A YEAR DEFERRED – EARLY EXPERIENCES AND LESSONS FROM COVID-19 IN VIETNAM A YEAR DEFERRED – EARLY EXPERIENCES AND LESSONS FROM COVID-19 IN VIETNAM ii A YEAR DEFERRED – EARLY EXPERIENCES AND LESSONS FROM COVID-19 IN VIETNAM Acknowledgements This report was prepared by a team from the Equitable Growth, Finance and Institutions Practice Group (EFI) who implemented the World Bank COVID-19 monitoring surveys of households and formal firms in Vietnam including the following team members: – Poverty & Equity (report task leader): Judy Yang (Senior Economist) and Matthew Wai-Poi (Lead Economist), England Rhys Can (Consultant), Philomena Panagoulias (Consultant), and Cuong Nguyen (Consultant). – Finance, Competitiveness, and Innovation: Shawn W. Tan (Senior Economist), Trang Thu Tran (Senior Economist), and Ngoc Phan (Consultant). The report would not be complete without important contributions provided by a cross-sectoral World Bank team consisting of the following: – Agriculture: Hardwick Tchale (Senior Agriculture Economist) – Development Economics, Indicators and Data Services: Daniel G. Mahler (Economist) – Education: Nguyet Thi Anh Tran (ET Consultant) – Gender: Daniel Halim (Economist) – Governance: Maham Faisal Khan (Consultant) – Health: Christoph Lemiere (HD Practice Leader), Huong Lan Dao (Senior Health Specialist), and Anh Thuy Nguyen (Senior Operations Officer) – Macroeconomics, Trade, and Investment: Hoang The Nguyen (ET Consultant) – Social Protection and Jobs: Nga Nguyet Nguyen (Senior Economist), Nga Thi Nguyen (Senior Economist), Harry Moroz (Economist), and Bao Ha Pham (Consultant) Additional comments and review were provided by: – Dr. Thang Nguyen (Director, The Centre for Analysis and Forecast, Vietnam Academy of Social Sciences); – Professor Edmund Malesky (Political Science Department, Duke University); – Sailesh Tiwari (Senior Economist, Poverty & Equity, the World Bank); and – Jacques Morisset (Lead Economist, Macroeconomics, Trade, and Investment, the World Bank). Report guidance was provided by: – Hassan Zaman (Regional Director, East Asia and Pacific, EFI); – Carolyn Turk (Country Director, Vietnam); – Rinku Murgai (Practice Manager, East Asia and Pacific, Poverty & Equity Global Practice); and – Zafer Mustafaoglu (Practice Manager, East Asia and Pacific, Finance, Competitiveness, and Innovation Global Practice). The report was edited by Honora Mara. The report design was produced by Saengkeo Touttavong. Data collection of the World Bank COVID-19 household and firm monitoring surveys is partially funded by grants from the Australia–World Bank Strategic Partnership for Vietnam and the World Bank Trust Fund for Statistical Capacity Building (TFSCB). Data collection was conducted by the Mekong Development Research Institute and the Vietnam General Statistics Office. Information on the World Bank COVID-19 household and firm monitoring surveys in Vietnam can be found here: https://www.worldbank.org/en/country/vietnam/brief/monitoring-households-and-firms-in-vietnam-during-covid-19. Cover image: Aerial photography of rooftops and architecture Ho Chi Minh City Vietnam © Paul/Adobe Stock TABLE OF CONTENTS iii Table of Contents Overview................................................................................................................................................................. x Notes ...............................................................................................................................................................................................xiv References......................................................................................................................................................................................xiv Chapter 1. Vietnam’s early COVID-19 context...................................................................................................1 References........................................................................................................................................................................................ 8 Chapter 2. Impacts on households and businesses: a year deferred.............................................................9 A year of adverse shocks............................................................................................................................................................. 10 What are the disruptive COVID-19 impact channels?.......................................................................................................... 15 What were the total impacts on household incomes?..........................................................................................................33 Notes................................................................................................................................................................................................39 References......................................................................................................................................................................................39 Chapter 3. Coping: A reliance on self-insurance and personal networks.................................................. 40 Coping strategies...........................................................................................................................................................................41 Household self-insuring and borrowing strategies................................................................................................................42 Business adjustment strategies................................................................................................................................................ 47 Notes................................................................................................................................................................................................54 References......................................................................................................................................................................................54 Chapter 4. Policies: a call to strengthen amid heightening risks.................................................................55 The health response: start and finish strong..........................................................................................................................56 The relief response: learning from experience........................................................................................................................ 67 Notes................................................................................................................................................................................................ 81 References...................................................................................................................................................................................... 81 Chapter 5. Impact on poverty in 2020: progress stalled but not reversed................................................82 A micro-macro simulation approach........................................................................................................................................83 Poverty Impacts............................................................................................................................................................................89 Notes................................................................................................................................................................................................92 Reference........................................................................................................................................................................................92 Chapter 6. Longer-term impacts: Will COVID-19 lead to widening inequality?........................................93 Unequal experiences during COVID-19.....................................................................................................................................94 Future plans are affected..........................................................................................................................................................103 Distribution-sensitive poverty projections—longer-term simulation.............................................................................106 Notes...............................................................................................................................................................................................112 References.....................................................................................................................................................................................112 iv A YEAR DEFERRED – EARLY EXPERIENCES AND LESSONS FROM COVID-19 IN VIETNAM Chapter 7. Policy Considerations.................................................................................................................... 114 Learn from implementation challenges early on during the COVID-19 pandemic...................................................... 115 Improve the design and implementation of household and firm support during the fourth wave............................116 Strengthen resilience and protection systems for the future........................................................................................... 118 Be observant of existing and widening monetary and nonmonetary gaps...................................................................120 Note.................................................................................................................................................................................................121 References.....................................................................................................................................................................................121 Appendices.........................................................................................................................................................122 Appendix A. Household demographic background.......................................................................................123 References.................................................................................................................................................................................... 125 Appendix B. Household Income Background.................................................................................................126 Measuring Gender Impacts From the World Bank COVID-19 household Appendix C.  monitoring surveys......................................................................................................................129 Reference......................................................................................................................................................................................130 Appendix D. Chapter 2 figures......................................................................................................................... 131 Appendix E. World Bank COVID-19 Household Monitoring Surveys..........................................................133 Sampling Procedure....................................................................................................................................................................133 Panel Sample................................................................................................................................................................................ 134 Weighting...................................................................................................................................................................................... 134 Questionnaires............................................................................................................................................................................. 134 Data Access.................................................................................................................................................................................. 134 Notes..............................................................................................................................................................................................135 Appendix F. World Bank COVID-19 Business Pulse Surveys.......................................................................136 Appendix G. Vietnam Labor Force Surveys.................................................................................................... 137 Appendix H. Chapter 3 figures........................................................................................................................138 Appendix I. Micro-Macro Simulation Technical Information......................................................................139 Data................................................................................................................................................................................................139 Macro-growth assumptions.....................................................................................................................................................139 Occupation choice.......................................................................................................................................................................139 Mincer regressions......................................................................................................................................................................140 Social assistance.........................................................................................................................................................................140 Estimating poverty.....................................................................................................................................................................140 References....................................................................................................................................................................................140 Appendix J. Distribution-sensitive poverty projections technical information....................................... 141 References.................................................................................................................................................................................... 142 TABLE OF CONTENTS v Figure Lists Figure 1.1 Vietnam’s poverty rates declined significantly over the last decade.............................................................. 2 Figure 1.2  Vietnam led the Southeast Asia region early on with the lowest numbers of COVID-19 ........................................................................................................................................................... 3 cases an deaths Figure 1.3 Only China and Vietnam are projected to resume strong growth in 2021..................................................... 4 Map 1.1 Vietnam’s fiscal response was not as multidimensional as responses of a number of other countries in the East Asia and Pacific region........................................................................................................ 5 Figure 1.4 Framework of the report............................................................................................................................................7 Figure 2.1 Concordance between World Bank COVID-19 household monitoring survey dates and Vietnam pandemic outbreaks................................................................................................................................. 11 Figure 2.2 Self-reporting of shocks is correlated to the timing of outbreaks and lockdowns in Vietnam............... 12 Figure 2.3 Channels of disruptive impacts to household earnings during COVID-19, Vietnam.................................. 16 Figure 2.4 Over time, fewer Vietnamese households are experiencing new cases of employment loss....................17 Figure 2.5 Transitions of economic activity in Vietnam, population aged 15 years and older................................... 18 Figure 2.6 The population of people aged 15 and older who were not working increased in 2020, Vietnam.......... 19 Figure 2.7 Share of unemployed in Q1 who remained unemployed in Q4, by year, Vietnam....................................... 19 Figure 2.8 Fewer Vietnamese households are experiencing labor income declines over time.....................................20 Figure 2.9 Large initial employment drop, with a small recovery in late 2020, Vietnam............................................ 21 Figure 2.10 Most of Vietnam’s employment changes happened in medium and large firms........................................ 21 Figure B2.2.1 Share of workers in Vietnam’s hotel and restaurant sector in multiple quarters, by year......................22 Figure B2.2.2  Transitions of Vietnamese hotel and restaurant workers from Q1 of 2020 into new sectors (Q2 or Q4).....................................................................................................................................................22 Figure B2.3.1 Among Vietnam’s wage workers, female main respondents reported worse outcomes during the pandemic.................................................................................................................................................23 Figure B2.3.2  Work participation of male and female respondents in COVID-19 monitoring survey, June 2020 vs. February 2020................................................................................................................................24 Figure 2.11 About 7 percent of Vietnamese households reported fewer adults working in March 2021 than in January 2020............................................................................................................................................... 27 Figure 2.12 Declines in income due to farming-related factors were more common among the poor and those in more rural regions of Vietnam................................................................................................................28 Figure 2.13 Farming operations and disruptions during COVID-19, Vietnam...................................................................29 Figure 2.14 Crop prices in Vietnam compared to the previous year...................................................................................30 Figure 2.15 Family business performance in Vietnam........................................................................................................... 31 Figure 2.16 Reduced family business income was more common than family business closures, Vietnam............. 31 Figure 2.17 Family business outcomes by male and female respondents engagement, Vietnam...............................32 Figure 2.18 Under a longer timeline, more Vietnamese households still have lower incomes.......................................34 Figure 2.19 Divergent recovery in an income index, Vietnam...............................................................................................36 Figure 2.20 Vietnamese households without any formal labor market income sources have a lower income index.................................................................................................................................................... 37 Figure 2.21 Changes in the household income index varied by region, Vietnam..............................................................38 vi A YEAR DEFERRED – EARLY EXPERIENCES AND LESSONS FROM COVID-19 IN VIETNAM Figure Lists Figure 3.1 Vietnamese households were more likely to use informal and self-coping strategies..............................42 Figure 3.2 Wealthier Vietnamese households that experienced a shock or income decline were more able to afford to reduce food and nonfood consumption.................................................................................43 Figure 3.3 Poor Vietnamese households are more likely to consume homemade goods.............................................44 Figure 3.4 Wealthier Vietnamese households are more able to rely on savings............................................................46 Figure 3.6 Indicators of financial access, Vietnam...............................................................................................................46 Figure 3.5 Vietnamese households are saving less than before........................................................................................46 Figure 3.7 Types of borrowing by Vietnamese households during COVID-19................................................................. 47 Figure 3.8 Different employment adjustments by firms in Vietnam................................................................................48 Figure 3.9 Part-time workers were the most likely to be laid off, Vietnam.....................................................................48 Figure 3.10 Firms in Vietnam are becoming less likely to lay off workers in response to drops in sales....................49 Figure 3.11 Small firms are more likely to opt for adjustments along intensive margins.............................................49 Figure 3.12 Vietnamese firms faced liquidity issues in June and October 2020, but the situation improved in January 2021.......................................................................................................................................50 Figure 3.13 External finance can double the time before firms experience cash flow shortages.................................50 Figure 3.14 Many Vietnamese firms have already fallen into arrears or expected to do so in the next six months......................................................................................................................................................... 51 Figure 3.15 Increasing shares of Vietnamese firms are restructuring their debt............................................................ 51 Figure 3.16 Many Vietnamese firms started or increased their use of digital platforms during the pandemic.......52 Figure 3.17 More Vietnamese firms are selling on e-commerce platforms and social networks.................................52 Figure 3.18 More Vietnamese firms are receiving and making orders on e-commerce platforms and social networks..........................................................................................................................................................52 Figure 3.19 Digital platforms increased e-commerce sales, but not overall sales..........................................................53 Figure 4.1 Vietnam led the Southeast Asia region early on with the lowest numbers of COVID-19 cases and deaths.......................................................................................................................................................56 Figure 4.2 Near unanimous approval of government response in Vietnam.................................................................... 57 Figure 4.3 Mask wearing in Vietnam eased after the first outbreak in April 2020.......................................................58 Figure 4.4 Oxford Stringency Index trends in Southeast Asia...........................................................................................59 Figure B4.1.1 Google Mobility Trends, Vietnam.......................................................................................................................... 60 Figure B4.1.2 Google Mobility, workplace visit trends .............................................................................................................. 61 Figure B4.1.3 Comparing Facebook Mobility data by province and case counts................................................................63 Figure 4.5 COVID-19 vaccination trends in Southeast Asia...............................................................................................64 Figure 4.6 Health workers, children, and senior citizens are most often chosen as vaccination priority groups among survey respondents in Vietnam...................................................................................65 Figure 4.7 Vietnam has one of the lowest testing rates in the region..............................................................................66 Figure 4.8 Incidence of Vietnamese households by policy target groups........................................................................69 Figure B4.3.1 Vietnam had the second-largest relative gap between household losses and support, East Asia and Pacific.................................................................................................................................................71 Figure B4.3.2 Vietnam spent much more on other forms of public spending than on income support...........................71 Figure 4.9 Perceptions of government response to COVID-19, Vietnam......................................................................... 73 Figure 4.10 About half of Vietnamese households view COVID-19 as a substantial threat to their finances........... 74 Figure 4.11 Poorer Vietnamese households are less likely to be optimistic during the pandemic............................... 74 Figure 4.12 Vietnamese firms’ access to government assistance has almost doubled since June 2020.................. 77 TABLE OF CONTENTS vii Figure Lists Figure 4.13 Implementation of Vietnam’s support measures has improved, but barriers to access remain............78 Figure 4.14 Gaps in Vietnam’s policy support widened, but targeting has not improved.............................................. 79 Figure 4.15 Policy considerations for recovery....................................................................................................................... 80 Figure 5.1 Illustration of model parameters to estimate welfare.....................................................................................84 Figure 5.2 Sector concentrations, by province......................................................................................................................85 Figure 5.3 Growth actuals in 2020 were much lower than pre-COVID-19 forecasts...................................................85 Figure 5.4 Distribution of Vietnamese households receiving benefits, by region and scenario..................................88 Figure 5.5 The characteristics of Vietnam’s new poor differ, by poverty line................................................................ 90 Figure 5.6 In a crisis scenario, the proportion of Vietnam’s poor in services is higher................................................. 91 Figure 6.1 Continuity of education varied across Vietnam’s regions and by household socioeconomic groups....95 Figure 6.2 An additional 2 million Vietnamese households began shopping online between February 2020 and January 2021.........................................................................................................................97 Figure 6.3 Facebook is the most popular digital business-to-consumer platform, Vietnam...................................... 97 Figure 6.4 Wealthier Vietnamese households are more likely to know someone who is engaged in the digital economy.........................................................................................................................................................98 Figure 6.5 Family businesses from wealthier households are more likely to have digital sales, Vietnam................99 Figure 6.6 Higher shares of large firms in Vietnam are using digital platforms............................................................99 Figure 6.7 Large firms in Vietnam are using digital platforms for more sophisticated business functions............99 Figure 6.8 Small Vietnamese businesses have been the slowest to recover from closures.......................................100 Figure 6.9 Negative effects on sales have lingered longest for small Vietnamese businesses.................................100 Figure 6.10 Ethnic minority and poor households in Vietnam are more likely to worry about food.......................... 101 Figure 6.11 Fewer Vietnamese households are eating less, but gaps remain across socioeconomic groups..........102 Figure 6.12 Distribution of household members who stopped work or reduced work hours to take on childcare.103 Figure 6.13 Vietnamese households changed plans because of income declines, by income quintile......................104 Figure 6.14 Poorer Vietnamese households were more likely to forgo investments into education..........................105 Figure 6.15 The pandemic disrupted the investment plans of most Vietnamese firms, especially agricultural businesses..........................................................................................................................................105 Figure 6.16 With improving business outlooks in January 2021, fewer Vietnamese firms expect to reduce investments................................................................................................................................................105 Figure 6.17 Business expectations of Vietnamese firms reached the lowest level in October 2020 but........................ have since recovered...............................................................................................................................................106 Figure 6.18 In Vietnam, business expectations for the next six months are more positive for firms with higher sales growth in the past month...............................................................................................................106 Figure 6.19 Inequality has been stable in Vietnam, but redistribution has not contributed to poverty reduction in recent periods... ................................................................................................................................108 Figure 6.20 Growth incidence curves, selected periods, Vietnam......................................................................................109 Figure 6.21 Distribution-sensitive poverty projections for Vietnam, 2018–23.............................................................. 110 Figure 6.22 Small changes in inequality can have large impacts on poverty in Vietnam, 2020................................ 110 Figure 6.23 Inequality impacts can accumulate over time, Vietnam, 2020–23............................................................. 111 Figure 7.1 Fiscal response, by type, selected countries......................................................................................................116 Figure A.1 Sixty percent of Vietnamese households have children................................................................................. 123 Figure A.2 Ethnic minorities comprise a small share of Vietnamese households........................................................ 124 Figure A.3 Population distribution by region........................................................................................................................ 124 viii A YEAR DEFERRED – EARLY EXPERIENCES AND LESSONS FROM COVID-19 IN VIETNAM Figure Lists Figure A.4 The maximum level of education in half of Vietnamese households is less than completed upper secondary...................................................................................................................................................... 124 Figure A.5 Fifty-six percent of households have a head that is 50 y/o or higher......................................................... 125 Figure A.6 Agriculture is still the most common economic activity among households............................................ 125 Figure B.1 The prevalence of income sources varies across households, Vietnam......................................................126 Figure B.2 Business and wage incomes are much higher than other income sources, Vietnam............................... 127 Figure B.3 A high share of Vietnamese households receives income from multiple source.......................................128 Figure B.4 Vietnamese households relying on only one income source..........................................................................128 Figure B.5 Primary income source in Vietnam, by decile...................................................................................................128 Figure D.1 Vietnamese households reporting lower income at the time of interview compared to last month....131 Figure D.2 Vietnamese households reporting lower income at the time of interview compared to last year....... 132 Figure G.1 Panel data structure of Vietnam Labor Force Survey.................................................................................... 137 Figure H.1 Vietnam has the second-lowest price level among economies in the East Asia and Pacific region.....138 Figure H.2 Most Vietnamese own their homes and have no large recurring expenses...............................................138 TABLE OF CONTENTS ix Table Lists Table 1.1 Most of Vietnam’s economic indicators dampened in 2020............................................................................4 Table 1.2 Vietnam used fewer fiscal responses characterized by speed and affordability than did other countries in the region...............................................................................................................................................6 Table 2.1 Correlates to Vietnamese households experiencing a negative shock........................................................12 Table B2.1.1 World Bank COVID-19 household monitoring surveys, Vietnam..................................................................14 Table 2.2 Employment impacts across personal networks, Vietnam............................................................................ 17 Table B2.3.1 Female vs. male work stoppage rates, Vietnam.............................................................................................. 25 Table 2.3 Employment impacts across personal networks, Vietnam........................................................................... 26 Table 2.4 Mediators of female-specific experience of significant drop in business turnover, Vietnam................ 33 Table 4.1 Vietnam’s household COVID-19 relief, planned vs. implementation............................................................ 69 Table B4.3.1 Spending on social assistance before and during the COVID-19 outbreak............................................... 70 Table 4.2 Social assistance in Vietnam during COVID-19................................................................................................72 Table 4.3 The highest share of recipients of COVID-19 benefits targeted to new applicants was located in the Northern and Coastal Central region of Vietnam...................................................................73 Table 5.1 Distribution of households by main economic sector of activity................................................................. 84 Table 5.2 Employment elasticity in Vietnam, 2020.......................................................................................................... 86 Table 5.3 Labor shares across scenarios, Vietnam........................................................................................................... 87 Table 5.4 Simulated cash transfer scenarios, Vietnam................................................................................................... 88 Table 5.5 Summary of poverty rates in Vietnam, 2018 (actual) and 2020 (simulated)........................................... 89 Table C.1 Household characteristics of female and male respondents in the World Bank Vietnam COVID-19 monitoring survey.............................................................................................................................. 129 Table C.2 Individual characteristics at baseline, Vietnam, 2018................................................................................. 130 Table E.1 Summary of five rounds of the World Bank Vietnam COVID-19 household monitoring surveys....... 133 Table E.2 The size of the panel sample across rounds of Vietnam COVID-19 monitoring survey........................ 135 Table F.1 Summary of three rounds of the World Bank Vietnam COVID-19 Business Pulse Surveys................. 136 Box Lists Box 2.1 The World Bank COVID-19 household monitoring surveys............................................................................14 Box 2.2 Workers in Vietnam’s hotels and restaurants...................................................................................................21 Box. 2.3 Employment impacts by gender.......................................................................................................................... 23 Box 4.1 Insights from mobility and movement data.....................................................................................................60 Box 4.2 National COVID-19 relief policies for workers and households in Vietnam................................................ 68 Box 4.3 COVID-19 relief packages to households, Vietnam vs. East Asia and Pacific region............................... 70 Box 7.1 Emergency household support during COVID-19 in the Philippines........................................................... 119 x A YEAR DEFERRED – EARLY EXPERIENCES AND LESSONS FROM COVID-19 IN VIETNAM A Year Deferred – Early Experiences and Lessons from COVID-19 in Vietnam Overview This report documents and explores the early economic impacts of COVID-19 (coronavirus) on households and businesses in Vietnam, leveraging unique information collected by the World Bank COVID-19 household and firm monitoring phone surveys collected from June 2020 to March 2021. Using new survey data, microsimulation techniques, and administrative data, this report looks in each chapter at (1) the impact of the crisis on households and businesses, (2) how they coped, (3) how the government responded, (4) how the trajectory to poverty was affected in 2020, and (5) potential longer-term consequences, particularly consequences related to increasing inequality. The period covered by the report marks the first phase of the pandemic in Vietnam, a period when COVID-19 was successfully controlled, and before the large outbreak in April 2021 caused by the Delta variant. Although COVID-19 cases in Vietnam were among the lowest in the world throughout 2020 and early 2021, households still experienced lower incomes, job loss, and hardships. Inequalities, differences in abilities to cope, vulnerabilities, and policy implementation challenges found during this early phase are cautionary signs and offer relevant lessons to consider as Vietnam faces a much more challenging phase of COVID-19 ahead. Overview  xi Chapter 1. The outbreak in April 2021 adds uncertainty to the Vietnam’s Early COVID-19 Context full extent of COVID-19’s impacts on households and firms. It is too early to conclude the full impact of COVID-19 erupted onto the world stage in early 2020, COVID-19 on households and businesses. In late April and Vietnam responded swiftly. The Vietnamese 2021, Vietnam entered its largest outbreak to date (the government was one of the first in the world to shut its fourth wave), with cases found in over 30 provinces within international borders in late March 2020, followed by a month. A month into the outbreak, the number of cases a nationwide lockdown for the full month of April. Its was as high as over the entire past year, linked to a more citizens were compliant and followed health protocols. transmissible Delta variant. Economic growth is at risk The government’s proactive and stringent actions because the latest outbreak is clustered particularly in resulted in some of the lowest numbers of COVID-19 industrial zones where many growth-driving foreign- cases in the world. owned manufacturing companies are located. The services sector will also suffer yet another depressed Vietnam’s early health response helped it perform summer and holiday season. Before the emergence of remarkably well economically compared to other the latest outbreak in April 2021, Vietnam was the only countries in 2020. The global contraction in 2020 was country in the region other than China projected to enjoy the largest since World War II, and over 100 million people a “V-shaped” economic recovery, with GDP projected to worldwide were estimated to fall into poverty. Vietnam was bounce back to pre-COVID-19 levels by the third quarter one of only about 10 economies in the world that maintained of 2021; but a rapid recovery is now less certain. In such positive economic growth in 2020. Poverty is projected to a highly evolving context, what was observed through the still be on a downward trajectory in 2020 but at a slightly World Bank monitoring surveys in 2020 and early 2021 slower pace than without the emergence of COVID-19. The tells only a partial story of COVID-19 in Vietnam. decline in Vietnam’s gross domestic product (GDP) at the height of the crisis in 2020 was the smallest of any country in the East Asia and Pacific region. Exports grew as some Chapter 2. manufacturing production relocated to Vietnam, and Impacts on Households and demand for some electronic goods increased as richer Businesses: A Year Deferred countries remained locked down and at home. Successful management of the crisis further attracted even more COVID-19 halted a period of rapid income and wage foreign direct investment throughout the year. growth for workers and households in Vietnam. Real household income per capita measured using the Despite the favorable economic outcomes in the Vietnam Household Living Standard Surveys (VHLSS) international context, growth decelerated, and in 2020 declined by 5 percent compared to 2019.1 In Vietnamese households and businesses reported comparison, real median household income was growing experiencing adverse shocks affecting employment, at an average of 7.2 percent per year from 2010 to 2018. incomes, and daily activities. GDP growth was 4 Before the full onset of COVID-19, wages were 9 percent percentage points lower in 2020 than in 2019. Even higher in the first quarter of 2020 than the same quarter sectors that managed to take advantage of the crisis grew the year before. However, for the remainder of 2020, at lower rates than in 2019. Exports had the smallest wages were lower than in corresponding quarters in decline in growth, still growing at 5.0 percent in 2020 the previous year. Wage growth in 2020 is a significant compared to 6.7 percent in 2019. Growth slowed more reversal from historical trends. In a span of six years dramatically in other sectors. GDP growth in industry and from 2012 to 2018, average real wages in industry/ services declined by nearly 5 percentage points each. construction and services had grown by 71 and 65 Private consumption growth nearly flattened from 7.4 percent respectively.2 percent in 2019 to 0.6 percent in 2020. Deposits data also show household deposits growing at a lower rate. xii A YEAR DEFERRED – EARLY EXPERIENCES AND LESSONS FROM COVID-19 IN VIETNAM These negative impacts were also echoed in the World Optimism about the impacts of COVID-19 improved Bank COVID-19 monitoring surveys that collected 3 over time, but households remained cautious. information on household and firm conditions. Those at the bottom of the welfare distribution were Given the slowdowns in economic growth and activity, more pessimistic than those at the top. These negative households and businesses were inevitably negatively perceptions coincide with poorer households more affected and experienced job losses, lower incomes, commonly reporting negative income shocks or their lower business turnover, and business closures. Adverse lack of capabilities to cope through shocks. At the same impacts from COVID-19 managed to affect households time, perception of financial risk was elevated over the across the entire welfare distribution. However, some entire survey period for households across the entire groups were still more likely to report lower incomes distribution. Understanding how households and firms after controlling for household economic activity and were affected by relatively milder shocks in 2020 and geographic locations. These groups include those without early 2021 is important for challenges ahead, because formal sources of income, women, and households with a year deferred may be prolonged into two amid children. Ethnic minorities were somewhat insulated heightening risks. from the economic shock because they are much more likely to be working in the agricultural sector that was less directly impacted by social distancing, but they were Chapter 3. more adversely affected in nonmonetary dimensions. Coping: A Reliance on Self-Insurance Not to be overlooked, crises can occur simultaneously, and Personal Networks and the Mekong Delta region was also afflicted by droughts in 2020. During COVID-19, households in Vietnam primarily relied on self-coping strategies through reducing Over a year after the onset of COVID-19, households consumption and support from personal networks. and firms are still on the path to recovery. The rate In contrast to those in developed countries, households of income loss lightened considerably over time, though and small businesses in many developing countries it did not disappear completely. According to responses tend to rely on more informal coping strategies. In June from the World Bank monitoring surveys, about 30 2020, over 50 percent of households reported reducing percent of households self-reported still having lower consumption, 16 percent borrowed from friends and incomes in March 2021 than a year before. Official family, and 5 percent borrowed from a financial institution. statistics reported that 9.1 million workers (12.8 percent Although, arguably, the COVID-19 shocks in 2020 did of all workers) had either lost their jobs or had reduced not necessitate large interventions, both household and wages in the first quarter of 2021, and average labor firm COVID-19-related relief programs faced challenges incomes were 2.3 percent lower compared to the previous with implementation (discussed in more detail in chapter year (Ha and Minh 2021). Firms started to recover, and 4). The lack of utilization of formal channels (financial almost all businesses were open by January 2021. institution and government support) by households to Although sales remained lower than in previous years, cope also reflects low levels of financial inclusion for the reductions in employment are smaller than at the start some vulnerable groups, a social protection system of the pandemic. But ongoing outbreaks will only further that requires modernization, and a highly informal labor delay a full recovery. force. Businesses had access to more formal coping mechanisms, such as through additional financing and adoption of remote work arrangements or new technologies to reach customers. However, small and informal businesses still tend to be more constrained. Many lacked adequate access to formal finance, and a large share of businesses had to downsize operations. Overview  xiii Chapter 4. The government passed policies in early 2020 to Policies: A Call to Strengthen amid provide relief to affected households, and it can Heightening Risks learn from the experience if future relief packages are implemented. Compared to other countries in the Arguably no country in the world proactively region, Vietnam spent less on COVID-19-related social managed challenges in 2020 better than Vietnam, assistance. The amounts of disbursements were also but heightening risks from COVID-19 in 2021 call lower than originally planned. Indeed, the impacts of for stronger actions. Reflecting on the impacts and COVID-19 early on were mild and perhaps relief was not disruptions felt by households and firms from a relatively as urgently needed as previously anticipated. However, mild year of shocks in 2020 and early 2021 is important there were clear implementation challenges that need as risks and uncertainty increase. Will the COVID-19 to be addressed in case another response is needed story for Vietnam be one of success from start to finish, or in the face of more lockdowns. The experience also one of early success but stalled progress as challenges foreshadows longer-term challenges to the effective and risks intensified? targeting and effectiveness of the social protection system if it is not modernized. Informal workers are out Vietnam took early action to contain COVID-19 and of the line of sight of government and were difficult to managed health risks remarkably well, but it is now register as new social assistance beneficiaries. Many behind on vaccinations amid rising cases. Risks informal workers could not provide proof or employer are increasing in 2021 as the fourth wave is the largest verification of their economic activity or show that it outbreak yet in Vietnam and more difficult to contain. had been affected by COVID-19. Other implementation Moreover, progress of vaccination rollouts in Vietnam is challenges included a lack of clarity from complex criteria the slowest in the Southeast Asia region. In May 2021, and procedures, lack of digital screening and verification only 0.02 percent of the population was fully vaccinated, tools, and under-resourced staff. far below averages in developing Southeast Asia region and worldwide. About half a billion people in the world Relief options for formal firms were different but were fully vaccinated in May 2021, or roughly 6 percent faced similar implementation challenges. Government of the world population. support focused mainly on providing payment extensions and reductions (in corporate income taxes, land rents, The government is accelerating in various strategies and trade union fees) and low-interest-rate loans to small to tackle the most recent outbreak. It has taken and medium enterprises. However, in June 2020, less measures to acquire vaccines faster and monitor data than 20 percent of surveyed firms reported benefiting in a more useful way, and has enacted strict policies from these support programs, increasing to 36 percent to minimize new cases. The government has set up a by January 2021. The two support policies from which fund to facilitate the purchase of vaccines for a target most firms benefited (corporate income tax reduction 70 percent of the population. Information from the and tax payment deferrals) are those that do not require government-run Blue Zone contact tracing and self- strong disbursement mechanisms. Most firms reported an reporting app will be more centralized to provide more initial lack of awareness of these programs in June, but useful data insights. By early June, the government has subsequently more firms reported issues with application spent 8 trillion Vietnamese dong (VND; US$347 million) difficulties and ineligibility for the programs. By January on COVID-19 prevention and policies. 