Parallel Realities: Exploring Poverty Dynamics using Mixed Methods in Rural Bangladesh

Peter Davis and Bob Baulch

All photos in this presentation © 2008 Peter Davis

Introduction• In poverty research, different methods

often lead to different findings• In the study of poverty dynamics

differences may be magnified

• Differences in findings can lead us to:– critically assess methods– mix methods strategically to

strengthen research findings– attempt to uncover drivers of change

more reliably– and therefore be able to suggest

more effective interventions

The focus of this presentation

• What can we learn by integrating quantitative and qualitative assessments of socio-economic mobility of the same individuals and households?

• The implications of these lessons for:– poverty-dynamics research– interventions to reduce chronic

poverty

The CPRC-DATA-IFPRI Bangladesh longitudinal study

• The study combined three IFPRI evaluations which started in 1994, 1996 and 2000/03, and used a mixture of quantitative and qualitative methods

• In 2006-7 we resurveyed the entire set of these households (plus new households created due to household division ) in three phases (qual-quant-qual)

The 2006-7 Study’s 3 Phases3 phases of data collection:• Summer 2006: focus group discussions

investigating causes of decline and improvement and the long term impact of 3 interventions (116 FGDs in 11 districts)

• Winter 2006-7: quantitative resurvey of panel households (1787 core + 365 splits in 14 districts)

• Spring-Summer 2007: life-history interviews and village histories in 8 districts (161 households – 293 individuals)

Map of the Study Sites

Nilphamari (38)

Kurigram (39)

Tangail (39)

Kishoreganj (19)

Mymensingh (18)

Manikganj (72)

Jessore (36)

Cox’s Bazar (32)

Life-history districts (number of interviews)

Poverty and Growth in the Study Sites

  Microfinance(1994-2006)

Agricultural technology(1996-2006)

Educational transfers(2000-2006)

Poverty headcount

Poverty in baseline survey

60% 62% 71%

Poverty in 2006/2007 21% 13% 28%

Growth in Per Capita Expenditures

Over period 28.0% 43.5% 44.3%

Annualised 2.1% 3.7% 6.5%

Methods used to assess poverty transitions 1) Quantitative: transition matrices based on per capita expenditures and the BBS upper poverty lines2) Qualitative: Changes in individual well-being levels

LevelEnglish Bangla Guideline

1Very poor ordestitute

khub gorib, na keye chole

Suffering tangible harm to health because of poverty, generally due toinsufficient food. Usually landless or near landless

2

Poor goribVery vulnerable but eating reasonably well. Could easily move into 1 due to a common shock. For a medium size household, usually less than an acre for a medium sized household

3

Mediummadhom

A common shock would not result in tangible harm or going without food. Hold household assets or generate household income equivalent to between one

andtwo acres of land for a medium-sized household.

4Rich

dhoniHold household assets or generate household income equivalent to thatgenerated by two to ten acres for a medium-sized household.

5Very rich

khub dhoniHold household assets or generate household income equivalent to that generated by ten acres or more for a medium sized household.

Transition matrix(from per capita expenditures)

First round

(1994,1996,

2000)

2006-7  

Poor Non-Poor Total

Poor 394 1081 1475

Non-Poor 66 598 664

Total 460 1679 2139

Transition matrix(from well-being levels)

First round

(1994,1996,

2000)

2006-7  

Poor Non-Poor Total

Poor 170 14 184

Non-Poor 23 86 109

Total 193 100 293

Mismatches between Qual and Quant Assessments of Poverty Dynamics

quantitativeexpenditure-basedcategories

qualitative wellbeing categories

(numbers of people)

PP PN NP NN Total

PP 50 3 4 9 66

PN 74 3 13 31 121

NP 20 0 2 4 26

NN 26 8 4 42 80

Total 170 14 23 86 293

Exploring the ‘mismatches’

1. Cases where per capita expenditure does not accurately reflect the economic wealth of the household– Asset-based transitions have more matches

1. Expenditure an imperfect indicator of wealth

Classifying quant transitions using land assets halves the mismatches

quantitative asset-basedcategories

qualitative matrix categories (numbers of people)

PP PN NP NN Total

PP 99 8 0 14 121

PN 6 0 3 6 15

NP 41 2 7 6 56

NN 24 4 13 58 101

Total 170 14 23 86 293

Box 1: Expenditure is an imperfect indicator of wealth

(qual PP: quant NN)Circumstances:• Woman (57)• Sold land to live

while husband ill - died in 1980

• Lives with son (29) working as a mason

• Son injured 1996-2001

• 4 decimals of land owned

• Own illness since 2004

1994 2007 Per Capita Expenditure 778 2538 Poverty line (BBS) 547 877 Land owned (decimals) 100 4

Exploring the ‘mismatches’

