Gender, Skill & Employability in India

Gender Skill and Employability in India

By: Jeemol Unni
For a successful skill attainment and removal of skill mismatch, supply driven incentives have to be replaced by the demands of the industries. This improves worker employability as well as helps increase work participation of women.

India’s youth population is expected to peak in 2020 with 64 per cent in the working age group. The nation’s young manpower is in fact set to increase to 464 million by 2021 (Shivakumar, 2013). This emergence of a youthful India ceases to be an advantage due to a growing mismatch between skilled jobs for the wage/salaried workers and education. With increasing use of technology in manufacturing and service industry, the gaps at the level of tertiary education constitute a major constraint. To tackle this challenge the Prime Minister’s Council for Skill Development had set up a manpower target of 500 million skilled workers by 2022 (Sardana, undated). However, the plan has been abandoned by the government in 2017 (Nanda, 2017). This target was divided among 20 odd ministries/departments including the National Skill Development Council (Sanghi, 2012). In this context, the recent news that the government is abandoning the supply driven well publicised skill target ( and making it demand based, came as a shocker. What is the harsh reality with regard to education, skills and employability in the labour market that could have led to this and what are its gender implications?

Level of education

Based on author’s computation from unit level data of the employment-unemployment survey by National Sample Survey Organisation (NSSO) for 2004-05 and 2011-12, the status of education and skill training among the youth (age group 15 to 35 years) shows that there has been an improvement in the levels of general education. Illiteracy has also declined sharply, particularly for women from 32 to 20 per cent. For men illiteracy was lower and declined from 17 to 11 per cent. Completion rates of secondary and higher secondary schooling rose by nearly 10 per cent for men and women over the period. An encouraging feature is that the gender gap in secondary (about 46 per cent for both) and higher secondary schooling (about 37 per cent for both) appeared to be closing. The gender gap has also closed for graduate education although the increase over the period was only of three percentage points.

We note an interesting gender difference between educational choices of men and women after schooling and graduation. Women have a slight edge over men in completion of post-graduation, while men are more likely to undertake a diploma/certificate course, as was also observed by us during our field studies. A rationale provided was that the boys, particularly from poorer households, have to enter the labour market earlier to support the family. Due to restriction on the mobility of girls, they were more likely to be allowed to continue with their education for a longer period, perhaps under the consideration that the educational institution provides a safe environment and may be closer home.

Skill Training

India’s performance in providing skill training has been dismal. Only about 1 per cent of the youth report to be enrolled in any vocational training course in 2011-12. About 16 per cent of male and 9 per cent of female youth reported having received some form of formal or informal training. Of course, one can expect that this is grossly underestimated, though it apparently includes hereditary training (nearly 3 per cent), that is within the family or from friends and neighbours, and on the job training (nearly 4 per cent). Young men receiving on the job training is much larger, nearly 6 per cent, compared to women (less than 2 per cent) (Fig 1). The low volume of training, both formal and informal, may reflect the lack of confidence among the employers to be able to retain the workers once trained, due to poaching by other enterprises in the industry. Among employees, the cost and quality of skill training on offer may be a concern.

Among those who received formal training, there is a gender difference in the field of training. About 32 per cent of the male youth were trained in engineering related vocations while the figure for female youth was about 3 per cent in 2011-12. Another male dominated job profile was that of a driver and a mechanic (nearly 18 per cent). About 26 per cent of female youth were trained in textile related activities, which could be weaving, tailoring, embroidery and more, as compared to less than 2 per cent men. About 11 per cent of women received training in health and paramedical services, in comparison to only 4 per cent men. One profession where there was gender equality was in computer trades (nearly 30 per cent of youth). The choice of trades in all possibility have been dictated by social norms and perceived demand.

In a survey of households engaged in informal work conducted in Surat city, researchers found more than 80 per cent respondents receiving training from non-formal sources. The salaried workers said they received on job training, which was the predominant source in the informal enterprises in the city (Kantor,, 2006). The predominance of such training raises the question of how much of knowledge is retained by short duration training. The duration of formal training was nearly five times longer (in days) than informal training.

Workforce participation

A worrying feature of women’s work is their low participation as compared to men. In fact in urban areas work participation is abysmally low at less than 15 per cent of the population of all ages. This is partly because women face a ‘double burden of work’, fulfilling both productive and reproductive roles. Further, women’s work participation has been observed to decline over time, while that of men has remained stable. There are various interpretations for this phenomenon—the dominant one being that as the economy prospers, income levels rise and women withdraw from the labour force (Abraham, 2013). However, an alternative view is that women enter the workforce when work is available. That is, women constitute a large part of the flexible workforce—becoming available when there is a large demand. For example the dip in the overall work participation of women in rural areas in 1999-00 and 2009-10 was due to poor agricultural years. This is however, not reflected in the urban work participation (Unni and Raveendran, 2006). Of course, the ambiguity about the dismal overall participation of women remains.

The age specific work force participation rates clearly show the late entry of women into the labour market, which is partly due to their continuation of formal education (as noted in the Surat case study) and partly to fulfil the reproductive function. This may accentuate the low level of training imparted to women employees, as employers do not want to invest if they perceive women in short term roles.

Broadly, there is a u-shaped relationship between participation in the labour market and the level of education (Fig 2). The illiterate and least educated men and women have the highest work participation, which mainly implies that they need to work in order for the family to survive. As the level of education goes up participation declines as people remain in school, until higher secondary level, after which the entry into the work force rises sharply. Persons with diploma or certificate education and the graduates have higher participation rates than those who only finished school. Diploma and certificate courses are primarily skill training programmes, and persons with training stand a better chance in securing employment, enhancing the work participation rate. Women clearly have lower participation, which suggests a lower access to skill training.

