Monitoring COVID-19 Monitoring COVID-19 impacts REPORT NO. 1 REPORT NO. 1 on households in Ethiopia 4 / June / 2020 4 / June / 2020 Impacts on Households in Ethiopia Results from a High-Frequency Phone Survey of Households Authors: Christina Wieser, Alemayehu A. Ambel, Tom Bundervoet, and Asmelash Haile The COVID-19 pandemic and its economic and social effects on households have created an urgent need for timely data to help monitor and mitigate the social and economic impacts of the crisis and protect the welfare of the least well-off in Ethiopian society. To monitor how the COVID-19 pandemic is affecting Ethiopia’s economy and people and to inform interventions and policy responses, the World Bank designed and conducted its High-Frequency Phone Survey of Households (HFPS-HH). The HFPS-HH builds on the national longitudinal Ethiopia Socioeconomic Survey (ESS) that the Central Statistical Agency (CSA) carried out in 2019 in collaboration with the World Bank. The HFPS-HH drew a subsample of the ESS sample that was representative of households with access to a working phone. The same households will be tracked over six months, with selected respondents (typically the household head) completing phone-based interviews every three to four weeks. This high-frequency follow-up allows for better understanding the effects of and household responses to the COVID-19 pandemic in near real time to support new, evidence-based responses. This survey brief summarizes the results of the first round of the HFPS-HH, implemented between April 22 and May 13, 2020.1 The brief is based on a sample of 3,249 households in both urban and rural areas in all regions of Ethiopia. The 15-minute questionnaire covers such topics as knowledge of COVID and mitigation measures, access to educational activities during school closures, employment dynamics, household income and livelihood, income loss and coping strategies, and assistance received. Households seem well aware of COVID-19, and the vast majority have knowledge of behaviors necessary to minimize the risk of contracting or spreading the virus. Schools have been closed for two months but in only 12 percent of rural households are children engaged in any form of distance learning. The percentage in urban areas is more than three times higher. The COVID-19 pandemic has hit total household incomes hard: 55 percent of respondents report that household incomes were either reduced or had totally disappeared. 13 percent of respondents lost their job since the outbreak of COVID-19 in Ethiopia—18 percent in urban areas and 10 percent in rural areas. Hospitality, construction, and wholesale and retail were the most affected in terms of job losses. Since the outbreak began 8 percent of households—10 percent of rural and 3 percent of urban—have received assistance from government, NGOs, or religious institutions. To prevent the spread of COVID-19 and to ensure that measures to slow it, such as mobility restrictions and market closures, are effective, it is essential that people be aware of the need to change their behaviors. Virtually every household (99.7 percent) had heard about the coronavirus or COVID-19. The respondents reported being well- informed about actions to reduce the spread. Almost everyone knew about handwashing, and 89 percent knew 1 The data collection was undertaken by Laterite (Ethiopia) Ltd. Monitoring COVID-19 impacts REPORT NO. 1 on households in Ethiopia 4 / June / 2020 that it is important to stay home and avoid gatherings (Table 1). Differences between urban and rural areas are relatively small. About 93 percent of respondents know of steps taken by the government or local authorities to curb the spread in their area, and almost all indicated they had changed their behavior to reduce the risk of contracting COVID-19. About 98 percent of respondents wash their hands more often than before COVID-19, 96 percent avoid handshakes or physical greetings, and 83 percent avoid gatherings (Table 2). However, we have to be careful in interpreting these results because there seems to be a tendency to overreport positive behavior changes. Table 1: Knowledge of Actions to Reduce Exposure, Percent Table 2: Changes in Behavior to Reduce Exposure, Percent Rural Urban National Rural Urban National Wash hands 99.3 99.9 99.5 Wash hands more frequently 98.1 99.1 98.4 Avoid handshaking and physical Use gloves 60.8 77 66.2 95.8 96.6 96.1 greetings Avoid travel 83.3 93.1 86.6 Avoid gatherings 81.3 