MYANM AR POVERT Y SY N T HESIS NOTE P. 1 Myanmar Poverty Synthesis Note 8 J U LY 2 0 2 2 Progress, Setbacks, & Uncertainty Effects of covid-19 & Coup on Poverty in Myanmar MYANM AR POVERT Y SY N T HESIS NOTE P. 2 Acknowledgements This poverty synthesis note is authored by Wendy Karamba (Economist) with contributions from Isabelle Salcher (Consultant). We are grateful to Lwin Lwin Aung (Consultant) and Kimsun Tong (Economist) for their support on the data collection of the Myanmar High-Frequency Phone Survey. The team would like to thank Giorgia Demarchi for her comments and sugges- tions for improvement, Sutirtha Sinha Roy for support with finalization, Arnold Marseille and the external communications team of the World Bank for their sup- port and guidance on publication and outreach, Sandi Soe Lwin, Thida Aung, Tin Hninn Yu and Mildred Gon- salvez for excellent administrative support, and Kamal Muhammad for excellent assistance in formatting the report. The team also wishes to thank Emilie Bernadette Perge and Giorgia Demarchi, whose invaluable work on the 2022 Myanmar Poverty Assessment has heavily in- formed this poverty synthesis and provides the basis of our understanding of the evolution and drivers of pov- erty reduction in Myanmar in the period preceding and during the coronavirus pandemic. The report was prepared under the guidance of Hassan Zaman (Regional Director for East Asia and the Pacific); Mariam J. Sherman (Country Director for Cambodia, Myanmar and LAO PDR); Kim Alan Edwards (Program Leader for EAP Equitable Growth, Finance and Insti- tutions Practice Group), and Rinku Murgai (Manager, Poverty and Equity Global Practice). The World Bank team wishes to convey a sincere thank you to the respondents of the Myanmar High-Frequen- cy Phone Survey for anonymously providing informa- tion in challenging conditions. ● MYANM AR POVERT Y SY N T HESIS NOTE P. 3 1 Introduction I n 2011, Myanmar embarked on a triple transi- tion: from military to civilian rule; from con- flict to peace; and from a planned economy to an open, market economy. Myanmar opened to the world, boosting opportunities for goods, people, and ideas to move across its borders. It also opened internally, with the space for public dis- course expanding as the political transition to civilian rule picked pace. Economic and political reforms trans- lated into vastly improved living standards. The dual crises of the COVID-19 pandemic and mili- tary coup on 1 February 2021 have setback Myanmar’s poverty reduction progress. The compounded effects of the COVID-19 pandemic and coup have eroded a decade of welfare gains. The growth slowdown accompanying the dual shocks has affected the country’s ability to de- liver a more prosperous future for its 54 million citizens. This poverty synthesis note documents Myanmar’s poverty reduction progress leading to the COVID-19 crisis, and setback to these gains brought about by the COVID-19 pandemic and coup. The note aims to extract lessons from the Myanmar Poverty Assessment and the World Bank High-Frequency Phone Surveys. Analysis of welfare trends and drivers of poverty chang- es draws from the Poverty Assessment and covers the 1 World Bank (2022). Myanmar period 2005–2017, in line with existing national house- Poverty Assessment: Gains under threat. hold surveys.1 Analysis of COVID-19 and 2021 military coup effects relies on the World Bank High-Frequency 2 World Bank Myanmar Monitoring Platform – Household Phone Surveys (HFPS) conducted between March 2020 Surveys (https://www.worldbank. org/en/country/Myanmar/brief/ and February 2022.2 Starting May 2020, seven rounds of monitoring-households). the phone survey data have been collected, each with 3 In HFPS round 6, the sample size was only 1,271 households national coverage consisting of a sample of 1,500 house- because data collection stopped holds, with the exception of the sixth round.3 Six sur- on the day of the military takeover on 1 February 2021. vey cover the period May 2020–January 2021 during the MYANM AR POVERT Y SY N T HESIS NOTE P. 4 pandemic and prior to the military coup, and one covers February 2022, one year after the military takeover on 1 February 2021. Annex I and Annex II provides more de- tails of the survey implementation and respondent profile. As with any analytical endeavor, there are limitations. The last time official poverty in Myanmar was assessed was in 2017. Hence, there are wide error bands around the poverty estimates projected between 2019 and 2022 amid uncertainty about the magnitude of poverty. HFPS are conducted over the phone with interviews lasting about 20–30 minutes for each household. Naturally, this limits the amount of information that can be col- lected to assess welfare and other socioeconomic out- comes. Phone surveys risk excluding segments of the population that do not have access to phones and those living where mobile coverage is weak, typically poor households. To overcome the “coverage” sampling bias, survey weight adjustments, including propensity score weighting and post-stratification weighting, are incor- porated into the analysis by drawing on data from the 2017 Myanmar Living Conditions Survey (MLCS). ● MYANM AR POVERT Y SY N T HESIS NOTE P. 5 2 Sustained poverty reduction & improved living standards prior to COVID-19 M yanmar’s economic liberaliza- tion delivered strong growth for over a decade. Between 2011 and 2017, GDP grew by an average of 7.3 percent per year, placing Myanmar among the five fast- est-growing countries in the world and well above the average for lower-middle income countries (3.3 percent in per capita terms) and for the East Asia and Pacific region. Growth was almost only led by the accumula- tion of capital (83 percent of the total growth between 2011 and 2017), and to a lesser extent by labor, while to- tal factor productivity remained close to zero over the entire period. Growth convergence, structural transfor- mation and private investment have fueled economic expansion, which in turn decreased poverty and vastly improved living standards.4 Strong growth, unleashed by economic liberalization and Myanmar’s new openness, drove poverty reduc- tion. Over the 2005–2017 period, growth in average consumption was responsible for almost the entire re- duction in poverty. Over time the redistribution com- ponent, indicating faster growth among the poorest, played a greater role. Poverty incidence and severity de- clined, and did so faster between 2015 and 2017. Median daily expenditures per adult equivalent increased from 4 World Bank (2022). 