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On construction of robust composite indices by linear aggregation

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  • Mishra, SK

Abstract

In 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 Info

Paper provided by University Library of Munich, Germany in its series MPRA Paper with number 9232.

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Date of creation: 19 Jun 2008
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Handle: RePEc:pra:mprapa:9232

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Related research

Keywords: Composite index; linear aggregation; principal components; robust correlation; Spearman; Signum; Bradley; Shevlyakov; Campbell; Hampel; outliers; mutilation of data;

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  1. Mishra, SK, 1984. "Taxonomical analysis of regional development by outranking relations on multiple principal components," MPRA Paper 8989, University Library of Munich, Germany.
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Cited by:
  1. 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.
  2. 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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