The mean/average years of education of youth, both men and women, in urban areas has improved over time among the wage and self-employed workers (Table 1). Women in formal jobs, had the higher mean years of education—nearly 10 years, compared to men with 8.7 years in 2011-12. Women in informal jobs also had higher mean years of education (8.2 years) compared to men (6.1 years) (Table 2). The same was true for women in regular and casual jobs. This reflects the point noted earlier that girls are more likely to continue in the formal education system after they have crossed the threshold of schooling, while boys opt for vocational training or enter the labour market. The policy implication is that if girls, or in effect their parents, can be persuaded to let their wards finish school, the chances of them entering and completing graduation is greater. This is addressed to some extent in programmes such as the Balika Cycle Yojana in Bihar.

With a skewed income distribution, the better off are likely to be better educated in India. Class was defined adapting Banerjee and Duflo (2008) definition of classes—lower class < 2 USD; lower middle class—2 to 4 USD; upper middle class­­­—4-10 USD; upper class > 10 USD per person per day. As expected, the mean years of education rose with the expenditure class, with the upper most class having the highest years of education for all categories of workers. The only exception was the male casual workers who received about 7 years of education irrespective of class. Women regular salaried workers in the middle classes had higher years of education than men in that class.

There is a higher work force participation in the lower class among casual workers and in the upper class among regular salaried workers. The self-employed, where the necessity and opportunity to work is considerably high, are a diverse group and occupations can vary from street vending to professional software consultants. However, even in the self-employed workforce, although a relatively larger participation is noted in the lower classes, the divergence is not so large in the upper class, particularly among women.

Where are these men and women absorbed in the workforce? What kind of work do they do? The changing occupational distribution of work among the youth tells us an interesting story. Men are mainly in senior management, service and marketing, crafts and elementary occupation (manual labour) (Table 3). Women are professionals (including in health and education), technicians and associated professionals, services and marketing, crafts and elementary occupations. Elementary occupations include urban domestic workers (Unni, 2017).

The increase of women in professional and associated occupations explains, to some extent, where the better educated women can and do find work. The predominance of women as technicians and associated professionals and in craft explains the predominance of training in computer trades, heath/paramedical services and textiles. Such choice of training can be demand driven as an increase in women’s participation in these occupations is perceived. While there may be a phenomenon of withdrawal of women from the workforce due to rise in incomes – increasing levels of education and the growing demand from the tertiary sector will hopefully see an increase in women work participation.


India today faces a strange phenomenon of skill mismatch. There is high rate of unemployment among the educated and uneducated youth, while employers claim a labour shortage.

We can identify two kinds of skill mismatch. Over-education, where persons are hired for jobs/activities that do not require such high qualifications. For example, a post-graduate in history is hired as a bus driver. A similar situation can arise when technically qualified persons are hired for non-technical jobs, where a marketing firm hires an engineer.

Quality skill-gap is a second form of skill mismatch, which occurs when firms hire apparently qualified workers, but find that the quality/skill is inadequate for such activities. The firms then have to invest a significant amount in training adding to the cost of the firms. For example, graduates in commerce are required to be trained in the accounting procedures of the firm. Such skill mismatch is costly to the employer and inefficient to the employee. The returns to the investment in education for the worker are lower when there is such an education-occupation mismatch. Studies have shown that workers earn less in the informal sector and in particular suffer additional penalty due to educational mismatch when compared with their formal counterparts (Herrera et al. 2015).

A recent report of the Centre for Monitoring the Indian Economy (CMIE) reported a decline in persons employed from May 2016 to July 2017, from 413 million to 405 million (Table 4). Also, there was a drop in persons seeking work from 44 million to 13.7 million during the same period. The Organisation of Economic Cooperation and Development (OECD), an inter-governmental economic organisation with 35 member countries, recently reported that over 30 per cent of youth aged 15-29 years in India are NEETs, that is, not in education, employment or training. (Verma, 2017).

A pessimistic view of the drop is that workers are discouraged and do not want to seek work, while an optimistic view offers that the better educated are waiting for good opportunities or are considering startups. The latter construct would see the economy picking up soon.

Overall, skill building is important to improve worker employability in a fast changing labour market. Abandoning the skill training targets by the Indian government given the enormity of the problem, may be a practical move. However, it would be better if the government could create incentive structures for reducing skill mismatch. Some suggestions for such an approach are highlighted.

  • Create an incentive system for skill training and technical education institutions that are able to find jobs and place their trainees and students.
  • Create incentives for firms to invest in their workers with on job training as a primary method adopted by formal and informal enterprises to train their employees.
  • Rejuvenate the old apprentice scheme meant for public sector in a privatised form.
  • Incentivise educational institutions and enterprises that maintain diversity of students and employees. Gender, social and economic diversity will benefit the enterprises, institutions and the country and drive up participation rates.

The Indian government has tried to implement schemes on all the ideas noted above. In fact, the Ministry of Skill Development and Entrepreneurship has created a very interesting online registration system for enterprises looking for employees with particular skills and apprentices as well as for persons looking for such work ( However they do not reward skill training, educational institutions and enterprises for their achievements. Unless this is propagated and an incentive structure is built in, the efforts are unlikely to show any results.


Once students and workers are able to see the benefits of education and training, they would be willing to invest. Further, if enterprises see the benefits of conducting training for their employees, there will be fewer poaching across enterprises. A demand driven incentive structure will thus help reduce the skill mismatch and improve employability. With policy interventions, work participation among women can also be targeted. Of course, this is based on the premise that high economic growth would soon be enabled, creating  an enhanced demand for workers.

Leave a Reply

Your email address will not be published. Required fields are marked *