1. 1 Kathleen Beegle Development Economics Research Group, The World Bank Maputo, August 14, 2009

2. 2 Improve the availability, quality and relevance of agricultural data for policy and research in Sub-Saharan Africa LSMS-ISA Objective

3. 3  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

4. 4  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.

5. 5 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.

6. 6 1. Household survey data production 2. Methodological validation/research 3. Capacity building 4. Dissemination Main Components of LSMS-ISA

7. 7  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

8. 8  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

9. 9  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

10. 10  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

11. 11  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

12. 12  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

13. 13  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 10 th 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

14. 14 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

15. 15 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?

16. 16 A 3 rd 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

17. 17 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.

18. 18 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

19. 19  Email: lsms@worldbank.org kbeegle@worldbank.org  Web: www.worldbank.org/lsms Contacts

20. 20 THANK YOU

21. 21  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

22. 22  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