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Foreword

Poverty maps are powerful visuals that enable government c1vH soc1ety and development partners to identify poorer areas with greater accuracy. In Bangladesh. there Is considerable demand from policy makers. planners. and researchers for more disaggregated poverty estimates to better understand the geographical variations and spatial inequality in growth and poverty .

Responding to this demand. the Bangladesh Bureau of Statistics initiated the poverty mapping exercise in September 2012. The World Bank and the World Food Programme (WFP) are pleased to have had tho opportunity to contribute to this updating exercise.

The initiative produced poverty estimates for key sub-national administrative units us1ng data from both the 2010 Household Income and Expenditure Survey (HIES) as well as the 2011 Population Census. and we hope the maps produced will strengthen the targeting of policy interventions and programs. building on the 1m proved knowledge of local conditions.

Poverty estimates for Bangladesh based on both the HIES and the poverty mapping exercises show that Rang pur and Barisal divisions have the highest incidence of poverty. while Chittagong and Sylhet have the lowest. The poverty maps have also been compared with other correlates of poverty - such as educational attainment of household heads and the average agricultural wage rate of laborers. The aim is for this mapping exercise to help policy makers make better informed decisions about poverty reduction Initiatives and design programs that serve those who need help the most.

With strong commitment sound policies. and effective government. Bangladesh has enormous potential to offer 1ts people a better. brighter future. We look forward to furthenng our partnership with the Government of Bangladesh and development partners to jointly tackle development challenges faced by the people of Bangladesh - to end poverty and boost shared prosperity in the country.

Johannes Zutt

Country Director World Bank Bangladesh

Golam Mostafa Kamal

Director General Bangladesh Bureau of Statistics

Christa R~der

Country Representative World Food Programme

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Acknowledgements

The World Bank team involved in preparation of the Poverty Maps included Faizuddin Ahmed, Naomi Ahmad, Mehar Akhter Khan, Dean Jolliffe, Mehrin A Mahbub, lftath Sharif, Nobuo Yoshida, and Salman Zaidi (task leader}, working under the guidance of Vinaya Swaroop (Sector Manager, SASEP} and Johannes Zutt (Country Director, Bangladesh, Nepal and Bhutan). The World Food Programme (WFP) team included Mahabubul Alam, Nusha Choudhury, and Kaye nat Kabir, working under the guidance of Christa Rader (Country Representative, WFP). The BBS team included Md. Zahidul Hoque Sardar, Dipankar Roy, AKM Tahidullslam, Md. Abdul Latif, Dinesh Roy, Enayet Hossain, Md. Rezaul Karim, and Md. Jibon Miah. Faizuddin Ahmed spearheaded the extensive analytical work to derive the regionally disaggregated poverty estimates using the 2010 HIES and 201 1 Population Census data sets. Mahabubul Alam and Faizuddin Ahmed prepared the various poverty maps presented in this report using GIS software.

The team acknowledges the leadership and support of Mr. Md. Nojibur Rahman (Secretary, Statistics and Informatics Division} and Mr. Golam Mostafa Kamal (Director General, Bangladesh Bureau of Statistics}. The team would like to thank members of the technical committee and the steering committee, who carefully reviewed both the methodology used as well as the results of the Poverty Mapping work. The team is also grateful to the UK Department for International Development (DFID} and International Fund for Agricultural Development (IFAD} for their financial support for the preparation and publication of the Poverty Maps .

3

Introduction

Poverty mapping is a statistical exercise to estimate the incidence of poverty at sub-national levels to enable the government, civil society organizations, and development partners to accurately identify locations with a relatively higher concentration of poor people. Due to the considerable demand from policy makers, planners, and researchers for more disaggregated poverty estimates, the current poverty mapping exercise was initiated in September 2012 by the Bangladesh Bureau of Statistics (BBS), the World Bank, and the World Food Programme (WFP) to produce reliable poverty estimates for key sub-national administrative units (zila and upazila) using data from both the 2010 Household Income and Expenditure SuNey (HIES) and the 2011 Population Census.1 According to this latest population census conducted by BBS, the total population of Bangladesh was about 150 million. For administrative purposes the country is divided Into 7 divisions. 64 districts. and 544 upazilas/thanas.