87.1 83.2 Stay home 86.1 94.5 88.9 Avoid gatherings 85.6 94.6 88.6 Self-distance 92.7 98.2 94.6 Avoid touching face 85.3 97.3 89.3 How COVID-19 has affected the availability and prices of medicine and food staples is yet to be fully understood. If individuals seek to stockpile in periods of scarcity, there may be scarcity and rises in the prices of commodities in demand. Combined with loss of income, higher food prices and eventual shortages could erode the welfare of households. The HFPS-HH survey instrument asked respondents whether their household was able to buy enough medicine and enough of the most important food items during the week preceding the survey.2 Where they were not, we asked for the reason. About 70 percent of households were able to buy medicine. Of those that could not, affordability was the main reason: 68 percent cited lower regular income and 14 percent higher prices. We see a similar pattern for the main food items households consume. Most households were able to buy enough of what they needed: teff (68 percent), wheat (82 percent), maize (86 percent), and edible oil (77 percent). Of those who could not buy enough food, affordability—again because of higher prices or less regular income—was the biggest challenge (Table 3). For some items, such as edible oil, local markets do not seem to be operating. To gauge price problems and whether markets are closing, it will be important in future rounds to monitor trends. When combining reasons related to all medicine and food staples, we observe that aside from affordability—a challenge in both urban and rural areas—urban areas are more affected by shops running out of stock (11 percent) and rural areas by markets not operating (9 percent). Table 3: Reasons for Household Inability to Buy Certain Items, Percent Limited/No Shops have run Local markets transportation Increase in Decrease in Other out of stocks not operating and restriction price regular income to go outside Medicines 5.3 1.9 6.8 13.9 67.6 4.5 Local markets not operating 1.5 4.3 1.3 28.5 58.8 5.6 Wheat 3.2 6.2 3.9 40.3 39.3 7.2 Maize 2.4 10.1 2.8 35.8 37.8 11.2 Oil 6.5 10.1 4.0 43.4 29.4 6.6 Table 4 shows differences across the bottom 40 percent of the distribution and the top 60 percent in terms of the reasons for why households were unable to buy certain items. We see that poorer households are disproportionally affected by increases in prices but less affected by decrease in regular income compared to the top three quintiles of the distribution. 2 According to the 2018‒19 ESS, the four most important food items are teff, wheat, and maize, whether grain, flour, or cooked, and edible oil. Monitoring COVID-19 impacts REPORT NO. 1 on households in Ethiopia 4 / June / 2020 Table 4: Reason for Household Inability to Buy Certain Items, by Bottom 40%, Percent Bottom 40% Top 60% Shops have run out of stock 5.8 8.6 Local markets not operating 8.8 6.6 Limited/no transportation & restriction to go outside 2.0 6.9 Increase in price 44.5 36.2 Decrease in regular income 30.2 41.0 Other 8.7 0.7 On March 16, 2020, Ethiopia closed all primary and secondary schools. In addition to students losing valuable months of schooling, school closures may deprive the children of poor families of food, because they often rely on school feeding programs; for example, all children in Addis Ababa public schools participate in a twice-daily school feeding program. Temporary school closures may also lead to permanent drop-out of children from vulnerable households, especially in rural areas where even in ordinary circumstances early drop-out is rife. The long-term impacts of lost months of schooling and nutrition will be particularly severe for children in poor families, because it will jeopardize their development of human capital and their earning potential. The survey asked households how many children (boys and girls separately) were in school before the outbreak began and whether they are now engaged in any learning activities. Once schools reopen, we will follow up to see how many children returned to school. About 76 percent of households (82 percent in rural and 64 percent in urban areas) have school-aged children. Of those, 91 percent have children who had attended school before outbreak; there was no difference for urban and rural households. Only 20 percent of children who attended school before closure are engaged in distance learning activities. In rural areas, just 12 percent of households have children