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?