1,711 kyats in 2005 to 2,181 kyats in 2017 (in 2017 kyat). Myanmar Poverty The proportion of people living below the national Assessment: Gains under threat poverty line was halved in just over a decade, declining 5 These figures are based on from 48.2 percent in 2005 to 24.8 percent in 2017.5 Be- Integrated Household Living Conditions Assessment-I tween 2015 and 2017, poverty decreased by 12.1 percent (IHLCA-I) 2005, IHLCA-II per year—a rate three times faster than between 2005 2010, 2015 MPLCS and 2017 MLCS estimations. and 2015. Between 2015 and 2017, 7.3 percent of house- MYANM AR POVERT Y SY N T HESIS NOTE P. 6 holds moved above the poverty line. Not only were few- er people in Myanmar poor, but those who still lived in poverty came closer to meeting their basic needs in 2017. In 2005 and 2010, average consumption for poor house- holds was equal to 14.2 and 12.2 percent of the poverty line, compared to 8.4 in 2015 and 5.2 percent in 2017— suggesting an increase in consumption for the poorest household and shifting them closer to the poverty line. Poverty severity (squared poverty gap) also decreased faster between 2015 and 2017. FIGURE 1 FIGURE 2 Trend in poverty Poverty gap, trend headcount at Union, rural 2005—2017 and urban level (2005—2017) Source: Central Statistical Organization (CSO), Source: Central Statistical Organization (CSO), UNDP and World Bank (2019) UNDP and World Bank (2019) Faster poverty declines took place around urban growth poles and in some states/regions in the south- east of the country. The rapid growth in service and manufacturing, especially in urban areas, combined with the higher share of educated and better-off house- holds employed in these sectors, delivered more rapid early gains to the non-poor and increased inequality. Households in Yangon and Mandalay Regions benefit- ed from the employment opportunities created by the early liberalization reforms and experienced welfare in- creases. Bago Region likely benefited from proximity to Yangon, facilitating exchanges and trade, and easy mi- MYANM AR POVERT Y SY N T HESIS NOTE P. 7 gration for workers. A high rate of non-farm enterprises and large natural resource base explain the progress in Tanintharyi Region, as well as remittances from tempo- rary workers in Thailand. However, Tanintharyi Region fared poorly in some non-monetary indicators such as access to a electricity grid and educational outcomes. Kayin State, located on the important trade route con- necting Myanmar and Thailand, likely benefited from the opportunities created by Myanmar’s economic tran- sition and opening to foreign trade and investment. As the benefits of the country’s liberalization and trade trick- led down over time and as new investments in public ser- vices and basic infrastructure picked up, poorer house- holds could benefit more. These opportunities were slow to materialize in rural and peripheral areas, however. Changes in returns to existing endowments played a greater role between 2005 and 2015, while changes in endowments (particularly access to basic services) appear to drive poverty reduction between 2015 and 2017. Between 2005 and 2015, 63.4 percent of the total poverty decline was explained by a change in returns to endowments, in contrast with 15.3 percent in the fol- lowing two-year period. As the transition started, those with existing endowments could capitalize on the new opportunities unleashed by the economic opening, in particular if they were located in growing trade and eco- nomic centers and able to access basic services like an electricity grid. As the transition progressed, opportu- nities for the poor to access basic services and improve their human and physical capital emerged and paid off quickly. Indeed, changes in endowments (that is, house- hold characteristics) explain close to 85 percent of the poverty change over the 2015–2017 period. Nonmonetary welfare also improved as opportunities for the poor to access basic services and education expanded; but poorer households still lagged in ac- cess. By 2017, the share of households using electricity 6 World Bank (2022). Myanmar Poverty Assessment: for lighting doubled compared to 2005.6 The number of Gains under threat. MYANM AR POVERT Y SY N T HESIS NOTE P. 8 households reporting no toilet facilities has halved, from 14 percent of households in 2015 to just under 6 percent in 2017. Access to improved water increased from 66 percent to 88 percent of households over the same peri- od. Net total middle school enrolment increased from 52 percent to 71 percent between 2010 and 2017, education- al outcomes improved among the younger generations, and gender gaps in educational attainment narrowed. Mobile phone ownership increased from 4.8 percent to 81.5 percent over the same period as smartphones became widespread. While millions were lifted out of non-monetary deprivation, poorer households were more likely to lack basic services. Households in low- er consumption quintiles were much less likely to have access to improved sources of drinking water and sani- tation, electricity, a bank account, other basic services, such as public hospitals. While inequality increased between 2005 and 2015, growth was more inclusive between 2015 and 2017. Between 2005 and 2015, growth was not as pro-poor as it could have been. The poverty-growth elasticity (PGE) between 2005 and 2015 was -0.27, indicating that a per- centage point change in growth delivered only a 0.27 percent decrease in poverty. The Gini coefficient, a mea- sure of inequality, increased from 0.31 to 0.37 between 2005 and 2015. The growth incidence curves (measur- ing consumption growth along the distribution) for 2005–2015 show marginally slower growth at the very bottom and faster growth at the very top. This is vast- ly attributable to rapid consumption growth in the top decile in urban areas. Between 2005 and 2015, the share of total consumption in urban areas belonging to the top 20 increased from 61 to 71 percent, while the share linked to the bottom 40 declined from 11 to 7 percent. A poverty-growth elasticity of -2.06 between 2015 and 2017 indicates a shift in gears, with growth becoming significantly more pro-poor. Over the period from 2015 to 2017, the annualized growth rate of per adult equiv- alent expenditures for the bottom 40 was 6.8 percent, MYANM AR POVERT Y SY N T HESIS NOTE P. 9 compared to 0.9 percent for the whole country, resulting in a positive—and indeed large—shared prosperity pre- mium. The Gini coefficient declined from 0.37 in 2015 7 The more limited coverage to 0.30 in 2017. Households at the bottom of the distri- of top income households in the 2017 MLCS compared to bution experienced fast consumption growth, while the 2015 MPLCS, together with a possible increased rate of households in the top decile, especially those in urban savings among