engaged in any form of learning activity, compared to 39 percent of urban households (Figure 1). Due to differences in electricity access and ownership of TVs, radios, and phones, the types of distance learning activities in urban and rural areas differ widely. For rural children engaged in learning activities, by far the most wide-reaching activity is listening to educational radio programs, as was done in 84 percent of the households with such learners (Figure 2). Only 9 percent of rural households use educational TV programs; 8 percent use mobile learning apps; 7 percent complete assignments provided by the teacher; and 6 percent have meetings with teachers. However, in urban areas the most common activity is to complete assignments provided by the teacher (38 percent), followed by watching educational TV programs (34 percent), listening to educational radio programs (19 percent); few urban children, perhaps surprisingly, use mobile learning apps (16.6 percent); and meetings with lesson teachers (15 percent). Figure 1: Households with Students who Previously Attended School Figure 2: Educational Activities Students Engage During School and now Engage in Learning Activities, Percent Closures, Percent 39.0 Listened to educational programs 19.1 on radio 84.4 Completed assignments 37.6 provided by the teacher 6.7 19.6 Watched educational TV 34.4 programs 8.6 12.4 16.6 Used mobile learning apps 7.6 Session/meeting with lesson 15.2 teacher (Tutor) 5.9 0.0 50.0 100.0 RURAL URBAN NATIONAL Urban Rural In Ethiopia protracted school closures affect both public and private schools and thus all income segments. However, because the better-off segments of society (e.g., with parents who themselves are educated, and can pay for private tutors) are better able to provide learning opportunities for their children, the already wide learning gap between children in poor vs. better-off households and rural vs. urban households can be expected to increase. Monitoring COVID-19 impacts REPORT NO. 1 on households in Ethiopia 4 / June / 2020 Indeed, Table 5 shows that richer quintiles are more likely to engage in distance learning activities in urban and rural areas and differences are particularly stark in urban areas where only 14 percent of the poorest 20 percent of households engages their children in distance learning activities but 38 percent of the richest 20 percent does so. Table 5: Any Learning Activity, by Consumption Quintile, Percent Q1: Poorest Q2: Poorer Q3: Middle Q4: Richer Q5: Richest Rural 11.5 9.6 13.3 17.4 14.8 Urban 34.9 31.9 32.4 37.8 51.1 National 13.8 13.2 18.1 27.1 37.5 One of the channels through which households are negatively affected by the pandemic and its associated restrictions of movement and assembly is through reduced income. The survey asked households about their income sources over the last 12 months and followed up by asking whether the income from a particular source has increased or decreased since COVID-19 broke out (Table 6). Not surprisingly, for 83 percent of rural households farming was the main means of livelihood over the previous 12 months, followed by nonfarm business (16 percent), wage employment (13 percent), and government assistance (12 percent). While rural households largely depend on farming, urban households tend to have a larger variety of income sources. For almost half of urban households, wage employment was a means of livelihood (47 percent), followed by nonfarm business (31 percent), and farming (24 percent). Table 6: Household Income Sources, Last 12 months, Percent Rural Urban National Farming, livestock, or fishing 83.0 23.7 63.4 Nonfarm business 16.4 31.1 21.3 Wage employment 12.6 47.1 24.0 Remittances from within Ethiopia 2.7 10.3 5.2 Remittances from abroad 3.6 6.0 4.4 Income from properties, investments, and savings 5.4 11.9 7.5 Pension 0.1 5.3 1.8 Government assistance 11.9 4.0 9.3 Assistance from an NGO or charitable organization 4.2 1.1 3.2 There was a steep reduction in self-reported labor income since the outbreak of COVID-19 (Table 7). About 85 percent of households that cited nonfarm business as a means of livelihood in the past 12 months reported less income from that source (58 percent) or a total loss of that income (28 percent). Income from farming, which usually is already low at this time of year due to seasonality, was also down for 40 percent of households; and as for wage employment, 34 percent of households with income from wages had lost