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Composite Indices Based on Partial Least Squares

Author

Listed:
  • Jisu Yoon

    (Georg-August-University Göttingen)

  • Stephan Klasen

    (Georg-August-University Göttingen)

  • Axel Dreher

    (University of Heidelberg)

  • Tatyana Krivobokova

    (Georg-August-University Göttingen)

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.

Suggested Citation

  • Jisu Yoon & Stephan Klasen & Axel Dreher & Tatyana Krivobokova, 2015. "Composite Indices Based on Partial Least Squares," Courant Research Centre: Poverty, Equity and Growth - Discussion Papers 171, Courant Research Centre PEG.
    • Handle: RePEc:got:gotcrc:171
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    File URL: http://www2.vwl.wiso.uni-goettingen.de/courant-papers/CRC-PEG_DP_171.pdf
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    More about this item

    Keywords

    Principal Component Analysis; PCA; Partial Least Squares; PLS; non-metric variables; wealth index; globalization;
    All these keywords.

    JEL classification:

    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • C43 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Index Numbers and Aggregation
    • R20 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Household Analysis - - - General
    • F63 - International Economics - - Economic Impacts of Globalization - - - Economic Development

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