based on a smaller sample of 34 countries, complemented by select findings from a few other studies.<sup>8</sup> We consider four primary outcome variables, defined below, on which the impacts of the pandemic are measured. The number of countries for which that outcome variable is available is in parentheses, since all variables are not available for every country.

- _Work stoppage or job loss_ : The share of respondents who stopped working during the pandemic out of those who were working pre-pandemic (46 countries).

- _Income loss_ : The share of respondents who report a decrease in total household income compared to pre-pandemic (30 countries).

- _Food insecurity_ : The share of households in which at least one adult went without eating for a whole day due to lack of resources (37 countries).<sup>9</sup>

- _Continued learning_ : Share of households with children in school prior to the pandemic who reported their children engaging in any learning activity during pandemic-induced school closures (38 countries)

# 4.1. Inequality in job and income losses

The rate of job loss in the first three months of the pandemic (April-June 2020) was much higher among women, younger workers, and workers with lower levels of education. Taking simple averages across countries, women were 8 percentage points more likely than men to stop working in the initial phase of the crisis, and gender disparities were larger than gaps by age, education, and location (urban versus rural) (Figure 5).<sup>10</sup> Regressions that consider the effects of all these factors taken together confirm that women and low-skilled (education of primary level or less) workers were significantly more likely to stop working relative to men and workers with college education (Figure 6a). The probability of job loss was higher for younger and older workers and lowest for prime-age workers (Figure 6b). Those working in manufacturing, commerce, and other services before the pandemic were significantly more likely to have stopped working than those in agriculture.<sup>11</sup> A greater share of urban workers lost jobs compared to rural workers, but this is the result of spatial differences in employment composition – when the effects of other factors like sector of 8 The countries included in the updated results for Bundervoet et al (2021) are from Sub-Saharan Africa (21 countries), Latin America and the Caribbean (13 countries), East Asia and the Pacific (8 countries), Middle East and North Africa (5 countries) and Europe and Central Asia (5 countries). Grouped by per capita GDP, the sample consists of 4 highincome, 12 upper-middle income, 21 lower-middle income, and 15 low-income countries. The data corresponds to the April 2021 vintage of the harmonized database. To assess the immediate impact of the crisis in a comparable way across countries, the authors select survey waves (between April and July 2020) that are no more than two months of the peak of the economic crisis, with the peak measured by Google mobility data when available or by policy index of social distancing measures, available from Oxford’s “Coronavirus Government Response Tracker” (OxCGRT).

9 This indicator is part of the standard Food Insecurity Experience Scale (FIES) and was included in the surveys for a subset of countries.

> 10 Kugler et al (2021), with sample of countries that may not exactly match those used by Bundervoet et al.

11 Having a school-age child in the household, which could affect labor force participation due to additional childcare responsibilities during school closures, did not significantly affect the likelihood of work stoppage. However, Cucagna and Romero (2021), using the same data source for three rounds of phone surveys in Latin American countries, find that the presence of school-age children in the household developed a greater association with loss of employment among women as the pandemic persisted, suggesting that childcare burden may affect labor force participation of women more as school closures stretched on.

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