Supporting Poverty Measurement In Europe and

Central Asia

Cesar Cancho

Poverty GP ECA

Workshop “Measuring Poverty - Concepts, Challenges and Recommendations”

Belgrade, Serbia

April 17th, 2015

World Bank engagement

• Goals• 3% extreme poverty in 2030

• Boosting shared prosperity (bottom 40%)

• Key component engagement with countries• Living conditions measurement (Poverty GP)

• Technical Assistance

Overview of Areas of Support

• Survey development• New household surveys

• New technologies

• Survey quality improvement• Sampling issues

• Data analysis for poverty measurement• Survey to survey imputations

Survey Development (1)

Sample issues• Georgia Integrated Household Survey

• Household Budget Survey • Labor Force Survey

• Support on design of sample• Common-core• Model consumption for extended LFS sample

• Advantages• Direct mapping labor outcomes – income• Continuity living conditions / labor statistics

Survey Development (2)

New technologieso PAPI : Paper Assisted Personal Interviewing

• Paper questionnaires and entered, either with a data entry application (CSPro) or scanning and at HQ/regional office.

o CAPI : Computer Assisted Personal Interviewing• Tablets or PDAs using interactive software• Regularly sent to HQ using mobile phone network.

o CAFE : Computer Assisted Personal Interviewing• Hybrid• Data collected on paper • Entered in the cluster on laptop and sent electronically to HQ.

Survey Development (3)

PAPI CAFE CAPI

• Not vulnerable to limited electric supply

• Provides verification – errors can be fixed in the field.

• Paper questionnaire still exist in case of mishap.

• Intermediate step

• Provides final complete data as soon as field work ends

• Slow – data entry and verification can take months

• Errors are not discovered until long after – to late for any corrections.

• Still takes processing time to do double entry.

• New technology• Needs good programmer

to be effective• Vulnerable to total loss• Capital investment• No power, no survey• Comparability issues

Survey Quality Improvement (1)

Sampling issues (a) Poverty Rates (b) Consumption distributions

2006 2009 2010 20110

5

10

15

20

25

30

35

40

19

27

31

38

0.0

00

0.0

01

0.0

02

0.0

03

0 200 400 600 800 1000

HH Annual Consumption, 2006 Denars (Thousands)

2005 2006 2008 2009 2010 2011

Notes: Vertical lines represent median value multiplied by 0.7. Horizontal axis is truncated at1 million denars

(a) Internal Margin (b) External Margin Items collected Non-response rates

Survey Quality Improvement (2)

2005 2006 2007 2008 2009 2010 2011 201230

31

32

33

34

35

36

37

38

39

40

10

11

12

13

14

15

16

17

18

19

20

38.2

3938.7

3938.7

37.8

36.9

38.4

17 17.116.8

16.516.2

14.8

13.413.9

Food Non-Food

2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 20120%

5%

10%

15%

20%

25%

30%

35%

40%

45%

19%16% 16% 16% 16% 17% 18%

20%

33%

41% 42%

Survey Quality Improvement (3)

• Recommendations• […]

• Strengthen supervision to enumerators by monitoring key variables collected by enumerator (number of items, household size, complex questions), as close as possible to the field work.

• […]

• Change the survey weight adjustment procedure for the strata with loss of enumeration districts to a two-step procedure: First adjusting for the loss of households in the enumeration district, and then adjusting for the loss of enumeration district in the strata.

Data analysis for poverty measurement (1)

Survey to survey imputations• HBS-SILC imputations

• Other analytical tools• Labor Income Poverty• Poverty Maps

Data analysis for poverty measurement (4)

Thanks!Хвала!

This presentation was prepared with contributions from Minh Nguyen, Osman Kaan Inan, Joao Pedro Azevedo and Kristen Himelein (Poverty GP)

Хвала!