Harmonized data from the EU Statistics on Income and Living Conditions (EU-SILC) show that in Q2 of 2020 across all EU countries for which data is available, the risk of temporary layoffs or reduced hours declines with household income. Moreover, in several countries in Southern Europe and in Ireland, the probability of employment loss is considerably higher for low-income households (Figure 3). Chetty et al (2020) similarly find that employment loss between January and April 2020 decreased monotonically with income, from 37 percent in the bottom wage quartile to 14 percent in the top wage quartile.

The within-country socio-economic disparities in access to remote work is mirrored by patterns across countries, with richer countries more likely to have a higher share of urban jobs that can be performed from home (Hatayama _et al.,_ 2020). This is largely because the share of self-employed workers, whose occupations are less conducive to working from home, tends to be large in poor countries (Gottlieb _et al.,_ 2020). Jobs in poor countries tend to be more intensive in physical/manual tasks, less intensive in ICT use, and workers do not always have as good internet connectivity at home (Hatayama _et al.,_ 2020). This means that urban areas in poorer countries were likely to be harder hit by lockdown policies and aversion behavior.

The impact of the shock is likely to have amplified some of the pre-existing inequalities within countries. The differences in losses across socio-economic groups are driven at least to some extent by structural inequalities in the labor market – in terms of how jobs before the pandemic were distributed by type among individuals with different circumstances. Crises tend to have a larger impact on households that have lower access to markets, capital, and basic services.<sup>3</sup> This implies that all other things being equal, crises would have larger distributional impacts in economies with greater pre-existing inequality of opportunities – in access to basic services, and to jobs, markets, and capital – that are also drivers of high income inequality. There is some evidence for this from the Gallup World Poll data: the socio-economic gap in job losses (difference in job-loss rate between those with college education and those without) due to COVID-19 tends to be significantly lower for countries with lower income inequality before the pandemic (Rothwell, 2021).

To what extent a shock widens pre-existing inequalities depends on who is exposed to the shock, to what extent, and for how long.<sup>4</sup> In the case of COVID-19, exposure to the economic risks has been disproportionately high among certain groups, relative to others. The distribution of impacts also depends on the adequacy (or lack thereof) of policies that support those who are affected, and how they might have adjusted their behavior to cope with the shock. Certain factors could alleviate the dis-equalizing effects in the short-run. In low-income countries, income inequality may be dampened by the initial impacts being lower on the poorest (who are often in rural areas and in agriculture in developing countries, which tend to be less affected by restrictions on economic activity) than among the less poor (who are employed in urban services and manufacturing). In middle-income countries, the moderating effect might come from social assistance provided by the government to temporarily replace incomes of poorer households. While the net short-term impact on income inequality is uncertain and varies widely across countries, simulations by the International Monetary Fund (IMF) estimated an increase in inequality across EMDEs by an average of 2.6 percentage points as a result of the crisis (IMF, 2020).

The short-term dis-equalizing effects could in turn lead to a more unequal recovery process, with worse implications for inequality of opportunities over time. As disadvantaged groups suffer larger, longer-lasting shocks, they are also more likely to adopt coping mechanisms (such as running down their savings and selling assets) that are harmful to their future economic prospects. Learning losses caused by education

> 3 Dercon, 2004; Lybbert et al., 2004; Thirumurthy et al., 2008; Hill and Porter, 2016.

> 4 For example, the financial crisis of 2008 often affected workers in the manufacturing sector the most in some middleincome countries, whereas the poorest tend to be in rural areas, which meant that inequality did not increase appreciably in these countries.

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