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Sensitivity Analysis of Composite Indicators through Mixed Model Anova

Author

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  • Cristina Davino, Rosaria Romano

    (University of Macerata)

Abstract

The paper proposes a new approach for analysing the stability of Composite Indicators. Starting from the consideration that different subjective choices occur in their construction, the paper emphasizes the importance of investigating the possible alternatives in order to have a clear and objective picture of the phenomenon under investigation. Methods dealing with Composite Indicator stability are known in literature as Sensitivity Analysis. In such a framework, the paper presents a new approach based on a combination of explorative and confirmative analysis aiming to investigate the impact of the different subjective choices on the Composite Indicator variability and the related individual differences among the statistical units as well.

Suggested Citation

  • Cristina Davino, Rosaria Romano, 2011. "Sensitivity Analysis of Composite Indicators through Mixed Model Anova," Working Papers 32-2011, Macerata University, Department of Studies on Economic Development (DiSSE), revised Mar 2011.
  • Handle: RePEc:mcr:wpaper:wpaper00032
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    File URL: http://www.unimc.it/sviluppoeconomico/wpaper/wpaper00032/filePaper
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    References listed on IDEAS

    as
    1. Amjad D. Al-Nasser, 2005. "Customer Satisfaction Measurement Models: Generalised Maximum Entropy Approach," Econometrics 0503013, EconWPA.
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    More about this item

    Keywords

    sensitivity analysis; composite indicators; analysis of variance; principal component analysis;

    JEL classification:

    • C38 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Classification Methdos; Cluster Analysis; Principal Components; Factor Analysis
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques

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