1. Expenditure is an imperfect indicator of wealth– Asset-based transitions have more matches

2. Cases where households’ expenditures are close to the poverty line in either, or both, survey rounds.– High numbers of households near the poverty lines

mean small changes in expenditure can cause transitions

2. Proximity to poverty lines: Distribution of per capita expenditures

and poverty lines0

.001

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Pro

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f H

ou

seho

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0 1000 2000 3000 4000Monthly per capita expenditure

1996

0.0

01

.002

Pro

port

ion o

f H

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0 1000 2000 3000 4000Monthly per capita expenditure

2007

Agricultural Technology Sites

Box 3: Proximity to poverty lines(qual PP quant NP)

1994 2007Per cap. Expenditure 796 690Poverty line (BBS) 547 877Household members 3 4Land owned (decimals) 13 3

Circumstances:

• Man 26• Married in 1996• Split from

parents in 2001• Lives with wife

and 2 daughters

• Only one household member the same as in 1994

• Day labourer• Own one cow

Exploring the ‘mismatches’1. Expenditure is an imperfect indicator of wealth

– Asset-based transitions have more matches2. Proximity to poverty lines

– High numbers of households near the poverty lines mean small changes in expenditure can cause poverty transitions

3. Non-monetary aspects of ill-being were not detected in the expenditure-based measurement-domestic violence, disability, illness, or vulnerability

Box 4: Non-monetary aspects of illbeing not detected(qual PP but quant PN)

Circumstances• Man (45) living with

his wife (36), 2 daughters, 2 sons

• Drives a van gari• One disabled daughter• Own chronic illness

since 2002• Dowry problems for

eldest daughter

1996 2007 Per Capita Expenditure 312 931 Poverty line (BBS) 551 773 Household size 6 6 Land owned (decimals) 174 12

Exploring the ‘mismatches’1. Expenditure is an imperfect indicator of wealth

– Asset-based transitions have more matches– Liberal spenders versus frugal spenders

2. Proximity to poverty lines– High numbers of households near the poverty lines

mean small changes in expenditure can cause transitions

3. Non-monetary aspects of ill-being were not detected in the expenditure based measurement-domestic violence, disability, illness, or vulnerability

4. Cases where changes in household size (often due to a ‘split’) led to changed household economies of scale

Box 5: mismatch caused by diseconomies of scale qual PP but quant PN

Circumstances• Woman (56) living

with her husband (64)

• Income from selling snacks

• 10 decimals of homestead land,12 trees

• 2 daughters and 3 sons separated

• Land sold to pay for daughter’s dowries

1994 2007 Per Capita Expenditure 412 906 Poverty line (BBS) 501 799 Household size 7 2

Exploring the ‘mismatches’

1. Expenditure is an imperfect indicator of wealth– Asset-based transitions have more matches– Liberal spenders versus frugal spenders

2. Proximity to poverty lines– High numbers of households near the poverty lines mean

small changes in expenditure can cause transitions3. Cases where some non-monetary aspects of ill-being were

not detected in the expenditure based measurement (such as the impact of domestic violence, disability, illness, or vulnerability)

4. Cases where changes in household size (often due to a ‘split’) led to changed household economies of scale

5. Cases where recall errors affected qualitative assessments

Sequential reduction in mismatches

Individual (per cent) Cumulative (per cent)

Total mismatches 196 (66.9) 196 (66.9)

Wealth not expenditures 93 (47.4) 103 (35.2)

Proximity to poverty line 60 (30.6) 69 (23.5)

Non-monetary aspects of ill-being

43 (21.9) 60 (20.5)

Changes in household size

33 (16.8) 46 (15.7)

Qualitative recall errors 16 (8.2) 42 (14.3)

Trajectory patterns

Direction Pattern DepictionNumber of Cases

Weighted Percent of

Cases

Stable Smooth 8 1.47

Improving Smooth 3 1.43

Declining Smooth 2 0.36

Stable Saw-tooth 135 44.98

Improving Saw-tooth 76 26.15

Declining Saw-tooth 30 6.90

Declining Single-step 2 0.48

Declining Multi-step 37 18.22

Total 293 100

Lessons from integration• Movement across monetary poverty lines can happen

with little tangible change in people’s well-being

• Various types of vulnerability are not visible in standard quantitative approaches

• Including assets helps to improve assessments

• Studying individuals and households over long periods adds to the conceptual and methodological complications of poverty measurement

• With new challenges to understand the impact of global changes on the chronically poor, we need reliable mixed-methods approaches to poverty dynamics

Some conclusions• Movements out of poverty are usually slow -

declines can be fast and irreversible• People move out of poverty

– by building up assets (land, livestock etc.) business, agriculture, educated children working, employment and remittances

• People moving out of poverty are still vulnerable– food prices, loss of income, illness, dowry

• Better understanding of the crises and opportunities poor people face assists in prioritising and rationalising anti-poverty interventions and enhancing social protection

The end ...

...but work continues...