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Jobless and Stuck: Youth Unemployment and COVID-19 in India

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Abstract

Youth unemployment is a big challenge in developing economies, but there is a limited understanding of the dynamics underlying the rise in unemployment among young workers. This article examines youth unemployment and inactivity in India, where the economic contraction from the pandemic was solely responsible for reversing the trend of decades of declining global inequality. Young workers face higher unemployment, have fewer transitions to work, and are more likely to get stuck in unemployment. The pandemic disproportionately pushed young workers out of work and reinforced the pre-existing trends of being more likely to be out of work and stuck in worklessness. Young workers have a strong desire for public employment programmes, with over 80 percent preferring job guarantees among policy options to tackle unemployment in survey experiments. Workers who lose their jobs and become discouraged from finding work afterward are most supportive of a job guarantee.

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Source: CEP Survey 2021

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Notes

  1. See, for example: Jacobson, LaLonde, and Sullivan (1993), Ruhm (1991), Sullivan and von Wachter (2009), Browning and Heinesen (2012), Eliason and Storrie (2009), and Bentolila and Jansen (2016) for long-term unemployment from the pandemic.

  2. In 2017/2018, informal employment amounted to 88.6 percent of total employment in India, with similar rates in the region (81 percent in Nepal, 94.7 percent in Bangladesh, 81.7 percent in Pakistan), but higher rates than Latin American countries (69.4 percent Peru, 62.4 percent Colombia) and much higher rate than for example South Africa 35.3 percent (Ohnsorge and Yu, 2021).

  3. The CPHS sample had a rural-urban ratio of 34:66 before the lockdown. However, during the period of 24th of March to 7th of April, the rural sample was overrepresented with a ratio of 43:57. This overrepresentation quickly got restored to 36:64 between April and July. In terms of household income, during the lockdown, the share of households in the middle of the income distribution, earning between Rs 150,000 and Rs 300,000 remained at 45%. Nevertheless, there was a change in the tail-ends of the income distribution. There was an over-representation of low-income households and an under-representation of high-income households. Specifically, households earning Rs 500,000 or more made up 13% of the sample before lockdown and 9% during the lockdown. Whereas those earning Rs. 84,000 to Rs.150,000 made up 19.6% of the sample before the lockdown and 25% during the lockdown. Finally, the share of those earning less than Rs.84,000 increased from 2.4% to 4.1% (“CPHS execution during the lockdown of 2020”, available online at consumerpyramidsdx.cmie.com)

  4. A discussion of the representativeness concerns arising from exclusions at the bottom end of the consumption distribution, especially in rural areas, is provided in Drèze and Somanchi (2021), Dhingra and Kondirolli (2022).

  5. Eighteen is the age of majority in India and therefore labor laws differ for 15–17 years old who are covered under child labor laws. The compulsory school leaving age in India is 14 years and therefore some official labor statistics are reported for those between 15 and 29 years old. We exclude individuals between 15 and 17 years from our analysis because they are minors who are also more likely to be pursuing high school education which occurs till age 17. However, including them in our analysis reinforces the main findings further.

  6. International Labour Organization. “ILO Modelled Estimates and Projections database (ILOEST).” ILOSTAT.

  7. The recontacted sample was interviewed over the phone and the boost sample was interviewed door-to-door (in person). Individuals in the control and treatment groups did not interact with each other as the interviews were conducted one on one by trained enumerators.

  8. The MGNREGA figure is computed from disbursements made by the government divided by number of individuals actually worked in 2020. These are available from the NREGA public data portal which put the figure at Rs 5642 precisely. The cash transfer figure is computed from the release of the Press Information Bureau (PIB), Government of India, Ministry of Finance, 08/09/2020 at 1:00PM by PIB Delhi. The figure ranges from about Rs 500 to Rs 1640 depending on the type of recipient.

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Acknowledgments

Financial support from the ERC Starting Grant 760037 is gratefully acknowledged. The primary survey was reviewed and approved by the LSE Research Ethics Committee (REC Ref. 1129) and conducted by Sunai. We are grateful to Stephen Machin and Uday Bhanu Sinha for their comments. There are no conflicts of interest to declare.

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Authors and Affiliations

  1. Department of Economics, London School of Economics, London, UK

    Swati Dhingra

  2. Centre for Economic Performance, London School of Economics, London, UK

    Swati Dhingra & Fjolla Kondirolli

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  1. Swati Dhingra
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Correspondence to Fjolla Kondirolli.

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Dhingra, S., Kondirolli, F. Jobless and Stuck: Youth Unemployment and COVID-19 in India. IMF Econ Rev 71, 580–610 (2023). https://doi.org/10.1057/s41308-023-00205-y

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