喪失生計(jì)：COVID-19對孟加拉國勞動力市場的影響

1、Losing Livelihoods:The Labor Market Impacts of COVID-19 in BangladeshAbstractThis paper provides early insights into the labor market impacts of the ongoing COVID-19 crisis in Bangladesh, with a special focus on three especially vulnerable areas: poor areas in Dhaka and Chittagong City Corporations

2、and Coxs Bazar district. We build on household surveys collected before the crisis and phone monitoring surveys collected after the start of the crisis to shed light on the implications of COVID-19 for employment and earnings. The findings presented here indicate substantial labor market impacts bot

3、h at the extensive and intensive margin, with important variation across areas and gender, largely due to the nature of occupations affected by the crisis. The findings also point to substantial uncertainty about job prospects.Keywords: COVID-19, coronavirus, Dhaka, Chittagong, Coxs Bazar, labor mar

4、ket, povertyJEL codes: D1, I15, I31, J2 J461 The world Bank group. Corresponding author: M.E. genoni (mgenoni). The authors are grateful to the ed- itor and referees for their helpful comments. we also thank Claudia Berg, Luz Carazo, Joaquin Endara, arshia haque, and flavio riva for excellent resear

5、ch assistance and valuable inputs into survey design and implementation. we also thank Benu Bidani, suleiman namara, and yutaka yoshino for their useful comments and guidance. The Coxs Bazar Panel survey (CBPs) is the result of a partnership between the yale Macmillan Center Program on refugees, for

6、ced Displacement, and humanitarian responses (yale Macmillan PrfDhr), the gender & adolescence: global Evidence (gagE) program, the Pov- erty and Equity global Practice of the world Bank, and the state and Peacebuilding fund (sPf) administered by the world Bank. The SPF is a global fund to finance c

7、ritical development operations and analysis in situations of fragility, conflict, and violence. The sPf is supported by australia, Denmark, germany, The netherlands, norway, sweden, switzerland, and The United Kingdom, as well as IBRD. The findings, interpretations, and conclusions expressed in this

8、 paper do not necessarily reflect the views of the World Bank, the Executive Directors of the World Bank, or the governments they represent. All errors and omissions are our own.IntroductionThe ongoing COVID-19 pandemic has creat- ed an unprecedented crisis in Bangladesh that risks erasing the subst

9、antial progress in household incomes and poverty reduc- tion achieved during the past decades. The sharp decline in demand for manufactured goods, particularly from the export-oriented ready-Made garments sector, is expected to affect employment creation in urban ar- eas, an important driver of pove

10、rty reduction in the past (hill and genoni, 2019). In addi- tion, large labor-income losses are expected for households engaged in informal services and labor-intensive sectors like construction, due to slower demand and social-distancing measures. Moreover, the domestic coronavi- rus outbreak and t

11、he consequent healthcare burden, together with related disruptions, will exacerbate the negative impacts on access to services and poverty.This article combines recent panel surveys and existing household surveys collected before and after the advent of COVID-19 to shed light on the impacts of the p

12、andemic on households economic wellbeing. In particular, the focus is on the labor market. high-den- sity slum and urban areas, as well as areas of high localized density in Coxs Bazar, may be particularly vulnerable to this crisis, as lockdowns and social-distancing measures overlap with elevated r

13、isks of disease spread. Thus, we zoom in on these three areas to bet- ter understand the implications of COVID-19 for these labor markets.The analysis is motivated by the fact that im- pacts of the pandemic on households econom- ic well-being and poverty will largely depend on how labor markets resp

14、ond to the crisis, as labor income has been the main source of poverty reduction in the past (hill and genoni, 2019). Pre-existing vulnerabilities are therefore a source of concern, particularly for the urban poor. first, even before the COVID-19 crisis, a large share of the population 8 in 10 Bangl

15、a- deshis were poor or vulnerable to falling into poverty, suggesting that income losses related to COVID-19 are likely to push a large share of the population into poverty. second, a sub- stantial part of this vulnerability, particularly in urban areas, arises from the fact that incomes among a lar

