Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/109027
Authors: 
Yoon, Jisu
Krivobokova, Tatyana
Year of Publication: 
2015
Series/Report no.: 
Courant Research Centre: Poverty, Equity and Growth - Discussion Papers 172
Abstract: 
This paper reviews various treatments of non-metric variables in Partial Least Squares (PLS) and Principal Component Analysis (PCA) algorithms. The performance of different treatments is compared in the extensive simulation study under several typical data generating processes and recommendations are made. An application of PLS and PCA algorithms with non-metric variables to the generation of a wealth index is considered.
Subjects: 
Principal Component Analysis
PCA
Partial Least Squares
PLS
non-metric variables
simulation
wealth index
JEL: 
C15
C43
R20
Document Type: 
Working Paper

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