Avoiding disaster while bracing for long-term impact: labour market policies in the Covid-19 crisis
Across the globe, the Covid-19 crisis has a devastating impact on labour markets, already affecting half the world population’s jobs and reducing incomes, including those in the informal sector, by as much as 60 percent (ILO, 2020). The shock is unevenly distributed, even in rich countries. The situation in developing countries is, however, much more complicated.
Across the globe, the Covid-19 crisis has a devastating impact on labour markets, already affecting half the world population’s jobs and reducing incomes, including those in the informal sector, by as much as 60 percent (ILO, 2020). The shock is unevenly distributed, even in rich countries. While in the United States, unemployment rates quadrupled from 3.5 to 14.7 percent between January and April 2020, the Netherlands only saw a marginal increase from 3.0 to 3.4 percent (OECD, 2020). To a large extent, this is due to the different types of labour market institutions and policies. For instance, many European countries make extensive use of furlough measures and temporary wage subsidies to keep unemployment low.
The situation in developing countries is, however, much more complicated. In the last weeks, the centre of gravity of the Covid-19 pandemic moved towards the Global South, where health infrastructure and social protection systems are generally less well equipped for dealing with the consequences of the crisis (Mahler and Wadhwa, 2020). Rigid lockdown measures had dramatic consequences for those cut off from their daily jobs and for informal workers in particular. In India, the unemployment rate exceeded 20 percent in April and in Nigeria, authorities expect it to exceed 30 percent (UN DESA a, 2020). The huge size of the informal sector and the more limited financial and administrative resources make labour policy interventions there much more difficult.
With the death toll and the economic cost of the pandemic increasing in low- and middle-income countries during the last few weeks, the World Bank corrected its April estimate of people being pushed into extreme poverty due to Covid-19 from 40-60 million to 71-100 million people (Mahler et al., 2020). Poor countries’ reactions to the crisis are severely hampered. For instance, the share of jobs which can be done from home is relatively low (Dingel and Niemann, 2020). The capacity to do tele-work is also highly unevenly distributed, since only some sectors and occupations can switch to routine working from home. Manufacturing, the tourism and commodity sectors are among the hardest hit in many lower- and middle-income countries (UN DESA a, 2020). Much of the impact of Covid-19 concentrates on vulnerable segments in society: informally employed people and women with low wages.
Countries in the Global South have reacted in several ways to the crisis (Gentilini et al., 2020). Many countries have expanded their cash transfer programmes or created new ones. This expansion is also the result of many scientific evaluations showing that such transfers indeed reduce poverty (for a recent review see Bastagli et al., 2019). Yet, the coverage of these transfers is still limited to 10-20 percent of the population. Given the large size of the informal sector in countries in the Global South, wage subsidies and unemployment benefits are far less effective, and they are thus used much less than in OECD countries. In addition, while OECD countries use large fiscal stimulus packages to uphold economic activities, such measures typically range between merely 1 and 2 percent of GDP in the Global South (UN DESA b, 2020).
There is only very preliminary and scattered evidence that social and labour market policies were effective in fighting the consequences of past pandemics (IPA, 2020). The long-run implications of the Covid-19 crisis are even harder to predict and yet potentially more severe. For example, it is very plausible that Covid-19 will enhance ongoing sectoral change and re-allocation processes due to automation and digitalisation. Even before Covid-19, physical and virtual automation, building on artificial intelligence and machine learning, increasingly made occupations redundant that until then had been considered safe. The general trend towards digitalisation and automation concerns a wide range of unskilled and routine-based jobs within agriculture, manufacturing and retail in low- and medium-income economies (McKinsey Global Institute, 2017).
To illustrate this threat, figure 1 shows the International Labour Organization’s estimates for how severe the economic impact of Covid-19 is on the horizontal axis. On the vertical axis, we plot the McKinsey Global Institute’s estimates for automation probability in each sector (McKinsey Global Institute, 2017), i.e. how many jobs in each sector are potentially vulnerable to automation. The sectors with the highest probability for automation are also among those hardest hit by the pandemic. This is because occupations threatened by automation very often require physical interaction with goods or customers. The fear of physical contact has pushed companies, service centres and consumers to consider technology: online purchases, online classes, automated delivery and services (EY, 2020). Healthcare and retail workers may be spared in the short run due to current public attention, but other recently displaced jobs may not return after the crisis is over (Barrero, 2020). The longer lockdowns are in place, the more likely will societies include automation into what will then be considered the new normal.