2021, a substantial share of firms (22 percent) still considered it too difficult to apply for support programs. Consistent with this finding, 35 percent would like simplification of eligibility conditions in the future, and 22 percent asked for improved practicality (such as lowered requirements for collaterals for loans). xiv A YEAR DEFERRED – EARLY EXPERIENCES AND LESSONS FROM COVID-19 IN VIETNAM Under the latest outbreak, households and Chapter 6. businesses will be adversely affected again, which Longer-Term Impacts: will COVID-19 may necessitate another round of relief measures. Lead to Widening Inequality? There are a host of reasons why the latest wave is concerning and may have more impact. Aside from Even as most households adapted throughout the the high transmissibility of the new strains, Vietnam is pandemic, goals and ambitions may have been behind on vaccinations and does not have widespread deferred; and those with more means were able to routine and accessible testing. Data from 2020 and early adapt better. Among households negatively affected, the 2021 show that, even under mild economic slowdowns, poorest are more likely to defer education needs, and households and businesses were adversely affected. If are still the least likely to use or adopt digital services a larger economic slowdown occurs, what would be the and technologies. Some trends proliferated across scale of impact? regions, such as differences in education continuity during lockdowns. Other disparate outcomes during COVID-19 build on preexisting disparities in food, digital Chapter 5. access, health care use, and education. Impacts to Impact on Poverty in 2020: Progress nonmonetary dimensions were also unevenly felt across Slowed Down but did not Reverse certain population groups such as women respondents and ethnic minorities. Despite relatively good macroeconomic outcomes in a COVID-19 context, adverse impacts from the Consequently, existing disparities have widened and, pandemic still permeated into daily lives and slowed left unchecked, will likely lead to widening inequality the trajectory of poverty reduction. Household and slower growth in the long term. These examples incomes declined following almost a decade of 6–7 illustrate the potential widening of existing monetary percent annualized growth. Despite lower incomes in and nonmonetary gaps caused by COVID-19, even in a 2020 relative to 2019, household expenditures (the basis country that was able to manage extremely well compared of poverty measurement) were still 13 percent higher in to most others in the world. Moreover, these gaps have 2020 than in 2018.4 Poverty is not expected to increase, long-term consequences: lost education is unlikely to be but the progress of poverty reduction has been delayed. recovered, with consequences for lifetime wages; sold Poverty is estimated to be slightly higher in a COVID-19 assets cannot produce future incomes; and employment context than in the absence of it. At the lower-middle- 5 scarring is also associated with lower lifetime earnings. income poverty line ($3.20/day 2011PPP), the new poor6 Minimizing future disparities will require forward-looking is a small group and tends to be informal and in the policies and improving existing support systems. agriculture sectors. Taken from a broader perspective, this is a small setback compared to increasing poverty The impact from inequality on poverty reduction experienced in other countries suffering from more can be just as large or larger than historical growth serious impacts and disruptions. The welfare-improving impacts. Moving from a no-crisis to a crisis scenario impacts of the household relief packages in Vietnam were increases poverty estimates by 0.3 percentage point in also small because of the ultimately small-scale rollout. 2020 (from 5.4 percent to 5.7 percent). However, a 1 percent increase in the Gini index would increase poverty by a higher rate under both the no-crisis and the crisis scenarios (0.4 and 0.6 percentage point, respectively). Globally, it was found that a 1 percent decrease in the Gini index in every country would lower global poverty more than a 1-percentage-point increase in GDP per capita (Lakner et al. 2020). Simulations also show that rising monetary inequality would further delay poverty reduction. Overview  xv Chapter 7. differential experiences between different groups Policy Recommendations of households and firms illustrate their preexisting vulnerabilities and the different capabilities in coping There is an opportunity to learn from early between groups. Observing how households and firms experiences to improve policy responses not only for were affected, even if by mild shocks; how they adapted; the remainder of the COVID-19 (coronavirus) crisis who received assistance; and who could not cope well but also to better guard against future shocks. The offers information on existing gaps in access to services, experiences captured by the World Bank COVID-19 the importance of building resilience, and the need for monitoring surveys are an opportunity to understand better safety nets to guard against poverty traps and the weakest links and who are the most exposed business closures. There are lessons both for the short to shocks. Fortunately, before the fourth wave, the term—how to improve the household and firm response impacts from COVID-19 in Vietnam were mild relative for the much more severe fourth wave—and for the long to the rest of the world. Yet, experiences from the early term—how to improve the broader social safety net for waves of COVID-19 still highlighted existing inequities times of crisis and times of normalcy. and revealed policy implementation challenges. The Key dates in the COVID-19 timeline in Vietnam Period Major events 2020 January 23: First positive case confirmed in Vietnam February March 22: International borders closed except to experts, repatriates, diplomats, and key businesspersons. April 1: Nationwide lockdown for one month (first wave) May June 28: First domestic positive case detected since April July 28: Da Nang lockdown and second wave begins 31: First domestic death August September October November December 2021 January 28: Hai Duong outbreak and third wave begins February March 8: Vaccinations commenced April 30: Fourth wave begins May 15: First domestic death since September 2020 xvi A YEAR DEFERRED – EARLY EXPERIENCES AND LESSONS FROM COVID-19 IN VIETNAM Notes 1  Vietnam’s General Statistics Office reported a 2 percent decline in household income in nominal terms (https://e.vnexpress.net/news/business/data-speaks/binh-duong-overtakes-major-cities-tops-per-capita-income-4282618.html). 2  Data from Havers Analytics. 3  This report primarily uses information from the World Bank COVID-19 household monitoring survey, which completed five rounds from June 2020 to March 2021. Three rounds of the World Bank COVID-19 firm monitoring surveys of formally registered firms were collected over the same period, and data collection is still ongoing. 4  Household income is measured annually in the VHLSS. Household expenditure, the basis of poverty measurement, is measured every two years on the even years in the VHLSS. Official estimates of household expenditure in 2019 is not available. 5  Poverty simulations in chapter 5 utilize the 2018 VHLSS dataset. Actual poverty rates using the VHLSS 2020 data set from the General Statistics Office were not yet available at the release time of this report. 6  The new poor are those who are estimated to fall into poverty during COVID-19, but would not have in its absence. References Ha, Thi, and Anh Minh. 2021. “Citizens, Businesses Hurt as Rising Prices Raise Inflation Concerns.” VNExpress, May 19, 2021. https://e.vnexpress.net/news/business/economy/citizens-businesses-hurt-as-rising-prices-raise-inflation-concerns-4279567.html. Lakner, Christoph, Daniel Gerszon Mahler, Mario Negre, and Espen Beer Prydz. 2020. “How Much Does Reducing Inequality Matter for Global Poverty?” Global Poverty Monitoring Technical Note 13, World Bank, Washington, DC. A YEAR DEFERRED – EARLY EXPERIENCES AND LESSONS FROM COVID-19 IN VIETNAM 1 Chapter 1. VIETNAM’S EARLY COVID-19 CONTEXT COVID-19 erupted onto the world stage in early 2020, and Vietnam responded swiftly. The government’s proactive and stringent actions resulted in some of the lowest numbers of COVID-19 cases in the world at the outset. Vietnam’s early health response helped it perform remarkably well economically compared to other countries in 2020. The decline in Vietnam’s gross domestic product (GDP) at the height of the crisis in 2020 was the smallest of any country in the East Asia and Pacific region. Despite the favorable economic outcomes in the international context, growth decelerated, and Vietnamese households and businesses reported experiencing adverse shocks affecting employment, incomes, and daily activities. In late April 2021, Vietnam entered its largest outbreak to date (the fourth wave), with cases found in over 30 provinces within a month. The latest outbreak adds uncertainty to the full extent of COVID-19’s impacts on households and firms. In such a highly evolving context, what was observed through the World Bank monitoring surveys in 2020 and early 2021 tells only a partial story of COVID-19 in Vietnam. 2 A YEAR DEFERRED – EARLY EXPERIENCES AND LESSONS FROM COVID-19 IN VIETNAM Vietnam has been extremely successful in reducing Key health measures included closing international poverty over the last decade. According to the World borders, strict containment policies, and a strong Bank’s lower-middle-income country poverty line, poverty public health awareness campaign. International dropped from 16.8 percent to 6.6 percent from 2010 borders were closed in March 2020, and by early April to 2018 (figure 1.1). Perceptions match the dramatic 2020 the country had entered a nationwide lockdown. declines in poverty. Today in the developing East Asia Even after the national lockdown ended, local mobility and Pacific region, the Vietnamese are among the most restrictions were quickly imposed when new cases optimistic about their future. Data from 2018 Gallup Polls were identified, including lockdowns of residential show 81 percent of Vietnamese said their standards of buildings, road blockages, and sometimes isolation living were getting better, second only to China. of entire provinces. However, over time and with experience, the containment measures became more Figure 1.1 Vietnam’s poverty rates declined localized and thus had less economic impact. There significantly over the last decade was generally good compliance with these measures, and they were accompanied by a strong public health awareness campaign that focused on social distancing 20 18 16.8 and healthy practices, communicated through various Poverty headcount rate (%) 16 channels, including the news, popular songs, and direct 14 13 text messaging. The public health response is explored 12 11 further in chapter 4. 10 7.8 8 6.6 Vietnam’s early health response helped it perform 6 4 remarkably well economically in 2020. The global 4 2.7 2.6 1.8 1.8 contraction in 2020 was the largest since World War II, 2 and over 100 million people worldwide were estimated 0 to fall into poverty. Vietnam was 1 of only about 10 2010 2012 2014 2016 2018 economies in the world that maintained positive economic growth in 2020. Poverty is projected to still be on a International extreme poverty line ($1.90/day 2011 PPP) Lower-middle-income poverty line ($3.20/day 2011 PPP) downward trajectory in 2020 but at a slightly slower pace. The decline in Vietnam’s gross domestic product (GDP) Source: World Bank staff estimates using VHLSS. at the height of the crisis in 2020 was the smallest of Note: PPP = purchasing power parity. any country in the East Asia and Pacific region. Exports During the year 2020 and first quarter of 2021, grew as some business diverted to Vietnam, and demand arguably no country in the world proactively for some electronic goods increased as richer countries contained COVID-19 better than Vietnam. Although remained locked down at home. Successful management Vietnam did not pay sufficient attention to vaccination of the crisis further attracted even more foreign direct before April 2021, its initial response to contain investment throughout the year. COVID-19—during 2020 was exceptionally quick and tremendously successful. Over the course of the first year of the pandemic, Vietnam led the region with the fewest cases and deaths related to COVID-19; in figure 1.2, Vietnam is barely visible above the x-axis. As other countries were locked down, Vietnam remained open domestically. Chapter 1.  VIETNAM’S EARLY COVID-19 CONTEXT 3 Figure 1.2 Vietnam led the Southeast Asia region early on with the lowest numbers of COVID-19 cases and deaths 2021 January February March April May June July Total cases per million 30K 20K 10K 0K 6 New deaths per million Vietnam 4 2 0 IDN KHM LAO MMR MYS PHL THA VNM Source: Mathieu et al. 2021, August 5, 2021 update. Despite positive GDP growth in 2020, actual growth The latest outbreak adds uncertainty to the full extent rates were still much lower than in previous years. of COVID-19’s impacts on households and firms. It GDP growth was nearly 4 percentage points lower than is too early to conclude the full impact of COVID-19 on forecasts made before the onset of COVID-19. Growth households and businesses (see chapter 2). In late April rates in the manufacturing and services sectors declined 2021, Vietnam entered its largest outbreak to date (the the most in percentage point terms. The decline in tourists fourth wave), with cases found in over 30 provinces and flights was severe, and the services-oriented tourism within a month. A month into the outbreak, the number of sector was one the most affected sectors in 2020. An cases was as many as over the entire past year, linked active domestic tourism sector prevented a complete to exposure from the more transmissible Delta variant. fallout, but many accommodation and tourism businesses Economic growth is at risk because the latest outbreak still closed. Between the first and second quarters of is clustered particularly in industrial zones where many 2020, about 30 percent of hotel and restaurant workers growth-driving foreign-owned manufacturing companies left the sector, either losing work completely or moving are located. The services sector will also suffer yet another to other sectors for employment. Agriculture, by contrast, depressed summer and holiday season. Before the performed better than before COVID-19, growing at 2.7 emergence of the latest outbreak in April 2021, Vietnam percent and surpassing services, the growth of which fell was the only country other than China projected to enjoy to 2.2 percent (table 1.1). However, looking at cumulative a “V-shaped” economic recovery, with GDP projected to sectoral performance since 2018, services still outpaced bounce back to pre-COVID-19 levels by the third quarter of agriculture by 4.7 percentage points. 2021 (figure 1.3); but a rapid recovery is now less certain. In such a highly evolving context, what was observed through the World Bank monitoring surveys in 2020 and early 2021, described and summarized later in this report, tells only a partial story of COVID-19 in Vietnam. 4 A YEAR DEFERRED – EARLY EXPERIENCES AND LESSONS FROM COVID-19 IN VIETNAM Table 1.1 Most of Vietnam’s economic indicators dampened in 2020 Real growth rates (%) 2018 2019 2020 2021 Real GDP 7.2 7.1 3.1 6.6 Agriculture 3.8 2.0 2.7 2.0 Industry 8.9 8.9 4.0 8.4 Services 7.0 7.3 2.4 6.6 Private consumption (% growth) 7.3 7.4 0.6 5.6 Exports, Goods and services 14.3 6.7 5.0 7.3 Imports, Goods and services 12.8 8.3 3.3 6.5 Other indicators International tourist arrivals (million) 15.5 18.0 3.8 Change in the number of flights –23% (passenger & commercial) Source: World Bank Macro Poverty Outlook; statistica.com; VNExpress. Figure 1.3 Only China and Vietnam are projected to resume strong growth in 2021 Index 2019-Q4 = 100 Index 2019-Q4 = 100 Index 2019-Q4 = 100 120 120 120 110 110 110 100 100 100 90 90 90 80 80 80 2019-Q4 2020-Q1 2020-Q2 2020-Q3 2020-Q4 2021-Q1 2021-Q2 2021-Q3 2021-Q4 2022-Q1 2022-Q2 2022-Q3 2022-Q4 2019-Q4 2020-Q1 2020-Q2 2020-Q3 2020-Q4 2021-Q1 2021-Q2 2021-Q3 2021-Q4 2022-Q1 2022-Q2 2022-Q3 2022-Q4 2019-Q4 2020-Q1 2020-Q2 2020-Q3 2020-Q4 2021-Q1 2021-Q2 2021-Q3 2021-Q4 2022-Q1 2022-Q2 2022-Q3 2022-Q4 China Vietnam Indonesia Malaysia Thailand Philippines Source: World Bank 2021a, March 2021 version. Vietnam’s choice of fiscal response differed markedly When income support for firms and households was from that of other countries in the region and did less considered, the response was narrower and smaller to mitigate income losses. Vietnam relied much more than responses by other countries in the region. The heavily on public works, accelerated spending, and public World Bank’s global database on fiscal responses to investment than any other country in the region, spending COVID-19 categorizes responses into seven categories twice as much on these responses than on direct income (see note to map 1.1). Vietnam deployed five such support to households and firms. China spent about the categories, fewer than the six or seven in many other same on the two categories of responses and all other countries in the region. An emergency response for both countries in the region spent much more on direct income firms and households was rolled out early on during the support (see chapter 4). As a result, Vietnam has the crisis, but was short in duration and limited in scope. second-largest relative gap between household income The national level household COVID-19 relief rollout losses and support received, after the Philippines where lasted for three months and was smaller than originally greater support was received but income losses were the planned due to implementation issues. Support for firms highest in the region. was primarily in the form of tax and debt deferrals, but Chapter 1.  VIETNAM’S EARLY COVID-19 CONTEXT 5 Map 1.1 Vietnam’s fiscal response was not as multidimensional as responses of a number of other countries in the East Asia and Pacific region 1 7 Source: Lacey, Massad, and Utz 2021. Note: Seven categories are (1) revenue measures to protect businesses; (2) revenue measures to protect individuals/boost consumption and demand; (3) revenue measures to promote availability of medical items; (4) direct support to businesses; (5) expenditure measures for individuals; (6) health expenditure measures; and (7) preferential loans to firms and households. these programs also faced implementation challenges primarily informal workers. However, difficulties in and benefited smaller and informal firms less. Table 1.2 assessing eligibility limited total expansion. Moreover, shows the characteristics of different fiscal responses for the benefits were low and short in duration. Chapter developing countries in East Asia as well as some of their 4 discusses Vietnam’s household and firm fiscal characteristics. Of note is that Vietnam’s response was support in more detail and the various implementation faster but less able to be targeted to particular populations issues, despite their relative noncomplexity; chapter 5 than the regional average, and was more focused on quantifies the limited nature of their mitigating effect on affordability and predictable cost control. Chapter 4 increases in poverty. discusses Vietnam’s household and firm fiscal support in more detail and the and various implementation issues, Support to firms also suffered from implementation despite their relative non-complexity. issues and tended to favor larger, more formal firms. Policies were primarily in the form of tax deferments and Support was boosted to existing social protection credits, and were available for a longer period of time. beneficiaries and expanded to cover additional Lack of awareness and other implementation issues informal workers, but relief benefits were small and existed, but the continuous availability of assistance to implementation issues limited their expansion. All firms over time has meant increasing coverage; more beneficiaries who were already enrolled in an income than one-third of firms had taken advantage of some support scheme received a top-up in addition to their support by January 2021. However, large firms are much standard benefits; the boost was smoothly implemented more likely to receive support than small and medium through existing distribution channels, although payments enterprises. The heavy reliance on tax reductions and were largely still cash-based, a potential issue during a deferrals favored formal (and larger) firms (see chapter pandemic. The government also identified new target 4 for a more detailed examination). groups that were adversely affected by COVID-19, 6 A YEAR DEFERRED – EARLY EXPERIENCES AND LESSONS FROM COVID-19 IN VIETNAM Table 1.2 Vietnam used fewer fiscal responses characterized by speed and affordability than did other countries in the region Count Target Speed Abuse Afford Cost Reverse Scale Admin China 23 0.7 0.7 0.3 0.2 0.3 0.6 0.3 0.2 Indonesia 25 0.5 0.8 0.4 0.1 0.5 0.6 0.6 0.4 Cambodia 18 0.7 0.9 0.3 0.2 0.6 0.5 0.8 0.2 Lao PDR 0 Myanmar 11 0.7 0.9 0.6 0.4 0.6 0.9 0.9 0.7 Mongolia 9 0.8 0.9 0.4 0.2 0.3 0.8 0.8 0.0 Malaysia 26 0.7 1.0 0.7 0.3 0.6 0.7 0.8 0.3 Philippines 21 0.9 1.0 0.7 0.1 0.5 0.9 0.8 0.2 Thailand 23 0.2 0.7 0.2 0.1 0.4 0.5 0.7 0.3 Timor-Leste 8 0.1 0.5 0.1 -0.1 0.5 0.6 0.5 0.8 Vietnam 10 0.6 0.9 0.5 0.4 0.8 0.8 0.8 0.7 Average 16 0.6 0.8 0.4 0.2 0.5 0.7 0.7 0.4 Source: Lacey, Massad, and Utz 2021. Note: Policy dimensions were scored on a scale from 0 (does not meet the criterion) or 1 (meets the criterion). The eight dimensions are (1) targetability—the extent to which the instrument allows to directly target specific business or population groups or activities; (2) speed—the time elapsed between the adoption of the instrument and the desired impact; (3) abuse resistance—the ease with which abuse by eligible beneficiaries and other parties involved with the measure can be controlled; (4) affordability—the extent to which the use of the instrument affects fiscal stability (for example, instruments that provide support in the form of credits or through the deferral of payments will have lower cost implications than instruments in the form of outright grants and expenditure); (5) predictability and control of cost—the extent to which upper limits for the cost of a program can be established and the actual cost can be reasonably well predicted; (6) scalability—the extent to which the instrument can be expanded or replicated for additional groups of beneficiaries in accordance with needs; (7) reversibility— the ease with which the response can be withdrawn, without causing economic and behavioral distortions; (8) administrative ease—the extent to which the instrument can be implemented within existing administrative capabilities. The score for each country is the unweighted average over all fiscal responses, regardless of program size. The rest of this report examines the impacts on and fiscal response to support both households and households and firms through different channels, firms. Chapter 5 brings together the earlier sections to and discusses policy responses and the potential ask what the overall impact on household poverty is longer-term impacts on inequality (figure 1.4). The likely to have been. Chapter 6 is more forward looking next chapter asks what shocks households and firms and asks whether disparities in impact, coping, and faced and how they were affected through different response are likely to have longer-term consequences channels. Chapter 3 asks what coping strategies for inequality in Vietnam. Finally, chapter 7 summarizes households adopted in the face of these shocks and policy recommendations. impacts, and chapter 4 examines both the public health Chapter 1.  VIETNAM’S EARLY COVID-19 CONTEXT 7 Figure 1.4 Framework of the report What shocks did households and firms face? Through what channels did those shocks affect households and firms? Ch pt r 2. What was the total impact on incomes? What was the range of coping strategies used by households? Ch pt r 3. What was the range of coping strategies used by firms? What was the initial public health response? How has vaccination progressed? Ch pt r 4. What fiscal support was there for households and firms? How effective was it? What was the estimated impact on household poverty in 2020? Ch pt r 5. Were different subgroups affected differently? How was future planning affected? Ch pt r 6. What are the potential long-term consequences for inequality of these differences? Policy recommendations Ch pt r 7. 8 A YEAR DEFERRED – EARLY EXPERIENCES AND LESSONS FROM COVID-19 IN VIETNAM References Lacey, Eric, Joseph Massad, and Robert Utz. 2021. “A Review of Fiscal Policy Responses to COVID-19 (February).” World Bank, Washington, DC. Mathieu, E., H. Ritchie, E. Ortiz-Ospina, M. Roser, J. Hasell, C. Appel, C. Giattino, and L. Rodés-Guirao. 2021. “A Global Database of COVID-19 Vaccinations.” Nature Human Behavior 5: 947–53. August 5, 2021, update. World Bank. 2021a. Uneven Recovery: World Bank East Asia and Pacific Economic Update (April). Washington, DC: World Bank. A YEAR DEFERRED – EARLY EXPERIENCES AND LESSONS FROM COVID-19 IN VIETNAM 9 Chapter 2. IMPACTS ON HOUSE- HOLDS AND BUSINESSES: A YEAR DEFERRED The COVID-19 (coronavirus) pandemic halted a period of rapid household income and wage growth in Vietnam as real household incomes and wages declined in 2020. Results from the World Bank COVID-19 monitoring surveys conducted between June 2020 and March 2021 echo the presence of adverse impacts. By March 2021, about 30 percent of households still self-reported that household incomes were lower than in March 2020. Despite a trend of steady recovery since the first lockdown, firm sales in January 2021 are still about 16 percent lower than pre-pandemic levels. In a rapidly changing context, impacts observed over the monitoring period are only a partial story of the household and business experience during COVID-19. In late April 2021, the largest outbreak to date broke through (the fourth wave). Understanding how households and firms were affected by relatively mild shocks in 2020 and early 2021 is important for challenges ahead, because a year deferred may be prolonged into two. 10 A YEAR DEFERRED – EARLY EXPERIENCES AND LESSONS FROM COVID-19 IN VIETNAM A YEAR OF ADVERSE SHOCKS Across the world, countries experienced disruptive Over the course of 2020 and early 2021, the share of impacts from COVID-19 that ranged from short households that reported experiencing new negative lockdowns to more dire battles of survival. shocks subsided dramatically after the first wave COVID-19 adversely affected all aspects of life including (figure 2.2).8 Almost 70 percent of households reported employment, income security, mortality, health, service experiencing a negative shock9 between February and delivery, food security, learning, and general well-being. June 2020, which covers the duration of nationwide Vietnam fared better than most countries throughout lockdowns in April 2020. Low responses to experiencing the world both economically and health-wise. However, adverse shocks in round 2 align with a period with no households were still adversely affected in 2020, a year local transmissions in Vietnam and when activities were deferred for some. There are risks that a year deferred relatively normal. Across the last three rounds of the will stretch closer to two. In late April 2021, Vietnam surveys, the share of households reporting negative entered its largest outbreak yet, a high-risk evolving shocks was much lower at less than a third, but the trend situation amid low vaccination rates. did not improve. During the last three survey rounds, the country was frequently on alert related to COVID-19 The World Bank COVID-19 monitoring surveys of outbreaks and containment. households were collected from June 2020 to March 2021, amid unpredictable episodes of outbreaks The crisis can affect households across the entire (see box 2.1 and appendix E for additional survey welfare distribution through a variety of channels information).7 Survey rounds asking about experiences in different ways. Wealthier households more likely during outbreak waves naturally led to more adverse experienced losses from family businesses, and poorer responses. In rounds 1, 3, and 5, respondents reported households experienced losses from farming activities. on conditions over a period that included an outbreak However, for poorer households, shocks can be poverty (figure 2.1). Rounds 2 and 4 did not reference conditions traps and thus more consequential to household welfare. during an outbreak. However, responses to survey round In three out of five survey rounds, households in the 4 referenced a period very close to the end of the Da top welfare quintile were less likely than the poorest to Nang wave. The Da Nang wave was prolonged and experience negative shocks (table 2.1). The bottom 20 marked the country’s first domestic death. Sporadic percent reported significantly higher negative shocks than cases continued to occur throughout December 2020 and the rest of households in two out of five rounds. may have affected perceptions and responses. Alert was still heightened in the end of 2020, even though domestic Other household demographics correlate to the transmission was low. The concordance between survey reporting of experiencing negative shocks. For dates and outbreaks in Vietnam are especially important example, households with children were more likely to to highlight because Vietnam went in and out of outbreaks report experiencing shocks in rounds 1 and 5, coinciding that caused time-specific shocks. with occurrences of school closures. There is also a significant gender component across most rounds coinciding with outbreaks (all rounds except round 2), in which male respondents are less likely than female respondents to report that the household experienced a negative shock. These gender differences persist after controlling for a range of observable household characteristics, and are likely related to women’s disproportionate burden of home care responsibilities. Chapter 2.  IMPACTS ON HOUSEHOLDS AND BUSINESSES: A YEAR DEFERRED 11 Household economic activities are related to the Reporting of negative shocks aligns with the timing likelihood of reporting negative shocks. All economic and location of outbreak epicenters. In round 1, there activities reported negative shocks in round 1. Across was no strong differences in the regional dispersion rounds, agriculture households were more likely to report of households experiencing negative shocks because shocks than nonagriculture households only in round 1, round 1 coincided with the nationwide lockdown in April reflecting the impacts of droughts that severely affected 2020 (see survey and outbreak concordance in figure farming in some regions. Family businesses reported 2.1). Households in the North and Central Coast region experiencing shocks throughout the survey cycle. were more likely to report negative shocks in round 3 Lockdowns and a general depressed demand in 2020 during the Da Nang outbreak, but effects were persistent, directly affected businesses. and households in this region were still more likely to report negative events in round 4, conducted several months later. By round 5, all other regions were less likely to report negative events relative to the reference region, the Red River Delta, where the center of the third outbreak wave—Hai Duong—was located. Figure 2.1 Concordance between World Bank COVID-19 household monitoring survey dates and Vietnam pandemic outbreaks Round 1 Round 2 Round 3 Round 4 Round 5 Survey Fieldwork reference period period 150 Wave 1 Wave 2 Wave 3 Wave 4 Domestic cases National Da Nang Hai Duong 100 lockdown 50 0 150 Imported cases 100 50 0 Feb 1,20 Apr 1,20 Jun 1,20 Aug 1,20 Oct 1,20 Dec 1,20 Feb 1,21 Apr 1,21 Jun 1,21 Source: World Bank Vietnam COVID-19 household monitoring surveys (rounds 1–5). Note: Reference period shown is for the “previous month.” Survey reference periods vary depending on the specific question. The fieldwork period for round 1 was the longest since the baseline sample had to be established. The baseline sample was also the largest to anticipate later attrition because subsequent rounds were mostly call-backs. Fieldwork for round 3 was also longer because an expansion sample was conducted in provinces affected by wave 2 of the pandemic. 12 A YEAR DEFERRED – EARLY EXPERIENCES AND LESSONS FROM COVID-19 IN VIETNAM Figure 2.2 Self-reporting of shocks is correlated to the timing of outbreaks and lockdowns in Vietnam 80 70 Share of households (%) 60 50 40 30 20 10 0 Feb - Jun 2020 Jun - Jul 2020 Jul - Aug 2020 December 2020 February 2021 Round 1 Round 2 Round 3 Round 4 Round 5 Source: World Bank Vietnam COVID-19 household monitoring surveys (rounds 1–5). Note: Dates shown are the survey reference period for each round. The reference period is typically the full month before the date of interview. The exception is round 1 for which the reference period is longer (from February to June 2020). The wording in round 1 was also slightly different, and asked if respondents experienced “income decline,” rather than a “negative shock.” In rounds in which field work spanned two months, the reference period also varied by date of interview. Table 2.1 Correlates to Vietnamese households experiencing a negative shock (1) (2) (3) (4) (5) (6) (7) (8) (9) (10) R1 R1 R2 R2 R3 R3 R4 R4 R5 R5 Household characteristics Bottom 20 0.04 0.07 0.19** 0.15* 0.02 (0.04) (0.07) (0.06) (0.06) (0.06) Quintile 2 0.12+ -0.13 0.06 -0.11 -0.04 (0.06) (0.09) (0.08) (0.09) (0.09) Quintile 3 0.09 -0.02 -0.12 -0.15 -0.01 (0.07) (0.11) (0.09) (0.10) (0.10) Quintile 4 0.09 -0.18 -0.21* -0.26* -0.09 (0.07) (0.11) (0.09) (0.10) (0.10) Quintile 5 -0.14* -0.26* -0.15 -0.23* -0.05 (0.07) (0.12) (0.10) (0.11) (0.11) Kinh majority 0.21** 0.19** -0.04 -0.02 0.05 0.04 0.22* 0.24* 0.15+ 0.16+ (0.07) (0.07) (0.12) (0.12) (0.08) (0.08) (0.09) (0.09) (0.09) (0.09) Chapter 2.  IMPACTS ON HOUSEHOLDS AND BUSINESSES: A YEAR DEFERRED 13 Table 2.1 Continued. (1) (2) (3) (4) (5) (6) (7) (8) (9) (10) R1 R1 R2 R2 R3 R3 R4 R4 R5 R5 HH w/child 0.31** 0.29** 0.08 0.06 0.08 0.08 0.11 0.11 0.12+ 0.12+ (0.04) (0.04) (0.08) (0.07) (0.06) (0.06) (0.07) (0.07) (0.07) (0.07) Male respondent -0.12** -0.12** -0.06 -0.06 -0.19** -0.19** -0.17** -0.17** -0.19** -0.19** (0.04) (0.04) (0.07) (0.07) (0.06) (0.06) (0.06) (0.06) (0.07) (0.06) Economic activity Wage 0.30** 0.29** -0.02 -0.01 0.01 0.01 0.02 0.02 0.05 0.05 (0.05) (0.05) (0.08) (0.08) (0.06) (0.07) (0.07) (0.07) (0.07) (0.07) Agriculture 0.13* 0.11* -0.04 -0.05 -0.09 -0.09 0.03 0.03 -0.20* -0.21* (0.05) (0.05) (0.08) (0.08) (0.07) (0.07) (0.09) (0.09) (0.08) (0.08) Family business 0.77** 0.78** 0.19* 0.20* 0.12+ 0.11 0.17* 0.18* 0.20** 0.20** (0.06) (0.06) (0.08) (0.08) (0.07) (0.07) (0.08) (0.08) (0.07) (0.07) Geography Urban -0.20** -0.18** -0.02 0.00 0.07 0.07 -0.10 -0.09 -0.22** -0.22** (0.05) (0.05) (0.08) (0.08) (0.07) (0.07) (0.08) (0.08) (0.08) (0.08) Midlands and North -0.07 -0.07 0.03 0.01 -0.03 -0.03 0.11 0.10 -0.01 -0.01 Mountains (0.07) (0.07) (0.12) (0.12) (0.09) (0.09) (0.10) (0.10) (0.10) (0.10) North and Central 0.00 -0.01 0.20+ 0.18+ 0.25** 0.25** 0.22* 0.21* -0.15+ -0.15+ Coast (0.06) (0.06) (0.10) (0.10) (0.08) (0.08) (0.09) (0.09) (0.09) (0.09) Central Highlands -0.13 -0.13 -0.04 -0.06 0.14 0.14 -0.05 -0.06 -0.16 -0.16 (0.08) (0.08) (0.14) (0.14) (0.11) (0.11) (0.12) (0.12) (0.12) (0.12) Southeast 0.10 0.11 0.18 0.18 0.07 0.07 0.08 0.08 -0.15 -0.14 (0.08) (0.08) (0.14) (0.14) (0.11) (0.11) (0.13) (0.13) (0.12) (0.12) Mekong Delta -0.10+ -0.12+ 0.17 0.16 0.11 0.11 0.04 0.04 -0.17+ -0.17+ (0.06) (0.06) (0.11) (0.11) (0.08) (0.08) (0.09) (0.09) (0.10) (0.10) Constant 0.00 0.03 -1.22** -1.08** -0.74** -0.57** -0.93** -0.73** -0.49** -0.45** (0.10) (0.10) (0.18) (0.17) (0.13) (0.13) (0.16) (0.16) (0.16) (0.15) Observations 6,148 6,148 3,932 3,932 4,559 4,559 3,945 3,945 3,922 3,922 Source: World Bank Vietnam COVID-19 household monitoring surveys (rounds 1–5). Note: Household (HH) quintiles are based on the welfare distribution in 2018. Standard errors in parentheses, *** p<0.01, ** p<0.05, + p<0.1, errors clustered by region. 14 A YEAR DEFERRED – EARLY EXPERIENCES AND LESSONS FROM COVID-19 IN VIETNAM Box 2.1 The World Bank COVID-19 household monitoring surveys Five rounds of the World Bank COVID-19 household monitoring surveys were conducted from June 2020 to March 2021 in Vietnam. The surveys covered a range of topics from behaviors to health, education, employment, coping, income changes, perceptions, food insecurity, and vaccines. Some questions were asked in all rounds, others were not, and some were added or removed as the context demanded. The majority of questions pertain to the household condition, such as if the household was affected by school closures, or trends in total household incomes. Other questions reflected the views and conditions of the main respondent, such as aspects of that person’s wage employment, and his or her opinions on vaccines and government policies. Surveys were collected at varying intervals that influence trends and comparisons across rounds (table B2.1.1). Round 1 had the longest fieldwork period because a baseline sample had to be established, and because a larger sample was contacted for the baseline to anticipate attrition in follow-ups. Some questions also had longer reference periods because it was the first round. For some questions in round 1, respondents were asked about experiences since the emergence of the pandemic (February 2020) to the time of interview. In subsequent rounds, questions usually asked about the current situation only at time of interview or over the last month. Round 2 is the only round in which the reference period does not cover a period with local transmission. Table B2.1.1 World Bank COVID-19 household monitoring surveys, Vietnam Round Field work dates Special notes 1 June 5–July 8, 2020 Round 1 was planned to be a larger sample than the subsequent rounds. The reference period for some questions in Round 1 included Wave 1 and as early as February 2020. 2 July 27–Aug. 12, 2020 This is the only round where there were no domestic cases recorded during the survey reference period. 3 Sept. 9–Oct. 1, 2020 This round covered conditions during the 2d wave. The sample size in this round is larger since there was an expansion cover more households in the 2nd wave outbreak areas. 4 January 2–15, 2021 Conditions covered by Round 4 are near the end of the 2nd wave. 5 March 13–31, 2021 The final round asked about conditions during the period including the 3rd outbreak as well as Tet. Source: World Bank The fourth and largest outbreak to date in Vietnam emerged at the end of April 2021 but is outside the period of analysis. In a span of one month from April to May 2021, Vietnam recorded as many cases as it had in the entire previous year. In a rapidly evolving context, what was observed through the World Bank monitoring surveys in 2020 and early 2021 is only a partial story of COVID-19 in Vietnam. However, lessons can still be learned to better handle the emerging and more challenging risks ahead. Additional information for the World Bank COVID-19 household monitoring surveys, World Bank Business Pulse Surveys, and the Vietnam Labor Force Surveys are provided in appendixes E–G. Chapter 2.  IMPACTS ON HOUSEHOLDS AND BUSINESSES: A YEAR DEFERRED 15 WHAT ARE THE DISRUPTIVE COVID-19 IMPACT CHANNELS? In the case of Vietnam, disruptive effects from in 2020. Prices for rice remained competitive, whereas COVID-19 were felt primarily through the labor some other crops saw prices decline as global supply market. Vietnam was extremely successful in the chains limited exports. However, in 2021, prices are management of COVID-19 health risks, and the disruptive showing signs of higher inflation as global demand begins impacts of COVID-19 to households were primarily increasing (Ha and Minh 2021). through declines in labor market earnings stemming from declining aggregate demand, supply disruptions, and the Public services largely operated normally. Disruptions associated decrease in employment and/or the returns to to public service delivery, particularly health and productive activities. Impacts were felt first and foremost education services, can negatively affect both physical by those employed in vulnerable sectors, such as tourism and cognitive development, which may also affect and traditional services (for example, transportation and mortality, morbidity, and a country’s future productivity. retail sales). Those employed in the informal sector or Throughout the pandemic, the health system was not engaged in small-scale family business activities also stressed and access to health was not affected, nor was proved more vulnerable. The World Bank monitoring public safety ever at risk. However, with the emergence surveys capture mostly household-level impact channels of the fourth wave, a much wider spread, and some except for information on individual employment changes clusters emerging from within hospitals, hospital capacity of the main respondent. Information on employment may begin to be strained and access to routine services trends during COVID-19 is complemented by information may become more challenging. School closures also from the Vietnam Labor Force Survey (LFS).10 occurred with inconsistent distance learning solutions. The nonmonetary impacts from COVID-19 will be Transfers did not have a large impact in off- discussed in chapter 6. setting changes to labor income. Indications from macroeconomic reporting show that international In the remainder of this chapter, the impacts on remittances increased by 3 percent in 2020. However, households through the earnings channel are described, from a welfare perspective, remittances are most likely following the categories shown in figure 2.3. In addition, received by wealthier households, thus increases in trends in total household income throughout the survey remittances are unlikely to have off-set income loses period are discussed, with a highlight on differential for poorer households (see appendix B on household impacts across groups. Appendixes A and B provide income sources). In aggregate, remittances are also a further background information on the demographics and small share of total household income. The COVID-19 income sources of Vietnamese households. social assistance cash support was minimal and did not have large welfare implications, as will be discussed in Employment chapters 3 and 4. The share of households reporting job losses within Price inflation did not materialize as an early risk, but the previous month(s) was at its highest point in the that may be changing. Disruptions in the functioning first two quarters (Q1 and Q2) of 2020, and reduced of markets due to decline in international trade, foreign substantially in subsequent quarters (figure 2.4).11 In direct investment, and domestic economic activity the first round of the World Bank COVID-19 surveys with could lead to price increases and/or rationing of basic fieldwork conducted from late June to mid-July, about consumption goods, including food (and production 30 percent of households reported losing employment inputs). Although this disruptive channel was relevant in between February and June 2020. In subsequent many other countries, it was less relevant in Vietnam rounds, the reporting of job loss reduced substantially.12 16 A YEAR DEFERRED – EARLY EXPERIENCES AND LESSONS FROM COVID-19 IN VIETNAM Figure 2.3 Channels of disruptive impacts to household earnings during COVID-19, Vietnam Earnings Non-market Income Market income Employment Wage Job loss or Social assistance Remittances down-grading Family business Farming Source: World Bank Note: Light orange indicates some adverse impacts were felt by households. Nonmarket income sources, highlighted in gray, are not discussed in detail in this chapter. The COVID-19 social assistance fiscal policy will be discussed in chapter 3. Information on remittance income was not captured in detail in the World Bank COVID-19 monitoring surveys. Households in the lower end of the welfare distribution minorities, who are more likely to be in agricultural self- were more likely to experience job loss during the employment. These differences reflect the dispersion of lockdowns in the first half of 2020. In regression analysis, hard-hit sectors due to lower mobility, tourists, and general households in the top quintile were significantly less economic activity. Among the primary sectors, agriculture likely to report job loss than other quintiles across all was the least affected in 2020 and grew at a higher rate in but the last round. Typically, the labor force in Vietnam 2020 than in 2019. The Central Highlands, Midlands, and experiences seasonal fluctuations, with the size of the Northern Mountainous areas are poorer and more rural labor force gradually increasing from Q1 to Q4. This areas. The share of respondents who knew someone trend was observed in the previous three years (2017– who had experienced job loss was highest in the Northern 19). However, in 2020, the labor force was smaller in and Coastal Central region where Da Nang is located. Q4 than in Q1, indicating that the usual seasonal job However, other regions were not far behind in the share growth was derailed in 2020 (GSO 2021a). Sectors with of households that knew someone experiencing job employment that grew year on year Q4 of 2018 to Q4 of switching and job loss. Despite their high rates of poverty, 2019, but contracted between Q4 2019 and 2020 were ethnic minority groups reported lower rates of adverse construction and trade. employment impacts across their personal networks, likely because of their heavier reliance on agricultural Adverse labor impacts occurred broadly across self-employment and lower likelihood of working in the different socioeconomic groups and geographic more exposed sectors such as services. However, they areas. A little less than one-third of all respondents knew were more affected across nonmonetary dimensions with someone who had lost a job or switched jobs since the potential consequences for widening disparities in the beginning of the pandemic (table 2.2). Rates are lower longer-term, as will be discussed in chapter 6. among households in poorer provinces and among ethnic Chapter 2.  IMPACTS ON HOUSEHOLDS AND BUSINESSES: A YEAR DEFERRED 17 Figure 2.4 Over time, fewer Vietnamese households are experiencing new cases of employment loss 40 Share of HHS that experienced job loss (%) 35 30 25 20 15 10 5 0 Feb-Jun 2020 Jun-Jul 2020 Jul-Aug 2020 Dec 2020 - Jan 2021 Feb 2021 Reference Period Bottom 20 Q2 Q3 Q4 Top 20 95% CI Source: World Bank Vietnam COVID-19 household monitoring surveys (rounds 1–5). Note: Dates shown are reference periods. In the first round, the reference period for questions on employment loss and wage declines referenced “Since February 2020,” thus the reference period is shown as “Feb – June 2020.” In subsequent rounds, questions refer to the “previous month” from the date of interview. Household (HH) quintiles (Q) are based on household consumption per capita in 2018. Table 2.2 Employment impacts across personal networks, Vietnam Reference period February 2020– March 2021 Do you know someone who Do you know someone Share of households (%) lost their job? who switched job? All 33.9 29.3 Urban 34.2 30.4 Rural 33.8 28.7 Top 60 34.0 31.3 Bottom 40 33.7 25.8 Kinh 35.1 30.6 Ethnic minorities 27.0 21.6 Red River Delta 37.7 33.3 Midlands and Northern Mountainous areas 27.1 23.4 Northern and Coastal Central Region 40.7 32.0 Central Highlands 28.1 24.1 Southeastern Area 30.4 27.4 Mekong Delta 30.7 28.0 Source: World Bank Vietnam COVID-19 household surveys (round 5). 18 A YEAR DEFERRED – EARLY EXPERIENCES AND LESSONS FROM COVID-19 IN VIETNAM In 2020, about 17 percent of the population aged severely in Q1of 2020. Compared to previous years, 15 and older changed sectors or economic activity more people in 2020 who were unemployed in the between Q1 and Q4. In the first half of 2020, a slightly beginning of the year also remained unemployed at the smaller share of workers held a job in the same sector in end of the year (figure 2.7) at 24.0 percent compared to two consecutive quarters compared to previous years. For 17.6 and 12.2 percent, respectively, in 2018 and 2019. example, in 2020, 82.7 percent of workers held a job in Employment levels across most sectors were quite the same sector in Q1 and Q2, compared to 83.8 percent stable, with the exceptions of decreasing agriculture and in 2019 and 86.7 percent in 2018 (figure 2.5, panel a). expanding manufacturing sectors. Given the small labor Visualizations of workers’ transitions show relatively market impacts, the shedding of jobs in agriculture and stable distribution of workers across sectors (figure 2.5, the growth of jobs in manufacturing did not largely deviate panel b) and with intersectoral dynamics similar to those from medium-term structural trends. in 2019. However, these dynamics are visible only when jobs move across broad sectors, which is a significant Although reports of new job loss have diminished move for workers. Job changes may be higher because substantially, not everyone who lost their job has been dynamics within sectors are likely also occurring but are able to find comparable new employment. According to more difficult to trace in the LFS. Changes in sectors LFS data, most workers were able to transition into other were particularly pronounced in hospitality (see box 2.2). employment. However, other indicators from the LFS suggest that there was not a full recovery in employment, The number of people aged 15 years and older with some people downgrading perhaps into less desirable who were not working increased by 2.4 million in jobs, being underemployed, or switching into informal 2020 compared to 2019. In 2020, 19.9 million people work. By Q4 of 2020, about 830,000 people were estimated aged 15 and older were laid off, unemployed, or not to be underemployed,13 with the highest rates among those working, compared to 17.5 million in 2019 (figure 2.6). in the agricultural sector. The informality rate at the end of This increase is significantly larger than what was seen 2020 was 56.2 percent, an uptick following a continuous from 2018 to 2019. Workers experienced job loss most decline in informality from 2016–19 (GSO 2021a). Figure 2.5 Transitions of economic activity in Vietnam, population aged 15 years and older a. Share of workers in the same activity across quarters b. Q1 2020 vs. Q4 2020 100 Share of workers in same activity (%) Agriculture Agriculture 80 Construction Construction Fishery Fishery Gas, water electricity Gas, water electricity 60 Hotels restaurants Hotels restaurants Layoff Layoff 40 Manufacture Manufacture Mining Mining 20 Not working Not working 0 Other services Other services Quarters Quarters Quarters Quarters 1&2 2&3 3&4 1&4 Trade Trade Transport Transport 2018 2019 2020 Unemployed Unemployed Source: Vietnam Labor Force Survey panel data, 2018, 2019, and 2020. Note: The population of those aged 15 years and older was 75 million in 2020. Chapter 2.  IMPACTS ON HOUSEHOLDS AND BUSINESSES: A YEAR DEFERRED 19 Figure 2.6 The population of people aged 15 Figure 2.7 Share of unemployed in Q1 who and older who were not working increased remained unemployed in Q4, by year, Vietnam in 2020, Vietnam 30 Share of the workforce unemployed in Q1 (%) 25 24.2 25,000 Number of people 15+ (thousand) 20,000 20 17.7 15,000 15 12.3 10,000 10 5,000 5 0 0 Agriculture Fishery Mining Manufacture Gas, water, electricity Construction Trade Hotels, restaurants Transport Other services Not working Laid off 2018 2019 2020 2018 2019 2020 Source: Vietnam Labor Force Survey, 2018, 2019, and 2020. Source: Vietnam Labor Force Survey, 2018, 2019, and 2020. Wage growth ground to a halt in 2020, in contrast In Vietnam and across the developing world, women to the high wage growth in earlier periods. Wage and young people were more likely to experience growth in Vietnam has been high over the last decade, job loss. At a global level across 40 countries where particularly in sectors in which new jobs were being World Bank COVID-19 household monitoring surveys created. Data from Havers Analytics showed that in were conducted, female, young, less educated, and a span of six years from 2012 to 2018, average real urban workers were found to stop working at higher wages in industry/construction and services grew by 71 rates (Kugler et al. 2021). Gender differences in job and 65 percent, respectively). Wages remain depressed loss are primarily driven by factors related to family care into 2021; average wages in the services sector in first responsibilities but are also related to sectoral selection. quarter of 2021 were only 1.5 percent higher than in the Younger populations are more services oriented, and the previous year (GSO 2021b). Throughout the course of the less educated are more likely to be employed informally, survey collection period, about 10 percent of households both areas of employment that were hard hit. Younger reported experiencing a reduction in household income populations are also those that are in transition from over the reference period (figure 2.8). school to work and likely face a more unwelcoming labor market. The share of 15-to-20-year-olds working in Q1 of 2020 and 2019 was similar (34.9 percent and 35.6 percent, respectively). However, by Q4, the working shares of the young between 2020 and 2019 were 30 percent and 33 percent, respectively. 