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Well-Being and Relational Goods: A Model-Based Approach to Detect Significant Relationships

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  • Stefania Capecchi

    () (University of Naples Federico II)

  • Maria Iannario

    () (University of Naples Federico II)

  • Rosaria Simone

    () (University of Naples Federico II)

Abstract

Abstract A statistical framework for modelling subjective perceptions expressed through ratings is presented. The paper deals with the relationships between personal covariates and self-declared happiness, taking into account several social activities, such as spending time with family and friends, participating in groups and associations, and so on. Our setting concerns a class of statistical models able to measure the effects on life satisfaction of the relational goods which have been proved significant in a large sample of respondents. By means of these models, the proposal enhances the different contributions of subjects’ covariates on their response patterns. The selected approach is based on a mixture model to interpret the assessed perception of two unobserved components, denoted as feeling and uncertainty, respectively, as a blend of real beliefs and indecision. Empirical evidence to support the usefulness of this methodological perspective is provided by a recent observational survey concerning happiness and relational goods.

Suggested Citation

  • Stefania Capecchi & Maria Iannario & Rosaria Simone, 2018. "Well-Being and Relational Goods: A Model-Based Approach to Detect Significant Relationships," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 135(2), pages 729-750, January.
  • Handle: RePEc:spr:soinre:v:135:y:2018:i:2:d:10.1007_s11205-016-1519-7
    DOI: 10.1007/s11205-016-1519-7
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    1. repec:spr:soinre:v:141:y:2019:i:1:d:10.1007_s11205-018-1848-9 is not listed on IDEAS
    2. M. Meleddu & M. Pulina & G. Solinas & S. Capecchi, 2019. "Mixture models for consumers' preferences in healthcare," Working Paper CRENoS 201901, Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia.

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