richer households as the transition was underway, areas, appear to have experienced slow or even negative likely explains the slow (or even consumption growth.7 negative) growth in the top decile in urban areas TABLE 1 Inequality indicators, by location (2005, 2015 and 2017) Union Urban Rural 2005 2015 2017 2005 2015 2017 2005 2015 2017 Gini coefficient 0.31 0.37 0.30 0.35 0.44 0.32 0.27 0.28 0.26 Consumption share Top 20 0.4 0.45 0.39 0.61 0.71 0.6 0.29 0.25 0.27 Bottom 40 0.21 0.19 0.22 0.11 0.07 0.1 0.27 0.29 0.3 Note: When excluding the Source: Myanmar Poverty Enumeration Areas (EAs) of two Assessment (2022) estimates townships in Northern Rakhine, using IHCLA 2005, MPLCS 2015, results are similar as the ones MLCS 2017 presented with all the EAs Households remained highly vulnerable to shocks even before the COVID-19 pandemic. Myanmar was facing two challenges in sustaining its poverty reduc- tion trajectory prior to the COVID-19 pandemic, which are still relevant. First, Myanmar’s exposure to covari- ate shocks, in particular natural and weather-related disasters, is high. Climate change and urbanization, which had been proceeding at a steady (but not overly fast) pace, will intensify risks of large impacts. Second, households in Myanmar in 2017 were extremely vulner- able to falling into poverty or more severe deprivation as a result of these or other shocks. A high share of house- holds is concentrated just above the poverty line, making them vulnerable to poverty following a shock. In 2017, households with an average daily per adult equivalent consumption between 1,590 kyats (the poverty line) and MYANM AR POVERT Y SY N T HESIS NOTE P. 1 0 2,385 kyats (1.5 times the poverty line) are considered at a high risk of falling into poverty. About a third of the population in that year was concentrated between these two lines. A 10-percent (or 15.90 kyats) decline in daily per adult equivalent consumption (i.e., poverty line in- creasing by 10 percent) would have caused poverty to be 13.7 percentage points higher—thus increasing from 24.8 to 38.5 percent of the population. On the other hand, an extra 15.90 kyats per-adult equivalent, assuming no changes in behaviors, would have decreased poverty to 11.5 percent. This illustrates the high levels of vulnera- bility among households near the poverty line. Direct cash transfer programs and Myanmar’s overall social protection system were in their nascent stage in 2017, and expanded rapidly since then even before COVID-19 hit. Extremely low coverage and generosity limited their redistributive impact. Cash transfers in 2017 represented a negligible share of GDP (around 0.03 per- cent) and only about 2 percent of households received them. Households in the lowest decile of the income dis- tribution received transfers amounting to about 0.79 per- cent of their income on average, while those in the 9th and 10th decile received transfers amounting to 0.07 percent and 0.03 percent of their income, respectively. Although Myanmar expanded its social protection programs since 2017 to protect people from socio-economic vulnerabili- ties, alleviate poverty, and promote human capital devel- opment, they were still relatively small programs. ● MYANM AR POVERT Y SY N T HESIS NOTE P. 11 3 A reversal of fortune in the wake of COVID-19 & the coup Substantial hardship on households amid COVID-19 and coup induced economic slowdown C OVID-19 and the 1 February 2021 mili- tary coup took a heavy human and eco- nomic toll on Myanmar. Over 19,000 people in Myanmar have reportedly died from the disease since the pandemic be- gan in 2020 and over 600,000 people have been infected.8 The immediate economic impacts of COVID-19 and the coup were severe, hugely damag- ing livelihoods. Around one million jobs were project- ed to be lost at the onset of the COVID-19 pandemic in 2020, equivalent to 4 to 5 percent of total employment in 2019.9 Many other workers experienced declines in incomes due to reduced hours or wages. Welfare sub- stantially declined. The coup compounded these liveli- hood and welfare challenges leading to further increase in poverty, heightened food insecurity, and deeper des- titution for those already poor. The dual shocks of COVID-19 and the coup led to a se- vere contraction of Myanmar’s economy in 2021. When the COVID-19 pandemic unfolded in 2020, Myanmar’s economy slowed to 3.2 percent in Myanmar’s 2020 Fis- cal Year (Oct 2019-Sep 2020), down from 6.8 percent in the previous year. Myanmar’s key growth drivers, ser- vices and industry, were most affected, growing at half 8 Our World In Data (https:// ourworldindata.org/). Note, the the pace of the previous 5 years. In February 2021, the number of confirmed infections and deaths may not accurately military assumed power in Myanmar, setting back the represent the true number of country’s democratic transition, and immediately im- deaths caused by COVID-19 pacting an economy that had already been weakened 9 World Bank (2021). Myanmar Economic Monitor July 2021. by COVID-19. GDP is projected to have fallen by 18 per- MYANM AR POVERT Y SY N T HESIS NOTE P. 1 2 cent in FY2021 (year ended September), with a broad- based contraction across all sectors. This means that the economy was around 30 percent smaller in September 2021 than it would have been in the absence of the dual 10 World Bank (2021). Myanmar Economic Monitor July 2021. shocks of COVID-19 and coup.10 FIGURE 3 COVID-19 and the coup induced an economic contraction in 2021 Note: e = estimate, f = forecast. Source: Macro Poverty Outlook 2022. FIGURE 4 There are signs of economic stabilization but at very low levels relative to other countries Note: e = estimate, f = forecast. Source: Macro Poverty Outlook 2022. MYANM AR POVERT Y SY N T HESIS NOTE P. 1 3 Taking Myanmar’s regional peers as an indication, the economic implications of the 2021 military coup were deeply profound. COVID-19’s effect on Myanmar’s econ- omy in 2020 had been among the least pronounced in East Asia and Myanmar could have showed signs of gradual economic recovery in 2021 similar to most regional peers. However, Myanmar’s economic recovery from COVID-19 induced slowdown received a major setback in early 2021 in the aftermath of the military coup. Myanmar under- went a severe economic deterioration from which it has not yet recovered. Myanmar’s GDP is currently projected to increase to 1 percent in FY2022 following the 18 per- cent contraction in FY2021. While consistent with some stabilization, growth is at a very low level. ● 4 Nearly a decade of welfare gains erased within two years of the crises P overty in Myanmar has increased sharply as a consequence of the dual crises. While no new national household