Conferences

The quality of life is a multidimensional concept composed of different component, traditionally classified in term of objective and subjective components. Many research measure the reality considering only objective information or subjective. A more realistic picture of the quality of life concept should be obtained if subjective and objective components are suitably combined. Some assumptions have to be made concerning the relationship between the two components. In broad outline, two perspectives can be alternatively defined: (a) objective quality of life at macro level can be considered an antecedent with respect to subjective quality of life (subjective well-being). In this case, objective indicators (input) can be interpreted in terms of contextual conditions that can explain the subjective indicators (output); (b) objective quality of life conditions at macro-level and subjective quality of life (perceptions) are independent; perceptions are influenced by individual characteristics and not by the objective living conditions. In this case, subjective indicators (input) can be considered as an important component driving the improvement of objective conditions.

The paper describes a procedure aimed at integrating objective and subjective data by showing an applicative study.

The possibility to develop integration between objective and subjective indicators is based upon the chance to rely on organized data, observed in long-term longitudinal perspective. This is particularly true with reference to subjective indicator, which are strongly dependent and linked to a great use of resources. In this perspective, a composite analytic approach should be defined. The study has been carried out on both subjective (from the European Social Survey project) and objective (provided by the Joint Research Centre – JRC – European Commission) data. The application shows how a simple integrative approach is able to reveal its efficacy in the perspective objective and subjective information.

The Econometrics and Applied Statistics Unit (EAS) of the JRC has actually and fruitfully contributed to the preparation of this study.

The approach is defined “composite” as carried out through subsequent steps (multi-stages) and by different analytical approaches (multi-techniques). In particular, four stages can be identified in order to complete the procedure.