The HIES is conducted by BBS every 4-5 years. and is the main source of data for official poverty related statistics in Bangladesh. The World Bank has provided extensive technical assistance to BBS over the past two decades to help improve the quality and timeliness of data collected through this suNey. The official poverty estimates are computed from the HIES at the National and Division-level only due to the limited sample size of the suNey.

According to the latest 2010 HIES based estimates. poverty incidence in Bangladesh varies from a low of 26.2 percent in Chittagong division to a high of 42.3 percent in Rang pur division. Similarly, extreme poverty incidence (i.e. estimates based on the lower poverty line) vanes from 13.1 percent in Chittagong division to 27.7 percent in Rang pur division.

' Two other such poverty mapping exercises have been carried out earlter in Bangladesh us1ng data from (I) the 2000 HIES and 2001 Population census and (II) the 2005 HIES and the 2001 PopulatiOn census. 2 The deflnlllon of the upper and lowet' poveny lines can be found in the 2013 Bangladesh -Poverty Assessment Assessing a decade of progress in reducing poverty. 2000-2010.

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Administrative Structure of Bangladesh

Districts and Upazilas in number

Districts Upazilas

64 544 Districts Upazllas

In Bangladesh In Bangladesh

By Division

• Districts • Upazilas

Dhaka 163

Chittagong

Rajshahi

Rang pur

Khulna

Sylhet

Barlsal

Upper and Lower Poverty Estimates for Bangladesh (20 1 0 HIES) 2

Headcount Poverty Rate (Bangladesh) Percent

31.5% Upper Poverty

Line

17.6% Lower Poverty

Line

Bangladesh

Headcount Poverty Rate (Division) Percent

Upper Poverty Line • Lower Poverty Line

L Dhaka

Chlttagong

Rajshahi

Rang pur

Khutna

Sythet

Barisat

Source: 2013 Bangladesh Poveny Assessment. World Bank

Poverty Mapping Methodology

The poverty mapping methodology used in this exercise is the so-called ELL method developed by Elbers et al. (2003) using Small Area Estimation (SAE) techniques The ELL method, which has been widely tested and validated around the world, takes advantage of the strengths of both sources of data used in such exercises.

The HIES includes the extremely rich data collected in an integrated household survey, including expenditure data. However this is for a relatively limited sample of households. On the other hand, the Population Census includes all households in the country, but collects data on a limited set of topics. The two data sets, HIES and Population Census, have common set of explanatory variables. The SAE technique uses the parameter estimates from a consumption model derived using the 20 1 0 HIES data to predict/simulate consumption data for each census household. These predicted/simulated consumption data lor all 2011 census households are then used to estimate poverty rates at the zila and upazila level using the same poverty lines used to derive the official poverty estimates using the 2010 HIES data.3

Poverty estimates for the Bangladesh Poverty Map and Extreme Poverty Maps were derived by using the upper and lower poverty lines in the HIES 2010 published by BBS, which were also used in the World Bank's latest Poverty Assessment.~ The spatial distribution of poverty in Bangladesh at the upazila level is presented in the two maps on the next pages.

3 Further details on methodology used to de~ve these esumates can be found In the Poveny Mapping technical repon (available upon request from the World Bank Dhaka Olflce).

• ~ladesh ·Poverty Assessment Assessing a decade of progress In redUCing poveny, 20(X}2010. World Bank 2013.