20 A YEAR DEFERRED – EARLY EXPERIENCES AND LESSONS FROM COVID-19 IN VIETNAM Figure 2.8 Fewer Vietnamese households are experiencing labor income declines over time 40 Share of HHS that experienced 35 30 lower income (%) 25 20 15 10 5 0 Feb-Jun 2020 Jun-Jul 2020 Jul-Aug 2020 Dec 2020 - Jan 2021 Feb 2021 Reference Period Bottom 20 Q2 Q3 Q4 Top 20 95% CI Source: World Bank Vietnam COVID-19 household monitoring surveys (rounds 1–5). Note: Dates shown are reference periods. In the first round, the reference period for questions on employment loss and wage declines referenced “Since February 2020,” thus the reference period is shown as “Feb – June 2020.” In subsequent rounds, questions refer to the “previous month” from the date of interview. Household (HH) quintiles (Q) are based on household consumption per capita in 2018. As a result of social mobility restrictions and more localized, restrictions in mobility have dampened closures, especially in April 2020, many firms the recovery. Employment changes may likely have experienced large employment losses in June worsened after January with the two recent waves in 2020 with a slight recovery in the second half of February and April 2021 that have resulted in more 2020. Surveyed formal firms suffered an aggregate mobility restrictions and business closures. Among firms, employment loss of 9.4 percent from the period before the labor adjustment mostly happened in medium and the pandemic (that is, January 2020) to June 2020 large firms (figure 2.10). Small firms did not trim their (figure 2.9). The large drop in employment experienced workforce at the initial stage of the pandemic, unlike by formal firms in the first period mirror trends in the medium and large firms that reduced their employment entire labor market, however formal firms represent a collectively by 18 and 10 percent, respectively, in June small share of total employment. Only 9.3 percent of 2020. Throughout the next six months, these firms the workforce are employed in domestic formal firms slowly recovered and have increased their employment (Cunningham, Pimhidzai, 2018). Despite a slight recovery in January 2021. Nonetheless, on average, medium and in employment between June and October 2020 with an large firms still lost 16 percent and 2 percent of their increase of 0.5 percent in employment, recovery stalled workforce, respectively, compared to pre-COVID-19 in early 2021 with little change in employment since. The levels. The average employment loss is 3 percent for reemergence of COVID-19 cases and subsequent, but firms of all sizes. Chapter 2.  IMPACTS ON HOUSEHOLDS AND BUSINESSES: A YEAR DEFERRED 21 Figure 2.9 Large initial employment drop, with a Figure 2.10 Most of Vietnam’s employment small recovery in late 2020, Vietnam changes happened in medium and large firms 2 25 0.5 20 18.6 Changing in employment (%) Changing in employment (%) 0 −0.01 15 −2 10 4.8 −4 5 1.6 1.4 0.9 1.4 0 −6 −2.1 −5 −8 −10 −9.6 −10 −9.4 −15 −20 −18.1 −12 Small Medium Large Before pandemic to June 2020 Before pandemic to June 2020 June to Sept/Oct 2020 June to Sept/Oct 2020 Sept/Oct 2020 to January 2021 Sept/Oct 2020 to January 2021 Source: World Bank COVID-19 Business Pulse Surveys. Source: World Bank COVID-19 Business Pulse Surveys. Note: Trends are robust to controlling for survey dates. Note: Trends are robust to controlling for survey dates. Box 2.2 Workers in Vietnam’s hotels and restaurants Employment in tourism-related sectors was expected to be severely hit as Vietnam closed its international border to tourism starting in March 2020. Jobs in the hotel and restaurant sector were indeed less stable; fewer workers were able to stay in the sector consistently in 2020 compared to 2018 and 2019 (figure B2.2.1). However, the share of the labor force in this sector as a primary occupation is small, representing about 4.4 percent of total workers, or 3.74 percent of the population aged 15 years and older. 22 A YEAR DEFERRED – EARLY EXPERIENCES AND LESSONS FROM COVID-19 IN VIETNAM Box 2.2 - continued Figure B2.2.1 Share of workers in Vietnam’s hotel and restaurant sector in multiple quarters, by year 100 80 Share of workers (%) 60 40 20 0 Quarters 1 & 2 Quarters 2 & 3 Quarters 3 & 4 Quarters 1 & 4 2018 2019 2020 Source: Vietnam Labor Force Survey panel data, 2018, 2019, and 2020. Workers in the hotel and restaurant sector initially faced much higher rates of layoffs, but most were able to adapt and find other jobs by the end of the year. In the short run, workers in hotels and restaurants faced layoffs and job loss. The transition in the first two quarters of 2020 shows much higher layoff and unemployment rates than in other years. Of those workers laid off in the first quarter, 8.5 percent of hotel and restaurant workers were still laid off in the second quarter and had not found other work (figure B2.2.2, panel a). But, by the end of the year, the majority of hotel and restaurant workers were able to find employment in other sectors or regain work (figure B2.2.2, panel b). However, these jobs are not necessarily better jobs; as discussed earlier, rates of informality and underemployment have increased. Figure B2.2.2 Transitions of Vietnamese hotel and restaurant workers from Q1 of 2020 into new sectors (Q2 or Q4) a. Quarters 1 and 2 of 2020 b. Quarters 1 and 4 of 2020 90 90 80 80 Share of hotel and restaurant There of hotel and restaurant 70 70 workers in Q1 (%) workers in Q1 (%) 60 60 50 50 40 40 30 30 20 20 10 10 0 0 Hotel and Different Laid off Unemployed Not Hotel and Different Laid off Unemployed Not restaurant sector working restaurant sector working 2018 2019 2020 2018 2019 2020 Source: Vietnam Labor Force Survey panel data, 2018, 2019, and 2020. Note: Based on broad sector classifications. Chapter 2.  IMPACTS ON HOUSEHOLDS AND BUSINESSES: A YEAR DEFERRED 23 Box 2.3 Employment impacts by gender See appendix F for more information on measuring gender impacts, including potential sample selection bias. Women were more likely to report losing a wage job early in the pandemic. Among main respondents who are wage workers, female respondents in the World Bank Vietnam COVID-19 household monitoring survey reported worse outcomes (figure B2.3.1). Significantly more female than male respondents lost a wage job between February and June 2020. This observation holds true in a weighted logit regression in the whole sample and in subsamples of urban, top-60 households and households with multiple earners. It is likely explained by the higher share of formal wage jobs and service-sector jobs found among female respondents. Controlling for age and education of respondents explains away the statistical significance of the female dummy variable in the regression. Conditional on working as a wage employee, male and female respondents are equally likely to be able to continue work (93 percent of male and female respondents). Although female respondents are slightly less likely to receive full payment than male respondents (85 percent compared to 89 percent, respectively), this difference is not statistically significant in a logit regression both with and without demographic controls. Figure B2.3.1 Among Vietnam’s wage workers, female main respondents reported worse outcomes during the pandemic a. Female respondents are more likely to lose a b. Likelihood of continuing to work and receiving full wage job than male respondents pay among male and female respondents 3 100 93 89 Share of wage worker respondents 93 Share of wage worker respondents 85 80 2 2.0 60 (%) (%) 1.3 40 1 20 0.7 0.8 0 0 Male Female Able to continue working Receive full pay Lost nonwage job Lost wage job Male Female Source: World Bank Vietnam COVID-19 household monitoring surveys (R1). Note: Wage job information is asked of only the main respondent of the household and may not be representative of the entire labor force. 24 A YEAR DEFERRED – EARLY EXPERIENCES AND LESSONS FROM COVID-19 IN VIETNAM Box 2.3 - continued Compared to other countries, the female labor force participation in Vietnam before the pandemic is high. However, female labor force participation is still lower compared to males; female respondents are 9.3 percentage points less likely to be working compared to male respondents. This is largely contributed by the preexisting gap in work participation between men and women, with female respondents 8.5 percentage points more likely to have never worked in February (before the pandemic) or in June 2020 (round 1of COVID-19 monitoring survey). The COVID-19 pandemic did widen the gender gap of labor market participation to a small extent; the share of female respondents dropping out from work, 2.8 percent, is 0.8 percentage points higher than men’s 1.9 percent (figure B2.3.2). Figure B2.3.2 Work participation of male and female respondents in COVID-19 monitoring survey, June 2020 vs. February 2020 Female 72.2 5.2 2.8 19.9 Male 80.1 6.5 1.9 11.5 0 20 40 60 80 100 Share of respondents (%) Working (same job) Working (different job) Stopped working Never worked Source: World Bank Vietnam COVID-19 household monitoring surveys (round 1). A higher incidence of women dropping out of the labor force can be explained by various factors. Table B2.3.1 reports the marginal effect of running logit regressions of work stoppage on a female respondent dummy. In the whole sample, the female coefficient is positive and statistically significant at the 10 percent level. Dividing the sample into urban and rural and those with and without a household farm, we note that the work stoppage for male and female respondents is not statistically different within each of these subsamples. However, female respondents have a higher likelihood of stopping work in top-60 households and in households with multiple adult earners. These households are less economically vulnerable, and individuals in them may be more educated and engaged in higher-skill occupations. The statistical significance goes away after we control for respondents’ age and education. Chapter 2.  IMPACTS ON HOUSEHOLDS AND BUSINESSES: A YEAR DEFERRED 25 Box 2.3 - continued Table B2.3.1 Female vs. male work stoppage rates, Vietnam All (N=6213) 0.008* (0.005) Rural (N=4421) Urban (N=1792) 0.005 0.011 (0.004) (0.011) Has household farm (N=3680) No household farm (N=2533) 0.001 0.010 (0.004) (0.009) Bottom 40 (N=2653) Top 60 (N=3560) 0.003 0.012* (0.006) (0.007) No or single adult earner (N=1088) Multiple adult earners (N=5125) 0.002 0.010** (0.011) (0.005) No child under 5 in 2018 (N=4387) Has child under 5 in 2018 (N=1826) 0.006 0.015** (0.006) (0.007) Source: World Bank staff calculations. Note: Dependent variable takes on 1 if respondent did not work in the first round of the COVID-19 monitoring survey but did work in February (before the outbreak of the pandemic). The table reports logit regressions of work stoppage rates on female dummy in the full sample and subsamples indicated in the column heading. Marginal effects can be interpreted as the percentage point change in the likelihood of stopping working if female respondent is true. Standard errors are reported in parentheses. Household-level weights are applied in the regression. N = number of observations. Childcare remains a pervasive issue that cannot be explained by age and education controls. Dividing the sample into households with a child under five years old in the 2018 Vietnam Household Living Standards Survey and those without, we note that female respondents are worse off than male respondents in households with a child under five in 2018. The statistical significance does not go away even after controlling for respondents’ age and education. 26 A YEAR DEFERRED – EARLY EXPERIENCES AND LESSONS FROM COVID-19 IN VIETNAM Employment is not yet fully jobs. Although it is difficult to interpret these results in recovered in early 2021 absolute numbers, it is still revealing that the percentage of respondents who knew someone who had switched a Employment levels in early 2021 are not yet back job since February 2020 is similar to the percentage who to pre-COVID-19 levels. In Q1 of 2021, the General knew someone currently looking for a job in March 2021. Statistics Office reported about 9.1 million people aged 15 Evidence of a high share of job seekers is supported by and older were adversely affected by job loss, furloughs, the increasing numbers of underemployed (as seen in the suspension of production and business operations, LFS). In Q1 of 2021, the underemployment rate rose to reduced working hours, or reduced labor incomes (GSO 2.2 percent, or 971,000 people (GSO 2021b). 2021b). The size of the labor force and number of workers in Q1 of 2021 was estimated at 49.9 million compared A small share of households had fewer adults to 50.1 million in Q1 2020. There is also some evidence working in March 2021 than in January 2020 before of some jobs shifting into the informal sector, especially COVID-19. In retrospective questions, about 7 percent of among women, and of higher rates of underemployment. households reported that fewer adults in their household were working in March 2021 than in January 2020 (figure In Q1 of 2021, responses from the World Bank 2.11). The differences are largest across geographic COVID-19 monitoring surveys in Vietnam show a regions, as opposed to across income distribution or moderate share of respondents who knew someone household ethnicity. The Southeast region reported the currently looking for a job. In March 2021, almost 30 largest share of households with fewer adults working in percent of respondents indicated they knew someone March 2021 than in January 2020. Farming regions such who was looking for a job now and had not found as the Mekong Delta had lower shares of households with one (table 2.3). This response can have a variety of fewer adults working, because the beginning of March interpretations. At a minimum, it suggests that the labor aligned with the rice sowing season. market was unsettled by COVID-19 and many who experienced job losses have not yet found suitable new Table 2.3 Employment impacts across personal networks, Vietnam March 2021 Do you know someone who is looking for a job now and Type of household has not found one? (% of respondents) All 29.3 Urban 31.2 Rural 28.2 Top 60 28.8 Bottom 40 30.1 Kinh 29.7 Ethnic minorities 27.1 Red River Delta 29.6 Midlands and Northern Mountainous areas 29.2 Northern and Coastal Central Region 37.2 Central Highlands 30.2 Southeastern Area 25.2 Mekong Delta 23.4 Source: World Bank Vietnam COVID-19 household monitoring surveys (round 5). Chapter 2.  IMPACTS ON HOUSEHOLDS AND BUSINESSES: A YEAR DEFERRED 27 Figure 2.11 About 7 percent of Vietnamese households reported fewer adults working in March 2021 than in January 2020 Mekong Delta 4 Southeastern Asia 11 Central Highlands 9 Northern and Coastal Central Region 5 Midlands and Northern Mountainous Areas 6 Red River Delta 7 National 7 0 20 40 60 80 100 Share of households (%) More Same Less Source: World Bank Vietnam COVID-19 household monitoring surveys (round 5) Family farms Most family farms reported being able to operate report farming-related factors as the reason for declining normally over the past year. Only about 10 percent household income. Agriculture-reliant regions such as the of farming households reported that they were unable Central Highlands and the Mekong regions persistently to perform normal activities. This aligns with the finding had the highest share of households reporting that they that the agriculture sector fared relatively well in 2020 experienced negative shocks related to farming, including compared to other sectors, with higher sectoral gross disruptions to activities as well as declines in sales domestic product growth in 2020 than in 2019. Farming prices (figure 2.12). households in Vietnam still experienced disruptive conditions from factors both related to and not related COVID-19 impacted supply chains and transportation to COVID-19. Compared to other countries in the East (figure 2.13). A lack of market demand and transportation Asia and Pacific region, the share of farming households was the second most common reason that farmers in Vietnam that were able to operate normally was lower reported for why they could not operate normally. Supply than in Cambodia, the Lao People’s Democratic Republic, chain challenges were more likely reported by households and Mongolia between May and July 2020. in the Red River Delta. Particularly in round 5, lockdowns near the Tet holiday severely affected sellers of peach, Over half of households are engaged in family cherry blossoms, and other seasonal crops that relied farming activities with a smaller share of households on the holiday as the main point of sales for the entire solely reliant on agriculture. Agriculture income is the year. Over the year, mobility restrictions and lockdowns primary source of income for 11 percent of all households, disappeared as reasons inhibiting farming functions. By and for 30 percent of households in the lowest welfare round 5, virtually no affected farming households cited decile. Thus, poorer households are more likely to social mobility restrictions as challenges. 28 A YEAR DEFERRED – EARLY EXPERIENCES AND LESSONS FROM COVID-19 IN VIETNAM Figure 2.12 Declines in income due to farming-related factors were more common among the poor and those in more rural regions of Vietnam 30 25 Share of households (%) 20 15 10 5 0 Feb-Jun 2020 Jun-Jul 2020 Jul-Aug 2020 Dec 2020 - Jan 2021 Feb 2021 Red River Delta Midlands and Northern Mtns North and Central Coast Central Highlands Southeast Mekong Source: World Bank Vietnam COVID-19 household monitoring surveys (rounds 1 - 5). Note: Dates shown are reference periods. In the first round, the reference period for questions on family farm income referenced “Since February 2020,” thus the reference period is shown as “Feb – June 2020.” In subsequent rounds, questions refer to the “previous month” from the date of interview. Persistent reasons reported for being unable Across different types of crops, the price of rice was to perform activities are unrelated to COVID-19 the most likely to remain high (figure 2.14). Across all reasons, an important reminder that crises can World Bank COVID-19 survey rounds in the field from occur simultaneously. Weather, natural disasters, and June 2020 to March 2021, farmers who were selling rice crop/animal diseases were the most commonly reported were the most likley to enjoy higher prices than compared causes of farming disruptions across all five rounds of to the same time a year ago. Among households, rice COVID-19 monitoring surveys. Weather and natural is predominantly sold by family farms in the North and disaster risks most severely affected the farmers in the Central Coastal and Mekong regions. Rice farmers Mekong Delta. During COVID-19, the Mekong Delta, also benefited from competitive prices because rice exports known as the “Rice Bowl,” was faced with a double crisis were able to maintain growth and competitiveness as droughts and saltwater intrusion afflicted the region during COVID-19, supply was limited because of the in early 2020. Other natural disasters hit Vietnamese drought, and the government stockpiled rice. However, farmers throughout the year but are not captured in the other agricultural products including fruits, vegetables, surveys because of the periodicity and timing of fieldwork. and livestock yielded lower prices. Agricultural products Typhoons landed on the central coast in October 2020, requiring time-sensitive transportation experienced the leading to over 200 deaths and caused flooding and most negative impacts from disruptions to supply chain landslides. Unseasonal frost in early 2021 also led to logistics. For example, fruit export revenues dropped by crop damages in northern mountain areas. 13 percent in 2020. These disruptions led to lower prices in the domestic market. Chapter 2.  IMPACTS ON HOUSEHOLDS AND BUSINESSES: A YEAR DEFERRED 29 Figure 2.13 Farming operations and disruptions during COVID-19, Vietnam By round 5, mobility restrictions were no longer a cause of farm operation disruptions a. Required to stay home b. Restrictions to movement/travel 20 30 25 Share of households Share of households 15 20 10 15 10 5 5 0 0 All Urban Rural Top 60 Bottom All Urban Rural Top 60 Bottom 40 40 R1 R5 R1 R5 However, supply chain logistics and natural disasters remained relevant challenges throughout the survey period 60 Share of effected farming HHs (%) 50 40 30 20 10 0 R1 R5 R1 R5 R1 R5 Unable to sell/Transport outputs Weather, natural disasters Livestock and crop disasters Red River Delta Midlands and Northern Mtns North and Central Coast Central Highlands Southeast Mekong Delta Source: World Bank Vietnam COVID-19 household monitoring surveys (round 1 and round 5). Note: Detailed questions on reasons farmers were negatively affected were only asked in round 1 (R1) and round 5 (R5) of the survey series. Field work for R1 was conducted between June 5 and July 8, 2020, with reference to “Since February 2020” to the date of interview. Fieldwork for R5 was conducted from March 13 to March 31, 2021, with reference to “Since January 2021” to date of interview. HH = household. 30 A YEAR DEFERRED – EARLY EXPERIENCES AND LESSONS FROM COVID-19 IN VIETNAM Figure 2.14 Crop prices in Vietnam compared to the previous year a. Rice b. Vegetables Mar 2021 Mar 2021 Jan 2021 Jan 2021 Sept/Oct 2020 Sept/Oct 2020 Jul/Aug 2020 Jul/Aug 2020 Jun/July 2020 Jun/July 2020 0 20 40 60 80 100 0 20 40 60 80 100 Share of farming households (%) Share of farming households (%) c. Livestock and poultry d. Fruits Mar 2021 Mar 2021 Jan 2021 Jan 2021 Sept/Oct 2020 Sept/Oct 2020 Jul/Aug 2020 Jul/Aug 2020 Jun/July 2020 Jun/July 2020 0 20 40 60 80 100 0 20 40 60 80 100 Share of farming households (%) Share of farming households (%) Higher Same Lower Not selling Source: World Bank Vietnam COVID-19 household monitoring surveys (rounds 1–5). Note: Comparison of crop prices within the last week from the time of interview (June 2020 – March 2021) to the same time last year (June 2019 – March 2020). Family businesses About 25 percent of households are engaged in a In the case of family businesses, economic impacts family business, and most activities are informal were more severe along the intensive margin rather and small-scale. Family businesses range from small than the extensive margin (figure 2.16). Family peddling activities to owning businesses with permanent business closure rates remained low throughout 2020. By storefronts. Most family businesses are in service- the second half of the year, most family businesses were oriented activities, followed by agriculture, and then open. Although most businesses remained open, a large manufacturing. About 20–25 percent of family businesses proportion of family businesses experienced reductions in pay rent for an additional storefront that is not connected business income. Wealthier households are more likely to to the home, or have a tax identifier (ID), indicating that have operations in family businesses, so impacts along most family businesses are small-scale and informal this economic channel are more salient at higher ends (figure 2.15). As expected, households with more means of the distribution. and who are wealthier, are more likely to have separate storefronts and tax IDs for formal revenue reporting. Chapter 2.  IMPACTS ON HOUSEHOLDS AND BUSINESSES: A YEAR DEFERRED 31 Figure 2.15 Family business performance in Vietnam a. Pays rent for storefront b. Has a tax ID 30 40 Share of family businesses (%) Share of family businesses (%) 35 25 30 20 25 15 20 15 10 10 5 5 0 0 Bottom Q2 Q3 Q4 Top 20 Bottom Q2 Q3 Q4 Top 20 20 20 Source: World Bank Vietnam COVID-19 household monitoring surveys (round 4). Note: Household (HH) quintiles (Q) are based on household consumption per capita in 2018. Figure 2.16 Reduced family business income was more common than family business closures, Vietnam a. Business closure b. Reduced business income Share of HHs experiencing reduction of 30 30 Share of HHs experiencing closure of family business income (%) 25 25 family business (%) 20 20 15 15 10 10 5 5 0 0 Feb-Jun 2020 Jun-Jul 2020 Jul-Aug 2020 Jan 2021 Feb 2021 Feb-Jun 2020 Jun-Jul 2020 Jul-Aug 2020 Jan 2021 Feb 2021 Dec 2020 - Dec 2020 - Reference Period Reference Period Bottom 20 Q2 Q3 Q4 Top 20 95% CI Source: World Bank Vietnam COVID-19 household monitoring surveys (rounds 1–5). Note: Dates shown are reference periods. In the first round, the reference period for questions on business closure and family business income referenced “Since February 2020,” thus the reference period is shown as “Feb – June 2020.” In subsequent rounds, questions refer to the “previous month” from the date of interview. Household (HH) quintiles (Q) are based on household consumption per capita in 2018. 32 A YEAR DEFERRED – EARLY EXPERIENCES AND LESSONS FROM COVID-19 IN VIETNAM Households with family businesses and those Increased care responsibilities were the main driver experiencing poor business conditions are likely to of the gender difference in lost turnover. Women be located in regions associated with lockdowns and are more likely to work in the service sector, but, even outbreaks. For example, closures were more common controlling for that, the gender gap on lower business in the North and Central Coast regions during round turnover remains. When reduced hours of work are also 3, coinciding with the Da Nang outbreak. In round 5, accounted for, the gap disappears and the reduced households with family businesses in the Red River Delta hours are statistically significant (see table 2.4).15 During were also more adversely affected, coinciding with the lockdowns, women tend to take on most of the burden location and timing of the third wave. of household care responsibilities. During round 1 (which covered the national lockdown period), mothers were also Some gender-biased impacts existed in family much more likely than fathers to report reducing hours or business turnover. Although the family businesses in 14 stopping work altogether to take care of children during which male and female respondents were engaged were school closures. equally likely to be operating at the time of the survey, female respondents’ family businesses experienced lower business turnovers than those of male respondents (figure 2.17). Their businesses were also more likely to experience a significant (greater than 50 percent) drop in business turnover. Figure 2.17 Family business outcomes by male and female respondents engagement, Vietnam 100 95 95 Share of family businesses (%) 80 60 40 37 28 20 18 11 0 Business still open Lower business turnover Drop by >=50% Male Female Source: World Bank Vietnam COVID-19 household monitoring surveys (round 1). Chapter 2.  IMPACTS ON HOUSEHOLDS AND BUSINESSES: A YEAR DEFERRED 33 Table 2.4 Mediators of female-specific experience of significant drop in business turnover, Vietnam (1) (2) (3) (4) (5) (6) Female 0.073*** 0.051** 0.048** 0.046** 0.042* 0.024 (0.024) (0.023) (0.023) (0.023) (0.022) (0.021) Urban 0.014 0.015 0.012 0.017 (0.023) (0.023) (0.023) (0.022) Bottom-40 0.030 0.027 0.025 (0.025) (0.026) (0.024) Ethnicity −0.054 −0.055 −0.067 (0.044) (0.045) (0.044) Single adult household 0.059 0.046 (0.042) (0.032) Reduced hours 0.206*** (0.019) Observations 1359 1337 1337 1337 1337 1337 Sector FE X X X X X Region FE X X X X Source: World Bank Vietnam COVID-19 household monitoring surveys (round 1). Note: Dependent variable takes on 1 if respondent’s family business experienced a significant (greater than 50%) drop in business turnover. Marginal effects can be interpreted as the percentage point change in the likelihood of experiencing a significant drop in business turnover if the binary correlates are true. Standard errors are reported in parentheses. Household-level weights are applied in the regression. FE = fixed effects. WHAT WERE THE TOTAL IMPACTS ON HOUSEHOLD INCOMES? The primary impact channel of adverse shocks related There are pros and cons to using either the last month to COVID-19 was through household incomes.16 or the last year as the baseline to measure changes The preceding section in this chapter illustrated how in income, which are important to bear in mind. The households reported being adversely affected through World Bank COVID-19 household monitoring surveys are a range of impact channels. These channels varied conducted by phone, and it was not possible to collect and affected households across the spectrum, affecting detailed income information. Because the surveys are not incomes for different groups in different ways. Households evenly implemented across time periods, there may be in the COVID-19 surveys were asked about their current missing information on income changes over periods that incomes compared to both the last month and the were not covered by the survey (see figure 2.1 for periods same time last year. First, self-reported changes in total not covered during the fieldwork). The survey may miss household incomes during COVID-19 are discussed. episodes of declining incomes if the reductions occurred Second, trends in an income index from June 2020 to during an off-survey period and not during the on-survey March 2021 are described. The index is constructed from period. Asking about changes to household income since a panel sample of households across all five rounds of the last year can also be problematic because conditions the World Bank COVID-19 surveys. in the baseline matter. For example, by the last round, more households report that incomes in March 2021 are 34 A YEAR DEFERRED – EARLY EXPERIENCES AND LESSONS FROM COVID-19 IN VIETNAM higher than in March 2020, in particular households in the The majority of households reported an income Mekong Delta. However, this can be related to COVID- decline in the first round, after which income trends 19’s having already exhibited impacts and affected the significantly improved (figure 2.18, panel a). After round baseline incomes, or because conditions in early 2020 1 which covered the nationwide lockdown, the share of were worse for some households because of droughts. households reporting lower current income compared to Recalling income from a year ago is also less precise the previous month slowly but consistently reduced over than recalling income from a month ago. time. The nationwide lockdown was the first in the country and a truly unexpected shock for households. Over time, Changes in household income even though outbreaks continued to emerge, households throughout the pandemic may have learned to adapt better as the country also learned to manage outbreaks more locally. Households along the entire welfare distribution reported episodes of declining household incomes. Income recovered on both the extensive and A range of underlying factors affected households from intensive margins. Fewer households reported declining many walks of life. For example, poorer households were household incomes as time passed. In round 2, conducted more likely to experience job loss and declines in farm in late June and early July of 2020, about 33 percent income, whereas richer households were more likely to of households reported lower current income than the experience reduced wages and family business income. previous month; this share reduced to 17 percent by the last round in March 2021. Among households reporting lower income, the magnitude of the decline also reduced. Figure 2.18 Under a longer timeline, more Vietnamese households still have lower incomes a. Current compared to last month b. Current compared to last year 100 100 Percentage of households (%) Percentage of households (%) 80 80 60 60 40 40 20 20 0 0 Jun/July Aug/Sept Jan/Feb March (R1*) Jul/Aug 2020 vs. Jun/Jul 2020 (R2) Aug/Sept 2020 vs. Jan/Feb 2021 vs. Dec 2020/Jan 2021 (R4) March vs. Feb 2021 (R5) Jun/July 2020 vs. Feb-June 2020 Jul/Aug 2020 (R3) 2020 vs. 2020 vs. 2021 vs. 2021 vs. previous previous previous previous year (R2) year (R3) year (R4) year (R5) Lower (>=100%) Lower (50-99%) Lower (25-49%) Lower (<25%) Same Higher Don't Know Declined (R1 only) Not decline (R1 only) Source: World Bank Vietnam COVID-19 household monitoring surveys (rounds 1–5) cross-section. Note: In round 1, the change in income was asked from the time of interview compared to Feb–Jun 2020, and responses were recorded only if income declined or not. Income changes compared to the last year was not asked in round 1. The amount of change was not recorded. For rounds 2–5, current income in the most recent full month at the time of interview is compared to either the last full month or the same month last year. For disaggregated trends by welfare quintile and region, see additional figures in the appendix D. Chapter 2.  IMPACTS ON HOUSEHOLDS AND BUSINESSES: A YEAR DEFERRED 35 In round 2, nearly 20 percent of all households reported Among those who still have lower incomes than last that current incomes were at least 25 percent lower year, some groups are more likely to report larger than in the previous month. By the last round in March reductions.17 A very small share of households reported 2021, about 10 percent of all households reported such 100 percent or total income loss compared to last year. levels of lower incomes. In the last round of the surveys, Wealthier households are more likely to report a lower households engaged in family businesses, families with percentage decline in income loss than the poorest children, and younger families were the most likely to households (< 25 percent decline). Wealthier households report declining income compared to the previous month. are also more likely to report that their incomes are higher in March 2021 than in the previous year. That wealthier Fewer households report declining incomes in the households were able to make gains during COVID-19, most recent survey round, but not all household and poorer households were not, is concerning for incomes have recovered to pre-COVID-19 levels. widening inequality. The good news is that over time Incomes compared to pre-COVID-19 periods show the share of households reporting large differences in that about 30 percent of households still self-report current incomes to the previous year is shrinking. About lower household income in March 2021 than in March 22 percent of all households reported that incomes in July 2020 (figure 2.18, panel b). In each survey round, more 2020 (round 2) were over 50 percent lower than at the households reported having lower income compared same time a year ago. By March 2021 (round 5), only 11 to last year than the previous month. Responses on percent of households reported that income levels were comparisons of current income to the previous year 50 percent lower than the previous year. are more reflective of a cumulative change in income and provide insights on longer-term welfare differences. Observing trends using a panel subset Responses to income changes compared to the previous month underrepresent all income changes On the basis of responses to changes in income because the survey did not cover all periods of time, since the previous month, an income index was with the longest off-survey period being during the created using a panel of households present in all prolonged second wave. five rounds. It is important to note the caveats presented in the beginning of this chapter, especially that the As the previous chapters show, impacts from surveys do not cover a continuous period of time and COVID-19 permeated through multiple aspects of that there are “off-survey” periods. The longest off-survey life and affected households throughout the entire period in which information was not collected was during welfare distribution, but some households were more the second outbreak. Thus, estimates of adverse impacts affected than others. After controlling for economic are expected to be a lower bound. The index is set at 100 activity, ethnicity, and region, households with certain in June 2020 for each household.18 The construction of characteristics were still more likely to report lower current the index is based on self-reported changes to household income relative to the last month. Households without a incomes from the previous month. The magnitudes formal source of income, either those lacking a formal of income change are reported only on the basis of wage contract or having a family business that lacked ranges: 1–24 percent, 25–49 percent, 50–99 percent, a tax registration ID, were more likely to report lower and 100+ percent. A low-impact estimate of the income incomes across all rounds. Households with children index assumes the lowest amount of income decline were also more likely to report lower incomes, because and the highest amount of income increase on the basis work hours were affected by greater care responsibilities. of responses. For example, consider a household that reported lower income between 1 percent and 24 percent. The low-impact estimate would assume income declined by only 1 percent. If a household reported that current household income was 25–49 percent higher than the previous month, the low-impact estimate would assume that income increased by 49 percent. 36 A YEAR DEFERRED – EARLY EXPERIENCES AND LESSONS FROM COVID-19 IN VIETNAM About half of households reported a decline in The current COVID-19 crisis may be more gender- household income more than once. Households were biased. Unlike typical past economic crises it is “self- more likely to report multiple episodes of declining income imposed” by mobility restrictions, business shutdowns, if they had a family business, if they had children, or if school and institutional childcare closures, or stay-at- the respondent was a wage worker, but were significantly home orders (Alon et al. 2020). The issue of childcare less likely if the household had a formal income channel. 19 arose as a key concern and a prerequisite for economic Households in the North and Central Coast as well as recovery. Although women typically bear a disproportionate the Southeast and Mekong Delta were the most likely to responsibility of childcare around the world, the COVID-19 repeat multiple episodes of declining incomes. pandemic exacerbated the pressure on women’s time. In a survey of 38 countries across different regions conducted Some groups reported more adverse changes to between April and November 2020, UN Women found income. Differences in income trends are not disparate that, since the pandemic hit, women spent on average enough to be considered “K-shaped,” but some groups an additional 5.2 hours per week, whereas men spent an are clearly recovering faster than others. Throughout additional 3.5 hours per week, on unpaid care work. In the period for which the income index was calculated, Vietnam, during the nationwide lockdown in April 2020, the following groups reported more protracted declines women were much more likely to care for children. In more in their household incomes; female respondents and than half of households, the care responsibility fell solely households in the bottom 20 percent of the welfare on the mother, whereas the responsibility was shared distribution before COVID-19, those without any between the father and the mother in almost 30 percent formal channels of income, and households in regions of households. In only 15 percent of households did fathers particularly hard-hit by COVID-19 (figure 2.19). take the sole responsibility, and the remaining 4 percent of households relied on other family members. Figure 2.19 Divergent recovery in an income index, Vietnam a. By gender of the respondent b. By welfare group 100 100 Income index (100 = June 2020) Income index (100 = June 2020) 80 80 60 60 40 40 20 20 0 0 Male Female Male Female Gender of respondent Household welfare quintile Jun/July 2020 Jul/Aug 2020 Sept/Oct 2020 Jan 2021 Mar 2021 95% CI Source: World Bank Vietnam COVID-19 household monitoring surveys (rounds 1–5) panel subset. Note: Exact rates of income change is not recorded, only ranges (<=25%, 25–49%, 50–99%, and 100+%). Low-impact estimates are shown and assume the largest rate of change if income is reported to be increasing, or the smallest rate of change if income is reported to be declining. Estimates assume income levels are constant over off-survey periods. Chapter 2.  IMPACTS ON HOUSEHOLDS AND BUSINESSES: A YEAR DEFERRED 37 Informality is strongly correlated with a lower There are regional differences in household income income index (figure 2.20). Informal employment and trends (figure 2.21). The North-Central Coast region business are very common. About 19 percent of the panel suffered from the lowest income index in March 2021, sample has either formal income sources through wage as can be expected from a highly service-dependent employment with a contract or a family business with a region that experienced repeated lockdowns from tax ID. All agricultural activity is assumed to be informal. the Da Nang outbreak. The Southeast, where Ho Chi Informality is associated with lower labor productivity and Minh City is located, may not have been as resilient limited access to finance. Informal workers or businesses because it is traditionally the largest entry point for have less access to safety nets. Despite a proactive effort international travelers and has the largest international by the government to provide cash support to informal ex-pat community. In 2019, Tan Son Nhat International workers who were affected by COVID-19, such policies Airport near Ho Chi Minh City handled about 40 million were difficult to carry out because informal workers are passengers, which is about 10 million more than Noi not registered and their activities are difficult to verify Boi International Airport in Hanoi. Hanoi, as the seat (more information on COVID-19 household relief policies of government, has a much more domestically driven is presented in chapter 4). economy. The income index in the Mekong Delta showed a rebound after having already been at a low point in early 2020 because of droughts. Figure 2.20 Vietnamese households without any formal labor market income sources have a lower income index 100 Income index (100 = June 2020) 90 80 70 60 50 No Yes Household has at least one formal income source Jun/July 2020 Jul/Aug 2020 Sept/Oct 2020 Jan 2021 Mar 2021 95% CI Source: World Bank Vietnam COVID-19 household monitoring surveys (rounds 1–5) panel subset. Note: Exact rate of income change is not recorded, only ranges (<=25%, 25–49%, 50–99%, and 100+%). Low-impact estimates are shown and assume the largest rate of change if income is reported to be increasing, or the smallest rate of change if income is reported to be declining. Estimates assume income levels are constant over off-survey periods. 38 A YEAR DEFERRED – EARLY EXPERIENCES AND LESSONS FROM COVID-19 IN VIETNAM Figure 2.21 Changes in the household income index varied by region, Vietnam 120 Income index (100 = June 2020) 100 80 60 40 20 0 Red River Delta Midlands and Northern and Costal Central Southeastern Mekong Delta Northern Central Region Highlands Area Mountainous Areas Region Jun/July 2020 Jul/Aug 2020 Sept/Oct 2020 Jan 2021 Mar 2021 95% CI Source: World Bank Vietnam COVID-19 household monitoring surveys (rounds 1–5) panel subset. Note: Exact rate of income change is not recorded, only ranges (<=25%, 25–49%, 50–99%, and 100+%). Low-impact estimates are shown and assume the largest rate of change if income is reported to be increasing, or the smallest rate of change if income is reported to be declining. Estimates assume income levels are constant over off-survey periods. CI = confidence interval. Chapter 2.  IMPACTS ON HOUSEHOLDS AND BUSINESSES: A YEAR DEFERRED 39 Notes 7  This report primarily uses information from the World Bank COVID-19 household monitoring survey, which completed five rounds from June 2020 to March 2021. Three rounds of the World Bank COVID-19 firm monitoring surveys were collected over the same period, and data collection is still ongoing. 8  The higher negative response rate in the first round may also be related to a longer reference period (four months, compared to one month in subsequent rounds). Questions also ask about new shocks, and those who are experiencing prolonged job loss may not repeatedly report this “shock.” 9  Shocks can be non-COVID-19 related such as illness or death in the family. 10  Employment information in the World Bank COVID-19 monitoring surveys primarily captures the conditions of the main respondent and are not representative of the full labor force. 11  Readers are directed to World Bank (2021d) for more detailed analysis of labor impacts during COVID-19 using the Vietnam Labor Force Surveys, 12  This may also be affected by the reference period for the first round being much longer (four months) than for other rounds (one month). 13  Those who are currently working but are willing and available for more work. 14  Because questions on family businesses are a household-level rather than an individual-level outcome, there is less concern regarding gender sample selection bias. 15  Mediation analysis is performed by sequentially adding factors that likely absorb some of the magnitude or statistical significance of the female dummy. The analysis starts with a basic logit regression of the binary indicator of experiencing a significant drop in business turnover on female dummy and sequentially adds other correlates in subsequent columns (table 2.4) until the coefficient of female is no longer statistically significant. 16  For background on household income sources, appendix B describes household incomes in the pre-COVID-19 context. 17  For disaggregated figures by welfare quintile and region, see additional figures in the Annex. 18  This question was first asked in Round 2 and June 2020 is the first reference period. 19  A formal income channel is if either the main respondent has a contract through wage employment or the family business has a tax ID. The employment contract status of other household members was not recorded. References Alon, Titan M., Matthias Doepke, Jane Olmstead-Rumsey, and Michele Tertilt. 2020. “The Impact of COVID-19 on Gender Equality.” NBER Working Paper 26947 National Bureau of Economic Research, Cambridge, MA. GSO (General Statistics Office). 2021a. “COVID-19 Impacts on Labour and Employment Situation in Quarter IV of 2020.” GSO, Hanoi, January 6. https://www.gso.gov.vn/en/data-and-statistics/2021/01/covid-19-impacts-on-labour-and-employment-situation- in-quarter-iv-of-2020/ GSO (General Statistics Office). 2021b. “Report on the COVID-19 Impacts on Labour and Employment Situation in the First Quarter of 2021.” GSO, Hanoi, April 16. https://www.gso.gov.vn/en/data-and-statistics/2021/04/report-on-the-covid-19-impacts-on-labour- and-employment-situation-in-the-first-quarter-of-2021/. Ha, Thi, and Anh Minh. 2021. “Citizens, Businesses Hurt as Rising Prices Raise Inflation Concerns.” VNExpress, May 19, 2021. https://e.vnexpress.net/news/business/economy/citizens-businesses-hurt-as-rising-prices-raise-inflation-concerns-4279567.html. Kugler, Maurice, Mariana Viollaz, Daniel Duque, Isis Gaddis, David Newhouse, Amparo Palacios-Lopez, and Michael Weber. 2021. “How Did the COVID-19 Crisis Affect Different Types of Workers in the Developing World?” Policy Research Working Paper 9703, World Bank, Washington, DC. World Bank. 2021d. “The Labor Market and the COVID-19 Outbreak in Vietnam: Impacts and Responses.” World Bank, Washington, DC 40 A YEAR DEFERRED – EARLY EXPERIENCES AND LESSONS FROM COVID-19 IN VIETNAM Chapter 3. COPING: A RELIANCE ON SELF-INSURANCE AND PERSONAL NETWORKS During the COVID-19 (coronavirus) pandemic, households have primarily relied on self-coping strategies and support from personal networks. On the one hand, COVID-19 did not necessitate large financial interventions. On the other hand, the lack of utilization of formal channels to cope (financial institution and government support) may also reflect low levels of financial inclusion for certain vulnerable groups, as well as a social protection system that requires modernization and the limited nature of the fiscal response. The labor force is highly informal, and both household and firm COVID-19-related relief programs faced challenges with implementation. Businesses had access to more formal coping mechanisms, such as through additional financing, adoption of remote work arrangements or new technologies to reach customers. However, small and informal businesses still tend to be more constrained. Many lacked adequate access to formal finance, and a large share of businesses had to downsize operations. Chapter 3.  COPING: A RELIANCE ON SELF-INSURANCE AND PERSONAL NETWORKS 41 COPING STRATEGIES Coping strategies that households rely on during Poor and rich households relied on different coping crises or shocks range from self-coping, personal strategies. Poor households had to rely on external networks, or formal external channels. In the face sources, whereas rich households were better able of crisis, household coping strategies can be based on to cope within their own means. For example, poor their own means (assets and savings), or households households had to borrow and receive assistance from can change behaviors and reduce consumption. They family and friends. Richer households were able to rely can also try to engage in more economic activities to on savings. Rich households could also afford to reduce smooth income. They can turn to assistance outside consumption to a larger extent than poor households their networks of family and friends. In countries that are already closer to subsistence levels. In earlier with developed social response systems, financial studies on coping behavior during the global financial or government institutions can also be a more likely crisis (2007-9), poor households having lesser assets means of support. either employed no coping strategies, sought external financial assistance from family and friends, or sought During COVID-19, most households in Vietnam additional income-generating activities (Tran 2015). primarily relied on self-coping and family or friend Richer households were more able to tap into their own networks for support. Household resiliency is notable savings and assets in order to cope. These differences given the lack of widespread social relief measures, and in coping strategies across poor and rich households Vietnamese households were largely self-insuring and strongly resemble the coping strategies observed self-sufficient (figure 3.1). A few also chose to engage during COVID-19, even though the global financial crisis in additional economic activities, but this was about half occurred a decade earlier. as many as those who reported putting more efforts into their existing jobs. The most common household coping In contrast, the coping strategies used by and strategy by far was to simply reduce consumption. The available to formal firms were quite different. Firms second most common was to borrow from friends. Other might run down their cash reserves to weather the strategies were less commonly used: growing food, negative impacts, but this option was usually limited to relying on savings, getting loans from an institution, larger firms. Small and medium firms were less likely to or receiving assistance from family members. Formal have built up this cash stock. Formal firms could also channels of assistance from financial institutions or access formal credit or restructure their debt through government were least common. The perhaps surprising financial institutions and markets. Last, firms undertook low levels of reliance upon formal public support are changes internally to cope with the impacts by adjusting partly due to the good containment of COVID-19 early on, their labor mix (either temporarily through worker leave or and also due in part to the limited coverage and benefit reduced pay, or permanently through firing) and adopting levels of the fiscal response, due to issues in both design technology to reach customers and automate processes. and implementation discussed in chapter 4. 