By Charity Troyer Moore, Rohini Pande, and Soledad Artiz Prillaman
This article first appeared on the IGC on February 23, 2018.

Skill India

Many low- and middle-income countries have launched government-funded vocational training programs to help youth integrate into labor markets and spur economic growth. India, with its burgeoning youth population, has a major impetus for improving the skills of young people. This accounts for the initiation of the Skill India initiative in 2014, which initially set out to train 500 million youth by 2022. A key challenge in India is to recruit and train a large rural labor force for mostly urban jobs. Skill India promises to do just that.

Vocational training, gender and mobility

We have little evidence of the efficacy of vocational training programs, and what we do know suggests that success is quite varied (McKenzie, 2017). While existing evidence suggests some programs can directly benefit women (Attanasio et al., 2011; Bandiera et al., 2017), it is not clear who these programs in fact benefit.

Skill India’s focus on urban migration may limit the involvement of women, whose migration may be constrained by a variety of factors. Women in India, similar to those in some other developing contexts, are subject to gender-biased norms that constrain their work, mobility, information, and access to networks (Farré and Vella, 2013; Jayachandran, 2015; Croft et al., 2014; Beaman et al., 2018).

Accordingly, despite investing millions of dollars in various programs under the aegis of Skill India, not much is known about how well these programs address specific constraints to women’s participation and success.

Two key questions remain unanswered:

  1. Are women being left behind by vocational training programs?
  2. How can these programs address underlying barriers to women’s participation in vocational training and labor markets?

The study

To address this knowledge gap, we conducted a survey in collaboration with a major Indian government vocational training program for below poverty line, rural youth. This program trains youth age 15 – 35 via publicly-funded, private training agencies, in a variety of trades, free of charge. Youth are then placed in formal-sector, above minimum wage jobs, often in urban centers, across the country.

The methodology

Our survey, conducted over the phone with 2,600 former trainees (1,900 women) from seven major states (Bihar, Chhattisgarh, Gujarat, Madhya Pradesh, Odisha, Rajasthan, Uttar Pradesh), asked youth about their training, job placement, and migration experiences.

The findings

Our data shows that women are being left behind:

  • Figure 1 shows the leaky pipeline that results in less than 25% of women being employed in their skilled job for more than three months.
  • Unfortunately, results for men are only slightly better, at 33%.
  • Women are also less likely to receive and accept job offers than men.
  • That said, when women are placed in jobs, they remain in them as long, or longer than, men

Graph of trainees and their job offers

Migration: A key constraint for women

Job locations are strong predictors of female outcomes. While female trainees are less likely to both receive job offers and accept those offers after skilling than men, they are even less likely to accept jobs that require migration.

Figure 2 plots predicted job placement rates for men and women conditional on job location, holding education, caste, age, trade of training, natal district, and training agency constant. It shows that women are less likely than men to accept jobs overall, but also that this gap widens for jobs farther from their homes.

Graph of a multi-state survey

The biggest reasons women reported dropping out of the labor force revolve around family-related challenges and difficulty migrating. Men, on the other hand, report challenges related to low pay and unfavorable working conditions.

Migration support for women workers

Migration support may counteract this leaky pipeline and improve female employment outcomes. Our survey evidence suggests that access to migration support was associated with higher labor force participation and longer job tenure (see Figure 3).

Respondents who migrated for work and had left their jobs were asked whether they received any of seven different types of migration support:

  1. Assistance finding accommodation
  2. Opening a bank account
  3. Setting up an account to receive government benefits
  4. Obtaining a phone number or SIM
  5. Finding food
  6. Finding medical help
  7. Using public transport

Figure 3 shows mean job duration for former trainees’ conditional on how many forms of migration support the youth received, irrespective of type. Receiving more migration support is associated with longer job durations. That said, this relationship is purely correlational since longer job tenure may increase exposure to potential support.

Graph of mean job tenure and migration support

The case of Odisha

Vocational training need not be gender-regressive: some states achieved parity in terms of training and placement outcomes for men and women. While our survey suggests women fare worse than men on a variety of labor market outcomes overall, results varied significantly by state.

In the context of a broader research-policy engagement with the state of Odisha, our research team evaluated administrative data from over 100,000 trainees. They found that the state achieves remarkably better than average results for women, in terms of employment outcomes.

For example, women are more likely than men to be placed in jobs for at least three months, and 55% of female trainees were placed in jobs for three months or longer. Crucially, these strong results did not reflect a tendency to place women in jobs near their homes: instead, most of Odisha’s female trainees migrated for their jobs.

Implications

Taken together, these results suggest that relatively poor female training and employment outcomes need not be a given under Skill India. Vocational training programs can be designed in such a way as to alleviate gender-specific constraints and usher women into the labor force.

Even so, there is still much to learn. Important areas for future inquiry include the rigorous testing of specific practices aimed to support women’s training enrolment and improve their employment outcomes, particularly in the context of urban migration.

 

References

Attanasio, O., Kugler, A. and Meghir, C. (2011). “Subsidizing Vocational Training for Disadvantaged Youth in Colombia: Evidence from a Randomized Trial”, American Economic Journal: Applied Economics, 3(3): 188-220.

Beaman, L., Keleher, N. and Magruder, J. (2018). “Do Job Networks Disadvantage Women? Evidence from a recruitment experiment in Malawi”, Journal of Labor Economics, 36(1): 121-157.

Bandiera, O., Buehren, N., Burgess, R., Goldstein, M., Gulesci, S., Rasul, I. and Sulaiman, M. (2017). “Women’s Empowerment in Action: Evidence from a Randomized Control Trial in Africa”, Working Paper.

Croft, A., Schmader, T., Block, K. and Baron, A. S. (2014). The second shift reflected in the second generation: Do parents’ gender roles at home predict children’s aspirations?, Psychological Science, 25(7), 1418-1428.

Farré, L. and Vella, F. (2013). “The intergenerational transmission of gender role attitudes and its implications for female labour force participation”, Economica 80(318): 219-247.

Jayachandran, S. (2015). “The roots of gender inequality in developing countries”, Annual Review of Economics7(1): 63-88.

McKenzie, D. (2017). How Effective Are Active Labor Market Policies in Developing Countries? A Critical Review of Recent Evidence, World Bank Group, Development Research Group, Finance and Private Sector Development Team. Policy Research Working Paper 8011.