The rural-urban divide in female labour force participation

Why in the News

The Periodic Labour Force Survey (PLFS) 2025 records a significant increase in the Female Labour Force Participation Rate (FLFPR) since 2020, following the COVID-19 pandemic. The overall rate for women aged 15 years and above rose from 30 per cent in 2019-20 to 40 per cent in 2025. The increase was far more pronounced in rural areas, where the rate rose from 33 per cent to 45.9 per cent, against a rise from 23.3 per cent to 27.7 per cent in urban areas. The tension the data raises is that the pace of improvement, measured as the Average Annual Percentage Point (AAPP) change, cannot be read on its own, since a State with a low pace may already sit at a high level of participation.

What is the Female Labour Force Participation Rate?

1. Definition: The Female Labour Force Participation Rate is the ratio of women in the labour force to women of working age, taken as 15 years and above.
2. What counts as participation: The labour force includes women who are employed and women who are unemployed but seeking or available for work, so the rate moves when women enter or leave the search for work, not only when they find it.
3. What it leaves out: Unpaid domestic work and unpaid caregiving inside a woman’s own household are not counted as labour force participation, so a large volume of work sits outside the measure by construction.

How large is the rural-urban gap in the headline numbers?

1. The national rate rose by ten percentage points: Female labour force participation for those aged 15 and above moved from 30 per cent in 2019-20 to 40 per cent in 2025.
2. Rural India accounts for most of the gain: The rural rate rose from 33 per cent to 45.9 per cent, a gain of about 12.9 percentage points across the period.
3. Urban India moved far less: The urban rate rose from 23.3 per cent to 27.7 per cent, a gain of about 4.4 percentage points, under half the pace of the rural gain in percentage point terms.
4. The gap widened rather than closed: Rural participation began roughly 9.7 percentage points above urban participation and ended about 18.2 percentage points above it.
5. The divergence is what needs explaining: This substantial rural-urban difference is what warrants a more granular, State level analysis rather than a single national figure.

Which States improved fastest in rural areas?

1. Seven States beat the national rural pace: West Bengal (3.68), Uttar Pradesh (3.64), Gujarat (3.38), Odisha (3.28), Bihar (3.23), Rajasthan (3.06) and Haryana (2.62) recorded Average Annual Percentage Point change above the all-India rural average, in percentage points per year between 2019-20 and 2025.
2. The middle band sat below the average: Madhya Pradesh (2.42), Tamil Nadu (2.06), Keralam (1.96), Punjab (1.80), Jharkhand (1.71), Chhattisgarh (1.48) and Andhra Pradesh (1.36) recorded change below the national rural average.
3. The slowest group still improved: Karnataka (1.20), Uttarakhand (1.18), Maharashtra (0.58), Telangana (0.48) and Goa (0.30) registered the smallest positive annual changes.
4. All five southern States sat below the rural average: Tamil Nadu, Keralam, Andhra Pradesh, Karnataka and Telangana all recorded change below the all-India rural figure, alongside Madhya Pradesh, Punjab, Jharkhand, Chhattisgarh, Uttarakhand, Maharashtra, Goa and Himachal Pradesh.
5. One State went backwards: Himachal Pradesh recorded a marginally negative change of -0.02 percentage points a year, which is notable because nearly 90 per cent of its population resides in rural areas.

Which States improved fastest in urban areas?

1. Two States cleared two percentage points a year: Rajasthan (2.30) and Gujarat (2.26) recorded particularly sturdy improvements in urban female participation.
2. Seven more beat the urban average: Uttarakhand (1.88), Keralam (1.76), Chhattisgarh (1.22), Karnataka (1.20), Odisha (1.12), Bihar (1.10) and Andhra Pradesh (0.94) recorded change above the all-India urban average.
3. The remainder fell below it: Tamil Nadu (0.76), Telangana (0.66), Jharkhand (0.64), Punjab (0.60), Uttar Pradesh (0.54), West Bengal (0.48) and Maharashtra (0.36) recorded change below the national urban average.
4. Strong urban gains occurred despite a slower overall pace: Several States recorded relatively strong gains even though the overall pace of improvement in urban areas was considerably lower than in rural areas.
5. The urban leaders are not the rural leaders: West Bengal and Uttar Pradesh led the rural table and sat near the bottom of the urban one, so a State’s rural performance does not predict its urban performance.

Why is pace alone an incomplete measure?

1. It measures speed, not level: The Average Annual Percentage Point change captures only the pace of change and does not consider the level of female labour force participation from which a State started.
2. A low pace can sit on a high level: A State with a lower annual change may already have a relatively high participation rate, so a low figure is not automatically a poor outcome.
3. The baseline has to be combined with the pace: Reading the 2019-20 rate for each State together with its annual change is what allows a State to be assessed properly.
4. It is not a ranking device: The measure is used to indicate the pace of improvement and is not intended to rank States against one another.
5. Himachal Pradesh shows why the pairing matters: Its marginally negative change is read against a rural population share of nearly 90 per cent, which places the figure in context rather than treating it as a simple last place.

