방법 비교

	Poverty Mapping (Small-Area Estimation)	Living Standards Measurement Study
분야	Development Studies	Development Studies
계열	Process / pipeline	Process / pipeline
기원 연도	2003	1980
창시자	Chris Elbers, Jean O. Lanjouw & Peter Lanjouw	World Bank (Living Standards Measurement Study programme)
유형	Census-survey small-area poverty estimation method	Multi-topic integrated household survey
원전	Elbers, C., Lanjouw, J. O., & Lanjouw, P. (2003). Micro-Level Estimation of Poverty and Inequality. Econometrica, 71(1), 355-364.	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
별칭	ELL Method, Poverty Mapping, Census-Survey Poverty Estimation, Small-Area Poverty Estimation	LSMS, LSMS Survey, Living Standards Survey, Integrated Household Survey
관련	4	4
요약	ELL poverty mapping, named after Chris Elbers, Jean Lanjouw, and Peter Lanjouw, is a small-area estimation method that produces poverty and inequality estimates for geographic units far smaller than a household survey can support on its own. It combines two data sources: a detailed household survey that measures consumption but covers too few households per locality, and a population census that covers everyone but does not measure consumption. The method estimates a model of consumption on variables common to both, imputes consumption into the census, and simulates to generate poverty estimates — with statistically valid standard errors — for districts, communes, or even villages, which are then drawn as poverty maps.	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.