COVID-19, inequality, and gig economy workers

Mark Stabile, Bénédicte Apouey, Isabelle Solal 01 April 2020

a

A

It is now evident that both the health and economic effects of COVID-19 are large and global.  While it will take us some time to process the overall magnitude, we can already observe that coronavirus is likely to widen social inequality.

Greater health risks for lower income individuals

Early research from the cases in China shows evidence of a higher incidence of serious infection and death among people with underlying health conditions.  Ma et al. (2020) show that the risk of severe symptoms from COVID-19 are elevated for people with hypertension, diabetes, and cardiovascular disease, among others. Data from WHO and the Chinese Centre for Disease Control and Prevention show that fatality rates for patients with hypertension are 8.4% and for patients with cardiovascular disease as high as 13.2%, significantly higher than the overall predicted mortality rate for the disease (WHO 2020). 

Long before COVID-19, researchers had documented income gradients in both these and other chronic conditions, as well as income gradients in access to care in several countries. For example, evidence from Canada shows that prevalence rates for a set of 17 chronic conditions are 15 percentage points higher for the bottom income quintile than the top income quintile (Mondor et al. 2018).  In addition, despite universal publicly financed health insurance, income gradients in access to care remain (Allin and Stabile 2012). 

It stands to reason then that if those with lower incomes are more likely to have multiple chronic conditions and those with multiple chronic conditions are more likely to experience severe responses to COVID-19, then low-income people are going to be hit harder by COVID-19, all else equal. Add to this the existence of access barriers for testing and care that still exist by income in many places, and the effect of getting COVID-19 if you are lower-income will be more severe on your health, on average. 

Income shocks for precarious workers

Along with the health consequences of COVID-19 there have already been, and will continue to be, severe economic consequences. Businesses are closed in many countries. Many people have been ordered to stay home to avoid contacting and spreading the virus as the virus thrives off social interaction. Those who have remained at work, despite the heightened risk of exposure, are deemed ‘essential’. Of course, these include medical workers who are taking significant risks to help treat the sick. However, in addition to these workers, grocery store workers, delivery workers, Amazon factory workers, street cleaners, and workers in a number of other occupations, that tend to be less well paid and who did not knowingly enter the occupation expecting elevated health risks from exposure, are still out working during the lockdowns.

Many individuals have transitioned to working from home during the lockdown. However. the ability to ‘telework’ is not uniform. Responses to the UK Quarterly Labour Force Survey suggest that manufacturers, sales and service workers, cleaners, and a number of other occupations are far less suited to adjusting to teleworking.  While some countries have provided assistance to workers unable to perform tasks from home, there are certain categories of workers who tend to fall through the cracks of these programmes. Among these are zero-hour contract workers, and small or off-market self-employed workers such as those who deliver food and clean homes. 

Along with Alexandra Roulet at INSEAD, we have been surveying (a small number of) precarious workers in France, including gig economy workers such as bikers who deliver food (using Deliveroo, Stuart, or Uber Eats applications, for instance) and drivers (Kapten or Le Cab for example). The survey was carried out just before France went into lockdown (16 and 17 March 2020) and a few days after the lockdown (19 and 20 March 2020). 

Before the lockdown, many participants reported being worried about reduced income and activity in the near future. However, some bikers noted that they were seeing or expecting increases in demand (indeed, they noted that Uber Eats had dropped delivery fees and that restaurants had no option but to do deliveries). Bikers noted that the platforms they worked for sent them information through their apps on heightened risk and on how to protect themselves (by offering no-contact delivery in particular). 

As the lockdown started, demand for services dropped off (though not entirely) and many workers in our sample stopped working (52%). However, 19% of them continued to work outside the home in order to continue to earn income. They noted in comments to us that while the government had put in measures to help those in precarious positions, they did not believe the measures would apply to them since they were not employed (and therefore couldn’t benefit from the measures to secure jobs while stopping work/partial unemployment) and were unlikely to be in the category where delayed tax filing and so on would provide any relief. Hence the need to keep working despite the highly elevated health risk of doing so. Traditional gig economy workers with incomes under €1,000 a month were more likely to keep working. 

Conclusions

We are only starting to understand the effects that the COVID-19 pandemic will have on worker health and wellbeing. However, the available evidence suggests that low-income workers are more likely to experience health shocks related to COVID-19 and that the income supports in place will leave some low-income workers exposed. As we continue to generate policy options to navigate this pandemic, keeping these distributional concerns in mind should be a priority. 

References

Allin, S and M Stabile (2012), “Socioeconomic Status and Child Health: What is the role of health care, health conditions, injuries and maternal health?”, Health Economics, Policy and Law 7(2).

Ma, C. et al (2020), “Incidence, clinical characteristics and prognostic factor of patients with COVID-19: a systematic review and meta-analysis”, medRxiv preprint doi:

Mondor, L, D Cohen, A I Kahn, W P Wodchis (2018), “Income inequalities in multimorbidity  prevelance in Ontario, Canada: a decomposition analysis of linked survey and health administrative data”, International Journal for Equity in Health 17(90).

WHO (2020), “Report of the WHO-China Joint Mission on Coronavirus Disease 2019”, 16-24 February.

a

A

Topics:  Covid-19 Labour markets Poverty and income inequality

Tags:  gig economy, COVID-19, coronavirus, Inequality

Professor, INSEAD

Professor, Paris School of Economics-CNRS

Postdoctoral research fellow, INSEAD

Events

CEPR Policy Research