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Bangladesh Poverty Map

India (Wcs1 13cngal)

India (Wcsl llcngnl)

lndtn (Wesl Bengal)

Pcrccntaf(c ol' the Popuhuion l'oot·

IS% or less

16% - 27%

28%-38%

Bo r

India (Assam)

f\dminislrnlivc Boundnry

lntcmalional Boundary

Divisional Boundary

-- Dis1ric1 Oou ndary

-- Upa:r.ila Boundary 39% -49%

I [ River I Ocean 50% or grealer * Capital

Proportion of Population below the *Upper Poverty Line 2010

*Note: The Upper poverty line corresponds to the moderate poor households whose food expenditure is at the level of the food poverty line us1ng the Cosl of Basic Needs/CBN method. Ref: Report of the Household Income £i Expenditure Survey/HIES 2010. BBS GoB.

Bay of Bengal

India (Mcghnlnyn)

India (Tripura)

.... c===----c=~ Km 0 25 50 75 100

'llle .ndmlni~l ffl th'< boundnrlei ••wl 1\JIIliC:~< ~o.l~n M lhu; tnllp do nQI hnpf) vfhdal Cll\IU111it.•mt:ll1 (Ill 11/XCplalX'C by the Unilcd N:ulon!i, lhe W<lf'ld &n~. 01 1}0~

l'i)\ (11)' 11¢11,1 Cowil kt!.!tl N11'1llcd u~ull 1~ t-11nall At~:.t 8umatcs CSAP) t«hniquc. Primlll)' •npub for the lNII)"tJt loclud~ f\lpu1ntHln Ulld l lou~oini l:c:Mllt lOl l and llll \ 2010

\ tap produced by WFP, 0$ Mil)' 201~

India (Assam)

Bangladesh Extreme Poverty Map

India (Wc>t Bengal)

India (West Bengal )

India (WcstUcngnl)

l'erccnhlgc of the l' olltllntion Extreme Poor

6% or lc>S

7%. 15%

16% . 24%

25%-34%

35% or greater

\ IJ ,JI'

l'abn

India (Assam)

randpur

AdminislnHivc Boundary

-- lmcrnational Boundary

Divisional Boundary

-- District Boundary

Upazila 13oundary

Ri ver I Ocean

* Capital

Proportion of Population below the *Lower Poverty Line 2010

• Note: The Lower poveny line corresponds to the extreme poor households whose total expendlturesareequal to the food poverty line using the COst of Basic Needs/CBN method. Ref: Report of the Household Income & Expenditure Survey/HIES 2010. BBS GoB.

Bhola

Bay of Bengal

India (Meghalaya)

\u r 1111

India (Tripurn)

---===----==::J Km 0 25 50 75 100

The ndnuniSUllll\'<: bOUIId.'ll'lt:i tm<l l'lll1M'f lJKYWn on Ou• map do not Imply ollku•l ('lldOI)ffi'Cflt 01 I«'C'piiiK"<' b)• tho: Ut~itc,J Nllltl)n.., the WCII'Id t)an\, a. UIJ\

1\weny I IClld Coont Rllt:l' C:f."liMIIlrd u,_in; the: Smlll Aftl Es1im.nus (SAt) • ~hnWlut. PrmUII')' lllp.ib (or the ualy,,. •.ncl\ldcd Population and ltoutou!J. {"t•n•"'" :'011 """' 1111~ 2010

( ' hittH~ •

Jl V ~

India (Assam)

Band ~rban

Results at a Glance

Division Level Poverty Estimates The poverty estimates derived through this Poverty Mapping exercise are quite close to those obtained from the 2010 HIES. The minor differences between these two sets of estimates (as summarized in the table below) are partly to be expected, since the methods used in the Poverty Mapping exercise match predicted consumption (i.e. not poverty rates) at the Mauza/Mahalla level in the two data sets - i.e. 2010 HIES and 2011 Population Census.