surveys are currently available to assess monetary welfare, simulations indicate that poverty in 2022 doubled compared to what poverty was estimated to be in March 2020 (see Annex III for poverty measurement methodology). The simulations suggest about 40 percent of the population in Myanmar are living below the poverty line in 2022, matching levels of poverty a decade prior. The dual cri- ses effectively erased nearly a decade of poverty reduc- tion progress in a matter of two years. These simulated poverty estimates for 2022 were produced combining the imputed poverty level across HFPS rounds for 2020 and 2021, and extending the analysis with estimated labor income losses (based on GDP sectoral projections) and non-labor income losses (as all public sector cash trans- fer programs and remittances stopped, see Annex 3). MYANM AR POVERT Y SY N T HESIS NOTE P. 14 FIGURE 5 Poverty doubled relative to the simulated 2019 level FIGURE 6 Many households in the middle of the pre- pandemic income distribution fell into poverty Source: Authors’ simulations based on 2017 MLCS data. Note: s = simulation. Simulations of income losses during the coup include additional losses of employment as reflected by sectoral changes in the GDP and two labor demand scenarios: elasticity of 0.7 (lower bound) and elasticity of 1.0 (upper bound). Military coup occurred on 1 February 2021; 2022 refers to the 7th round of high frequency household survey conducted between February to March 2022. See Annex 3 for more information. Amid substantial uncertainty around the magnitude of poverty, there are wide error bands around the pov- erty estimates projected between 2019 and 2022. Dif- ferent source data, methodological choices, combined with varying assumptions will produce different pov- erty estimates. The United Nations Development Pro- 11 UNDP (2021). Impact of the Twin Crises on Human Welfare in gramme (UNDP) estimated that about 46 percent could Myanmar. be living in poverty by early 2022.11 World Bank’ SWIFT 12 Karamba, Perge, Behal, Uulu, poverty estimates for each HFPS round also yields sim- Li, Yoshida, Zhang, and Aron (unpublished). ilar trends yet more conservative estimates of poverty.12 MYANM AR POVERT Y SY N T HESIS NOTE P. 1 5 Regardless, all trends point to deteriorating household welfare since COVID-19 and the coup. Deeper destitution for those already poor Destitution among the poor also rose substantially. Simulations indicate the depth of poverty in 2022, mea- sured by the poverty gap index, rose to levels four times those in 2019 (poverty gap index measures how far the poor are from the poverty line on average). The poorest were hit hardest. Prior to the coup, people in the bottom 40 percent of the consumption distribution experienced a decline in consumption of about 14 percent from the 2019 levels due to COVID-19. The coup further reduced the con- sumption of the bottom 40 percent. Simulations suggest that one year after the coup, consumption of the bottom 40 percent had declined 25 percent from the 2019 level. FIGURE 7 The poor fell into deeper destitution Source: Authors’ simulations based on 2017 MLCS data. Note: s = simulation. Simulations of income losses during the coup include additional losses of employment as reflected by sectoral changes in the GDP and two labor demand scenarios: elasticity of 0.7 (lower bound) and elasticity of 1.0 (upper bound). See Annex 3 for more information. MYANM AR POVERT Y SY N T HESIS NOTE P. 16 FIGURE 8 COVID-19 and the coup deepened inequality Inequality rose substantially following Inequality increased substantially during the twin cri- the dual crises ses. Myanmar’s pre-pandemic inequality, as measured by the Gini coefficient, was low by international compari- son and stood at 30.7 percent in 2017. Growth had been inclusive and more pro-poor during 2015-2017; the shared prosperity premium—per adult equivalent consumption growth of the bottom 40 relative to average growth—was Source: Authors’ simulations based on 2017 large at 6.8 percentage points.13 Inequality initially rose MLCS data. Note: s = simulations. Simulations of income losses during the coup include in the wake of COVID-19 and further rose in 2021, driven additional losses of employment as reflected by sectoral changes in the GDP and two labor by the disproportionate income losses among poorer and demand scenarios: elasticity of 0.7 (lower near-poor households and end of cash transfers that sup- bound) and elasticity of 1.0 (upper bound). See Annex 3 for more information. ported households during COVID-19 in 2020. FIGURE 9 Disposable income decreased more than proportionately for poorer people Source: Authors’ simulations based on 2017 MLCS data. Note: s = simulations. Simulations of income losses during the coup include additional losses of employment as reflected by sectoral changes in the GDP and two labor demand scenarios: elasticity of 0.7 (lower bound) and elasticity of 1.0 (upper bound). See Annex 3 for more information. 13 World Bank (2022). Myanmar Poverty Assessment: Gains under threat. MYANM AR POVERT Y SY N T HESIS NOTE P. 1 7 Growing perception of impoverishment rela- tive to others since 1 February 2021 Since 1 February 2021, more households perceive that their household ranks worse in terms of socioeconom- ic status compared to others in the area. In February 2022, 33 percent of households perceived they were poor relative to others in the area before 1 February 2021, but 43 percent perceived they were poor relative to others in the area after 1 February 2021. FIGURE 10 Perception of being poorer relative to others living in the area is growing Source: HFPS 2022 (Round 7). Heightened food insecurity at pandemic on- set, during COVID-19 second wave, and since 1 February 2021 Households faced heightened food insecurity during the crises, especially at the onset of the pandemic, in October 2020 following strict containment measures in main urban centers, and in February 2022 when in- comes reduced and prices rose following the coup. De- spite concerns easing during various points of the crises, almost half of all households worried about not having enough food to eat because of a lack of money. Job and income losses also caused households to be less able to afford foodstuff and to reduce food quantity and quali- ty as a way to smooth their consumption. Poor house- holds and women-headed households were more likely to have experienced food issues than other households. With reduced quality and quantity of food intake, mal- nutrition and long-term impacts on children’s develop- ment become concerning in a country already highly affected by stunting. ● MYANM AR POVERT Y SY N T HESIS NOTE P. 18 FIGURE 11 Food insecurity