some or all of their income from this source. Table 7: Change of Total Household Income Since the Outbreak by Source, Percent Total Loss/ No Increased Stayed the Same Reduced Income Farming, livestock, or fishing 1.9 56.8 39.6 1.8 Nonfarm business 1.2 13.6 57.6 27.5 Wage employment 0.6 65.0 22.8 11.7 Remittances from within Ethiopia 3.1 52.1 33.1 11.7 Remittances from abroad 1.0 36.5 23.8 38.7 Income from properties, investments, and savings 2.4 55.9 33.9 7.9 Pension 0.6 95.4 3.9 0.1 Government assistance 12.5 60.2 13.1 14.3 Assistance from an NGO or charitable organization 15.4 42.8 20.2 21.6 Monitoring COVID-19 impacts REPORT NO. 1 on households in Ethiopia 4 / June / 2020 When looking at changes in total household income since the outbreak of COVID-19 by consumption quintile, we observe that there are little differences in reduced income among the poor and the rich (Table 8). The poorest 20 percent are more likely to see reduced incomes (53 percent) compared to the richest 20 percent (47 percent) but the rich are more likely to experience a total loss of income. Table 8: Change of Total Household Income Since the Outbreak, by Consumption Quintile, Percent Q1: Poorest Q2: Poor Q3: Middle Q4: Rich Q5: Richest Increased 1.2 2.0 1.6 0.7 1.1 Stayed the same 44.6 44.8 40.2 44.7 46.4 Reduced 52.8 48.2 54.8 49.8 46.9 Total (100%) loss 1.2 5.0 3.4 4.5 5.6 In the previous 12 months domestic or international remittances contributed to their livelihoods for 16 percent of urban and 6 percent of rural households (Table 4), but that has plunged since the virus attacked. About 45 percent of households that reported domestic remittance as a recent means of livelihood have seen the reduction or total loss of remittances from within the country. Remittances from abroad have been even more strongly affected: 24 percent of beneficiary households reported a reduction and 39 percent a total loss. The reduction in remittances from abroad experienced by two-thirds of recipient households is a particular concern because beyond being a source of income for many Ethiopians, remittances also account for a significant fraction of the country’s foreign exchange. An estimated 2 million Ethiopians live and work elsewhere in the world; most of them reside in the U.S., Europe, and the Middle East. The decrease in their remittances can be particularly harmful for the urban poor. According to the 2016 ESS, vulnerable urban households, those in the second quintile of the welfare distribution, rely most on remittances from abroad—almost 8 percent of the quintile. Government assistance is a source of income for 9 percent of households, and another 3 percent receive assistance from a nongovernmental organization (NGO) or other charitable organization: 15 percent of households relying on NGO help and 13 percent of those relying on government assistance reported an increase in this source of income since the outbreak began. On the other hand, 42 percent of households previously receiving income from NGOs now have less or no income from them. Now, when households need assistance the most, it will be vital to ensure that they continue to receive it from somewhere. Not surprisingly, income from pensions has largely held steady through the outbreak. Asked whether the total income of the household has changed since the outbreak began (Figure 3), 55 percent of respondents report either a reduction (51 percent) or a total loss (4 percent). Households suffering from less or no income were then asked what if any coping strategies they had applied to better manage the income reduction. More than half had not applied a coping strategy to compensate (Table 9). The most common coping strategy applied was to rely on savings—almost one fifth of households relied on savings to cope with reduced income, with a much larger percentage in urban (34 percent) compared to rural areas (11 percent). The second and third most prevalent coping strategies are to reduce food consumption (applied by 13 percent of households) and reducing nonfood consumption (10 percent). Reducing consumption is concerning as it could affect the long-term health of household members. Coping strategies are also quite different across the distribution. There are slight differences in coping strategies among the poorer and richer Ethiopians. The bottom 40 percent are more likely to have done nothing (60 percent) while the top 60 percent are more likely to have relied on savings (25 compared to 12 percent