16、ge share of Bangladeshi workersand their households depend on activities that are being directly affected by the crisis. Third, the absence of formal safety nets is expected to exacerbate impacts, as income shocks tend to be largely managed with households own resources.Information from the recently

17、 collected rep- resentative phone surveys in poor and slum areas of Dhaka and Chittagong and in Coxs Bazar highlight the substantial labor market impacts due to COVID-19. Job losses and tem- porary absence are widely reported in all three areas, with Dhaka reporting the largest job losses, whereas i

18、n Coxs Bazar, respondents tended to report being employed, but tem- porarily absent from work. given the largely informal nature of the jobs held by the major- ity of active and temporarily absent workers who report themselves as being employed, it is difficult to predict how fully this currently re

19、ported employment will translate into active jobs post-lockdown. Job and monetary losses are accompanied by widespread uncertain- ty about whether people will be able to keep their jobs or keep their businesses running.In addition, given the low rates of female labor force participation, women appea

20、r to be dis- proportionately affected by the COVID-19 crisis and have experienced relatively higher job loss- es. In Dhaka and Chittagong, these have trans- lated into women leaving the labor force, while in Coxs Bazar, women have been more likely to look for work. In addition, in Dhaka and Chit- ta

21、gong, women who remained actively work- ing experienced larger declines in earnings and more uncertainty about their job prospects.The analysis indicates that the differential im- pacts across areas and gender are linked to workers occupations before the crisis. The COVID-19 pandemic has disrupted a

22、ctivities to varying degrees, and workers in certain vulner- able activities have been more affected. The differential impacts for women are also related to their engagement in highly impacted sectors, such as garments and housemaid services.The next section describes the panel surveys and household

23、 surveys used for the analysis. Subsequently, the main findings are presented. The final section provides some reflections.Data sourcesnational-level analysis before the COVID-19 crisis relies on the household Income and Expenditure survey (hIEs) collected between april 2016 and March 2017 by the Ba

24、ngladesh Bureau of Statistics. This is the latest official source of household income, consumption, and poverty data for Bangladesh (ahmed et al, 2017, 2020). The findings post COVID-19 draw on two rapid panel phone surveys described below.Monitoring surveys in poor and slum areas of Dhaka and Chitt

25、agong City CorporationsTo track the impacts of the COVID-19 crisis on labor markets and household coping strategies, a rapid phone survey was implemented on a representative sample of households living in poor and slum areas of Dhaka and Chittagong City Corporations (CCs). The analysis presented her

26、e summarizes results from the first round of the rapid phone survey conducted from June 10 to July 10, 2020.The monitoring survey built on baseline sur- veys conducted before the COVID-19 crisis. The sample for Dhaka is a follow-up of the DIgnITy (Dhaka low Income area gender, Inclusion, and poverTy

27、) survey which was representative of low-income areas and slums of the Dhaka City Corporations and an additional low-income sitefrom the greater Dhaka statistical Metropolitan Area, following a two-stage stratification design. The enumeration areas were selected during the first stage using probabil

28、ity proportional to size, stratified by the poverty headcount ratio esti- mated using small-area techniques. all house- holds in the selected enumeration areas were listed during the second stage, from which20 households were selected for interview- ing based on a demographic stratification. This se

29、cond level of stratification was defined as follows: (i) households with both working-age male and female members; (ii) households with only a working-age female; (iii) households with only a working-age male. households were ran- domly selected from each stratum with the pre- determined ratio of 16

30、:3:1 (Kotikula et al, 2019). The DIgnITy survey, administered between July and september 2018, collected information from 2,376 individuals across 1,302 households.The monitoring survey in Chittagong is a follow- up of the CITy (Chittagong low income area Inclusion, and PoverTy) survey carried out i

