Constructing socio-economic status indices: how to use principal components analysis
London School of Hygiene & Tropical Medicine
Abstract
Theoretically, measures of household wealth can be reflected by income, consumption or expenditure information. However, the collection of accurate income and consumption data requires extensive resources for household surveys. Given the increasingly routine application of principal components analysis (PCA) using asset data in creating socio-economic status (SES) indices, we review how PCA-based indices are constructed, how they can be used, and their validity and limitations. Specifically, issues related to choice of variables, data preparation and problems such as data clustering are addressed. Interpretation of results and methods of classifying households into SES groups are also discussed. PCA has been…
Citation impact
- FWCI
- 78.82
- Percentile
- 100%
- References
- 19
Authors
2Topics & keywords
- Principal component analysis
- Asset (computer security)
- Cluster analysis
- Consumption (sociology)
- Data collection
- Population
- Principal (computer security)
- Affect (linguistics)
- No poverty