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The use of discrete data in principal component analysis for socio-economic status evaluation – Russia Longitudinal Monitoring Survey of HSE

The use of discrete data in principal component analysis for socio-economic status evaluation

Citation

Kolenikov, Stanislav & Angeles, Gustavo (2005). The use of discrete data in principal component analysis for socio-economic status evaluation. UNC Chapel Hill.

Abstract

Outline
1. Motivation for socio-economic status (slide 3)
Who is interested in SES, and why?
2. Principal component analysis (slide 11)
Is this a reasonable procedure to generate weights for SES index?
3. Applications: Bangladesh DHS+, 2000 (slide 23) and Russia, RLMS 1994–2001 (slide 34)
Does it work for developing countries? Does it work for middle income countries?
Does it work with binary data only?
4. Monte Carlo study of the different flavors of PCA (slide 40)
Can we make any general conclusions about the methods?
5. Conclusions and references (slide 48)
How much room is there for improvement?

URL

http://www.unc.edu/~skolenik/talks/Gustavo-Stas-PCA-generic.pdf

Reference Type

Generic

Year Published

2005

Author(s)

Kolenikov, Stanislav
Angeles, Gustavo