42 A YEAR DEFERRED – EARLY EXPERIENCES AND LESSONS FROM COVID-19 IN VIETNAM Figure 3.1 Vietnamese households were more likely to use informal and self-coping strategies Share of households adversely affected (%) 60 50 40 30 20 10 0 Grew food for self-consumption Relied on savings Reduced food consumption Reduced non-food consumption Returned home (migration) Received assistance from friends & family Borrowed from friends & family Sold harvest in advance Sale of assets Engaged in additional income generating activities Put more effort on current jobs Took a loan from a financial institution Credited purchases Delayed payment obligations Received assistance from NGO Received assistance from government Was covered by insurance policy Took advanced payment from employer Self Family and friends Economic Financial institutions Government Jun-July 2020 Jul-Aug 2020 Dec 2020 - Jan 2021 Feb 2021 Source: World Bank Vietnam COVID-19 monitoring surveys (rounds 2–5). Note: Coping questions were asked only of households reporting income loss or having experienced negative shocks within survey reference periods. NGO = nongovernmental organization. HOUSEHOLD SELF-INSURING AND BORROWING STRATEGIES Vietnamese households are resilient, independent, which reduces the serious implications of moderate and adaptable. Certain preexisting characteristics declines in income. High recurring monthly expenses helped households cope through bouts of declining such as housing rent, mortgages, car payments, or income. Vietnamese households have high savings debt payments are uncommon in Vietnamese society. rates, have strong family networks and support systems, Vietnam has one of the lowest shares of renters in the and are economically ambitious with households having region at 2.6 percent.20 Among homeowners, only 9.6 multiple income streams. A low cost of living also ensures percent have an outstanding housing loan.21 In contrast that essentials items are still affordable, and growing in developed countries, a missed wage payment could food for self-consumption was also common before lead to insolvency on debt payments or loss of assets. COVID-19 among poorer households. These conditions Accordingly, policy makers in developed countries provided households with some buffers during periods of responded by implementing rent moratoriums and debt lockdowns, which helped minimize risks of permanent falls postponement to prevent mass evictions and preserve into poverty. Vietnamese households are not indebted, income for essential purchases. Chapter 3.  COPING: A RELIANCE ON SELF-INSURANCE AND PERSONAL NETWORKS 43 Reducing consumption and Poorer households were less likely to be able to increasing self-consumption reduce food and nonfood consumption to cope (figure 3.2). Reducing food consumption can be regarded Reducing food and nonfood consumption was the as a coping strategy to save money, but it can also be most common coping strategy among adversely potentially harmful if consumption is reduced too much. affected households. On average, 56 and 54 percent Although the rate of consumption reduction is not largely of adversely affected households reduced food and different across welfare quintiles, there is more concern nonfood consumption, respectively, in July 2020. The for households at the lower end of the welfare distribution trends diverged over time. Fewer affected households not being able to eat enough. The poorest households reduced food consumption in later rounds, whereas perhaps did not need to reduce food consumption more households reduced nonfood consumption in later because they were growing food for self-consumption, rounds. The majority of affected households also report or because they were already consuming the minimum reducing both food and nonfood consumption at the same needed to survive. Adequate quality and diversified time. However, in the last round, there was a shift, with food consumption is still a concern among vulnerable a slightly higher share of households reporting reduced groups. In March 2021 (round 5), about a quarter of nonfood but not food consumption. This could be related households reported that in the last month there was to the timing of the survey over Tet holidays in February, at least one instance when they ate too few kinds of when families celebrate the new year and consume foods or were unable to eat healthy and nutritious foods disproportionately more than other times in the year. because of a lack of resources (see more in chapter 5). Adequate food was also a challenge for some households before COVID-19. At the end of 2019, 15.6 percent of households reported that the family had gone without enough food at least once in 2019.22 Figure 3.2 Wealthier Vietnamese households that experienced a shock or income decline were more able to afford to reduce food and nonfood consumption a. Reduced food consumption b. Reduced nonfood consumption 80 80 70 70 Share of households adversely Share of households adversely 60 60 50 50 affected (%) affected (%) 40 40 30 30 20 20 10 10 0 0 Feb-Jun 2020 Jun-Jul 2020 Jul-Aug 2020 Jan 2021 Feb 2021 Feb-Jun 2020 Jun-Jul 2020 Jul-Aug 2020 Jan 2021 Feb 2021 Dec 2020 - Dec 2020 - Bottom 20 Q2 Q3 Q4 Top 20 95% CI Source: World Bank Vietnam COVID-19 monitoring surveys (rounds 2–5). Note: Coping questions were asked only of households reporting income loss or having experienced negative shocks. The magnitude of the reductions is not recorded. Household (HH) quintiles (Q) are based on household consumption per capita in 2018. 44 A YEAR DEFERRED – EARLY EXPERIENCES AND LESSONS FROM COVID-19 IN VIETNAM Reductions in nonfood consumption can also be a households growing food to cope during COVID-19 was concern because some forms may potentially lead to not high, perhaps because it was already an existing a widening of nonmonetary inequality. When asked activity for most before the pandemic. Households, if households changed future plans, some deferred especially poorer ones, commonly produced homemade spending on education. This response was more likely for goods for self-consumption before COVID-19 and likely households at the lower ends of the welfare distribution. continued or increased home production during the Chapter 6 explores this finding in more detail. pandemic. Among the poorest deciles, a majority of households had homemade food or nonfood consumption Growing food for self-consumption in 2018 (figure 3.3). In the poorest decile, over 90 percent of households have a portion of food consumption that Growing food for self-consumption was a more is homemade, making up on average 36 percent of all common coping strategy for poor households. food consumption. Compared to other coping strategies, the rate of Figure 3.3 Poor Vietnamese households are more likely to consume homemade goods a. Household consuming homemade food or goods 100 Share of houlseholds (%) 80 60 40 20 0 Poorest 2 3 4 5 6 7 8 9 Top decile decile (1) (10) Homemade Food Homemade nonfood b. Household spending on homemade food and goods 100 Share of expenditure on homemade 80 food and goods (%) 60 40 20 0 Poorest 2 3 4 5 6 7 8 9 Top decile decile (1) (10) Food Nonfood Source: World Bank staff calculations using the 2018 Vietnam Household Living Standards Survey. Chapter 3.  COPING: A RELIANCE ON SELF-INSURANCE AND PERSONAL NETWORKS 45 In addition, the low cost of living in Vietnam benefited past coping studies in Vietnam. Poor households are also households. The costs for daily necessities such as food much less likely than richer ones to use formal savings. and petrol are relatively low and affordable compared to Sixty-six percent of households earning more than 10 costs in other countries. East Asia and Pacific (EAP) as a million Vietnamese dong (VND) per month have formal region tends to be cheaper than others in the same level savings channels, compared to less than 20 percent of development. According to price data collection from for households earning less than VND 1.3 million per the 2017 International Comparison Program, price levels month. Official deposits data also indicate that household in the EAP region are low, which means that prices to deposits growth over the medium term has been declining purchase a comparable basket of goods are lower in the (figure 3.5). This is important to point out because much EAP region than in other regions. Within EAP, Vietnam of the savings behavior data is from 2019 or earlier, and has the second-lowest price level. in 2020 savings deposits have declined considerably. Savings Borrowing Saving is an important form of self-insurance because Financial inclusion is low in Vietnam for certain it allows households to smooth consumption during vulnerable groups. In 2017, just over 26 percent income shocks. Vietnam has a higher rate of savings of adults in Vietnam had an account at a financial compared to averages among other EAP countries and institution. This rate increased to 42 percent by 2019 lower-middle-income countries. In Vietnam, 56.0 percent (figure 3.6), but there are still differences in access by of individuals (aged 15 years and older) reported saving socioeconomic groups. Less than 17 percent of people any money in 2017 compared to 53.1 percent in EAP, in poor households have an account, compared to 83 and 39.7 percent in lower-middle-income countries. A 23 percent of people in rich households (World Bank 2019).25 2019 financial inclusion survey in Vietnam finds that 60.1 Large differences in access also exist by education percent of Vietnamese adults saved (World Bank 2019). group, which is correlated to household wealth and Vietnamese save to buffer against shocks, in particular age cohort. Differences in the share of adults with illness; out-of-pocket health expenses in Vietnam are accounts are smaller across geographic regions than some of the highest in EAP (World Bank 2019). Other across wealth and education groups. This highlights common reasons cited for savings are preparing for old that financial inclusion is not necessarily due to limited age, education, investment in businesses, and purchases supply but to household-specific constraints to access of high-value assets in the future. that disproportionately affect the vulnerable. It is unclear, however, if household savings are Having large family networks has been shown to sufficient to be used for emergency funds. In 2017, provide financial resilience. Family members tend 70 percent of respondents (aged 15 and older) reported to be more altruistic toward each other, share common being able to come up with emergency funds, but only obligations, and have stronger contract enforcement 14 percent of this group reported savings to be the main (Cox and Fafchamps 2008; Hamilton 1964; La Ferrara source of emergency funds.24 The majority would have 2011). Half of households in the World Bank COVID-19 relied on money from working as a source of emergency monitoring surveys are engaged in family businesses with funds, which obviously would be less viable during an common incentives. Families are essential and core social economic crisis. units. Societal values in Vietnam revere the importance of family ties, roles, and responsibilities. Family units also During COVID-19, poor households were less likely have implications in administrative processes. The family than rich households to tap into savings (figure 3.4). registry book (a vestige of French colonial rule), passed Because poor households have less assets and savings, down for generations, is an essential for life events such this finding is not unexpected and is also consistent with as marriages, opening bank accounts, and so on. 46 A YEAR DEFERRED – EARLY EXPERIENCES AND LESSONS FROM COVID-19 IN VIETNAM Figure 3.4 Wealthier Vietnamese households are Figure 3.5 Vietnamese households are saving more able to rely on savings less than before 20 25 Growth in household deposits (%) Share of households adversely 20 15 affected (%) 15 10 10 5 5 0 0 April April April April April April Feb-Jun 2020 Jun-Jul 2020 Jul-Aug 2020 Jan 2021 Feb 2021 Dec 2020 - 2016 2017 2018 2019 2020 2021 Bottom 20 Q2 Q3 Q4 Top 20 95% CI Sources: World Bank Vietnam COVID-19 household monitoring Sources: World Bank database surveys (rounds 2–5) Note: Savings Deposits at Credit Institutions (end of period, not Note: Coping questions were asked only of howuseholds reporting seasonally adjusted, year-on-year % change) income loss or having experienced negative shocks. Figure 3.6 Indicators of financial access, Vietnam a. Borrowing from family and friends is the b. Use of financial services has improved on some most common source dimensions and less in others 80 50 70 42.3 Share of respondents (%) Share of respondents (%) 60.2 40 60 48.4 50 30 42.0 26.4 40 24.0 30 20 20 10 10 3.9 3.2 – 0 0 From a financial From family or From an informal Has an account Has a debit Has a credit institution friends savings club card card 2017 2017 2019 Source: Based on 2017 data from the Global Findex database and World Bank 2019. Notes: The Findex target population is the population of individuals aged 15 years and older. Chapter 3.  COPING: A RELIANCE ON SELF-INSURANCE AND PERSONAL NETWORKS 47 During COVID-19, relying on financial assistance from BUSINESS family and friends was the second most commonly reported coping strategy among those who reported ADJUSTMENT experiencing adverse shocks or reductions in STRATEGIES income. In developing countries, borrowing from family and friends is a common strategy in the presence of unexpected shocks (Demirguç-Kunt and Klapper 2013; Chapter 3 concludes by looking at the adjustment Pearlman 2010). In Vietnam during COVID-19, borrowing strategies different types of formal firms adopted on from friends and family was significantly more used by the their own. Firms can adjust and survive through both the poor (figure 3.7). The poor were also more likely to borrow actions they take to address the crisis and the support from an institution than to rely on personal savings. This they receive from the government. Chapter 4 will discuss trend is consistent with previous research that poor the fiscal support that different firms receive, and the households tend to rely on external sources, whereas greater utilization of that support by larger, formal firms rich households are better able to cope within their own compared to informal and small and medium enterprises. means. The percentage of adversely affected households The rest of this section summarizes the actions different that borrowed from a financial institution is much lower firms took themselves in reaction to economic pressures. than those that borrowed from personal networks. These financial institutions include State Policy Banks and farming cooperatives and other noncommercial banks, which do provide loans to agricultural and poor households. Figure 3.7 Types of borrowing by Vietnamese households during COVID-19 a. Took a loan from a financial institution b. Borrowed from family and friends 80 80 70 70 Share of households adversely Share of household adversely 60 60 50 50 affected (%) affected (%) 40 40 30 30 20 20 10 10 0 0 Feb-Jun 2020 Jun-Jul 2020 Jul-Aug 2020 Jan 2021 Feb 2021 Feb-Jun 2020 Jun-Jul 2020 Jul-Aug 2020 Jan 2021 Feb 2021 Dec 2020 - Dec 2020 - Bottom Q1 Q2 Q3 Q4 Top 20 95% CI Source: World Bank Vietnam COVID-19 household monitoring surveys (rounds 2–5). Note: Coping questions were asked only of households reporting income loss or having experienced negative shocks. 48 A YEAR DEFERRED – EARLY EXPERIENCES AND LESSONS FROM COVID-19 IN VIETNAM Employment adjustment In the second half of 2020 and in early 2021, mechanisms firms started to reduce their use of temporary employment coping mechanisms. Although some In order to cope with the negative impacts firms still responded to the negative COVID-19 impacts of COVID-19, formal firms turned to different by reducing the wages and hours of workers, fewer employment adjustment mechanisms to survive firms were granting leave of absence. There are also (figure 3.8). Businesses can choose to fire workers in encouraging signs of recovery among firms, which difficult times but will be reluctant to do so if they believe report hiring workers in September–October 2020 and the downturn is temporary because firing workers can January 2021. Firms are also becoming less likely to lay have long-term effects, requiring firms to find and train off workers in response to drops in sales (figure 3.10). new workers later. Instead, businesses may choose The relationship between worker layoffs and changes temporary adjustment mechanisms such as granting in firm sales is becoming weaker over the three survey workers leave of absence with or without pay, and rounds, which could be explained by two conjectures. reducing worker wages and hours. At the initial stage of Businesses may have adapted their processes to deal the pandemic in June 2020, about 20 percent of firms with contraction without layoffs, or businesses (especially chose to reduce the wages and hours of their workers. those that suffered a lot negatively) have already trimmed A smaller proportion of firms chose to grant leave of their labor forces to essential workers or the bare absence with or without pay. However, a sizeable minimum. Both explanations point toward a reduction of percentage of firms (15 percent) chose to fire workers worker layoffs in response to future sales drops, but it in June 2020, probably in response to the large negative does not preclude some failing businesses exiting the impacts from the April lockdown. Part-time workers form market, along with the jobs they provide. the group that is most vulnerable to layoffs. Firms with higher shares of part-time workers in the workforce are more likely to reduce their payroll (figure 3.9). Figure 3.8. Different employment adjustments by Figure 3.9. Part-time workers were the most firms in Vietnam likely to be laid off, Vietnam 25 10 Share of firms making employment 23 Change in employment (%) 20 20 0 adjustments (%) 15 15 14 12 12 12 −10 11 10 10 9 8 8 7 5 5 −20 5 3 3 2 0 −30 0 20 40 60 80 Hired workers Fired workers Granted leave of absence Reduced wages Reduced hours Granted leave of absence with pay Share of part-time workers (%) Jun 2020 Sept/Oct 2020 Jan 2021 Source: World Bank COVID-19 Business Pulse Surveys. Source: World Bank COVID-19 Business Pulse Surveys. Note: The figure captures a binned scatterplot. Chapter 3.  COPING: A RELIANCE ON SELF-INSURANCE AND PERSONAL NETWORKS 49 Figure 3.10 Firms in Vietnam are becoming Small firms are less likely to fire workers in order less likely to lay off workers in response to weather the pandemic. As discussed above, to drops in sales compared to medium and large firms, small firms show smaller changes in employment between June 2020 and January 2021. Indeed, small firms are more likely to use intensive margins of adjustments, such as reduction 0.5 in hours or wages, or granting leaves of absence, Likelihood of laying off workers compared to extensive margins of adjustments, such as 0.4 firing workers. In January 2021, 7 percent of small firms 0.3 fired workers compared to almost 15 percent of medium and large firms. Small firms may have less ability to fire 0.2 workers because it is costly to fire workers, who have tacit knowledge, during a downturn and then replace 0.1 them quickly when demand picks up, or because small firms may already have such a small staff they cannot 0 −10 −50 0 80 operate with less. As a result, small firms may choose Change in sales relative to last year (%) to adopt more intensive margins of adjustments such as reducing worker hours and wages, or granting leaves of absence (figure 3.11). June Sept/Oct January Source: World Bank COVID-19 Business Pulse Surveys. Note: Conditional on region, sector, and size fixed effects. Figure 3.11 Small firms are more likely to opt for adjustments along intensive margins a. Adjustments on extensive margin b. Adjustments on intensive margin Small 7 Small 13 Medium 13 Medium 18 Large 16 Large 14 0 5 10 15 20 0 5 10 15 20 Share of firms making adjustment in January 2021 (%) Share of firms making adjustment in January 2021 (%) Source: World Bank COVID-19 Business Pulse Surveys. Note: Extensive adjustments are defined as firing workers; intensive adjustments are defined as reduction in hours, wages, or granting leaves of absence. 50 A YEAR DEFERRED – EARLY EXPERIENCES AND LESSONS FROM COVID-19 IN VIETNAM Access to external financing firms expect to fall into arrears in the next six months, albeit at a slightly lower share than in January 2021. One Faced with closures and reduced sales, firms had reason may be that more firms are restructuring their liquidity issues especially at the early stages of the debts. The share of firms that already made adjustment pandemic, but the situation had recovered in January in credit or loans repayment terms increased from 11 2021. In June 2020, the median firm expected on average percent to 13 percent from September–October 2020 to about 9 weeks before they ran out of cash, with an January 2021 (figure 3.15). average firm facing 22 weeks (figure 3.12). The cash flow shortages did not improve in September–October Digital adjustments 2020. However, firms started to improve in January 2021, with the average time until the next cash flow shortage Firms have also turned toward digital technologies increasing more than 1.5 times to 36 weeks. Some as an alternative coping strategy. Firms in Vietnam firms were able to access external finances, and these had been steadily adopting digital technologies before firms have on average twice as much time before they the pandemic, but the social distancing measures and experience cash flow shortages (figure 3.13). lockdown from March 2020 and lingering negative impacts even in 2021 accelerated firms’ motivation to Restructuring debt adopt digital technologies. Firms digitized their business operations to make it possible to work remotely and A sizeable share of firms has fallen in arrears during virtually, and to reach their customers. Many firms made the pandemic, but the rates are declining. The share this change to their business operations in June 2020, of businesses having already fallen in arrears increased with almost 50 percent of firms reporting that they started from 17 percent in September–October 2020 to 24 using or increased their use of digital platforms, online percent in January 2021 (figure 3.14). Similar shares of social media, or specialized apps in response to the Figure 3.12 Vietnamese firms faced liquidity Figure 3.13 External finance can double the time issues in June and October 2020, but the before firms experience cash flow shortages situation improved in January 2021 60 80 Average time until cash flow Time until expected cash flow 52 70 50 shortage (weeks) 60 shortage (weeks) 39 40 36 50 30 40 25 22 22 30 20 12 20 36 10 9 25 10 0 0 Average Median Sept/Oct 2020 Jan 2021 Jun 2020 Sept/Oct 2020 Jan 2021 With access to external finance Without access to external finance Source: World Bank COVID-19 Business Pulse Surveys. Source: World Bank COVID-19 Business Pulse Surveys. Chapter 3.  COPING: A RELIANCE ON SELF-INSURANCE AND PERSONAL NETWORKS 51 COVID-19 outbreak (figure 3.16). More firms steadily platforms and social networks has increased from about increased their use over the next six months with 62 10–15 percent between 2014 and 2018, to 17 percent percent and 73 percent of firms doing so in September in 2019, and 22 percent in 2020 (figure 3.17). The trend 2020 and January 2021, respectively. A less common has increased in 2020 as more firms are receiving and strategy among firms was to invest in digital solutions or making orders through e-commerce platforms and repackage their product mix to respond to the pandemic. social networks. The most common method of sales At the start, only 5 percent of firms had invested in digital and purchases by firms is through email, with over 80 solutions in June 2020, increasing to 20 percent of firms percent of firms in the Vietnam E-commerce Association in January 2021. The slower increase of investments in E-business Index receiving and making orders through digital solutions may be explained by the costs in terms this medium. This share has been steady over the last of time, human resources, and changes to business five years. Similarly, the share of firms using websites to operations required by firms. Firms may not have been receive and make orders has been about 40 percent in willing to invest such costs at the start of the pandemic, the last three years. However, there has been a steady thinking that the negative impacts would be short- rise in the share of firms using e-commerce platforms and term and temporary, but they began investing in digital social network to reach their customers and suppliers solutions as the pandemic continued into 2021. (figure 3.18). The share of firms receiving orders from e-commerce platforms and social networks increased by COVID-19 has accelerated the existing trends of about 15 percentage points between 2018 and 2020, with firms’ adoption of digital technology. There has 10 percentage points of that increase coming in 2020. been a marked increase in firms selling on e-commerce There was also a similar percentage increase in the share platforms over the last eight years, and firms have been of firms making orders on e-commerce platforms and moving from websites to e-commerce platforms and social networks between 2018 and 2020. social media. The share of firms selling on e-commerce Figure 3.14 Many Vietnamese firms have already Figure 3.15 Increasing shares of fallen into arrears or expected to do so in the Vietnamese firms are restructuring next six months their debt 60 56 15 Share of firms adjusting credit or loan Share of firms that risk falling in 52 13 arrears in next 6 months (%) repayments terms/schedule (%) 50 12 11 40 9 30 26 24 24 6 20 17 3 10 0 0 Yes, already Yes, will fall No Sept/Oct 2020 Jan 2021 in arrears Sept/Oct 2020 Jan 2021 Source: World Bank COVID-19 Business Pulse Surveys. Source: World Bank COVID-19 Business Pulse Surveys. 52 A YEAR DEFERRED – EARLY EXPERIENCES AND LESSONS FROM COVID-19 IN VIETNAM Figure 3.16 Many Vietnamese firms started Figure 3.17 More Vietnamese firms are selling on or increased their use of digital platforms e-commerce platforms and social networks during the pandemic 80 25 73 Share of firms using adjustment 70 62 20 60 Share of firms (%) mechanisms (%) 50 48 15 40 10 30 21 21 20 12 13 5 10 5 7 0 0 2014 2015 2016 2017 2018 2019 2020 Increased Investment Repackage use of digital in digital product mix platforms solutions Jun 2020 Sept/Oct 2020 Jan 2021 Source: World Bank COVID-19 Business Pulse Surveys. Source: E-business Index, Vietnam E-commerce Association. Figure 3.18 More Vietnamese firms are receiving The use of digital platforms has resulted in more and making orders on e-commerce platforms and e-commerce sales among firms, but this increase social networks may represent substitution from traditional sales methods rather than an increase in total sales. The 80 use of digital platforms is associated with higher share 70 of e-commerce sales in January 2021 (figure 3.19). 63 61 There is about 5 percent increase in the e-commerce 60 Share of firms (%) 49 sales after firms started using or increased their use of 50 45 44 40 digital platforms. This effect is statistically significant 40 36 37 and conditional on other firm characteristics. The use of 30 31 29 digital platforms did not affect overall sales or cash flows, 20 19 however, suggesting that, although firms reached more 10 13 customers online, these online customers substituted 0 for the decrease in customers through traditional sales 2018 2019 2020 methods. There is also a positive relationship between the use of digital platforms and the expansion of businesses. Website - sales Website - purchase The use of digital platforms is associated with an 8.5 Ecommerce - sales Social network - sales Ecommerce - purchase Social network - purchase percent increase in the probability of hiring, and it is not significantly correlated with layoffs. Source: E-business Index, Vietnam E-commerce Association. Chapter 3.  COPING: A RELIANCE ON SELF-INSURANCE AND PERSONAL NETWORKS 53 Figure 3.19 Digital platforms increased e-commerce sales, but not overall sales Effect of adopting digital platforms on firm performance during January 2021 15 10 Share of firms (%) 5 0 −5 % E-commerce sales Avg. change in sales Probability of hiring Probability of laying off workers Avg. days until cash flow shortage Source: World Bank COVID-19 Business Pulse Surveys. Note: Coefficient estimates from regressing firm outcome on digital adoption, controlling for size, region, and sector fixed effects.” 54 A YEAR DEFERRED – EARLY EXPERIENCES AND LESSONS FROM COVID-19 IN VIETNAM Notes 20  East Asia and Pacific Team for Statistical Development household surveys circa 2010–15. See appendix H for figure. 21  Based on dxata from the Global Findex database. 22  According to data from the World Values Survey. 23  Global Findex database. 24  Global Findex database. 25  In World Bank (2019), poor is defined as income of less than or equal to VND 900,000 per month, and rich is defined as income of less than or equal to VND 10 million per month. References Cox D., and M. Fafchamps. 2008. “Extended Family and Kinship Networks: Economics Insights and Evolutionary Direction.” In Handbook of Development Economics, Vol. 4, edited by T. P. Schultz and J. Strauss. 3711–84. Amsterdam: Elsevier. Demirguç-Kunt, Asli, and Leora Klapper. 2013. “Measuring Financial Inclusion: Explaining Variation in Use of Financial Services across and within Countries.” Brookings Papers on Economic Activity 2013: 279–340. Hamilton, W. 1964. “The Genetical Evolution of Social Behaviour I.” Journal of Theoretical Biology 7: 1–16. La Ferrara, E. 2011. “Family and Kinship Ties in Development: An Economist’s Perspective.” In Culture, Institutions and Development: New Insights into an Old Debate, edited by J. P. Platteau and R. Peccoud. New York: Routledge. Pearlman, S. 2010. Flexibility matters: Do more rigid loan contracts reduce demand for microfinance? CFA Working Paper No. 2010/10. Tran, Van Q. 2015 “Households’ Coping Strategies and Recoveries from Shocks in Vietnam.” Quarterly Review of Economics and Finance 56 (May): 15–29. World Bank. 2019. “Survey Report. Financial Access of Individuals in Vietnam.” World Bank, Washington, DC. A YEAR DEFERRED – EARLY EXPERIENCES AND LESSONS FROM COVID-19 IN VIETNAM 55 Chapter 4. POLICIES: A CALL TO STRENGTHEN AMID HEIGHTENING RISKS Arguably no country in the world proactively managed challenges in 2020 better than Vietnam, but heightening risks from rising COVID-19 (coronavirus) cases in 2021 call for stronger actions. Reflecting on the impacts and disruptions felt by households and firms from a year of relatively milder shocks in 2020 and early 2021 is important as risks and uncertainty increase. How much did policies affect households? This chapter reviews a set of policies that directly affected households in the space of health and fiscal responses. The health response to contain COVID-19 was stringent but tremendously successful, which allowed the economy to function in a closed setting but still relatively normally. However, each successive outbreak has been larger than the last, and Vietnam is behind on vaccinations. The government made plans to disburse cash support to existing and new target groups. Although the impact of the crisis was small, the intended support faced implementation challenges that motivate modernization of the social protection system to have more effective impact to mitigate future shocks. 56 A YEAR DEFERRED – EARLY EXPERIENCES AND LESSONS FROM COVID-19 IN VIETNAM THE HEALTH RESPONSE: START AND FINISH STRONG Vietnam led early with a strong and successful pandemic Effective management at the start response, but amid rising risks will it finish strong as well? Over the course of the first year of the pandemic, Vietnam Vietnam took early and strong measures against led the world with some of the fewest cases and deaths COVID-19 compared to other countries. International related to COVID-19. As other countries were locked borders were closed on March 25, 2020, and the down, Vietnam remained open domestically and enjoyed country entered a nationwide lockdown in early April for positive economic growth. However, new outbreaks are one month. Early actions are notable for preventing a emerging that are larger and more widespread. These surge in COVID-19 cases and minimizing transmissions. risks challenge Vietnam ability to adequately guard the Throughout the early phases of pandemic, Vietnam led country through existing strategies. As the developed the region and world with some of lowest case counts and world is accelerating on vaccinations, and reopening, deaths (figure 4.1). However, cases and deaths are rising Vietnam is now falling behind. Under strong government dramatically with latest outbreak in April 2021. commitment and leadership, Vietnam can stay the course and continue its success but will need to move substantially faster on rolling out vaccinations, testing, and timely monitoring. Figure 4.1 Vietnam led the Southeast Asia region early on with the lowest numbers of COVID-19 cases and deaths 2021 January February March April May June July Total cases per million 30K 20K 10K 0K 6 New deaths per million Vietnam 4 2 0 IDN KHM LAO MMR MYS PHL THA VNM Source: Mathieu et al. 2021, August 5, 2021 update. Chapter 4.  POLICIES: A CALL TO STRENGTHEN AMID HEIGHTENING RISKS 57 Vietnam had a strong public health campaign related Many of the health strategies adopted to quickly to COVID-19 risks and management. There was an identify cases were effective and strict. Domestic abundance of public service messages about safety, health response included instances of lockdown of social distancing, and healthy practices broadcast residential buildings, notification, road blockages, through the news and text messages. The public was isolation of entire provinces, and large fines for those asked to follow the 5 Ks: Khau trang (face mask), khu not wearing masks in public or failing to report that they khuan (hand sanitation), Khoang cach (social distancing), had been in outbreak areas. Compliance with these khong tu tap (no gatherings), and khai bao y te (medical containment efforts was generally good, with occasional declaration). The media campaign was taken one step violations clearly publicized and prosecuted by law. further. In February 2020, the Ministry of Health released a song and dance named “Ghen Co Vy,” composed by The public highly supported the pandemic popular Vietnamese musicians, to remind citizens of management response by the government, reflecting practices of handwashing and face covering. This song trust in government decision-making. Perceptions of quickly reached international popularity. During the height the government health response strategy remained high of the first lockdown in April 2020, the Ministry of Health throughout various outbreaks (figure 4.2). Most domestic sent notifications several times a day through mobile and foreign firms are willing to repeat the same lockdown providers reminding residents of COVID-19 precautions. process in the event of further outbreaks, despite the negative effects they felt from such restrictions (Malesky 2021). Over 80 percent of firms would agree with the government’s resuming strict social isolation and measures even if the probability of an outbreak was low at 25 percent. Figure 4.2 Near unanimous approval of government response in Vietnam 100 Share of HHs satisfied with government coronavirus management response (%) 80 60 40 20 0 March/April 2020 lockdown Da Nang (July 2020) Hai Duong (January 2021) Bottom 20 Q2 Q3 Q4 Top 20 95% CI Source: World Bank COVID-19 household monitoring surveys (round 3, round 5). Note: Household (HH) quintiles (Q) are based on household consumption per capita in 2018.Perceptions on March/April and Da Nang outbreak management were asked in round 3. Perceptions on the Hai Duong outbreak management were asked in round 5. 58 A YEAR DEFERRED – EARLY EXPERIENCES AND LESSONS FROM COVID-19 IN VIETNAM Over time, with each successive outbreak, was removed as a quarantine location option, and all containment measures became more localized travelers regardless of status were required to isolate at and targeted as the government became more designated sites. During the beginning of the fourth wave, experienced in identifying cases and containing the quarantine periods were temporarily extended to three spread. Even though some later outbreaks were larger weeks at a quarantine facility plus an additional week of with more COVID-19 cases, experience from earlier home isolation.26 With exposure to new variants, there containment efforts allowed the government to contain was also consideration of separate quarantine areas for in a more targeted manner that led to less disruption in those arriving from high-risk countries. Illegal immigration movement and business activity. and those entering Vietnam providing false credentials as experts also became an issue. In late May and early With borders closed to tourists, other international June 2021, international airports were briefly closed to travelers became the primary risk channel for in-bound flights. COVID-19 transmission. Since March 2020, only a small set of groups including repatriations, international By the second quarter of 2021, the government also experts, business leaders, and diplomats has been expressed concern about compliance with COVID-19 allowed to enter Vietnam under strict protocols. The precautions and public complacency. In July 2021, entry process remained strict throughout the year, mask use in Vietnam was 75 percent, compared to with high penalties for those who deviated from policy. still nearly universal levels in the Republic of Korea, Restrictions to in-bound travelers became stricter as time Singapore, and Japan. Other neighboring developing passed but COVID-19 cases still managed to leak into countries had similar or higher mask use rates (figure 4.3). the community. In early January 2021, home quarantine Figure 4.3 Mask wearing in Vietnam eased after the first outbreak in April 2020 100 Make use on July 1, 2021 (%) 80 60 40 20 0 Vietnam Indonesia Malaysia Philippines Singapore Japan Republic of Korea Source: Institute for Health Metrics and Evaluation, https://covid19.healthdata.org/. Chapter 4.  POLICIES: A CALL TO STRENGTHEN AMID HEIGHTENING RISKS 59 An important aspect of Vietnam’s health response Stringency index for Vietnam was at its highest value was social distancing and managing movement. in April 2020 during the nationwide lockdown. Because Using a more targeted prevention policy approach, case counts were much higher in other Southeast Asian Vietnam’s overall stringency was not necessarily higher countries, policies in Vietnam were relatively more relaxed than other countries in the region. Vietnam had either the when observed over the entire pandemic period. See box highest or second-highest stringency in about 100 out of 4.1 for data insights using mobile phone mobility data. over 400 days since March 2020 (figure 4.4). The Oxford Figure 4.4 Oxford Stringency Index trends in Southeast Asia 100 80 Stringency Index 60 40 20 0 January February March April May June July August January February March April May September October November December 2020 2021 IDN KHM LAO MMR MYS PHL THA VNM Source: Mathieu et al. 2021, May 18, 2021, update. 60 A YEAR DEFERRED – EARLY EXPERIENCES AND LESSONS FROM COVID-19 IN VIETNAM Box 4.1 Insights from mobility and movement data Information from third-party mobility data can be used in a more informative way to monitor movement during COVID-19.a Mobility data from various third-party sources are strongly correlated with periods of lockdowns and outbreaks. Both Google and Facebook data sources rely on location-activated smartphones to track movement. Google data measure the number of visits to tagged locations by categories. Facebook provides a wider range of mobility metrics, such as movement from one location to another, or indicators on staying in place. It is very likely that these data are informative at the least and somewhat representative of the full population, given that ownership of smartphones is virtually universal at the household level and Facebook usage is also high (over 68 million estimated users in 2020). These trends can inform on movement patterns in relation to trends in COVID-19 case counts. At a national level, Google and Facebook mobility data accurately reflect expected changes in movement associated with lockdowns or other large events. For example, Google mobility trends data show a strong decline in overall movement during the national lockdown in April 2020, and workplace visits during the Tet holiday in February 2021 (figure B4.1.1). Movement trends are seen to decline sharply across all provinces, indicating that even among poor or remote provinces, there is coverage from Facebook and Google data. Figure B4.1.1 Google Mobility Trends, Vietnam 40 7-day rolling average change 20 from baseline (%) 0 −20 −40 −60 0 March April May June July August February March April May September October November December January 2020 2021 Grocery and Pharmacy (rebase) Parks (rebase) Retail and Recreation (rebase) Transit (rebase) Workplace (rebase) Source: World Bank staff calculations using Google Mobility data, download June 8, 2021. Note: Rebased to March 2020. Chapter 4.  POLICIES: A CALL TO STRENGTHEN AMID HEIGHTENING RISKS 61 Box 4.1 - continued Google Mobility Data Beyond national trends, more interesting correlations between localized movement and cases can be derived. For example, the impact of the pandemic and lockdowns is likely very different across regions. Starting in early March 2020, the changes in the number of visits to workplace locations compared to the baseline was similar across the 53 provinces in Vietnam (figure B4.1.2). The standard deviation in workplace visits across provinces increased from less than 5 points before the nationwide lockdown in April 2020 to over 10 points after the Da Nang outbreak in fall of 2020. After Tet in February 2021, large cities (Can Tho, Da Nang, Ha Noi, Ho Chi Minh City) were more likely to rebound with the highest workplace visits relative to the baseline in March 2020. The prolonged pandemic may be hurting provinces without large economic centers of activity. Figure B4.1.2 Google Mobility, workplace visit trends Workplaces (7-day moving average) 40 20 0 −20 −40 −60 −80 March April May June July August January February March April May September October November December 2020 2021 Standard deviation 10 5 0 Source: World Bank staff calculations using Google Mobility data, download June 8, 2021. Note: Rebased to March 2020. Top panel shows trends for each province. Bottom panel shows the standard deviation in workplace visits per day across all provinces. 62 A YEAR DEFERRED – EARLY EXPERIENCES AND LESSONS FROM COVID-19 IN VIETNAM Box 4.1 - continued Facebook Movement Data Despite many caveats to the data, big data are at a minimum useful to monitor changes in activity across regions, and potentially also predictive. Facebook Mobility Movement Datab can illustrate the correlation between the degree of movement in areas and be compared to timing of outbreaks. As illustrated in figure B4.1.3 for the eight municipalities/provinces with the highest case numbers, we see variation both in how quickly and for how long movement in provinces is affected (illustrated by the mobility data) and, where possible, whether future outbreaks occur. In the case of the recent outbreaks in the Northern, more industrialized (a) Bac Giang and (b) Bac Ninh, we see a 30 percent increase in the percentage of users staying home as soon as the first cases were detected. By contrast, in (c) Hai Duong, we see that people started staying put after case numbers had become high in March 2021. Despite the delay in staying put, cases in Hai Duong quickly stabilized. Outbreaks in the more services-based cities (Da Nang, Hanoi, and Ho Chi Minh City) have been characterized by much smaller and more contained outbreaks relative to cases (a)–(c). These municipalities have also responded rapidly to each wave, with a large jump (20–30 percent) in the share of Facebook users staying put as cases are detected. Notably, however, the most recent outbreak in Ha Noi appears to be different. Despite far higher case numbers in 2021 compared to 2020, the share of Facebook users staying home has increased by a smaller rate, 15 percent. Although part of this is explained by more localized lockdowns in 2021 than the more expansive and stringent lockdowns in 2020, it may also be indicative of what is being called “lockdown fatigue” or “adherence fatigue” and can be instrumental in informing future policy. Google data also confirm that users are staying home in residential locations to a lower degree compared to the baseline in March 2020. Lastly, two provinces with smaller outbreaks but unique mobility trajectories are pictured in cases (g) and (h). Perhaps most striking, on the South Coast in Khanh Hoa and Ba Ria–Vung Tau, there are prolonged increases in case numbers without corresponding increases in the percentage of Facebook users staying put. These areas can become hotbeds for future outbreaks and may warrant more proactive measures, such as increased testing, lockdowns, or vaccination programs. Chapter 4.  POLICIES: A CALL TO STRENGTHEN AMID HEIGHTENING RISKS 63 Box 4.1 - continued Figure B4.1.3 Comparing Facebook Mobility data by province and case counts a) BAG GIANG a) BAG GIANG 60 1000 50 40 500 20 0 0 Agriculture Industry Services b) BAC NINH b) BAC NINH 60 50 40 200 20 0 0 Agriculture Industry Services c) HAI DUONG c) HAI DUONG 60 50 Percentage of Facebook users ‘Staying Put’ (staying in a single 600m2 Bing tile all) 40 100 20 0 0 Agriculture Industry Services d) HA NOI d) HA NOI 60 50 100 Provincial structure of GDP (% breakdown) 40 50 20 0 0 Agriculture Industry Services e) HO CHI MINH e) HO CHI MINH 60 200 50 40 100 20 0 0 Agriculture Industry Services f) DA NANG f) DA NANG 60 50 40 100 20 0 0 Agriculture Industry Services g) KAHNH HOA g) KAHNH HOA 60 20 50 40 10 20 0 0 Agriculture Industry Services h) BA RIA - VUNG TAU h) BA RIA - VUNG TAU 60 50 40 10 20 0 0 2020–07 2020–09 2020–11 2021–01 2021–03 2021–05 Agriculture Industry Services Source: World Bank staff calculations using Facebook Mobility Data. Note: Left panel: Changes in the number of Facebook users “Staying Put” (green lines), plotted against the 10 provinces and centrally controlled municipalities with the largest outbreaks in Vietnam (pink bars). Right panel: For each province, the percentage structure of provincial GDP is also provided. As illustrated, the largest and latest three outbreaks, (a) Bac Giang, (b) Bac Ninh, and (c) Hai Duong, all appear to be highly industrialized. This is relative to initial outbreaks from 2020, which were concentrated in the highly populous and more services-based cities of (d) Ha Noi, (e) Ho Chi Minh City, and (f) Da Nang. a. Original Google Mobility trends are benchmarked to the median day-of-the-week value from the five-week period in January. Some persistent depression in mobility could be explained by the absence of international travelers. If the baseline is moved to March when international flights began to be suspended, we see patterns that may more accurately describe the internal movement of citizens, and a rather contained population, with minimum entry and exit, which thus more accurately represents movement of the Vietnamese people. International flights were cancelled on March 25, 2020, and the country entered a nationwide lockdown in April. Early March is likely the most representative. b. Facebook data come with varying levels of granularity and spatial aggregation. In this report we use Movement Range Maps, which provide two indicators of movement at district/city level: (1) staying put, the number of people staying in a single 600m x 600m Bing tile all day, and (2) change in movement, the percentage change in total tiles visited on a given day. 64 A YEAR DEFERRED – EARLY EXPERIENCES AND LESSONS FROM COVID-19 IN VIETNAM Stepping up to tackle higher risks before the fourth wave. However, that may change given that the fourth wave has resulted in hospitals being Uncertainty looms regarding the duration of the cluster cases themselves, and that the number of cases pandemic and potential episodes of new outbreaks. is spreading and will stretch medical capacity. In 2020, Vietnam experienced only one national lockdown, and several severe localized lockdowns. The high transmissibility of the new outbreak is The outbreak in Da Nang in late July 2020, and another concerning because Vietnam faces higher risks significant outbreak right before the Tet holidays in 2021, from a lagging vaccine rollout. Vietnam started to showed that reoccurrences of the pandemic are hard to commit government funding to vaccine purchases only predict or prevent entirely. In late April 2021, Vietnam very late, in May 2021. In other words, Vietnam made its experienced its largest outbreak since March 2020. The biggest vaccine orders at a time when vaccine supply new outbreak led to the first domestic COVID-19 death issues were already widespread around the world. So far, since September 2020. In a span of one month, Vietnam Vietnam has received only about 8 million doses. In mid- recorded over 3,000 cases, as many as it had over the July 2021, Vietnam had vaccinated about 4 percent of the entire previous year. population, but less than 1 percent are fully vaccinated, a low rate compared to nearly 25 percent of the population Access to health services was not an issue early of Cambodia being fully vaccinated (figure 4.5). The rate on but may become one now. Previous rounds of of fully vaccinated people in Vietnam is also the lowest monitoring surveys did not find any disruption to health in developing Southeast Asia. facilities as is expected given the low volume of cases Figure 4.5 COVID-19 vaccination trends in Southeast Asia 2021 40 People vaccinated per hundred 20 0 30 People fully vaccinated per hundred 20 10 0 January February March April May June July IDN KHM LAO MMR MYS PHL THA VNM Source: Mathieu et al. 2021, August 5, 2021 update. Chapter 4.  