supports largely dropped off by August 2020 and all groups had low access to external support thereafter.

**Overall, these results suggest that urban households relying on informal enterprises were particularly vulnerable to the COVID-19 crisis and may need further assistance to get back on their feet.** While these households experienced significant income loss, neither public nor private income support was disproportionately directed to them. Enterprise-owning households that were poor, female-headed, and youth-led faced particular difficulties during the recovery.

# **1. Data and Definitions**

**We use data from Waves 1 through 11 of the High-Frequency Phone Survey (HFPS) that were supported and harmonized by the World Bank during the first year of the COVID-19 pandemic** . The HFPS is a World Bank data collection initiative that sought to implement phone surveys in a variety of countries.<sup>2</sup> To construct the sample for the HFPS in each country, a random sample was drawn from a previously sampled household survey that provided cell phone numbers.<sup>3</sup> We use the data that were collected across the first year of the HFPS effort, from April 2020 to April 2021.

**We use a subset of 13 African countries that include variables that allow us to identify urban households that own enterprises** . Since the survey questionnaire differs between countries, we are not able to use all the HFPS data collected in SSA. We use only those surveys that include variables to identify urban household enterprises and income changes. We focus on urban households because they were more heavily affected by the crisis, due to their greater reliance on face-to-face economic interactions that were severely curtailed by lockdowns.<sup>4</sup> The countries in Sub-Saharan Africa that meet our criteria are Burkina Faso, Chad, Ethiopia, Madagascar, Malawi, Nigeria, São Tomé and Príncipe, Senegal, Sierra Leone, Somalia, South Sudan, Sudan, and Zimbabwe, representing 45 percent of the population of SSA (516 million people) in a range of countries from different parts of the continent, large and small economies, different levels of economic development, and large and small labor forces. While the sample is not representative of the Sub-Saharan Africa region, it does reflect the region’s diversity.<sup>5</sup>

**The HFPS is a nationally representative sample of households, with two important caveats** . The HFPS includes weights that attempt to make the survey nationally representative of households. These weights are derived from nationally representative baseline surveys conducted prior to the crisis (Brubaker et al. 2021).  However, the sampling frame has two major limitations. First, the survey excludes the portion of the population that were unwilling or unable to participate, for example because of lack of access to phones or a stable phone network.<sup>6</sup> Second, because

> 2 https://www.worldbank.org/en/data/interactive/2020/11/11/covid-19-high-frequency-monitoring-dashboard

> 3 The HFPS sample was not stratified by poverty status, social assistance receipt, or any other variable.

> 4 As shown in Contreras-Gonzalez et al. (2021) and Kugler et al (2021), although rural households were affected by the pandemic (especially through increasing prices and inflation, as well as reduction in remittances), they were able to maintain a more stable farm income and cope with the crisis.

> 5 Given the differences in how and when COVID-19 affected economies across Africa, we were unable to identify a weighting strategy so that the sample could be representative of the region.

> 6 This may have been a small share since we focus on urban areas, which have quite high cell phone coverage in Africa.

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