Synthetic Indicators of the Quality of Life in Europe

  1. Somarriba Arechavala, Noelia 1
  2. Pena Trapero, Bernardo 2
  1. 1 Universidad de Valladolid
    info

    Universidad de Valladolid

    Valladolid, España

    ROR https://ror.org/01fvbaw18

  2. 2 Universidad de Alcalá
    info

    Universidad de Alcalá

    Alcalá de Henares, España

    ROR https://ror.org/04pmn0e78

Libro:
Encyclopedia of Quality of Life and Well-Being Research

ISBN: 9783319699097 9783319699097

Año de publicación: 2021

Páginas: 1-8

Tipo: Capítulo de Libro

DOI: 10.1007/978-3-319-69909-7_3729-2 GOOGLE SCHOLAR lock_openAcceso abierto editor

Resumen

The evaluation of the quality of life involves evaluating multiple aspects of society and implies the simultaneous use of many social indicators. In this multidimensional evaluation, the indicators’ weighted sum is generally used as an integrated measure for the purpose of offering a global synthesis of welfare. In this respect, synthetic indicator-construction methods are particularly interesting in this field of research, especially within the European Union context.

Referencias bibliográficas

  • Betti, G. (2016). Fuzzy measures of quality of life: A multidimensional and comparative approach. International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems, 24(November 2015), 25–37. https://doi.org/10.1142/S021848851640002X.
  • Betti, G. (2017a). Fuzzy measures of quality of life in Germany: A multidimensional and comparative approach. Quality & Quantity, 51(1), 23–34. https://doi.org/10.1007/s11135-015-0291-0.
  • Betti, G. (2017b). What impact has the economic crisis had on quality of life in Europe? A multidimensional and fuzzy approach. Quality and Quantity, 51(1), 351–364. https://doi.org/10.1007/s11135-015-0308-8.
  • Betti, G., Soldi, R., & Talev, I. (2016). Fuzzy multidimensional indicators of quality of life: The empirical case of macedonia. Social Indicators Research, 127(1), 39–53. https://doi.org/10.1007/s11205-015-0965-y.
  • Chen, P. Y., & Yao, G. (2015). Measuring quality of life with fuzzy numbers: In the perspectives of reliability, validity, measurement invariance, and feasibility. Quality of Life Research, 24(4), 781–785. https://doi.org/10.1007/s11136-014-0816-3.
  • Cuenca, E., Rodríguez, J. A., & Navarro, M. (2010). The features of development in the Pacific countries of the African, Caribbean and Pacific Group. Social Indicators Research, 99(3), 469–485. https://doi.org/10.1007/s11205-010-9594-7.
  • Despotis, D. K. (2005a). A reassessment of the human development index via data envelopment analysis. Journal of the Operational Research Society, 56, 969–980.
  • Despotis, D. K. (2005b). Measuring human development via data envelopment analysis: The case of Asia and the Pacific. The International Journal of Management Science, 33, 385–390.
  • Farrell, M. J. (1957). The measurement of productive efficiency. Journal of the Royal Statistical Society, Series A, 3, 253–290.
  • Fattore, M. (2015). Partially ordered sets and the measurement of multidimensional ordinal deprivation. Social Indicators Research. https://doi.org/10.1007/s11205-015-1059-6.
  • Fattore, M., Bruggemann, R., & Owsinski, J. (2011). Using POSET theory to compare fuzzy multidimensional material deprivation across regions. In F. Maggino & M. Fattore (Eds.), New tools for the construction of ranking and evaluation indicators in multidimensional systems of ordinal variables. Presented at the conference on “new techniques and technologies for statistics” – EUROSTAT. Session “construction of indicators”.
  • Fattore, M., Maggino, F., & Colombo, E. (2012). From composite indicators to partial orders evaluating socio-economic phenomena through ordinal data. In F. Maggino & G. Nuvolati (Eds.), Quality of life in Italy: Research and reflections (pp. 41–68). New York: Springer.
  • Fattore, M., Maggino, F., & Arcagni, A. (2015). Well-being evaluation. Statistics in Transition New Series, 16(3), 409–428.
  • Ferrara, A. R., & Nisticò, R. (2015). Regional well-being indicators and dispersion from a multidimensional perspective: Evidence from Italy. The Annals of Regional Science, 55(2), 373–420.
  • González, E., Cárcaba, A., & Ventura, J. (2011). Quality of life ranking of Spanish municipalities. Revista de Economía Aplicada Número, 56, 123–148.
  • González, E., Cárcaba, A., & Ventura, J. (2018). Weight constrained DEA measurement of the quality of life in spanish municipalities in 2011. Social Indicators Research, 136(3), 1157–1182. https://doi.org/10.1007/s11205-016-1426-y.
  • Hashimoto, A., & Ishikawa, H. (1993). Using DEA to evaluate the state of society as measured by multiple social indicators. Socio-Economic Planning Sciences, 27, 257–268.
