentage points.

Second, and more strikingly, the size of the post-secondary recovery is shrinking. The rise from the Higher Secondary trough to the Post-Graduate peak was 23.1 percentage points in 2017-18; by 2023-24 it had fallen to 15.7 points, a decline of nearly a third. This is the same phenomenon Klasen and Pieters (2015) identified using pre-2010 data, where they observed the graduate-level rebound weakening over successive NSS rounds.

The PLFS series shows that this weakening has continued, and arguably accelerated, in the years since. If rising education were, on its own, sufficient to draw women into salaried employment, the rebound at the top of the education ladder should be holding steady or growing as female higher-education enrolment expands. Instead it is contracting, which points to a demand-side constraint, a shortage of the specific salaried, socially sanctioned jobs that educated women are willing and able to take, rather than a supply-side one.

Rural-Urban Differences in the U-Curve

The all-India figures in Table 1 combine rural and urban women, but the underlying PLFS statements report the two separately, and the difference between them is substantial. Female Worker Population Ratio by education level, for persons aged 15 years and above for 2023-24, for rural India has been represented by Table 2 and for urban India by Table 3.

Table 2: Female Worker Population Ratio (%) by education level, usual status (ps+ss), persons aged 15 and above, rural India.

Level of Education Completed	2017-18	2018-19	2019-20	2020-21	2021-22	2022-23	2023-24
Not Literate	29.1	30.7	39.4	43.5	43.7	48.1	54.7
Literate & Upto Primary	26.0	29.8	36.3	42.6	43.4	46.4	56.7
Middle	18.3	21.0	27.4	31.7	30.6	37.3	43.3
Secondary	15.6	17.2	21.6	23.8	23	30.3	34.3
Higher Secondary	12.5	13.8	18.1	19.3	20.9	25.8	29.4
Graduation	18.6	18.4	21.1	23.5	25.7	28.3	31.5
Post-graduation	31.1	31.5	38.3	38.1	35.3	42.2	39.8

Source: Author’s Compilation of Data from PLFS Annual Reports, 2017-18 to 2023-24, Ministry of Statistics and Programme Implementation, Government of India

Table 3: Female Worker Population Ratio (%) by education level, usual status (ps+ss), persons aged 15 and above, urban India.

Level of Education Completed	2017-18	2018-19	2019-20	2020-21	2021-22	2022-23	2023-24
Not Literate	21.6	21.9	25.2	25.5	24.0	26.1	29.8
Literate & Upto Primary	21.7	20.6	23.6	24.7	26.5	27.7	31.9
Middle	13.8	15.9	17.8	18.3	18.8	21.6	23.7
Secondary	10.6	9.9	12.0	13.1	13.8	15.2	17.4
Higher Secondary	9.9	9.5	12.7	13.1	13.8	14.0	14.7
Graduation	22.8	23.1	26.0	23.6	25.9	28.1	29.8
Post-graduation	35.7	36.8	38.1	36.9	37.4	39.6	39.5

Source: Author’s Compilation of Data from PLFS Annual Reports, 2017-18 to 2023-24, Ministry of Statistics and Programme Implementation, Government of India

Figure 3: The rural U-curve rises sharply and consistently across all seven years, with the entire curve, including the trough, shifting upward year after year.

Source: Author’s construction, based on data from PLFS Annual Reports 2017-18 to 2023-24, Ministry of Statistics and Programme Implementation, Government of India.

Figure 4: The urban U-curve, plotted on the same scale as Figure 3, barely moves. The trough in particular stays close to the same level across all seven rounds, the clearest visual evidence of the urban stagnation this section describes.

Source: Author’s construction, based on data from PLFS Annual Reports 2017-18 to 2023-24, Ministry of Statistics and Programme Implementation, Government of India.

Two findings emerge from comparing the rural and urban series across all seven years.

First, the urban trough is far more stagnant than the rural one. Urban Higher Secondary WPR moved only from 9.9 per cent in 2017-18 to 14.7 per cent in 2023-24, a rise of 4.8 points. Rural Higher Secondary WPR, by contrast, moved from 12.5 per cent to 29.4 per cent over the same period, a rise of 16.9 points which is more than three times as large. This all but reproduces, in more recent data, the specific finding Klasen and Pieters (2015) built their paper around: female labour force participation in urban India is comparatively stuck, even as rural participation moves a great deal.

Second, the nationally shrinking post-graduate rebound documented earlier turns out to be a largely rural phenomenon, not an urban one. The rural rebound, from the Higher Secondary trough to the Post-Graduate peak, fell from 18.6 percentage points in 2017-18 to 10.4 points in 2023-24, a decline of 44 per cent. The urban rebound, over the same seven years, moved only from 25.8 points to 24.8 points which is essentially flat, a decline of under 4 per cent.

The national-level shrinking rebound reported earlier in this article is therefore driven almost entirely by the rural trough rising fast enough to compress the gap to the rural peak, not by any weakening of the urban recovery. The urban U-curve, on this evidence, is not so much shrinking as remaining exactly where it has been for seven years, which is itself the more concerning finding, since it means urban India’s specific bottleneck, the one Klasen and Pieters identified using pre-2010 data, has not moved in the PLFS era at all.

