_Note:_ Based on logistic regression of whether a household reports continued learning among children on several covariates with country dummies; sample limited to households with children going to school before the pandemic _Source:_ Based on Bundervoet et al (2021), updated by the authors with April 2021 vintage of harmonized HFPS data Children in rural areas and from households with lower levels of education were significantly less likely to continue learning during school closures, widening the pre-existing learning gap with urban children and children from better-off households (education of household head is a good proxy for socioeconomic status of a household) within countries (Figure 9). Children living in households with secondary- and tertiaryeducated respondents were nearly 8 and 11 percentage points more likely to continue learning during school closures relative to children in households with primary-educated respondents. Children in households with job loss during the pandemic, which were typically higher among the less-educated, were also less likely to continue learning. Interestingly, there is a small significant negative association of a household head (respondent) being a man and likelihood of continued learning among children, which might indicate the positive influence of mothers on their children’s education when they are also the main decision-maker of the household. Notably, all the gaps were larger for children in low and lower middle-income countries, where pre-existing inequalities are already larger, than for the full sample of countries.<sup>14</sup>

# 4.4. Adequacy of policy response

By September 2020, advanced economies had on average spent 7.4 percent of GDP on “above the line” measures in the form of budgetary fiscal support to people and firms in response to the pandemic (Bundervoet et al, 2021). These measures, which include cash transfers, expanded unemployment insurance, wage subsidies, and deferral of tax obligations, utility payments and social security contributions, have helped to mitigate the socio-economic impacts of the crisis on households and workers. Governments in EMDEs, however, have been able to spend far less on relief measures because of limited fiscal space. Spending on above the line fiscal measures by September 2020 amounted to 3.8 percent of GDP in emerging markets and 2.4 percent of GDP in low-income developing countries. As a result, though the economic downturn was on average less severe in lower-income countries, the impact on households and individuals may have been far worse, especially for the poor and vulnerable.

The vast gap in adequacy of relief measures between advanced and developing economies is apparent from social protection expenditures that are critical for protecting households, even though many developing countries have extended existing safety net programs and/or introduced temporary new ones. Low-income countries have spent an average of US$4 per person in COVID-19 social protection responses, compared to US$30 in lower middle-income and US$156 in upper middle-income countries (Annex, Figure A-4). Spending on social protection measures is especially low in South Asia and Sub-Saharan Africa (Gentilini et al., 2020). In the HFPS data, the share of households who report receiving public assistance in April-July 2020 rises with per capita GDP, with coverage rates of less than 10 percent seen for most low-income countries in Sub-Saharan Africa (Figure 10a). Coverage among those who lost jobs during the pandemic is also strongly correlated with per capita GDP – a large share of those affected in low-income countries did not receive public assistance, at least during the first few months of the crisis (Figure 10b).

Thus, by all indications, public social assistance in the early months of the pandemic was highly inadequate in most developing countries and particularly so in low-income countries. Within countries, those receiving assistance were more likely to have reported job and income loss during the pandemic and have low socioeconomic status (lower education level and larger household size). This suggests that for countries in our

> 14 While the indicator used here is whether the child engaged in any learning activities during school closures, using alternative outcome variables that specify the kind of learning activity the child was engaged in (completing homework provided by teacher, watching educational TV programs, meeting with teacher or private tutor) shows similar results.

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