31、n Chittagong City Corporation following the same sampling strategy as the DIgnITy survey. Data was collected from 1,289 individuals across 805 households between september and October 2019. figure 1 presents the location of the sampled areas in Dhaka and Chittagong.a. Dhakadignity_neighborhooda. Chi

32、ttagongFigure 1. Location of sampled areas in Dhaka and ChittagongSource: authors rendition, based on the DIgnITy and CITy data.for the monitoring survey, a representative sub-sample of 1,500 households out of a total 2,107 baseline households was targeted. The recontact rate was 1,483 households (9

33、9.5 percent). In this first tracking survey 1,483 out of the 3,665 adults surveyed in baseline were covered. It is important to note that at the time of the follow-up, 2.3 percent of adults had moved residence from their baseline location. The analysis includes those adults even though they are curr

34、ently located outside the City Corporations. given the small share of the sample that moved, the results are not affected by their inclusion.Table 1 presents some descriptive characteris- tics by area and gender. The adults interviewed in 2020 were 35 years old on average, and 45 percent of them wer

35、e female. approximately 57 percent of the adults interviewed were the main breadwinner of households with an aver- age household size of 4 people. On average, 1.4 household members generate income. respon- dents from Dhaka are more likely to be living in slum areas than those located in Chittagong (

36、70 versus 52 percent, respectively). Chittagong households are larger (0.4 members more on average) and therefore show higher dependen- cy ratios. about 49 percent of slum residents are women, on average, contrasting with a low- er percentage in other areas (39 percent).Bangladeshs local economy sta

37、rted experi- encing impacts of the COVID-19 crisis in early to mid-March 2020, with the countrys first case being reported on March 7. a full coun- trywide lockdown was in place from March26 to May 28, 2020. The monitoring survey measured outcomes across three periods: (i) During the survey period (

38、7 days prior to sur- vey period between June 10 and July 10; (ii) from March 25 to the time of the interview for individuals who reported being unemployed in the week preceding the interview; and (iii) from January to March 25, 2020, for individu- als who reported being unemployed from 25 March onwa

39、rds (immediately before the lock- down started).Coxs Bazar rapid phone surveya rapid phone survey was implemented in april-May 2020 on a representative sample of recently displaced rohingya households and their host communities in the Coxs Bazar dis- trict of Bangladesh, to track the impacts of theC

40、OVID-19 crisis on labor markets, wages, and household coping strategies. This survey built on the 2019 Coxs Bazar Panel survey (CBPs), which is a multi-topic survey that focused on socio-economic outcomes and access to health services.Table 1. Descriptive characteristics of adults living in poor and

41、 slum areas of Dhaka and ChittagongMaleFemaleNon- SlumDhakaChittagong SlumAllfemale (%)44.845.344.248.7 39.4age (mean)35.035.134.834.735.637.1 32.5Breadwinner (%)57.458.756.256.957.692.1 14.7household members (#) 4.3Members who contribute1.411.431.381.441.361.43 1.39to hh earnings

42、(#)slum (%)61.170.452.057.0 65.9Dependency ratio(Members 15-64/Members15 and 65+)0.590.570.610.600.570.550.63Observations1483836647951493770 713Note: Information from round 1 collected between June 10 and July 10, 2020. figures are weighted.The CBPs was designed to be representative of recently arri

43、ved rohingya (displaced after august 2017) and Bangladeshi households re- siding in host communities in Coxs Bazar, and the baseline for this survey was completed in august 2019. The CBPs survey was represen- tative of two types of hosts: those with low and high exposure to the Rohingya influx. To d

44、istinguish between host communities that are more or less affected by the arrival of the rohingya, the surveys sampling strategy uses a threshold of 3-hours walking time from a campsite to define two strata for hosts: (i) host communities with potentially high expo- sure to the displaced rohingya, a

45、nd (ii) host communities with potentially low exposure. Table 2 summarizes key characteristics of the CBPs baseline respondents in host communi- ties (both high and low exposure).This first round of the rapid phone survey, one of a series of high frequency follow-up surveys to track the evolution of