  • Hashimoto, A., & Kodama, M. (1997). Has livability of Japan gotten better for 1956-1990?: A DEA approach. Social Indicators Research, 40, 359–373.
  • Holgado Molina, M., Salinas Fernández, A., & Rodriguez, A. (2015). A Synthetic indicator to measure the economic and social cohesionon of the regions of Spain and Portugal. Revista de Economía Mundial, 39, 223–240.
  • Iglesias, K., Suter, C., Beycan, T., & Vani, B. P. (2017). Exploring multidimensional well-being in Switzerland: Comparing three synthesizing approaches. Social Indicators Research, 134(3), 847–875. https://doi.org/10.1007/s11205-016-1452-9.
  • Ivaldi, E., Bonatti, G., & Soliani, R. (2016). Is there a two-speed Europe also in the well-being? – Esiste un’Europa a due velocità anche nel benessere ? Economia Internazionale/International Economics, 69(1), 45–68.
  • Mahlberg, B., & Obersteiner, M. (2001). Reameasuring the HDI by data envelopment analysis (Working paper). International Institute for Applied Systems Analysis.
  • Martín, J. C., & Mendoza, C. (2013). A DEA approach to measure the quality-of-Life in the municipalities of the Canary Islands. Social Indicators Research, 113(1), 335–353. https://doi.org/10.1007/s11205-012-0096-7.
  • Mazziotta, M., & Pareto, A. (2012). A Non-compensatory approach for the measurement of the quality of life. In F. Maggino & G. Nuvolati (Eds.), Quality of life in Italy (Social indicator research series 48) (pp. 27–40). Netherlands: Springer.
  • Mazziotta, M., & Pareto, A. (2019). Use and misuse of PCA for measuring well-being. Social Indicators Research, 142(2), 451–476. https://doi.org/10.1007/s11205-018-1933-0.
  • Mishra, S. K. (2012). Construction of Pena’s DP2-based ordinal synthetic indicator when partial indicators are rank scores. SSRN Electronic Journal, (August). https://doi.org/10.2139/ssrn.2069500.
  • Montero, J. M., Chasco, C., & Larrraz, B. (2010). Building an environmental quality index for a big city: A special interpolation approach combined with a distance indicator. Journal of Geographical Systems, 12(4), 435–459.
  • Murias, P., Martínez, F., & De Miguel, C. (2006). An economic wellbeing index for the spanish provinces: A data envelopment analysis approach. Social Indicators Research, 77, 395–417.
  • Nissi, E., & Sarra, A. (2018). A measure of well-being across the Italian Urban Areas: An integrated DEA-entropy approach. Social Indicators Research, 136(3), 1183–1209. https://doi.org/10.1007/s11205-016-1535-7.
  • Pena, J. B. (1977). Problemas de la medición del bienestar y conceptos afines. Una aplicación al Caso Español. Madrid: I.N.E.
  • Ram, R. (1982). Composite indices de physical quality of life, basic needs fulfilment as income. Journal of Development Economics, 11, 227–247.
  • Rodriguez, J. A. (2010). An index of child health in the Least Developed Countries (LDCs) of Africa. Social Indicators Research, 105(3), 309–322. https://doi.org/10.1007/s11205-010-9778-1.
  • Slottje, D., Scully, G., Hirschberg, J. G., & Hayes, K. J. (1991). Measuring the quality of life across countries. Boulder, Editorial: Westview.
  • Somarriba, N. (2008). Approach to the social and individual quality of life in the European Union. Doctoral thesis, Valladolid University.
  • Somarriba Arechavala, N., & Zarzosa Espina, P. (2019). Quality of life in the european union: An econometric analysis from a gender perspective. Social Indicators Research, 142(1), 179–200. https://doi.org/10.1007/s11205-018-1913-4.
  • Somarriba, N., & Pena, B. (2009a). Synthetic indicators of quality of life in Europe. Social Indicators Research, 94(1), 115–133. https://doi.org/10.1007/s11205-008-9356-y.
  • Somarriba, N., & Pena, B. (2009b). La medición de la calidad de vida en Europa, el papel de la información subjetiva. Estudios de Economía Aplicada, 27(2), 373–396.
  • Somarriba, N., Zarzosa, P., & Pena, B. (2015). The Economic Crisis and its Effects on the Quality of Life in the European Union. Social Indicators Research, 120(2), 323–343. https://doi.org/10.1007/s11205-014-0595-9.
  • Sulis, I., Tedesco, N., Cagliari, U., & Ignazio, V. S. (s. f.). Quality of life among university students in Cagliari. A synthetic indicator. Sciences-New York, 1–36.
  • Szeles, M. R., & Fusco, A. (2013). Item response theory and the measurement of deprivation: Evidence from Luxembourg data. Quality & Quantity, 47(3), 1545–1560. https://doi.org/10.1007/s11135-011-9607-x.
  • Zadeh, L. A. (1965). Fuzzy sets. Information and Control, 8, 338–353.
  • Zarzosa, P., & Somarriba, N. (2013). An assessment of social welfare in Spain: Territorial analysis using a synthetic welfare indicator. Social Indicators Research, 111(1), 1–23. https://doi.org/10.1007/s11205-012-0005-0.