worsened at various stages of the crises Source: HFPS 2020–2022 FIGURE 12 Poor households were more likely to have experienced food insecurity Source: HFPS Round 7 - February 2022. MYANM AR POVERT Y SY N T HESIS NOTE P. 1 9 5 Declining income & rising prices L abor and employment were hit hard with the initial shock of the pandemic. This sharp reduction in employment is the re- sult of strict containment measures at the start of the pandemic and global demand shocks. Employment gradually improved as containment measures eased from May 2020 to Au- gust 2020, with encouraging recovery in urban areas; however, employment fell in October 2020 due to the second wave of COVID-19 pandemic and in February 2022 in the aftermath of the military coup. Employment losses affected all sectors. Throughout the pandemic, employment fluctuated the most in urban areas, mostly because of the COVID-19 movement restrictions. Throughout the pandemic, workers in urban areas were the ones to suffer the most from loss of employment but also to recover more quick- ly when restrictions were lifted ( June through August 2020). By October 2020, the new stay-at-home orders prompted by a second wave of COVID-19 dispropor- tionately affected townships in Yangon and Mandalay Regions. Movement restrictions were further extended to most of the country by November 2020. FIGURE 13 Employment of the household head who had stopped working and had less income compared with previous survey rounds Note: For May 2020, share of households’ main workers is measured against a pre- March baseline. Source: HFPS 2020–2022 MYANM AR POVERT Y SY N T HESIS NOTE P. 2 0 However, even if employment gradually improved when the initial shocks of the crises subsided, there was not such recovery in income.14 Household heads who were working still reported lower income, where reports of losses were most pronounced in May 2020 during the initial COVID-19 wave, October 2020 during strict containment measures, and February 2022 one year after the coup. Labor income across all sectors was adversely affected, with pronounced impacts on retail and tourism. In February 2022, about 60 percent of a household’s main earners working in retail or tourism 14 Qualitative evidence has revealed that wages in rural areas reported lower earnings relative to January 2021 earn- might have decreased as a result from an increased supply in labor ings. While agricultural earnings faced less volatility force, as economic migrants throughout the crises, still about 50 percent of agri- returned to their villages from cities or from abroad as a result cultural workers reported lower earnings compared to of containment measures and job losses. In addition, as domestic previous rounds. Further, 61 percent of household non- and global demand decreased, many firms have reduced the farm businesses generated lower or no earnings in Feb- numbers of hours of operation, ruary 2022 despite most businesses still being in opera- which could also explain why incomes are lower. tion; this contrasts with 39% in January 2021. ● FIGURE 14 Labor incomes across all sectors were adversely affected after 1 February 2022 Percent of households’ main workers with lower incomes between rounds by month and type of activities Source: HFPS 2020–2022. FIGURE 15 Non-farm business incomes adversely affected after 1 February 2022 Percent of non-farm business households still in operation between rounds and reporting lower/no earnings Source: HFPS 2020–2022. MYANM AR POVERT Y SY N T HESIS NOTE P. 2 1 6 Households under stress with no social assistance one year after the Myanmar coup O ne year after the Myanmar coup, households find themselves under financial stress but with little sup- port. Households experienced sub- stantial negative income and expense shocks, while much of the public sec- tor social assistance given to households to cope with COVID-19 has been withdrawn since the coup. Both crises have reduced household income, but households perceive “events since 1 February 2021” to have had the biggest impact as they have had to grapple with both negative income and expense shocks. FIGURE 16 Events since 1 February 2021 have had the biggest impact on household income Source: HFPS (Round 7, February 2022). MYANM AR POVERT Y SY N T HESIS NOTE P. 2 2 Since 1 February 2021, 98 percent of households in Myanmar have experienced at least one shock, with price and livelihood shocks being the most promi- nent. Only 2 percent of households report not having experienced any negative shocks since 1 February 2021. Among households that experienced a shock, 95 percent faced increased prices of major food items and 65 percent faced a livelihood shock such a job loss or disruptions to family farming or non-farm family business activities. FIGURE 17 Nearly all households experienced at least one shock since 1 February 2021 Source: HFPS (Round 7, February 2022). FIGURE 18 Price and livelihood shocks were the most prominent since 1 February 2021 (%) Source: HFPS (Round 7, February 2022). Note: Food price shock includes (i) increase in price of major food items. Livelihood shocks includes (i) job loss, (ii) closure of a non- farm business, (iii) disruption of farming activities, (iv) increased price of farming/business inputs, (v) reduced price of farming/business output, (vi) lack of availability of business/farming inputs, and (vii) reduction of farming/business output. Health shocks include (i) Illness, injury, or death of income earning household member. Natural disasters includes (i) flooding, and (ii) drought. Security threats includes (i) theft/looting of cash and other property, and (ii) conflict or community violence. MYANM AR POVERT Y SY N T HESIS NOTE P. 2 3 Households in Myanmar maintain a diverse range of livelihoods. Wage employment provides income for 1 in 2 households in Myanmar. Other common sources of income include farming (38 percent), and non-farm family businesses (21 percent). Remittances and pen- sions supplement household incomes for 4 percent and 3 percent of all households respectively. TABLE 2 All sources of household income in the last 12 months Union Urban Rural Family farming 38.3% 10.7% 49.5% Non-farm family business 20.8% 32.1% 16.2% Wage employment 51.7% 59.3% 48.6% Domestic remittances 2.2% 1.4% 2.5% International remittances 2.0% 2.1% 1.9% Assistance from family / non-family 1.4% 2.2% 1.0% Properties, investments or savings 1.2% 3.7% 0.2% Pensions 3.0% 5.2% 2.1% Assistance from the public sector 0.03% 0.07% 0.02% Assistance from NGOs 0.04% 0.10% 0.01% Refused to answer 0.49% 0.71% 0.40% Source: HFPS (Round 7, February 2022). Over half of all households in Myanmar report re- duced household income in February 2022 