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A Longitudinal Cross-Country Dataset on Agricultural Productivity and Welfare in Sub-Saharan Africa

Author

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  • Thomas Patrick Bentze
  • Philip Randolph Wollburg

Abstract

Since 2008, the World Bank's Living Standards Measurement Study–Integrated Surveys on Agriculture (LSMS-ISA) program has supported the collection of nationally representative, longitudinal, multi-topic household survey data to inform researchers and policy makers of living standards in Sub-Saharan Africa. The surveys maintain a distinct focus on the agricultural sector, collecting detailed plot-level data and information about agricultural activities, while measuring socioeconomic conditions of thousands of smallholder farmers and households across multiple countries. This paper presents a harmonized panel dataset (HP) from LSMS-ISA surveys from 2008 to 2021 in seven Sub-Saharan African countries: Ethiopia, Malawi, Mali, Niger, Nigeria, Tanzania, and Uganda, from 2008 to 2021. It includes more than 200,000 agricultural plot observations, more than 400,000 individuals, and about 59,000 households. The HP allows for in-depth analysis of farm, household, and individual dynamics over time and across countries. It is ideal for researchers interested in studying the dynamics between agriculture, economic development, and welfare outcomes in Sub-Saharan Africa.

Suggested Citation

  • Thomas Patrick Bentze & Philip Randolph Wollburg, 2024. "A Longitudinal Cross-Country Dataset on Agricultural Productivity and Welfare in Sub-Saharan Africa," Policy Research Working Paper Series 10976, The World Bank.
    • Handle: RePEc:wbk:wbrwps:10976
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    References listed on IDEAS

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    1. Stefan Dercon & Douglas Gollin, 2014. "Agriculture in African Development: Theories and Strategies," Annual Review of Resource Economics, Annual Reviews, vol. 6(1), pages 471-492, October.
    2. Gollin, Douglas, 2010. "Agricultural Productivity and Economic Growth," Handbook of Agricultural Economics, in: Robert Evenson & Prabhu Pingali (ed.), Handbook of Agricultural Economics, edition 1, volume 4, chapter 73, pages 3825-3866, Elsevier.
    3. Douglas Gollin & Christopher Udry, 2021. "Heterogeneity, Measurement Error, and Misallocation: Evidence from African Agriculture," Journal of Political Economy, University of Chicago Press, vol. 129(1), pages 1-80.
    4. Little, Roderick J A, 1988. "Missing-Data Adjustments in Large Surveys," Journal of Business & Economic Statistics, American Statistical Association, vol. 6(3), pages 287-296, July.
    5. Calogero Carletto, 2021. "Better data, higher impact: improving agricultural data systems for societal change [Correlated non-classical measurement errors, ‘second best’ policy inference, and the inverse size-productivity relationship in agriculture]," European Review of Agricultural Economics, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 48(4), pages 719-740.
    6. Diego Restuccia & Richard Rogerson, 2013. "Misallocation and productivity," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 16(1), pages 1-10, January.
    7. Stefan Dercon & Douglas Gollin, 2014. "Agriculture in African Development: A Review of Theories and Strategies," CSAE Working Paper Series 2014-22, Centre for the Study of African Economies, University of Oxford.
    8. Tasso Adamopoulos & Diego Restuccia, 2020. "Land Reform and Productivity: A Quantitative Analysis with Micro Data," American Economic Journal: Macroeconomics, American Economic Association, vol. 12(3), pages 1-39, July.
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    1. Amankwah, Akuffo & Ambel, Alemayehu & Gourlay, Sydney & Kilic, Talip & Markhof, Yannick & Wollburg, Philip, 2025. "Smallholder farming, fertilizer use, and the polycrisis period: Cross-country evidence from longitudinal surveys in Sub-Saharan Africa," Food Policy, Elsevier, vol. 133(C).

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