The Pacific Observatory Socio-economic impacts of COVID-19 in Vanuatu Insights from High Frequency Phone Surveys, July-September 2022 The Pacific Observatory is… a World Bank analytical program that aims to improve welfare for the poor and vulnerable in Vanuatu and the The Pacific Pacific Island Countries through expanding socio-economic information for better data-driven policymaking. Key findings Observatory in This presentation utilizes data from the Pacific Observatory’s first round of high frequency Vanuatu phone survey in Vanuatu… To detail socio-economic indicators related to: - Employment and incomes - Child education, food insecurity and coping strategies - Health care access and COVID-19 Background Context: - The government issued a state of emergency for COVID-19 in March 2020. However, the first case of community transmission was observed only on March 4, 2022, followed by the implementation of lockdown and other restrictions. High Frequency Phone Surveys (HFPS): - To assess and monitor the economic and social impacts of the COVID-19 pandemic, the World Bank launched a household- level HFPS with a plan to continue surveys until mid-2024. - Surveys aim to interview the same households across rounds, with a complement of new households, to monitor various socio-economic outcomes and inform policy and government programs. - Similar HFPS have been implemented in Papua New Guinea, Solomon Islands, and Tonga, with Fiji in the pipeline, under the World Bank Pacific Observatory initiative. Employment and Income Key findings More than half of workers experienced income decline/loss in agriculture, manufacturing, and tourism-related service jobs. Poorer workers were less likely to be working at the time of the survey. Education Poorer households were more likely to stop their children from attending schools: 13% of children from those households have The findings point to the need of support for dropped out during the last 12 months. poorer households who tend to be disproportionately affected by economic Coping with the pandemic shocks. Moreover, a formal social While many people received private transfers (such as receiving protection system needs to be established as food and cash from family members, relatives, and friends) to deal informal social protection systems may not be with the shock, poorer people also relied on coping strategies that effective in the presence of covariate shocks would not last for long, such as cutting consumption and spending that affect both supporting and receiving from savings. families. Poorer people faced food insecurity more often. While 27% of population experienced food insecurity during the last month from the time of the survey, 38% of poorer people did so. Survey timing - before, during and after the COVID-19 outbreak First case of community transmission 3/4/2022 The first-round survey was collected after 300 100 the lifting of COVID-19 restrictions 90 250 80 - The Vanuatu HFPS interviewed 2,515 households % of people fully vaccinated / stringency index 70 between July 19 and Sept 16, 2022. 200 new COVID-19 cases 60 - The survey asked households about various socio- 150 50 economic characteristics – such as age and sex, 40 100 livelihood, asset ownership, food insecurity – to assess 30 20 the socio-economic impacts of the recent COVID-19 50 10 outbreak.* 0 0 1-Mar-2022 1-Apr-2022 1-May-2022 1-Jun-2022 1-Jul-2022 1-Aug-2022 1-Sep-2022 data collection period new COVID-19 cases (smoothed, LH axis) stringency index (RH axis) % of people fully vaccinated (RH axis) * See the Annex slide for the details of the survey methodology. Source: Our World in Data https://ourworldindata.org/. Data retrieved on September 2, 2022. Note: Stringency index is a composite measure based on nine response indicators including school closures, workplace closures, and travel bans, rescaled to a value from 0 to 100 (100 = strictest). Poorer people were less likely to be working at the time of the survey Employment Private transfers were an important household and incomes income source Experience of income reductions was prevalent, except for workers with professional or public jobs Household income sources (% of HHs, multiple choice) Private transfers, including Family farming or livestock 58% remittances, were an important Wage employment 49% household income source Assistance from family within the country 30% Remittances from abroad 28% Pension 27% Aside from incomes from agriculture and wage jobs, Fishing 25% households received private transfers from various Non-farm family business 22% sources, such as remittances* from abroad (28%), family members in the country (30%), and non-family Assistance from other non-family individuals 20% individuals (20%). Unemployment benefits 19% Households received government assistance in the form Assistance from NGOs 7% of unemployment benefits (19%) and pension (27%). The 6% Income from properties, investments, or saving former may reflect government’s third financial stimulus package, including Small Business Grants (SBG). Assistance from the government 3% 0% 10% 20% 30% 40% 50% 60% 70% 80% * Remittances refer to only transfers from abroad in this report. Note: Error bars indicate 90 percent confidence intervals. Source: Vanuatu HFPS R1 (July-Sept 2022) More than half the households experienced income reductions from non-farm family Changes in household incomes (% of households) businesses 0% 100% Income from farm business 23% 39% 37% A large proportion of households reported reduction