1

Poverty Monitoring

Taking a Stock of What is Out There

Ruslan Yemtsov and Asad Alam

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Plan

• International publications on poverty monitoring

• Poverty monitoring: separate activity or integral part of statistical work?

• Data quality: is there a difference between what is needed for poverty monitoring and other purposes of statistical work

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Sources

• World Bank

• UN Statistical Commission

• UNDP

• Eurostat/European Commission

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Key elements of poverty monitoring

• Key poverty indicator: headcount (and associated measures) is monitored over time – There is (are) regular representative survey (s) done with certain

intervals (frequency)– Which allows comparisons over time and with other sources of

data – e.g. SNA (consistency)– And in addition to income/consumption poverty contains other

policy relevant data– That this is transparent process to derive poverty indicators

(access)– There is officially established consistent poverty line which

allows comparisons (regularized)• Key elements of poverty monitoring are identical to

key elements of good Household survey system

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Does it have to be official?

• Most poverty indicators in the world are based on surveys conducted by the Government statistical agencies

• But a lot of data are supplied by surveys conducted outside statistical offices (often with state support)

• What matters is quality of data and transparency of their use

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General aspects of quality

• Representativeness: surveys are nationally representative and, for larger countries, regionally/sub-nationally representative.

• Integrativeness: data on different dimensions of living standards are available from the same survey so as to permit a multidimensional analysis.

• Regularity: surveys follow a regular, predictable, preferably annual cycle

• Consistency: surveys are comparable over time and with other data

• Accessibility: unit record data are publicly available according to a transparent, rules-based system.

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Representativeness, frequencyand cost

• Representative data requires proper sampling

• Larger surveys allow collect representative data for more units / breakdowns

• But larger surveys are more difficult/expensive to do frequently

• It is hard to get an optimal balance

• But it has to be a balance

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Household Sample Sizes

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Household sample size in EU-SILC - cross-sectional component

2250 Iceland

3250 CyprusLuxembourg

3750

IrelandLatvia

NorwaySlovenia

4000 FinlandLithuania

4500Austria

PortugalSweden

4750

5000 Netherlands

6500 Spain

7250 FranceItaly

7500United

Kingdom

8250

Household sample size for 27 countries: 127.000

Germany

BelgiumGreece

Czech RepHungary

4250DenmarkSlovakia

3500 Estonia

3000 Malta

6000 Poland

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Consistency

• Comparability over time

• Comparability with other sources of information

• Copnmparabiliity with other countries

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• Global relationship between survey and NA means holds for ECA; quality problems may be on both sides

• Data show a consistent relationship between macro and survey data at the country level

Source: Angus Deaton Measuring poverty in a growing world 2004 Note: ECAPOV definition of consumption (no health, durables and rental)

Consistency: survey and macro (1) WORLD ECA

H U N02

H U N01

H U N00

H U N99H U N98

POL02POL01POL00

POL99

POL98

R U S02R U S01R U S00

TR K02

R U S99

R U S97R U S98

BEL02

KAZ03

BEL01

KAZ02

SAM03

BEL00

BEL98

KAZ01

BU L03

R OM02

BU L01

SAM02

U ZB02

R OM00R OM01

R OM98

U ZB03

BEL99

R OM99

U KR 02

U ZB01

U KR 03

ALB02

GEO02

GEO01GEO00

AR M02

GEO99GEO98

GEO97

AR M01AR M00

MOL03MOL02KYR 01KYR 02

MOL01

KYR 00MOL98

MOL00

MOL99

TAJ 03

TAJ 99

.4.6

.81

1.2

Act

ual r

atio

: Sur

vey

to N

A c

ons.

/sm

ooth

5 6 7 8 9LNNAGDPPC1995PPP

Consumption Survey/NA for ECA

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• On average growth rates as measured by survey data in ECA (and globally) are robust to the measurement problems

• Tight correlation between changes in household consumption from SNA and survey mean consumption (0.75)• But outliers

Consistency: Survey and macro (2)

GSM=-0.634+0.834GPC R2=0.228

WORLD WITHOUT ECA (43 countries, 115 spells) ECA (15 countries, 43 spells)

Source: M. Ravallion Measuring Aggregate Welfare In Developing Countries: How Well Do National Accounts And Surveys Agree?

Note: $ 2.15 at 2000 PPP as a poverty line

H U N02

H U N01

H U N00

H U N99

POL02POL01

POL00POL99

R U S02

R U S01

R U S00

R U S99

R U S98

BEL02KAZ03

BEL01

KAZ02SAM03

BEL00

BU L03

R OM02

U ZB02

R OM00

R OM01

U ZB03

BEL99

R OM99

U KR 03GEO02

GEO01GEO00

AR M02

GEO99

GEO98AR M01

MOL03

MOL02

KYR 01

KYR 02

MOL01

MOL00

MOL99

TAJ 03

-.2

-.1

0.1

.2G

row

th r

ate

in s

urve

y m

ean/

Fitt

ed v

alue

s-.2 -.1 0 .1 .2

Grow th rate in NA consumption

GSM=-.002+.776GPC

R2= 0.354

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Coverage/integrativeness

• Covering different dimensions of living standards at once

• Covering mobility at the individual level

• Compatible with other sources of information – Personal ID– GSD– Info on HH networks

