Kathleen Beegle
Development Economics Research Group, The World Bank
Maputo, August 14, 2009
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LSMS-ISA Objective
Improve the availability, quality and
relevance of agricultural data
for policy and research in
Sub-Saharan Africa
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Motivation: Present Data Issues
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Accuracy
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Relevance
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Triangulation
Measurement and methods
Coverage, frames
Periodicity and comparability
Lack of analytic capacity: lowers demand, affects resources,
lowers quality…
Timeliness
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Lag between data collection and availability
Lag between new questions and answers
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Motivation, cont.
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Thematic Isolation
 Failure to address high levels of diversification of farm
households
 Linkages to non-farm activities
 Poverty, vulnerability, coping strategies
Institutional Isolation
 Falling between the cracks: MinAgr links with NSO
 Limits synergies with other data (geographic, social,
economic, infrastructure)
 Limits synergies w/ other data collection exercises
 Lack of National Statistics System- fully integrated
Below optimal coordination among donors
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Motivation, cont.
Within the World Bank:
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WB focus on Sub-Saharan Africa; WDR-08
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Core mandate of the Development Economics
Research Group (DECRG)
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Living Standards Measurement Study (LSMS) program:
experience in implementing multi-topic surveys in
collaboration with national statistics offices.
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Main Components of LSMS-ISA
1.
Household survey data production
2.
Methodological validation/research
3.
Capacity building
4.
Dissemination
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(1) Panel Household Surveys
 Panel
 Every 3 years…or more frequently (e.g. Uganda, Tanzania)
 Project in 6 Sub-Saharan African countries (plus ‘pilot’
in Tanzania)
 Sample
 3-5,000 households:2 or more rounds, track households and individuals
as feasible
 Population-based frame: national and sub-national, urban/rural
 Integrated approach
 Multi-topic questionnaire: Agr+poverty+soc+anthro…
 Build on existing/planned surveys (NSDS)
 Link to other data sources
 Inter-institutional Collaboration
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(2) Methodological Validation, Research
 LSMS-IV: continue research on improving
methods
 Computer Assisted Personal Interview (CAPI)
 Planned validation/experimentation
 Improve measures of crop yields
 Plot size
 Quantities (Measurement tools such as Diaries/crop
cards, Crop cutting)
 Income sources (Ag., non-farm self-employment)
 Satellite imaging: Ground-truthing of satellite imaging
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(3) Capacity Building
 Learning by doing:
 multiple surveys, medium term (5-6 yrs.) program ( example of
MECOVI program)
 linking data producers and data users
 Resident Advisor + Technical assistance
 Guidelines/sourcebooks, better modules
 Anthropometrics sourcebook
 Livestock module development
 Fisheries module development
 Income measurement sourcebook
 Climate change & adaptation sourcebook
 Weighting issues in panel surveys
 Panel Survey implementation sourcebook
 Regional training workshops
 Within project and linking to other regional initiatives
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(4) Dissemination
 Open access data policy
 Complete documentation
 Website, newsletter, …
 Connecting with other data/analysis initiatives:
ADePT-Ag (www.worldbank.org/adept), CLSP
 Regional workshops
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Governance Structure, Partners
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Managed by LSMS team
Steering Committee (WB, IFAD, FAO, …)
Technical Advisory Board (overall)
Technical Working Groups (within countries)
Government counterparts (NSO, MoA, …)
WB Operations (impact evaluation)
Research/academic institutions (special studies)
 WB Research group
 Other (Yale U., Duke U., IFPRI, Cornell…)
 Donors/co-financing
 WFP, IFAD, UNFPA, UNICEF, Dutch, Danish, Norway…
 Collaborations (WFP, FAO, IFAD, WFC…)
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Possible Extensions
 Work in more countries in SSA
 Full-fledged LSMS-ISA
 High-risk/post-conflict countries pilot studies
 Expand scope
 Project evaluation, e.g. Nigeria CADP
 Specific crops/production systems/livestock
 Other special studies
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Progress to date
Project launch: December 9, 2008
Technical Advisory Board meeting: Feb 6, 2009
Steering Committee, April 7, 2009
‘Pilot’: support to the Tanzania National Panel
Survey (in 10th month of data collection)
 Uganda National Panel Survey: training for field
work beginning now
 Niger, Ethiopia, Malawi and Nigeria: Various
stages of development with respect to Concept
Note, questionnaires, samples…
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The Strategic Vision for the
Integrated Survey Framework
• Integrated Agriculture Survey Framework:
• focus on integration as coordination of
efforts to collect/produce statistics …by
connecting as many samples as possible… in
agriculture.
• “The integration of achieved by connecting
as many of the samples as possible”
• Discussion points focus on a broader view of
integration
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Another view of integration
• Coordination within the system of surveys/statistics in
the national statistical system.
• Timing with respect to major survey efforts
(Household Budget Surveys, Labour Force Surveys,
Demographic Health Surveys, price data)
• Feasibility of annual national estimates of ag stats
from surveys given financial and human resource
limitations.
• Example: HBS, DHS, LFS rarely done annually.
• Sub-national estimates greater challenge
• Implication: reliance on non-survey data?
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A 3rd view of integration
• Consistency in questionnaires across surveys:
• Not just with respect to agricultural surveys
• Especially important if agricultural surveys
cannot be done annually
• Examples: definition of agricultural
household, income questions (levels or
sources), labor questions
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Achieving integration though
connecting samples…
• Not clear how many of the in the framework
samples would be connected. Examples:
• Administrative data connected to annual
household surveys
• at the district level? PSU? HH?
• Agri businesses data and annual HH surveys?
• Windshield surveys and annual HH surveys?
• Integration is more that connecting as many
samples as possible.
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Other aspects of sample
integration
• The Strategy focuses on agricultural
households.
• Other national surveys will have large
coverage of this population
• Potential to conduct, for example, HBS
and Ag Survey in same household
• Have to coordinate field work, avoid
respondent burden
• What about coverage of non-agricultural
households for understanding agriculture?
• Labor market options, relative position
with respect to economic activities
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Contacts
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Email:
lsms@worldbank.org
kbeegle@worldbank.org
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Web: www.worldbank.org/lsms
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THANK YOU
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Advantages of an LSMS Survey
 Provide policy-relevant data
 Consumption-based welfare measure
 Multi-Topic questionnaire
 Multiple instruments
 Customization to country needs
 Quality control
 Explicit link between data users and producers
 Open data access
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LSMS: Multi-topic Household Survey
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HH roster
Education
Health
•Land (size, tenure)
Migration
•Production and sales
Food expenditures
•Inputs
Home production
•Tech. & Investment
Non-food expenditures
•Extension Services
•Market Access
Agriculture and livestock
•Access to information
Labor
Non-farm household business/enterprise
Non-labor income
Credit
Social capital
Shocks and vulnerability
Anthropometrics
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