POLICIES: A CALL TO STRENGTHEN AMID HEIGHTENING RISKS 65 Most of Vietnam’s population would agree to be In January and March 2021, survey respondents vaccinated. Surveys suggest that most of the population chose health workers, children, and senior citizens would agree to be vaccinated if the vaccine came at no to be prioritized to receive the vaccine (figure 4.6). cost, but a slightly lower percentage would agree if it Respondents were asked to identify, without prompting, came with a cost. In March 2021, a small sample was priority groups that should receive the vaccine first. asked if they would take the vaccine at cost or no cost, Seniors and children were top choices, followed by health and households in the bottom 40 percent of the income care workers and medical professionals. Almost half of distribution were more likely to report they would take respondents identified senior citizens as a vaccination the vaccine at no cost but not at cost.27 It is important priority group. Older respondents were more likely to to ensure equitable access to vaccines, because fewer identify government workers as priority groups. Younger among the poorest households would agree to take the respondents were more likely to select children and vaccine if it was offered at cost versus no cost and it is pregnant women as priority groups. The selection also less affordable. Among those who do not agree to of young children, who are less likely to contract the receiving a vaccine, they either worry about the safety disease or suffer serious illness and for whom the of the vaccine or deem it unnecessary under current vaccine has not yet been approved, suggests the need conditions. Data collection was conducted before the for revisions to the public communications strategy as the fourth wave, and perceptions about and willingness to vaccine is rolled out. take vaccinations are very likely to have altered. Figure 4.6 Health workers, children, and senior citizens are most often chosen as vaccination priority groups among survey respondents in Vietnam People who are COVID-19 positive People living and working in crowded spaces People who travel and meet other people frequently People suspected of having COVID-19 identified by the authorities Middle-age (40-60) Young people (16-30) Pupils, students Women People with disabilities Priority group People contributed to the Revolution The vaccine should be offered on a first-come first-serve basis Poor Public transport workers Elected national and local government officials Domestic or international travelers Young working adults (20-40) Senior citizens Patients of long-term/chronic diseases Children Military, police Health workers & medical professionals 0 10 20 30 40 50 60 Share selecting each priority group (%) 95% CI Source: World Bank Vietnam COVID-19 household surveys (round 4). Note: This question was asked in an open-ended manner and unprompted. Responses were post-coded into the categories shown. Multiple selections are allowed per respondent. 66 A YEAR DEFERRED – EARLY EXPERIENCES AND LESSONS FROM COVID-19 IN VIETNAM The government is speeding up vaccination (as of June 8, 2021, with contributions increasing daily). procurement and should ensure equitable access and Despite these last-minute efforts, the delay in purchasing distribution. The Prime Minister signed and promulgated vaccines and the current global issues in vaccine supply Resolution No.09/NQ-CP dated May 18, 2021, on the mean that Vietnam is expected to receive the bulk of its purchase of COVID-19 vaccines. In the resolution, the purchased doses no earlier than Q4 2021 and Q1 2022. government assigned the Ministry of Health to urgently organize the purchase of vaccines as quickly as possible Testing should be made more commonplace. With so that vaccines can be widely distributed to the people. only 0.7 test per thousand people, Vietnam testing At the time of writing this report, the government target is rate remains on the low side, compared to some other to secure 150 million doses to vaccinate 70 percent of the neighboring Southeast region countries (figure 4.7). This population by the end of the first quarter in 2022, which is despite a huge ramping-up effort accomplished in a is expected to cost 25.2 trillion Vietnamese dong (about record time: since May 2021, the country has tripled its US$1 billion). In late May, the government established testing rate and doubled its capacity. Additional efforts are a COVID-19 vaccination fund to mobilize all resources, possible (especially for introducing antigenic tests more including the government budget at both central and widely), but further investments are mostly constrained local levels, individual contributions, or donations. Within by procurement bottlenecks (like for vaccines). weeks, contributions amounted to over US$181 million Figure 4.7 Vietnam has one of the lowest testing rates in the region 2021 Total tests per thousand 400 population 200 0 January February March April May June July IDN KHM LAO MMR MYS PHL THA VNM Source: Mathieu et al. 2021, August 5, 2021, update. Chapter 4.  POLICIES: A CALL TO STRENGTHEN AMID HEIGHTENING RISKS 67 THE RELIEF RESPONSE: LEARNING FROM EXPERIENCE The nationwide COVID-19 relief rollout for households of social assistance measures in April was later than lasted for a short duration (April–July 2020) and was in Indonesia, Malaysia, Mongolia, the Philippines, and smaller than originally planned. Arguably, the impacts Thailand, which announced responses in the second half of COVID-19 were mild and perhaps relief was not as of March. Unlike in Vietnam, many countries in the region urgently needed as originally envisioned. Yet the gap including Cambodia, Indonesia, Malaysia, Mongolia, between income losses and the support received by the Philippines, and Thailand have also extended cash households was proportionally larger than in all other transfers into 2021. Vietnam’s measures lasted only countries in the East Asia and Pacific region, except between April and June of 2020. for the Philippines where households experienced very high losses. The relief rollout to new target groups faced Existing beneficiaries in the social protection system implementation challenges that foreshadow longer-term received top-ups to their regular benefits. It is reported challenges and motivate modernization of the social that all beneficiaries who were already enrolled in an protection system. Formal firms were offered different income support scheme received a top-up in addition to types of relief, primarily in the form of deferrals, and their standard benefits. The implementation of COVID-19 rollouts lasted longer, but these programs faced similar cash support to existing beneficiaries went smoothly implementation challenges as the household relief because it was universally applied, and disbursement packages. The emergence of a fourth COVID-19 outbreak channels were already in place. There were no conditions in May 2021 led to the largest outbreak in the country that beneficiaries be affected by COVID-19. yet. Thus, there is still a chance to learn from previous implementation challenges of COVID-19 responses to The government also identified new target groups potentially improve future packages and build resilience that were adversely affected by COVID-19, but the for future systemic shocks. expansion of coverage was less than in other East Asia and Pacific countries. Additional categories Strong early planning to assist of households not already registered in the social households, but rollouts faced protection system were identified that were eligible to implementation challenges receive payments including informal and contracted workers (“the new target groups”). However, definitions In early 2020, the government responded swiftly, of new target groups as defined by the central policy passing multiple resolutions to support people facing did not include everyone that may have been adversely difficulties caused by the COVID-19 pandemic. A affected by COVID-19. Some groups that did not fit national decree set in April 2020 outlined a relief plan into the targeted beneficiary groups include employees that would assist existing beneficiary groups, as well as not receiving salary from the state budget in public groups newly affected by COVID-19. See box 4.2 for a education institutions, small household businesses selling list of national policies to respond to the pandemic. nonessential items (clothes, shoes), mechanics, builders, tailors, porters in factories, self-employed workers in Vietnam’s assistance was announced later than that household businesses, and workers in agriculture. in other countries in the region and had a shorter duration. Vietnam’s expansion of social assistance in The original target number of new beneficiaries was response to the COVID-19 outbreak was in line with the 5 million workers, but the relief as implemented introduction of new and/or expanded programs in most reached fewer beneficiaries. Because of the strict countries in the region. However, the announcement criteria and the lack of data on informal sector workers 68 A YEAR DEFERRED – EARLY EXPERIENCES AND LESSONS FROM COVID-19 IN VIETNAM that could be verified or cross-checked against social The main new beneficiary group targeted for insurance or other databases, the program was smaller in COVID-19 relief was informal workers. Informality scale than originally proposed. By the end of March 2021, is extremely prevalent: 21 million or 81 percent of all about 1 million informal workers were reached (table 4.1). households have at least one household member who The share of the population added as new beneficiaries either has a wage job without a contract, is engaged in was only 1 percent, which is lower than all other countries self-employed agriculture, or is engaged in self-employed in East Asia and Pacific that added new beneficiaries. business. Given the reported implementation figures, the COVID-19 relief aid to informal workers did not There are two observations on beneficiary targeting reach all of the potential recipients in this group. Actual worth noting related to the distribution of existing disbursements also showed that few households received target groups (poor and social assistance recipients) income support for informal workers, at only 20 percent and new target groups (informal workers) (figure of planned recipients. 4.8). The existing vulnerable population is those already receiving income support under poor, near- The benefit amount provided through the relief poor, social assistance, or merit (National Devotee) package was small on a per household basis. The programs. These groups by default received top-ups to national-level package was announced in late April 2020 their existing benefits. Households classified as poor in and implemented from May to July 2020. The duration of their communes and receiving social assistance before benefits was for a maximum of three months. In the most COVID-19 represent most but not all of the poor. The generous case scenario, National Devotees received groups of National Devotees are people receiving other about VND 1.5 million over three months. In comparison, social protection benefits and are categorical target minimum monthly wages are about VND 4 million per groups not related to poverty targeting and alleviation. month. Results from chapter 5 of this report will also illustrate the minimal welfare-improving impacts of the COVID-19 relief implementation. Box 4.2 National COVID-19 relief policies for workers and households in Vietnam The following is a list of national policies that were put in place in Vietnam to respond to COVID-19 in April 2020, and their subsequent amendments. Some local governments also passed resolutions to support households in their jurisdictions. • Resolution 42/NQ-CP dated April 9, 2020, of the government on measures to support people facing difficulties caused by the COVID-19 pandemic • Decision 15/2020/QD-TTg dated April 24, 2020, of the prime minister on regulating the implementation of policies to support people facing difficulties caused by the COVID-19 pandemic • Resolution 154/NQ-CP dated October 19, 2020 of the government on amending and supplementing the Resolution 42/NQ-CP dated April 9, 2020 of the government on measures to support people facing difficulties caused by the COVID-19 pandemic • Decision 32/2020/ NQ-CP dated October 19, 2020, of the prime minister on amending and supplementing a number of articles of the Decision 15/2020/QD-TTg dated April 24, 2020, of the prime minister on regulating the implementation of policies to support people facing difficulties caused by the COVID-19 pandemic Chapter 4.  POLICIES: A CALL TO STRENGTHEN AMID HEIGHTENING RISKS 69 Table 4.1 Vietnam’s household COVID-19 relief, planned vs. implementation NATIONAL Estimated Implementation (3 months maximum) Cost (billion, Cost (billion No. of Amount/ No. of Spending Vietnamese Vietnamese people month person per person dong) dong) Income support to existing target groups Poor and near-poor households 9,200,000 250,000 6,900 7,001,991 5,374.15 767,517 SA beneficiaries 3,000,000 500,000 4,500 2,839,544 4,227.65 1,488,849 Merit people (National Devotees) 1,135,000 500,000 1,703 991,907 1,483.05 1,495,154 Income support to new target groups Contracted employees on 1,000,000 1,800,000 5,400 139,180 141.76 1,018,508 temporary unpaid leave at least for one month, or not qualified for UI benefit Informal sector employees being 5,000,000 1,000,000 15,000 1.04 million 1.027 980,000 affected Tax-registered household 760,000 1,000,000 2,280 32,409 40.19 1,239,995 businesses with income <100 million per year Source: World Bank, Social Protection and Jobs (as of March 2021) Note: SA = social assistance; UI = Unemployment insurance. Figure 4.8 Incidence of Vietnamese households by policy target groups a. Incidence of households receiving social benefits b. Incidence of households with informal workers 100 100 80 80 Share of households (%) Share of households (%) 60 60 40 40 20 20 0 0 Merit SA SP Poor Household decile households Poorest decile (1) 2 3 4 5 6 7 8 9 Highest decile (10) Source: World Bank staff calculations using Vietnam Household Living Standards Survey, 2018. Note: Merit or National Devotee income, social assistance (SA), and social protection (SP) are based on declarations of income received in these categories. Poor households are those that were defined to be poor in their commune in 2018. 70 A YEAR DEFERRED – EARLY EXPERIENCES AND LESSONS FROM COVID-19 IN VIETNAM Box 4.3 COVID-19 relief packages to households, Vietnam vs. East Asia and Pacific region Vietnam spent less on COVID-19-related social assistance than other countries in the region did. Vietnam spent only 0.11 percent of gross domestic product on new social assistance beneficiaries, the second- lowest in the East Asia and Pacific region among countries that extended social assistance to new beneficiaries and well behind the Philippines’ expansion of 0.62 percent and Indonesia’s expansion of 0.57 percent. As a result of the modest top-up spending and the low spending on new beneficiaries, Vietnam’s total spending on social assistance during the pandemic was 0.86 percent of gross domestic product, among the lowest in the region and significantly lower than Mongolia’s 4.2 percent, Thailand’s 3.0 percent, and the Philippines’ 2.1 percent (table B4.3.1). Table B4.3.1 Spending on social assistance before and during the COVID-19 outbreak Pre-COVID Pre-COVID New Pre-COVID beneficiaries beneficiaries Total COVID-19 Country beneficiaries spending receiving top-up new program spending spending spending spending China 1.56 — — 0.09 1.65 Cambodia 0.09 0 0 0.63 0.72 Indonesia 0.28 0.05 0 0.67 0.95 Lao 0.04 0.00 0 0.00 0.00 Malaysia 0.53 — — — 1.40 Mongolia 1.77 1.79 0 0.60 4.16 Myanmar 0.08 0.09 0 0.53 0.62 Philippines 1.19 1.03 0.30 0.62 2.12 Thailand 0.77 0.15 1.70 0.40 3.00 Vietnam 0.66 0.09 0 0.11 0.86 Source: World Bank Social Protection and Jobs database. Note: Estimates based on bottom-up calculations. — = not available. Consequently, although employment and wage losses were lower in Vietnam than in other countries, the gap between those losses and the support that households did receive was proportionally larger than in all other countries except for the Philippines, where households experienced very high losses (figure B4.3.1). Unlike other East Asia and Pacific countries, Vietnam spent much more on other forms of public spending than on income support (figure B4.3.2). Chapter 4.  POLICIES: A CALL TO STRENGTHEN AMID HEIGHTENING RISKS 71 Box 4.1 - continued Figure B4.3.1 Vietnam had the second-largest Figure B4.3.2 Vietnam spent much more relative gap between household losses and on other forms of public spending than support, East Asia and Pacific on income support 10 16 8 Percentage of gross 12 domestic income Percent of GDP 6 8 4 2 4 0 0 Philippines Indonesia Malaysia Cambodia Thailand China Mongolia Vietnam Myanmar Vietnam Mongolia Thailand Malaysia Indonesia Philippines Earnings loss Support to households Spending on income support Public works, accelerated spending, and public investment Source: World Bank 2021a. Data from the World Bank COVID-19 household The delivery of social assistance benefits is still monitoring surveys show that more households primarily cash based. The majority of social assistance applied for but had not received COVID-19 relief. is provided by cash directly handed out by local staff, Program implementation of the COVID-19 relief package rather than as payments through bank account deposits. announced in April 2020 faced challenges. Disbursement Other modes were reported, such as in-kind assistance of new COVID-19 relief packages was low at the time of like food or medical supplies and assistance in the form first round of World Bank COVID-19 surveys undertaken of discounts on electricity and hospital bills. in June 2020. About 10 percent of households had applied for the new COVID-19 relief programs,28 but Some regions were more successful than others in only about 1 in 10 of those households had received the reaching people affected by COVID-19. Some localities relief (table 4.2). Urban areas had slightly higher rates provided locally funded support that supplemented the of receipt: 13 percent of households in urban areas had national COVID-19 relief programs. Provincial-level received relief as compared to 10 percent of households programs were implemented in Da Nang and Ho Chi in rural areas. About 4 percent of households received in- Minh City. Da Nang was found to have a particularly kind food relief. The receipt of new COVID-19 relief was 29 successful rollout compared to some other regions. The also relatively even across the income distribution, which city implemented two waves of social relief, whereas the indicates that poor households were not necessarily national relief lasted for only one wave. prioritized in being granted relief. By July, the national “Wave 1” programs ended because benefits were offered for a maximum of three months (May–July 2020). 72 A YEAR DEFERRED – EARLY EXPERIENCES AND LESSONS FROM COVID-19 IN VIETNAM Table 4.2 Table 4.2 Social assistance in Vietnam during COVID-19 Percent of households In 2020... February–June/July 2020 Classified Received Received Received Applied for Received as poor in support for support from cash support new COVID-19 assistance commune purchasing any national or for existing relief from new health international vulnerable programs COVID-19 insurance organization groups relief programs All 6.6 38.3 7.7 19.8 10.2 1.2 Urban 3.7 31.5 4.6 14.2 13.7 1.8 Rural 8.1 41.8 9.4 22.7 8.4 0.9 Top 60 2.4 31.7 4.7 13.1 11.4 1.4 Bottom 40 13.3 48.7 12.5 30.4 8.3 0.9 Kinh majority 4.8 33.3 6.9 18.5 10.8 1.3 Ethnic minority 16.8 66.1 12.5 26.7 6.8 0.7 Source: World Bank COVID-19 household monitoring surveys (round 1). Notes: Existing targeted social assistance programs include cash support for poor and near-poor households, social assistance beneficiaries, and merit people (or National Devotees). Merit people refer to those contributed during the “revolution and war times.” The Northern and Coastal Central region including had more positive perceptions of the government relief Da Nang had a higher percentage of households response. Using a panel subsample across all five receiving COVID-19 benefits for new target groups rounds of the household COVID-19 monitoring surveys, (table 4.3). Nationally, 1.5 percent of households received households that applied and received support under new some benefits from COVID-19 relief targeted to new COVID-19 relief programs up to July/August 2020, were groups. In the Northern and Coastal Central region, the more likely to agree that the VND 62 trillion relief plan share was higher at 2.5 percent of all households. The reached the poorest households in need. success rate of applicants was also higher than average in this region. Over half of all households that applied for Poorer perceptions on relief response may be related COVID-19 relief for new target groups received benefits to households feeling persistently at financial risk, between July and September 2020. Round 3 of the despite a well-contained health risk. Government World Bank monitoring survey was conducted in early relief policies ended in June 2020. Even with exceptional September, so it is possible that even more applicants health management and containment, many households received benefits afterward. experienced negative economic impacts and still felt financially at risk. A year after the onset of COVID-19, Perceptions of Vietnam’s COVID-19 health response households still viewed COVID-19 as a threat to their management are more positive than perceptions household finances (figure 4.10). Moreover, these of the relief response. Virtually all households were perceptions did not significantly change over a six-month satisfied with the government response on COVID-19 period from September 2020 to March 2021. Poorer health management, but not as satisfied with the households were also less likely to be optimistic during effectiveness of support for households (figure 4.9). the pandemic (figure 4.11. The last monitoring survey Results from earlier rounds of the World Bank COVID-19 was conducted in March 2021, but a new and even household surveys also show that very few households larger outbreak in May 2021 will likely dampen optimism received benefits from newly proposed relief programs as the lack of predictability of new outbreaks adds to targeted to those that were negatively affected by uncertainty and depresses economic activity. depresses COVID-19. Households that applied and received aid economic activity. Chapter 4.  POLICIES: A CALL TO STRENGTHEN AMID HEIGHTENING RISKS 73 Table 4.3 The highest share of recipients of COVID-19 benefits targeted to new applicants was located in the Northern and Coastal Central region of Vietnam Location/type of household New Target Group Relief July–Sept. 2020 Applied (%) Received (%) All 3.2 1.5 Urban 4.2 2.2 Rural 2.7 1.1 Top 60 3.9 1.7 Bottom 40 2.1 1.0 Kinh majority 3.4 1.6 Ethnic minority 2.5 0.8 Red River Delta 3.1 1.4 Midlands and Northern Mountainous Areas 1.9 0.9 Northern and Coastal Central 4.8 2.5 Central Highlands 0.9 0.1 Southeastern Area 4.0 1.0 Mekong Delta 2.4 1.5 Source: World Bank COVID-19 household monitoring surveys (round 3). Figure 4.9 Perceptions of government response to COVID-19, Vietnam COVID-19 relief Food is easily accessible and affordable Enough is being done to help those who have lost their jobs or had to close their business The VND 62 trillion program reached the most in need Comfortable with internal travel International flights should remain limited until the COVID-19 management pandemic ends April lockdown was a correct length Border control of immigrants Response to Da Nang outbreak Response during March/April crisis 0 20 40 60 80 100 Share of respondents agreeing or satisfied (%) Source: World Bank Vietnam COVID-19 household surveys (round 3). Note: It is important to note that perceptions can change very quickly depending on the timing of the survey, and results should be interpreted with caution. For example, fieldwork for round 3 occurred during the entire month of September 2020 and the share of respondents who did not feel comfortable traveling internally ranged from nearly 30 percent in week 1 of fieldwork that occurred near the Da Nang outbreak, to 10 percent by the end of the month. 74 A YEAR DEFERRED – EARLY EXPERIENCES AND LESSONS FROM COVID-19 IN VIETNAM Figure 4.10 About half of Vietnamese households view COVID-19 as a substantial threat to their finances 100 Share of households (%) 80 60 40 20 0 September 2020 January 2021 March 2021 Bottom 20 Q2 Q3 Q4 Top 20 95% CI Source: World Bank Vietnam COVID-19 household monitoring surveys (rounds 3–5). Note: Household (HH) quintiles (Q) are based on household consumption per capita in 2018. Perception at time of interview. Figure 4.11 Poorer Vietnamese households are less likely to be optimistic during the pandemic a. More optimistic b. Less optimistic 100 100 80 80 Share of households (%) Share of households (%) 60 60 40 40 20 20 0 0 September 2020 January 2021 March 2021 September 2020 January 2021 March 2021 Bottom 20 Q2 Q3 Q4 Top 20 95% CI Source: World Bank Vietnam COVID-19 household monitoring surveys (rounds 3–5). Note: Household (HH) quintiles (Q) are based on household consumption per capita in 2018. Perception at time of interview. Chapter 4.  POLICIES: A CALL TO STRENGTHEN AMID HEIGHTENING RISKS 75 Challenges in implementation of The definitions of new target groups were very household and worker cash support specific and added complications to enrollment. programs Eligibility criteria for new target groups were complicated, and occupations approved for relief were overly specific. Qualitative interviews were conducted to learn For example, employees working in enterprises and about implementation challenges on the ground. educational institutions had to have lost their jobs and The challenges summarized in this section come from social insurance on or after April 1, 2020. However, many qualitative interviews in Da Nang with Department establishments had already stopped operating before of Labour, Invalids and Social Affairs and local-level that date, and other businesses tried to maintain social representatives. Da Nang is a high-capacity city that was insurance for employees after it. As a result, many groups able to implement and target relatively well. Da Nang of employees were adversely affected but were ineligible. even supplemented the national relief packages with its own additional relief package. Lower-capacity provinces Required documentation was cumbersome and very likely experienced wider-scale challenges than unclear for applicants, discouraging many from described here. completing applications. Challenges were expected because residents were unfamiliar with new registration The nationwide relief program was announced in and verification processes. Many submitted applications April 2020 by the central government and swiftly lacked supporting documents, especially paperwork for implemented by local government. The speed of the identification (ID card, household registration). However, rollout led to some timing and coordination challenges the inability to quickly verify and enroll applicants between central and local levels. During the first wave, foreshadows larger social assistance challenges guidance from central to local levels was swiftly passed in Vietnam in the absence of modernization. Some down via many channels. Because the program was applicants were discouraged by complex application new, new forms, questionnaires, and procedures had procedures and did not attempt to follow up or complete to be developed very quickly. Some local governments applications. Confusion and long wait times also led some moved proactively and conducted trainings for villages households to reapply while they waited to hear on their and communes, and designed application forms before application status, causing duplications. central guidance and paperwork and policy specifics were finalized. Thus, some efforts had to be redone. The large volume of applications to process and check meant grass roots staff were overburdened There were challenges associated with verifying the with new workloads. The burden of work was primarily eligibility of applicants under prescribed definitions carried by commune/ward and village level officials. for the new target groups. Employees were required Their responsibilities included policy communications, to have verification from employers that they had lost guiding residents on registration and collecting supporting employment. Getting this type of verification was documents, checking applications, making the list sometimes difficult in large organizations, and some of beneficiaries, organizing review and assessment, employers did not assist with applications and provide submitting completed applications to the district level, necessary documentation for the applications. Eligibility notifying applicants of results, and resolving feedback was based on location of residence rather than work, and complaints from people and communities. In some putting migrant workers at a disadvantage. Informality areas, staff in communes/wards and villages were posed additional challenges to verification. First, informal already engaged in carrying out anti-epidemic tasks, and workers without a labor contract could not, in most cases, their capacity was further stretched. verify their employment. Household businesses were required to confirm their taxable turnover. If they did not keep receipts, they had to prove turnover through the Tax Division. 76 A YEAR DEFERRED – EARLY EXPERIENCES AND LESSONS FROM COVID-19 IN VIETNAM Improving the country’s ability to respond to future More widespread access corresponds to increased shocks, whether COVID-19-driven over the next year awareness of support policy, but implementation or climate-driven in the coming decades, is critical challenges remain. Initially, a major concern of for strengthening household resilience. Identifying the government’s support program was the lack of informal nonpoor during a shock is the hardest task in the communication to potential beneficiaries: 34 percent of targeting of social assistance. But a number of lessons firms were not aware of support policies, and 25 percent from other countries, both during COVID-19 and before, considered them too difficult to apply for. By January suggest better ways of identifying those vulnerable to or 2021, only 14 percent of firms reported not being aware hit by shocks and the importance of the evaluating and of such policies. Among those without access, the main improving the entire social assistance delivery chain in reason was ineligibility, increasing from 45 percent in making sure those affected are not left out (Grosh et al., June 2020 to 63 percent in January 2021. However, a forthcoming). Countries with existing social registries were large fraction of firms, 22 percent, still considered the most prepared to respond. Many countries focused initially support programs inaccessible because it is too difficult to on speed of response, topping up existing benefits, as apply (figure 4.13, panel a). To improve implementation, Vietnam did, but also significantly expanding coverage, firms consider the simplification and improved practicality which Vietnam did not. After a fast and broad response, of eligibility conditions to be the most important changes, countries then tapered and targeted ongoing support. above processing time, information, or even the amount of support (figure 4.13, panel b). A comparative experience of formal firms There is a persistent inequality in access and some evidence of mistargeting. As of the latest survey Relief packages designed for formal firms were round, about 50 percent of all large firms benefited from different than those for households, but they some government assistance, compared to just over 30 experienced similar implementation challenges in percent of small firms (figure 4.14, panel a).30 Moreover, the early stages. These policies were primarily in the although small and medium enterprises are less likely form of deferments and credits, and were available for to have benefited from support, evidence also suggests a longer period. Despite the differences, these policies that having received government support in the past also experienced implementation challenges. Given the correlates with a lower likelihood of making a downward continuous availability of assistance to firms, however, employment adjustment on the intensive margin (for there appears to be some learning from experience and example, cutting hours). By contrast, for medium and improvement in implementation over time. large firms, there is no significant correlation between employment outcomes and government assistance Access to government support among firms has (figure 4.14, panel b). These results suggest that there steadily increased over time. In June 2020, less than may be higher returns to supporting small firms if the 20 percent of surveyed firms reported benefiting from any policy objective is to preserve employment. Overall, government support. By January 2021, more about 36 evidence suggests that access to government support percent of firms had taken advantage of some support is not well correlated with potential needs of firms. Figure policies (figure 4.12, panel a). The most common relief 4.14, panel c, shows that access is not correlated with the received is in the form of income tax reductions and probability that firms experienced a drop in sales, or the deferrals, followed by low-interest-rate loans to small amount of available cashflow, and, if anything, is higher and medium enterprises and extension of land rental for firms that were able to remain open. This result is payment deadlines (figure 4.11, panel b). The dominance perhaps not surprising given that most access has been of corporate income tax reductions and tax deferrals is in the form of income tax deferrals and reductions. By consistent with the nature of these measures – they definition, these measures benefit firms that had some automatically apply as firms file taxes and a wide range positive income, and that may also be able to weather of businesses are eligible. the crisis better. Chapter 4.  POLICIES: A CALL TO STRENGTHEN AMID HEIGHTENING RISKS 77 Figure 4.12 Vietnamese firms’ access to government assistance has almost doubled since June 2020 a. Access to government support, June 2020–January 2021 40 35 Share of firms with access to 30 support policies (%) 25 20 15 10 5 0 June 2020 September/October 2020 January 2021 b. Access by policy type, January–February 2021 CIT reduction Extension of tax payment deadline and exemption of late payment interest Lower interest rate loans to SMEs Extension of deadline for land and rental payments Other Reduction of land rents Extension of deadline for trade union fees Extension of tax payment deadline for payable special compensation Loans for employee salary Temporary suspension of payment to retirement fund Simplified customs procedures and suspensions of inspections Reduction of fee for registration for use of foreign barcodes and industry property fees Reduction of road user fees and charges for transportation businesses 0 10 20 30 40 50 Share of firms received each type of support (%) Source: World Bank COVID-19 Business Pulse Surveys. Note: Figure shows support policies among firms that received some support. CIT = corporate income tax; SMEs = small and medium enterprises. 78 A YEAR DEFERRED – EARLY EXPERIENCES AND LESSONS FROM COVID-19 IN VIETNAM Figure 4.13 Implementation of Vietnam’s support measures has improved, but barriers to access remain a. Main reason for not receiving support b. Suggestions for implementation 70 63 Simplify and improve clarification 35.2 Share of firms not benefiting from of eligibility conditions 60 54 Improve practically for support 22.1 support policies (%) 50 45 Increase amount of support 18.2 40 34 Improve information on how 30 25 14.5 22 to access support 18 17 20 14 Reduce application 9.2 10 10 processing time 10 4 1 2 2 1 0.6 Other 0 0 0 Was not Too Not Applied No Other aware difficult eligible but not need 0 10 20 30 40 to apply received Share of firms suggesting implementation changes (%) June 2020 Sept/Oct 2020 January 2021 Source: World Bank COVID-19 Business Pulse Surveys. As Vietnam faces the fourth wave, the impact on In the longer run, additional policy instruments are businesses and demand for government assistance also needed to support recovery for the private will likely deepen. The government may wish to sector. Simplification of administrative procedures is consider targeting not only by type of firm but also by still considered the most important needed reform by policy instrument. Tax deferrals disproportionally benefit 64 percent of firms (figure 4.15, panel a). This result large firms and are also considered to be more useful by suggests that, despite this acute crisis, improving the large firms. Policies such as low-interest-rate loans and business environment remains a key priority for the land payment deferrals have more limited access and private sector in Vietnam. This is consistent with global yet are considered critical to survival for recipient firms, evidence suggesting that economies respond more especially for small and medium enterprises (figure 4.14, sluggishly to crises in the presence of regulatory barriers panel d). However, access to these policies potentially to business entry and expansion (Barrero, Bloom, and have much more complicated and often impractical Davis 2020). Given the severe demand shocks during eligibility conditions, requiring improvement in design this crisis, it is also important to consider policies to and implementation. Different sectors also have different support firms’ access to new markets and customers. needs. Agricultural firms, for example, appear to have So far, most support measures in Vietnam still focus on distinct demand for low-interest-rate loans, the deferral resolving the short-term liquidity crisis. Looking to other of land rental payments, and reduction in land fees. On countries in the region, more advanced economies such the basis of these demands, the government can focus as Malaysia have already implemented a range of other outreach efforts based on specific needs by different firm policies to help firms improve their capabilities. They sizes and sectors. include measures such as subsidies for skills training and innovation investments (figure 4.15, panel b). New support packages will need to consider similar measures to prepare firms in the recovery phase and become more resilient to future shocks. Chapter 4.  POLICIES: A CALL TO STRENGTHEN AMID HEIGHTENING RISKS 79 Figure 4.14 Gaps in Vietnam’s policy support widened, but targeting has not improved a. Access to support policies, by firm size b. Impact of support policy, by firm size Change in probability Small Share of firms with access to support policies (%) 60 0.4 0.2 0 0 0 −0.01 −0.10 −0.02 −0.2 −0.11 −0.24 −0.34 −0.4 40 −0.6 30 Change in probability Medium 0.4 0.2 0.01 0.03 0.15 0.02 20 0 −0.09 −0.03 −0.08 −0.2 −0.27 −0.4 −0.6 10 Change in probability Large 0.4 0 0.2 0.07 0.01 0.11 0 0 1 2 3 −0.2 −0.29 −0.16 −0.29 −0.09 Round −0.4 −0.6 Small Medium Large Being open Hiring Firing workers Leaves of absence Cutting wages Cutting hours Extensive adjustment Intensive adjustment Estimated coefficients from regressions of access to support policies by Round 3 on performance variables lagged by one period, while controlling for size, sector and location FEs c. Firm lagged outcomes and current access to support d. Support policies considered most helpful/critical to firms 82.6 Lower interest rate 0.3 0.31 60.0 loans to SMEs 69.1 Change in probability of getting support 0.2 Extension of deadline for 82.5 land rental payments 72.2 56.0 0.1 Extension of tax payment 66.8 0.03 0 deadline and exemption of 53.6 0 late payment interest 83.1 62.7 −0.1 CIT reduction 45.5 46.6 −0.2 50.2 Reduction of land rents 50.3 43.5 −0.3 0 Other 19.4 Open Sales drop Cash flow 60.9 0 20 40 60 80 100 Estimated coefficients from regressions of access to support Share of firms receiving support that policies by Round 3 on performance variables lagged by one period, consider it helpful, by type of support (%) while controlling for size, sector and location FEs Small Medium Large Source: World Bank COVID-19 Business Pulse Surveys. Note: CIT = corporate income tax; FE = fixed effect; SMEs = small and medium enterprises. 80 A YEAR DEFERRED – EARLY EXPERIENCES AND LESSONS FROM COVID-19 IN VIETNAM Figure 4.15 Policy considerations for recovery a. Most needed new support policy b. Access to government support in East Asia and Pacific Indonesia Malaysia 100 100 80 80 Share of firms with access to support (%) Simplification of administrative procedures 64.3 60 60 Support to access new markets, 40 40 value chain participation,matching 26.8 20 20 with customers and suppliers 0 0 SMEs Large SMEs Large No, existing policies are sufficient 4.4 Philippines Vietnam Support to adopt digital technologies 3.9 100 100 80 80 Other 60 60 0.7 40 40 0 10 20 30 40 50 60 70 80 20 20 0 0 Share of firms not suggesting SMEs Large SMEs Large new support policies (%) Wage subsides Liquidity support Capabilities support Other Liquidity support includes grants, payments deferrals, access to credit, and fiscal exemptions. Capabilities support includes support for innovation, skills, and tech adoption. Latest available survey wave for each county used. Source: World Bank COVID-19 Business Pulse Surveys. Note: SME = small and medium enterprises. Chapter 4.  POLICIES: A CALL TO STRENGTHEN AMID HEIGHTENING RISKS 81 Notes 26  These isolations were also required of F1 (first-degree contacts) in institutionalized facilities, F2 (second-degree contacts), and the subsequently identified contacted people at home. 27  Due to the evolving situation, the vaccination questionnaire was updated throughout survey implementation. The survey asked the full sample about agreeing to no-cost vaccinations take-up in R4, and vaccination with cost in R5. Only a small sample were asked both questions concurrently in Round 5. 28  Households in urban areas were slightly more likely to apply, reflecting that economic centers are more hard-hit: 13.7 percent and 8.4 percent of households in urban and rural areas applied, respectively. Although the bottom 40 percent of the income distribution and ethnic minorities are the poorest groups, they were also the least likely to apply for new COVID-19 relief. 29  Very likely the result of the new rice ATMs, adoption and use of which took off quickly. These semiautomated machines dispensed 1.5 to 2.0 kilograms of rice at a time. Although these ATMs were initially installed in Ho Chi Minh City to support those experiencing job loss amid the pandemic, more were installed across the country in collaboration with private donors and sponsors. 30  The differences in levels across three size groups are weakly significant. When access to government support is regressed on firm size, large firms are 7.4 percent more likely to access support than small firms (p = 0.08). Limiting the sample to round 3 only, large firms are 14.6 percent more likely to have accessed support than small firms (p = 0.066). The differences in trends are not statistically significant. References Barrero, Jose Maria, Nicholas Bloom, and Steven J. Davis. 2020. “COVID-19 Is Also a Reallocation Shock.” NBER Working Paper 27137, National Bureau of Economic Research, Cambridge, MA. Grosh, Margaret, Phillippe Leite, Matthew Wai-Poi, and Emil Tesliuc. Forthcoming. “A New Look at Old Dilemmas: Revisiting Targeting in Social Assistance.” World Bank, Washington, DC. Malesky. Edmund J. 2021. “How Businesses in Vietnam Weathered the COVID-19 Crisis: Implications for the Country’s Post- Pandemic Trajectory.” Unpublished Paper. Mathieu, E., H. Ritchie, E. Ortiz-Ospina, M. Roser, J. Hasell, C. Appel, C. Giattino, and L. Rodés-Guirao. 2021. “A Global Database of COVID-19 Vaccinations.” Nature Human Behavior 5: 947–53. August 5, 2021, update. World Bank. 2021a. World Bank East Asia and Pacific Economic Update, April 2021: Uneven Recovery. Washington, DC: World Bank. © World Bank 82 A YEAR DEFERRED – EARLY EXPERIENCES AND LESSONS FROM COVID-19 IN VIETNAM Chapter 5. IMPACT ON POVERTY IN 2020: PROGRESS SLOWED DOWN BUT DID NOT REVERSE Despite Vietnam’s enviable macroeconomic outcomes in 2020 and early 2021 in the COVID-19 (coronavirus) context, the pandemic halted a period of rapid income and wage growth for households. Previous chapters provided evidence on the estimated impacts felt by households during COVID-19 through various channels. Simulations in this chapter discuss how many people fell into poverty during COVID-19, that otherwise would not have in its absence. The share of the new poor is small, primarily because of strong agricultural sector growth in 2020, where most of the poor work. At the global lower-middle-income poverty line ($3.20 per day in 2011 purchasing power parity [PPP] dollars), the estimated share of new poor31 is small, less than half a percent of the population; at this line, preexisting vulnerable informal and agricultural households are still likely to be the most at risk of falling below the poverty line in a COVID-19 context and make up the majority of the new poor. At the higher upper-middle- income poverty line ($5.50/day 2011PPP), the new poor represent about 1 percent of the population; at this line, households in manufacturing, construction, and retail sectors make up a larger share of the new poor. Simulations estimate that COVID-19 slowed the poverty reduction trajectory and stalled progress by about a year. The welfare-improving impact from cash support programs to households was small. Chapter 5.  IMPACT ON POVERTY IN 2020: PROGRESS SLOWED DOWN BUT DID NOT REVERSE 83 A MICRO-MACRO SIMULATION APPROACH The primary objective of the approach is to measure The remainder of this chapter is organized as the differences in the poverty and inequality follows. The following three subsections will describe trajectories across different growth and social assumptions and trends across three broad factors: assistance scenarios. Previous chapters illustrated sector growth, employment, and social protection. The a range of impact channels and self-reported changes next section then discusses the cumulative impact from to household incomes during COVID-19. This chapter these three sets of factors on poverty under two scenarios asks, how much did COVID-19 slow down the trajectory (no-COVID-19 and COVID-19). Figure 5.1 illustrates the of poverty reduction, and for whom? model parameters used. This exercise follows simulation methods similar Growth factors to those used in other developing countries for assessing COVID-19 impacts on poverty32. There Two growth scenarios are considered to compare are a variety of simulation methods available to project welfare impacts under different conditions. The first, poverty rates under different conditions. These methods the no-COVID-19 scenario assumes a growth pattern range from the simplest ones, based on growth-poverty similar to that of 2019. The second, COVID-19 scenario elasticities, to more comprehensive computational uses actual growth rates from 2020. general equilibrium models. The micro-macro simulation technique used in this report goes beyond a growth- 1.  No-COVID-19 scenario: the same sectoral growth in elasticity method by allowing for different rates of growth 2020 as in 201933 and growth-employment elasticities across sectors. The strategies employed in this chapter capture the primary 2.  COVID-19 scenario: actual sectoral level impact channels, but not as many behavioral changes growth rates in 2020 as would a computational general equilibrium model. Overall, results still provide a useful assessment of the Despite positive gross domestic product (GDP) growth impact on poverty and inequality under different growth in 2020, actual growth rates were still much lower than and redistribution scenarios. expected. GDP growth was nearly 4 percentage points lower than forecasts made before the onset of COVID-19. Using the micro-macro-simulation method presented Growth rates in the manufacturing and services sectors in this chapter, the primary channel through which declined the most in percentage point terms. The decline in COVID-19 affected households is assumed to be tourists and flights was severe, and the services-oriented through labor market incomes and employment. tourism sector was one of the hardest-hit sectors in 2020. Sector-specific growth rates affect the degree of labor An active domestic tourism sector prevented a complete allocation across sectors or shedding into unemployment. fallout, but many accommodation and tourism businesses Losses or gains in employment subsequently affect still closed. Between the first and second quarters of labor market income and household welfare and 2020, about 30 percent of hotel and restaurant workers poverty. Differences in actual sectoral growth rates and left the sector, either losing work completely or moving estimates made before COVID-19 will lead to different to other sectors for employment. Agriculture, by contrast, shifts in employment and poverty impacts that allow for performed better than before COVID-19, growing at 2.7 counterfactual comparisons. The simulation also includes percent and surpassing services, the growth of which fell an assessment of the welfare impacts of the COVID-19 to 2.2 percent. However, looking at cumulative sectoral social assistance policy in Vietnam (figure 5.1). performance since 2018, services still outgrew agriculture by 4.7 percentage points. 84 A YEAR DEFERRED – EARLY EXPERIENCES AND LESSONS FROM COVID-19 IN VIETNAM The ability to disaggregate projected growth rates well as the North and Central coastal area where Da Nang across sectors allows for the impact of growth on is located, which is heavily reliant on tourism. employment levels to be different across sectors. Sectors shed or gain workers at different rates. This is Like other Southeast Asian economies, a large share especially important given the agricultural sector’s natural of the labor force is active in the agricultural sector, decline due to structural transformation. Sectors have but the sector contributes a smaller fraction of GDP varying contributions to GDP, productivity, and labor (table 5.1). In 2018, 14.3 percent of GDP was from intensity. The initial welfare status of households also agricultural activity, but 39 percent of workers participated varies significantly by sector, with those in agricultural in the sector. When examining the prevalence of being obviously the poorest. agriculture at the household level, just over 50 percent of households had at least one adult who still participated There are strong regional differences in sectoral in agriculture in 2018 and almost 43 percent of household composition (figure 5.2). Agriculture tends to be the heads are also active in the sector. By contrast, of those dominant sector in the Central Highlands and Mekong Delta household members participating in the manufacturing regions. Industrial zones are scattered across the country, sector, a much lower proportion are household heads, but there are larger concentrations outside of Hanoi and Ho reinforcing that it is primarily younger cohorts that have Chi Minh City. The major cities are also services oriented, as been able to engage and participate in manufacturing. Table 5.1 Distribution of households by main economic sector of activity Share of GDP, Share of GDP, Share of HHs with Distribution of Distribution of 2020 (%) 2018 (%) someone working in main sector of workers aged 15 the sector (%) the HH head (%) and older (%) Agriculture 13.6 14.3 50.9 42.8 39.2 Manufacturing 36.5 35.5 41.8 12.5 17.6 Services 38.6 38.7 50.6 44.6 43.3 Source: Vietnam General Statistics Office; World Bank staff calculations using Vietnam Household Living Standards Survey, 2018. Note: The share of households with someone working in the sector doesn not add to 100 percent. HH= household. Figure 5.1 Illustration of model parameters to estimate welfare Growth Employment and income Social assistance policy Population and workforce GDP growth by sector growth into 2020 Scenarios of actual and Welfare Welfare expanded COVID-19 cash impacts impacts Growth-employment Labor reallocation across support policies with SA elasticities sectors or into unemployment based on sector size predicted by growth-employment elasticities Changes in wages based on reallocation and growth Source: World Bank staff elaboration. Note: SA = social assistance. Chapter 5.  