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| Living Standards Measurement Study× | Asset Index Construction× | |
|---|---|---|
| Field | Development Studies | Development Studies |
| Family | Process / pipeline | Process / pipeline |
| Year of origin≠ | 1980 | 2001 |
| Originator≠ | World Bank (Living Standards Measurement Study programme) | Deon Filmer & Lant Pritchett |
| Type≠ | Multi-topic integrated household survey | Composite socioeconomic-status proxy index |
| Seminal source≠ | 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 | Filmer, D., & Pritchett, L. H. (2001). Estimating Wealth Effects without Expenditure Data—or Tears: An Application to Educational Enrollments in States of India. Demography, 38(1), 115-132. DOI ↗ |
| Aliases≠ | LSMS, LSMS Survey, Living Standards Survey, Integrated Household Survey | Wealth Index, Asset Index, PCA Wealth Index, Socioeconomic Status Index |
| Related | 4 | 4 |
| Summary≠ | 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. | Asset index construction builds a proxy for household wealth or socioeconomic status from observable possessions — durable goods, housing quality, and access to utilities — when reliable income or consumption data are unavailable. The dominant approach, popularized by Deon Filmer and Lant Pritchett in 2001, applies principal component analysis (PCA) to a set of asset variables and uses the first principal component as a set of weights, producing a single wealth score for each household. The method underlies the wealth quintiles reported in Demographic and Health Surveys and many other household surveys across low- and middle-income countries. |
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