46、 the COVID-19 crisis, was conducted from 21 april-20 May 2020 (a month into the two-month-long COVID-19 lockdown). a sub-sample of 3,176 out of the 5,020 households surveyed at baseline were covered by this survey. The baseline CBPs survey was designed to be administered to two randomly selected adu

47、lts in each household. In this first tracking survey, 3,009out of the 9,045 adults surveyed in baseline were covered.2similarly to the Dhaka and Chittagong surveys, the labor module for the Coxs Bazar survey measured outcomes across three periods:(i) During the survey period (7 days prior to survey

48、period in late april to mid-May); (ii) from March 1 to early april 2020 for individuals who report being unemployed during the survey period (when a potential lockdown was under discussion and gradually came into effect); and (iii) from January to early March 2020 for individuals who report being un

49、employed from March 1 onwards (when the first known cases of COVID-19 were identified in Bangladesh).The findings from the follow-up are present- ed as a panel update on baseline Bangladeshi adults. Employment is defined as the share of the labor force reporting having worked at least one hour in th

50、e past seven days or being temporarily absent from work. The labor force is defined as adults over the age of 15 who are either currently employed or not employed but actively seeking work over the past seven days. similarly, unemployment rates are re- ported as a percentage of the labor force that

51、has not worked in the past seven days or been temporarily absent from a job but has actively looked for work in the stated recall period.Table 2: Descriptive statistics for host communities, Coxs Bazar Panel SurveyHouseholdsAdult Respondents%womenHousehold sizeAges 0-6Ages 7-14Ages 15-64Ages 65+Fema

52、le- headed% householdswomenAge (av- erage)50.7%5.116.6%21.6%58.0%3.7%17.7%57.4%33FindingsPre-crisis vulnerabilitiesThe impacts of COVID-19 on households eco- nomic well-being and poverty will largely de- pend on how labor markets respond to the cri- sis, as labor income has been the main source of B

53、angladeshs poverty reduction in the past and, on average, comprises more than 80 per- cent of total household income for the poor- est 40 percent of households (hill and genoni, 2019). Pre-existing vulnerabilities are thereforea source of concern, particularly for the urban poor who rely on the info

54、rmal sector for work and incomes.Even before the COVID-19 crisis, a large share of the population 8 in 10 Bangladeshis 2 The results are weighted using adjusted baseline weights that account for non-response and selection into the inter- view based on characteristics measured at baseline.were poor o

55、r vulnerable to falling into poverty. according to the hIEs 2016/17 about 25 percent of the population were living in poverty and another 54 percent could be considered vulnerable, as they had consumption levels very close to the poverty line (between the official upper poverty line and twice the li

56、ne).3 Poverty and vulnerability were high in both urban and rural areas (figure 2), suggesting that income losses related to COVID-19 are likely to push a large share of the population into poverty.focuses on short-term labor-income impacts due to slower GDP growth in the fiscal year 2020. The analy

57、sis considers the slowdown in growth in agriculture, industry, and services, along with changes in inflation.5 It uses a full pass-through rate to model a slowdown in household real incomes and increases in the cost of living. Moreover, as an important share of household incomes are informal and not

58、 well captured in macro-growth projections, the simulation separately models additional reductions in labor incomes for daily and in- formal workers, as well as for self-employedFigure 2. Poverty and vulnerability by area (% of the population)PoorVulnerableMiddle class192527515455301922100806040200N

59、ationalRuralUrbanSource: authors calculations using hIEs 2016/17.Note: Poverty defined using the official upper poverty rate. Vulnerable households are households with per capita con- sumption between the official upper poverty line and twice the upper poverty line. Middle class households are those

60、 with per capita consumption above twice the upper pov- erty line.a micro-simulation using the hIEs 2016/17 was conducted to assess the potential impacts of the COVID-19 crisis on household per capita consumption and poverty rates in 2020, com- pared to a non-COVID situation.4 The simulation 3 Pover