||1<br>Jul-Sep20|31|75|83|53|50|13|
|---|---|---|---|---|---|---|---|
|Philippines|2<br>Oct-Dec20|24|57|76|58|37|33|
||3<br>Apr-Jun21|21|63|90|14|35||
|PNG|1<br>May-Jun20|44|59|52|30|44||
||2<br>Oct-Dec20|33||||||
||1<br>May-Jun20|3|32|16|5||58|
|Vietnam|2<br>Jul-Sep20|9|31|8|2|||
||3<br>Jul-Sep20|7|27|8|1|||

First, we look at work stoppages and reductions in labor income in order to assess how the pandemic has affected employment and income for workers and households across the welfare distribution. _Work stoppages_ are defined as the share of respondents (i.e., subjects of the employment module) working prepandemic who were not working in the seven days preceding the survey. _Reductions in labor income_ are defined as the share of households with wage or farm/non-farm business income that reported experiencing a reduction in income from these sources since the previous round.<sup>10</sup> We also assume that work stoppages translate into losses in labor income.<sup>11</sup> To examine the _coping strategies_ households have employed to deal with pandemic-induced shocks, we examine the use of savings in addition to coping mechanisms that involve selling productive assets or are potentially debt-increasing – namely, crediting purchases, delaying payments, or borrowing from friends, family, moneylenders, or other sources. Both outcomes look at use of coping mechanisms among all households since the previous survey round.

Finally, we explore potential longer-term effects on human capital accumulation by looking at food insecurity and engagement in interactive distance learning among school-age children. In this paper, we define _food insecurity_ as the share of households that reported that they had either run out of food, went hungry, or was hungry but did not eat, due to a lack of money or resources in the 30 days preceding the survey. _Engagement in interactive distance learning_ is the share of households with children attending school before the pandemic whose children either used mobile apps, online or in-person meetings/sessions with a teacher or tutor, or other online learning platforms in the week prior to the survey.

# Mobility and timing of the surveys

Across and within the seven EAP countries included in this analysis, mobility restrictions varied substantially between May 2020 and May 2021,<sup>12</sup> reflecting the variation in the severity of the pandemic and related

> 10 Looking at changes in income between rounds does not take into consideration net changes in income since pre-pandemic. For example, a household may have faced an income loss between pre-pandemic and round 1 but may have experienced an income gain between round 1 and round 2. Without information on the magnitude of these changes, it is difficult to say whether the household experienced a net loss, net gain, or income stayed the same relative to before the pandemic. Information on net losses are only available for a few country-rounds, so we look at changes in income between rounds instead.

> 11 Data from Mongolia and Myanmar, for instance, indicate that the majority of those who stop working do not have a job to return to or have a job to return to but have experienced a reduction in wages. Thus, the assumption of lower labor income appears to be reasonable.

> 12 Mobility is measured using data from the Google Mobility Reports, and the mobility index is here defined as the average percentage change in mobility to retail and recreation, transit stations, parks and workplace, relative to a pre-pandemic baseline level. We also analyzed the stringency index - as reported by the Oxford Coronavirus Government Response Tracker (OxCGRT)

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