Download - 1 Kathleen Beegle Development Economics Research Group, The World Bank Maputo, August 14, 2009
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Kathleen BeegleDevelopment Economics Research Group, The World BankMaputo, August 14, 2009
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Improve the availability, quality and
relevance of agricultural data for policy and research in
Sub-Saharan Africa
LSMS-ISA Objective
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Accuracy Triangulation Measurement and methods Coverage, frames Periodicity and comparability
Relevance Lack of analytic capacity: lowers demand, affects
resources, lowers quality… Timeliness
Lag between data collection and availability Lag between new questions and answers
Motivation: Present Data Issues
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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
Motivation, cont.
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Within the World Bank:
WB focus on Sub-Saharan Africa; WDR-08
Core mandate of the Development Economics Research Group (DECRG)
Living Standards Measurement Study (LSMS) program: experience in implementing multi-topic surveys in collaboration with national statistics offices.
Motivation, cont.
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1. Household survey data production
2. Methodological validation/research
3. Capacity building
4. Dissemination
Main Components of LSMS-ISA
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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
(1) Panel Household Surveys
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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
(2) Methodological Validation, Research
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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
(3) Capacity Building
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Open access data policy
Complete documentation
Website, newsletter, …
Connecting with other data/analysis initiatives: ADePT-Ag (www.worldbank.org/adept), CLSP
Regional workshops
(4) Dissemination
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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…)
Governance Structure, Partners
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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
Possible Extensions
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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…
Progress to date
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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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THANK YOU
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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
Advantages of an LSMS Survey
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HH roster Education Health Migration Food expenditures Home production Non-food expenditures Agriculture and livestock Labor Non-farm household business/enterprise Non-labor income Credit Social capital Shocks and vulnerability Anthropometrics
•Land (size, tenure)•Production and sales•Inputs•Tech. & Investment•Extension Services•Market Access•Access to information
LSMS: Multi-topic Household Survey