On construction of robust composite indices by linear aggregation
AbstractIn this paper we construct thirteen different types of composite indices by linear combination of indicator variables (with and without outliers/data corruption). Weights of different indicator variables are obtained by maximization of the sum of squared (and, alternatively, absolute) correlation coefficients of the composite indices with the constituent indicator variables. Seven different types of correlation are used: Karl Pearson, Spearman, Signum, Bradley, Shevlyakov, Campbell and modified Campbell. Composite indices have also been constructed by maximization of the minimal correlation. We find that performance of indices based on robust measures of correlation such as modified Campbell and Spearman, as well as that of the maxi-min based method, is excellent. Using these methods we obtain composite indices that are autochthonously sensitive and allochthonously robust. This paper also justifies a use of simple mean-based composite indices, often used in construction of human development index.
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Bibliographic InfoPaper provided by University Library of Munich, Germany in its series MPRA Paper with number 9232.
Date of creation: 19 Jun 2008
Date of revision:
Composite index; linear aggregation; principal components; robust correlation; Spearman; Signum; Bradley; Shevlyakov; Campbell; Hampel; outliers; mutilation of data;
Find related papers by JEL classification:
- C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
- C43 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Index Numbers and Aggregation
- C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
- C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
This paper has been announced in the following NEP Reports:
- NEP-ALL-2008-06-21 (All new papers)
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Mishra, SK, 1984. "Taxonomical analysis of regional development by outranking relations on multiple principal components," MPRA Paper 8989, University Library of Munich, Germany.
- Nayak, Purusottam & Mishra, SK, 2012. "Efficiency of Pena’s P2 Distance in Construction of Human Development Indices," MPRA Paper 39022, University Library of Munich, Germany.
- Mishra, SK, 2012. "A note on the indeterminacy and arbitrariness of pena’s method of construction of synthetic indicators," MPRA Paper 37534, University Library of Munich, Germany.
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