Frequency and Comparability of Poverty Data in SSA

Andrew DabalenRose Mungai

Nobuo Yoshida

PREM Knowledge and Learning April 20, 2011

Multiple goals:◦ Monitor household welfare, demographic changes, ◦ Capture impact of short and long term shocks, etc.◦ International obligations – MDGs, IDA results, etc.

Ideal Data – characteristics:◦ Content is relevant to context◦ Timely◦ Regularity – dependable cycle or constant frequency◦ Comparable

Do we have such data?

Availability of poverty data

Recent WDI exercise◦ Many teams involved:

DECDG, DECRG, PRMPR, Regions

◦ Increased data points: 231 data points (Nov 2010) to 577 data points (April

2011)

◦ Provides answers to these questions

How are we doing?

Timeliness?

SSA EAP ECA LAC MNA SAR WORLD0.0

1.0

2.0

3.0

4.0

5.0

6.0

7.0

8.0

9.0

1.5

3.3

8.2

6.7

1.62.0

3.8

No. of poverty figures per country in the 2000s

Newness

SSA EAP ECA LAC MNA SAR WORLD2002.0

2003.0

2004.0

2005.0

2006.0

2007.0

2008.0

2009.0

Latest year for which poverty figure is available

Only 16 countries in Africa have

undertaken a survey (2007-

10)

Comparability problems

SSA EAP ECA LAC MNA SAR WORLD0%

10%

20%

30%

40%

50%

60%

51%

8%

0% 0% 0%

17%14%

Percentage of countries where the last two poverty figures are not comparable

Surveys in Africa

1-2-3 Survey Core Welfare In-dicators Survey

Core Welfare In-dicators Survey+

+

Income and Ex-penditure Survey

Integrated Survey (non-LSMS)

Living Standards Measurement

Surveys

Priority Surveys0

5

10

15

20

25

30

Types of Surveys in Africa 2000-2011

Comparability issues –contd.

Country Name 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 00 01 02 03 04 05 06 07

Ghana LSMS LSMS LSMS LSMS LSMS

Kenya WMS WMS WMS IES

South Africa IES IES IES

Zambia LSMS LSMS LSMS LSMS LSMSnon-LSMS

non-LSMS

Lack of comparability and timeliness in selected Sub-Saharan African countries

Availability of $2 a day poverty rates since 1980s

Country Name 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 00 01 02 03 04 05 06 07

Cote d'Ivoire 24 25 27 35 44 49 47

Ghana 79 78 78 63 54

Guinea 98 64 87

Guinea Bissau 58 76 78

Niger 91 92 86

◦ Development impact cannot be known.

Outcomes not credible

Results not believable

Why Does Comparability Matter?

Expansion or contraction of consumption list◦ Food and non-food

Seasonality

Recall periods

Population samples

Field work errors – increase or decline

Ref: Kinnon

Recognizing comparability problems

Short term goals:◦ Guideline Note – Survey choice and implementation

Support National statistics office to develop effective strategies

Rely on the guide as a tool for making good decisions

◦ Regional project Survey Based Harmonized Indicator Program (SHIP)

◦ Retail interventions Household survey clinics Poverty Assessments

◦ Partnerships – DECRG, PRMPR and DECDG

What are we doing about these problems?

Longer term goals:◦ Regularize and shorten the survey cycle

◦ Financing - Sustainability of surveys

◦ Timeliness - Learn from on-going innovations/experiments and explore scalability

◦ DREAM Every country or a large plurality to undertake a

survey for the period 2010-2014 to have results for the MDG in 2015.

What are we doing about these problems?