Improving the Use and Usability of Survey Data: the LSMS Experience Gero Carletto DEC Data Group The World Bank

LSMS-Integrated Surveys on Agriculture Working on 3 Fronts 1. Collect multi-topic panel household survey data with a focus on agriculture in 8 African countries 2. Improve methods based on rigorous experimentation and tool development 3. Make data accessible, enhance its usability and promote its use

Improving Data Use and Usability: A multi-pronged approach 1. Users’ group, wide consultation 2. Make microdata available – fully documented, user-friendly – Reduce time lag for dissemination – Support/hotline 3.Generate and disseminate geovariables 4.Promote and conduct policy research – Link to country policy dialogue/operations 5.Develop tools

2. Making Microdata available

LSMS-ISA: number of downloads

The Tanzania National Panel Survey (TZNPS) is the most commonly used LSMS-ISA dataset (176 results), followed by the Uganda (127) and Malawi (98) surveys. We find fewer results using the LSMS- ISA data from Ethiopia (64), Nigeria (58) and Niger (43). A separate search for research using the EGC-ISSER Ghana Panel Survey yielded 12 results. Use of Country Surveys Data *Note: Results could be coded as including research on multiple countries SOURCE: EPAR

Sources of LSMS-ISA Research The majority of LSMS-ISA analysis (291 of 417 results reviewed) originated from authors based solely in developed countries, but 80 results originated solely from authors in Sub-Saharan Africa, and 46 results are collaborations of authors located in both developed and developing countries. SOURCE: EPAR

3. Generate and disseminate geo-variables Dataset Integration: generate geographic variables to capture relevant site-specific or landscape characteristics elevation (m) annual rainfall (mm) travel time to city (hrs) mean7181,1273 range stdev

Average Annual Rainfall (mm)Average Annual Temperature (°C) Climatology

Elevation (m) Topography can have a significant influence on yields Elevation and derivatives (slope, relief roughness, topographic wetness index) affect water availability, soil fertility, land degradation & management requirements Landscape typology

Rainfall (mm) Rainfall time series 2010 Rainfall as % of Normal

Vegetation time series 2010 Max EVI Deviation from Mean sparsedense moderate NDVI sparsedense moderate

3. Conduct and promote policy research

5. Develop Tools ADePT Objective: Enhance the utilization of data, broaden the users of LSMS-type (and other) data Automatizes and standardizes the production of analytical reports Uses micro data from surveys to produce a rich set of tables and graphs Reduces time needed, and minimizes human error Modules available: poverty & inequality, social protection, food security, employment, gender, health, education, livestock and now crops Master class sessions March 18 in MC2-800: 9:00 Survey Solutions 11:00 ADePT Crops worldbank.org/adept

Outline of a descriptive report from LSMS- type data Crops: – Farm structure and land characteristics – Inputs, production, income and sales Livestock: – Production, ownership, income, inputs and outputs worldbank.org/adept 5. Develop Tools (cont’d) ADePT: The Agriculture modules

Domains: Size of holdings Tenancy arrangements Land distribution (Gini) Land use Quality: Irrigation, erosion etc. Use of inputs (fertilizers, mechanization) Analysis by: Urban and Rural Regions Land quintiles Welfare quintiles worldbank.org/adept 5. Develop Tools (cont’d) ADePT: Land characteristics

Some final thoughts … Increase use and usability starts before the survey is collected Put in place feedback mechanism: Collect, Use, Repeat Challenges remains … – increase usage in countries (e.g. SSA) – geo-references