Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/108555
Authors: 
Yoon, Jisu
Klasen, Stephan
Dreher, Axel
Krivobokova, Tatyana
Year of Publication: 
2015
Series/Report no.: 
Courant Research Centre: Poverty, Equity and Growth - Discussion Papers 171
Abstract: 
In this paper, we compare Principal Component Analysis (PCA) and Partial Least Squares (PLS) methods to generate weights for composite indices. In this context we also consider various treatments of non-metric variables when constructing such composite indices. Using simulation studies we find that dummy coding for non-metric variables yields satisfactory performance compared to more sophisticated statistical procedures. In our applications we illustrate how PLS can generate weights that differ substantially from those obtained with PCA, increasing the composite indices' predictive performance for the outcome variable considered.
Subjects: 
Principal Component Analysis
PCA
Partial Least Squares
PLS
non-metric variables
wealth index
globalization
JEL: 
C15
C43
R20
F63
Document Type: 
Working Paper

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