IMPACT ON POVERTY IN 2020: PROGRESS SLOWED DOWN BUT DID NOT REVERSE 85 Figure 5.2 Sector concentrations, by province Share of GDP from Agriculture Share of GDP from Industry Share of GDP from Services Source: GSO Statistical Yearbook. Notes: Provincial GDP shares are 2018 preliminary calculations. The difference in realized growth rates of GDP and manage the outbreak. However, from the household side private consumption also suggest varying impacts as measured in aggregate by Private Consumption, an of COVID-19 on the macroeconomy versus on inevitably slower domestic economy with 14 million fewer households at a microlevel (figure 5.3). The export- tourists and economic activity interrupted by occasional oriented manufacturing sector in Vietnam was resilient lockdowns led to income and job losses, business during COVID-19, growing by 4 percent and attracting closures, delays to large investments and purchases, foreign investment as other countries struggled to and lower spending. Figure 5.3 Growth actuals in 2020 were much lower than pre-COVID-19 forecasts a. GDP per capita growth rate b. Private consumption per capita growth rate 8 8 7 7 6 6 Growth rate (%) Growth rate (%) 5 5 4 4 3 3 2 2 1 1 0 0 −1 −1 2018 2019 2020 2021 2022 2023 2018 2019 2020 2021 2022 2023 Pre-COVID (fall 2019) Baseline (March 2021) Pre-COVID (fall 2019) Baseline (March 2021) Source: World Bank. Note: Macro growth series estimated before COVID-19 were calculated in fall of 2019, use actuals from 2018–19, and are forecasts from 2020 onward. March 2021 macro data use actuals from 2018–20, and forecasts from 2021 onward. 86 A YEAR DEFERRED – EARLY EXPERIENCES AND LESSONS FROM COVID-19 IN VIETNAM Employment factors Employment in manufacturing has the largest elasticity, which is expected because millions of new manufacturing The growth elasticity of employment by sector is used jobs have been created over the last decade, matching to determine the change in the size of employment the sector’s continued strong export-oriented growth even by sector under different growth scenarios (table 5.2). during COVID-19. One important calculation that is key to the modeling is the calculation of growth elasticity of employment by sector. Vietnam’s population continued to grow in 2020, but These elasticities vary by five sectors: (1) agriculture, it is aging. The size of the working-age population is industry disaggregated into (2) manufacturing and (3) growing, but not by a large share because of the declining other industry, and services split into (4) traditional and demographic dividend. The total workforce in 2020 is (5) modern services. The elasticities are calculated projected to be 64.5 million (individuals aged 15–64). on the basis of a simple regression using a GDP and However, the growth of the labor force is expected to employment series from 2005 to 2019 including crisis be slightly smaller in the COVID-19 scenario than in a interaction terms to allow for different elasticities during no-COVID-19 scenario. People are being absorbed into COVID-19 and no-COVID-19 scenarios. This pandemic other sectors, but into jobs of lesser quality. is not the first time Vietnam has experienced a crisis and managed well. During the 1997 Asian and 2008 The size of the employed labor force is smaller under global financial crises, Vietnam continued to grow as the COVID-19 and downside scenarios (table 5.3). The neighboring countries experienced growth slowdowns employed share in the COVID-19 scenario is estimated and recessions. The growth elasticity of employment to be 84.2 percent, compared to 86.2 percent in the no- during the global financial crisis is an important point COVID-19 scenario. Although employment rates continue of comparison to estimate the growth elasticity of to increase from 2019 levels in both scenarios, the employment during the COVID-19 crisis period. The important point of comparison is between the COVID-19 growth elasticity of employment in agriculture is negative; and no-COVID-19 scenarios. The COVID-19 scenario the sector has been naturally shedding jobs for years as shows higher unemployment rates. In the COVID-19 it continues to age and become increasingly mechanized, scenario, agriculture is expected to shed fewer workers, and as young people are drawn to off-farm jobs. and other sectors are expected to gain fewer workers. Table 5.2 Employment elasticity in Vietnam, 2020 No COVID-19 (no crisis) COVID-19 (crisis) Overall 0.2800 0.2799 Agriculture –0.4763 –0.4759 Manufacturing 0.6826 0.6792 Other Industry 1.0071 1.0065 Traditional services 0.6324 0.6284 Modern services 0.4919 0.4908 Source: World Bank staff calculations using Vietnam Household Living Standards Survey, 2018. Note: Employment elasticity of output (percent change in employment associated with a 1 percent change in GDP). Chapter 5.  IMPACT ON POVERTY IN 2020: PROGRESS SLOWED DOWN BUT DID NOT REVERSE 87 Table 5.3 Labor shares across scenarios, Vietnam 2018 2020 Scenarios (Actual from VHLSS) No COVID-19 (no crisis) COVID-19 (crisis) Total workforce (aged 15–64) 1 1 1 Employed 0.819 0.862 0.842 Unemployed/out of labor force 0.181 0.138 0.158 Agriculture 0.368 0.338 0.345 Manufacturing 0.180 0.195 0.192 Other industry 0.093 0.101 0.099 Traditional services 0.242 0.247 0.245 Modern services 0.118 0.120 0.119 Source: World Bank staff calculations using Vietnam Household Living Standards Survey (VHLSS), 2018. Note: Although employment elasticities of growth are assumed to be the same for the entirety of the manufacturing and services sectors, for the labor reallocation exercise, these sectors can be disaggregated. According to the sectoral growth elasticity of loss (GSO 2021a). Beneficiary analysis for scenario 2 employment, the employed workforce is about considering a much larger expanded program uses these 2 million fewer people in the COVID-19 scenario statistics as benchmarks for the number of workers who than in the no-COVID-19 scenario. The majority of could have benefited from cash support. The total costs this disparity comes from the markedly lower growth in of these scenarios range from VND 12 trillion to VND 208 the manufacturing and the traditional services sectors trillion. Vietnam’s planned budget allocation in April 2020 in the COVID-19 scenario. In both the no-COVID-19 for COVID-19-related relief to households was VND 62 and the COVID-19 scenarios, the size of the employed trillion (about 0.85 percent of 2019 GDP). Thus, the actual workforce is increasing, but it does so to a lesser extent implementation was smaller than planned. in the COVID-19 scenario. In the COVID-19 scenario, the number employed in agriculture is higher but close to Because existing vulnerable groups and social that in the no-COVID-19 scenario; in both scenarios, the assistance recipients were preapproved to receive agricultural share of the labor force is declining. COVID-19 relief top-ups, the benefits from COVID-19 relief were more likely to be received by poor Social protection factors households (figure 5.4). Nationally, the incidence of households receiving benefits in the actual and expanded Early in the pandemic, a nationwide COVID-19 relief scenarios are 13 and 39 percent, respectively. Forty- package was announced to support households, six percent of households in the poorest welfare decile as discussed in chapter 4. To measure and compare received COVID-19 relief in the form of top-ups. However, the impact of the cash support onto households, two the amount of top-ups to poor and near-poor households scenarios are considered (table 5.4). Scenario 1 is based is lower than amounts provided to informal workers. on the actual disbursements and number of beneficiaries. The expanded social assistance scenario considers Scenario 2 considers a larger rollout both in terms of an increase in new beneficiaries from 1 million informal the number of beneficiaries and the duration of benefits. workers to 32 million workers. This expansion increases The General Statistics Office of Vietnam estimates that the share of beneficiaries across the entire distribution, by quarter 1 of 2021, 32 million workers were affected without further criteria on the type of affected worker. by COVID-19, either through job, hours, or income 88 A YEAR DEFERRED – EARLY EXPERIENCES AND LESSONS FROM COVID-19 IN VIETNAM Table 5.4 Simulated cash transfer scenarios, Vietnam Scenario 1 – actual SA Scenario 2 – expanded SA (original max of 3 months) (6 months) No. of people Spending per person No. of people Spending per person for 3 months (D) for 6 months (D) Income support to existing target groups Poor and near-poor 7 million 770,000 7 million 1.5 million households SA beneficiaries 2.8 million 1.5 million 2.8 million 3 million National Devotees 1 million 1.5 million 1 million 3 million Income support to new target groups Workers affected by 1 million 1 million 32 million 6 million COVID-19 (informal workers) Total cost 12.1 trillion 208.2 trillion Source: MOLISA. Note: National Devotees are those who contributed during the “revolution and war times.” D = Vietnamese dong; SA = social assistance. Figure 5.4 Distribution of Vietnamese households receiving benefits, by region and scenario 80 70 Share of households (%) 60 50 40 30 20 10 0 Lowest 2 3 4 5 6 7 8 9 Top welfare welfare decile (1) decile (10) Actual SA Expanded SA Source: World Bank staff calculations using Vietnam Household Living Standards Survey, 2018. Note: SA = social assistance. Chapter 5.  IMPACT ON POVERTY IN 2020: PROGRESS SLOWED DOWN BUT DID NOT REVERSE 89 POVERTY IMPACTS COVID-19 slowed the progress of rapid poverty 2011 PPP) converts to just under VND 1 million per reduction in Vietnam but did not reverse it. capita per month. The monetary poverty threshold in Consumption-based poverty rates in Vietnam are the General Statistics Office’s multidimensional poverty reported every two years. Poverty in 2020 is not expected index was just recently updated to about VND 1 million to be higher than poverty in 2018, but the pace of poverty per month per capita. Thus, whether the actual rollout reduction is much slower than historical trends. Based on of social assistance (scenario 1) or the intended rollout growth and employment factors , simulation results show 34 (scenario 2) is modeled, the poverty mitigation effects are that poverty estimates in 2020 is higher by 0.3 percentage limited by the low level of benefits. This is an important points compared to a no-COVID scenario (6.1 vs. 5.8 consideration for the design of any future COVID-19 percent, under the $3.20/day 2011 PPP poverty line) responses in case the fourth or later waves require (table 5.5). The share of new poor is very small, supported significant lockdowns. by a resilient agriculture sector where most of the poor are economically engaged. Under the higher Upper- There are some caveats of the model to consider. Middle Income class poverty line ($5.5/day 2011PPP), For example, not all sources of income are impacted the size of the new poor is larger, at one percent of the through this particular model, such as remittances population. At higher poverty lines, households are more or financial income. It does not allow for simulation diverse and extend into those economically engaged in considering multiple sources of household-level incomes. the relatively more impacted services and manufacturing The simulation relies on measuring changes through sectors compared to agriculture. labor incomes of the primary job, and also agriculture and business as a secondary income source.36 Other Welfare-improving impacts from both social income sources were also affected during COVID-19. assistance scenarios are small. Under the expanded As described in appendix B, households tend to have social assistance scenario, beneficiaries would receive more than one source of income, for example, through about VND 6 million on average for the year, or VND secondary wage jobs, agriculture, and small businesses. 500,000 per month, or VND 125,000 per capita per month However, only the primary source of household income (assuming an average household size of four).35 This was taken to be simulated because modeling the amounts to only a small proportion of average household dynamics between the primary and other sources of consumption per capita, which is about VND 3.6 million income would both increase the complexity and add per month per capita. Benefits are also small compared more sources of uncertainty. Income impacts through to thresholds considered to be the cost of basic minimum modeled channels can thus be taken to be a lower needs. The World Bank LMIC poverty line ($3.20/day bound of potential total household income impacts. Table 5.5 Summary of poverty rates in Vietnam, 2018 (actual) and 2020 (simulated) 2018 2020 Actual No COVID-19 COVID-19 No SA Actual SA Expanded SA Lower-middle-income poverty rate 6.6 5.8 6.1 6.0 5.6 ($3.20/day 2011 PPP) Upper-middle-income poverty rate 22.36 16.0 17.0 16.9 16.1 ($5.50/day 2011 PPP) Source: World Bank staff estimates using Vietnam Household Living Standards Survey, 2018 Note: PPP = purchasing power parity; SA = social assistance. 90 A YEAR DEFERRED – EARLY EXPERIENCES AND LESSONS FROM COVID-19 IN VIETNAM Second, although in the case of Vietnam there are strong At higher poverty lines, the profile of the new poor regional and localized characteristics in play, the model will also differ (figure 5.5). At lower poverty lines, the does not consider region-specific shocks, because such majority of households at the lower end of the distribution a simulation would require regional-sectoral GDP growth rely on agriculture, and small changes in income will push rates that are not available. them into poverty. By sector, households in agriculture (which is highly informal), retail services, and with heads Figures 5.5 and 5.6 illustrate the composition of the who are not working are also more likely to be new poor. new poor. Specifically, the composition in the figures is of At higher poverty lines, more households outside of the those who are not poor in 2020 under the no-COVID-19 agricultural sector also become vulnerable—notably, scenario but are under the COVID-19 scenario without the share of households that are the new poor under a social assistance. It is important to note that this is a higher line increases in manufacturing, construction, and very small group to begin with (only 0.33 percent of the retail sectors. population). Even though the results do not account for region-specific effects, they do reflect the nature of the Changes in poverty rates under the COVID-19 and expected geographic profile of new poor. For example, no-COVID-19 scenarios are not substantial, hence the the largest shares of new poor by region are found in the profile of the poor is not significantly different; but Mekong Delta and Northern Coastal areas. The Mekong there are some small shifts by certain characteristics. Delta was hard hit by droughts in early 2020, and the In a COVID-19 scenario, the profile of the poor skews second outbreak in Da Nang is located in the Northern slightly more to those working in services whereas those Coastal region. The majority of the new poor are also in agriculture make up a slightly smaller share of the households without formal sources of income. poor (figure 5.6). This result is driven by the fact that the services sector experienced the largest percentage point decline in the expected and actual sectoral growth rate in 2020. Figure 5.5 The characteristics of Vietnam’s new poor differ, by poverty line a. Sector of the new poor ($3.20/day 2011 PPP) 0 20 40 60 80 100 Share of new poor (%) b. Sector of the new poor ($5.50/day 2011 PPP) 0 20 40 60 80 100 Share of new poor (%) Agriculture Mining and Quarrying Manufacture Utilities Construction Wholesale, Retail Transportation Finance, Insurance, Public Not working Others Real Estate Source: World Bank staff micro-macro simulation estimates. Note: PPP = purchasing power parity. Chapter 5.  IMPACT ON POVERTY IN 2020: PROGRESS SLOWED DOWN BUT DID NOT REVERSE 91 Figure 5.6 In a crisis scenario, the proportion of Vietnam’s poor in services is higher a. Lower-middle-income poverty rate b. Upper-middle-income poverty rate ($3.20/day 2011 PPP) ($5.50/day 2011 PPP) 50 50 Distribution of the poor, Distribution of the poor, 40 40 by scenario by scenario 30 30 20 20 10 10 0 0 Agriculture Manufacturing Services Not Working Agriculture Manufacturing Services Not Working 2020 No COVID-19 2020 No COVID-19 2020 COVID-19 No SA 2020 COVID-19 No SA 2020 COVID-19 Actual SA 2020 COVID-19 Actual SA Source: World Bank staff micro-macro simulation estimates. Note: PPP = purchasing power parity; SA = social assistance. 92 A YEAR DEFERRED – EARLY EXPERIENCES AND LESSONS FROM COVID-19 IN VIETNAM Notes 31  The new poor are defined as those estimated to be poor in 2020 under a COVID-19 scenario but who otherwise would not have been poor. The share of the new poor is calculated for different poverty lines. 32  See appendix I for more information on the micro-macro simulation. 33  This option is chosen because pre-COVID-19 sectoral growth projections based on desired disaggregation are unavailable. 34  Results using actual 2020 GDP growth rates (rather than growth rates estimated pre-COVID) and no expansion/top- up in SA programs 35  Welfare concepts used to measure poverty are measured in per capita terms. 36  Labor market income is either wage, agriculture, or net business income. First, wage (formal or informal) income for all individuals is applied. For households in the agriculture sector and without any reported wage income, labor market income is applied from agriculture production and business income. This approach is taken because wage income is available at the individual level, but agriculture and business income are available only at the household level. References GSO (General Statistics Office). 2021a. “COVID-19 Impacts on Labour and Employment Situation in Quarter IV of 2020.” GSO, Hanoi, January 6. A YEAR DEFERRED – EARLY EXPERIENCES AND LESSONS FROM COVID-19 IN VIETNAM 93 Chapter 6. LONGER-TERM IMPACTS: WILL COVID-19 LEAD TO WIDENING INEQUALITY? Over the past decades, inequality in Vietnam has remained low and stable, and poverty reduction has been growth driven. Will COVID-19 (coronavirus) lead to larger distributional changes in the welfare distribution? Even as most households survived and adapted throughout the pandemic by using various coping strategies, goals and ambitions may have been deferred—and households with more means were able to adapt better. Earlier chapters showed that household income recovery was slowest for those in the bottom welfare quintile, and widening nonmonetary inequality is a concern. Among households negatively affected, the poorest are more likely to defer education needs and are still the least likely to use or adopt digital services and technologies. Some trends proliferated across regions, such as differences in education continuity during lockdowns. Disparities caused by COVID-19 also build on preexisting inequalities in food, digitization, health care, and education. Simulations in this chapter show that rising monetary inequality would further delay poverty reduction. 94 A YEAR DEFERRED – EARLY EXPERIENCES AND LESSONS FROM COVID-19 IN VIETNAM UNEQUAL EXPERIENCES DURING COVID-19 Inequality may lead to slower economic growth and between 6 and 18 years of age experienced school poverty reduction. A certain degree of inequality can be closures. Households with children from urban areas, positive, by rewarding those who work hard, innovate, the Red River Delta, and Southeast regions were most and take risks. But income inequality is unfair when not affected. As many as 50 out of 63 provinces closed everyone has the same initial opportunities in life. The schools early in January and February 2021 ahead of consequences of doing nothing and allowing inequality Tet holidays because of the third outbreak. to grow unchecked could be serious, giving rise to slower economic growth and poverty reduction.37 Adverse learning effects from school closures remain challenging because of limited access to distance COVID-19 can be expected to increase monetary learning and remedial learning. Among households and nonmonetary inequality for a range of reasons. with children having school disruptions, only 61 percent From the monetary perspective, households in the had access to online classes and almost 20 percent did poorest quintile were seen to have the slowest income not have access to any distance learning opportunities recovery trajectory from June 2020 to March 2021 between September 2020 and March 2021. In locations (chapter 2). Households with lesser means coped less where online classes were not available or accessible, well (chapter 3). According to Vietnam’s Labor Force the Ministry of Education and Training and the provincial Survey, informality and underemployment rates rose, and Departments of Education and Training arranged to wage growth remained stagnated into the first quarter of broadcast learning sessions on television and/or radio. 2021. The COVID-19 relief program aiming to support However, these mediums account for only a negligible informal workers who lost their jobs, implemented on a portion of distance learning. Short Message Service– and small scale for a short period early in the pandemic, is paper-based self-studying are the second most popular estimated to have had minimal welfare impacts (chapter methods, but they are generally considered ineffective 4 and 5). Among firms, large firms had better capacity to by teachers and students. cope and adopt than smaller firms. Inequality may have widened over a range on nonmonetary dimensions as School closures hit economically disadvantaged, well, affecting longer-term equity. Evidence of potentially ethnic minorities, and low-achieving students widening gaps in education, food consumption, and digital particularly hard (figure 6.1). Over 60 percent of inclusion will be discussed in the next sections. Changes 38 households in the lowest welfare quintile and ethnic in future plans of households and firms are illustrated, minorities, and close to 59 percent of those living which are followed by simulations of distribution-sensitive in the Midlands and Northern Mountainous Areas, poverty projections. Central Highlands, and the Mekong Delta regions did not have online learning offered during school Disparities in distance learning closures. By contrast, only 4 percent of households in the Red River Delta region (Hanoi area) did not receive During the first outbreak in early 2020, Vietnam’s distance learning. The Red River Delta region and the education sector responded early and decisively to Southeastern region, where Hanoi and Ho Chi Minh City COVID-19 risks and closed all schools for almost are located, had very high rates of online live classes. three months—among the most prolonged closures in the world. Although containment measures became more localized and targeted over time, school closures were still widespread. Between September 2020 and March 2021, 72 percent of households with a child Chapter 6.  LONGER-TERM IMPACTS: WILL COVID-19 LEAD TO WIDENING INEQUALITY? 95 Figure 6.1 Continuity of education varied across Vietnam’s regions and by household socioeconomic groups a. Households affected by school closures, by income group 100 Share of affected households (%) 80 60 40 20 0 No distance Online live classes SMS Paper-based Other learning self-learning Bottom 20 Q2 Q3 Q4 Top 20 b. Households affected by school closures, by region 100 Share of affected households (%) 80 60 40 20 0 No distance Online live classes SMS Paper-based Other learning self-learning Red River Delta Midlands and Northern Mountainous Areas Northern and Coastal Central Region Central Highlands Southeastern Area Mekong Delta Source: World Bank Vietnam COVID-19 household monitoring surveys (round 5). Note: Household welfare quintiles (Q) are based on household consumption per capita in 2018. SMS = Short Message Service. 96 A YEAR DEFERRED – EARLY EXPERIENCES AND LESSONS FROM COVID-19 IN VIETNAM These regional differences reflect not only business sides, with some differences across household inequality across households but also inequality characteristics and business types. in public services across regions. Access rates and performance of the Midlands and Northern Mountainous The number of households that shopped online Area, Central Highlands, and the Mekong Delta regions increased by 30 percent after the onset of the have persistently lagged other regions at all levels of pandemic. About one-quarter of households, or 6.7 education. These regions also suffer from a technological million were shopping online on business-to-consumer infrastructure deficit, inhibiting their ability to implement platforms before February 2020. By January 2021, an distance learning. Poor information and communication additional 2 million households that were not previously technology capacity is reflective not just of insufficient shopping online began to do so for the first time (figure infrastructure but also of weaker governance, in 6.2). Facebook is by far the most popular digital platform, addition to poor and unsustainable financing, given that but it is slightly more popular among poorer households governance and financing for general education are (figure 6.3). Items purchased online over business-to- highly decentralized to provinces. consumer platforms are primarily clothing, shoes, and accessories, followed by household items. As a point of The situation remains fluid, and provinces continue comparison, 18.8 percent of individuals aged 15 years reopening and reclosing schools in a relatively and older were shopping online in 2017.39 Thus, it does disruptive manner in response to new outbreaks. appear that the growth of new online shoppers was faster The start of the fourth wave has resulted in widespread during COVID-19. school closures in 49 out of 63 provinces, mostly in the form of early summer breaks or complete closure without Wealthier households are more likely to be existing remedies or access to distance learning. The latest wave and new online shoppers. Households in urban areas of closures also coincides with a key assessment and and at the higher end of the welfare distribution were testing period. It is still uncertain how these high-stakes more likely to already be online shoppers before the assessments, including secondary graduation exams, will pandemic. In terms of the adoption of digital technology, be implemented. Given that high-stakes exams are used the emergence of new online shoppers was higher among as a key qualification to enter upper-secondary schools households at the higher end of the welfare distribution. and higher education, school interruption and exam cancellation can have potential long-term consequences Households at the higher end of the welfare distribution for education completion. Because more poorly resourced are also more likely to participate in the digital economy provinces are less able to provide education continuity, from the supply side. Sellers and those employed in inequities in education completion may also widen across digital ride-sharing services are also more likely to be at socioeconomic groups. the higher end of the welfare distribution (figure 6.4). Digital participation among households Digital exclusion was apparent in distance learning, but differences in digital participation also manifested in other ways. Because of restrictions on social mobility, and the prevalence of home-based work, COVID-19 was expected to accelerate digital adoption. In the case of Vietnam, it was not clear if this trend would materialize in a significant manner because of the successful containment of the virus and relative normalcy to pre-COVID periods. However, there is evidence of increased digital up-take from both the household and the Chapter 6.  LONGER-TERM IMPACTS: WILL COVID-19 LEAD TO WIDENING INEQUALITY? 97 Figure 6.2 An additional 2 million Vietnamese households began shopping online between February 2020 and January 2021 a. Households shopping online, by income group b. Households shopping online, by region 50 50 40 40 Share of households (%) Share of households (%) 30 30 20 20 10 10 0 0 Bottom Q2 Q3 Q4 Top Red River Delta Mountainous Areas Midlands and Northern Northern and Coastal Central Region Central Highlands Southeastern Area Mekong Delta 20 20 Existing online shopper New online shopper Existing online shopper New online shopper Source: World Bank Vietnam COVID-19 household monitoring surveys (round 4). Note: Household welfare quintiles (Q) are based on household consumption per capita in 2018. Figure 6.3 Facebook is the most popular digital business-to-consumer platform, Vietnam 80 70 Share of households (%) 60 50 40 30 20 10 0 Facebook Shopee Zalo Lazada Tiki Other Bottom 20 Q2 Q3 Q4 Top 20 Source: World Bank Vietnam COVID-19 household monitoring surveys (round 5). Note: Household welfare quintiles (Q) are based on household consumption per capita in 2018. 98 A YEAR DEFERRED – EARLY EXPERIENCES AND LESSONS FROM COVID-19 IN VIETNAM Figure 6.4 Wealthier Vietnamese households are more likely to know someone who is engaged in the digital economy 35 30 Share of households (%) 25 20 15 10 5 0 Do you know anyone who sells products online? Do you know anyone who is a driver for Grab, Bee, Gojek, Now, Baemin? Bottom 20 Q2 Q3 Q4 Top 20 Source: World B COVID-19 household monitoring surveys (round 5). Note: Household welfare quintiles (Q) are based on household consumption per capita in 2018. Small firms suffered larger impacts of large firms using digital platforms may be because but were less able to adapt using these firms have more financial and human resources to digital solutions adopt the digital technology. Moreover, large firms can invest such resources to adopt digital platforms for more Family businesses were less likely than formal firms sophisticated business functions, such as production to adopt technology, highlighting another gap (figure planning, supply chain management, and fabrication, 6.5). Households in the top welfare quintile and who had for back-end purposes (figure 6.7). family businesses were the most likely to adopt digital technology and acquire sales from digital platforms, as In contrast, the update of digital platforms by small well as to increase the share of their sales from digital and medium firms is mainly focused on front-end platforms. At a broader level, the Labor Force Survey business functions, such as marketing, sales, and also found that digital technology was brought into the payment methods. All firms—small and medium workplace. In quarter 1 of 2021, about 78,000 workers enterprises (SMEs) and large firms—started using digital reported adoption of information technology applications platforms for front-end purposes at beginning of the due to the COVID-19 pandemic (GSO 2021b). pandemic, and this trend has increased over three survey rounds. By January 2021, almost 90 percent of large firms Formal firms adopted digital technologies as a and over 90 percent of SMEs had started or increased coping strategy to mitigate the negative impacts their use of digital platforms for front-end purposes. of the pandemic, but the uptake of technologies, However, fewer SMEs have done so for back-end especially for more sophisticated functions, has been purposes: about 60 percent of SMEs started or increased skewed toward larger firms. More large firms have their use of digital platforms for these purposes, whereas consistently been using digital platforms compared with almost 90 percent of large firms had done so by January small and medium firms (figure 6.6). Consistently, the 2021. It is easy for small firms to adapt these simpler share of large firms that started using or increased their business functions to digital platforms, but incorporating use of digital platforms between June 2020 and January digital technologies into more complex business functions 2021 is 10–15 percentage points greater than that of requires more resources and capabilities. small and medium firms that did so. The higher share Chapter 6.  LONGER-TERM IMPACTS: WILL COVID-19 LEAD TO WIDENING INEQUALITY? 99 Figure 6.5 Family businesses from wealthier households are more likely to have digital sales, Vietnam a. Family business with digital sales b. Share of sales from digital platforms 5 20 Share of family businesses (%) 4 15 Share of sales (%) 3 10 2 5 1 0 0 Bottom Q2 Q3 Q4 Top Bottom Q2 Q3 Q4 Top 20 20 20 20 Jun/Aug 2020 Jan 2021 Mar 2021 Jun/Aug 2020 Jan 2021 Mar 2021 Source: World Bank Vietnam COVID-19 household monitoring surveys (rounds 2, 4, and 5). Note: Household welfare quintiles (Q) are based on household consumption per capita in 2018. Figure 6.6 Higher shares of large firms in Vietnam Figure 6.7 Large firms in Vietnam are using are using digital platforms digital platforms for more sophisticated business functions a. Firms using digital platforms b. Firms using digital platforms for back-end purposes for front-end purposes 80 100 100 Share of firms using digital platforms (%) 70 Share of firms (%) Share of firms (%) 80 80 60 60 60 50 40 40 40 1 2 3 1 2 3 June 2020 Sept/Oct 2020 January 2021 Survey round Survey round Small Medium Large SMEs Large Source: World Bank COVID-19 Business Pulse Surveys. Source: World Bank COVID-19 Business Pulse Surveys. Note: Back-end purposes include business administration, production planning, and supply chain management. Front-end purpose include marketing, sales, payment methods, and service delivery. 100 A YEAR DEFERRED – EARLY EXPERIENCES AND LESSONS FROM COVID-19 IN VIETNAM Among formal firms, small firms have suffered Chronic conditions among the most during the pandemic. Many firms had to ethnic minorities temporarily or permanently close because of COVID-19. According to the World Bank COVID-19 Business Pulse Ethnic minorities were adversely affected during surveys, the share of businesses that were closed in COVID-19 across nonmonetary dimensions. Living in June 2020 was 3.3 percent, decreasing to 1.9 percent predominantly rural and remote areas, ethnic minorities in both round 2 and round 3. Yet small firms have had were less affected by social distancing and outbreaks in the most difficulties in reopening; by January 2021, 2.3 urban centers, and they did not experience heightened percent of small businesses remained closed (figure 6.8). income losses during COVID-19. However, differences In contrast, more large firms reacted quickly by closing in food and health conditions during COVID-19 highlight at the start of the pandemic but most had reopened the ongoing nature of existing disparities in these by January 2021. The negative effects on sales also nonmonetary dimensions. Health, nutrition, and food lingered the longest for small firm (figure 6.9). Large firms have long-term impacts on human development and are experienced about a 30 percent decrease in June 2020 also important determinants for intergenerational poverty sales relative to the previous year, but sales recovered reduction and upward economic mobility. in January 2021 to just under 5 percent less than the previous year (January 2020). However, small firms During COVID-19, ethnic minorities and poorer experienced a decrease of almost 40 percent in sales households were the most concerned about food in June 2020 relative to the previous year, and January security, which may reflect financial uncertainty and 2021 sales were still 20 percent less than for the same a general inability to stock up on food (figure 6.10). period in the previous year. Although food security concerns subsided substantially, trends persisted across some groups. In keeping with prepandemic trends, food insecurity and low dietary diversity appear more acute among ethnic minority Figure 6.8 Small Vietnamese businesses have Figure 6.9 Negative effects on sales have lingered been the slowest to recover from closures longest for small Vietnamese businesses 6 0 Change in sales relative to previous year (%) Temporarily or permantly closed −10 Share of firms (%) 4 −20 2 −30 −40 0 June 2020 Sept/Oct 2020 January 2021 June 2020 Sept/Oct 2020 January 2021 Small Medium Large Small Medium Large Source: World Bank COVID-19 Business Pulse Surveys. Source: World Bank COVID-19 Business Pulse Surveys. Chapter 6.  LONGER-TERM IMPACTS: WILL COVID-19 LEAD TO WIDENING INEQUALITY? 101 populations in Vietnam (figure 6.11). Because roughly The key determinants of undernutrition among 75 percent of Vietnam’s ethnic minority groups live in ethnic minority populations are multisectoral. Ethnic the Northern Mountains and Central Highlands regions, minority children are fed less nutritious food, get sick these trends illustrate how demographics and geography more frequently, and have less access to health services influence the extent of nutrition disparities throughout the as well as water and sanitation resources compared to country (Mbuya, Atwood, and Huynh 2019). majority children (Mbuya, Atwood, and Huynh 2019). On average, women living in mountainous and remote areas In recent decades, Vietnam has been recognized get married younger, have lower educational levels, and for its remarkable improvements in nutritional receive less reproductive care compared to their peers status, but progress is slowing down as stunting in lowland and urban areas. Poverty, an important basic has stagnated. Between 2000 and 2020, the national determinant of undernutrition, is also concentrated among stunting rates dropped by nearly half from 36.5 percent ethnic minorities; although ethnic minority groups account to 19.6 percent.40 However, Vietnam’s childhood stunting for only 14 percent of the total population, they account rate (children under 5) has stagnated in recent years. The for 73 percent of those living in poverty in Vietnam, World Bank Human Capital Index (HCI) estimates show according to 2016 estimates. increased stunting rates between 2010 and 2020. In early 2020 before the pandemic, the stunting rate among the Kinh majority was 17.1 percent whereas it was much higher among ethnic minority groups at 32.0 percent. In fact, the gap in stunting prevalence between the majority and minority groups widened from a 14.3-percentage- point difference in 2010 to a 17.9-percentage-point difference in 2020.41 Figure 6.10 Ethnic minority and poor households in Vietnam are more likely to worry about food a. Households worrying about food, by welfare quintile b. Households worrying about food, by ethnic minority or majority status 60 60 50 50 Share of households (%) Share of households (%) 40 40 30 30 20 20 10 10 0 0 Bottom 20 Q2 Q3 Q4 Top 20 Kinh Ethnic minority May/June 2020 Jun/Jul 2020 Aug/Sept 2020 May/June 2020 Jun/Jul 2020 Aug/Sept 2020 Source: World Bank Vietnam COVID-19 household monitoring surveys (rounds 1–3). Note: Household welfare quintiles (Q) are based on household consumption per capita in 2018. Reference period is shown and is the last 30 days from date of interview. 102 A YEAR DEFERRED – EARLY EXPERIENCES AND LESSONS FROM COVID-19 IN VIETNAM Figure 6.11 Fewer Vietnamese households are eating less, but gaps remain across socioeconomic groups a. Households unable to eat healthy and nutritious food b. Households that ate a few kinds of food 60 60 50 50 Share of households (%) Share of households (%) 40 40 30 30 20 20 10 10 0 0 May/June 2020 Jun/Jul 2020 Feb 2021 May/June 2020 Jun/Jul 2020 Feb 2021 Kinh Ethnic minority Kinh Ethnic minority Source: World Bank Vietnam COVID-19 household monitoring surveys (rounds 1, 2, and 5). Notes: Reference period is shown and is the last 30 days from date of interview. Health services were largely accessible throughout households (75 percent) are also classified as bottom the pandemic, and households did not defer or avoid 40 whereas two-thirds (66 percent) of ethnic majority necessary and routine health check-ups. Nearly all households are classified as top 60. respondents from the World Bank COVID-19 household monitoring surveys (96 percent and 98 percent in rounds A gender-biased crisis 1 and 2, respectively) reported that their households were able to access medical treatment if needed. In past economic crises, men were typically more Access to these services was consistent across the affected in the labor market, because of lost welfare distribution, geography (that is, urban and rural). employment, than women. Women may even enter Likewise, in round 1 of data collection, most households 42 the labor market to cope with the loss or reduction of with children under the age of two reportedly brought their household income (for example, Bandiera et al. 2019; children to a health center for immunizations (86 percent) Frankenberg, Thomas, and Beegle 1999), thereby and most households with pregnant women were able temporarily reducing the gender gap in labor market to access a health facility for antenatal care (89 percent) participation. Although this effect might dissipate when the within the last three months.43 economy recovers, some crises may lead to persisting level of higher female labor force participation, especially Despite those positive numbers, reporting during when the economy also introduced transformative COVID-19 reconfirmed some existing disparities structural transformations, such as the Lanham Act of related to the use of health services across groups. 1940, in which the United States government introduced Antenatal care visits were more common for the top the first and only federally administered universal 60 (91 percent) than for the bottom 40 households (85 childcare program to help mothers to participate in war percent) and were more common for Kinh majority (90 production efforts (Herbst 2017). Recent studies show percent) households than for ethnic minority households that the war-induced crisis had positive long-run effects on (84 percent). These differences across subgroups female labor force participation in the United States and are consistent with broader household demographic that those effects persisted even after the war (Acemoglu, composition: three-fourths of surveyed ethnic minority Autor, and Lyle 2004; Goldin and Olivetti 2013). Chapter 6.  LONGER-TERM IMPACTS: WILL COVID-19 LEAD TO WIDENING INEQUALITY? 103 Figure 6.12 Distribution of household members who stopped work or reduced work hours to take on childcare 60 Share of households with children (%) 50 40 30 20 10 0 Mother only Mother and father Father only Other family members All households Married couple households Source: World Bank Vietnam COVID-19 household monitoring surveys (round 1). The current COVID-19 crisis is, however, unlike typical that responsibility was shared between the father and past economic crises because it is “self-imposed” the mother in close to 30 percent of households. In by mobility restrictions, business shutdowns, school only 15 percent of households did fathers take the sole and institutional childcare closures, or stay-at-home responsibility, and the remaining 4 percent of households orders (Alon et al. 2020). The issue of childcare arose as relied on other family members. a key concern and a prerequisite for economic recovery. Women typically bear a disproportionate responsibility of childcare around the world, and the COVID-19 pandemic has exacerbated the pressure on women’s time. FUTURE PLANS ARE AFFECTED Temporary school and institutional childcare facilities closures are expected to exert a greater pressure on Changed plans among households women’s time, away from paid work activities. Close to 70 percent of households interviewed in the World In January 2021, 16 percent of households reported Bank Vietnam COVID-19 monitoring surveys have at that they had changed their plans in the last year least one child between the ages of 3 and 22. In slightly because of COVID-19 (figure 6.13). The incidence of more than a quarter of households with a child, someone households reporting these changes was similar across in the household had to stop working or had to reduce the welfare distribution, reflecting the broad and varied hours worked to care for children staying home because economic impact channels that permeated across the of school closures. entire distribution and affected households in different ways. Delaying housing renovation or construction was Mothers are more likely than fathers to take up the the most deferred activity; in rural areas, self-construction added childcare responsibility at the expense of their of homes is common. A host of other responses also employment (figure 6.12). The distribution does not differ ranged from delays in making investments in farming, much when looking at all households or only at married opening businesses, repaying loans, seeking health couple households. In more than half of households, the care, and traveling, to family planning such as marriage care responsibility fell solely on the mother, whereas or starting a family. 104 A YEAR DEFERRED – EARLY EXPERIENCES AND LESSONS FROM COVID-19 IN VIETNAM How households changed their plans for the future secondary levels, middle-class families spend over differed across the welfare distribution (figure 6.14). seven times as much on coaching and study materials Richer households delayed purchases of land, homes, than poor and economically vulnerable households or apartments. Poorer households deferred spending on do. For children around age 8, the participation rate in education. The impacts to poorer households are arguably extra classes is almost twice as high among top-quintile more consequential, because delays in investments in households compared to bottom-quintile households. education have longer-term generational impacts. These Among older children aged 12, the participation rates impacts compound already large differences in education in top-quintile households is almost three times higher. investment between poor and wealthy households. In Moreover, among wealthy households, participation 2018, at every level of education, Vietnamese families in extra classes increases with age, whereas, in the in the middle class spent three to four times more poorest households, participation declines with age. on education than poor or economically vulnerable These differences in education investment create uneven households. These expenditures include tuition and opportunities and realities for future education attainment, fees, coaching, enrichment, and uniforms. At the upper- skill development, and access to jobs. Figure 6.13 Vietnamese households changed plans because of income declines, by income quintile 20 Share of households (%) 15 10 5 0 Bottom 20 Q2 Q3 Q4 Top 20 Source: World Bank Vietnam COVID-19 household monitoring surveys (round 4). Note: Household welfare quintiles (Q) are based on household consumption per capita in 2018. Figure 6.14 Poorer Vietnamese households were more likely to forgo investments into education 10 Share of affected households (%) 8 6 4 2 0 Purchase of Car Purchase of Housing construction/ Education Other land/house/apt renovation Bottom 20 Q2 Q3 Q4 Top 20 Source: World Bank Vietnam COVID-19 household monitoring surveys (round 4). Note: Household welfare quintiles (Q) are based on household consumption per capita in 2018. Chapter 6.  LONGER-TERM IMPACTS: WILL COVID-19 LEAD TO WIDENING INEQUALITY? 105 Dampened business investments and Business expectations suffered greatly from the expectations for the future economic impacts of the pandemic, and firms remain pessimistic about the future (figure 6.17). In all three Disrupted investments may become a drag on future survey rounds, firms expected sales in the next six months productivity. By January 2021, 65 percent of firms had to drop to below 80 percent of what they were during the delayed or reduced their planned investment because of same period the previous year. Business expectations the pandemic (figure 6.15). Further, there is evidence that reached their nadir in October 2020 (65 percent) but had some sectors are disproportionally affected. Agricultural recovered to some extent by January 2021 (77 percent). firms, followed by manufacturing firms, are the most With the survey round 1 in June 2020 as the reference affected, with about 85 percent of agricultural firms and group, the outlook was statistically significantly worse in 75 percent of manufacturing firms delaying or reducing round 2 (Sep/Oct 2020) before getting much better in their planned investments. With the slight improvement round 3 (January 2021). This recovery most likely stems in business expectations in January 2021, there are from Vietnam’s impressive performance in containing signs of recovery. Only 1.7 percent of firms expect future the pandemic up to that point. However, the largest and delays or reduction in their planned investment in the most recent outbreak in April 2021 may damper this next six months (figure 6.16). Despite that improvement, slight optimism. it is clear that past disruptions increased uncertainty for the businesses that suffered from them. Agricultural firms remain the group with the most pessimistic outlook (1.8 percent expect future delays). Figure 6.15 The pandemic disrupted the Figure 6.16 With improving business outlooks in investment plans of most Vietnamese firms, January 2021, fewer Vietnamese firms expect to especially agricultural businesses reduce investments reduced planned investment (%) Share of firms expecting to delay 90 1.9 or reduce future investment (%) Share of firms delayed or 80 1.8 70 1.7 60 1.6 50 1.5 Agriculture Manufacturing Commerce Other Agriculture Manufacturing Commerce Other services services Sector Sector 95% confidence intervals 95% confidence intervals Source: World Bank COVID-19 Business Pulse Surveys. Source: World Bank COVID-19 Business Pulse Surveys. Note: Lines represent 95 percent confidence intervals. Note: Lines represent 95 percent confidence intervals. 106 A YEAR DEFERRED – EARLY EXPERIENCES AND LESSONS FROM COVID-19 IN VIETNAM Figure 6.17 Business expectations of Vietnamese Figure 6.18 In Vietnam, business expectations for firms reached the lowest level in October 2020 the next six months are more positive for firms but have since recovered with higher sales growth in the past month 100 85 Mean expected change in sales Mean expected change in sales in next six months (%) in next six months (%) 80 80 60 75 40 70 20 65 0 60 1 2 3 −100 −50 0 50 100 Round Change in sales in past 30 days compared to last year (%) 95% confidence intervals Source: World Bank COVID-19 Business Pulse Surveys. Source: World Bank COVID-19 Business Pulse Surveys. Note: The graph shows average weighted expectations, controlling Note: The diagram is a binned scatterplot. for firm fixed effects. Lines represent 95 percent confidence intervals. Further, there are signs that the reallocation shock DISTRIBUTION- due to COVID-19 may be a persistent shock. If we expect all firms to recover to their prepandemic levels, SENSITIVE POVERTY those that were more negatively affected should have had PROJECTIONS— more positive expectations. However, the survey results suggest that firms with better recent business outcomes LONGER-TERM are also more likely to be optimistic about the future: there SIMULATION is a positive correlation between future expected sales and change in sales in the past 30 days (figure 6.18). This result is also consistent with evidence from the past three Disparities in nonmonetary dimensions of well-being survey rounds, which show that firms that experienced can lead to widening monetary inequality in the higher sales growth in the previous rounds are more likely future. Examples in the preceding sections illustrated the to do so in the next survey round. The results suggest potential widening of existing monetary and nonmonetary that there may be a divergent path for recovery whereby gaps caused by COVID-19, even during an early period better-performing firms keep gaining ground while worse when Vietnam managed the crisis extremely well performing firms continue to lose market shares. compared to most others in the world. Moreover, these gaps have long-term consequences: lost education is unlikely to be recovered, with consequences for lifetime wages; sold assets cannot produce future incomes; and employment scarring is also associated with lower lifetime earnings. Minimizing future disparities will require forward-looking policies and improving existing support systems. This section describes longer-term poverty trajectory scenarios, with the main purpose of illustrating the potential impacts of increasing inequality on poverty.44 Chapter 6.  LONGER-TERM IMPACTS: WILL COVID-19 LEAD TO WIDENING INEQUALITY? 