and in and out of the region early on. Border closures and restricted trade with China, in addition to precautionary containment measures that were put in place at the onset of the pandemic had a profound economic impact on many EAP countries in the early months of 2020, before many other countries had felt its toll. Furthermore, despite being geographically close, many developing EAP countries had differing experiences during the pandemic in terms of the severity of local COVID-19 transmission, mobility restrictions, and economic impacts. For example, countries like Vietnam and Lao PDR had few COVID-19 cases throughout 2020 and after a brief period of mobility restrictions and an economic contraction in the first half of 2020, their economies rebounded relatively quickly until experiencing an uptick in cases in mid2021. On the other hand, countries such as Indonesia and the Philippines experienced a pandemic-induced health crisis early on which led to economic contractions that crippled the economy for much of 2020. Thus, the prolonged and varied impact of the pandemic across middle-income countries in the EAP region provides a befitting context to explore the distributional impacts of the economic crisis that have unfolded from the pandemic across different economies.

Our main source of data is the High Frequency Phone Surveys (HFPS), collected by the World Bank from May 2020 in collaboration with National Statistics Offices of numerous developing countries.<sup>2</sup> While these surveys are not without their caveats due to constraints of the mobile phone survey methodology,<sup>3</sup> they provide timely and useful indicative evidence on how COVID-19 has affected households, in the absence of standard labor force and expenditure surveys. Between May 2020 and June 2021, 11 countries in the EAP region administered the HFPS, of which nine implemented at least two surveys. The HFPS data analyzed in this paper<sup>4</sup> comes from seven of these countries and spans one year of the pandemic, from May 2020 to May 2021. Countries included in the analysis are Indonesia, Lao PDR, Mongolia, Myanmar, Philippines, Papua New Guinea (PNG), and Vietnam.<sup>5</sup> While the design of the HFPS differs slightly across countries, all surveys share a core set of indicators that provide insight into the socioeconomic impacts of the pandemic, including information on employment, income losses, coping mechanisms, food insecurity, and access to services.

The paper contributes to the burgeoning literature on the distributional impacts of the COVID-19 pandemic around the world. Numerous studies have documented the labor market and income impacts of the pandemic in high-income countries such as the United States, Japan, and the European Union, among many others. In the United States, Chetty et al. (2020) find that the pandemic led to widespread layoffs, which were greater and more long-lasting for low-wage workers. Other studies such as Gould and Wilson (2020) have documented the disproportionate impact the pandemic has had on black, Hispanic, and female workers in the United States. Several recent studies have used the World Bank’s global harmonized data

> 2 While most countries administered the HFPS in consultation with their local NSO, Mongolia was the only country in which the NSO was the implementing agency of the HFPS. Country-specific briefs and reports, produced by the country teams, can be found in the website links available here: <u>https://www.worldbank.org/en/topic/poverty/brief/high-frequency-monitoring-surveys</u>

> 3 All HFPS used here are nationally representative of households that have phones; hence their national representativeness depends on the country’s mobile phone penetration. In addition, by design, the questionnaires are much shorter (ideally, they should take less than 15 minutes to complete, with relatively simple questions) than standard face-to-face surveys, to ensure quality of responses. This means that the resulting indicators collected may differ from the official definitions (for instance, on employment) and that the analysis may be less comprehensive than what can be done with standard labor force surveys or the equivalent.

> 4 Note that the data used in this paper does not come from the World Bank’s global harmonized data set. While from the same sources of raw data, the data used here has been harmonized specifically for the purposes of this paper.

> 5 Four countries – Cambodia, Malaysia, Solomon Islands, and Thailand – also administered the HFPS but are not included in this analysis. At the time of this paper, Malaysia and Thailand had only implemented one round, for which data were not yet available. Solomon Islands had low representation of bottom 40 households. Cambodia’s small sample size, particularly in later rounds, made quintile-level disaggregation difficult.

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