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A Novel approach to construct a composite indicator by maximizing its sum of squared correlations with Sub-indicators

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Abstract

In the paper, a novel practical approach to construct a composite indicator (CI) is proposed. The key idea is to decide the weights of sub-indicators in constructing a composite indicator by maximizing the sum of squared correlations between the CI and sub-indicators. The CI obtained in this fashion has the maximum sum of squared correlations among all linear estimators. In addition, the simple, exact and explicit solutions of weights are proposed under the condition of non-negative irreducible matrix. Moreover, under this particular condition, the proposed method will become the principal component analysis. For illustration purpose, the proposed novel approach is utilized to calculate Sustainable Energy Index and Human Development Index which are two often-used cases to compare models in the literatures. The results show that the power of the proposed method outweigh the methods of Hatefi, et al. (2010) and Zhou, et al. (2007) in terms of the sum of absolute values of all sub-indicators’ correlations

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Authors and Affiliations

  1. School of Business, Renmin University of China, Beijing, 100872, China

    Wuqing Wu

  2. Department of Statistics, University of Connecticut, 215 Glenbrook RD U-4120, Storrs, Connecticut, 06269, USA

    Xiaojing Wang

Authors
  1. Wuqing Wu
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  2. Xiaojing Wang
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Correspondence to Xiaojing Wang.

Additional information

This research was supported by National Natural Science Foundation of China under Grant No. 71003100,the Fundamental Research Funds for the Central Universities, and the Research Funds of Renmin University ofChina under Grant No.11XNK027.

This paper was recommended for publication by Editor ZOU Guohua.

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Wu, W., Wang, X. A Novel approach to construct a composite indicator by maximizing its sum of squared correlations with Sub-indicators. J Syst Sci Complex 28, 925–937 (2015). https://doi.org/10.1007/s11424-014-3089-6

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  • DOI: https://doi.org/10.1007/s11424-014-3089-6

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