107 Poverty projections with distributional For the first time since the aftermath of the global assumptions financial crisis, the welfare trajectory is potentially being significantly altered from a distributional Concepts of poverty reduction, inequality and perspective. Over almost three decades (1992–2018), inclusive growth are connected. The literature notes the only instance when inequality increased substantially the importance of the impact of inequality on poverty in Vietnam was in 2010, and it then quickly reverted back reduction, highlighting a “double-dividend” effect down in 2012. In 2018, inequality was inching upward, and (Alvaredo and Gasparini 2015; Bourguignon 2004). At changes in the distribution hampered poverty reduction. a macro level, changes in poverty can be decomposed Distribution-sensitive welfare estimates in 2020 show, at into a combination of growth and redistribution effects the minimum, a slowdown in poverty reduction and, in (Bourguignon 2003, 2004; Datt and Ravallion 1992; scenarios with increasing inequality, possible reversals of Ferreira 2012). As a growth effect, poverty reduction can poverty rates. This subsection discusses poverty trends be driven by growth in mean income or in consumption. under scenarios of growth and redistribution at a national The second channel is redistribution, or through changes level. Longer-term projections of poverty are influenced in inequality. Reducing inequality has a double-dividend by assumptions of inequality. effect because it promotes poverty reduction today and accelerates poverty reduction in the future. Lower levels In illustrating longer-term poverty trajectories, the of inequality have been empirically associated with higher main objective is of illustrating the potential impacts growth elasticity of poverty reduction. of increasing inequality on poverty reduction in Vietnam in a post-COVID-19 setting. The distribution- Over the past decade, Vietnam’s welfare trajectory sensitive poverty projections in this section follow has been primarily growth driven with a smaller role methods described in Lakner et al. (2020). The growth from redistribution as a channel of poverty reduction of household consumption is assumed to align with the (figure 6.19, panel a). From 2010 to 2018, about 85 projections of gross domestic product per capita growth. percent of poverty reduction was attributed to growth of Assumptions on the shape of the growth incidence curve the mean of household consumption. Redistribution had of household welfare and the degree of inequality affect a stronger impact in the earlier half of the decade than how growth passes through to households differently in the latter. Relative inequality over the past decades in along the distribution. When inequality is present, Vietnam has remained remarkably stable. The Gini Index households do not experience the same rates of growth was 35.6 in 1992 and 35.7 in 2018 (figure 6.19, panel b). in household welfare. In recent periods, the growth of the bottom 40 percent of the population has been lower than the national average The simulation allows for distribution-sensitive (figure 6.19, panel c). Although relative inequality is not poverty projections by assuming growth passes high compared to other developing East Asia and Pacific through to households differently along the economies, absolute gaps were increasing before the distribution. This is done using specific parameterization pandemic (figure 6.19, panel d). The absolute difference assumptions of what growth looks like across the welfare in annual per capita consumption between the poorest distribution (growth incidence curves), which can be and richest 10 percent has increased from VND 26 million either linear or convex under the utilized approach. in 2010 to VND 58 million in 2018. Empirically, the growth incidence curve appears more linear than convex in Vietnam (figure 6.20). Interestingly, but not fortunately, the shape of the growth incidence curve has reverted in the sense that, in the early period (2010–12), the highest growth rates were observed at the lower ends of the distribution. However, in later periods (2014–18, and 2016–18), the highest rates of growth were observed at the higher ends of the distribution. 108 A YEAR DEFERRED – EARLY EXPERIENCES AND LESSONS FROM COVID-19 IN VIETNAM Figure 6.19 Inequality has been stable in Vietnam, but redistribution has not contributed to poverty reduction in recent periods a. Redistribution did not contribute to poverty reduction from b. Official inequality trends have been stable over the 2014 to 2018 ($3.20/day 2011 PPP) long term 5 Percentage point change in poverty rate 0 50 -5 40 −10 30 Index −15 20 −20 10 −25 0 2010–18 2010–14 2014–18 1998 2000 2002 2004 2006 2008 2010 2012 2014 2016 2018 Growth Distribution Gini index MLD index c. In recent years, growth at the bottom of the d. Absolute inequality is widening distribution slowed down (relative to the mean) 10 40,000 35,000 95% confidence intervals 8 30,000 25,000 Growth (%) 6 20,000 4 15,000 10,000 2 5,000 0 0 2010–12 2012–14 2014–16 2016–18 2010 2012 2014 2016 2018 Growth of the bottom 40 percent (%) 90–10 Percentiles Average growth (%) 90–50 Percentiles 80–20 Percentiles Source: World Bank calculation using the Vietnam Household Living Standards Survey, PovcalNet, and Pimhidzai and Niu 2021. Note: MLD = mean log deviation. Chapter 6.  LONGER-TERM IMPACTS: WILL COVID-19 LEAD TO WIDENING INEQUALITY? 109 Figure 6.20 Growth incidence curves, selected periods, Vietnam 8 6 Annual growth (%) 4 2 0 −2 2010–128 2012–14 2014–16 2010–18 2014–18 2016–18 National Source: World Bank calculation using the Vietnam Household Living Standards Survey. Note: Figure shows anonymous distribution, that is, not a panel. A few pieces of empirical evidence suggest that available. In a no-crisis context in which growth was modeling poverty projections with a positive increase not downgraded because of the COVID-19 pandemic in Gini may be more accurate than modeling without. and inequality was not increasing, poverty in 2020 was Changes to the distribution are based on assumptions, estimated to be 5.4 percent (blue line in figure 6.21). In but observations from the World Bank COVID-19 a context in which growth is downgraded because of the household monitoring surveys in Vietnam suggest pandemic, poverty would reach 5.2 in 2021 (about a one- that it is likely that inequality has increased. In earlier year delay; orange line). Under conditions of a growth chapters, it was shown that, based on the construction of downgrade and inequality increase, poverty would reach an income index, the bottom 20 are not yet experiencing 5.3 in 2022 (about a two-year delay, yellow line). a clear income recovery, and the Midlands and Northern Mountains region is also the only region where the A downgrade in growth alone would not stall income index continues to decline. Based on recent poverty reduction, but, in a scenario of a downgrade official household data from the Vietnam GSO, the combined with increasing inequality, poverty change in the Gini coefficient increased 1.2 percent from reduction from 2019 to 2020 would stagnate. In the 2016 to 2018 (from 35.3 to 35.7). The small increase in scenario in which growth declined but inequality remained inequality also coincides with a slower pace of poverty unchanged, poverty was estimated to continue to decline reduction. Moreover, micro-macro simulations conducted from 2019 to 2020 (6.0 to 5.4 percent, respectively; see independently (see chapter 4) also found inequality to be blue line in figure 6.21). However, with the addition of rising in 2020 under COVID-19 scenarios. rising inequality starting in 2018, poverty reduction stalled between 2019 and 2020 (6.3 percent in both years; see Results—inequality plays a role in yellow line in figure 6.21). poverty reduction After COVID-19, poverty reduction will get back on A downgrade in growth from the COVID-19 pandemic track, but higher inequality will slow the pace of slowed poverty reduction by about one year, and a an already delayed poverty reduction trajectory. 1 percent increase in the Gini may delay poverty Assuming growth returns to a pre-COVID-19 trajectory, reduction by another year (figure 6.21). These poverty is expected to fall once again. Even so, it will estimates are based on projections starting from 2018, be behind compared to projections without inequality the most recent year for which official poverty data are increasing and without the onset of COVID-19. 110 A YEAR DEFERRED – EARLY EXPERIENCES AND LESSONS FROM COVID-19 IN VIETNAM Figure 6.21 Distribution-sensitive poverty projections for Vietnam, 2018–23 7.5 7.0 Poverty rate at $3.20/day (2011 PPP) 6.6 6.5 6.3 6.3 6.6 6.0 5.8 6.0 5.7 5.7 5.3 5.5 5.4 5.1 5.4 5.2 5.1 5.0 4.8 5.0 4.8 4.5 4.4 4.3 4.0 4.0 2018 2019 2020 2021 2022 2023 No, crisis, No change in Gini Crisis, No change in Gini No crisis, +1% change in Gini Crisis, +1% change in Gini Source: World Bank staff estimations using Vietnam Household Living Standards Survey, 2018. Note: Poverty rates in 2018 are based on actual survey data, and rates in 2019 onward are based on GDP per capita growth rates. Growth rates between crisis and no-crisis scenarios differ in 2020 and 2021. Changes in inequality, if any, are assumed to start in 2018. Distributionally sensitive simulations are based on Lakner et al. (2020). Poverty projections under different simulation methods yield different results. PPP = purchasing power parity. Figure 6.22 Small changes in inequality can have The adverse impact of inequality on poverty large impacts on poverty in Vietnam, 2020 reduction can be just as large as the impact of a growth downgrade (figure 6.22). A growth downgrade due to the crisis and without any change in inequality 1.0 Percentage point change in poverty would increase poverty in 2020 to 5.7 percent, or by rate at $3.20/day (2011 PPP) 0.8 0.3 percentage points. In the absence of COVID-19 but a 1 percent increase in inequality annually from 2018, 0.6 poverty in 2020 is estimated to be 5.8 percent, or an increase of 0.4 percentage points from the no-impact 0.4 scenario. A combination of a growth downgrade and a 0.2 1 percent increase in inequality would elevate poverty to 6.3 percent in 2020, or an increase of 0.9 percentage 0.0 points compared to the no-impact scenario. Growth 1% increase Growth downgrade in inequality downgrade and 1% increase in Gini Small increases in inequality can slow down poverty reduction, especially when accumulated over multiple years (figure 6.23). The difference in poverty projections under the same growth scenario, but with various Gini assumptions, widens over time. A growth Source: World Bank staff estimations using Vietnam Household Living Standards Survey, 2018. downgrade from a no-crisis to crisis scenario increases Note: Changes in poverty in 2020 compared to a no-impact poverty estimates 0.3 percentage point in 2020 (from 5.4 scenario. The 2020 poverty rate in a no-crisis and no-inequality percent to 5.7 percent). However, a 1 percent increase increase scenario is estimated to be 5.4 percent. PPP = purchasing power parity. in Gini would increase poverty by a higher rate under Chapter 6.  LONGER-TERM IMPACTS: WILL COVID-19 LEAD TO WIDENING INEQUALITY? 111 both the no-crisis and the crisis scenarios. Under the no- and inequality. Yet the distribution-sensitive poverty crisis scenario, poverty would increase by 0.4 percentage projections presented here for 2020 are in the same point, and under the crisis scenario poverty increases range as the 2020 poverty estimates calculated using by 0.6 percentage point. Globally, it was also found that the micro-macro simulation methods in chapter 4. Under a 1 percent decrease in the Gini index in every country micro-macro simulations, the no-crisis poverty rate in would lower global poverty more than a 1 percentage 2020 was 5.76 percent and the crisis poverty rate was 6.0 point increase in GDP per capita (Lakner et al. 2020). percent. Simulations in this chapter are more long-term Bergstrom (2020) also finds that a 1 percent reduction and extend beyond 2020, which allows for discussions in inequality leads to a more than 1 percent increase in on how much the progress of poverty reduction has mean incomes, based on global analysis. been delayed. These numbers are estimates and will be continuously updated as more recent information Estimates of distribution-sensitive poverty becomes available. Actual 2020 poverty rates based on projections in this chapter are in the same range official data are forthcoming, and long-term projections as poverty rates simulated for 2020 in chapter 4. will be updated reflecting the new benchmark. Projections are estimates, and different simulation methods will yield different exact projections of poverty Figure 6.23 Inequality impacts can accumulate over time, Vietnam, 2020–23 1.2 Percentage point change in poverty rate at $3.20/day (2011 PPP) 1.0 0.8 0.6 0.4 0.2 0.0 Growth downgrade 1% increase in inequality Growth downgrade and 1% increase in Gini 2020 2021 2022 2023 Source: World Bank staff estimations using Vietname Household Living Standards Survey, 2018. Note: Based on estimated poverty rates in 2020. No-crisis and crisis growth rates differ in 2020 and 2021. PPP = purchasing power parity. 112 A YEAR DEFERRED – EARLY EXPERIENCES AND LESSONS FROM COVID-19 IN VIETNAM Notes 37  For example, Dabla-Norris et al. 2015 indicate that a higher Gini coefficient leads to lower and less stable economic growth. Moreover, when the share of total income held by the richest 20 percent of people increases by 5.0 percentage points, economic growth falls by 0.4 of a percentage point. At the same time, when the share of total income held by the poorest 20 percent of people increases by 5.0 percentage points, growth increases by 1.9 percentage points. Increased income shares for the second- and third-poorest 20 percent of the population also increase growth. 38  Because of survey limitations as a phone-based survey, the World Bank Vietnam COVID-19 phone-based household monitoring surveys were able to reflect on some but not all nonmonetary dimensions of well-being during COVID-19. 39  Based on data from the Global Findex database. 40  From the Ministry of Health, National Institute of Nutrition, Main findings of General Nutrition Survey 2019–20. 41  Likewise, the HCI data highlight wide disparities across income and ethnic minority groups. According to the 2020 HCI, the productivity of a child born today as a future worker exhibits a 27-percentage-point gap between the top and bottom 20 percent of the income distribution of Vietnamese households. This is high compared to the 15-percentage-point average among 50 countries for which HCI estimates are disaggregated by socioeconomic status. The disparity is even wider for the not stunted rate, presenting a 35-percentage-point gap between the top and bottom 20 percent, which well exceeds the 19-percentage-point average. 42  These variables were not included in the second round of data collection. 43  Among the households that elected not to bring their children to a health facility for immunizations and/or that had pregnant women who did not seek antenatal visits, about one in five cited fear of contracting COVID-19 as the deterring reason although the most common reason was simply that immunizations or postnatal care were not required for those households. 44  Simulation strategies here differ than those in chapter 4 because there is a different purpose. The purpose of the simulations presented here is to illustrate how the addition of inequality would alter the trajectory of poverty. References Acemoglu, Daron, David H. Autor, and David Lyle. 2004. “Women, War, and Wages: The Effect of Female Labor Supply on the Wage Structure at Midcentury.” Journal of Political Economy 112 (3): 497–551. Alon, Titan M., Matthias Doepke, Jane Olmstead-Rumsey, and Michele Tertilt. 2020. “The Impact of COVID-19 on Gender Equality.” NBER Working Paper 26947 National Bureau of Economic Research, Cambridge, MA. Alvaredo, Facundo, and Leonardo Gasparini. 2015. “Recent Trends in Inequality and Poverty in Developing Countries.” In Handbook of Income Distribution, vol. 2A, edited by Anthony B. Atkinson and François J. Bourguignon, 697–805. Handbooks in Economics Series. Amsterdam: North-Holland. Bandiera, Oriana, Niklas Buehren, Markus P. Goldstein, Imran Rasul, and Andrea Smurra. 2019. “The Economic Lives of Young Women in the Time of Ebola: Lessons from an Empowerment Program.” World Bank, Washington, DC. Bergstrom, K.A. 2020. The Importance of Inequality Toward Poverty Reduction. Unpublished Working Paper. Bourguignon, François J. 2003. “The Growth Elasticity of Poverty Reduction: Explaining Heterogeneity across Countries and Time Periods.” Working Paper 28104, World Bank, Washington, DC. Bourguignon, François J. 2004. “The Poverty-Growth-Inequality Triangle.” Working Paper 125, Indian Council for Research on International Economic Relations, New Delhi. Chapter 6.  LONGER-TERM IMPACTS: WILL COVID-19 LEAD TO WIDENING INEQUALITY? 113 Dabla-Norris, E., K. Kochhar, N. Suphaphiphat, F. Ricka, and E. Tsounta. 2015. Causes and Consequences of Income Inequality: A Global Perspective. IMF Staff Discussion Note SDN/15/13. Washington, DC: International Monetary Fund. Datt, Guarav, and Martin Ravallion. 1992. “Growth and Redistribution Components of Changes in Poverty Measures: A Decomposition with Applications to Brazil and India in the 1980s.” Journal of Development Economics 38 (2): 275–95. Ferreira, Francisco H. G. 2012. “Distributions in Motion: Economic Growth, Inequality, and Poverty Dynamics.” In The Oxford Handbook of the Economics of Poverty, edited by Philip N. Jefferson, 427–62. New York: Oxford University Press. Frankenberg, E., D. Thomas, and K. Beegle. 1999. “The Real Costs of Indonesia’s Economic Crisis: Preliminary Findings from the Indonesia Family Life Surveys.” Land and Population Working Paper 99-04, RAND - Labor and Population Program, RAND, Santa Monica, CA. Goldin, Claudia, and Claudia Olivetti. 2013. “Shocking Labor Supply: A Reassessment of the Role of World War II On Women’s Labor Supply.” American Economic Review 103 (3): 257–62. GSO (General Statistics Office). 2021b. “Report on the COVID-19 Impacts on Labour and Employment Situation in the First Quarter of 2021.” GSO, Hanoi, April 16. https://www.gso.gov.vn/en/data-and-statistics/2021/04/report-on-the-covid-19-impacts-on-labour- and-employment-situation-in-the-first-quarter-of-2021/. Herbst, Chris M. 2017. “Universal Child Care, Maternal Employment, and Children’s Long-Run Outcomes: Evidence from the US Lanham Act of 1940.” Journal of Labor Economics 35 (2): 519–64. Lakner, Christoph, Daniel Gerszon Mahler, Mario Negre, and Espen Beer Prydz. 2020. “How Much Does Reducing Inequality Matter for Global Poverty?” Global Poverty Monitoring Technical Note 13, World Bank, Washington, DC. Mbuya, Nkosinathi V.N., Stephen J. Atwood, and Phuong Nam Huynh. 2019. Persistent Malnutrition in Ethnic Minority Communities of Vietnam: Issues and Options for Policy and Interventions. International Development in Focus. Washington, DC: World Bank. Pimhidzai, Obert, and Chiyu Niu. 2021.Shared Gains: How High Growth and Anti-Poverty Programs Reduced Poverty in Vietnam - Vietnam Poverty and Shared Prosperity Update Report (English). Washington, DC: World Bank Group. 114 A YEAR A YEAR DEFERRED – EARLY EXPERIENCES AND LESSONS DEFERRED FROM – EARLY COVID-19 EXPERIENCES AND LESSONS FROM COVID-19 IN VIETNAM IN VIETNAM Chapter 7. POLICY CONSIDERATIONS There is time to learn from early experiences to improve policy responses and understanding of vulnerabilities, not only for the remainder of the COVID-19 (coronavirus) crisis but also for the future. Fortunately, before the fourth wave, the impacts from COVID-19 in Vietnam were mild relative to the rest of the world and households could cope on their own for the most part, with poverty rates in 2020 still estimated to be on a downward trajectory, albeit reducing at a slower pace. Firms were hit hard early on during the pandemic, but operating conditions slowly improved. Despite mild impacts, experiences before the fourth wave still highlighted existing inequities and revealed policy implementation challenges. The differential experiences between different groups of households and firms illustrate their preexisting vulnerabilities and the different capabilities in coping between groups. Observing how households and firms were affected, even if by mild shocks; how they adapted; who received assistance; and who could not cope well offers information on existing gaps in access to services, the importance of building resilience, and the need for better safety nets to guard against poverty traps and business closures. There is still some room to learn and to adapt policies to minimize adverse impacts on households and firms in the face of future shocks. There are lessons both for the short term—how to improve the household and firm response for the much more severe fourth wave—and for the long term—how to improve the broader social safety net for times of crisis and times of normalcy. Chapter 7.  POLICY CONSIDERATIONS 115 LEARN FROM IMPLEMENTATION CHALLENGES EARLY ON DURING THE COVID-19 PANDEMIC The experiences captured by the World Bank the cost of the assistance as actually implemented was COVID-19 monitoring surveys are an opportunity to even less, about 12 trillion Vietnamese dong (VND) understand the weakest links and who are the most compared to a budgeted VND 62 trillion. This disparity exposed to shocks to strengthen policies during a reflects the fact that only 1 million new informal worker new period when more effective interventions may beneficiaries were reached out of a target of 5 million, be needed. A range of health and fiscal policies helped primarily because of an inability to verify eligibility. Vietnam manage well during the pandemic. Although most policies were highly effective, not all policies led to The household response in April 2020 was too small large impacts, and some need to accelerate amid rising and its duration was too short. The most generous COVID-19 risks during the fourth wave. benefits were for a maximum of three months and for VND 1 million per affected person, compared to the Vietnam’s fiscal response mix early in the pandemic pre-COVID-19 average monthly per capita household was different from that of other countries in the consumption of VND 3.6 million. Chapter 5 estimates that, region, with far less spending on direct income as a consequence of poor implementation and design, support. Early on in the pandemic Thailand, Malaysia, only 0.1 percentage point of poverty was mitigated the Philippines, and Indonesia all budgeted more for by the household relief program. Much of this comes income support than Vietnam did (figure 7.1), even before from the design. A VND 208 trillion program perfectly considering its very low execution rate (Indonesia had implemented to cover the 32 million workers estimated executed 80 percent of its social protection response by the General Statistics Office to have been affected in budget by November of 2020). As chapter 4 discusses, the first quarter of 2021 would have reduced poverty by Vietnam spent twice as much on public investment, and 0.5 percentage points. accelerated spending than it did on income support. This is a very different pattern from other countries in The firm response faced similar implementation the region; China spent equally on both categories, and challenges as the household relief response. These all other countries either spent solely on income support policies were primarily in the form of deferments and or at least the significant majority. As a consequence, credits and were available for a longer period than was the overall support to Vietnamese households was the household relief. The initial constraint to policy access small when compared to other benchmarks such as was a lack of communication but this was remedied by the minimum wage. January 2021. Instead, the main constraint became the ineligibility to support programs and the difficulty in Implementation problems meant that the social application. Large firms were better able to access and assistance expansion and disbursement fell well benefit from government benefits than small and medium short of plans. Even though Vietnam budgeted less enterprises. Moreover, these policies were limited to for income support than other countries in the region, formal firms and informal businesses were mostly left out. 116 A YEAR DEFERRED – EARLY EXPERIENCES AND LESSONS FROM COVID-19 IN VIETNAM Figure 7.1 Fiscal response, by type, selected countries 15 Percent of GDP 10 5 0 Thailand Brazil Malaysia China Philippines Indonesia Vietnam Mexico Other spending Loans, equity and guarantees Additional health-related spending Additional spending on income support and revenue measures Average Source: International Monetary Fund (June 2020), World Bank staff estimates. Notes: The "other spending" category includes the forgone revenues and tax incentives. "Average" represents the mean of ther fiscal package of the countries presented in the chart. Data for Indonesia's fiscal package are based on the restuctured scheme of the package, published in the October 2020 monthly budget report (APBN Kita) IMPROVE THE DESIGN AND IMPLEMENTATION OF HOUSEHOLD AND FIRM SUPPORT DURING THE FOURTH WAVE There are lessons from experiences during the or loss for affected informal workers. Eligibility criteria COVID-19 relief rollout that can be used to strengthen was overly specific, which increased the complexity of responses for the fourth wave.45 Both the household implementation. To ensure timely and effective delivery and firm COVID-19 relief packages were well intentioned of assistance in the immediate aftermath of a massive but faced some implementation challenges on the ground. shock, targeting criteria could be set more broadly and This is a normal course when new policies are designed eligibility conditions should be reduced or simplified and implemented quickly. It would be beneficial to learn to ensure that all who need financial support have from the implementation to improve future program access to it. The support programs for firms were not design and implementation logistics. designed to target firms based on how much they were impacted by the COVID-19 pandemic: corporate tax Targeting criteria and mechanisms can be improved reductions applied to a large majority of firms earning and simplified for both households and firms. below 200 billion VND and the deferred tax payments Whereas existing beneficiaries were able to receive had no eligibility requirements related to revenues or benefits easily, new beneficiaries faced challenges to profits. Administrative relief packages to firms can also register and be verified. Intake and registration systems be simplified, and lines of relief can be increased in need to be made more nimble and able to process greater practicality such as reducing collateral requirements or numbers faster. New targeting methods are needed that assistance with accessing new markets. account for the lack of formal documentation of income Chapter 7.  POLICY CONSIDERATIONS 117 Identifying eligible households for expanding Health. Using this application, potential beneficiaries coverage is challenging in the short term and likely could fill in their information. Verification could also then would require a similar approach to that of Thailand. take place electronically through cross-referencing with Vietnam’s lack of a social registry means it could mostly other administrative databases such as social assistance expand only vertically (top-up payments to existing and poverty, National Devotees, and social and health beneficiaries) rather than also horizontally (temporary insurance. Village officials can then act as the last payments to new beneficiaries) as Indonesia and the verification step. Philippines did, as discussed in lessons for the longer term which follow. In response to the fourth wave, In the short term, technology can be leveraged to depending on how it unfolds and the extent of necessary facilitate self-registration and online registration lockdown containment measures, Vietnam could adopt a to identify informal workers for assistance. Several similar approach to that of Thailand. Thailand increased countries were more successful in reaching the informal benefits for the 8 million existing social assistance sector by applying online registration, such as Indonesia, beneficiaries—that is, the pre-COVID-10 vulnerable; Malaysia, Thailand, and the Philippines. Thailand however, the bulk of the 2.5 percent of gross domestic approved around 23 million applications from informal product spent on household transfers went to informal sector workers and farmers—more than half of the workers and farmers who were not considered vulnerable working-age population. Within a few weeks, more than 6 before the pandemic (World Bank 2021c). As a result, 23 million online benefit applications were validated in South million of the 31 million recipients in 2020 represented an Africa. Brazil registered about 27 million households in expansion of coverage. The number of new beneficiaries a matter of weeks through its online process. Vietnam, has risen to 33 million in 2021 (albeit on smaller benefits however, lacks a database on informal workers. than in 2020), meaning 90 percent of households are now covered. An important component of Thailand’s approach For the fourth wave, the size of the relief package was allowing individuals who believed they were eligible should be much bigger, with benefit levels to apply for assistance online. Similarly, Vietnam could significantly increased and coverage expanded provide assistance to any applying worker or household even if targeting problems will remain. The World that does not have a formal income above a certain level Bank high-frequency surveys found that about 30 through an online portal and verify this against the social percent of households experienced job loss or knew of security database. Doing so would potentially cover 81 someone who was looking for a job in the first quarter percent of households and be a significant temporary of 2021, before the onset of the 4th wave. Given a outlay, but it would provide widespread support with little more severe phase of COVID-19, extending the scope exclusion of affected households. of support is warranted. Adverse labor market impacts will unquestionably increase. Initial announcements Digitalizing the payment mechanisms would help indicate that the second cash support package to workers make payments more efficient, transparent, safe, (resolution 68) will focus on informal workers in selected and fast. The implementation of the COVID-19 support sectors and workers with a labor contract but who are program relied heavily on delivery of cash payments via ineligible for unemployment benefits. Benefits will be face-to-face exchanges during the physical distancing disbursed between May and December 20201 and cash and movement restriction periods. It was time-consuming support is higher at VND 1.5 million per person. However, and fraught with the possibility of error and corruption. initial announcements also indicate that workers will only Direct deposit into a checking account or cash card or be eligible to receive benefits once during this period. provision of mobile banking to beneficiaries would be safe, more efficient, and transparent. In Vietnam, one idea is to develop a phone application, like the health declaration that has been introduced by the Ministry of 118 A YEAR DEFERRED – EARLY EXPERIENCES AND LESSONS FROM COVID-19 IN VIETNAM STRENGTHEN RESILIENCE AND PROTECTION SYSTEMS FOR THE FUTURE High informality means that high shares of the The social protection system requires modernization population are outside the government’s line of sight to more adeptly respond to crises in the future. The and that they face disadvantages during crises. A lessons of COVID-19 discussed so far underscore the significant challenge for the future is providing safety importance of longer-term social assistance reforms. nets to the informal sector, or those affected by new Without a social registry Vietnam’s options and the crises, and that is where the social protection system creation of an integrated social protection system in the will need to modernize to react swiftly and decisively. short term are either to do relatively little to respond to Informality is extremely prevalent: 21 million households households in need or to cover much of the population in 2018, 81 percent of all households, had at least one somewhat indiscriminately. This highlights the need to household member who either has a wage job without a modernize the social assistance system to prepare for contract, is engaged in self-employed agriculture, or is the next crisis. More crises will emerge in the future engaged in self-employed business. Only 27 percent of that require a more sophisticated and digital response. a predominantly informal workforce had social insurance Guarding against risks is essential to prevent households coverage in 2019. Global evidence of an uncoordinated from falling back into poverty in the event of shocks recovery of formal sector output and informal sector or disasters that can be poverty traps. Developing an employment suggests that informal workers and inclusive and responsive social protection system is at businesses will face a slower recovery than those in the the core of this objective. COVID-19 has highlighted formal sector. challenges in delivering assistance to new vulnerable groups. Without modernization, the same implementation Financial inclusion is still limited for certain challenges experienced during COVID-19 will manifest in vulnerable groups. The impacts of COVID-19 did the event of future crises. Digitization and modernization not necessitate large financial interventions. However, can also reduce staff burden, reduce errors, speed up behaviors still highlight that financial services are disbursements, and alleviate capacity constraints. underused by certain groups. Populations without COVID-19 affected countries like the Philippines and access to financial services are disadvantaged in growing Thailand considerably harder than Vietnam, but those savings or investible funds that can enhance credit countries were able to respond quickly and widely creation and capital accumulation. These disadvantages because of their strong existing safety nets systems; can further widen the gaps between the rich and poor. preparedness and investments in data were key (box 7.1). The delivery mechanism for the transfers made under the COVID-19 response relied heavily on cash payments via face-to-face exchanges. This impeded payments during the physical distancing and movement restriction periods. A financial inclusion strategy for Vietnam was established in early 2020. The use of direct deposit or digital payments can also help households get assistance faster. Digital payment pilots of regular social assistance cash transfers made via Viettel pay or Vietinbank in collaboration with VN Post in Cao Bang, Hue and Can Tho are great examples of improving implementation of the Government’s income support package during the COVID-19 pandemic. Chapter 7.  POLICY CONSIDERATIONS 119 Box 7.1 Emergency household support during COVID-19 in the Philippines The Philippine government approved a sizeable package (totalling 3.0 percent of gross domestic product) of fiscal response measures to mitigate the health and socioeconomic impacts of the COVID-19 pandemic, and to help jump-start economic recovery. The social protection pillar focused largely on financial support to the poor and vulnerable, with emergency cash transfers worth 5,000–8,000 Philippine pesos per month for two months to about 18 million households that are either poor or in the informal sector. The program cost 1.1 percent of gross domestic product, and additional social protection programs included employment support programs such as small businesses wage subsidies, cash assistance to displaced workers and overseas Filipino workers, and unemployment benefits for members of the social security system. An emergency employment program was also implemented for affected informal workers (see World Bank 2020a and 2020b). The cash transfers included both top-up benefits to about 10 million existing beneficiary households and a temporary expansion to cover 8 million more informal sector workers and vulnerable households. Unlike in Vietnam, the additional beneficiaries could be identified immediately because of significant historical investments in the Philippines’ social registry, Listahanan, from which the new beneficiaries were drawn. Having a standing registry made it possible for the country to get cash out quickly to a much larger number of households than were currently receiving assistance (World Bank 2020b). Despite those successes, the Philippines’ experience during COVID-19 also highlighted improvements needed in Listahanan to make it more adaptive during large shocks like COVID-19, lessons that should be taken into account when developing a modern social registry in Vietnam (World Bank 2020b). First, when expanding the list of eligible beneficiaries, existing data need to be dynamic and up-to-date; the data in Listahanan are from a 2015–16 survey sweep. Other countries such as Chile, Colombia, Pakistan, and Peru had dynamic social registries that were used to expand the list of eligible beneficiaries and so likely had more accurate responses. Alternatively, other countries such as Brazil, Jordan, and Thailand set up online applications for anyone to apply but verified eligibility by crosschecking against existing administrative databases using a national identifier. In the Philippines the process was paper-based and the lack of a national identifier hindered checking against databases, for example, to see if an applicant was already receiving assistance from another program. Second, although existing beneficiaries had cash cards that could be topped up, new beneficiaries relied upon house-to-house cash delivery or collection at pay-out points, which slowed receipt of benefits and was more dangerous during a pandemic. More global lessons about facilitating social protection responses during COVID are discussed in Grosh et al. (forthcoming). 120 A YEAR DEFERRED – EARLY EXPERIENCES AND LESSONS FROM COVID-19 IN VIETNAM BE OBSERVANT OF EXISTING AND WIDENING MONETARY AND NONMONETARY GAPS COVID-19 highlighted existing inequalities and Inequality can be expected to increase during differences in coping and adaptation. Even before COVID-19 for a range of reasons. Women bear a the onset of the COVID-19 pandemic, new signs of larger share of care responsibilities and their labor widening inequality were emerging. The absolute market activities were more adversely impacted than difference in annual per capita consumption between men’s. Informal workers have the least safety nets the poorest and richest 10 percent of the populations and experienced the most challenges when seeking increased from VND 26 million in 2010 to VND 58 million government cash support. The continuity of education in 2018. From 2016 to 2018, the household consumption was uneven during COVID-19, and the pandemic has growth of the bottom 40 percent of the population was potentially widened gaps in human capital formation lower than average. Education outcomes in Vietnam because of the uneven capacity of schools across the is varied by socioeconomic status,46 and progress in country. The future is digital, but there are gaps in digital reducing stunting had also stagnated. Women, those use and inclusion. Wealthier households are more able in the informal sector, and households in the bottom to participate in the digital economy both as sellers and 20 percent experienced the slowest household income as buyers on digital platforms. recovery between June 2020 and March 2021. In terms of coping during COVID-19, poor households were more Increasing inequality can have longer term reliant on external sources such as borrowing, while rich implications. Inequities today can have long-term households were better able to cope through the own consequences: lost education is unlikely to be recovered, means such as tapping into savings. with consequences for lifetime wages; sold assets cannot produce future incomes; and employment scarring is also associated with lower lifetime earnings. Larger businesses and wealthier households were also able to make investments to reap larger sales from digital orders, which may lead to widening inequality down the road Minimizing future disparities will require forward-looking policies and improving existing support systems. Chapter 7.  POLICY CONSIDERATIONS 121 Notes 45  See World Bank 2021d for a more detailed discussion on the April 2020 household relief package and implementation challenges. 46  The Human Capital Index is 0.85 for children in the richest 20 percent of households, compared to 0.58 for children in the poorest 20 percent. Unsurprisingly, children in the top 20 percent have higher nutrition, health, and education outcomes. For some outcomes, the gap between the top and bottom is larger in Vietnam than the average gap among other countries. The gap in the Human Capital Index between the top 20 and bottom 20 in Vietnam is 0.27 point, higher than the average gap among 50 countries (0.15 point). References Grosh, Margaret, Phillippe Leite, Matthew Wai-Poi, and Emil Tesliuc. Forthcoming. “A New Look at Old Dilemmas: Revisiting Targeting in Social Assistance.” World Bank, Washington, DC. World Bank. 2020a. “Promoting Competitiveness and Enhancing Resilience to Natural Disasters.” Sub-Program 2 Development Policy Loan Program Document, November 2020, World Bank, Washington, DC. World Bank.2020b. Philippines Economic Update, June 2020: Braving the New Normal. Washington, DC: World Bank. World Bank. 2021c. Thailand Economic Monitor, July 2021: The Road to Recovery. Washington, DC: World Bank. World Bank. 2021d. Vietnam Fiscal Note Series. Note 2: The Impact of COVID-19 Fiscal Policies on Households in Da Nang. 122 A YEAR DEFERRED – EARLY EXPERIENCES AND LESSONS FROM COVID-19 IN VIETNAM Appendices APPENDIX A. HOUSEHOLD DEMOGRAPHIC BACKGROUND APPENDIX B. HOUSEHOLD INCOME BACKGROUND APPENDIX C. MEASURING GENDER IMPACTS FROM THE WORLD BANK COVID-19 HOUSEHOLD MONITORING SURVEYS APPENDIX D. CHAPTER 2 FIGURES APPENDIX E. WORLD BANK COVID-19 HOUSEHOLD MONITORING SURVEYS APPENDIX F. WORLD BANK COVID-19 BUSINESS PULSE SURVEYS APPENDIX G. VIETNAM LABOR FORCE SURVEYS APPENDIX H. CHAPTER 3 FIGURES APPENDIX I. MICRO-MACRO SIMULATION TECHNICAL INFORMATION APPENDIX J. DISTRIBUTION-SENSITIVE POVERTY PROJECTIONS TECHNICAL INFORMATION Appendices   123 APPENDIX A. HOUSEHOLD DEMOGRAPHIC BACKGROUND In 2018, there were about 26 million households in Ethnic minorities represent about 15 percent of the Vietnam, with an average of 3.7 members and 2.2 adults population, or 3.8 million households. Across regions, per household. The most common household composition, they are most heavily concentrated in the Midlands representing over half of all households, are multiadult and Northern Mountain region, where they even households with at least one child (figure A.1). Sixty outnumber the Kinh majority (figure A.2). However, in percent of households have children. Single-adult male- other regions, particularly regions with large cities and headed households with a child are much more common vibrant economies, they are less represented. Ethnic than single-adult female-headed households with a child. minority households are smallest in number in the Red Skip-generation households, those with seniors and River Delta (fewer than 100,000 households). Because children, are very uncommon. Vietnamese society values ethnic minorities are primarily in agriculture and less in strong family networks or support, and members will exposed sectors, they were not largely economically support extended family in difficult times as much as they affected during COVID-19 (coronavirus), but they still are able, which is important as a coping strategy. suffer chronic nutrition and poverty challenges. Living standards vary across regions (figure A.3). About Figure A.1 Sixty percent of Vietnamese 20 percent of all households live in the poorer Central households have children Highlands and Midlands and Northern Mountains regions. The Red River Delta and the Southeast regions are where 20 the largest cities and economic poles in Vietnam are located (Hanoi and Ho Chi Minh City, respectively); they Number of households (millions) are home to 40.5 percent of all households and are where 15 industrial zones are most concentrated. The single region with the largest number of households is the Northern and 10 Coastal Central region. Agriculture is a large part of the economy in the Mekong Delta and the Central Highlands. 5 Although education is improving, education levels are still low in the typical household. In half of all households, 0 the maximum level of education of any member is lower- No children Has children secondary level or less (figure A.4). Eleven percent of households have a member who has completed upper- 1 adult male 1 adult female Multiple adults Only seniors 65+ secondary education, and only 2 percent of households have a member who has completed university level education or higher. Source: World Bank staff calculations using the Vietnam Household Living Standards Survey, 2018. 124 A YEAR DEFERRED – EARLY EXPERIENCES AND LESSONS FROM COVID-19 IN VIETNAM Figure A.2 Ethnic minorities comprise a small share of Vietnamese households 6 Number of households (millions) 5 4 3 2 1 0 Red River Midlands and Northern and Central Southeast Mekong Delta Delta Northern Mountains Coastal Central Highlands Kinh Ethnic minority Source: World Bank staff calculations using the Vietnam Household Living Standards Survey, 2018. Figure A.3 Population distribution by region 17% 24% Red River Delta Midlands and Northern Mountainous Areas Northern and Coastal Central Region 17% Central Highlands Southeastern Area 13% Mekong Delta 6% 23% Source: World Bank staff calculations using the Vietnam Household Living Standards Survey, 2018. Figure A.4 The maximum level of education in half of Vietnamese households is less than completed upper secondary Some or completed university 2.1 Some or completed upper-secondary 11.1 Completed lower-secondary or some upper-secondary 7.9 Some lower-secondary 1.5 Primary 3.2 Preschool 0 No education 0.3 0 2 4 6 8 10 12 Number of households (millions) Source: World Bank staff calculations using the Vietnam Household Living Standards Survey, 2018. Appendices   125 Figure A.5 Fifty-six percent of households have a Figure A.6 Agriculture is still the most common head that is 50 y/o or higher economic activity among households 8 15 6.7 7.0 Number of households engaged 7 12.6 12.2 Number of households 12 6 4.6 9.9 5 (millions) (millions) 4.0 9 4 3.1 3 6 2 0.8 3 1 0.0 0 0 10–19 20-29 30–39 40–49 50–59 60–69 70+ Agriculture Manufacturing Services Source: World Bank staff calculations using the Vietnam Source: World Bank staff calculations using the Vietnam Household Living Standards Survey, 2018. Household Living Standards Survey, 2018. Vietnam is one of the fastest aging economies in Asia. Informality is extremely prevalent in Vietnam. Twenty- The demographic dividend has already past peak and one million households, or 81 percent of all households, is declining. In 56 percent of households, the age of have at least one household member who either has a the household head is 50 years of age or over (figure wage job without a contract, is engaged in self-employed A.5). Vietnam is projected to become old before it agriculture, or is engaged in self-employed business. becomes rich, by aging at levels that are much higher The informal economy was more vulnerable during than other lower-middle-income developing countries COVID-19. Because informal workers are unregistered (World Bank 2016). and out of the line of sight of government, they faced difficulties in benefiting from government relief measures Agriculture is the most common sector in which at least even though such measures were intended for workers one person in a household is engaged. Households who were adversely affected by COVID-19. are often engaged in multiple sectors, either because of multiple working adults or because the same person is engaged with different labor activities across different seasons. About 80 percent of households have at least References two people employed. About 30 percent have at least three people employed. About 12.6 million households, or 48 percent of all households, have some engagement in the World Bank. 2016. “Taking Stock. An Update on Vietnam’s agricultural sector (figure A.6). This does not necessarily Recent Economic Developments. Special Focus: Promoting mean these households are reliant on agricultural income Healthy and Productive Aging in Vietnam.” World Bank, (agriculture is one of the lowest-paying income streams); Washington, DC. it is more likely that agriculture is an easy activity for diversification and income supplementation. Households are diversified across sectors; almost the same number of households are engaged in services, and 38 percent are engaged in manufacturing. 126 A YEAR DEFERRED – EARLY EXPERIENCES AND LESSONS FROM COVID-19 IN VIETNAM APPENDIX B. HOUSEHOLD INCOME BACKGROUND There are strong distributional differences in some The incidence of households receiving either public or sources of income in Vietnam (figure B.1). The poorest private transfers is relatively even across the welfare households in Vietnam are significantly more reliant on distribution. Social assistance schemes include agriculture income. For households in the poorest welfare programs not just targeted to the poor but also based on decile, nearly 90 percent receive agriculture income in characteristics—that is, people with disabilities, people with some amount, and nearly 30 percent in the poorest decile HIV, the elderly, and National Devotees (war veterans). In rely on agriculture as the main source of household the 2018 Vietnam Household Living Standards Survey, income. Households in the top decile is significantly more about 17.6 percent of households reported receiving a likely than other households to receive remittances and social benefit of some kind (including social assistance, other financial income. National Devotees, or disaster relief benefits). The social assistance system in Vietnam is fragmented. The share Wage income is the most common source of household of households receiving some form of public transfer is income, although it is significantly less common for lower than compared to other countries in the region such households in the lowest welfare decile. It is also important as Thailand, where over half of households received some to note that there is large variation in the type of work form of public assistance in 2017. The share of households and quality of work associated with “wage” employment. receiving private transfers through remittances is also lower Wage income can be derived from all sectors (agriculture, than in Thailand, where about 30 percent of households manufacturing, and services) and obtained through received remittance income in 2019. In terms of the informal work or skilled contract work. The labor market amount of income, both private and public transfers are in Vietnam is still highly informal, with only 27 percent of on average larger for wealthier households than for poorer wage workers having a contract through which employers ones. Thus, the reliance on domestic labor market income contribute to social insurance and health care. in Vietnam is larger than in some neighboring countries. Figure B.1 The prevalence of income sources varies across households, Vietnam 100 Share of households (%) 80 60 40 20 0 Agriculture Sideline Business Wage Domestic and Public Other agriculture international transfer remittances Poorest decile (1) 2 3 4 5 6 7 8 9 Richest decile (10) Source: World Bank staff calculations using the Vietnam Household Living Standards Survey, 2018. Appendices   127 Business and wage incomes are the highest (figure There are some differences in the primary source of B.2). Average incomes for the top decile tend to be household incomes across the welfare distribution. significantly higher than for all other deciles. For some Most households rely on wages as the largest source of income categories (remittances and business incomes), household income. Across the entire welfare distribution, the average income for the top decile is even double the no more than 10 percent of households in any decile average for the ninth decile. has a primary source of income from nonlabor market categories (remittances, public transfers, and other) A high share of Vietnamese households receives income (figure B.5). There is one exception, which are households from multiple sources (figure B.3). Nearly 30 percent in the lowest decile having a starkly higher dependence of households in Vietnam have three income streams on agriculture incomes. For those households deriving across broad categories representing diversification the largest share of income from wages, the poorest of activities and sources. Income categories are primarily receive agriculture and manufacturing wages, significantly different and do not reflect differences in whereas the richest earn wages predominantly in the crops in agriculture or sectors in wages. For example, services sector. There are also strong distributional if a household grows multiple types of crops, it is still differences in agricultural and business income. Business considered to have one type of income source and rather income is about nine times more likely to be the leading than separate income streams for the purposes of this income source among households in the top decile than analysis. Poorer households tend to have slightly higher among households in the bottom decile. Conversely, over income diversification across broad categorizations. 