Objectives:
Measuring complex multidimensional phenomena such as the community well-being over time provides several challenges. The main difficulties are due to changes of well-being – at both group/community level and at the individual/household level. To deal with it a ’diachronic’ approach is employed through transforming time-related data into Functional Data.

Material and methods:
The complexity of the intertwining methodological and substantive issues involved in analyzing the relationship between individual and community well-being, is addressed in two steps: (i) at the measurement level, the Functional Data measurement approach is employed; (ii) having constructed a classification of both local communities and their inhabitants the spatial effects of community development on the cross-categorizized units are assessed in terms of spatial patterns (autocorrelation and clustering tendency).

Results:
Following the conceptualization of the interdependence of data, measurement, and model, it seems worthwhile to note that in light of the above presented empirical results, Functional Data approach to multidimensional measurement of community well-being, as well as to selected measures of subjective well-being, allows clarifying the between individual (micro) and commune (macro) level relationships.

Conclusions:
In conclusion, by taking into account the dynamic aspect of the local development process (by applying the Functional Data approach) in the analysis of its impact on the personal well-being of residents, both planning and resource allocation policies become better informed and, one might expect, more effective (for example, a given level of individual well-being can be achieved by using a more accurate policy-relevant information than otherwise, even at a higher cost, while neglecting it)