Generation COVID and Social Mobility: Evidence and Policy

  • Funded by UK Research and Innovation (UKRI)
  • Total publications:0 publications

Grant number: ES/V010433/1

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Key facts

  • Disease

    COVID-19
  • Known Financial Commitments (USD)

    $355,482.72
  • Funder

    UK Research and Innovation (UKRI)
  • Principal Investigator

    Pending
  • Research Location

    United Kingdom
  • Lead Research Institution

    London School of Economics and Political Science
  • Research Priority Alignment

    N/A
  • Research Category

    Secondary impacts of disease, response & control measures

  • Research Subcategory

    Social impacts

  • Special Interest Tags

    N/A

  • Study Subject

    Non-Clinical

  • Clinical Trial Details

    N/A

  • Broad Policy Alignment

    Pending

  • Age Group

    Unspecified

  • Vulnerable Population

    Unspecified

  • Occupations of Interest

    Unspecified

Abstract

Our aim is to provide a comprehensive picture of the challenges the pandemic presents in terms of fostering a more socially mobile society in absolute and relative terms. Young people who fall into low quality jobs, long-term unemployment, or who fail to achieve the exam grades needed to pursue the next steps in education, training or employment, are unlikely to rise above the economic status of their parents during their lifetime. They face the prospect of faring worse than previous generations. Our focus is on these aspects of young people's lives and, in particular, on how policy can prevent an even greater chasm opening between the 'haves' and the 'have nots' by preventing educational and labour market 'scarring' of the hardest hit members of the COVID-19 generation. The starting point of the empirical analysis is to show how children's educational environment has been affected by the pandemic and how opportunities for learning from home differ by socioeconomic status. We will document how differences across individuals in parental time inputs, monetary inputs (such as online tutoring), and access to online schooling resources, differ by socioeconomic background. We will also explore how parental job loss and labour market status have shaped the home learning environment. Parents facing financial hardship, greater stresses caused by failing health, or increased workload due to having key worker status, are unlikely to be able to provide as much time and support for their children as higher earning parents who are able to work from home. We aim to quantify how these inputs combine to produce marketable skills and discuss policies to remedy the falls in inputs and ensure that the talent of children who have missed out on key instruction time does not go unfulfilled. Economic and educational hardship go hand in hand. Failing to reach one's potential at school can close the door not only to higher education, but also to the most desirable jobs and early career training opportunities. A dearth of opportunities early on can lead to limited opportunities later in life. In addition to education, we will focus on how the pandemic has affected those entering the labour market and those early in their careers. Given our focus on social mobility, we will look at how individuals from different backgrounds have had different labour market outcomes during lockdown. We will discuss what these outcomes are likely to mean for individuals as the lockdown ends and the transition towards a functioning labour market begins. Once again, we will present a series of proposals, and assess their efficacy, in light of our findings. The policy proposals are aimed at preventing current economic inequalities being further exacerbated by COVID-19. In particular, we will consider evidence (of our own and from others) to look at policies surrounding school and university admissions, vocational training and reskilling, and more general labour market policies such as job guarantees. In order to carry out the above, we will make use of a range of datasets that follow young people as they age. These data allow us to link home environments with labour market outcomes for birth cohorts. The three datasets that we will use - Understanding Society, the Millennium Cohort Study, and Next Steps - also contain, or will contain, modules looking at how the Covid-19 pandemic has affected study participants. In order to gauge the extent to which the polices we propose are supported by the public, we will also carry out a survey asking participants of their views on the redistributive polices that we propose.