from the HFPS to look at the pandemic’s socioeconomic and distributional impacts in the developing world. Kugler et al. (2021) and Khamis et al. (2021) have shown that these surveys are a rapid, efficient, and reliable source of data despite potential shortcomings. Kugler et al. (2021) as well as Bundervoet et al. (2021) both show that women, youth, and less-educated workers were significantly more likely to lose their job and experience reductions in income. Agrawal et al. (2021) use HFPS data from 17 developing countries to look at the distributional impacts of the pandemic, particularly how inequality has played a role in their economic recovery. They find that the lower-skilled, youth, and women were more likely to be impacted initially and that the recovery in employment was not sufficient to reduce the initial disparities in losses.

Our main contribution is threefold. First, we examine the differential impact of the pandemic on households across the welfare distribution using recent pre-existing or imputed data of welfare status before the onset of the pandemic, thus building on previous studies which mainly focus on impacts by gender, location, and education. We are able to obtain pre-COVID-19, household-level welfare data for all the high-frequency surveys administered in the EAP, allowing us to analyze the impacts the pandemic has had across welfare quintiles on household-level outcomes such as income, coping mechanisms, food insecurity, access to services, in addition to individual employment. Second, we take advantage of multiple rounds of data in each country, examining the evolution of impacts and coping methods over time: from periods of stringent mobility restrictions and lockdown to reopening and (limited) recovery. Third, unlike the global studies mentioned above, we aim to capture the heterogeneity of experiences across these seven EAP economies while highlighting emerging common patterns.

Our study suggests the following. First, at the extensive margin (work stoppages), employment impacts during the pandemic have been substantial among middle-income EAP countries, but particularly during periods of tighter mobility restrictions, either due to sudden or continuing lockdown measures. Second, the pandemic may have exacerbated existing inequalities, although in ways different from those typically observed in high-income countries. When mobility restrictions were high, workers experienced work stoppages across a wide range of sectors, and employment impacts were distributed relatively evenly across the welfare distribution. As economies in the EAP reopened, however, work stoppages became more selective, disproportionally affecting poorer workers. Our analysis also shows that less-educated, female, and urban workers were more likely to stop working. Taken together, these findings suggest unequal impacts of the pandemic that may jeopardize an inclusive recovery and exacerbate inequality in the EAP. Third, despite significant expansions of safety nets in several middle-income EAP countries, the depletion of physical and human capital has been more dire among the poor: When faced with income losses, poorer household are more likely to reduce their food consumption, accumulate debt and sell productive assets, undermining their ability to recover from the crisis. Finally, with prolonged disruptions in education in many EAP countries, differences in distance learning opportunities across welfare groups may be leaving poorer children behind, potentially having negative long-term consequences in inequality.

The paper is structured as follows. The first section describes the data and provides summary statistics of the key indicators used in this paper. Section 2 analyzes work stoppages by country-specific quintiles of the welfare distribution, across countries and over time. While impacts have been heterogeneous across countries, notable patterns emerge. Section 3 looks beyond work stoppages at changes in household labor income across the distribution. Section 4 briefly presents differences across quintiles in coping strategies, food insecurity, and access to education, which may have potential long-term implications for inequality within countries. Section 5 concludes.

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