of the bottom 40 percent). Monitoring COVID-19 impacts REPORT NO. 1 on households in Ethiopia 4 / June / 2020 Figure 3: Change in Total Income since the Table 9: Coping Strategies, Percent Outbreak, Percent Increased Stayed the same Bottom Rural Urban Top 60% National Reduced Total (100%) loss 40% 1.8 8.1 3.9 Sale of assets (Agricultural and 5.9 0.7 5.4 3.0 4.0 Non-agricultural) Engaged in additional income 49.8 50.7 2.9 2.6 3.5 2.4 2.8 52.4 generating activities Received assistance from friends & 0.9 7.3 2.3 3.8 3.2 family Borrowed from friends & family 4.0 3.7 4.0 3.7 3.8 46.7 Reduced food consumption 11.0 16.0 12.1 13.3 12.8 38.6 44.1 Reduced nonfood consumption 9.1 11.5 10.7 9.5 10.0 Relied on savings 11.3 33.8 12.0 24.7 19.5 1.6 0.9 1.3 Did nothing 59.1 48.4 60.0 52.0 55.2 RURAL URBAN NATIONAL All others 5.9 2.4 4.1 5.0 4.6 The COVID-19 pandemic is affecting economic activity in Ethiopia; some of the sectors being hit hardest are aviation, horticulture, light manufacturing, and the hospitality industry. Though the State of Emergency declaration prohibits firms from laying off workers, in Ethiopia’s sizable informal sector lay-offs can nevertheless be expected. The HFPS-HH provides evidence about changes in the employment situation of households resulting from the pandemic. About 63 percent of respondents were working at the time of the phone interview, with few differences between urban and rural households (Table 10). Of respondents not working at the time of the interview, about 26 percent had been working before the outbreak—a percentage that rises to 42 percent in urban areas. Overall, 13 percent of respondents had lost their jobs since the outbreak of COVID-19 began (18 percent in urban areas and 10 percent in rural). Of those, 63 percent attributed their job loss to the outbreak and 19 percent to seasonal or casual work, with a higher proportion in rural areas (27 percent) engaged in seasonal agricultural activities. About 11 percent indicated that they are temporarily absent, suggesting that they intend to go back to their jobs. Table 10: Current and Pre-COVID-19 Employment Status, Percent Rural Urban National Currently Working 62.9 64.5 63.4 Currently Not Working 37.1 35.5 36.6 Out of those who are not currently working Working pre-COVID-19 18.6 42.3 26.0 Not Working pre-COVID-19 81.4 57.7 74.0 Reasons for job ending since the outbreak began Due to COVID-19 61.2 64.3 62.8 Seasonal/ casual work 27.4 11.2 19.2 Temporary absence 9.0 13.7 11.4 Other reasons 2.4 10.7 6.6 Respondents most likely to have lost their jobs since the outbreak worked in the hospitality industry (38 percent), followed by construction (33 percent), and wholesale and retail trade (31 percent) (Figure 4). Agricultural workers had, as expected, the lowest probability of losing their jobs. However, given the importance of agriculture and wholesale and retail trade in total employment, these sectors together still account for over 40 percent of job losses so far.3 In terms of employment status, casual workers were most likely to have lost jobs (38 percent), followed by wage employees in the private sector (20 percent) and the self-employed (11 percent) (Figure 5). Given the magnitude of self-employment in Ethiopia, this employment type accounts for the bulk of the individuals losing jobs (54 percent of all job losses). 3 Note that although 61 of these job losses are COVID-related, 39 percent are not. Monitoring COVID-19 impacts REPORT NO. 1 on households in Ethiopia 4 / June / 2020 Figure 4: Respondent Job Loses since the Outbreak Began, by Figure 5: Respondents who Lost Jobs since the Outbreak Began, by Sector, Percent Employment Status, Percent Restaurants, hotels, bars,… 38.4 Casual work 37.8 Construction 32.7 Wholesale and retail trade 31 Personal services 27.5 Private sector wage employee 20 Industry/manufacturing 22.8 Transport services 16.5 Self-employed 10.8 Agriculture 5.3 0 10 20 30 40 50 0 10 20 30 40 50 Job losses have so far been lower among poor households, which tend to rely on agricultural employment (and agriculture had the lowest job losses). Female respondents were more likely to have lost their job (15 percent) relative to male respondents (12 percent)4, and younger respondents were also more likely to have lost their job (17 percent of 15 to 29-year-olds lost their job since the outbreak). Job losses were highest among respondents with incomplete secondary education (28 percent), who are overrepresented in