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Synthesis of Statistical Indicators to Evaluate Quality of Life in the Italian Provinces

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  • Massimo Alfonso Russo

    ()

  • Roberto Gismondi

    ()

Abstract

This work remarks the need to carefully evaluate the real importance of each variable used in a multivariate analysis context, with particular regard to cases when an overall performance ranking is the main final purpose. In particular, both a preliminary transformation of variables – aimed at reducing asymmetry and variability of their variation ranges – and the evaluation of their intrinsic explicative power – through redundancy analysis and weighting methods – are proposed. Theoretical and empirical considerations are developed in the frame of quality of life evaluation, carried out at the Italian provinces level on the basis of a yearly survey managed by the Italian economic newspaper "Il Sole24ore". A particular emphasis is given to some normalisation criteria and the case when original variables are grouped "a priori" into logical blocks. A final comparison between the actual ranking method and a series of alternatives is proposed as well.

Suggested Citation

  • Massimo Alfonso Russo & Roberto Gismondi, 2008. "Synthesis of Statistical Indicators to Evaluate Quality of Life in the Italian Provinces," Quaderni DSEMS 02-2008, Dipartimento di Scienze Economiche, Matematiche e Statistiche, Universita' di Foggia.
  • Handle: RePEc:ufg:qdsems:02-2008
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    File URL: http://www.economia.unifg.it/sites/sd01/files/allegatiparagrafo/29-11-2016/q022008.pdf
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    References listed on IDEAS

    as
    1. Massimo Alfonso Russo & Roberto Gismondi, 2007. "Methodological Proposals for a Qualitative Evaluation of Italian Durum Wheat Varieties," Quaderni DSEMS 23-2007, Dipartimento di Scienze Economiche, Matematiche e Statistiche, Universita' di Foggia.
    2. Massimo A. Russo & Roberto Gismondi, 2004. "Definizione e calcolo di un indice territoriale di turisticita' un approccio statistico multivariato," Quaderni DSEMS 11-2004, Dipartimento di Scienze Economiche, Matematiche e Statistiche, Universita' di Foggia.
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    Keywords

    multivariate analysis; principal components analysis; ranking; redundant variable; weighing system.;

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