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2015 | 16 | 3 | 409-428

Article title

Exploiting Ordinal Data for Subjective Well-Being Evaluation

Content

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Abstracts

EN
The evaluation of subjective well-being, and of similar issues related to quality of life, is usually addressed through composite indicators or counting procedures. This leads to inconsistencies and inefficiency in the treatment of ordinal data that, in turn, affect the quality of information provided to scholars and to policy-makers. In this paper we take a different path and prove that the evaluation of multidimensional ordinal well-being can be addressed in an effective and consistent way, using the theory of partially ordered sets. We first show that the proper evaluation space of well-being is the partially ordered set of achievement profiles and that its structure depends upon the importance assigned to well-being attributes. We then describe how evaluation can be performed extracting information out of the evaluation space, respecting the ordinal nature of data and producing synthetic indicators without attribute aggregation. An application to subjective well-being in Italy illustrates the procedure.

Year

Volume

16

Issue

3

Pages

409-428

Physical description

Contributors

author
  • Department of Statistics and Quantitative Methods, University of Milan – Bicocca, Italy
  • Department of Statistics, Informatics, Applications "G. Parenti" (DiSIA), University of Florence, Italy
  • Department of Statistics and Quantitative Methods, University of Milan – Bicocca, Italy

References

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  • CERIOLI, A., ZANI, S., (1990). A Fuzzy Approach To The Measurement Of Poverty. In: Dagum, C., Zenga, M. Income and Wealth distribution, Inequality and Poverty. Berlin Heidelberg: Springer-Verlag. pp. 272–284.
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  • FATTORE, M., BRUEGGEMANN, R., OWSIŃSKI, J., (2011). Using poset theory to compare fuzzy multidimensional material deprivation across regions. In: Ingrassia S., Rocci R. and Vichi, M. New Perspectives in Statistical Modeling and Data Analysis. Berlin: Springer-Verlag.
  • FATTORE, M., MAGGINO, F., COLOMBO, E., (2012). From composite indicators to partial orders: evaluating socio-economic phenomena through ordinal data. In: Maggino F., Nuvolati G. Quality of life in Italy: researches and reflections. Berlin: Social Indicators Research Series.
  • FATTORE, M., ARCAGNI, A., (2014). PARSEC: an R package for poset-based evaluation of multidimensional poverty. In: Bruggemann R., Carlsen L. and Wittmann J. Multi-Indicator Systems and Modelling in Partial Order. Berlin: Springer.
  • FATTORE, M., ARCAGNI, A., BARBERIS, S., (2014). Visualizing Partially Ordered Sets for Socioeconomic analysis. Revista Colombiana de Estadistica, 34(2), pp. 437–450.
  • FATTORE, M., MAGGINO, F., (2015). A new method for measuring and analyzing suffering – Comparing suffering patterns in Italian society. In: Anderson R. E. World Suffering and the Quality of Life. New York: Springer.
  • MADDEN, D., (2010). Ordinal and cardinal measures of health inequality: an empirical comparison. Health Economics, 19, pp. 243–250.
  • NEGGERS, J., KIM, S. H., (1998). Basic posets. Singapore: World Scientific.
  • QIZILBASH, M., (2006). Philosophical Accounts of Vagueness, Fuzzy Poverty Measures and Multidimensionality. In Lemmi A. and Betti G. Fuzzy Set Approach to Multidimensional Poverty Measurement. New York: Springer.
  • SEN, A., (1992). Inequality reexamined, Harvard University Press.

Document Type

Publication order reference

Identifiers

YADDA identifier

bwmeta1.element.desklight-abd3ff34-2d53-4ef1-9a48-97586986f8fb
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