Comparison of Poverty Estimates: 2010 HIES and Poverty Mapping

Division

Bangladesh

Dhaka

Chittagong

Rajshahi

Rang pur

Khulna

Sylhet

Barisal

HIES

2010 Poverty Head count (in percent)

31.5

30.5

262

29.7

42.3

32.1

28.1

39.4

Poverty Mapping Exercise

2010 Poverty Headcount (in percent)

30.7

30.5

26.1

27.4

42.0

31.9

25.1

38.3

Number of Poor (as% of overall population)

100.0

32.3

16.8

11.6

15.0

11.4

5.7

7.3

• Poverty estimates for Bangladesh based on both the HIES and the poverty mapping exercises show that Rangpur and Barisal divisions have the highest incidence of poverty, while Chittagong and Sylhet have the lowest incidence.

• Because of their large overall populations. Dhaka division {32.3 percent) and Chittagong division ( 16.8 percent) have the highest share of Bangladesh's poor.

• Compared to other divisions. Sylhet division has both the lowest headcount rate (25.1 percent) as well as the lowest number of poor people {5.7 percent of the country's poor).

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Zila Level and Upazila Level Poverty Maps As the following maps on the next pages illustrate. the resolution of spatial variation in poverty incidence improves considerably on moving from the division to zila level and upazila level poverty maps - there is considerable spatial variation in poverty incidence within individual divisions.

Key features of the variation In poverty Incidence at the zlla level are highlighted below

Division Average Poverty Rate Minimum Rate Maximum Rate (in percent) (in percent) (in percent)

Dhaka 30.5 15.7 52.6 Dhaka district Shariatpur district

Chittagong 26.1 9.6 51.0 Noakhali district Chandpur district

Rajshahi 27.4 16.6 38.7 Bogra district Sirajganj district

Rang pur 42.0 26.7 63.7 Panchagarh district Kurigram district

Khulna 31.9 3.6 46.3 Kushtia district Satkhira district

Sylhet 25.1 24.1 26.0 Sylhet district Sunamganj district

Barisal 38.3 19.0 54.8 Barguna district Barisal district

Overall 30.7 3.6 63.7 Bangladesh Kushtia district Kurigram district

• Poverty incidence in the 10 poorest upazilas in Dhaka division is 55 percent or higher; by contrast poverty incidence in the 10 richest upazilas is less than 4 percent

• Similarly poverty incidence in the 6 poorest upazilas of Chittagong division is 50 percent or higher, while that in the 6 richest upazilas is less than 4 percent

• Even the poorest division of Bangladesh has considerable spatial variation in concentration of poverty: the incidence of poverty in the 11 richest upazilas in Rangpur division is lower than the national average; by contrast poverty incidence in the 7 poorest upazilas is more than twice the national average O.e. it is 60+ percent)

• While Sylhet division is amongst Bangladesh's most well-off regions. over 50 percent of the population of Gowainghat upazila lives below the national poverty line; similarly, 3 upazilas in Khulna division have a poverty rate of 50 percent or higher.

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Zlla Poverty Map HCR Upper Poverty Line

India (West Bcngn I)

Indio (West Bengnl)

N.•og-.wn

Kus:htia

India (West Bengal)

Bogm

Pabna

Percentage of the Population Poor

[_ c

20% or less

21%- 29%

30%- 36%

37%- 46%

4 7% or greater

Uhola

I

India (Mcghnlnyn)

Sunamg:1nj

./Sylhet

'lo>khalo

Hobig>nj

India (Tripura)

Bay of Bet~ gal

0 IS 30 60 90

International Boundary

Division Boundary

District Boundary

River I Ocean

S>lhtt India (Assam)

M>uh ob:llllr

Rang:unati

Bandari>:on

Myanmar

Upazila Poverty Map HCR Upper Poverty Line

India (West Bengal)

India (West Bengal)

NIIOgdOO

Jessore

India (West Oengnl)

Tongod

Bay of Benxal

India (Mcghalaya)

Sunamganj

India (Tripum)

.:::IIICJ--..:===---•Km 0 IS 30 60 90 120

Percentage of the Population Poor -- International Boundary

Division Boundary

District Boundary

Upat:ila Boundary

River I Ocean

15% or less 39%- 49%

16%- 27% 50% or greater

28%-38%

Rangamati

India (Assam)