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Why coverage is important? Poverty is linked to deprivation in

other dimensionsOverlapping Poverty Dimensions

No access when ill=39

Consumption poor=8

2 7

2

1

28

9

3

Russia, 2002

All Population=100

No Piped Water=19

155

EU-SILC : domains coveredHousehold information

Basic data

(including degreeof urbanisation

(X,L)

Income (X,L)Total household

income (gross and disposable)

Gross income at component level

HousingDwelling type,

tenure status and housing

conditions (X,L)Amenities (X)

Housing costs (X)

Social exclusionHousing and non-housing

related arrears (X,L)Non-monetary deprivation indicators (X,L)

Physical and social environment (X)

Labour information (X)

Child care

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EU-SILC: domains covered - Personal information

Demographic data (for persons aged

under 16 (X,L), for persons aged 16+ (X,L)

and for former household members (L))

Income (X,L)(gross personal income,

total andcomponents

Basic data

(X,L)

HealthHealth status and

chronic illness and condition (X,L)

Access to health care (X)

Education (X,L)(including highest

ISCED level attained)

LabourBasic information on current activity

and current main job, incl on last main job for unemployed (X,L)

Basic information on activity status during income reference period (X)

Total number of hours worked on current second/third jobs (X)

Detailed labour information (X,L)Activity history (L)

Calendar of activities (L)

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Access

• Dimensions:– “Internal” access for stat office staff– Access for international organizations– Access for researchers/institutes– Access for other parts of the Government

• Elements– Data dissemination standard (see

http://www.surveynetwork.org/home/)– Rules and procedure that enable timely access to

anonymized micro datasets– Capacity/culture

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National poverty lines around 2000, in PPP

ECA Countries Hungary

Latvia Ukraine

Tajikistan

Bulgaria

Non-ECA Countries

NigeriaBurkina

Faso

Greece

Portugal

0

1

2

3

4

5

6

7

8

9

1 10 100

Level of consumption per capita, $ a day/person

Nat

ion

al p

over

ty li

nes

, $ a

da

y/ p

erso

n

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Background

• Recent history of poverty monitoring• Systematic data collection effort for poverty

monitoring initiated within the last few years, with technical and financial support from the donor community:– Albania (2002), Bosnia and Herzegovina (2001),

Kosovo (2000), FYR Macedonia (1997), Montenegro (2002), Serbia (2002)

• The first Poverty Assessments produced subsequently

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Institutional Arrangements

• Data collection and poverty monitoring typically led by the main Statistical Agency, with strong donor support

• Main actors in the donor community: the World Bank, Italy’s Istituto Nazionale di Statistica (ISTAT), and the UK Department for International Development (DfiD) in two or more countries in the Western Balkans; Statistics Sweden/SIDA in Kosovo and UNDP in Bosnia

• Generally very little capacity for poverty monitoring and analysis outside of Government

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Poverty monitoring in ECAFreq/Repr Coverage Consistency Access

Albania LSMS LSMS LSMS LSMS

Armenia IHS IHS IHS HIS

Azerbaijan HBS HBS HBS HBS

Belarus HBS HBS HBS HBS

Bosnia and Herzegovina LSMS->HBS LSMS->HBS LSMS->HBS LSMS->HBS

Bulgaria IHS IHS IHS IHS

Croatia HBS HBS HBS HBS

Czech Republic HBS HBS HBS HBS

Estonia HBS->SILC HBS->SILC HBS->SILC HBS->SILC

FYR Macedonia HBS HBS HBS HBS

Georgia IHS IHS IHS IHS

Hungary HBS->SILC HBS->SILC HBS->SILC HBS->SILC

Kazakhstan HBS HBS HBS HBS

UNMIKosovo LSMS->HBS LSMS->HBS LSMS->HBS LSMS->HBS

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Freq/Repr Coverage Consistency Access

Latvia HBS->SILC HBS->SILC HBS->SILC HBS->SILC

Lithuania HBS->SILC HBS->SILC HBS->SILC HBS->SILC

Moldova IHS IHS IHS IHS

Montenegro IHS->HBS IHS->HBS IHS->HBS IHS->HBS

Poland HBS->SILC HBS->SILC HBS->SILC HBS->SILC

Romania IHS IHS IHS IHS

Russian Federation HBS->IHS HBS->IHS HBS->IHS HBS->IHS

Serbia LSMS->HBS LSMS->HBS LSMS->HBS LSMS->HBS

Slovak Republic HBS->SILC HBS->SILC HBS->SILC HBS->SILC

Slovenia HBS->SILC HBS->SILC HBS->SILC HBS->SILC

Tajikistan LSMS LSMS LSMS LSMS

Turkey HBS HBS HBS HBS

Turkmenistan LSMS/HBS LSMS/HBS LSMS/HBS LSMS/HBS

Ukraine HBS HBS HBS HBS

Uzbekistan HBS HBS HBS HBS

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Pending Issues in Poverty Monitoring

• Sustainability: Generally no provision for the sustained financing of poverty monitoring from central budgetary resources

• Access: Access to primary data remains limited in selected countries, constraining evidence-based policymaking and analytical capacity building.

• Comparability: The shift from one data source to another (e.g., LSMS to HBS) may hinder the creation of a consistent series of poverty monitoring indicators

• Adequacy: HBS, as originally implemented, may not provide sufficient information on broader dimensions of poverty