Beds in Health Facilities in the Italian Regions: A Socio-Economic Approach

In this article, we consider the determinants of the beds in healthcare facilities-BEDS in the Italian regions between 2004 and 2022. We use the ISTAT-BES database. We use different econometric techniques i.e.: Panel Data with Fixed Effects, Panel Data with Random Effects, Pooled Ordinary Least Squares-OLS, Weighted Least Squares-WLS, and Dynamic Panel at 1 Stage. The results show that the level of BEDS is positively associated, among others, to " General Doctors with a Number of Clients over the Threshold" and "Life Satisfaction ", and negatively associated among others, to " Trust in Parties " and " Positive Judgment on Future Prospects ". Furthermore, we apply a clusterization with the k-Means algorithm optimized with the Silhouette Coefficient and we find the presence of two clusters in terms of BEDS. Finally, we make a confrontation among eight machine-learning algorithms and we find that the best predictor is the ANN-Artificial Neural Network. JEL CODE: I11, I12, I13, I14, I15, I18