What does the rural baseline-pace map show?

1. Low baseline with faster improvement: Bihar, Uttar Pradesh, West Bengal and Haryana started with relatively low female participation but recorded change above the all-India average, indicating a relatively faster pace of improvement.
2. Low baseline with slower improvement: Goa and Punjab started from relatively low baseline levels and recorded change below the national average, indicating slower improvement despite having considerable scope to grow.
3. High baseline with faster improvement: Odisha, Gujarat and Rajasthan started with relatively higher baseline rural participation and still recorded above average change, showing that faster improvement is not confined to States starting from a low base.
4. High baseline with slower improvement: Madhya Pradesh, Jharkhand, Uttarakhand, Chhattisgarh, Maharashtra, Himachal Pradesh and the five southern States had relatively higher baseline levels but recorded change below the national average.

What does the urban baseline-pace map show?

1. Low baseline with faster improvement: Rajasthan, Gujarat, Uttarakhand and Bihar started from relatively low baseline levels and recorded change above the all-India average.
2. Low baseline with slower improvement: Uttar Pradesh, Jharkhand, Haryana and Punjab also started from relatively low levels but recorded below average change, indicating slower improvement.
3. High baseline with faster improvement: Keralam, Karnataka, Chhattisgarh, Odisha and Andhra Pradesh already had relatively higher urban participation and continued to make relatively rapid gains.
4. High baseline with slower improvement: Tamil Nadu, Telangana, West Bengal, Maharashtra, Madhya Pradesh, Himachal Pradesh and Goa recorded slower improvement despite their relatively higher starting levels.

Challenges to raising the Female Labour Force Participation Rate

1. The rise is concentrated in low productivity work: Most of the increase sits in self-employment, home based work and unpaid family labour, which raises participation without raising earnings. Eg. Over 64 per cent of working women are self-employed and nearly 64 per cent of working women are in agriculture. Fix. Link Self Help Group producers to the Open Network for Digital Commerce so household enterprise output reaches priced markets rather than local thrift.
2. Unpaid care work caps available hours: Domestic and caregiving responsibility absorbs the working day before paid work is considered, which pushes women toward part time and proximate options. Eg. Women spend 363 minutes daily on unpaid work against 123 minutes for men. Fix. Raise care economy investment toward 2 per cent of Gross Domestic Product, which is estimated to create around 11 million jobs held largely by women.
3. Mobility constraints narrow the job set: Unsafe transport and inadequate childcare restrict how far a woman can travel for work, so employers outside walking distance are effectively unavailable. Eg. Preference for nearby work pushes rural women into home based employment even where factory jobs exist in the district. Fix. Fund working women’s hostels and last mile transport on the Tamil Nadu Thozhi hostel model in industrial districts.
4. Formal sector entry stays narrow: Manufacturing and much of services remain male dominated, so women who enter the labour force do not enter the formal payroll. Eg. Women are 43 per cent of Science, Technology, Engineering and Mathematics graduates but only 14 per cent of the corresponding workforce. Fix. Attach a minimum female workforce ratio as a qualifying condition for Production Linked Incentive disbursal.
5. Hiring costs are loaded onto the employer: Statutory maternity cost sits entirely with the firm, which discourages some employers from hiring women of working age. Eg. The 26 week paid maternity leave entitlement, though progressive, can discourage some firms from hiring women. Fix. Move maternity benefit funding to a shared employer and social insurance pool rather than a single employer liability.
6. Pay gaps blunt the incentive to stay: Women earn less than men for comparable work, which lowers the return on staying in the labour force after a break. Eg. India ranked 131st of 148 countries in the Global Gender Gap Report 2025. Fix. Enforce the equal remuneration provisions of the Code on Wages, 2019 through mandatory gender disaggregated pay reporting above a firm size threshold.

Conclusion

Female labour force participation has risen substantially since 2019-20, but the gain is rural rather than national, and the rural-urban gap has widened rather than narrowed. The State picture cannot be read off the pace of change alone: Bihar, Uttar Pradesh, West Bengal and Haryana are improving fast from a low rural base, while the five southern States are improving slowly from a high one, and both readings are correct. The unresolved question is composition, since a rise driven by self-employment and unpaid family work raises the participation rate without raising women’s earnings. Whether the trend converts into better outcomes depends on the movement of women into paid, formal and urban employment, which is exactly where the data shows the least progress.

Back2Basics: Periodic Labour Force Survey

1. Conducting body: The Periodic Labour Force Survey is conducted by the National Statistical Office under the Ministry of Statistics and Programme Implementation.
2. When it began: It was launched in 2017, replacing the earlier quinquennial employment and unemployment surveys of the National Sample Survey Office.
3. What it reports: It gives quarterly estimates for urban areas and annual estimates covering both rural and urban areas, and has moved to monthly release of key indicators.
4. How it measures: It reports labour force indicators on both the usual status, based on activity over the preceding year, and the current weekly status, based on activity in the preceding seven days.

Matching Previous Year Question

“[2025, GS2, 10 marks] Women’s social capital complements in advancing empowerment and gender equity. Explain.”