40 percent of households in the lowest decile receive the majority of their household income from agriculture Few households rely on only one income channel. sources, compared to less than 5 percent of households About 3.5 million households (out of 26 million) have in the top decile. only one income source (figure B.4). Among these, about 1.5 million rely on wages. However, almost a million (970,000) rely solely on remittances. Households relying on remittances are more likely to be those with only elderly household members. Figure B.2 Business and wage incomes are much higher than other income sources, Vietnam 35,0000 Animal income (VND, thousand) 30,0000 250,000 200,000 150,000 100,000 50,000 0 Agriculture Sideline Business Wage Domestic and Public Other agriculture international transfer remittances Poorest decile (1) 2 3 4 5 6 7 8 9 Richest decile (10) Source: World Bank staff calculations using the Vietnam Household Living Standards Survey, 2018. Note: VND = Vietnamese dong. 128 A YEAR DEFERRED – EARLY EXPERIENCES AND LESSONS FROM COVID-19 IN VIETNAM Figure B.3 A high share of Vietnamese households receives income from multiple source a. Average number of income sources, by decile b. Distribution of the number of income sources 4 30 3.5 25 Number of income sources Share of households (%) 3 20 2.5 2 15 1.5 10 1 5 0.5 0 0 Poorest 2 3 4 5 6 7 8 9 Richest 1 2 3 4 5 6 7 decile decile (1) (10) Number of income sources Source: World Bank staff calculations using the Vietnam Household Living Standards Survey, 2018. Figure B.4 Vietnamese households relying on only one income source only one income source (thousands) 2000 Number of household relying on 1500 1000 500 0 Agriculture Sideline Business Wage Domestic and Public Other agriculture international transfer remittances Source: World Bank staff calculations using the Vietnam Household Living Standards Survey, 2018. Figure B.5 Primary income source in Vietnam, by decile 100 Share of households (%) 80 60 40 20 0 Poorest 2 3 4 5 6 7 8 9 Richest decile decile (1) (10) Agriculture Sideline agriculture Business Wage Domestic and international remittances Public transfers Other Source: World Bank staff calculations using the Vietnam Household Living Standards Survey, 2018. Appendices   129 APPENDIX C. MEASURING GENDER IMPACTS FROM THE WORLD BANK COVID-19 HOUSEHOLD MONITORING SURVEYS To monitor the impacts of COVID-19 (coronavirus), the First, men and women may have different rates of phone World Bank began an unprecedented data collection ownership and survey response. For example, in rural effort in over 100 countries, including Vietnam. With areas, households may have only one cell phone that mobility restrictions and to ensure the safety of is kept by the male household head. Therefore, the type enumerators and survey respondents, data collection of household represented by a female respondent may turned from the typical face-to-face household survey, be different from the type of household represented by which asks questions of all adult household members a male respondent. Table C.1 compares household (especially related to labor market participation), to characteristics of male and female respondents who remote survey collection by phone. This mode of survey interviewed in a pre-COVID-19 baseline survey and collection adds challenges to inferring population- included in the COVID-19 monitoring survey. Female based estimates on the gender-differentiated impacts of respondents tend to come from households in urban COVID-19. The majority of indicators from the COVID-19 areas and from single-adult households with fewer monitoring surveys are measured at the household-level, working adults; they are less likely to come from but gender-differentiated impacts require individual-level households of ethnic minority, in the bottom 40 percent information and representativeness. of the income distribution, with access to a household farm, and with health insurance support in 2019. Table C.1 Household characteristics of female and male respondents in the World Bank Vietnam COVID-19 monitoring survey Female Male Female – Male Urban 0.381 0.313 0.069*** (0.49) (0.46) (0.012) Ethnic minority 0.126 0.176 -0.050*** (0.33) (0.38) (0.009) Bottom 40 0.370 0.401 -0.031** (0.48) (0.49) (0.012) Single adult household 0.165 0.084 0.081*** (0.37) (0.28) (0.008) Number of working adults 2.063 2.286 -0.223*** (1.07) (1.09) (0.028) Household farm 0.477 0.593 -0.116*** (0.50) (0.49) (0.013) Health insurance support in 2019 0.365 0.413 -0.048*** (0.48) (0.49) (0.012) Observations 2826 3387 Source: World Bank. Note: Household weights are applied. “Single adult household” and “number of working adults” come from merging the COVID19 monitoring survey with the 2018 Vietnam Household Living Standards Survey. 130 A YEAR DEFERRED – EARLY EXPERIENCES AND LESSONS FROM COVID-19 IN VIETNAM Second, a phone survey—constrained by short duration— of education and are less likely to be the spouse of the typically interviews only one member per household and head of household, whereas female respondents are asks about his or her own labor market participation. The more likely to be the spouse of the household head than phone number collected at baseline may be that of the other individuals in the household (table C.2). household head or the spouse of the household head. This means that the type of male and female individual Preliminary effort to address this sample selection issue captured in the phone survey may be different from with a different reweighting adjustment led to a similar the distribution of male and female individuals in the conclusion on the gender-differentiated impacts of population. Of note, male and female household heads/ COVID-19. It suggests that further research is needed spouses may have stronger labor market attachments to understand whether a reweighting adjustment than other male and female individuals in the household. (or a different type of reweighting adjustment) can In fact, male and female respondents of the COVID-19 adjust for the sample selection bias (Kugler et al. monitoring survey are older than other individuals in the 2021). The analysis presented in this report uses the household, are more likely to be married, are more likely original household sampling weight, without additional to work at baseline, and are more likely to be the head reweighting adjustment. of the household. Male respondents have fewer years Table C.2 Individual characteristics at baseline, Vietnam, 2018 All household COVID-19 survey members respondents (1) (2) (2) – (1) (2) Female Male Female Male Female Male Female – Male Age 44.22 42.44 46.87 49.10 2.756*** 6.991*** -2.224*** (18.33) (17.45) (13.00) (12.77) (0.371) (0.322) (0.333) Years of education 8.308 8.754 8.170 8.281 -0.144 -0.498*** -0.111 (4.81) (4.47) (4.48) (4.16) (0.100) (0.084) (0.113) Married 0.660 0.713 0.747 0.929 0.090*** 0.226*** -0.182*** (0.47) (0.45) (0.44) (0.26) (0.010) (0.008) (0.009) Work participation 0.721 0.798 0.874 0.918 0.159*** 0.126*** -0.044*** (0.45) (0.40) (0.33) (0.27) (0.009) (0.007) (0.008) Head of household 0.210 0.504 0.349 0.881 0.145*** 0.395*** -0.531*** (0.41) (0.50) (0.48) (0.32) (0.008) (0.009) (0.010) Spouse of the household head 0.430 0.102 0.544 0.039 0.118*** -0.065*** 0.504*** (0.50) (0.30) (0.50) (0.19) (0.010) (0.006) (0.009) Observations 65492 63910 2733 3306 Source: World Bank. Note: COVID-19 survey respondents (column 1) is restricted to respondents who were household members in the 2018 Vietnam Household Living Standards Survey (VHLSS). All household members in the 2018 VHLSS sample (column 2) are restricted to households that responded to the employment module and have nonmissing household weights, and to individuals who were 15 years old or older in the 2018 VHLSS. References Kugler, Maurice, Mariana Viollaz, Daniel Duque, Isis Gaddis, David Newhouse, Amparo Palacios-Lopez, and Michael Weber. 2021. “How Did the COVID-19 Crisis Affect Different Types of Workers in the Developing World?” Policy Research Working Paper 9703, World Bank, Washington, DC. Appendices   131 APPENDIX D. CHAPTER 2 FIGURES Figure D.1 Vietnamese households reporting lower income at the time of interview compared to last MONTH a. Households, by income quintile 100 Share of households (%) 80 60 40 20 0 R2 R3 R4 R5 R2 R3 R4 R5 R2 R3 R4 R5 R2 R3 R4 R5 R2 R3 R4 R5 Q1 (Bottom 20) Q2 Q3 Q4 Q5 (Top 20) Don’t know Higher Lower (<25%) Lower (50–99%) Same Lower (25–49%) Lower (>=100%) b. Households, by region 100 Share of households (%) 80 60 40 20 0 R2 R3 R4 R5 R2 R3 R4 R5 R2 R3 R4 R5 R2 R3 R4 R5 R2 R3 R4 R5 R2 R3 R4 R5 Red River Delta Midlands and Northern and Central Highlands Southeastern Mekong Delta Northern Coastal Central Area Mountainous Region Don’t know Higher Lower (<25%) Lower (50–99%) Same Lower (25–49%) Lower (>=100%) Source: World Bank Vietnam COVID-19 household monitoring surveys (rounds 2–5) cross-section. Note: Income in the most recent full month at the time of interview compared to the last full month. Welfare quintiles are based on household consumption per capita in 2018. 132 A YEAR DEFERRED – EARLY EXPERIENCES AND LESSONS FROM COVID-19 IN VIETNAM Figure D.2 Vietnamese households reporting lower income at the time of interview compared to last YEAR a. Households, by income quintile 100 Share of households (%) 80 60 40 20 0 R2 R3 R4 R5 R2 R3 R4 R5 R2 R3 R4 R5 R2 R3 R4 R5 R2 R3 R4 R5 Q1 (Bottom 20) Q2 Q3 Q4 Q5 (Top 20) Don’t know Higher Lower (<25%) Lower (50–99%) Same Lower (25–49%) Lower (>=100%) b. Households, by region 100 Share of households (%) 80 60 40 20 0 R2 R3 R4 R5 R2 R3 R4 R5 R2 R3 R4 R5 R2 R3 R4 R5 R2 R3 R4 R5 R2 R3 R4 R5 Red River Delta Midlands and Northern and Central Highlands Southeastern Mekong Delta Northern Coastal Central Area Mountainous Region Don’t know Higher Lower (<25%) Lower (50–99%) Same Lower (25–49%) Lower (>=100%) Source: World Bank Vietnam COVID-19 household monitoring surveys (rounds 2–5) cross-section Notes: Income in the most recent full month at the time of interview compared to the same month last year. Welfare quintiles are based on household consumption per capita in 2018. Appendices   133 APPENDIX E. WORLD BANK COVID-19 HOUSEHOLD MONITORING SURVEYS To monitor the social and economic effects on fieldwork is important to note because fieldwork is not households amid the pandemic, the World Bank designed evenly spaced, and outbreaks were unpredictable. Thus, and conducted its COVID-19 High-Frequency Phone some fieldwork periods occurring during lockdowns, and Surveys of Households in Vietnam. These monitoring others do not. Comparisons of trends across rounds data help to gather insights on household well-being as should therefore take into account field work and post lockdown reopening unfolds, and to highlight the reference periods. effects on the most vulnerable members of Vietnamese society. The household surveys are collected by the Sample Procedure Mekong Development Research Institute, under the supervision of the World Bank. Globally, the World Bank The 2020/1 Vietnam COVID-19 High Frequency Phone has conducted the COVID-19 monitoring surveys in over Survey of Households used a nationally representative 100 countries worldwide as part of a large global effort household survey from 2018 as the sampling frame. The (for more information, visit https://www.worldbank.org/en/ 2018 baseline survey included 46,980 households from topic/poverty/brief/high-frequency-monitoring-surveys). 47 3,132 communes (about 25 percent of total communes in Vietnam). In each commune, one enumeration area (EA) From June 2020 to March 2021, five rounds of the was randomly selected, and then 15 households were COVID-19 household monitoring surveys were randomly selected in each EA for interview. implemented (table E.1). The initial round was planned to have the largest sample to take into account attrition. The surveys also oversample ethnic minorities to obtain a representative sample of this group. The timing of Table E.1 Summary of five rounds of the World Bank Vietnam COVID-19 household monitoring surveys Round Field work dates Target sample size Special notes 1 June 5–July 8, 2020 Round 1 was planned to be a larger sample than Approximately 6,300 households the subsequent rounds. The reference period for (at least 1,300 minority households) some questions in round 1 included the first wave and as early as February 2020. 2 July 27–Aug. 12, 2020 This is the only round during which there were no Approximately 4,000 households domestic COVID-19 cases recorded during the (at least 1,000 minority households) survey reference period. 3 Sept. 9–Oct. 1, 2020 This round covered conditions during the second Approximately 4,500 households wave. The sample size in this round is larger at least 1,000 minority households) because there was an expansion cover more households in the second wave outbreak areas. 4 January 2–15, 2021 Approximately 4,000 households Conditions covered by round 4 reflect the period (at least 1,000 minority households) near the end of the second wave. 5 March 13–31, 2021 Approximately 4,000 households The final round asked about conditions during the (at least 1,000 minority households) period including the third outbreak as well as Tet. 134 A YEAR DEFERRED – EARLY EXPERIENCES AND LESSONS FROM COVID-19 IN VIETNAM The target sample size for round 1 was to complete Weighting interviews for 6,300 households, of which 1,888 households were located in urban areas and 4,475 For each round, cross-section sampling weights were households in rural areas. In addition, at least 1,300 calculated independently. The steps for weight adjustment ethnic minority households were to be interviewed. A to ensure national and regional representativeness are random selection of 6,300 households was made out of 7,951 households for official interview and the rest for • Start with base weights from 2018 survey. replacement. However, the refusal rate in the first round • Conduct household selection and nonresponse of the survey was about 27 percent, and households from adjustment using propensity score and probability of the same EA were randomly contacted for replacement. selection correction. • Poststratification: Rescale weights to match national, Sampling of subsequent rounds was treated in the region, and urban/rural populations based on the same manner. An attempt was made first to recontact 2019 population census. all existing respondents, and then new households from • Trim weights. the same locations were contacted as needed to reach the target sample size for each round (see table E.2). Questionaires Thus, attrition does not affect representativeness of cross-sectional samples around rounds. Moreover, cross- The Vietnam COVID-19 High Frequency Phone Survey sectional sampling weights for each round are provided. questionnaire covered the following topics, with topics varying across survey rounds: Panel Sample • Household roster A balanced panel was constructed out of households that • Behavior and social distancing responded across all five survey rounds. Panel weights • Access to health services were constructed following the same weighting principles • Education and childcare as the cross-sectional data sets, and are representative • Employment of the respondent at the regional level. Attrition was expected, and round 1 • Family farm and family businesses purposely had a larger target sample size than subsequent • Shocks/coping rounds (6,300 households in round 1 compared to 4,000 • Safety nets in subsequent rounds). In round 2, only 10 households • Food Insecurity Experience Scale were new contacts. Round 3 purposely expanded to • Opinions on policies and government action new households in provinces affected by the Da Nang • Vaccination outbreak. Even given this expansion, attrition was high in round 3, with 700 households from round 2 dropping out Data Access in round 3. Households on the lower end of the welfare distribution were more likely to drop out than households Anonymized cross-sectional data sets are available at the top end. Households in the Southeast and Mekong to registered users on the World Bank Microdata Delta region were also more likely to drop out. With each Library website. successive round, fewer original households dropped out, only 354 and 229 in rounds 4 and 5, respectively. Balanced panel weights were created that recalibrated to fit predetermined regional and decile distributions. Appendices   135 Table E.2 The size of the panel sample across rounds of Vietnam COVID-19 monitoring survey Round 1 Round 2 Round 3 Round 4 Round 5 Number of original round 1 households 6,213 3,924 3,234 2,880 2,651 Total number of households 6,213 3,935 4,560 3,948 3,922 Source: World Bank. Notes 47  Information on the World Bank global household monitoring efforts can be found at: https://www.worldbank.org/en/topic/poverty/ brief/high-frequency-monitoring-surveys. 136 A YEAR DEFERRED – EARLY EXPERIENCES AND LESSONS FROM COVID-19 IN VIETNAM APPENDIX F. WORLD BANK COVID-19 BUSINESS PULSE SURVEYS Three rounds of the COVID-19 Business Pulse Surveys The BPS rounds were implemented at varying intervals, (BPS) were conducted in Vietnam between June 2020 adjusting to the three COVID-19 waves. The first round and April 2021. The COVID-19 BPS is a rapid survey was in the field in June–July 2020 and asked questions designed to measure the various channels of impact with reference to business performance during the April of COVID-19 on firms, firm adjustment strategies, and lockdown and June 2019. The second round was in the public policy responses. In addition to the core questions field in late September to mid-October 2020 and captured tracking firm performance during the pandemic, special the recovery and smaller, localized second wave in modules were included in different rounds to collect Danang. The third round was in the field from late January more in-depth information about certain topics. These to March 2021 to capture recovery, but implementation modules included supply chain issues (round 2) and was delayed as a result of the third wave and the Tet the effectiveness of government support (round 3). holidays. The survey collected responses from firms Firms were sampled randomly from the Technology outside of Hanoi from late January to early February Adoption Survey, which was recently implemented 2021. For firms in Hanoi and selected firms in other in February 2020. The BPS collected responses from provinces, collection was done in late February (after the 500 firms across 15 provinces though a mix of phone Tet holidays) to March 2021. For comparability, firms were and in-person interviews. The sample is representative asked about their performance in January 2021, so the of all formal firms in Vietnam and is stratified by three data miss some of the negative consequences from the firm size categories and four broad sectors: agriculture, business closures and business and consumer anxiety in manufacturing, commerce (wholesale and retail), and all the third wave. Two additional survey rounds are planned other services. The results presented in this report are from July to December 2021. These rounds will capture calculated using sampling weights. The panel retention the impacts of the fourth wave. rate is high, with a total of 475 firms (or 92.1 percent) appearing in all three rounds. Table F.1 Summary of three rounds of the World Bank Vietnam COVID-19 Business Pulse Surveys Round Fieldwork dates Notes 1 June 15–July 7, 2020 The reference period includes the first wave. 2 September 21–October 15, 2020 The reference period includes the second wave. 3 January 25–April 10, 2021 The implementation was affected by the third wave and the Tet holidays. The reference period does not include the third wave. Source: World Bank. Appendices   137 APPENDIX G. VIETNAM LABOR FORCE SURVEYS This study uses the Vietnam Labor Force Surveys be noted that the sample is selected alternately: each (LFSs) from 2015 to 2020. LFSs are conducted annually enumeration area is divided into two rotational groups by the General Statistics Office of Vietnam. The LFS whose households are selected into sample in two uses a two-stage stratified cluster design. There are 126 adjacent quarters, and then excluded in two succeeding strata, which are urban and rural areas of 63 provinces adjacent quarters. It means that we can have a panel throughout the country. (At the first-level administrative of households and individuals by two adjacent quarters. division, Vietnam consists of 58 provinces and 5 central- Moreover, 50 percent of individuals surveyed in the first level cities or municipalities. A province is divided into quarter are reinterviewed in the fourth quarter. The panel districts, and a district is further divided into communes or structure is illustrated in figure G.1. This panel structure wards. Currently, there are about 700 districts and 11,000 allows for examining the mobility of workers across short communes.) The list of enumeration areas is based on term (three months) and medium term (nine months). the most recent Population and Housing Census (2009) or Intercensal Population and Housing Survey (2014). LFSs contain basic demographic information for all The number of enumeration areas in each stratum is individuals. People aged 15 years and older are surveyed selected by the method of probability proportional to for detailed information on employment, wages, and size. In the second stage, 15 households are randomly working hours. Information on unemployment is also selected from each enumeration area. The total sample conducted for unemployed people. These data sets size for each LFS is about 800,000 individuals. allow for analysis disaggregated for different population groups such as occupations (managers, skilled, The sample size is allocated for all the months throughout unskilled, and so on), sectors (public, private, and a year. Thus, about one-twelfth of the sampled households foreign direct investment), age groups, gender, urban/ is surveyed in each month. LFSs are representative at rural areas, and regions. the national, urban-rural, and provincial levels. It should Figure G.1 Panel data structure of Vietnam Labor Force Survey Quarter 1 Quarter 2 Quarter 3 Quarter 4 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec id1 id1 id2 id2 id3 id3 id4 id4 id5 id5 id6 id6 id7 id7 id9 id9 id9 id9 id10 id10 id11 id11 id12 id12 Source: World Bank illustration. 138 A YEAR DEFERRED – EARLY EXPERIENCES AND LESSONS FROM COVID-19 IN VIETNAM APPENDIX H. CHAPTER 3 FIGURES Figure H.1 Vietnam has the second-lowest price level among economies in the East Asia and Pacific region 180 160 Price level index (World = 100) 140 120 100 80 60 40 20 0 Australia Vietnam East Asia & Pacific Mongolia Cambodia Lao PDR Indonesia Philippines Thailand Malaysia Fiji Brunei Darussalam Taiwan, China China Singapore Hong Kong SAR, China Korea, Rep. Japan New Zealand Myanmar Source: World Bank International Comparison Program data visualization (https://www.worldbank.org/en/news/slideshow/2020/10/20/pli-chart2). Figure H.2 Most Vietnamese own their homes and have no large recurring expenses 25 Percentage of households that are renters 20 15 10 5 0 PNG 2009 THA 2017 TON 2015 TUV 2010 VUT 2010 FJI 2013 PHL 2015 IDN 2017 NMR 2015 FSM 2013 SLB 2013 WSM 2013 KHM 2016 MNG 2016 VNM 2016 TLS 2014 LAO 2012 Source: World Bank, East Asia and Pacific Team Statistics Development. Appendices   139 APPENDIX I. MICRO-MACRO SIMULATION TECHNICAL INFORMATION The micro-macro simulation uses the 2018 Vietnam Data Household Living Standards Survey to simulate techniques following approaches described in Micro data come from the 2018 Vietnam Household Bourguignon et al. (2008) and Ferreira et al. (2008), with Living Standards Survey. The sample is about the important simplification of omitting the computable 9,300 households. general equilibrium component to produce poverty simulations for 2020 under various scenarios. Notable Macro-level data come from (1) historical and actual applications to global financial crisis impacts include sectoral level employment and GDP from 2005 to 2019 Habib et al. 2010 and Olivieri et al. 2014. (data source: World Bank) and 2) population growth projection to account for demographic changes (source: The method essentially takes existing 2018 household General Statistics Office estimates). surveys as a starting point and uses the following information to simulate the consumption distribution in Macro-growth assumptions 2020 under various scenarios. Sectoral level GDP and employment levels are available • Macro-growth projections under various from 2005 to 2019. These series are essential to estimate scenarios in 2020 subsector growth-employment elasticities to project the • Estimated structural relationships between composition of the labor force across sectors in 2020 employment in specific sectors and output in that under different growth scenarios. sector, using the sectoral growth-employment elasticities to estimate changes to sector level Occupation choice employment under various gross domestic product (GDP) growth scenarios The probability of working in each subsector is predicted • Parameters from estimated occupational choice using multinomial logistic regressions. The regressions models to determine sectoral sorting and reallocation are performed separately for low- and high-skilled of workers to match sectoral distributions under individuals, defined using years of education, and scenarios in 2020 take into account several individual and household • Parameters from an estimated earnings model to characteristics: gender, age, education, household head calibrate labor and other sources of income status, marital status, school enrollment, household • Scenarios of different levels of social assistance dependency ratio, and presence of a public sector response taken into account following policies employee in the household. The probabilities are then described in chapter 4. predicted based on the regressions, and these are then • Simulated household income converted to household used to sort individuals by likelihood of being employed consumption for poverty estimation and profiling in each sector. 140 A YEAR DEFERRED – EARLY EXPERIENCES AND LESSONS FROM COVID-19 IN VIETNAM Mincer regressions agriculture income is mapped to household members without labor market earnings but who participate in the Workers who are not reallocated into a different sector agriculture sector. preserve their existing wages. Wages for job switchers are calculated using Mincerian regions. Like the occupational Social assitance choice models, these are run separately by skill level but take into account a slightly different set of characteristics. See chapter 4 for description of policies. All existing In addition to individual characteristics—marital status, social assistance beneficiaries are assumed to receive gender, education, and potential experience—the model the average top-up. New beneficiaries under the two also includes the type of employment, contractual status, scenarios are categorically selected on the basis of average work hours, and whether the individual has more informality and employment status, and are not related than one job, and geographical dummies. These help to income thresholds. to produce better estimates in the Vietnamese context with high informality and geographical heterogeneity. Estimating poverty However, as job switchers are not guaranteed to retain the occupational characteristics of the previous job, Simulated total household income is the simulated labor and similarly previously unemployed individuals do not income, simulated social assistance income, and a have these characteristics, they need to be assigned component of other income that is constant. Although before the predictions can be done. They are randomly the full range of income sources is not simulated in this assigned, keeping in mind the underlying distribution of model, the labor income component is by far the largest characteristics in the labor market. component of household income. See appendix B for a discussion on household income sources. Using One challenging aspect of using the household surveys empirical consumption-income ratios, the simulated is that households tend to have multiple labor income values of total household income are converted to sources. Multiple workers in the same family are taken total household consumption per capita for poverty into account in the model. However, the presence of estimation and profiling. household-level agriculture and family business income is challenging to model. In the case of agriculture, family References Bourguignon, F., M. Bussolo, and L. Pereira da Silva. 2008. “Introduction: Evaluating the Impact of Macroeconomic Policies on Poverty and Income Distribution.” In The Impact of Macroeconomic Policies on Poverty and Income Distribution, ed. F. Bourguignon, M. Bussolo, and L. Pereira da Silva, 1–23. World Bank Group, Washington, DC. Ferreira, F., P. Leite, L. Pereira da Silva, and P. Picchetti. 2008.“Can the Distributional Impacts of Macroeconomic Shocks Be Predicted? A Comparison on Top-Down Macro-Micro Models with Historical Data for Brazil.” In the Impact of Macroeconomic Policies on Poverty and Income Distribution, ed. F. Bourguignon, M. Bussolo, and L. Pereira da Silva, 119–75. World Bank Group, Washington, DC. Habib, Bilal, S. Olivieri, and C. Sánchez- Páramo, 2010. “Assessing ex ante the Poverty and Distributional Impact of the Global Crisis in a Developing Country: A Micro-Simulation Approach with Application to Bangladesh.” Policy Research Working Paper 5238, World Bank, Washington, DC. Olivieri, Sergio; S. Radyakin, S. Kolenikov, M. Lokshin, A. Narayan, and C. Sánchez- Páramo. 2014. Simulating Distributional Impacts of Macro-dynamics: Theory and Practical Applications. World Bank Group, Washington, DC. APPENDIX J. DISTRIBUTION-SENSITIVE TECHNICAL TECHNICAL TECHNICAL POVERTY INFORMATION INFORMATION INFORMATION PROJECTI redistribution effects (Bourguignon TECHNICAL 2003, 2004; Datt INFORMATION and Ravallion 1992; Ferreira 2012 projections can be At madea Atmacro At aa macro taking macro level, TECHNICAL level, into changes level, account changes changes in poverty these in poverty in INFORMATION two can be poverty channels. can can be decomposed In be decomposed decomposed simplified a combination into into a into scenari com At aAt macro a macrolevel, changes level, redistribution in redistribution changes redistribution poverty in effects poverty effects effects can (Bourguignon can (Bourguignon be bedecomposed (Bourguignon decomposed 2003, 2003, 2004; 2003, into 2004; intoDatt 2004; a a Datt and combination and Datt Ravallion and Ravallion Ravallionofof 1992grg can be projected on the basis of growth alone, when growth is assumed to be even across redistribution redistribution effects (Bourguignon projections effects projections (Bourguignon projections can be can can2003, madebe 2003, be 2004; made taking made 2004; Datt taking into taking Datt and into account and into Ravallion account accountthese Ravallion these two these1992; two channels. 1992; two Ferreira channels. Ferreira channels. 2012 In fora 201 In sim In distribution under a neutral-distribution assumption. This assumption Appendices   allows 141 projections projections can can be canmade be becan made cantaking be projected be projected taking into projected on account into theon account on the basis the these basis of these basis two growthof of growth two channels. alone, growth alone, channels. when alone, InIn a when growth when simplified a growth is simplified growth scenari is assumed is assum scenar assum to calculations, but may not be accurate in aall cases. A distribution-sensitive poverty can be projected can be projectedon the basis distribution distribution onis the basis of growth under of under growth alone, alone, when growth neutral-distribution a neutral-distribution growth when distribution. is assumed assumption. assumption. is assumed to be This to even This be even across assumptio assu assumes that growth distribution uneven calculations, under acrossbut may a neutral-distribution the welfare not be accurate in assumption. all Calculations cases. A This ofacros distributio assu dist distribution under a neutral-distribution calculations, distribution under calculations, but a neutral-distribution may not but may not assumption. be accurate assumption. be accurate This in all This assumption cases. in assumption A all cases. Aallows allows distribution-sen distributio for for sensitive poverty projections assumes follow that the methods growth is uneven described in Lakner et al. (2020) calculations, calculations, but butmay assumes maynot assumes be thatbe not accurate growth thataccurate growth in uneven is all in is cases. all cases. uneven acrossA across A across the welfare the distribution-sensitive the welfare distribution-sensitive welfare distribution. distribution. poverty poverty distribution. Calc calculated using the povsim sensitive STATA poverty command projections documented follow in Lakner, Negre, the and Pryd assumes assumes that that growth sensitive growth is uneven is poverty sensitive uneven across poverty the projections across the welfare projections follow welfare distribution. the follow the methods methods distribution. methodsCalculations described described Calculations described inof in Lakne of dist indisL L sensitive sensitivepoverty poverty calculated projections calculated projections calculated using using follow the follow using the the povsim the thepovsim methods povsim The initial poverty rate is the 2018 $3.20/day 2011 PPP (purchasing power parity) pove STATA methods STATA described STATA command command described command indocumented in Laknerdocumented Lakner documented et in et al.al. in Lakner, in Lak (2020) (2020 Lak N APPENDIX J. calculated calculated Vietnam, using based the using on povsim the the povsim most The initial The The initial STATA STATA recently poverty initial poverty poverty command rate is command available rate ratetheis is documented survey the 2018 the 2018 documented 2018 data. $3.20/day inin Poverty $3.20/day $3.20/day Lakner, Lakner, 20112011 2011 Negre, Negre, projections PPP PPP (purchasin PPP (purchasing andandPryd begin (purchasin Pry pow in The The initial Vietnam, poverty Vietnam, rate is based the based on 2018 theon the the most most $3.20/day recently recentlyavailableavailable survey survey data. data. Poverty Povertyproj Growthinitial of poverty household rate Vietnam, is the consumption 2018 based on $3.20/day is assumed to2011 most 2011 PPP recently follow PPP (purchasing available (purchasing similar patterns power survey power parity) data. parity) of gross Povertypov pove domest Vietnam, Vietnam, (GDP) per based based capita on on the the growth most most from Growth recently recently national of available available accounts. surveysurvey data. data. Poverty Poverty projections projections begin begin ini Growth Growthof householdof household household consumptionconsumption consumption is is assumed is assumed assumed to follow to to followsimilar follow similar patterns similar patt patt Distribution-sensitive poverty projections technical - Growth Growth Actual household ofGDP (GDP) of household growth (GDP) per consumption (GDP) consumptionrates per capita per are capita growth capita is is assumed assumed used growth growth for from to from poverty national fromto follow follow national accounts. national similar similar projections accounts. accounts. patterns patterns in 2019 of of gross gross and 2020. domes domest For (GDP) (GDP)growth per per capita capita growth growth from from national national accounts. accounts. information projections- Actual - Actual are - usedGDP Actual growth for GDP poverty growth GDP projections growth growthrates are rates projection are used rates used are for used arecalculations. for poverty used poverty for for poverty poverty projections projection projections projections in 2019 calculatio in in - A- pass-through Actual GDP - Actual GDP growth rates rate growth is growth fixed projections rates growth atare are used 1. This used projections are assumes for for poverty used poverty are used for that the poverty projections for poverty projections welfare projection in in 2019 aggregate 2019 projection calculations. and and 2020. grows 2020. calculatio Fora For same rate growth as GDP projections - A or- - A private are pass-through A pass-through usedconsumption pass-through for poverty rate israte ratefixed is per fixed capita. projection is at fixed at 1. This at 1. This 1. This calculations. assumes This assumes thethat isassumes most that the that the optimistic welfare welfa the welfa ags At a macro level, changes in povertygrowth projections can be decomposed are is same used modeled for rate poverty as GDP through projection or private parameterized calculations. consumptionassumptions per capita. This is A A pass-through - pass-through ratesame rate isof rate is same fixed as fixedrateGDP atas or 1.GDPThis private assumes or consumption private that the consumption per capita. welfare per This grows aggregate capita. is theis grows This m into a combination of growth - redistribution Assumptions and on the shape effects regarding the at how 1. growth This welfare assumes incidence grows at that curve the differentand welfare rateschanges aggregate along in inequality a same same rate rate as as GDP GDP Assumptions orthe or private private on consumption the consumption shape per of perthe capita. capita. growth This This is incidence is the the most most curve optimistic optimisticand chs (Bourguignon 2003, 2004; degree Datt and how ofRavallion growth Assumptions 1992; is Assumptions distributed on the welfare onshape theacross distribution. of shape Thethe households. of growth shape the of growthincidence this growthInequality incidence curve curve is and curve modeled change and ch Ferreira 2012). Poverty projections Assumptions parameterized can be made Assumptions on degree on the assumptions taking the shape degreeof shape degree along howof of regarding of A thethehow PPENDIX howgrowth welfare the growth growth howgrowth growth is J. distributed incidence welfare distribution incidence isD distributed ISTRIBUTION growscurve is is distributed referred curve and across toat and as across across different the changes growth changes - households. SENSITIVE households. households. rates in Inequal in inequality along inequality Ine PO Ine th degree distribution. into account these two channels. In a of simplified how The shape scenario, parameterized growth parameterized parameterized of is this incidenceis growth curve assumptions distributed assumptions assumptions curve. On across theregarding along basis regarding households. regarding of how the welfare empirically how welfare how welfare Inequality welfare distribution observed grows grows at grows is at modele different at referred diff diff degree of how growth distributed across households. TECHNICAL Inequality INFORMAT modeled iswelfare poverty can be projected on theparameterized growth incidence basis of growth curve. alone, distribution. distribution. assumptions distribution. On growththe The basis The shape regarding The incidence of shape of how shape empirically curves this of of this growth welfare this using growth growth observed the curve grows Vietnam curve along at curve growth Household along the different along the welfare rates the incidence distribu along welfarecurves di dit parameterized assumptions At a macrohow regarding level, changes welfare in poverty grows at can berates different decomposed along th when growth is assumed to Vietnam Household Living be distribution. even across The the growth entire growth shape incidence growth of Standards Living incidence this incidence curve. growth Standards curve. Survey, On curve curve. Survey, the aOnOn along linear the basis a basis linearof the thegrowth of empirically basis of welfare growth empirically empirically incidence distribution incidence observed curve observed observed growth is isand referre assumed grow grow in distribution. The shape of curve redistribution this growth effects curve along (Bourguignon the welfare 2003, 2004; distribution Datt is Rava referred Vietnam Vietnam Household Household Living Living Standards Standards Survey, Survey,a linear a linear growth incide growth distribution under a neutral-distribution incidence assumption. curve. This Vietnam assumption also yields moreprojections On the basis Household is assumed. conservative can ofA empirically Living linear projections be made taking Standards assumption observed of poverty Survey, also into account growth rates: these two channec growth yields a linear more incidence incidence growth curve incide growth assumption allows for simplified incidence Vietnam Household calculations, but curve. assumption may not On assumption Living assumption the also Standards conservative basis also yields of empirically yields also yields more Survey, projections more conservative more of conservative a linear poverty observed growth conservative rates: growth projectionsprojections incidence projections incidence of of poverty of poverty curve is rates: povertycurves assume ra raa Vietnam Household Living can Standards be projected Survey, on a the linear basis of growth growthincidence alone, when curve growth is assumed is assumption also be accurate in all cases. A distribution-sensitive yields more poverty conservative projections of poverty rates: projection assumes that growthassumption is uneven also yields across the moredistribution conservative under ! projections = a neutral-distribution $ − & of ∗ poverty ( rates: assumption. This calculations, but may not be accurate ! ! !! = ! !! $ = in − $ = & $all∗ cases. − − ( & & ∗ (!A distri where welfare distribution. Calculations of distributional sensitive ! ! ! ∗ (! ! where where where assumes that growth !! = is $ uneven − & ∗ (! across the welfare distribut poverty projections follow the methods described in where !! = the growth rate for percentile sensitive = the group poverty ! =i. projections $ − & ∗ (follow the methods described Lakner et al. (2020), and arewhere calculated using the !! = ! !the! = ! ! the growth growth the rate growth growth !rate for rate rate percentile for for for percentile percentile percentile ! group group group i. group. i. i . where(! =! ainpercentile group icalculated . The = a poorest a percentile using the povsim households group areSTATA percentile command group documented 1, and richest in povsim STATA command documented ! = the growth Lakner, Negre, =( (! rate (a! for !percentile ! = percentile a percentilegroup percentile group group i. The group i. i. i . The The . poorest The poorest poorest households poorest households households households are are are percentile are percentile percentile grou percentile !! =(the group rate growth 100.for percentile percentile The initial group group poverty 100. i.richest rate isare the 2018 $3.20/day 2011 and Prydz (2014). ! = a percentile percentile group percentile percentilei.group The group poorest 100. group 1, and 100. households percentile are percentilegroup 100. group 1,PPPand (purch riche $ and & = growth parameters $ and iVietnam, & that = can growth based beon considered parameters the most to that recentlyreflect can be aconsidered available transfer survey andto tax. reflect a a percentile (! =percentile groupgroup 100. $ and $ .and & The and &poorest = growth growth = growth households parameters parameters parameters that are that can percentile can that be be can considered considered group be considered to1, to data. and reflect riches a tran reflect Po a The initial poverty rate is the 2018 $3.20/day 2011 PPP to reflect a transfer and tax. Thepercentile final and & $ Gini group = growth obtained 100. parameters will The The final depend Growth Gini that on of the obtainedcan household be values will considered of $ )*+ & depend consumption onto the .reflect isThe values assumed a transfer parametersof to$ )*+ & follow and $ and tax. . The simila & (purchasing power parity) poverty rate in Vietnam, The based final Gini final obtained Gini obtained will depend will on the depend on values the of values of $ )*+ & . The $ )*+ & . param The that$ and & solve growth parameters the=Gini following equation that solve (GDP) that that the per can yields following capita bethe considered desired equation growth from to change that reflect yields national in a transfer inequality. the accounts.desired and change tax.in i on the most recently availableThe surveyfinal that obtained data. Poverty solve that solve The thefinal will following depend the following Gini on equation the obtained values equation will that ofyields dependthat $ )*+ & onthe yields . the desired The the parameters values change desired in change$ inequ and in& i projections begin in 2019. The that final solve Ginithe following obtained will of equation depend δ- that θ.on and Actual The yields theGDP values parameters the of growth desired δ $ )*+ & and rates θchange are are . Thevalues used inequality. inparameters for poverty $ that and & projectio that solve the following equation solve the that yields following growth the desired equation projections that change are usedyields the for in inequality. desired poverty projection calcu Growth of household consumption is assumed to follow change in inequality. 01*1 "#$%&'()%* ($, &) 01*1 01*1 "#$%&'()%* 01*1 "#$%&'()%* "#$%&'()%* "#$%&'()%* ($, &)($, ($,that&) &) − - ,($, A&) pass-through = ,($,rate,($,&)is fixed ,($, = &) &) = = at− 1. 1This assumes − 1 − the 11 similar patterns of gross domestic product (GDP) per same rate 01*1 as GDP 01*1 "#$%&'()%* or private($, &) consumption 01*1 01*1 01*1per capita. Th capita growth from national accounts. ,($, &) = − 1 158 01*1($, &) 158 158 01*1 "#$%&'()%* Assumptions ,($, &) = on the shape of the growth − 1 158 incidence curve an • Actual GDP growth rates are used for poverty 01*1 158 degree of how growth is distributed across households projections in 2019 and 2020. Forparameterized assumptions 2021– 158 regarding how welfare grows a 23, growth projections are used for poverty distribution. Poverty in 2018 The shape is based of thethis on growth initial welfarecurve values along the welfa Poverty Povertyin 2018 based iscalculations. in 2018 on the is based on initial the welfare initial values welfare 3! .3 valuesPoverty The in final2018 is welfare based ∗ on ∗ 3! )values (curve. Poverty the initial determined is!determined in 2018 welfare byby is based values on 3 .the The initial fina projection Poverty in 2018 is based !.. on The growth The the final incidence final welfare welfare ∗initial welfare (is 3 )On is 3determined the basis by empirically offormula the ! ∗ ! . The final welfare (3! ) is dete observed theis rty in 2018 based the on • formula formula the below, initial below, welfare assuming assuming values everyone everyone 3!taxed is . isThe in taxedfinal welfare the below, proportion in formula Vietnam proportion to(3 )below, their ! to is determined assuming Household initial their welfare initial by Living welfarethe formula (everyone 3! Standards )3 ( and is theirbelow, taxed Survey, inassuming proportion a linear everyon to growththe i ! ) and their A pass-through rate is fixed at 1. This assumes that assuming everyone is taxed in proportion to their the formula below, assuming everyone is taxed in proportion to their initial welfare (3! ormula below, rank assuming ((! ( rank the welfare ): (! ): everyone aggregateis grows in taxed same rateto proportion at the as their GDPrankinitial assumption ( initial (welfare ): welfare ( 3 also ! ) and their yields and their rank more rank conservative ( ( ! ):: projections of pover rank ((! ): ! ((! ): or private consumption per capita. This is the most ∗ optimistic scenario. 3!∗ =3!∗ (1=+ (1$)3 +! $)3 −! & −∗(&! ∗ ∗ (!3! ∗ 3 3 ! ∗ = (1 + $)3 − & 3∗∗ ! (= (1 ∗ 3+ $)3! − & ∗ (! ∗ 3 3!! ! ! ! ! 3!∗ = (1 + $)3! − & ∗ (! ∗ 3! !! = $ − & ∗ (! where Assumptions on the shape of the growth incidencewhere where where where where where e .! = i! ! = .the the value initialgrowth value rate for of welfare 3 = percentile for the initial group value . of welfare fo i. 3 i. a percentile group i. 3! =curve the and changes = initial value in inequality of welfare affect for the degree of the initial of welfare for a! percentile group 3! the initial value of welfare 3! a initialgroup =percentile for a percentile the value iof group welfare for a percentile group 3! = the initial value of welfare how growth for a percentile is distributed group i. Inequality across households. (! = a percentile group i. The poorest households are perc percentile group 100. REFERENCES REFERENCES REFERENCES $ and & = growth parameters REFERENCES that can be considered to ref REFERENCES ERENCES Bourguignon, François J. 2003. “The Growth Elasticity The offinal Bourguignon, Gini Poverty obtained François Bourguignon, will J. 2003. Reduction: depend “The on Explaining François the values Growth of2003. J. Elasticity of “T $ )*+ & P. 142 A YEAR DEFERRED – EARLY EXPERIENCES AND LESSONS FROM COVID-19 IN VIETNAM References Bourguignon, François J. 2003. “The Growth Elasticity of Poverty Reduction: Explaining Heterogeneity across Countries and Time Periods.” Working Paper 28104, World Bank, Washington, DC. Bourguignon, François J. 2004. “The Poverty-Growth-Inequality Triangle.” Working Paper 125, Indian Council for Research on International Economic Relations, New Delhi. Datt, Guarav, and Martin Ravallion. 1992. “Growth and Redistribution Components of Changes in Poverty Measures: A Decomposition with Applications to Brazil and India in the 1980s.” Journal of Development Economics 38 (2): 275–95. Ferreira, Francisco H. G. 2012. “Distributions in Motion: Economic Growth, Inequality, and Poverty Dynamics.” In The Oxford Handbook of the Economics of Poverty, edited by Philip N. Jefferson, 427–62. New York: Oxford University Press. Lakner, Christoph, Mario Negre, and Espen Beer Prydz. 2014. “Twinning the Goals: How Can Shared Prosperity Help to Reduce Global Poverty?” Policy Research Working Paper 7106, World Bank, Washington, DC. Lakner, Christoph, Daniel Gerszon Mahler, Mario Negre, and Espen Beer Prydz. 2020. “How Much Does Reducing Inequality Matter for Global Poverty?” Global Poverty Monitoring Technical Note 13, World Bank, Washington, DC.