Province dataset example
provinceThis data set allows to estimate the relationships among Health (HEALTH),
Education and training (EDU) and Economic well-being (ECOW)
in the Italian provinces using a subset of the indicators collected by the Italian Statistical
Institute (ISTAT) to measure equitable and sustainable well-being (BES, from the Italian Benessere
Equo e Sostenibile) in territories. Data refers to the 2019 edition of the BES report (ISTAT, 2018,
2019a, 2019b). A subset of 16 indicators (manifest variables) are observed on the 110 Italian provinces
and metropolitan cities (i.e. at NUTS3 level) to measure the latent variables HEALTH, EDU
and ECOW. The interest in such an application concerns both advances in knowledge
about the dynamics producing the well-being outcomes at local level (multiplier effects or trade-offs)
and a more complete evaluation of regional inequalities of well-being.
Data Strucuture
A data frame with 110 Italian provinces and metropolitan cities and 16 variables (i.e., indicators) related to three latent variables: Health (3 indicators), Education and training (7 indicators), and Economic well-being (6 indicators).
Manifest variables description for each latent variable:
Education and training (EDU)
Economic wellbeing (ECOW)
#'
Health (HEALTH)
For a full description of the variables, see table 3 of Davino et al. (2020).
Davino, C., Dolce, P., Taralli, S. and Vistocco, D. (2020). Composite-based path modeling for conditional quantiles prediction. An application to assess health differences at local level in a well-being perspective. Social Indicators Research, doi:10.1007/s11205-020-02425-5.
Davino, C., Dolce, P., Taralli, S., Esposito Vinzi, V. (2018). A quantile composite-indicator approach for the measurement of equitable and sustainable well-being: A case study of the italian provinces. Social Indicators Research, 136, pp. 999--1029, doi: 10.1007/s11205-016-1453-8
Davino, C., Dolce, P., Taralli, S. (2017). Quantile composite-based model: A recent advance in pls-pm. A preliminary approach to handle heterogeneity in the measurement of equitable and sustainable well-being. In Latan, H. and Noonan, R. (eds.), Partial Least Squares Path Modeling: Basic Concepts, Methodological Issues and Applications (pp. 81--108). Cham: Springer.
ISTAT. (2019a). Misure del Benessere dei territori. Tavole di dati. Rome, Istat.
ISTAT. (2019b). Le differenze territoriali di benessere - Una lettura a livello provinciale. Rome, Istat.
ISTAT. (2018). Bes report 2018: Equitable and sustainable well-being in Italy. Rome, Istat.