hard-hit sectors (hospitality, wholesale and retail, construction, personal services). Moreover, for respondents engaged in wage employment, 81 percent (84 percent in urban areas and 76 percent in rural) indicated that they were able to carry out their job as usual, either at work or from home. For those not able to carry out their work “normally” (19 percent), about 50 percent were still being paid (65 percent in urban areas, just 30 percent in rural). Almost one quarter of respondents owned a nonfarm family business—18 percent in rural and 30 percent in urban areas. Of those, 86 percent in urban and 69 percent in rural areas indicated that their income from the family business is less than usual or has disappeared (Table 11). The reasons most often stated for the reduction in business income are that (1) the place of business is closed because of coronavirus, (2) there are no customers, and (3) they are unable to sell or transport outputs (Table 12). Table 11: Nonfarm Family Businesses: Changes in Income since Table 12: Reasons for Lower Business Income since COVID-19 the COVID-19 Onset, Percent Onset, Percent Higher The same Less than Rural Urban National No income than usual as usual usual Usual place of business closed 45.8 43.8 44.7 Rural 2.5% 28.8% 42.5% 26.2% because of coronavirus Urban 0.7% 13.4% 67.4% 18.5% Usual place of business closed for 14.2 7.0 10.1 National 1.7% 21.9% 53.7% 22.8% reason other than coronavirus Seasonal closure 9.1 11.1 10.2 No customers 301.2 54.5 44.4 Unable to acquire or transport 12.8 11.2 11.9 inputs Unable to sell or transport 31.0 23.9 27.0 outputs One drawback of the phone survey is the necessary restrictions on questionnaire length and complexity, which prevents us from asking about other household members in detail. However, given our interest in employment, we did ask respondents about the employment status of other household members. About 7 percent of rural and 26 percent of urban households had members who were wage-employed before the outbreak began. Of those, 30 percent in rural and 21 percent in urban areas had since lost their jobs, with about 80 percent relating the job loss directly to the pandemic. 4 However, given that men are more likely to be employed to begin with, the bulk of people who lost their job are men (71 percent). Monitoring COVID-19 impacts REPORT NO. 1 on households in Ethiopia 4 / June / 2020 Though food security in Ethiopia has improved in recent years, and though the share of Ethiopians who experienced a food shortage dropped from 22 to 10 percent between 2011 and 2016 (Welfare Monitoring Surveys [WMS]), food security is still a major concern, particularly for rural populations, and is at the heart of Ethiopia’s social protection system. To gauge how Ethiopians are faring on food security indicators in the pandemic, the survey instrument asks about food insecurity. We learned that 23 percent of households had run out of food in the previous 30 days, in 21 percent an adult went hungry but did not eat, and in 14 percent an adult went without eating for the whole day. There are no major food insecurity differences between urban and rural areas. Food security is, not surprisingly, higher for households in the upper part of the distribution. For example, 20 percent of the poorest 20 percent of households indicated that an adult went hungry without eating the whole day but only 7 percent of the richest 20 percent did (Table 13). Food security is measured for the previous 30 days, which for this phase of our survey is mid-March and April. March is the month in which food security tends to diminish and food prices start to rise. By then many rural households, especially smallholder farmers, are beginning to run out of the food they stocked up after the harvest. Based on monthly food security patterns identified by the ESS, we expect food security to deteriorate over the next few months, until the harvest. Results from the food security questions will be even more valuable when compared with those of the coming survey rounds, which will give us the opportunity to look at changes in food security throughout the pandemic. Table 13: Household Food Insecurity Experience by Consumption Quintile, Percent Q1: Poorest Q2: Poorer Q3: Middle Q4: Richer Q5: Richest Household ran out of food 29.8 28.3 25.8 16.7 15.0 Adult hungry but didn't eat 24.3 25.2 23.7 17.3 14.9 Adult went without eating for whole day 19.6 16.6 15.3 9.1 7.4 Note: The food insecurity experience