方法对比

	Household Livelihood Survey	Living Standards Measurement Study
领域	Development Studies	Development Studies
方法族	Process / pipeline	Process / pipeline
起源年份	2000	1980
提出者	Frank Ellis; CIFOR Poverty Environment Network	World Bank (Living Standards Measurement Study programme)
类型	Multi-source income and assets household survey	Multi-topic integrated household survey
开创性文献	Ellis, F. (2000). Rural Livelihoods and Diversity in Developing Countries. Oxford: Oxford University Press. ISBN: 9780198296966	Grosh, M., & Glewwe, P. (Eds.). (2000). Designing Household Survey Questionnaires for Developing Countries: Lessons from 15 Years of the Living Standards Measurement Study. Washington, DC: World Bank. ISBN: 9780821345283
别名	Livelihood survey, Household income survey, Rural livelihoods survey, Income and assets survey	LSMS, LSMS Survey, Living Standards Survey, Integrated Household Survey
相关	4	4
摘要	A household livelihood survey is an instrument designed to capture the full portfolio of activities, income sources, assets, and expenditures through which a household secures its living. Rooted in the rural-livelihoods literature associated with Frank Ellis and in global comparative income studies such as the CIFOR Poverty Environment Network, it measures welfare and resilience by mapping the diversity of a household's economic activities — farming, wage labour, self-employment, environmental harvesting, transfers, and remittances — rather than reducing the household to a single income or consumption figure.	The Living Standards Measurement Study (LSMS) is a multi-topic integrated household survey programme launched by the World Bank in 1980 to improve the quality of household data for measuring and analysing welfare in developing countries. Built around a modular questionnaire that links a detailed household interview to community and price questionnaires, the LSMS measures living standards through consumption expenditure rather than income, and connects welfare outcomes to their determinants — employment, education, health, agriculture, and access to services — within a single, internally consistent dataset.