relative to January 2021 before the coup. Family business or farm operators were among the hardest hit. About 60 percent of family business households had lower income in Feb- ruary 2022 relative to January 2021. About 51 percent of family farm households had lower income in February 2022 relative to January 2021. The economic strains from job and income losses have also had a negative impact on domestic remittances, with 57 percent of households reporting reduced remittances. Since 1 February 2021, one-third of households that experienced earnings contractions, reported their in- come declined because of rising prices and constrained earnings growth. About 25 percent of all households MYANM AR POVERT Y SY N T HESIS NOTE P. 24 indicate household income fell due to reduced farm or business revenues, and 16 percent state the decline is due to wage reduction. Employment challenges have also contributed to declined income; 27 percent of house- holds attribute the decline in household income to lack of employment opportunities while 17 percent attribute it to employment losses. FIGURE 19 Since 1 February 2021, 1 in 2 Myanmar households faced reduced household income Note: Percentages in the figure are conditional on households receiving the incomes from the stated source. Source: HFPS 2020–2022. Respondent can respond on more than source of income. FIGURE 20 Many households saw their income decline due to reduced earnings amid rising prices Note: The estimates are conditional on households Source: HFPS (Round 7, February 2022). Respondents can reporting a decline in incomes since 1 February, 2021. provide more than one answer. MYANM AR POVERT Y SY N T HESIS NOTE P. 25 In February 2022, most households operated their farms as usual, but faced rising input costs. About 82 percent of farming households report that farm input costs were more expensive in February 2022, up from 33 percent more than one year prior. Farm inputs mainly required for crop production—seed, fertilizer, pesticide and fuel—were most affected. About 23 percent of farm- ing households report being unable to farm as normal or having stopped working on their farm in February 2022. Most faced challenges acquiring farm inputs; about 39 percent of farm households unable to farm normally report being unable to acquire or transport inputs as a challenge. The impact of Ukraine war on food and fuel prices may account for some of these observations as some households during the February 2022 survey round were interviewed in the first week of March 2022. FIGURE 21 Cost of farm inputs increased for more than 4 in 5 farm households since 1 February 2021 Source: HFPS 2020–2022 FIGURE 22 Cost of all farm inputs increased, especially those for crop production Source: HFPS 2020–2022 MYANM AR POVERT Y SY N T HESIS NOTE P. 2 6 Overwhelmingly, households reduced expenditures as a way to cope with the economic impacts of the COVID-19 pandemic and the coup. In the months of stricter containment measures and more dire employ- ment and income losses (May and October 2020) and one year following the coup (February 2022), about 5 in 10 households cut down their non-food expenditures to divert them toward more pressing food needs. In these same months, 4 in 10 households had to cut down their food expenditures. In a number of rural communities, households would forage their food, hunt, and fish to make sure they receive enough nutrients. Households also reduced social expenditures (e.g., for weddings, burial ceremonies, and donations), both due to income losses and due to COVID-19 contagion risks and restric- tions. Households also commonly relied on savings and borrowing from friends, and more recently selling as- sets to cover living expenses. FIGURE 23 Households commonly reduced consumption, relied on savings, or borrowed from friends Source: HFPS 2020–2022 MYANM AR POVERT Y SY N T HESIS NOTE P. 2 7 Since 1 February 2021, a growing share of households reduced expenditures and sold assets. Reliance on sav- ings and borrowing from financial institutions or mon- ey lenders sharply declined, likely because of liquidity shortages and banking sector disruptions. FIGURE 24 Households increasingly reduced consumption, and credited purchases, and sold assets following the 1 February 2022 Source: HFPS 2020–2022 FIGURE 25 The bottom 40 were more likely to reduce consumption and adopt potentially scarring coping mechanisms Source: Source: HFPS (Round 7, February 2022) MYANM AR POVERT Y SY N T HESIS NOTE P. 28 The bottom 40 were more likely to cut down spend- ing on food and non-food items, and to adopt coping mechanisms with the potential to harm long-term consumption. Increasing household debt and selling assets could have long-term negative impacts on house- holds’ capacity to fulfil its basic needs, strengthen hu- man capital, and ensure financial solvency. Social assistance from the public sector given to house- holds during COVID-19 has been withdrawn, leaving poor households to manage deteriorating household budgets on their own. During the February 2022 sur- vey round, 36 percent of households reported having re- ceived assistance from the public sector before 1 February 2021, but only 4 percent received such assistance since then. Pro-poor cash assistance is no longer available for 18 percent of households; only 1 percent of households received cash assistance in February 2022. About 12 per- cent of households no longer receive food assistance. FIGURE 26 Assistance from the public sector to households declined sharply Note: Percent of households receiving public sector assistance before 1 February 2021 was drawn from Round Source: HFPS (Round 7, 7. Estimates may differ if previous rounds are used. For instance, Round 6 suggests 51 percent of households February 2022). received cash transfers administered through the General Administration Department (GAD). MYANM AR POVERT Y SY N T HESIS NOTE P. 29 Public sector social assistance had scaled up during the pandemic and was more likely to reach the poor. The food assistance that the public sector distributed during the pandemic was pro-poor and by May 2020, had reached 32 percent of the poor and 22 percent of the overall population. Assistance shifted to cash transfers, which were expanded between August and October 2020. According to HFPS, only 3 percent of households report having received cash assistance from the public sector in June 2020, compared with 31 percent in August and 43 percent in October 2020. With the expansion, the poor were more likely to receive cash assistance. Since the poor tend to be concentrated in rural areas, more ru- ral than urban households report receiving public sec- tor social assistance during the