Social Indicators Research

, Volume 137, Issue 1, pp 83–91 | Cite as

Some Considerations on Well-Being Evaluation Procedures, Taking the Cue from “Exploring Multidimensional Well-Being in Switzerland: Comparing Three Synthesizing Approaches”

  • Marco Fattore
  • Filomena Maggino


In this short paper, we outline some considerations on three different procedures for the statistical evaluation of multidimensional well-being, taking the cue from a recent paper of Iglesias et al. There, the authors apply and compare Confirmatory Factor Analysis, the Alkire–Foster counting approach and the Partial Order Approach on real data, pointing out limitations and potentialities of each procedure. To deepen, and partially correct, some of their (albeit interesting) remarks, here we review the fundamental features of those approaches, so as to shed light on their structural differences and to show that they move from, and may lead to, alternative views on well-being.


Well-being Confirmatory factor analysis Alkire–Foster counting approach Partial order approach 


  1. Alkire, S., & Foster, J. (2011). Counting and multidimensional poverty measurement. Journal of Public Economics, 95(7–8), 476–487.CrossRefGoogle Scholar
  2. Alkire, S., & Foster, J. (2011). Understandings and misunderstandings of multidimensional poverty measurement. Journal of Economic Inequality, 9(2), 289–314.CrossRefGoogle Scholar
  3. Bollen, K. A. (1989). Structural equations with latent variables. New York: Wiley.CrossRefGoogle Scholar
  4. Bubley, R., & Dyer, M. (1999). Faster random generation of linear extensions. Discrete Mathematics, 201, 81–88.CrossRefGoogle Scholar
  5. Bruggemann, R., & Patil, G. P. (2011). Ranking and prioritization for multi-indicator systems. New York: Springer-Verlag.CrossRefGoogle Scholar
  6. Bruggemann, R., Restrepo, G., Voigt, K., & Annoni, P. (2013). Weighting intervals and ranking. Exemplified by leaching potential of pesticides. MATCH Communications in Mathematical and in Computer Chemistry, 69, 413–432.Google Scholar
  7. Bruggemann, R., & Carlsen, L. (2017). Incomparable: What now, IV. Incomparabilities: A Modelling challenge. In M. Fattore & R. Bruggemann (Eds.), Partial order concepts in applied sciences (pp. 35–47). Cham, Switzerland: Springer.CrossRefGoogle Scholar
  8. Fattore, M. (2008). Hasse diagrams, poset theory and fuzzy poverty measures, Rivista Internazionale di Scienze Sociali 1/2008.Google Scholar
  9. Fattore, M., Maggino, F., & Greselin, F. (2011). Socio-economic evaluation with ordinal variables: Integrsting counting and poset approaches. Statistica & applicazioni, Special Issue 2011, 31–42.Google Scholar
  10. Fattore, M., & Maggino, F. (2014). Partial orders in socio-economics: A practical challenge for poset theorists or a cultural challenge for social scientists? In R. Bruggemann, L. Carlsen, & J. Wittmann (Eds.), Multi-indicator systems and modelling in partial order. Berlin: Springer.Google Scholar
  11. Fattore, M. (2016). Partially ordered sets and the measurement of multidimensional ordinal deprivation. Social Indicators Research, 128(2), 835–858.CrossRefGoogle Scholar
  12. Fattore, M., & Arcagni, A. (2016). A reduced posetic approach to the measurement of multidimensional ordinal deprivation. Social Indicators Research. doi: 10.1007/s11205-016-1501-4.
  13. Iglesias, K., Suter, C., Beycan, T., & Vani, B. P. (2016). Exploring multidimensional well-being in Switzerland. Social Indicators Research. doi: 10.1007/s11205-016-1452-9.
  14. Madden, D. (2010). Ordinal and cardinal measures of health inequality: An empirical comparison. Health Economics, 19, 243–250.CrossRefGoogle Scholar
  15. Schoenemann, P. H., & Steiger, J. H. (1978). On the validity of indeterminate factor scores. Bulletin of the Psychonomic Society, 12(4), 287–290.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media Dordrecht 2017

Authors and Affiliations

  1. 1.University of Milano-BicoccaMilanItaly
  2. 2.University of Rome - SapienzaRomeItaly

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