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Construction of composite indices in presence of outliers

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Abstract

Effects of outliers on mean, standard deviation and Pearson’s correlation coefficient are well known. The Principal Components analysis uses Pearson’s product moment correlation coefficients to construct composite indices from indicator variables and hence may be very sensitive to effects of outliers in data. Median, mean deviation and Bradley’s coefficient of absolute correlation are less susceptible to effects of outliers. This paper proposes a method to obtain composite indices by maximization of the sum of absolute Bradley’s correlation coefficients between the indicator variable and the derived composite index.

Suggested Citation

  • Mishra, SK, 2008. "Construction of composite indices in presence of outliers," MPRA Paper 8874, University Library of Munich, Germany.
    • Handle: RePEc:pra:mprapa:8874
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    File URL: https://mpra.ub.uni-muenchen.de/8923/1/MPRA_paper_8923.pdf
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    References listed on IDEAS

    as
    1. Mishra, SK, 2007. "Performance of Differential Evolution Method in Least Squares Fitting of Some Typical Nonlinear Curves," MPRA Paper 4634, University Library of Munich, Germany.
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    More about this item

    Keywords

    Composite index; Principal Components analysis; absolute; Bradley’s correlation coefficient; outliers; median; mean deviation; Differential Evolution; global optimization;
    All these keywords.

    JEL classification:

    • C43 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Index Numbers and Aggregation
    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • C01 - Mathematical and Quantitative Methods - - General - - - Econometrics

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