by any adult household member for the 30 days Households have been hit hard by the COVID-19 pandemic, with over half reporting a reduction in total household income since the virus broke out. About 8 percent of households—10 percent of rural and 3 percent of urban— have received assistance through any means (government, NGOs, or religious institutions) since the outbreak began (Table 14). The largest proportion of the assistance provided was free food (47 percent) and direct cash transfers (39 percent). The largest contributor was the government: 77 percent of assistance (83 percent in urban and 76 percent in rural areas). About 80 percent of government assistance came through the urban and rural Productive Safety Net Programs. Future survey rounds will be able to show whether assistance to households is being expanded during the pandemic and if assistance reaches those most in need. Table 14: Assistance to Households since the COVID-19 Outbreak, by Type and Source, Percent Rural Urban National Household received assistance: Any source 10.0 3.1 7.8 Assistance type: Free food 44.1 67.7 47.2 Assistance type: Food or cash for work 16.9 7.9 15.7 Assistance type: Direct cash transfer 39.4 33.5 38.6 Assistance source: Government 76.0 82.6 76.9 Assistance source: NGO 13.6 0.2 11.8 Assistance source: Religious Organization 4.2 4.1 4.2 Assistance source: Volunteer/ youth Organization 6.1 12.4 7.0 Note: Assistance source and assistance type conditional on assistance received. Monitoring COVID-19 impacts REPORT NO. 1 on households in Ethiopia 4 / June / 2020 This survey brief is the first in a series reporting on the findings of the HFPS-HH. It reports on results from round 1, for which households in Ethiopia were interviewed between April 22 and May 13, 2020, about the effects of and responses to the COVID-19 pandemic. Data collection will continue by following up with the same households every three to four weeks. Round 2 began on May 15, 2020. Each round’s survey brief, table of indicators, and microdata will be available at https://www.worldbank.org/en/country/ethiopia/brief/phone-survey-data- monitoring-covid-19-impact-on-firms-and-households-in-ethiopia. The high-frequency phone survey of households monitors the economic and social impacts of and responses to the COVID-19 pandemic on households in terms of such topics as access to food staples, access to educational activities during school closures, employment dynamics, household incomes and livelihoods, income losses and coping strategies, and external assistance. The final dataset will cover a panel of about 3,200 households that is representative of households with access to a mobile phone nationally and of urban and rural areas. To the extent possible, the same households and respondents will be tracked for six months, with selected respondents completing phone- based interviews every three to four weeks. This high-frequency follow-up allows for a better understanding of the effects of and responses to the COVID-19 pandemic on households in order to inform interventions and policy responses and monitor their effects. The respondent is typically the household head; where that person cannot be reached despite numerous call-backs, another knowledgeable household member will be selected as the respondent. The HFPS-HH sample consists of a subsample interviewed for the Ethiopia Socioeconomic Survey (ESS) in 2019, namely those households with access to a phone, covering urban and rural areas in all regions of Ethiopia. The HFPS-HH called all households providing a valid phone number in the ESS, totaling 5,374 households. Phone penetration rates in rural Ethiopia are low; roughly 40 percent of households in rural areas have access to a phone compared to over 90 percent in urban areas. This not only means that our sample size in rural areas is relatively low, we also observe a systematic difference among households owning a phone and those who do not. Phone owning households are better off in terms of total consumption, educational attainment, access to improved water and sanitation, access to assets, and access to electricity. The sample of the HFMP-HH is therefore only representative of households who have access to phones in urban and rural Ethiopia. Data collection parameters, round 1 ❖ Data collection period: April 22 and May 13, 2020 ❖ Completed interviews: 3,249 households (978 in rural areas, 2,271 in urban areas) ❖ Average duration of interview: 16 minutes