Why the Curve Persists

The consistency of the trough at secondary and higher secondary education, holding across seven years of rapid aggregate WPR growth, is best explained by the interaction of two forces rather than either alone. On the supply side, rising household income associated with a moderately educated woman’s family reduces the economic necessity to work, while prevailing social norms in much of India continue to treat visible wage work in low-status sectors as undesirable for a household that can now afford to keep a daughter or wife at home.

On the demand side, the sectors driving India’s urban job growth over this period i.e., construction, low-end retail and informal services, are precisely the sectors that carry this stigma, while the formal, white-collar jobs considered acceptable for secondary-educated women have not grown fast enough to absorb the rising number of school leavers each year. The shrinking post-graduate rebound suggests this demand-side constraint has, if anything, tightened rather than eased over the PLFS period.

Way Forward

Three implications follow for policymakers seeking to convert rising female education into productive employment.

First, the trough needs targeted job-linkage, not just more schooling. Since the shortfall is concentrated among secondary and higher-secondary educated women, general education expansion at this level will keep feeding women into the same bottleneck unless it is paired with placement-linked skilling and apprenticeship programmes that connect this specific group to formal employers, rather than treating all levels of education as equally job-ready.

Second, formal job creation needs to reach the sectors women are willing to enter. The sectors driving urban job growth over this period i.e., construction, low-end retail, informal services, are the ones this group avoids. Expanding formal, salaried positions in sectors already coded as socially acceptable for women, such as healthcare, education, retail chains and business process services, would do more to lift the trough than further increases in enrolment.

Third, the shrinking post-graduate rebound should be tracked as a standing indicator, not a one-time finding. A rebound that keeps narrowing year after year is an early signal that the supply of educated women is outpacing the supply of jobs suited to them. Watching this gap in each future PLFS round would give policymakers a live warning sign, well before it shows up in the headline WPR figure.

Conclusion

The relationship between female education and employment outcomes in India is not a statistical curiosity that appears in one survey year and vanishes in the next. It is a structural feature of the female labour market, present without exception in every PLFS annual report published since the survey’s inception in 2017-18. What has changed over these seven years is not the shape of the curve but its scale and slope: overall female WPR has risen substantially across every education tier, the relative depth of the mid-education trough has narrowed slightly, but the reward for reaching the top of the education ladder, the rebound that is supposed to draw educated women into work, has shrunk by nearly a third.

Closing this gap permanently will depend less on further expanding female education, which is already rising steadily across every tier, than on expanding the specific categories of formal, socially sanctioned employment that have historically been the binding constraint on educated Indian women’s work.

References

Goldin, C. (1994). The U-shaped female labor force function in economic development and economic history (NBER Working Paper No. 4707). National Bureau of Economic Research. https://www.nber.org/system/files/working_papers/w4707/w4707.pdf

Klasen, S., & Pieters, J. (2015). What explains the stagnation of female labor force participation in urban India? The World Bank Economic Review, 29(3), 449–478. https://documents1.worldbank.org/curated/en/466621488434287942/pdf/112477-JRN-PUBLIC-WBER-2015-29-3-what-explains-the-stagnation-of-female-labor-force-participation-in-urban-india-Copy.pdf

Ministry of Statistics and Programme Implementation. (2019, May 31). Annual report: Periodic Labour Force Survey (PLFS), 2017-18. Government of India. https://www.mospi.gov.in/sites/default/files/publication_reports/Annual%20Report%2C%20PLFS%202017-18_31052019.pdf

Ministry of Statistics and Programme Implementation. (2020, June 4). Annual report: Periodic Labour Force Survey (PLFS), 2018-19. Government of India. https://www.mospi.gov.in/sites/default/files/publication_reports/Annual_Report_PLFS_2018_19_HL.pdf

Ministry of Statistics and Programme Implementation. (2021, July 23). Annual report: Periodic Labour Force Survey (PLFS), 2019-20. Government of India. https://mospi.gov.in/sites/default/files/publication_reports/Annual_Report_PLFS_2019_20F1.pdf

Ministry of Statistics and Programme Implementation. (2022, June 14). Annual report: Periodic Labour Force Survey (PLFS), 2020-21. Government of India. https://www.mospi.gov.in/sites/default/files/publication_reports/Annual_Report_PLFS_2020%2021_0.pdf

Ministry of Statistics and Programme Implementation. (2023, February 24). Annual report: Periodic Labour Force Survey (PLFS), 2021-22. Government of India. https://www.mospi.gov.in/sites/default/files/publication_reports/AnnualReportPLFS2021-22F1.pdf

Ministry of Statistics and Programme Implementation. (2023, October 9). Annual report: Periodic Labour Force Survey (PLFS), 2022-23. Government of India. https://www.mospi.gov.in/sites/default/files/publication_reports/AR_PLFS_2022_23N.pdf

Ministry of Statistics and Programme Implementation. (2024, September 23). Annual report: Periodic Labour Force Survey (PLFS), 2023-24. Government of India. https://www.mospi.gov.in/sites/default/files/publication_reports/AnnualReport_PLFS2023-24L2.pdf

The Royal Swedish Academy of Sciences. (2023). The Prize in Economic Sciences 2023: Popular science background — History helps us understand gender differences in the labour market. https://www.nobelprize.org/uploads/2023/10/popular-economicsciencesprize2023.pdf

About The Contributor

Shruti Sethi is a Research & Editorial Intern at IMPRI. She holds a bachelor’s degree in Economics from St. Xavier’s University, Kolkata. Her research interests include Gender & Labour Economics.