<mark>In Sri Lanka and Brazil, there is a clear pattern between the magnitude and direction of income changes and the position in the initial income distribution. The first quintiles suffered larger income declines than the top quintiles. In Sri Lanka income changes range between -2.4% and - 2.5% in quintile 1 to quintile 3, while the corresponding changes were -2.0% and -1.6% in quintiles 4 and 5, respectively. In Brazil, differences were larger with declines between -11.6% and -13.0% in quintiles 1 to 3, and reductions of -8.8% and -10.0% at the top (in a simulation that does not account for the generous emergency transfer program undertaken by the government of Brazil in</mark> 2020, which covered a large part of the population and protected the poorest from income loss).

<mark>In South Africa and the Philippines, middle- and top-income quintiles are the ones suffering the largest income declines. In South Africa, income declines range between -6.5% in quintile 5 and - 9.1% in quintile 4. Bottom quintiles, on the other hand, suffered smaller income losses (-1.8% in quintile 1 and -3.9% in quintile 2). The Philippines exhibits a similar pattern. Income reductions</mark> are around -7% for quintiles 2 to 4, while it is -4.4% for quintile 1.

<mark>In Türkiye, income changes were very small for all quintiles of the per capita household income distribution. The smallest changes were between -0.4% and -0.5% in quintiles 2 to 4, while the</mark> largest change was a reduction of 1.1% in quintile 1.

<mark>Overall, the shock caused income declines across the distribution, but with no pattern across countries. This suggests that differences in the structure of the labor market captured by the household survey as well as the sectoral growth patterns taken from National Accounts lead to</mark> diverse patterns of projected distributional impacts. This would require further study.

<mark>We also study how income changes correlate with the educational level and occupation of the household head. Panel A of Table 1 shows that in four out of five countries —Türkiye, Philippines, South Africa, and Brazil—income losses were larger the lower the educational level of the household head. The magnitude of the losses, however, differ between countries. For instance, household where the head has up to complete primary education faced an average income loss of 8.3% in South Africa and of 11.6% in Brazil. For households where the head has tertiary education, the loss was of 6.3% in South Africa and 8.4% in Brazil. Sri Lanka is the only exception to the negative correlation between education of the household head and magnitude of the income loss. In this country, households where the head has up to complete primary education experienced an</mark> income increase, while households with more educated household heads faced income reductions.

<mark>Panel B of Table 1 presents income changes by initial occupation of the household head. We do not find a clear pattern in this case. For instance, in Philippines, households where the head was initially an unpaid worker or a wage employee suffered the largest income losses (10.6% and 7.8% respectively). In South Africa, the largest income losses were for households where the head was</mark> self-employed, unemployed or wage employee (19.1%, 7.5% and 7.3% respectively).

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