Much concern is voiced about the low labour force participation of Indian women. But the rapid changes taking place in this and the reasons for them, are less noticed and are the subject of this piece.

Overlapping U-shaped curves have affected women’s labour force participation through the ages. There is evidence that women’s position deteriorated as the agricultural revolution made male roles more remunerative than female roles, unlike in the hunter-gatherer economy that had lasted for millions of years and where women had brought home 60-80 per cent of the evening meal.

Claudin, who won this years’ economics Nobel Prize for her careful work with US data, finds the participation of married women decreased further with the transition from an agrarian to an industrial society in the early nineteenth century, but then started to increase with the growth of the service sector in the early twentieth century.

But East Asian manufacturing assembly lines, that largely employed women, improved their work participation. In India social constraints reduced women’s participation but economic necessity increased it. So work participation is higher in rural than in urban areas and it fell in post-reform India as incomes rose.

NSS various rounds reports the Female Labour Force Participation Rate (LPR), measured as those more than 15 years old and working or seeking or available for work over the past year, falling from 34.1 per cent in 1999-00 to 27.2 per cent in 2011-12, when it was 15.5 per cent for urban and 56.3 per cent for rural women. The NSS 68th round showed it to be 22.5 per cent, even lower than in many less developed economies.

The turnaround

The Periodic Labour Force Survey (PLFS) began measuring this annually. The 2022-23 Report shows it at 37 per cent (urban 25.4 per cent, rural 41.5 per cent) in 2023, risen from a 2017-18 low of 23.3 per cent (urban 20.4 per cent, rural 24.6 per cent).

Many factors have contributed to this climb up an Indian U curve, including changes in the convenience and safety of working, in social norms and in preferences.

Women’s contribution to domestic work is not measured. An ILO survey at the time of the slump in participation had found that one-third of women reporting their occupation as ‘domestic duties’ were willing to work if the work was made available at their premises.

Women do allocate more time to the household, especially in a period that could be critical in their career, so their productivity in the external market falls, reducing their earnings compared to males. It follows if she works more at home and the partner more outside, total household earnings rise. But, over time, this leads to a loss of her human capital. As learning-by-doing in remunerative skills falls, future wages fall as well. Thus an allocation of household resources that may be efficient at a point in time reduces the household’s consumption set over time.

Internet and communications technologies (ICT) have the potential to correct these distortions at the source, since they facilitate distance work, flexi-time activity and reduce location constraints. They make it easier for women to maintain and upgrade skills without disruptions. The Indian mobile communication sector grew in double digits after 2000, from just 5 million telephone (mobile plus landline) subscribers in 1991 to 37 million in 2001 and 933.01 million in 2014. Mobile cellular subscriptions per 100 at 70.78 by 2013 compared well with the US figure of 95.53.

The spread of the smartphone coincides with the rising LPR. It has greatly increased access to the Internet and has perhaps contributed to climbing the U curve as work from home (WFH) became easier. It was a rare example of an inclusive high tech innovation. The pandemic also contributed to the acceptance of WFH and this fact, along with rising economic necessity may explain the puzzle of why women’s LPR increased in this period when employment was falling. As rapid growth creates skill shortages, it remains worthwhile for firms to make special efforts, including flexi-work, to retain their skilled women employees. Moreover, since the latter better understand the needs of the growing share of women customers, workplace diversity contributes to profits.

In the US in 2022 women’s LPR was 56.8 per cent, so India has a long climb as yet. More participation can contribute to faster as well as more balanced development in India. Women’s share in political power, in boards and in many professions is less than their population ratios. How to accelerate this share?

Policy interventions

The long stay at the bottom of the U created distortion in perceptions and power that are entrenched in historical processes playing out over time. It is not only employers and patriarchs that have distorted perceptions; women also do in self-reinforcing traps. Modern ICT may have the potential to correct the source distortion, but just its availability is not enough. Changing perceptions and embedded social norms requires special policies. Bottom-up, context, and culture sensitive policies have a better chance of success. Supportive social and institutional change is especially a prerequisite.

Some of this is happening but needs to go further. There are signs of deep social change in attitudes to the female sex. Beti padhao beti bhachao has reached every village and its message is reinforced by the sports medals young village girls are winning. Piped water reduces onerous water-fetching duties that girls were often trapped in. Better sanitation improves nutrition, health and safety. Government credit schemes, such as Mudra, favour women entrepreneurs, who often WFH. The possibility set has expanded for girls and their families, leading to rise in girl-child preference. This already reflects in a sharp fall in excess female deaths and missing female births in the last decade and will show up in more even sex ratios.

Policy interventions continue to be necessary to make social structures and perceptions supportive. A better social infrastructure for care-taking is essential to release time for women. A major reason for the shrinking population and low birth rates in Italy is the relative paucity of such infrastructure there, compared to other European countries. The care burden, for both the young and the old, also largely falls on women. Local women leaders understand these issues and would act to resolve them.

Since this is the age of big data, sex-disaggregated data can help fine-tune policies to remove gender biases while creating more business opportunities. Finance, for example, generates a lot of data, which can be used to understand usage, preferences and constraints of women, to sensitise both sexes and to develop winning need-specific products, thus enabling greater participation by women.

The writer is Emeritus professor, IGIDR