in income from non-farm businesses since March 2022. Income from non-farm business More than half of households with non-farm businesses 27% 16% 57% (57%) had their incomes decreased since March 2022, while 27% of household experienced an increase. Remittances 17% 33% 50% Half of the households reported a reduction in the amount of remittances received. Remittances increased for 17% of households and stayed the same for 33% of Increase Stay the same Decrease or no income households. Source: Vanuatu HFPS R1 (July-Sept 2022) Note: Respondents reported income change between Mar and Sept 2022 retrospectively. * Farming activities involve growing crops, raising livestock and fishing Poorer people were less Employment status (% of adults) likely to be working at the 100% time of the survey 42% 41% 62% At the time of the survey, 58% of adults were working. 34% 33% The proportion of working adults are reported to be higher among male (64%) as opposed to female (51%) 6% 22% 6% and richer people (59%) as opposed to poor people 4% 19% 19% (38%). 12% 0% Among those working, 57% was doing so in the service All adults Bottom 40 Top 60 sector, followed by agriculture (33%) and industry (10%). Agriculture Industry Services Not working Source: Vanuatu HFPS R1 (July-Sept 2022) Note: Bottom 40 (Top 60) refer to workers in the households whose consumption levels are ranked in the bottom 40 percentiles (top 60 percentiles) based on the consumption distribution in the 2019 HIES data. Workers in agriculture, manufacturing, transportation, and tourism sectors experienced reductions in incomes… A large share of workers experienced reduction in their incomes in the following sectors: manufacturing (73%), transportation (72%), agriculture (57%), and tourism (54%). By contrast, relatively a small portion of workers reported reduction in incomes in financial and other professional sectors (13%) and education, health, and public administration (21%). Changes in income since the lockdown in March 2022 (% of workers) Manufacturing Transportation Mining Agriculture/Fishery/Livestock Buying&Selling/Personal Services Tourism/Hotels/Bars&Restaurants Domestic Household Services Construction/Utilities Handicrafts/Cultural Industries Education/Healthcare/Public Administration Professional/Scientific/Technical Activities Financial Services 0% 100% Increased Stay the same Decreased or no income Source: Vanuatu HFPS R1 (July-Sept 2022) … and many of those experiencing income reductions are informal workers Changes in income since the lockdown in March 2022 (% of workers) Manufacturing Transportation Mining Agriculture/Fishery/Livestock Buying&Selling/Personal Services Tourism/Hotels/Bars&Restaurants Domestic Household Services Construction/Utilities Handicrafts/Cultural Industries Education/Healthcare/Public Administration Professional/Scientific/Technical Activities Financial Services 0% 100% Increased Stay the same Decreased or no income Source: Vanuatu HFPS R1 (July-Sept 2022) Most households accessed healthcare when needed Access to Health Care and Households were not able to access health care mainly because they could not travel due to COVID-19 Education Children from poorer households were more likely to drop out of school during the last 12 months Most households were able to access health care when needed More than 95% of households accessed urgent/routine/preventive health care when needed during the last month. Households were not able to access health care mainly because they could not travel due to COVID-19. % of households who accessed health case when needed Urgent care Routine care Preventive care 3% 2% 5% 97% 95% 98% Yes No Source: Vanuatu HFPS R1 (July-Sept 2022) 7% of children dropped out during the last 12 months, with a higher 45% % of children with school attendance disrupted dropout rate among children from 40% poorer households 35% 30% Nearly 30% of children stopped going to school for some period during the last 12 months, and a quarter of them 25% (=7% of children) did not return to school (i.e., dropped 20% out). 15% Older children were more likely to have dropped out: 11% among the age 13-18 group. 10% Children belonging to poorer households are more likely 5% to have dropped out of school (13% in Bottom 40 vs 7% 0% in Top 60). All age 9 or younger 10-12 13-18 Bottom 40 Top 60 No distinct pattern is observed across locations. Did not go to school for some period during the last 12 months Dropped out Source: Vanuatu HFPS R1 (July-Sept 2022) Note: Error bars indicate 90% confidence intervals Food insecurity was prevalent – particularly among poorer Food security, people coping strategies and financial People dealt with shocks by relying on coping strategies that could not last for long anxiety Two thirds of households worried about their financial status for the next month Food insecurity was common, Experience of food insecurity during the last month (% of population) though households with 0% 10% 20% 30% 40% 50% 60% 70% 80% agricultural activities were less Did not have enough food likely to face the problemhello Unable to eat healthy food 3 in 5 people (60%) reported that they did not have Ate only few kinds of food enough food during the last month. Some people experienced a more severe situation: 14% Skipped a meal of people had an experience of being hungry during the last month. Moreover, 7% of people spent at least a Ate less whole day without eating anything. Ran out of food Households that engaged agricultural activities were less likely to