Thus Covid-19 will have impact way beyond 2020. The sooner societies in the Global South begin to discuss a desirable future of work and the sooner governments begin to experiment with novel policy options, the more capable economies will be to influence their fate. The economists Richard Baldwin and Rikard Forslid argue for a radical shift towards a service-led development path (Baldwin and Forslid, 2020). To manage the long-term implications of the crisis would also require improving public finances as well as universalising social security to include informal and new types of jobs. It might even challenge countries in the Global South to revisit the very notion of work and how they define valuable activities.
Baldwin, R. and R. Forslid (2020), “Globotics and development: when manufacturing is jobless and services are tradable, Working Paper No. 26731, National Bureau of Economic Research (NBER), Cambridge, MA., https://doi.org/10.3386/w26731.
Barrero, J. M., N. Bloom and S.J. Davis (2020), “Covid-19 is also a reallocation shock”, Working Paper 2020-59, Becker Friedman Institute for Economics at the University of Chicago, Chicago, https://doi.org/10.2139/ssrn.3592953.
Bastagli, F., J. Hagen-Zanker, L. Harman and V. Barca (2019) „The Impact of Cash Transfers: A Review of the Evidence from Low- and Middle-income Countries”, Journal of Social Policy, Vol. 48/ No. 3, pp. 569-594. https://doi.org/10.1017/S0047279418000715.
Dingel, J. I. and B. Nieman (2020), „How many jobs can be done at home?”, White paper, Becker Friedman Institute for Economics at the University of Chicago, Chicago, https://bfi.uchicago.edu/wp-content/uploads/BFI_White-Paper_Dingel_Neiman_3.2020.pdf .
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Fox, L. and L. Signé (2020), Covid-19 and the future of work in Africa: How to reduce income loss for formal sector employees (Africa in focus). Brookings Institution, https://www.brookings.edu/blog/africa-in-focus/2020/05/21/covid-19-and-the-future-of-work-in-africa-how-to-reduce-income-loss-for-formal-sector-employees/.
Gentilini, U. et al. (2020), “Social protection and jobs responses to Covid-19: a real-time review of country measures”, Living Paper No. 10, World Bank, Washington, DC, http://hdl.handle.net/10986/33635.
Innovations for Poverty Action (IPA) (2020), Research for effective Covid-19 responses (RECOVR), https://www.poverty-action.org/recovr.
International Labour Organization (2020), Covid-19 and the world of work, updated estimates and analysis (ILO Monitor), third edition, Geneva, https://www.ilo.org/wcmsp5/groups/public/@dgreports/@dcomm/documents/briefingnote/wcms_743146.pdf.
Mahler, D. G. et al. (2020), Updated estimates of the impact of Covid-19 on global poverty, data blog, World Bank, https://blogs.worldbank.org/opendata/updated-estimates-impact-covid-19-global-poverty?cid=ECR_TT_worldbank_EN_EXT.
Mahler, D. G. and D. Wadhwa (2020), The center of gravity of the Covid-19 pandemic is heading to the global south, data blog, World Bank, https://blogs.worldbank.org/opendata/center-gravity-covid-19-pandemic-heading-global-south.
McKinsey Global Institute (2017), Where machines could replace humans. In a future that works: automation, employment and productivity, Executive summary, McKinsey Global Institute, https://public.tableau.com/en-us/gallery/where-machines-could-replace-humans?tab=viz-of-the-day&type=viz-of-the-day.
Organisation for Economic Co-operation and Development (OECD) (2020), Unemployment rates: Updated May 2020, http://www.oecd.org/sdd/labour-stats/unemployment-rates-oecd-update-may-2020.htm.
United Nations Department of Economic and Social Affairs (UN DESA) (2020), “World economic situation and prospects: May 2020 Briefing. The pandemic crisis will worsen global inequality”, Monthly briefing on the world economic situation and prospects No. 137, New York, NY, https://www.un.org/development/desa/dpad/publication/world-economic-situation-and-prospects-may-2020-briefing-no-137/.
United Nations Department of Economic and Social Affairs (UN DESA) (2020), “World economic situation and prospects: June 2020 Briefing. A full-blown employment crisis in emerging economies”. Monthly briefing on the world economic situation and prospects No. 138, New York, NY, https://www.un.org/development/desa/dpad/publication/world-economic-situation-and-prospects-june-2020-briefing-no-138/
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