Myanmar

Key Correlates of Poverty Incidence in Bangladesh

The reliability of the poverty maps can be evaluated by comparing the estimates obtained from the poverty mapping exercise with the results of the PerceptiOn SuNey on Relative Prevalence of Poverty commissioned by the WFP in 2014 in 16 districts across Bangladesh. The results reveal a very high correlation between the two sets of poverty estimates, and provide strong corroborating evidence of the robustness of disaggregated poverty estimates obtained from the Poverty Mapping exercise.

The poverty maps can also be compared with other geographic and regional characteristics that are likely correlated w1th poverty incidence.

The Poverty Map and Average Agricultural Wage Rate of Male Laborers Zila Poverty Map HCR Upper Poverty Line

India (West Bengal)

India (West Bengal)

Ku!r>hlln

India (Wcsl Bengal)

Percentage of the Population Poor

20% or less 37% - 46%

21 %-29% 4 7% or greater

30%-36%

Bay of Bengal

0 IS 30 60 90

lndi:t (Meghalnya)

SunamglnJ

llobipnJ

India (Tripurn)

-International Boundary

Division Boundary

-- District Boundary

River I Ocean

Rangatn.lti

India (Assam)

Myanmar

The maps contrast poverty rates with average agricultural wages rates (BBS datal. and illustrate the negative association between these two variables. Darker areas on the maps correspond to areas with high poverty rates and low wage rates.

Average Agriculture Wage Rate

Wage Rate (BOT)

86 - 102

103 - 118

119 - 140

Bogra Region

Jamalpur Region

141- 164

165 - 211

Dhaka Region

. ./

0

Noakhali Region

" r ·- ~.J/ '· ~ "'\~

/ ) . ..... Bay of Bengal

35i:::::::=70

\

Regi

I

\

140 KM

The Poverty Map and Educational Attainment of Household Heads Zila Poverty Map HCR Upper Poverty Line

India (Wcs1 Ocngnl)

NJO¥;wn

India (Wesl Bengal)

lndiu (Meghnlayn)

SunlmJ-11\J

./Syl

Sylh<t

Alauh'lb37ar

India (Wes1 Bengnl)

Kuslui~•

Pabna

Percentage of the Population Poor

20% or less 37% - 46%

21%- 29% 47% or greater

30% -36%

I

llobig;mj

India (Tdpurn)

Bay of 8 e11gal

.::::.1::1---====---Km 0 IS 30 90 120

I nlernational Boundary

Division Boundary

District Boundary

Ri ver I Ocean

India (J\ ssam)

The maps compare poverty rates with educational attainment of household heads (2011 Population census data). Darker areas on the maps correspond to areas with high poverty rates and lower rates of completion of primary education. As the maps show. districts in north and southeastern Bangladesh whose poverty rates are high also suffer from low primary school completion.

Household Head Completed Primary Education

Percentage(%) of Household Head with Primary Education

9% or less I 1 15%- 16%

I 0% - 12% I I 17% or greater _..., 13%- 14%

I .r

' Bay of Bengal

---. lntcmutiouai Doundnry

-- Divisionnl 13oundnry

-- District 13oundury

River I Ocean

HabiganJ)

\.,

Sylhet

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Concluding Remarks Poverty Mapping is a powerful tool for Identifying and monitoring pockets of affluence and poverty across the country. The resultant maps provide a rich information base and can be used to help policy makers and development partners better plan their resource allocations. which in turn can contribute to faster and more effective poverty reduction. The usefulness of poverty maps can be further reinforced by combining them With other gee-referenced databases such as maps of human development indicators. maps of natural disasters, and maps of the impending 1mpacts of climate change .

Cover Photo Mahfuzul Hasan Bhuiyan

Designed by Mohammad lnamul Shahriar and printed by Progressive Printer Private Ltd., Bangladesh

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