experience food insecurity. Were hungry Did not eat a whole day Source: Vanuatu HFPS R1 (July-Sept 2022) Note: Error bars indicate 90% confidence intervals A quarter of people experienced food insecurity during the last month, with poor people more Food insecurity during the last month (% of population) likely to have done so 38% 30% 31% 31% 27% 26% 26% 24% Based on the Food Insecurity Experience Scale (FIES) measure, 27% and 5% of population experienced moderate and 5% 7% 7% 8% 4% 3% severe food insecurity, respectively, during 2% 1% the last month since the time of the survey. All people Shefa Sanma Other Urban Rural Bottom 40 Top 60 provinces Food insecurity was relatively higher in Location Wealth Group urban areas (31%, compared to 26% in rural areas) and among poorer people (38%, Moderate Severe compared to 26% among richer people). Source: Vanuatu HFPS R1 (July-Sept 2022) Note: Moderate food insecurity is typically associated with the inability to regularly eat healthy, balanced diets. Severe food insecurity implies a high probability of reduced food intake and therefore can lead to more severe forms of undernutrition, including hunger. Have you had to do any of the following since the lockdown starting in March 2022? (% of households, multiple choice) Many households, particularly Reduced non-food consumption 0% 20% 40% 60% 80% poorer ones, relied on coping Reduced food consumption Find ways to earn extra money strategies that could not last for long Spending from savings Reduce number of children attending school Other assistance from friends/family Sell harvest in advance A large proportion of households relied on coping Purchase on credit strategies that would harm them in the medium and long Delayed repayments terms, such as reducing non-food consumption (61%) and Advance from employer food consumption (46%), spending from savings (44%), Assistance from church/other religious body Assistance from community-based… and reducing number of children attending school (38%). Received cash or borrow from friends/family Poor households were more likely to rely on Assistance from NGO unsustainable coping strategies. Received a payout from provident fund Assistance from government Receiving private assistance was also common: from Start/Increase fishing friends and family (33%); church (15%); and community- Loan from moneylender/saving group Loan from financial institution based organizations (13%). Sold assets Only 9% of households relied on government assistance Sold livestock to cope with the shock. Source: Vanuatu HFPS R1 (July-Sept 2022) Note: Error bars indicate 90% confidence intervals Nearly 70% of households are worried about their financial status for the next month, though many are optimistic about the economy down the road hello Around two thirds of households were worried about their financial status for the next month, regardless of their income levels. Half of the households believed that the economy was going in the right direction, while 39% believed the opposite. People in Shefa were more likely to be optimistic about the future economy. Are you worried about your household's financial status for One year from now, do you think the state of the economy the next month? (% of households) will be…? (% of households) 100% 100% 33% 38% 33% 38% 39% 40% 4% 10% 11% 67% 62% 67% 58% 51% 49% 0% 0% All households Bottom 40 Top 60 All households Bottom 40 Top 60 Better Same Worse Worried Not Worried Source: Vanuatu HFPS R1 (July-Sept 2022) Source: Vanuatu HFPS R1 (July-Sept 2022) Note: Bottom 40 (Top 60) refer to workers in the households whose consumption levels are ranked in the bottom 40 percentiles (top 60 percentiles) based on the consumption distribution in the 2019 HIES data. Acknowledgments and further information Core Team: Rajee Kanagavel, Elene Metreveli, Shohei Nakamura* Extended team: Ritika Khandelwal, Anjali Agrawal, Shivapragasam Shivakumaran, Nobuo Yoshida Task Team Leaders: Utz Pape* and David Gould Practice Manager: Rinku Murgai *For inquiries, please contact Shohei Nakamura (snakamaura2@worldbank.org) and Utz Pape (upape@worldbank.org). The team gratefully acknowledges the Australian Department of Foreign Affairs and Trade for providing financial support for the data collection and analysis. All data collection and analysis was coordinated and carried out by the World Bank with support from the Vanuatu Bureau of Statistics. References World Bank COVID-19 Household Monitoring Dashboard Annex: survey methods The Round 1 Vanuatu HFPS was collected from 2,515 households between July 19 and September 16, 2022. The implementation was led by Sistemas Number of interviewed households Integrales in collaboration with Vanuatu National by location Statistics Office. Comparison of welfare distributions in HFPS 2022 and HIES 2019/20 The sample was drawn from 1) the National # of HHs 30 Sustainable Development Plan Baseline Survey Shefa Urban (Port Vila) 1,035 25 % of population 2019/20 (406 households) and 2) based on a Shefa Rural 569 20 Random Digit Dialing (RDD) method (2,109 15 Sanma Urban 294 households), covering all the cell phones in the (Luganville) 10 country. Sanma Rural 222 5 Household consumption expenditures are imputed Other rural areas 395 0 1 2 3 4 5 6 7 8 9 10 with the SWIFT approach that develops a prediction Total 2,515 Decile based on HIES model based on the HIES 2019/20. HFPS (weighted) HIES The sample is weighted to adjust for population distributions across locations and other socio- economic characteristics.