pandemic. Myanmar’s policy response helped contain the negative impacts on the poor and vulnerable but was insufficient to protect them fully against income losses. Compared to a scenar- io without these interventions, the poverty rate is sim- ulated as having been kept 1.7 percentage points lower. However, these policies had no impacts on inequality, which has slightly increased as a result of the crisis.15 More than half of households worry about their fu- ture household finances and ability to meet food needs. Throughout the dual crises, nearly 60 percent of households report worrying about households finances 15 World Bank Myanmar Poverty in the next month, while over 45 percent report worry- Assessment (2022). ing about having enough to eat the following week. FIGURE 27 More than half of households worry about finances and having enough to eat Source: HFPS 2020–2022 MYANM AR POVERT Y SY N T HESIS NOTE P. 30 Mental stress has increased since 1 February 2021, with the people of Myanmar experiencing elevated levels of anxiety and a growing sense of hopelessness. In February 2022, 60 percent of households state they experienced some form of mental or emotional distress. Most feel anxious (43 percent). Since 1 February, the percentage of household respondents feeling hopeless doubled from 15 percent in November 2020 to 29 percent in February 2022. The percentage of household respon- dents feeling sad, lonely and having difficulty sleeping or concentrating has also increased. ● FIGURE 28 Mental stress is on the rise Source: HFPS 2020–2022 "Mental stress has increased since 1 February 2021, with the people of Myanmar experiencing elevated levels of anxiety and a growing sense of hopelessness" MYANM AR POVERT Y SY N T HESIS NOTE P. 31 References IFPRI. 2022. The Agri-food System and Poverty in Myanmar: Finding from the Myanmar Household Welfare and Agriculture Performance Surveys. UNDP. 2021. Impact of the Twin Crises on Human Welfare in Myanmar. World Bank. 2021. Myanmar Economic Monitor, July 2021: Progress Threatened; Resilience Tested. World Bank, Myanmar. World Bank. https://openknowledge.worldbank.org/ handle/10986/36020. World Bank. 2022. Myanmar Poverty Assessment: Gains under threat. MYANM AR POVERT Y SY N T HESIS NOTE P. 32 Annex 1 Round 7 of the Myanmar high-frequency phone survey was conducted 11 February 2022-9 March 2022, one year High-frequency phone sur- after the previous wave of the survey. A sample size of vey parameters N=1,500 respondents from across the country were in- terviewed. Pilot survey parameters Before launching the full-scale survey, a pilot survey was conducted from 1 February 2022 with a sample of 13 respondents to test the questionnaire and identify cor- responding adjustments to make before full-scale data collection began. TABLE A.1 Pilot data collection period Data collection period (DD.MM.YYYY) Start 1.2.2022 End 1.2.2022 TABLE A.2 Interview length of pilot test Length of Interview Shortest 29.5 minutes Average 46.3 minutes Longest 72 minutes Full-scale survey incidence rates Over 7,000 numbers were contacted to achieve comple- tion of sample size of 1,500. While some of the surveys were completed on the spot, prior appointments were needed with some respondents. TABLE A.3 Pilot data collection period Data collection period (DD.MM.YYYY) Start 11.2.2022 End 9.3.2022 MYANM AR POVERT Y SY N T HESIS NOTE P. 33 TABLE A.3 Interview length of pilot test Data collection period (DD.MM.YYYY) Average 29 minutes TABLE A.5 Full-scale survey response rate Round 6 respondents Total Percentages Complete 669 55% Incomplete appointment 145 12% Unsuccessful - Power off/No An- 289 24% swer Decline 114 9% Total 1,217 100% New respondents Total Percentages Complete 831 14% Incomplete appointment 346 6% Unsuccessful - Power off/No An- 4,457 74% swer Decline 385 6% Total 6,019 100% Annex 2 TABLE A.6 State/Region Sample by location Urban Rural Total Respondent profile Kachin 19 34 53 Kayah 3 7 10 Kayin 10 35 45 Chin 3 11 14 Sagaing 26 127 153 Tanintharyi 11 30 41 Bago 30 106 136 Magway 17 90 107 Mandalay 63 117 180 Mon 15 39 54 Rakhine 16 75 91 Yangon 162 71 233 Shan 48 129 177 Ayeyawaddy 22 149 171 Naypyitaw 11 24 35 Total 456 1044 1500 MYANM AR POVERT Y SY N T HESIS NOTE P. 34 FIGURE A.1 Gender FIGURE A.2 Gender of household head N=1,500 FIGURE A.3 Age groups FIGURE A.4 Main language spoken N=1,500 FIGURE A.5 Household composition N=1,500 MYANM AR POVERT Y SY N T HESIS NOTE P. 35 Introduction Annex 3 Poverty measurement This analysis aims to assess the changes in the pover- methodology ty rate in Myanmar since 2019, accounting for the ef- fects of the COVID-19 pandemic that began in the first quarter of 2020 and the military coup that occurred in the first quarter of 2021. The effects of these exogenous shocks on household incomes are measured using (1) six rounds of the HFPS carried out between the first quar- ter of 2020 and the first quarter of 2021, which are used to measure the effects of the COVID-19 pandemic and the policy response; (2) effects of sectoral GDP changes from the first half of 2021, losses of remittances and the withdrawal of public sector cash transfers at the onset of the military coup; and (3) changes in income as mea- sured by the seventh round of the HFPS carried out in the first quarter of 2022. Each of these three shocks are extrapolated across the relevant time period to measure changes in poverty and inequality in Myanmar since the pre-pandemic levels in 2019. Data and the microsimulation model Microsimulations of the impact of the COVID-19 pan- demic on employment and incomes in Myanmar seek to assess the scale of the crisis in regard to poverty and inequality, as well as the efficiency of policy respons- es in shielding households from the fallout. The sim- ulations were conducted on a new dataset developed specifically for this purpose through the merging of The Myanmar Living Conditions Survey (MLCS) and the High Frequency Monitoring of COVID-19 Impacts Survey (HFPS). The MLCS was last carried out in 2017 and covered over 60,000 respondents. The survey con- tains questions on a wide variety of demographic and well-being measures such as household composition, employment status, consumption (including healthcare and education) and incomes. Consumption (used as a proxy for disposable income) was uprated based on real wage growth by sector of employment and inflation to MYANM AR POVERT Y SY N T HESIS NOTE P. 36 create a dataset with baseline (pre-COVID) 2019 dispos- able incomes. Using the microsimulation model developed according to the Commitment to Equity (CEQ ) framework for tax and benefit incidence analysis, changes in poverty rates and inequality were measured at their pre-pandemic levels using the uprated MLCS data. The 2017 poverty line was indexed to 2019 in line with inflation. To mea- sure the effects of the pandemic, households from the 2017 MLCS data were matched using selected house- hold characteristics and three sources of income (labor income, income from agricultural production, remit- tances) with respondents in the HFPS, which collect- ed information on changes in the employment status, incomes and material conditions of a sample of 1,500 households in each wave. Simulating income losses Income losses during the pandemic were simulated based on information on changes in employment and agricultural activity across each wave of the HFPS. The HFPS only has one respondent per household, but in- cludes questions about the activity of the household head. Thus, we apply the employment status of the household head to all business and employment in- come (work income) in the household. The survey also asks respondents about the agricultural activity of the household, which is not directly tied to the household head. Thus, we treat these two income streams sep- arately: work income and agricultural income of the household. We apply a randomly assigned seasonal ad- justment based on the proportion of HH in which the head reports working in the MLCS but has not worked over the past week. We assume that this proportion of HH heads would not be working during a particular point in time without the impact of the pandemic, and thus we do not decrease their income. Since we do not have information in the MLCS on seasonal agricultural activity we use employment in the agricultural sector as MYANM AR POVERT Y SY N T HESIS NOTE P. 37 a proxy. The status of each of these incomes is treated independently for each wave of the survey, with each wave covering two months of income. These losses are then distributed across the year to measure the average monthly income loss for the entire year. Furthermore, the survey also includes information on changes in in- come even if employment or agricultural activity con- tinues. In cases of reduced or increased reported income we use a factor of 0.2 for the pertinent two-month peri- od. Finally, we account for reported losses of remittanc- es, also included in the HFPS. Based on these income losses, new income measures were calculated accord- ing to the CEQ income concepts in order to develop the poverty and inequality assessments. Public sector response Public sector responses were simulated on household incomes after incurred losses resulting from the pan- demic. Just as in the case of lost incomes, the value of conditional cash transfers was distributed across the year, resulting in a monthly value per household. The Maternal Cash Transfer, Social Pension and electricity subsidy were included in the 2019 baseline income con- cepts due to their implementation prior to 2020. How- ever, expansions of these programs during the pandem- ic were treated as COVID response policies and only included in the 2020 income concepts after losses and cash transfers. The GAD COVID relief scheme, the most expensive of the four simulated programs, was rolled out in 5 waves, each expanding in scope. A combina- tion of regional and self-reported material characteris- tics from the survey were used to match the eligibility criteria and recipient numbers of each wave of the GAD scheme. By comparing poverty and inequality after in- come losses, but before transfers, to the same measures after the transfers were received it was possible to assess the success of these policies in mitigating the impact of MYANM AR POVERT Y SY N T HESIS NOTE P. 38 the pandemic on household material conditions. Military coup Income losses from the coup are simulated based on sectoral changes in the GDP. We assign losses randomly to the proportion of workers in each sector at an upper bound scenario of labor demand elasticity of 1.0 and a lower bound scenario of labor demand elasticity of 0.7. The lost net labor income is then calculated on a per capita basis and removed from the HH’s per capita dis- posable income. Since changes in GDP were measured in comparison to a 2019 baseline, we only apply losses that occur on top of what has already been simulated in the COVID-19 assessment, since the HFPS has captured part of the effect observed in the GDP figures. We also decrease disposable income by what remains of remit- tances after the losses captures in the first six rounds of the HFPS, and eliminate all public sector cash transfer programs and indirect subsidies that were simulated in the baseline. This includes COVID response policies, the maternal cash transfer, the social pension and elec- tricity subsidy. Since we do not have external data on ag- ricultural activity, we assume agricultural income stays at the same level, but maintain losses from the past year of the HFPS. Round seven of the HFPS The HFPS was once again conducted in Myanmar be- tween February and March of 2022. This allows for an assessment of income changes since the onset of the military coup in 2021, and a corresponding update of the poverty and inequality figures. Entering 2022, we use the higher bound scenario of the sectoral employment losses resulting from the military coup, since more re- cent estimates of the overall contraction of the economy in Myanmar from 2021 continued to grow in the second half of 2021. We maintain the poverty line, disposable income, and income from our three separate sources (work, agriculture and remittances) in real terms. On MYANM AR POVERT Y SY N T HESIS NOTE P. 39 top of the employment losses captured by the simula- tions from 2021, we either restore income or reduce work income according to reporting in round seven of the HFPS. While in 2020 we had six rounds of the sur- vey, so incomes could be adjusted for each two-month period and extrapolated for the year, at this time there is only one wave of data available for 2022, and thus in- come changes in February and March are applied to the total monthly income. It is worth to note that these loss- es could fluctuate throughout the year and may diverge if newer data becomes available. However, the seasonal adjustment mechanism applied in the simulation seeks to minimize these fluctuations that occur throughout the year. We also adjust HH agricultural activity, which was held constant at pre-coup levels (from the begin- ning of 2021) in the poverty measures from the coup. Remittances were zeroed out in 2021 since after seizing power the military had frozen international bank trans- fers – however, in the HFPS households report receiving remittances once again. We adjust remittances, accord- ingly, depending on the changes reported in the HFPS.